1
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Kawaji T, Fujibayashi M, Abe K. Goal-directed and flexible modulation of syllable sequence within birdsong. Nat Commun 2024; 15:3419. [PMID: 38658545 PMCID: PMC11043396 DOI: 10.1038/s41467-024-47824-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 04/09/2024] [Indexed: 04/26/2024] Open
Abstract
Songs constitute a complex system of vocal signals for inter-individual communication in songbirds. Here, we elucidate the flexibility which songbirds exhibit in the organizing and sequencing of syllables within their songs. Utilizing a newly devised song decoder for quasi-real-time annotation, we execute an operant conditioning paradigm, with rewards contingent upon specific syllable syntax. Our analysis reveals that birds possess the capacity to modify the contents of their songs, adjust the repetition length of particular syllables and employing specific motifs. Notably, birds altered their syllable sequence in a goal-directed manner to obtain rewards. We demonstrate that such modulation occurs within a distinct song segment, with adjustments made within 10 minutes after cue presentation. Additionally, we identify the involvement of the parietal-basal ganglia pathway in orchestrating these flexible modulations of syllable sequences. Our findings unveil an unappreciated aspect of songbird communication, drawing parallels with human speech.
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Affiliation(s)
- Takuto Kawaji
- Lab of Brain Development, Graduate School of Life Sciences, Tohoku University, Katahira 2-1-1, Sendai, Miyagi, 980-8577, Japan
| | - Mizuki Fujibayashi
- Lab of Brain Development, Graduate School of Life Sciences, Tohoku University, Katahira 2-1-1, Sendai, Miyagi, 980-8577, Japan
| | - Kentaro Abe
- Lab of Brain Development, Graduate School of Life Sciences, Tohoku University, Katahira 2-1-1, Sendai, Miyagi, 980-8577, Japan.
- Division for the Establishment of Frontier Sciences of the Organization for Advanced Studies, Tohoku University, Sendai, Miyagi, 980-8577, Japan.
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2
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Steiner LA, Crompton D, Sumarac S, Vetkas A, Germann J, Scherer M, Justich M, Boutet A, Popovic MR, Hodaie M, Kalia SK, Fasano A, Hutchison Wd WD, Lozano AM, Lankarany M, Kühn AA, Milosevic L. Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson's disease. Nat Commun 2024; 15:3130. [PMID: 38605039 PMCID: PMC11009243 DOI: 10.1038/s41467-024-47552-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 04/02/2024] [Indexed: 04/13/2024] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson's disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.
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Affiliation(s)
- Leon A Steiner
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, 10117, Germany
- Berlin Institute of Health (BIH), Berlin, 10178, Germany
| | - David Crompton
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada
| | - Srdjan Sumarac
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada
| | - Artur Vetkas
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
| | - Jürgen Germann
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
- Department of Surgery, University of Toronto, Toronto, ON, M5G 2C4, Canada
| | - Maximilian Scherer
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada
| | - Maria Justich
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Department of Neurology, University of Toronto, Toronto, ON, M5S 3H2, Canada
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
| | - Alexandre Boutet
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, M5G 1×6, Canada
| | - Milos R Popovic
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada
- KITE Research Institute, University Health Network, Toronto, ON, M5G 2A2, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
| | - Mojgan Hodaie
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
- Department of Surgery, University of Toronto, Toronto, ON, M5G 2C4, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Suneil K Kalia
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
- Department of Surgery, University of Toronto, Toronto, ON, M5G 2C4, Canada
- KITE Research Institute, University Health Network, Toronto, ON, M5G 2A2, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Alfonso Fasano
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Department of Neurology, University of Toronto, Toronto, ON, M5S 3H2, Canada
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - William D Hutchison Wd
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Department of Surgery, University of Toronto, Toronto, ON, M5G 2C4, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
- Department of Physiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Andres M Lozano
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, M5T 2S8, Canada
- Department of Surgery, University of Toronto, Toronto, ON, M5G 2C4, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Milad Lankarany
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada
| | - Andrea A Kühn
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Luka Milosevic
- Krembil Brain Institute, University Health Network, Toronto, ON, M5T 1M8, Canada.
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada.
- KITE Research Institute, University Health Network, Toronto, ON, M5G 2A2, Canada.
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, M5T 2S8, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, M5S 1A8, Canada.
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3
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Wang Y, Lak A, Manohar SG, Bogacz R. Dopamine encoding of novelty facilitates efficient uncertainty-driven exploration. PLoS Comput Biol 2024; 20:e1011516. [PMID: 38626219 PMCID: PMC11051659 DOI: 10.1371/journal.pcbi.1011516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 04/26/2024] [Accepted: 03/23/2024] [Indexed: 04/18/2024] Open
Abstract
When facing an unfamiliar environment, animals need to explore to gain new knowledge about which actions provide reward, but also put the newly acquired knowledge to use as quickly as possible. Optimal reinforcement learning strategies should therefore assess the uncertainties of these action-reward associations and utilise them to inform decision making. We propose a novel model whereby direct and indirect striatal pathways act together to estimate both the mean and variance of reward distributions, and mesolimbic dopaminergic neurons provide transient novelty signals, facilitating effective uncertainty-driven exploration. We utilised electrophysiological recording data to verify our model of the basal ganglia, and we fitted exploration strategies derived from the neural model to data from behavioural experiments. We also compared the performance of directed exploration strategies inspired by our basal ganglia model with other exploration algorithms including classic variants of upper confidence bound (UCB) strategy in simulation. The exploration strategies inspired by the basal ganglia model can achieve overall superior performance in simulation, and we found qualitatively similar results in fitting model to behavioural data compared with the fitting of more idealised normative models with less implementation level detail. Overall, our results suggest that transient dopamine levels in the basal ganglia that encode novelty could contribute to an uncertainty representation which efficiently drives exploration in reinforcement learning.
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Affiliation(s)
- Yuhao Wang
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Armin Lak
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Sanjay G. Manohar
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
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4
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Liénard JF, Aubin L, Cos I, Girard B. Estimation of the transmission delays in the basal ganglia of the macaque monkey and subsequent predictions about oscillatory activity under dopamine depletion. Eur J Neurosci 2024; 59:1657-1680. [PMID: 38414108 DOI: 10.1111/ejn.16271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 12/31/2023] [Accepted: 01/21/2024] [Indexed: 02/29/2024]
Abstract
The timescales of the dynamics of a system depend on the combination of the timescales of its components and of its transmission delays between components. Here, we combine experimental stimulation data from 10 studies in macaque monkeys that reveal the timing of excitatory and inhibitory events in the basal ganglia circuit, to estimate its set of transmission delays. In doing so, we reveal possible inconsistencies in the existing data, calling for replications, and we propose two possible sets of transmission delays. We then integrate these delays in a model of the primate basal ganglia that does not rely on direct and indirect pathways' segregation and show that extrastriatal dopaminergic depletion in the external part of the globus pallidus and in the subthalamic nucleus is sufficient to generate β-band oscillations (in the high part, 20-35 Hz, of the band). More specifically, we show that D2 and D5 dopamine receptors in these nuclei play opposing roles in the emergence of these oscillations, thereby explaining how completely deactivating D5 receptors in the subthalamic nucleus can, paradoxically, cancel oscillations.
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Affiliation(s)
- Jean F Liénard
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
| | - Lise Aubin
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
| | - Ignasi Cos
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
- Facultat de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
- Serra-Hunter Fellow Program, Barcelona, Spain
| | - Benoît Girard
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
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5
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Tian Y, Murphy MJH, Steiner LA, Kalia SK, Hodaie M, Lozano AM, Hutchison WD, Popovic MR, Milosevic L, Lankarany M. Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus. Neuromodulation 2024; 27:464-475. [PMID: 37140523 DOI: 10.1016/j.neurom.2023.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 01/27/2023] [Accepted: 03/02/2023] [Indexed: 05/05/2023]
Abstract
OBJECTIVE Deep brain stimulation (DBS) is an effective treatment for movement disorders, including Parkinson disease and essential tremor. However, the underlying mechanisms of DBS remain elusive. Despite the capability of existing models in interpreting experimental data qualitatively, there are very few unified computational models that quantitatively capture the dynamics of the neuronal activity of varying stimulated nuclei-including subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate nucleus (Vim)-across different DBS frequencies. MATERIALS AND METHODS Both synthetic and experimental data were used in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work, and the experimental data were provided using single-unit microelectrode recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we developed a novel mathematical model to represent the firing rate of neurons receiving DBS, including neurons in STN, SNr, and Vim-across different DBS frequencies. In our model, the DBS pulses were filtered through a synapse model and a nonlinear transfer function to formulate the firing rate variability. For each DBS-targeted nucleus, we fitted a single set of optimal model parameters consistent across varying DBS frequencies. RESULTS Our model accurately reproduced the firing rates observed and calculated from both synthetic and experimental data. The optimal model parameters were consistent across different DBS frequencies. CONCLUSIONS The result of our model fitting was in agreement with experimental single-unit MER data during DBS. Reproducing neuronal firing rates of different nuclei of the basal ganglia and thalamus during DBS can be helpful to further understand the mechanisms of DBS and to potentially optimize stimulation parameters based on their actual effects on neuronal activity.
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Affiliation(s)
- Yupeng Tian
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada
| | | | - Leon A Steiner
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; Berlin Institute of Health, Berlin, Germany; Department of Surgery, University of Toronto, Toronto, ON, Canada; Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Suneil K Kalia
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Mojgan Hodaie
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Andres M Lozano
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - William D Hutchison
- CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Surgery, University of Toronto, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Milos R Popovic
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada
| | - Luka Milosevic
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada
| | - Milad Lankarany
- Krembil Research Institute - University Health Network, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada; CRANIA, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada.
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6
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Tanimoto Y, Kakinuma H, Aoki R, Shiraki T, Higashijima SI, Okamoto H. Transgenic tools targeting the basal ganglia reveal both evolutionary conservation and specialization of neural circuits in zebrafish. Cell Rep 2024; 43:113916. [PMID: 38484735 DOI: 10.1016/j.celrep.2024.113916] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/18/2024] [Accepted: 02/17/2024] [Indexed: 04/02/2024] Open
Abstract
The cortico-basal ganglia circuit mediates decision making. Here, we generated transgenic tools for adult zebrafish targeting specific subpopulations of the components of this circuit and utilized them to identify evolutionary homologs of the mammalian direct- and indirect-pathway striatal neurons, which respectively project to the homologs of the internal and external segment of the globus pallidus (dorsal entopeduncular nucleus [dEN] and lateral nucleus of the ventral telencephalic area [Vl]) as in mammals. Unlike in mammals, the Vl mainly projects to the dEN directly, not by way of the subthalamic nucleus. Further single-cell RNA sequencing analysis reveals two pallidal output pathways: a major shortcut pathway directly connecting the dEN with the pallium and the evolutionarily conserved closed loop by way of the thalamus. Our resources and circuit map provide the common basis for the functional study of the basal ganglia in a small and optically tractable zebrafish brain for the comprehensive mechanistic understanding of the cortico-basal ganglia circuit.
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Affiliation(s)
- Yuki Tanimoto
- Laboratory for Neural Circuit Dynamics of Decision-making, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Hisaya Kakinuma
- Laboratory for Neural Circuit Dynamics of Decision-making, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Ryo Aoki
- Laboratory for Neural Circuit Dynamics of Decision-making, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Toshiyuki Shiraki
- Research Resources Division, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Shin-Ichi Higashijima
- Exploratory Research Center on Life and Living Systems, Okazaki, Aichi 444-8787, Japan; National Institute for Basic Biology, Okazaki, Aichi 444-8787, Japan
| | - Hitoshi Okamoto
- Laboratory for Neural Circuit Dynamics of Decision-making, RIKEN Center for Brain Science, Saitama 351-0198, Japan; RIKEN CBS-Kao Collaboration Center, Saitama 351-0198, Japan.
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7
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Wullimann MF. Good heavens! Finally a landslide analysis of basal ganglia circuitry in teleosts. Cell Rep 2024; 43:113915. [PMID: 38484736 DOI: 10.1016/j.celrep.2024.113915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 02/15/2024] [Accepted: 02/16/2024] [Indexed: 04/02/2024] Open
Abstract
Tanimoto et al.1 report essential information on teleostean basal ganglia circuitry. This analysis opens gateways into studying neurophysiology, neuropharmacology, and behavior in zebrafish, guided by this complex functional neural system common to all vertebrates.
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Affiliation(s)
- Mario F Wullimann
- Genes - Circuits - Behavior, Max-Planck-Institute for Biological Intelligence, Am Klopferspitz 18, 82152 Martinsried, Germany; Department Biology II, Division of Neurobiology, Ludwig-Maximilians-University (LMU Munich), 82152 Martinsried, Germany.
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8
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Quan Z, Li Y, Cheng X, Nie Y, Wang S. Amplitude Adaptive Modulation of Neural Oscillations Over Long-Term Dynamic Conditions: A Computational Study. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1154-1163. [PMID: 38446651 DOI: 10.1109/tnsre.2024.3370948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Closed-loop deep brain stimulation (DBS) shows great potential for precise neuromodulation of various neurological disorders, particularly Parkinson's disease (PD). However, substantial challenges remain in clinical translation due to the complex programming procedure of closed-loop DBS parameters. In this study, we proposed an online optimized amplitude adaptive strategy based on the particle swarm optimization (PSO) and proportional-integral-differential (PID) controller for modulation of the beta oscillation in a PD mean field model over long-term dynamic conditions. The strategy aimed to calculate the stimulation amplitude adapting to the fluctuations caused by circadian rhythm, medication rhythm, and stochasticity in the basal ganglia-thalamus-cortical circuit. The PID gains were optimized online using PSO, based on modulation accuracy, mean stimulation amplitude, and stimulation variation. The results showed that the proposed strategy optimized the stimulation amplitude and achieved beta power modulation under the influence of circadian rhythm, medication rhythm, and stochasticity of beta oscillations. This work offers a novel approach for precise neuromodulation with the potential for clinical translation.
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9
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Qi ZX, Yan Q, Fan XJ, Peng JY, Zhu HX, Jiang YM, Chen L, Zhuang QX. Role of HCN channels in the functions of basal ganglia and Parkinson's disease. Cell Mol Life Sci 2024; 81:135. [PMID: 38478096 PMCID: PMC10937777 DOI: 10.1007/s00018-024-05163-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/19/2024] [Accepted: 02/06/2024] [Indexed: 03/17/2024]
Abstract
Parkinson's disease (PD) is a motor disorder resulting from dopaminergic neuron degeneration in the substantia nigra caused by age, genetics, and environment. The disease severely impacts a patient's quality of life and can even be life-threatening. The hyperpolarization-activated cyclic nucleotide-gated (HCN) channel is a member of the HCN1-4 gene family and is widely expressed in basal ganglia nuclei. The hyperpolarization-activated current mediated by the HCN channel has a distinct impact on neuronal excitability and rhythmic activity associated with PD pathogenesis, as it affects the firing activity, including both firing rate and firing pattern, of neurons in the basal ganglia nuclei. This review aims to comprehensively understand the characteristics of HCN channels by summarizing their regulatory role in neuronal firing activity of the basal ganglia nuclei. Furthermore, the distribution and characteristics of HCN channels in each nucleus of the basal ganglia group and their effect on PD symptoms through modulating neuronal electrical activity are discussed. Since the roles of the substantia nigra pars compacta and reticulata, as well as globus pallidus externus and internus, are distinct in the basal ganglia circuit, they are individually described. Lastly, this investigation briefly highlights that the HCN channel expressed on microglia plays a role in the pathological process of PD by affecting the neuroinflammatory response.
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Affiliation(s)
- Zeng-Xin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China
- National Center for Neurological Disorders, Shanghai, 200030, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, 200030, China
| | - Qi Yan
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Xiu-Juan Fan
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Jian-Ya Peng
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Hui-Xian Zhu
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Yi-Miao Jiang
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Liang Chen
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200030, China.
- National Center for Neurological Disorders, Shanghai, 200030, China.
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200030, China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, 200030, China.
| | - Qian-Xing Zhuang
- Department of Physiology, School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China.
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10
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Larry N, Zur G, Joshua M. Organization of reward and movement signals in the basal ganglia and cerebellum. Nat Commun 2024; 15:2119. [PMID: 38459003 PMCID: PMC10923830 DOI: 10.1038/s41467-024-45921-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 02/06/2024] [Indexed: 03/10/2024] Open
Abstract
The basal ganglia and the cerebellum are major subcortical structures in the motor system. The basal ganglia have been cast as the reward center of the motor system, whereas the cerebellum is thought to be involved in adjusting sensorimotor parameters. Recent findings of reward signals in the cerebellum have challenged this dichotomous view. To compare the basal ganglia and the cerebellum directly, we recorded from oculomotor regions in both structures from the same monkeys. We partitioned the trial-by-trial variability of the neurons into reward and eye-movement signals to compare the coding across structures. Reward expectation and movement signals were the most pronounced in the output structure of the basal ganglia, intermediate in the cerebellum, and the smallest in the input structure of the basal ganglia. These findings suggest that reward and movement information is sharpened through the basal ganglia, resulting in a higher signal-to-noise ratio than in the cerebellum.
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Affiliation(s)
- Noga Larry
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel.
| | - Gil Zur
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel
| | - Mati Joshua
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel.
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11
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Azizpour Lindi S, Mallet NP, Leblois A. Synaptic Changes in Pallidostriatal Circuits Observed in the Parkinsonian Model Triggers Abnormal Beta Synchrony with Accurate Spatio-temporal Properties across the Basal Ganglia. J Neurosci 2024; 44:e0419232023. [PMID: 38123981 PMCID: PMC10903930 DOI: 10.1523/jneurosci.0419-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/27/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
Excessive oscillatory activity across basal ganglia (BG) nuclei in the β frequencies (12-30 Hz) is a hallmark of Parkinson's disease (PD). While the link between oscillations and symptoms remains debated, exaggerated β oscillations constitute an important biomarker for therapeutic effectiveness in PD. The neuronal mechanisms of β-oscillation generation however remain unknown. Many existing models rely on a central role of the subthalamic nucleus (STN) or cortical inputs to BG. Contrarily, neural recordings and optogenetic manipulations in normal and parkinsonian rats recently highlighted the central role of the external pallidum (GPe) in abnormal β oscillations, while showing that the integrity of STN or motor cortex is not required. Here, we evaluate the mechanisms for the generation of abnormal β oscillations in a BG network model where neuronal and synaptic time constants, connectivity, and firing rate distributions are strongly constrained by experimental data. Guided by a mean-field approach, we show in a spiking neural network that several BG sub-circuits can drive oscillations. Strong recurrent STN-GPe connections or collateral intra-GPe connections drive γ oscillations (>40 Hz), whereas strong pallidostriatal loops drive low-β (10-15 Hz) oscillations. We show that pathophysiological strengthening of striatal and pallidal synapses following dopamine depletion leads to the emergence of synchronized oscillatory activity in the mid-β range with spike-phase relationships between BG neuronal populations in-line with experiments. Furthermore, inhibition of GPe, contrary to STN, abolishes oscillations. Our modeling study uncovers the neural mechanisms underlying PD β oscillations and may thereby guide the future development of therapeutic strategies.
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Affiliation(s)
- Shiva Azizpour Lindi
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
| | - Nicolas P Mallet
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
| | - Arthur Leblois
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
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12
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Sousani M, Seydnejad SR, Ghahramani M. Insights from a model based study on optimizing non invasive brain electrical stimulation for Parkinson's disease. Sci Rep 2024; 14:2447. [PMID: 38291112 PMCID: PMC10828384 DOI: 10.1038/s41598-024-52355-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/17/2024] [Indexed: 02/01/2024] Open
Abstract
Parkinson's Disease (PD) is a disorder in the central nervous system which includes symptoms such as tremor, rigidity, and Bradykinesia. Deep brain stimulation (DBS) is the most effective method to treat PD motor symptoms especially when the patient is not responsive to other treatments. However, its invasiveness and high risk, involving electrode implantation in the Basal Ganglia (BG), prompt recent research to emphasize non-invasive Transcranial Electrical Stimulation (TES). TES proves to be effective in treating some PD symptoms with inherent safety and no associated risks. This study explores the potential of using TES, to modify the firing pattern of cells in BG that are responsible for motor symptoms in PD. The research employs a mathematical model of the BG to examine the impact of applying TES to the brain. This is conducted using a realistic head model incorporating the Finite Element Method (FEM). According to our findings, the firing pattern associated with Parkinson's disease shifted towards a healthier firing pattern through the use of tACS. Employing an adaptive algorithm that continually monitored the behavior of BG cells (specifically, Globus Pallidus Pars externa (GPe)), we determined the optimal electrode number and placement to concentrate the current within the intended region. This resulted in a peak induced electric field of 1.9 v/m at the BG area. Our mathematical modeling together with precise finite element simulation of the brain and BG suggests that proposed method effectively mitigates Parkinsonian behavior in the BG cells. Furthermore, this approach ensures an improvement in the condition while adhering to all safety constraints associated with the current injection into the brain.
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Affiliation(s)
- Maryam Sousani
- Faculty of Science and Technology, University of Canberra, Bruce, Canberra, 2617, ACT, Australia.
| | - Saeid R Seydnejad
- Department of Electrical Engineering, Shahid Bahonar University of Kerman, Pajoohesh Sq., Kerman, Kerman, Iran
| | - Maryam Ghahramani
- Faculty of Science and Technology, University of Canberra, Bruce, Canberra, 2617, ACT, Australia
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13
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Luu P, Tucker DM, Friston K. From active affordance to active inference: vertical integration of cognition in the cerebral cortex through dual subcortical control systems. Cereb Cortex 2024; 34:bhad458. [PMID: 38044461 DOI: 10.1093/cercor/bhad458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 12/05/2023] Open
Abstract
In previous papers, we proposed that the dorsal attention system's top-down control is regulated by the dorsal division of the limbic system, providing a feedforward or impulsive form of control generating expectancies during active inference. In contrast, we proposed that the ventral attention system is regulated by the ventral limbic division, regulating feedback constraints and error-correction for active inference within the neocortical hierarchy. Here, we propose that these forms of cognitive control reflect vertical integration of subcortical arousal control systems that evolved for specific forms of behavior control. The feedforward impetus to action is regulated by phasic arousal, mediated by lemnothalamic projections from the reticular activating system of the lower brainstem, and then elaborated by the hippocampus and dorsal limbic division. In contrast, feedback constraint-based on environmental requirements-is regulated by the tonic activation furnished by collothalamic projections from the midbrain arousal control centers, and then sustained and elaborated by the amygdala, basal ganglia, and ventral limbic division. In an evolutionary-developmental analysis, understanding these differing forms of active affordance-for arousal and motor control within the subcortical vertebrate neuraxis-may help explain the evolution of active inference regulating the cognition of expectancy and error-correction within the mammalian 6-layered neocortex.
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Affiliation(s)
- Phan Luu
- Brain Electrophysiology Laboratory Company, Riverfront Research Park, 1776 Millrace Dr., Eugene, OR 97403, United States
- Department of Psychology, University of Oregon, Eugene, OR 97403, United States
| | - Don M Tucker
- Brain Electrophysiology Laboratory Company, Riverfront Research Park, 1776 Millrace Dr., Eugene, OR 97403, United States
- Department of Psychology, University of Oregon, Eugene, OR 97403, United States
| | - Karl Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3AR, United Kingdom
- VERSES AI Research Lab, Los Angeles, CA 90016, USA
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14
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Spiliotis K, Butenko K, Starke J, van Rienen U, Köhling R. Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model. J Neural Eng 2024; 20:066045. [PMID: 37988747 DOI: 10.1088/1741-2552/ad0e7c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 11/21/2023] [Indexed: 11/23/2023]
Abstract
Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.
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Affiliation(s)
| | - Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Starke
- Institute of Mathematics, University of Rostock, Rostock, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | - Rüdiger Köhling
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
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15
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Fang LZ, Creed MC. Updating the striatal-pallidal wiring diagram. Nat Neurosci 2024; 27:15-27. [PMID: 38057614 DOI: 10.1038/s41593-023-01518-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 11/06/2023] [Indexed: 12/08/2023]
Abstract
The striatal and pallidal complexes are basal ganglia structures that orchestrate learning and execution of flexible behavior. Models of how the basal ganglia subserve these functions have evolved considerably, and the advent of optogenetic and molecular tools has shed light on the heterogeneity of subcircuits within these pathways. However, a synthesis of how molecularly diverse neurons integrate into existing models of basal ganglia function is lacking. Here, we provide an overview of the neurochemical and molecular diversity of striatal and pallidal neurons and synthesize recent circuit connectivity studies in rodents that takes this diversity into account. We also highlight anatomical organizational principles that distinguish the dorsal and ventral basal ganglia pathways in rodents. Future work integrating the molecular and anatomical properties of striatal and pallidal subpopulations may resolve controversies regarding basal ganglia network function.
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Affiliation(s)
- Lisa Z Fang
- Washington University Pain Center, Department of Anesthesiology, St. Louis, MO, USA
- Division of Biomedical Sciences, Faculty of Medicine, Memorial University, St. John's, Newfoundland and Labrador, Canada
| | - Meaghan C Creed
- Washington University Pain Center, Department of Anesthesiology, St. Louis, MO, USA.
- Departments of Psychiatry, Neuroscience and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
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16
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Nambu A, Chiken S. External segment of the globus pallidus in health and disease: Its interactions with the striatum and subthalamic nucleus. Neurobiol Dis 2024; 190:106362. [PMID: 37992783 DOI: 10.1016/j.nbd.2023.106362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 11/02/2023] [Accepted: 11/19/2023] [Indexed: 11/24/2023] Open
Abstract
The external segment of the globus pallidus (GPe) has long been considered a homogeneous structure that receives inputs from the striatum and sends processed information to the subthalamic nucleus, composing a relay nucleus of the indirect pathway that contributes to movement suppression. Recent methodological revolution in rodents led to the identification of two distinct cell types in the GPe with different fiber connections. The GPe may be regarded as a dynamic, complex and influential center within the basal ganglia circuitry, rather than a simple relay nucleus. On the other hand, many studies have so far been performed in monkeys to clarify the functions of the basal ganglia in the healthy and diseased states, but have not paid much attention to such classification and functional differences of GPe neurons. In this minireview, we consider the knowledge on the rodent GPe and discuss its impact on the understanding of the basal ganglia circuitry in monkeys.
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Affiliation(s)
- Atsushi Nambu
- Division of System Neurophysiology, National Institute for Physiological Sciences, Okazaki, Aichi 444-8585, Japan; Department of Physiological Sciences, SOKENDAI, Okazaki, Aichi 444-8585, Japan.
| | - Satomi Chiken
- Division of System Neurophysiology, National Institute for Physiological Sciences, Okazaki, Aichi 444-8585, Japan; Department of Physiological Sciences, SOKENDAI, Okazaki, Aichi 444-8585, Japan
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17
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Cavarretta F, Jaeger D. Modeling Synaptic Integration of Bursty and β Oscillatory Inputs in Ventromedial Motor Thalamic Neurons in Normal and Parkinsonian States. eNeuro 2023; 10:ENEURO.0237-23.2023. [PMID: 37989589 PMCID: PMC10726287 DOI: 10.1523/eneuro.0237-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 10/16/2023] [Accepted: 11/05/2023] [Indexed: 11/23/2023] Open
Abstract
The ventromedial motor thalamus (VM) is implicated in multiple motor functions and occupies a central position in the cortico-basal ganglia-thalamocortical loop. It integrates glutamatergic inputs from motor cortex (MC) and motor-related subcortical areas, and it is a major recipient of inhibition from basal ganglia. Previous in vitro experiments performed in mice showed that dopamine depletion enhances the excitability of thalamocortical (TC) neurons in VM due to reduced M-type potassium currents. To understand how these excitability changes impact synaptic integration in vivo, we constructed biophysically detailed mouse VM TC model neurons fit to normal and dopamine-depleted conditions, using the NEURON simulator. These models allowed us to assess the influence of excitability changes with dopamine depletion on the integration of synaptic inputs expected in vivo We found that VM neuron models in the dopamine-depleted state showed increased firing rates with the same synaptic inputs. Synchronous bursting in inhibitory input from the substantia nigra pars reticulata (SNR), as observed in parkinsonian conditions, evoked a postinhibitory firing rate increase with a longer duration in dopamine-depleted than control conditions, due to different M-type potassium channel densities. With β oscillations in the inhibitory inputs from SNR and the excitatory inputs from cortex, we observed spike-phase locking in the activity of the models in normal and dopamine-depleted states, which relayed and amplified the oscillations of the inputs, suggesting that the increased β oscillations observed in VM of parkinsonian animals are predominantly a consequence of changes in the presynaptic activity rather than changes in intrinsic properties.
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Affiliation(s)
| | - Dieter Jaeger
- Department of Biology, Emory University, Atlanta, GA 30322
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18
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Sun Y, Lü J, Zhou Y, Liu Y, Chai Y. Suppression of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model. J Biol Phys 2023; 49:463-482. [PMID: 37572243 PMCID: PMC10651615 DOI: 10.1007/s10867-023-09641-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 07/28/2023] [Indexed: 08/14/2023] Open
Abstract
Excessive neural synchronization of neural populations in the beta (β) frequency range (12-35 Hz) is intimately related to the symptoms of hypokinesia in Parkinson's disease (PD). Studies have shown that delayed feedback stimulation strategies can interrupt excessive neural synchronization and effectively alleviate symptoms associated with PD dyskinesia. Work on optimizing delayed feedback algorithms continues to progress, yet it remains challenging to further improve the inhibitory effect with reduced energy expenditure. Therefore, we first established a neural mass model of the cortex-basal ganglia-thalamus-pedunculopontine nucleus (CBGTh-PPN) closed-loop system, which can reflect the internal properties of cortical and basal ganglia neurons and their intrinsic connections with thalamic and pedunculopontine nucleus neurons. Second, the inhibitory effects of three delayed feedback schemes based on the external globus pallidum (GPe) on β oscillations were investigated separately and compared with those based on the subthalamic nucleus (STN) only. Our results show that all four delayed feedback schemes achieve effective suppression of pathological β oscillations when using the linear delayed feedback algorithm. The comparison revealed that the three GPe-based delayed feedback stimulation strategies were able to have a greater range of oscillation suppression with reduced energy consumption, thus improving control performance effectively, suggesting that they may be more effective for the relief of Parkinson's motor symptoms in practical applications.
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Affiliation(s)
- Yuqin Sun
- School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China
| | - Jiali Lü
- School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China
| | - Ye Zhou
- School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China
| | - Yingpeng Liu
- School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China
| | - Yuan Chai
- School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China.
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19
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Friedman AD, Yin HH. Selective Activation of Subthalamic Nucleus Output Quantitatively Scales Movements. J Neurosci 2023; 43:7967-7981. [PMID: 37816600 PMCID: PMC10669786 DOI: 10.1523/jneurosci.0734-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 09/07/2023] [Accepted: 09/29/2023] [Indexed: 10/12/2023] Open
Abstract
The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) treatments of Parkinsonian motor symptoms. According to the dominant model, the STN output can suppress movement by enhancing inhibitory basal ganglia (BG) output via the indirect pathway, and disrupting STN output using DBS can restore movement in Parkinson's patients. But the mechanisms underlying STN DBS remain poorly understood, as previous studies usually relied on electrical stimulation, which cannot selectively target STN output neurons. Here, we selectively stimulated STN projection neurons using optogenetics and quantified behavior in male and female mice using 3D motion capture. STN stimulation resulted in movements with short latencies (10-15 ms). A single pulse of light was sufficient to generate movement, and there was a highly linear relationship between stimulation frequency and kinematic measures. Unilateral stimulation caused movement in the ipsiversive direction (toward the side of stimulation) and quantitatively determined head yaw and head roll, while stimulation of either STN raises the head (pitch). Bilateral stimulation does not cause turning but raised the head twice as high as unilateral stimulation of either STN. Optogenetic stimulation increased the firing rate of STN neurons in a frequency-dependent manner, and the increased firing is responsible for stimulation-induced movements. Finally, stimulation of the STN's projection to the brainstem mesencephalic locomotor region was sufficient to reproduce the behavioral effects of STN stimulation. These results question the common assumption that the STN suppresses movement, and instead suggest that STN output can precisely specify action parameters via direct projections to the brainstem.SIGNIFICANCE STATEMENT Our results question the common assumption that the subthalamic nucleus (STN) suppresses movement, and instead suggest that STN output can precisely specify action parameters via direct projections to the brainstem.
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Affiliation(s)
- Alexander D Friedman
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina 27708
| | - Henry H Yin
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina 27708
- Department of Neurobiology, Duke University School of Medicine, Durham, North Carolina 27708
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20
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Albaugh DL, Gittis AH. Basal ganglia: Appreciating the 'value' of the GPe. Curr Biol 2023; 33:R1060-R1062. [PMID: 37875082 DOI: 10.1016/j.cub.2023.09.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Reward predictions and prediction errors are encoded in the GPe in a cell type-specific manner. A newly discovered cell type, the Slow Pacemaker, robustly encodes reward value and generates prediction errors in a manner remarkably similar to midbrain dopamine neurons.
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Affiliation(s)
- Daniel L Albaugh
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Aryn H Gittis
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
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21
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Bond K, Rasero J, Madan R, Bahuguna J, Rubin J, Verstynen T. Competing neural representations of choice shape evidence accumulation in humans. eLife 2023; 12:e85223. [PMID: 37818943 PMCID: PMC10624421 DOI: 10.7554/elife.85223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 10/10/2023] [Indexed: 10/13/2023] Open
Abstract
Making adaptive choices in dynamic environments requires flexible decision policies. Previously, we showed how shifts in outcome contingency change the evidence accumulation process that determines decision policies. Using in silico experiments to generate predictions, here we show how the cortico-basal ganglia-thalamic (CBGT) circuits can feasibly implement shifts in decision policies. When action contingencies change, dopaminergic plasticity redirects the balance of power, both within and between action representations, to divert the flow of evidence from one option to another. When competition between action representations is highest, the rate of evidence accumulation is the lowest. This prediction was validated in in vivo experiments on human participants, using fMRI, which showed that (1) evoked hemodynamic responses can reliably predict trial-wise choices and (2) competition between action representations, measured using a classifier model, tracked with changes in the rate of evidence accumulation. These results paint a holistic picture of how CBGT circuits manage and adapt the evidence accumulation process in mammals.
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Affiliation(s)
- Krista Bond
- Department of Psychology, Carnegie Mellon UniversityPittsburghUnited States
- Center for the Neural Basis of CognitionPittsburghUnited States
- Carnegie Mellon Neuroscience InstitutePittsburghUnited States
| | - Javier Rasero
- Department of Psychology, Carnegie Mellon UniversityPittsburghUnited States
| | - Raghav Madan
- Department of Biomedical and Health Informatics, University of WashingtonSeattleUnited States
| | - Jyotika Bahuguna
- Department of Psychology, Carnegie Mellon UniversityPittsburghUnited States
| | - Jonathan Rubin
- Center for the Neural Basis of CognitionPittsburghUnited States
- Department of Mathematics, University of PittsburghPittsburghUnited States
| | - Timothy Verstynen
- Department of Psychology, Carnegie Mellon UniversityPittsburghUnited States
- Center for the Neural Basis of CognitionPittsburghUnited States
- Carnegie Mellon Neuroscience InstitutePittsburghUnited States
- Department of Biomedical Engineering, Carnegie Mellon UniversityPittsburghUnited States
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22
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Mizes KGC, Lindsey J, Escola GS, Ölveczky BP. Dissociating the contributions of sensorimotor striatum to automatic and visually guided motor sequences. Nat Neurosci 2023; 26:1791-1804. [PMID: 37667040 DOI: 10.1038/s41593-023-01431-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/14/2023] [Indexed: 09/06/2023]
Abstract
The ability to sequence movements in response to new task demands enables rich and adaptive behavior. However, such flexibility is computationally costly and can result in halting performances. Practicing the same motor sequence repeatedly can render its execution precise, fast and effortless, that is, 'automatic'. The basal ganglia are thought to underlie both types of sequence execution, yet whether and how their contributions differ is unclear. We parse this in rats trained to perform the same motor sequence instructed by cues and in a self-initiated overtrained, or 'automatic,' condition. Neural recordings in the sensorimotor striatum revealed a kinematic code independent of the execution mode. Although lesions reduced the movement speed and affected detailed kinematics similarly, they disrupted high-level sequence structure for automatic, but not visually guided, behaviors. These results suggest that the basal ganglia are essential for 'automatic' motor skills that are defined in terms of continuous kinematics, but can be dispensable for discrete motor sequences guided by sensory cues.
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Affiliation(s)
- Kevin G C Mizes
- Program in Biophysics, Harvard University, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Jack Lindsey
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York City, NY, USA
| | - G Sean Escola
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York City, NY, USA
- Department of Psychiatry, Columbia University, New York City, NY, USA
| | - Bence P Ölveczky
- Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
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23
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Wilson CJ, Jones JA. Propagation of Oscillations in the Indirect Pathway of the Basal Ganglia. J Neurosci 2023; 43:6112-6125. [PMID: 37400253 PMCID: PMC10476642 DOI: 10.1523/jneurosci.0445-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/22/2023] [Accepted: 06/23/2023] [Indexed: 07/05/2023] Open
Abstract
Oscillatory signals propagate in the basal ganglia from prototypic neurons in the external globus pallidus (GPe) to their target neurons in the substantia nigra pars reticulata (SNr), internal pallidal segment, and subthalamic nucleus. Neurons in the GPe fire spontaneously, so oscillatory input signals can be encoded as changes in timing of action potentials within an ongoing spike train. When GPe neurons were driven by an oscillatory current in male and female mice, these spike-timing changes produced spike-oscillation coherence over a range of frequencies extending at least to 100 Hz. Using the known kinetics of the GPe→SNr synapse, we calculated the postsynaptic currents that would be generated in SNr neurons from the recorded GPe spike trains. The ongoing synaptic barrage from spontaneous firing, frequency-dependent short-term depression, and stochastic fluctuations at the synapse embed the input oscillation into a noisy sequence of synaptic currents in the SNr. The oscillatory component of the resulting synaptic current must compete with the noisy spontaneous synaptic barrage for control of postsynaptic SNr neurons, which have their own frequency-dependent sensitivities. Despite this, SNr neurons subjected to synaptic conductance changes generated from recorded GPe neuron firing patterns also became coherent with oscillations over a broad range of frequencies. The presynaptic, synaptic, and postsynaptic frequency sensitivities were all dependent on the firing rates of presynaptic and postsynaptic neurons. Firing rate changes, often assumed to be the propagating signal in these circuits, do not encode most oscillation frequencies, but instead determine which signal frequencies propagate effectively and which are suppressed.SIGNIFICANCE STATEMENT Oscillations are present in all the basal ganglia nuclei, include a range of frequencies, and change over the course of learning and behavior. Exaggerated oscillations are a hallmark of basal ganglia pathologies, and each has a specific frequency range. Because of its position as a hub in the basal ganglia circuitry, the globus pallidus is a candidate origin for oscillations propagating between nuclei. We imposed low-amplitude oscillations on individual globus pallidus neurons at specific frequencies and measured the coherence between the oscillation and firing as a function of frequency. We then used these responses to measure the effectiveness of oscillatory propagation to other basal ganglia nuclei. Propagation was effective for oscillation frequencies as high as 100 Hz.
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Affiliation(s)
- Charles J Wilson
- Department of Neuroscience, Developmental and Regenerative Biology, University of Texas at San Antonio, San Antonio, Texas 78249
| | - James A Jones
- Department of Neuroscience, Developmental and Regenerative Biology, University of Texas at San Antonio, San Antonio, Texas 78249
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24
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Wärnberg E, Kumar A. Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia. Proc Natl Acad Sci U S A 2023; 120:e2221994120. [PMID: 37527344 PMCID: PMC10410740 DOI: 10.1073/pnas.2221994120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 06/08/2023] [Indexed: 08/03/2023] Open
Abstract
It is well established that midbrain dopaminergic neurons support reinforcement learning (RL) in the basal ganglia by transmitting a reward prediction error (RPE) to the striatum. In particular, different computational models and experiments have shown that a striatum-wide RPE signal can support RL over a small discrete set of actions (e.g., no/no-go, choose left/right). However, there is accumulating evidence that the basal ganglia functions not as a selector between predefined actions but rather as a dynamical system with graded, continuous outputs. To reconcile this view with RL, there is a need to explain how dopamine could support learning of continuous outputs, rather than discrete action values. Inspired by the recent observations that besides RPE, the firing rates of midbrain dopaminergic neurons correlate with motor and cognitive variables, we propose a model in which dopamine signal in the striatum carries a vector-valued error feedback signal (a loss gradient) instead of a homogeneous scalar error (a loss). We implement a local, "three-factor" corticostriatal plasticity rule involving the presynaptic firing rate, a postsynaptic factor, and the unique dopamine concentration perceived by each striatal neuron. With this learning rule, we show that such a vector-valued feedback signal results in an increased capacity to learn a multidimensional series of real-valued outputs. Crucially, we demonstrate that this plasticity rule does not require precise nigrostriatal synapses but remains compatible with experimental observations of random placement of varicosities and diffuse volume transmission of dopamine.
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Affiliation(s)
- Emil Wärnberg
- Department of Neuroscience, Karolinska Institutet, 171 77Stockholm, Sweden
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| | - Arvind Kumar
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
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25
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Monteiro T, Rodrigues FS, Pexirra M, Cruz BF, Gonçalves AI, Rueda-Orozco PE, Paton JJ. Using temperature to analyze the neural basis of a time-based decision. Nat Neurosci 2023; 26:1407-1416. [PMID: 37443279 DOI: 10.1038/s41593-023-01378-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 06/12/2023] [Indexed: 07/15/2023]
Abstract
The basal ganglia are thought to contribute to decision-making and motor control. These functions are critically dependent on timing information, which can be extracted from the evolving state of neural populations in their main input structure, the striatum. However, it is debated whether striatal activity underlies latent, dynamic decision processes or kinematics of overt movement. Here, we measured the impact of temperature on striatal population activity and the behavior of rats, and compared the observed effects with neural activity and behavior collected in multiple versions of a temporal categorization task. Cooling caused dilation, and warming contraction, of both neural activity and patterns of judgment in time, mimicking endogenous decision-related variability in striatal activity. However, temperature did not similarly affect movement kinematics. These data provide compelling evidence that the timecourse of evolving striatal activity dictates the speed of a latent process that is used to guide choices, but not continuous motor control. More broadly, they establish temporal scaling of population activity as a likely neural basis for variability in timing behavior.
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Affiliation(s)
- Tiago Monteiro
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- Department of Biology, University of Oxford, Oxford, UK
| | | | - Margarida Pexirra
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Bruno F Cruz
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
- NeuroGEARS Ltd., London, UK
| | - Ana I Gonçalves
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | | | - Joseph J Paton
- Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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26
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Abstract
Striosomes form neurochemically specialized compartments of the striatum embedded in a large matrix made up of modules called matrisomes. Striosome-matrix architecture is multiplexed with the canonical direct-indirect organization of the striatum. Striosomal functions remain to be fully clarified, but key information is emerging. First, striosomes powerfully innervate nigral dopamine-containing neurons and can completely shut down their activity, with a following rebound excitation. Second, striosomes receive limbic and cognition-related corticostriatal afferents and are dynamically modulated in relation to value-based actions. Third, striosomes are spatially interspersed among matrisomes and interneurons and are influenced by local and global neuromodulatory and oscillatory activities. Fourth, striosomes tune engagement and the motivation to perform reinforcement learning, to manifest stereotypical behaviors, and to navigate valence conflicts and valence discriminations. We suggest that, at an algorithmic level, striosomes could serve as distributed scaffolds to provide formats of the striatal computations generated through development and refined through learning. We propose that striosomes affect subjective states. By transforming corticothalamic and other inputs to the functional formats of the striatum, they could implement state transitions in nigro-striato-nigral circuits to affect bodily and cognitive actions according to internal motives whose functions are compromised in neuropsychiatric conditions.
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Affiliation(s)
- Ann M Graybiel
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
| | - Ayano Matsushima
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
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27
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Kameda M, Niikawa K, Uematsu A, Tanaka M. Sensory and motor representations of internalized rhythms in the cerebellum and basal ganglia. Proc Natl Acad Sci U S A 2023; 120:e2221641120. [PMID: 37276394 PMCID: PMC10268275 DOI: 10.1073/pnas.2221641120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 05/04/2023] [Indexed: 06/07/2023] Open
Abstract
Both the cerebellum and basal ganglia are involved in rhythm processing, but their specific roles remain unclear. During rhythm perception, these areas may be processing purely sensory information, or they may be involved in motor preparation, as periodic stimuli often induce synchronized movements. Previous studies have shown that neurons in the cerebellar dentate nucleus and the caudate nucleus exhibit periodic activity when the animals prepare to respond to the random omission of regularly repeated visual stimuli. To detect stimulus omission, the animals need to learn the stimulus tempo and predict the timing of the next stimulus. The present study demonstrates that neuronal activity in the cerebellum is modulated by the location of the repeated stimulus and that in the striatum (STR) by the direction of planned movement. However, in both brain regions, neuronal activity during movement and the effect of electrical stimulation immediately before stimulus omission were largely dependent on the direction of movement. These results suggest that, during rhythm processing, the cerebellum is involved in multiple stages from sensory prediction to motor control, while the STR consistently plays a role in motor preparation. Thus, internalized rhythms without movement are maintained as periodic neuronal activity, with the cerebellum and STR preferring sensory and motor representations, respectively.
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Affiliation(s)
- Masashi Kameda
- Department of Physiology, Hokkaido University School of Medicine, Sapporo060-8638, Japan
| | - Koichiro Niikawa
- Department of Physiology, Hokkaido University School of Medicine, Sapporo060-8638, Japan
| | - Akiko Uematsu
- Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - Masaki Tanaka
- Department of Physiology, Hokkaido University School of Medicine, Sapporo060-8638, Japan
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28
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Barnett WH, Kuznetsov A, Lapish CC. Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior. PLoS One 2023; 18:e0279841. [PMID: 36943842 PMCID: PMC10030038 DOI: 10.1371/journal.pone.0279841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 12/15/2022] [Indexed: 03/23/2023] Open
Abstract
Cortical and basal ganglia circuits play a crucial role in the formation of goal-directed and habitual behaviors. In this study, we investigate the cortico-striatal circuitry involved in learning and the role of this circuitry in the emergence of inflexible behaviors such as those observed in addiction. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal-directed and habit learning. The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC) which represents outcomes, and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and learning a punished outcome. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the impairment of executive control, which was implemented as poor outcome representation in the PFC. The degraded executive control reduced the efficacy of goal-directed learning, and stimulus-response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model describes how circuits of the dorsal striatum are dynamically engaged to control behavior and how the impairment of executive control by the PFC enhances inflexible behavior.
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Affiliation(s)
- William H. Barnett
- Department of Psychology, Indiana University—Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Alexey Kuznetsov
- Department of Mathematics, Indiana University—Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Christopher C. Lapish
- Department of Psychology, Indiana University—Purdue University Indianapolis, Indianapolis, Indiana, United States of America
- Stark Neurosciences Research Institute, Indiana University—Purdue University Indianapolis, Indianapolis, Indiana, United States of America
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29
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Sabzevar FT, Vautrelle N, Zheng Y, Smith PF. Vestibular modulation of the tail of the rat striatum. Sci Rep 2023; 13:4443. [PMID: 36932124 PMCID: PMC10023713 DOI: 10.1038/s41598-023-31289-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/09/2023] [Indexed: 03/19/2023] Open
Abstract
Fragmented and piecemeal evidence from animal and human studies suggests that vestibular information is transmitted to the striatum, a part of the basal ganglia that degenerates in Parkinson's Disease. Nonetheless, surprisingly little is known about the precise effects of activation of the vestibular system on the striatum. Electrophysiological studies have yielded inconsistent results, with many studies reporting only sparse responses to vestibular stimulation in the dorsomedial striatum. In this study, we sought to elucidate the effects of electrical stimulation of the peripheral vestibular system on electrophysiological responses in the tail of the rat striatum, a newly discovered region for sensory input. Rats were anaesthetised with urethane and a bipolar stimulating electrode was placed in the round window in order to activate the peripheral vestibular system. A recording electrode was positioned in the tail of the striatum. Local field potentials (LFPs) were recorded ipsilaterally and contralaterally to the stimulation using a range of current parameters. In order to confirm that the vestibular system was activated, video-oculography was used to monitor vestibular nystagmus. At current amplitudes that evoked vestibular nystagmus, clear triphasic LFPs were evoked in the bilateral tail of the striatum, with the first phase of the waveform exhibiting latencies of less than 22 ms. The LFP amplitude increased with increasing current amplitude (P ≤ 0.0001). In order to exclude the possibility that the LFPs were evoked by the activation of the auditory system, the cochlea was surgically lesioned in some animals. In these animals the LFPs persisted despite the cochlear lesions, which were verified histologically. Overall, the results obtained suggest that there are vestibular projections to the tail of the striatum, which could possibly arise from projections via the vestibular nucleus or cerebellum and the parafasicular nucleus of the thalamus.
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Affiliation(s)
| | - Nico Vautrelle
- Department of Anatomy, School of Biomedical Sciences, and Brain Health Research Centre, University of Otago, Dunedin, New Zealand
| | - Yiwen Zheng
- Department of Pharmacology and Toxicology, University of Otago, Dunedin, New Zealand
- The Eisdell Moore Centre for Hearing and Balance Research, University of Auckland, Auckland, New Zealand
| | - Paul F Smith
- Department of Pharmacology and Toxicology, University of Otago, Dunedin, New Zealand.
- The Eisdell Moore Centre for Hearing and Balance Research, University of Auckland, Auckland, New Zealand.
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30
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Song J, Lin H, Liu S. Basal ganglia network dynamics and function: Role of direct, indirect and hyper-direct pathways in action selection. Network 2023; 34:84-121. [PMID: 36856435 DOI: 10.1080/0954898x.2023.2173816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/11/2022] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
Basal ganglia (BG) are a widely recognized neural basis for action selection, but its decision-making mechanism is still a difficult problem for researchers. Therefore, we constructed a spiking neural network inspired by the BG anatomical data. Simulation experiments were based on the principle of dis-inhibition and our functional hypothesis within the BG: the direct pathway, the indirect pathway, and the hyper-direct pathway of the BG jointly implement the initiation execution and termination of motor programs. Firstly, we studied the dynamic process of action selection with the network, which contained intra-group competition and inter-group competition. Secondly, we focused on the effects of the stimulus intensity and the proportion of excitation and inhibition on the GPi/SNr. The results suggested that inhibition and excitation shape action selection. They also explained why the firing rate of GPi/SNr did not continue to increase in the action-selection experiment. Finally, we discussed the experimental results with the functional hypothesis. Uniquely, this paper summarized the decision-making neural mechanism of action selection based on the direct pathway, the indirect pathway, and the hyper-direct pathway within BG.
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Affiliation(s)
- Jian Song
- School of Mathematics, South China University of Technology, Guangzhou, China
| | - Hui Lin
- Department of Precision Instruments, Tsinghua University, Beijing, China
| | - Shenquan Liu
- School of Mathematics, South China University of Technology, Guangzhou, China
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31
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Morita K, Shimomura K, Kawaguchi Y. Opponent Learning with Different Representations in the Cortico-Basal Ganglia Circuits. eNeuro 2023; 10:ENEURO.0422-22.2023. [PMID: 36653187 PMCID: PMC9884109 DOI: 10.1523/eneuro.0422-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/06/2022] [Accepted: 01/03/2023] [Indexed: 01/20/2023] Open
Abstract
The direct and indirect pathways of the basal ganglia (BG) have been suggested to learn mainly from positive and negative feedbacks, respectively. Since these pathways unevenly receive inputs from different cortical neuron types and/or regions, they may preferentially use different state/action representations. We explored whether such a combined use of different representations, coupled with different learning rates from positive and negative reward prediction errors (RPEs), has computational benefits. We modeled animal as an agent equipped with two learning systems, each of which adopted individual representation (IR) or successor representation (SR) of states. With varying the combination of IR or SR and also the learning rates from positive and negative RPEs in each system, we examined how the agent performed in a dynamic reward navigation task. We found that combination of SR-based system learning mainly from positive RPEs and IR-based system learning mainly from negative RPEs could achieve a good performance in the task, as compared with other combinations. In such a combination of appetitive SR-based and aversive IR-based systems, both systems show activities of comparable magnitudes with opposite signs, consistent with the suggested profiles of the two BG pathways. Moreover, the architecture of such a combination provides a novel coherent explanation for the functional significance and underlying mechanism of diverse findings about the cortico-BG circuits. These results suggest that particularly combining different representations with appetitive and aversive learning could be an effective learning strategy in certain dynamic environments, and it might actually be implemented in the cortico-BG circuits.
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Affiliation(s)
- Kenji Morita
- Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo 113-0033, Japan
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo 113-0033, Japan
| | - Kanji Shimomura
- Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo 113-0033, Japan
- Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira 187-8551, Japan
| | - Yasuo Kawaguchi
- Brain Science Institute, Tamagawa University, Machida 194-8610, Japan
- National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan
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32
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Yoshida J, Oñate M, Khatami L, Vera J, Nadim F, Khodakhah K. Cerebellar Contributions to the Basal Ganglia Influence Motor Coordination, Reward Processing, and Movement Vigor. J Neurosci 2022; 42:8406-8415. [PMID: 36351826 PMCID: PMC9665921 DOI: 10.1523/jneurosci.1535-22.2022] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
Both the cerebellum and the basal ganglia are known for their roles in motor control and motivated behavior. These two systems have been classically considered as independent structures that coordinate their contributions to behavior via separate cortico-thalamic loops. However, recent evidence demonstrates the presence of a rich set of direct connections between these two regions. Although there is strong evidence for connections in both directions, for brevity we limit our discussion to the better-characterized connections from the cerebellum to the basal ganglia. We review two sets of such connections: disynaptic projections through the thalamus and direct monosynaptic projections to the midbrain dopaminergic nuclei, the VTA and the SNc. In each case, we review the evidence for these pathways from anatomic tracing and physiological recordings, and discuss their potential functional roles. We present evidence that the disynaptic pathway through the thalamus is involved in motor coordination, and that its dysfunction contributes to motor deficits, such as dystonia. We then discuss how cerebellar projections to the VTA and SNc influence dopamine release in the respective targets of these nuclei: the NAc and the dorsal striatum. We argue that the cerebellar projections to the VTA may play a role in reward-based learning and therefore contribute to addictive behavior, whereas the projection to the SNc may contribute to movement vigor. Finally, we speculate how these projections may explain many of the observations that indicate a role for the cerebellum in mental disorders, such as schizophrenia.
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Affiliation(s)
- Junichi Yoshida
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
| | - Maritza Oñate
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
| | - Leila Khatami
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
| | - Jorge Vera
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
| | - Farzan Nadim
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
- Department of Biological Sciences, New Jersey Institute of Technology, Newark, New Jersey, 07102
| | - Kamran Khodakhah
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
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33
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McNamara CG, Rothwell M, Sharott A. Stable, interactive modulation of neuronal oscillations produced through brain-machine equilibrium. Cell Rep 2022; 41:111616. [PMID: 36351413 PMCID: PMC7614081 DOI: 10.1016/j.celrep.2022.111616] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/28/2022] [Accepted: 10/17/2022] [Indexed: 11/09/2022] Open
Abstract
Closed-loop interaction has the potential to regulate ongoing brain activity by continuously binding an external stimulation to specific dynamics of a neural circuit. Achieving interactive modulation requires a stable brain-machine feedback loop. Here, we demonstrate that it is possible to maintain oscillatory brain activity in a desired state by delivering stimulation accurately aligned with the timing of each cycle. We develop a fast algorithm that responds on a cycle-by-cycle basis to stimulate basal ganglia nuclei at predetermined phases of successive cortical beta cycles in parkinsonian rats. Using this approach, an equilibrium emerges between the modified brain signal and feedback-dependent stimulation pattern, leading to sustained amplification or suppression of the oscillation depending on the phase targeted. Beta amplification slows movement speed by biasing the animal's mode of locomotion. Together, these findings show that highly responsive, phase-dependent stimulation can achieve a stable brain-machine interaction that leads to robust modulation of ongoing behavior.
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Affiliation(s)
- Colin G McNamara
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK.
| | - Max Rothwell
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
| | - Andrew Sharott
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK.
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Singh M, Skippen P, He J, Thomson P, Fuelscher I, Caeyenberghs K, Anderson V, Nicholson JM, Hyde C, Silk TJ. Longitudinal developmental trajectories of inhibition and white-matter maturation of the fronto-basal-ganglia circuits. Dev Cogn Neurosci 2022; 58:101171. [PMID: 36372005 PMCID: PMC9660590 DOI: 10.1016/j.dcn.2022.101171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/06/2022] [Accepted: 10/29/2022] [Indexed: 01/13/2023] Open
Abstract
Response inhibition refers to the cancelling of planned (or restraining of ongoing) actions and is required in much of our everyday life. Response inhibition appears to improve dramatically in early development and plateau in adolescence. The fronto-basal-ganglia network has long been shown to predict individual differences in the ability to enact response inhibition. In the current study, we examined whether developmental trajectories of fiber-specific white matter properties of the fronto-basal-ganglia network was predictive of parallel developmental trajectories of response inhibition. 138 children aged 9-14 completed the stop-signal task (SST). A subsample of 73 children underwent high-angular resolution diffusion MRI data for up to three time points. Performance on the SST was assessed using a parametric race modelling approach. White matter organization of the fronto-basal-ganglia circuit was estimated using fixel-based analysis. Contrary to predictions, we did not find any significant associations between maturational trajectories of fronto-basal-ganglia white matter and developmental improvements in SST performance. Findings suggest that the development of white matter organization of the fronto-basal-ganglia and development of stopping performance follow distinct maturational trajectories.
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Affiliation(s)
- Mervyn Singh
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia.
| | - Patrick Skippen
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
| | - Jason He
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Phoebe Thomson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Vicki Anderson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia; The Royal Children's Hospital, Melbourne, Australia
| | - Jan M Nicholson
- Judith Lumley Centre, La Trobe University, Melbourne, Australia
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Timothy J Silk
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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35
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Mizrahi-Kliger AD, Kaplan A, Israel Z, Bergman H. Entrainment to sleep spindles reflects dissociable patterns of connectivity between cortex and basal ganglia. Cell Rep 2022; 40:111367. [PMID: 36130495 DOI: 10.1016/j.celrep.2022.111367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/20/2022] [Accepted: 08/25/2022] [Indexed: 11/18/2022] Open
Abstract
Sleep spindles are crucial for learning in the cortex and basal ganglia (BG) because they facilitate the reactivation of previously active neuronal ensembles. Studying field potentials (FPs) and spiking in the cortex and BG during sleep in non-human primates following pre-sleep learning, we show that FP sleep spindles are widespread in the BG and are similar to cortical spindles in morphology, spectral content, and response to the pre-sleep task. Further, BG spindles are concordant with electroencephalogram (EEG) spindles and associated with increased cortico-BG correlation. However, spindles across the BG differ markedly in their entrainment of local spiking. The spiking activity of striatal projection neurons exhibits consistent phase locking to striatal and EEG spindles, producing phase windows of peaked cross-region spindling. In contrast, firing in other BG nuclei is not entrained to either local or EEG sleep spindles. These results suggest corticostriatal synapses as the main hub for offline cortico-BG communication.
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Affiliation(s)
- Aviv D Mizrahi-Kliger
- Department of Neurobiology, Institute of Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 9112001 Jerusalem, Israel.
| | - Alexander Kaplan
- Department of Neurobiology, Institute of Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 9112001 Jerusalem, Israel; The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, 9190401 Jerusalem, Israel
| | - Zvi Israel
- Department of Neurosurgery, Hadassah University Hospital, 9112001 Jerusalem, Israel
| | - Hagai Bergman
- Department of Neurobiology, Institute of Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 9112001 Jerusalem, Israel; The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, 9190401 Jerusalem, Israel; Department of Neurosurgery, Hadassah University Hospital, 9112001 Jerusalem, Israel
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36
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Sych Y, Fomins A, Novelli L, Helmchen F. Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning. Cell Rep 2022; 40:111394. [PMID: 36130513 PMCID: PMC9513804 DOI: 10.1016/j.celrep.2022.111394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 05/31/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Adaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior. Multi-fiber photometry reveals brain network adaptations during learning Activity in most regions temporally shifts from reward to predictive stimulus Cross-regional interactions in the CBGTC network increase and stabilize with learning Internal pallidum, VM thalamus, and prefrontal cortex regions emerge as hubs
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Affiliation(s)
- Yaroslav Sych
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland.
| | - Aleksejs Fomins
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland
| | - Leonardo Novelli
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland.
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Whalen TC, Parker JE, Gittis AH, Rubin JE. Transmission of delta band (0.5-4 Hz) oscillations from the globus pallidus to the substantia nigra pars reticulata in dopamine depletion. J Comput Neurosci 2022; 51:361-380. [PMID: 37266768 PMCID: PMC10527635 DOI: 10.1007/s10827-023-00853-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 01/20/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023]
Abstract
Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.
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Affiliation(s)
- Timothy C Whalen
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
- Design Interactive, Inc., Orlando, FL, United States
| | - John E Parker
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Aryn H Gittis
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Jonathan E Rubin
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States.
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38
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Zhou J, Hormigo S, Sajid MS, Castro-Alamancos MA. Caution Influences Avoidance and Approach Behaviors Differently. J Neurosci 2022; 42:5899-5915. [PMID: 35705490 PMCID: PMC9337599 DOI: 10.1523/jneurosci.1892-21.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 06/09/2022] [Accepted: 06/13/2022] [Indexed: 01/29/2023] Open
Abstract
While conflict between incompatible goals has well-known effects on actions, in many situations the same action may produce harmful or beneficial consequences during different periods in a nonconflicting manner, e.g., crossing the street during a red or green light. To avoid harm, subjects must be cautious to inhibit the action specifically when it is punished, as in passive avoidance, but act when it is beneficial, as in active avoidance or active approach. In mice of both sexes performing a signaled action to avoid harm or obtain reward, we found that addition of a new rule that punishes the action when it occurs unsignaled delays the timing of the signaled action in an apparent sign of increased caution. Caution depended on task signaling, contingency, and reinforcement type. Interestingly, caution became persistent when the signaled action was avoidance motivated by danger but was only transient when it was approach motivated by reward. Although caution is represented by the activity of neurons in the midbrain, it developed independent of frontal cortex or basal ganglia output circuits. These results indicate that caution disrupts actions in different ways depending on the motivational state and may develop from unforeseen brain circuits.SIGNIFICANCE STATEMENT Actions, such as crossing the street at a light, can have benefits during one light signal (getting somewhere) but can be harmful during a different signal (being run over). Humans must be cautious to cross the street during the period marked by the appropriate signal. In mice performing a signaled action to avoid harm or obtain reward, we found that addition of a new rule that punishes the action when it occurs unsignaled, delays the timing of the signaled action in an apparent sign of increased caution. Caution became persistent when the signaled action was motivated by danger, but not when it was motivated by reward. Moreover, the development of caution did not depend on prototypical frontal cortex circuits.
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Affiliation(s)
- Ji Zhou
- Department of Neuroscience, University of Connecticut School of Medicine, Farmington, Connecticut 06001
| | - Sebastian Hormigo
- Department of Neuroscience, University of Connecticut School of Medicine, Farmington, Connecticut 06001
| | - Muhammad S Sajid
- Department of Neuroscience, University of Connecticut School of Medicine, Farmington, Connecticut 06001
| | - Manuel A Castro-Alamancos
- Department of Neuroscience, University of Connecticut School of Medicine, Farmington, Connecticut 06001
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Adam EM, Brown EN, Kopell N, McCarthy MM. Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks. Proc Natl Acad Sci U S A 2022; 119:e2120808119. [PMID: 35500112 PMCID: PMC9171607 DOI: 10.1073/pnas.2120808119] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 03/25/2022] [Indexed: 12/03/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.
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Affiliation(s)
- Elie M. Adam
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Emery N. Brown
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114
| | - Nancy Kopell
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215
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40
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Möller M, Manohar S, Bogacz R. Uncertainty-guided learning with scaled prediction errors in the basal ganglia. PLoS Comput Biol 2022; 18:e1009816. [PMID: 35622863 PMCID: PMC9182698 DOI: 10.1371/journal.pcbi.1009816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 06/09/2022] [Accepted: 05/05/2022] [Indexed: 11/19/2022] Open
Abstract
To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward, and the estimate of the mean reward should be updated to a smaller extent after each observation. However, it is not known how the magnitude of the observation noise might be tracked and used to control prediction updates in the brain reward system. Here, we introduce a new model that uses simple, tractable learning rules that track the mean and standard deviation of reward, and leverages prediction errors scaled by uncertainty as the central feedback signal. We show that the new model has an advantage over conventional reinforcement learning models in a value tracking task, and approaches a theoretic limit of performance provided by the Kalman filter. Further, we propose a possible biological implementation of the model in the basal ganglia circuit. In the proposed network, dopaminergic neurons encode reward prediction errors scaled by standard deviation of rewards. We show that such scaling may arise if the striatal neurons learn the standard deviation of rewards and modulate the activity of dopaminergic neurons. The model is consistent with experimental findings concerning dopamine prediction error scaling relative to reward magnitude, and with many features of striatal plasticity. Our results span across the levels of implementation, algorithm, and computation, and might have important implications for understanding the dopaminergic prediction error signal and its relation to adaptive and effective learning.
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Affiliation(s)
- Moritz Möller
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Sanjay Manohar
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Rafal Bogacz
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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41
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Parr AC, Calabro F, Tervo-Clemmens B, Larsen B, Foran W, Luna B. Contributions of dopamine-related basal ganglia neurophysiology to the developmental effects of incentives on inhibitory control. Dev Cogn Neurosci 2022; 54:101100. [PMID: 35344773 PMCID: PMC8961188 DOI: 10.1016/j.dcn.2022.101100] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 02/23/2022] [Accepted: 03/16/2022] [Indexed: 01/19/2023] Open
Abstract
Inhibitory control can be less reliable in adolescence, however, in the presence of rewards, adolescents' performance often improves to adult levels. Dopamine is known to play a role in signaling rewards and supporting cognition, but its role in the enhancing effects of reward on adolescent cognition and inhibitory control remains unknown. Here, we assessed the contribution of basal ganglia dopamine-related neurophysiology using longitudinal MR-based assessments of tissue iron in rewarded inhibitory control, using an antisaccade task. In line with prior work, we show that neutral performance improves with age, and incentives enhance performance in adolescents to that of adults. We find that basal ganglia tissue iron is associated with individual differences in the magnitude of this reward boost, which is strongest in those with high levels of tissue iron, predominantly in adolescence. Our results provide novel evidence that basal ganglia neurophysiology supports developmental effects of rewards on cognition, which can inform neurodevelopmental models of the role of dopamine in reward processing during adolescence.
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Affiliation(s)
- Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 14213, United States.
| | - Finnegan Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 14213, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 14213, United States
| | | | - Bart Larsen
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Will Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 14213, United States
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 14213, United States.
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42
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Abstract
In this issue of Neuron, Chevée et al. (2022) performed extracellular electrophysiological recordings from claustrum neurons during a sensory selection task. They found that neural activity in the claustrum reflected future motor output rather than sensory inputs and that chemogenetic suppression of claustrum activity reduced motor impulsivity in this task.
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Affiliation(s)
- Alison D Do
- Department of Physiology, University of Alberta, Edmonton, AB, Canada
| | - Jesse Jackson
- Department of Physiology, University of Alberta, Edmonton, AB, Canada; Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
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43
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Spiliotis K, Starke J, Franz D, Richter A, Köhling R. Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model. Biol Cybern 2022; 116:93-116. [PMID: 34894291 PMCID: PMC8866393 DOI: 10.1007/s00422-021-00909-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 10/31/2021] [Indexed: 06/14/2023]
Abstract
A large-scale computational model of the basal ganglia network and thalamus is proposed to describe movement disorders and treatment effects of deep brain stimulation (DBS). The model of this complex network considers three areas of the basal ganglia region: the subthalamic nucleus (STN) as target area of DBS, the globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus. Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi. Macroscopic quantities are derived which correlate closely to thalamic responses and hence motor programme fidelity. It can be demonstrated that depending on different levels of striatal projections to the GPe and GPi, the dynamics of these macroscopic quantities (synchronisation index, mean synaptic activity and response efficacy) switch from normal to Parkinsonian conditions. Simulating DBS of the STN affects the dynamics of the entire network, increasing the thalamic activity to levels close to normal, while differing from both normal and Parkinsonian dynamics. Using the mentioned macroscopic quantities, the model proposes optimal DBS frequency ranges above 130 Hz.
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Affiliation(s)
| | - Jens Starke
- Institute of Mathematics, University of Rostock, 18057 Rostock, Germany
| | - Denise Franz
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
| | - Angelika Richter
- Institute of Pharmacology, Pharmacy and Toxicology, Faculty of Veterinary Medicine, University of Leipzig, Leipzig, Germany
| | - Rüdiger Köhling
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
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44
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Li J, Curley WH, Guerin B, Dougherty DD, Dalca AV, Fischl B, Horn A, Edlow BL. Mapping the subcortical connectivity of the human default mode network. Neuroimage 2021; 245:118758. [PMID: 34838949 PMCID: PMC8945548 DOI: 10.1016/j.neuroimage.2021.118758] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/29/2021] [Accepted: 11/23/2021] [Indexed: 01/17/2023] Open
Abstract
The default mode network (DMN) mediates self-awareness and introspection, core components of human consciousness. Therapies to restore consciousness in patients with severe brain injuries have historically targeted subcortical sites in the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia, with the goal of reactivating cortical DMN nodes. However, the subcortical connectivity of the DMN has not been fully mapped, and optimal subcortical targets for therapeutic neuromodulation of consciousness have not been identified. In this work, we created a comprehensive map of DMN subcortical connectivity by combining high-resolution functional and structural datasets with advanced signal processing methods. We analyzed 7 Tesla resting-state functional MRI (rs-fMRI) data from 168 healthy volunteers acquired in the Human Connectome Project. The rs-fMRI blood-oxygen-level-dependent (BOLD) data were temporally synchronized across subjects using the BrainSync algorithm. Cortical and subcortical DMN nodes were jointly analyzed and identified at the group level by applying a novel Nadam-Accelerated SCAlable and Robust (NASCAR) tensor decomposition method to the synchronized dataset. The subcortical connectivity map was then overlaid on a 7 Tesla 100 µm ex vivo MRI dataset for neuroanatomic analysis using automated segmentation of nuclei within the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia. We further compared the NASCAR subcortical connectivity map with its counterpart generated from canonical seed-based correlation analyses. The NASCAR method revealed that BOLD signal in the central lateral nucleus of the thalamus and ventral tegmental area of the midbrain is strongly correlated with that of the DMN. In an exploratory analysis, additional subcortical sites in the median and dorsal raphe, lateral hypothalamus, and caudate nuclei were correlated with the cortical DMN. We also found that the putamen and globus pallidus are negatively correlated (i.e., anti-correlated) with the DMN, providing rs-fMRI evidence for the mesocircuit hypothesis of human consciousness, whereby a striatopallidal feedback system modulates anterior forebrain function via disinhibition of the central thalamus. Seed-based analyses yielded similar subcortical DMN connectivity, but the NASCAR result showed stronger contrast and better spatial alignment with dopamine immunostaining data. The DMN subcortical connectivity map identified here advances understanding of the subcortical regions that contribute to human consciousness and can be used to inform the selection of therapeutic targets in clinical trials for patients with disorders of consciousness.
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Affiliation(s)
- Jian Li
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - William H Curley
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Bastien Guerin
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Darin D Dougherty
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Adrian V Dalca
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Andreas Horn
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Movement Disorders & Neuromodulation Section, Department of Neurology, Charité - Universitätsmedizin, Berlin, Germany
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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45
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Bowden DM, German DC. Mapping reward mechanisms by intracerebral self-stimulation in the rhesus monkey (Macaca mulatta). J Comp Neurol 2021; 529:3564-3592. [PMID: 33978232 PMCID: PMC8920750 DOI: 10.1002/cne.25188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 05/01/2021] [Accepted: 05/03/2021] [Indexed: 11/08/2022]
Abstract
The objective of the study was to identify brain structures that mediate reward as evidenced by positive reinforcing effects of stimuli on behavior. Testing by intracerebral self-stimulation enabled monkeys to inform whether activation of ~2900 sites in 74 structures of 4 sensorimotor pathways and 4 modulatory loop pathways was positive, negative or neutral. Stimulation was rewarding at 30% of sites, negative at 17%, neutral at 52%. Virtually all (99%) structures yielded some positive or negative sites, suggesting a ubiquitous distribution of pathways transmitting valence information. Mapping of sites to structures with dense versus sparse dopaminergic (DA) or noradrenergic (NA) innervation showed that stimulation of DA-pathways was rewarding or neutral. Stimulation of NA-pathways was not rewarding. Stimulation of association areas was generally rewarding; stimulation of purely sensory or motor structures was generally negative. Reward related more to structures' sensorimotor function than to density of DA-innervation. Stimulation of basal ganglia loop pathways was rewarding except in lateral globus pallidus, an inhibitory structure in the negative feedback loop; stimulation of the cerebellar loop was rewarding in anterior vermis and the spinocerebellar pathway; and stimulation of the hippocampal CA1 loop was rewarding. While most positive sites were in the DA reward system, numerous sites in sparsely DA-innervated posterior cingulate and parietal cortices may represent a separate reward system. DA-density represents concentrations of plastic synapses that mediate acquisition of new synaptic connections. DA-sparse areas may represent innate, genetically programmed reward-associated pathways. Implications of findings in regard to response habituation and addiction are discussed.
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Affiliation(s)
- Douglas M. Bowden
- Department of Psychiatry and Behavioral Sciences and National Primate Research Center, University of Washington, Seattle, Washington
| | - Dwight C. German
- Department of Psychiatry and Behavioral Sciences and National Primate Research Center, University of Washington, Seattle, Washington
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
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46
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Singh Alvarado J, Goffinet J, Michael V, Liberti W, Hatfield J, Gardner T, Pearson J, Mooney R. Neural dynamics underlying birdsong practice and performance. Nature 2021; 599:635-639. [PMID: 34671166 PMCID: PMC9118926 DOI: 10.1038/s41586-021-04004-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 09/07/2021] [Indexed: 11/09/2022]
Abstract
Musical and athletic skills are learned and maintained through intensive practice to enable precise and reliable performance for an audience. Consequently, understanding such complex behaviours requires insight into how the brain functions during both practice and performance. Male zebra finches learn to produce courtship songs that are more varied when alone and more stereotyped in the presence of females1. These differences are thought to reflect song practice and performance, respectively2,3, providing a useful system in which to explore how neurons encode and regulate motor variability in these two states. Here we show that calcium signals in ensembles of spiny neurons (SNs) in the basal ganglia are highly variable relative to their cortical afferents during song practice. By contrast, SN calcium signals are strongly suppressed during female-directed performance, and optogenetically suppressing SNs during practice strongly reduces vocal variability. Unsupervised learning methods4,5 show that specific SN activity patterns map onto distinct song practice variants. Finally, we establish that noradrenergic signalling reduces vocal variability by directly suppressing SN activity. Thus, SN ensembles encode and drive vocal exploration during practice, and the noradrenergic suppression of SN activity promotes stereotyped and precise song performance for an audience.
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Affiliation(s)
| | - Jack Goffinet
- Department of Computer Science, Duke University, Durham, NC, USA
| | - Valerie Michael
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - William Liberti
- Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA, USA
| | - Jordan Hatfield
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Timothy Gardner
- Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, Eugene, OR, USA
| | - John Pearson
- Department of Neurobiology, Duke University, Durham, NC, USA.
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, USA.
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA.
| | - Richard Mooney
- Department of Neurobiology, Duke University, Durham, NC, USA.
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47
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West TO, Berthouze L, Farmer SF, Cagnan H, Litvak V. Inference of brain networks with approximate Bayesian computation - assessing face validity with an example application in Parkinsonism. Neuroimage 2021; 236:118020. [PMID: 33839264 PMCID: PMC8270890 DOI: 10.1016/j.neuroimage.2021.118020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 03/16/2021] [Accepted: 03/21/2021] [Indexed: 11/21/2022] Open
Abstract
This paper describes and validates a novel framework using the Approximate Bayesian Computation (ABC) algorithm for parameter estimation and model selection in models of mesoscale brain network activity. We provide a proof of principle, first pass validation of this framework using a set of neural mass models of the cortico-basal ganglia thalamic circuit inverted upon spectral features from experimental, in vivo recordings. This optimization scheme relaxes an assumption of fixed-form posteriors (i.e. the Laplace approximation) taken in previous approaches to inverse modelling of spectral features. This enables the exploration of model dynamics beyond that approximated from local linearity assumptions and so fit to explicit, numerical solutions of the underlying non-linear system of equations. In this first paper, we establish a face validation of the optimization procedures in terms of: (i) the ability to approximate posterior densities over parameters that are plausible given the known causes of the data; (ii) the ability of the model comparison procedures to yield posterior model probabilities that can identify the model structure known to generate the data; and (iii) the robustness of these procedures to local minima in the face of different starting conditions. Finally, as an illustrative application we show (iv) that model comparison can yield plausible conclusions given the known neurobiology of the cortico-basal ganglia-thalamic circuit in Parkinsonism. These results lay the groundwork for future studies utilizing highly nonlinear or brittle models that can explain time dependant dynamics, such as oscillatory bursts, in terms of the underlying neural circuits.
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Affiliation(s)
- Timothy O West
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom.
| | - Luc Berthouze
- Centre for Computational Neuroscience and Robotics, University of Sussex, Falmer, United Kingdom; UCL Great Ormond Street Institute of Child Health, Guildford St., London WC1N 1EH, United Kingdom
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery, Queen Square, London WC1N 3BG, United Kingdom; Department of Clinical and Movement Neurosciences, Institute of Neurology, Queen Square, UCL, London WC1N 3BG, United Kingdom
| | - Hayriye Cagnan
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
| | - Vladimir Litvak
- Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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48
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Moeller M, Grohn J, Manohar S, Bogacz R. An association between prediction errors and risk-seeking: Theory and behavioral evidence. PLoS Comput Biol 2021; 17:e1009213. [PMID: 34270552 PMCID: PMC8318232 DOI: 10.1371/journal.pcbi.1009213] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 07/28/2021] [Accepted: 06/23/2021] [Indexed: 11/19/2022] Open
Abstract
Reward prediction errors (RPEs) and risk preferences have two things in common: both can shape decision making behavior, and both are commonly associated with dopamine. RPEs drive value learning and are thought to be represented in the phasic release of striatal dopamine. Risk preferences bias choices towards or away from uncertainty; they can be manipulated with drugs that target the dopaminergic system. Based on the common neural substrate, we hypothesize that RPEs and risk preferences are linked on the level of behavior as well. Here, we develop this hypothesis theoretically and test it empirically. First, we apply a recent theory of learning in the basal ganglia to predict how RPEs influence risk preferences. We find that positive RPEs should cause increased risk-seeking, while negative RPEs should cause risk-aversion. We then test our behavioral predictions using a novel bandit task in which value and risk vary independently across options. Critically, conditions are included where options vary in risk but are matched for value. We find that our prediction was correct: participants become more risk-seeking if choices are preceded by positive RPEs, and more risk-averse if choices are preceded by negative RPEs. These findings cannot be explained by other known effects, such as nonlinear utility curves or dynamic learning rates.
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Affiliation(s)
- Moritz Moeller
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jan Grohn
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Sanjay Manohar
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Rafal Bogacz
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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49
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Benavidez NL, Bienkowski MS, Zhu M, Garcia LH, Fayzullina M, Gao L, Bowman I, Gou L, Khanjani N, Cotter KR, Korobkova L, Becerra M, Cao C, Song MY, Zhang B, Yamashita S, Tugangui AJ, Zingg B, Rose K, Lo D, Foster NN, Boesen T, Mun HS, Aquino S, Wickersham IR, Ascoli GA, Hintiryan H, Dong HW. Organization of the inputs and outputs of the mouse superior colliculus. Nat Commun 2021; 12:4004. [PMID: 34183678 PMCID: PMC8239028 DOI: 10.1038/s41467-021-24241-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/02/2021] [Indexed: 11/16/2022] Open
Abstract
The superior colliculus (SC) receives diverse and robust cortical inputs to drive a range of cognitive and sensorimotor behaviors. However, it remains unclear how descending cortical input arising from higher-order associative areas coordinate with SC sensorimotor networks to influence its outputs. Here, we construct a comprehensive map of all cortico-tectal projections and identify four collicular zones with differential cortical inputs: medial (SC.m), centromedial (SC.cm), centrolateral (SC.cl) and lateral (SC.l). Further, we delineate the distinctive brain-wide input/output organization of each collicular zone, assemble multiple parallel cortico-tecto-thalamic subnetworks, and identify the somatotopic map in the SC that displays distinguishable spatial properties from the somatotopic maps in the neocortex and basal ganglia. Finally, we characterize interactions between those cortico-tecto-thalamic and cortico-basal ganglia-thalamic subnetworks. This study provides a structural basis for understanding how SC is involved in integrating different sensory modalities, translating sensory information to motor command, and coordinating different actions in goal-directed behaviors.
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Affiliation(s)
- Nora L Benavidez
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael S Bienkowski
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Muye Zhu
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Luis H Garcia
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Marina Fayzullina
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Lei Gao
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ian Bowman
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Lin Gou
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Neda Khanjani
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kaelan R Cotter
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Laura Korobkova
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Marlene Becerra
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chunru Cao
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Monica Y Song
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Bin Zhang
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Seita Yamashita
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Amanda J Tugangui
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Brian Zingg
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kasey Rose
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
| | - Darrick Lo
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Nicholas N Foster
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Tyler Boesen
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Hyun-Seung Mun
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Sarvia Aquino
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ian R Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Giorgio A Ascoli
- Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Houri Hintiryan
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Hong-Wei Dong
- Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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50
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Moorman S, Ahn JR, Kao MH. Plasticity of stereotyped birdsong driven by chronic manipulation of cortical-basal ganglia activity. Curr Biol 2021; 31:2619-2632.e4. [PMID: 33974850 PMCID: PMC8222193 DOI: 10.1016/j.cub.2021.04.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 03/05/2021] [Accepted: 04/13/2021] [Indexed: 10/21/2022]
Abstract
Cortical-basal ganglia (CBG) circuits are critical for motor learning and performance, and are a major site of pathology. In songbirds, a CBG circuit regulates moment-by-moment variability in song and also enables song plasticity. Studies have shown that variable burst firing in LMAN, the output nucleus of this CBG circuit, actively drives acute song variability, but whether and how LMAN drives long-lasting changes in song remains unclear. Here, we ask whether chronic pharmacological augmentation of LMAN bursting is sufficient to drive plasticity in birds singing stereotyped songs. We show that altered LMAN activity drives cumulative changes in acoustic structure, timing, and sequencing over multiple days, and induces repetitions and silent pauses reminiscent of human stuttering. Changes persisted when LMAN was subsequently inactivated, indicating plasticity in song motor regions. Following cessation of pharmacological treatment, acoustic features and song sequence gradually recovered to their baseline values over a period of days to weeks. Together, our findings show that augmented bursting in CBG circuitry drives plasticity in well-learned motor skills, and may inform treatments for basal ganglia movement disorders.
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Affiliation(s)
- Sanne Moorman
- Psychology Department, Utrecht University, Yalelaan 2, 3584 CM Utrecht, the Netherlands; Biology Department, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA.
| | - Jae-Rong Ahn
- Biology Department, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA
| | - Mimi H Kao
- Biology Department, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA; Neuroscience Graduate Program, Tufts University, Boston, MA 02111, USA.
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