1
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Bastos-Gonçalves R, Coimbra B, Rodrigues AJ. The mesopontine tegmentum in reward and aversion: From cellular heterogeneity to behaviour. Neurosci Biobehav Rev 2024; 162:105702. [PMID: 38718986 DOI: 10.1016/j.neubiorev.2024.105702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 04/06/2024] [Accepted: 05/01/2024] [Indexed: 05/18/2024]
Abstract
The mesopontine tegmentum, comprising the pedunculopontine tegmentum (PPN) and the laterodorsal tegmentum (LDT), is intricately connected to various regions of the basal ganglia, motor systems, and limbic systems. The PPN and LDT can regulate the activity of different brain regions of these target systems, and in this way are in a privileged position to modulate motivated behaviours. Despite recent findings, the PPN and LDT have been largely overlooked in discussions about the neural circuits associated with reward and aversion. This review aims to provide a timely and comprehensive resource on past and current research, highlighting the PPN and LDT's connectivity and influence on basal ganglia and limbic, and motor systems. Seminal studies, including lesion, pharmacological, and optogenetic/chemogenetic approaches, demonstrate their critical roles in modulating reward/aversive behaviours. The review emphasizes the need for further investigation into the associated cellular mechanisms, in order to clarify their role in behaviour and contribution for different neuropsychiatric disorders.
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Affiliation(s)
- Ricardo Bastos-Gonçalves
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Bárbara Coimbra
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.
| | - Ana João Rodrigues
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.
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2
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Rodriguez AC, Perich MG, Miller L, Humphries MD. Motor cortex latent dynamics encode spatial and temporal arm movement parameters independently. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.26.542452. [PMID: 37292834 PMCID: PMC10246015 DOI: 10.1101/2023.05.26.542452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The fluid movement of an arm requires multiple spatiotemporal parameters to be set independently. Recent studies have argued that arm movements are generated by the collective dynamics of neurons in motor cortex. An untested prediction of this hypothesis is that independent parameters of movement must map to independent components of the neural dynamics. Using a task where monkeys made a sequence of reaching movements to randomly placed targets, we show that the spatial and temporal parameters of arm movements are independently encoded in the low-dimensional trajectories of population activity in motor cortex: Each movement's direction corresponds to a fixed neural trajectory through neural state space and its speed to how quickly that trajectory is traversed. Recurrent neural network models show this coding allows independent control over the spatial and temporal parameters of movement by separate network parameters. Our results support a key prediction of the dynamical systems view of motor cortex, but also argue that not all parameters of movement are defined by different trajectories of population activity.
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Affiliation(s)
| | - Matthew G. Perich
- Département de neurosciences, Faculté de médecine, Université de Montréal, Montréal, Canada
- Québec Artificial Intelligence Institute (Mila), Québec, Canada
| | - Lee Miller
- Northwestern University, Department of Biomedical Engineering, Chicago, USA
| | - Mark D. Humphries
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
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3
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La Chioma A, Schneider DM. Auditory neuroscience: Sounds make the face move. Curr Biol 2024; 34:R346-R348. [PMID: 38714161 DOI: 10.1016/j.cub.2024.03.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
Animals including humans often react to sounds by involuntarily moving their face and body. A new study shows that facial movements provide a simple and reliable readout of a mouse's hearing ability that is more sensitive than traditional measurements.
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Affiliation(s)
| | - David M Schneider
- Center for Neural Science, New York University, New York, NY 10003, USA.
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4
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Clayton KK, Stecyk KS, Guo AA, Chambers AR, Chen K, Hancock KE, Polley DB. Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities in mice. Curr Biol 2024; 34:1605-1620.e5. [PMID: 38492568 PMCID: PMC11043000 DOI: 10.1016/j.cub.2024.02.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/02/2024] [Accepted: 02/23/2024] [Indexed: 03/18/2024]
Abstract
Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicited rapid and stereotyped facial twitches. Facial motion energy (FME) adjacent to the whisker array was 30 dB more sensitive than the acoustic startle reflex and offered greater inter-trial and inter-animal reliability than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of broadband sounds, providing a means to study behavioral discrimination of complex auditory stimuli, such as speech phonemes in noise. Approximately 25% of layer 5-6 units in the auditory cortex (ACtx) exhibited firing rate changes during facial movements. However, FME facilitation during ACtx photoinhibition indicated that sound-evoked facial movements were mediated by a midbrain pathway and modulated by descending corticofugal input. FME and auditory brainstem response (ABR) thresholds were closely aligned after noise-induced sensorineural hearing loss, yet FME growth slopes were disproportionately steep at spared frequencies, reflecting a central plasticity that matched commensurate changes in ABR wave 4. Sound-evoked facial movements were also hypersensitive in Ptchd1 knockout mice, highlighting the use of FME for identifying sensory hyper-reactivity phenotypes after adult-onset hyperacusis and inherited deficiencies in autism risk genes. These findings present a sensitive and integrative measure of hearing while also highlighting that even low-intensity broadband sounds can elicit a complex mixture of auditory, motor, and reafferent somatosensory neural activity.
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Affiliation(s)
- Kameron K Clayton
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02114, USA.
| | - Kamryn S Stecyk
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA
| | - Anna A Guo
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA
| | - Anna R Chambers
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02114, USA
| | - Ke Chen
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02114, USA
| | - Kenneth E Hancock
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02114, USA
| | - Daniel B Polley
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear, Boston, MA 02114, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02114, USA
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5
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Han J, Choi J, Jeong H, Park D, Cheong E, Sung J, Choi HJ. Impact of Impedance Levels on Recording Quality in Flexible Neural Probes. SENSORS (BASEL, SWITZERLAND) 2024; 24:2300. [PMID: 38610511 PMCID: PMC11014004 DOI: 10.3390/s24072300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/14/2024]
Abstract
Flexible neural probes are attractive emerging technologies for brain recording because they can effectively record signals with minimal risk of brain damage. Reducing the electrode impedance of the probe before recording is a common practice of many researchers. However, studies investigating the impact of low impedance levels on high-quality recordings using flexible neural probes are lacking. In this study, we electrodeposited Pt onto a commercial flexible polyimide neural probe and investigated the relationship between the impedance level and the recording quality. The probe was inserted into the brains of anesthetized mice. The electrical signals of neurons in the brain, specifically the ventral posteromedial nucleus of the thalamus, were recorded at impedance levels of 50, 250, 500 and 1000 kΩ at 1 kHz. The study results demonstrated that as the impedance decreased, the quality of the signal recordings did not consistently improve. This suggests that extreme lowering of the impedance may not always be advantageous in the context of flexible neural probes.
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Affiliation(s)
- Juyeon Han
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea; (J.H.)
| | - Jungsik Choi
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea; (J.H.)
- Nformare Inc., Seodamun-gu, Seoul 03722, Republic of Korea
| | - Hyeonyeong Jeong
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Daerl Park
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea; (J.H.)
| | - Eunji Cheong
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Jaesuk Sung
- Nformare Inc., Seodamun-gu, Seoul 03722, Republic of Korea
| | - Heon-Jin Choi
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea; (J.H.)
- Nformare Inc., Seodamun-gu, Seoul 03722, Republic of Korea
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6
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Pereira-Obilinovic U, Hou H, Svoboda K, Wang XJ. Brain mechanism of foraging: Reward-dependent synaptic plasticity versus neural integration of values. Proc Natl Acad Sci U S A 2024; 121:e2318521121. [PMID: 38551832 PMCID: PMC10998608 DOI: 10.1073/pnas.2318521121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/16/2024] [Indexed: 04/02/2024] Open
Abstract
During foraging behavior, action values are persistently encoded in neural activity and updated depending on the history of choice outcomes. What is the neural mechanism for action value maintenance and updating? Here, we explore two contrasting network models: synaptic learning of action value versus neural integration. We show that both models can reproduce extant experimental data, but they yield distinct predictions about the underlying biological neural circuits. In particular, the neural integrator model but not the synaptic model requires that reward signals are mediated by neural pools selective for action alternatives and their projections are aligned with linear attractor axes in the valuation system. We demonstrate experimentally observable neural dynamical signatures and feasible perturbations to differentiate the two contrasting scenarios, suggesting that the synaptic model is a more robust candidate mechanism. Overall, this work provides a modeling framework to guide future experimental research on probabilistic foraging.
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Affiliation(s)
- Ulises Pereira-Obilinovic
- Center for Neural Science, New York University, New York, NY10003
- Allen Institute for Neural Dynamics, Seattle, WA98109
| | - Han Hou
- Allen Institute for Neural Dynamics, Seattle, WA98109
| | - Karel Svoboda
- Allen Institute for Neural Dynamics, Seattle, WA98109
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY10003
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7
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Kersten Y, Moll FW, Erdle S, Nieder A. Input and Output Connections of the Crow Nidopallium Caudolaterale. eNeuro 2024; 11:ENEURO.0098-24.2024. [PMID: 38684368 PMCID: PMC11064124 DOI: 10.1523/eneuro.0098-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 03/14/2024] [Indexed: 05/02/2024] Open
Abstract
The avian telencephalic structure nidopallium caudolaterale (NCL) functions as an analog to the mammalian prefrontal cortex. In crows, corvid songbirds, it plays a crucial role in higher cognitive and executive functions. These functions rely on the NCL's extensive telencephalic connections. However, systematic investigations into the brain-wide connectivity of the NCL in crows or other songbirds are lacking. Here, we studied its input and output connections by injecting retrograde and anterograde tracers into the carrion crow NCL. Our results, mapped onto a published carrion crow brain atlas, confirm NCL multisensory connections and extend prior pigeon findings by identifying a novel input from the hippocampal formation. Furthermore, we analyze crow NCL efferent projections to the arcopallium and report newly identified arcopallial neurons projecting bilaterally to the NCL. These findings help to clarify the role of the NCL as central executive hub in the corvid songbird brain.
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Affiliation(s)
- Ylva Kersten
- Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Tübingen 72076, Germany
| | - Felix W Moll
- Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Tübingen 72076, Germany
| | - Saskia Erdle
- Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Tübingen 72076, Germany
| | - Andreas Nieder
- Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Tübingen 72076, Germany
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8
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Churchland MM, Shenoy KV. Preparatory activity and the expansive null-space. Nat Rev Neurosci 2024; 25:213-236. [PMID: 38443626 DOI: 10.1038/s41583-024-00796-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/26/2024] [Indexed: 03/07/2024]
Abstract
The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.
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Affiliation(s)
- Mark M Churchland
- Department of Neuroscience, Columbia University, New York, NY, USA.
- Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA.
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
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9
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Chae S, Sohn JW, Kim SP. Differential Formation of Motor Cortical Dynamics during Movement Preparation According to the Predictability of Go Timing. J Neurosci 2024; 44:e1353232024. [PMID: 38233217 PMCID: PMC10883619 DOI: 10.1523/jneurosci.1353-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 12/10/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024] Open
Abstract
The motor cortex not only executes but also prepares movement, as motor cortical neurons exhibit preparatory activity that predicts upcoming movements. In movement preparation, animals adopt different strategies in response to uncertainties existing in nature such as the unknown timing of when a predator will attack-an environmental cue informing "go." However, how motor cortical neurons cope with such uncertainties is less understood. In this study, we aim to investigate whether and how preparatory activity is altered depending on the predictability of "go" timing. We analyze firing activities of the anterior lateral motor cortex in male mice during two auditory delayed-response tasks each with predictable or unpredictable go timing. When go timing is unpredictable, preparatory activities immediately reach and stay in a neural state capable of producing movement anytime to a sudden go cue. When go timing is predictable, preparation activity reaches the movement-producible state more gradually, to secure more accurate decisions. Surprisingly, this preparation process entails a longer reaction time. We find that as preparatory activity increases in accuracy, it takes longer for a neural state to transition from the end of preparation to the start of movement. Our results suggest that the motor cortex fine-tunes preparatory activity for more accurate movement using the predictability of go timing.
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Affiliation(s)
- Soyoung Chae
- Ulsan National Institute of Science and Technology, Ulsan 44929, South Korea
| | - Jeong-Woo Sohn
- Catholic Kwandong University, Gangwon-do 25601, South Korea
| | - Sung-Phil Kim
- Ulsan National Institute of Science and Technology, Ulsan 44929, South Korea
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10
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Zimnik AJ, Cora Ames K, An X, Driscoll L, Lara AH, Russo AA, Susoy V, Cunningham JP, Paninski L, Churchland MM, Glaser JI. Identifying Interpretable Latent Factors with Sparse Component Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.05.578988. [PMID: 38370650 PMCID: PMC10871230 DOI: 10.1101/2024.02.05.578988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
In many neural populations, the computationally relevant signals are posited to be a set of 'latent factors' - signals shared across many individual neurons. Understanding the relationship between neural activity and behavior requires the identification of factors that reflect distinct computational roles. Methods for identifying such factors typically require supervision, which can be suboptimal if one is unsure how (or whether) factors can be grouped into distinct, meaningful sets. Here, we introduce Sparse Component Analysis (SCA), an unsupervised method that identifies interpretable latent factors. SCA seeks factors that are sparse in time and occupy orthogonal dimensions. With these simple constraints, SCA facilitates surprisingly clear parcellations of neural activity across a range of behaviors. We applied SCA to motor cortex activity from reaching and cycling monkeys, single-trial imaging data from C. elegans, and activity from a multitask artificial network. SCA consistently identified sets of factors that were useful in describing network computations.
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Affiliation(s)
- Andrew J Zimnik
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
| | - K Cora Ames
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
| | - Xinyue An
- Department of Neurology, Northwestern University, Chicago, IL, USA
- Interdepartmental Neuroscience Program, Northwestern University, Chicago, IL, USA
| | - Laura Driscoll
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Allen Institute for Neural Dynamics, Allen Institute, Seattle, CA, USA
| | - Antonio H Lara
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
| | - Abigail A Russo
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
| | - Vladislav Susoy
- Department of Physics, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - John P Cunningham
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
| | - Liam Paninski
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
| | - Mark M Churchland
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University, New York, NY, USA
- Kavli Institute for Brain Science, Columbia University Medical Center, New York, NY, USA
| | - Joshua I Glaser
- Department of Neurology, Northwestern University, Chicago, IL, USA
- Department of Computer Science, Northwestern University, Evanston, IL, USA
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11
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Chen S, Liu Y, Wang ZA, Colonell J, Liu LD, Hou H, Tien NW, Wang T, Harris T, Druckmann S, Li N, Svoboda K. Brain-wide neural activity underlying memory-guided movement. Cell 2024; 187:676-691.e16. [PMID: 38306983 DOI: 10.1016/j.cell.2023.12.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/19/2023] [Accepted: 12/27/2023] [Indexed: 02/04/2024]
Abstract
Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.
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Affiliation(s)
- Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yi Liu
- Stanford University, Palo Alto, CA, USA
| | | | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Liu D Liu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA
| | - Han Hou
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Nai-Wen Tien
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tim Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Timothy Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Johns Hopkins University, Baltimore, MD, USA
| | - Shaul Druckmann
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Stanford University, Palo Alto, CA, USA.
| | - Nuo Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA.
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA.
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12
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Criado-Marrero M, Ravi S, Bhaskar E, Barroso D, Pizzi MA, Williams L, Wellington CL, Febo M, Abisambra JF. Age dictates brain functional connectivity and axonal integrity following repetitive mild traumatic brain injuries. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.25.577316. [PMID: 38328104 PMCID: PMC10849649 DOI: 10.1101/2024.01.25.577316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Traumatic brain injuries (TBI) present a major public health challenge, demanding an in-depth understanding of age-specific signs and vulnerabilities. Aging not only significantly influences brain function and plasticity but also elevates the risk of hospitalizations and death following repetitive mild traumatic brain injuries (rmTBIs). In this study, we investigate the impact of age on brain network changes and white matter properties following rmTBI employing a multi-modal approach that integrates resting-state functional magnetic resonance imaging (rsfMRI), graph theory analysis, diffusion tensor imaging (DTI), and Neurite Orientation Dispersion and Density Imaging (NODDI). Utilizing the CHIMERA model, we conducted rmTBIs or sham (control) procedures on young (2.5-3 months old) and aged (22-month-old) male and female mice to model high risk groups. Functional and structural imaging unveiled age-related reductions in communication efficiency between brain regions, while injuries induced opposing effects on the small-world index across age groups, influencing network segregation. Functional connectivity analysis also identified alterations in 79 out of 148 brain regions by age, treatment (sham vs. rmTBI), or their interaction. Injuries exerted pronounced effects on sensory integration areas, including insular and motor cortices. Age-related disruptions in white matter integrity were observed, indicating alterations in various diffusion directions (mean, radial, axial diffusivity, fractional anisotropy) and density neurite properties (dispersion index, intracellular and isotropic volume fraction). Inflammation, assessed through Iba-1 and GFAP markers, correlated with higher dispersion in the optic tract, suggesting a neuroinflammatory response in aged animals. These findings provide a comprehensive understanding of the intricate interplay between age, injuries, and brain connectivity, shedding light on the long-term consequences of rmTBIs.
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13
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Chen C, Liang Y, Xu S, Yi C, Li Y, Chen B, Yang L, Liu Q, Yao D, Li F, Xu P. The dynamic causality brain network reflects whether the working memory is solidified. Cereb Cortex 2024; 34:bhad467. [PMID: 38061696 DOI: 10.1093/cercor/bhad467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/13/2023] [Accepted: 11/15/2023] [Indexed: 01/19/2024] Open
Abstract
Working memory, which is foundational to higher cognitive function, is the "sketchpad of volitional control." Successful working memory is the inevitable outcome of the individual's active control and manipulation of thoughts and turning them into internal goals during which the causal brain processes information in real time. However, little is known about the dynamic causality among distributed brain regions behind thought control that underpins successful working memory. In our present study, given that correct responses and incorrect ones did not differ in either contralateral delay activity or alpha suppression, further rooting on the high-temporal-resolution EEG time-varying directed network analysis, we revealed that successful working memory depended on both much stronger top-down connections from the frontal to the temporal lobe and bottom-up linkages from the occipital to the temporal lobe, during the early maintenance period, as well as top-down flows from the frontal lobe to the central areas as the delay behavior approached. Additionally, the correlation between behavioral performance and casual interactions increased over time, especially as memory-guided delayed behavior approached. Notably, when using the network metrics as features, time-resolved multiple linear regression of overall behavioral accuracy was exactly achieved as delayed behavior approached. These results indicate that accurate memory depends on dynamic switching of causal network connections and shifting to more task-related patterns during which the appropriate intervention may help enhance memory.
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Affiliation(s)
- Chunli Chen
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yi Liang
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China
| | - Shiyun Xu
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chanlin Yi
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yuqin Li
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Baodan Chen
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lei Yang
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qiang Liu
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu 610000, China
| | - Dezhong Yao
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Fali Li
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Peng Xu
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
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14
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Gonzalo-Martín E, Alonso-Martínez C, Sepúlveda LP, Clasca F. Micropopulation mapping of the mouse parafascicular nucleus connections reveals diverse input-output motifs. Front Neuroanat 2024; 17:1305500. [PMID: 38260117 PMCID: PMC10800635 DOI: 10.3389/fnana.2023.1305500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 11/10/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction In primates, including humans, the centromedian/parafascicular (CM-Pf) complex is a key thalamic node of the basal ganglia system. Deep brain stimulation in CM-Pf has been applied for the treatment of motor disorders such as Parkinson's disease or Tourette syndrome. Rodents have become widely used models for the study of the cellular and genetic mechanisms of these and other motor disorders. However, the equivalence between the primate CM-Pf and the nucleus regarded as analogous in rodents (Parafascicular, Pf) remains unclear. Methods Here, we analyzed the neurochemical architecture and carried out a brain-wide mapping of the input-output motifs in the mouse Pf at micropopulation level using anterograde and retrograde labeling methods. Specifically, we mapped and quantified the sources of cortical and subcortical input to different Pf subregions, and mapped and compared the distribution and terminal structure of their axons. Results We found that projections to Pf arise predominantly (>75%) from the cerebral cortex, with an unusually strong (>45%) Layer 5b component, which is, in part, contralateral. The intermediate layers of the superior colliculus are the main subcortical input source to Pf. On its output side, Pf neuron axons predominantly innervate the striatum. In a sparser fashion, they innervate other basal ganglia nuclei, including the subthalamic nucleus (STN), and the cerebral cortex. Differences are evident between the lateral and medial portions of Pf, both in chemoarchitecture and in connectivity. Lateral Pf axons innervate territories of the striatum, STN and cortex involved in the sensorimotor control of different parts of the contralateral hemibody. In contrast, the mediodorsal portion of Pf innervates oculomotor-limbic territories in the above three structures. Discussion Our data thus indicate that the mouse Pf consists of several neurochemically and connectively distinct domains whose global organization bears a marked similarity to that described in the primate CM-Pf complex.
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Affiliation(s)
| | | | | | - Francisco Clasca
- Department of Anatomy and Neuroscience, Autónoma de Madrid University, Madrid, Spain
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15
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Morgenstern NA, Esposito MS. The Basal Ganglia and Mesencephalic Locomotor Region Connectivity Matrix. Curr Neuropharmacol 2024; 22:1454-1472. [PMID: 37559244 PMCID: PMC11097982 DOI: 10.2174/1570159x21666230809112840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/16/2023] [Accepted: 02/23/2023] [Indexed: 08/11/2023] Open
Abstract
Although classically considered a relay station for basal ganglia (BG) output, the anatomy, connectivity, and function of the mesencephalic locomotor region (MLR) were redefined during the last two decades. In striking opposition to what was initially thought, MLR and BG are actually reciprocally and intimately interconnected. New viral-based, optogenetic, and mapping technologies revealed that cholinergic, glutamatergic, and GABAergic neurons coexist in this structure, which, in addition to extending descending projections, send long-range ascending fibers to the BG. These MLR projections to the BG convey motor and non-motor information to specific synaptic targets throughout different nuclei. Moreover, MLR efferent fibers originate from precise neuronal subpopulations located in particular MLR subregions, defining independent anatomo-functional subcircuits involved in particular aspects of animal behavior such as fast locomotion, explorative locomotion, posture, forelimb- related movements, speed, reinforcement, among others. In this review, we revised the literature produced during the last decade linking MLR and BG. We conclude that the classic framework considering the MLR as a homogeneous output structure passively receiving input from the BG needs to be revisited. We propose instead that the multiple subcircuits embedded in this region should be taken as independent entities that convey relevant and specific ascending information to the BG and, thus, actively participate in the execution and tuning of behavior.
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Affiliation(s)
- Nicolás A. Morgenstern
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
- Faculty of Medicine, University of Lisbon, Instituto De Medicina Molecular João Lobo Antunes, Lisbon, Portugal
| | - Maria S. Esposito
- Department of Medical Physics, Centro Atomico Bariloche, CNEA, CONICET, Av. Bustillo 9500, San Carlos de Bariloche, Rio Negro, Argentina
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16
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Lisco G, Giagulli VA, De Pergola G, Guastamacchia E, Jirillo E, Vitale E, Triggiani V. Chronic Stress as a Risk Factor for Type 2 Diabetes: Endocrine, Metabolic, and Immune Implications. Endocr Metab Immune Disord Drug Targets 2024; 24:321-332. [PMID: 37534489 DOI: 10.2174/1871530323666230803095118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/01/2023] [Accepted: 06/20/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND Chronic stress is a condition of pressure on the brain and whole body, which in the long term may lead to a frank disease status, even including type 2 diabetes (T2D). Stress activates the hypothalamus-pituitary-adrenal axis with release of glucocorticoids (GCs) and catecholamines, as well as activation of the inflammatory pathway of the immune system, which alters glucose and lipid metabolism, ultimately leading to beta-cell destruction, insulin resistance and T2D onset. Alteration of the glucose and lipid metabolism accounts for insulin resistance and T2D outcome. Furthermore, stress-related subversion of the intestinal microbiota leads to an imbalance of the gut-brain-immune axis, as evidenced by the stress-related depression often associated with T2D. A condition of generalized inflammation and subversion of the intestinal microbiota represents another facet of stress-induced disease. In fact, chronic stress acts on the gut-brain axis with multiorgan consequences, as evidenced by the association between depression and T2D. Oxidative stress with the production of reactive oxygen species and cytokine-mediated inflammation represents the main hallmarks of chronic stress. ROS production and pro-inflammatory cytokines represent the main hallmarks of stress-related disorders, and therefore, the use of natural antioxidant and anti-inflammatory substances (nutraceuticals) may offer an alternative therapeutic approach to combat stress-related T2D. Single or combined administration of nutraceuticals would be very beneficial in targeting the neuro-endocrine-immune axis, thus, regulating major pathways involved in T2D onset. However, more clinical trials are needed to establish the effectiveness of nutraceutical treatment, dosage, time of administration and the most favorable combinations of compounds. Therefore, in view of their antioxidant and anti-inflammatory properties, the use of natural products or nutraceuticals for the treatment of stress-related diseases, even including T2D, will be discussed. Several evidences suggest that chronic stress represents one of the main factors responsible for the outcome of T2D.
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Affiliation(s)
- Giuseppe Lisco
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
| | - Vito Angelo Giagulli
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
| | - Giovanni De Pergola
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
| | - Edoardo Guastamacchia
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
| | - Emilio Jirillo
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
| | - Elsa Vitale
- Department of Mental Health, University of Bari Aldo Moro, Local Health Authority Bari, Bari, Italy
| | - Vincenzo Triggiani
- Interdisciplinary Department of Medicine, University of Bari, "Aldo Moro", Bari, Italy
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17
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Vincent JP, Economo MN. Assessing cross-contamination in spike-sorted electrophysiology data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572882. [PMID: 38187738 PMCID: PMC10769346 DOI: 10.1101/2023.12.21.572882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Recent advances in extracellular electrophysiology now facilitate the recording of spikes from hundreds or thousands of neurons simultaneously. This has necessitated both the development of new computational methods for spike sorting and better methods to determine spike sorting accuracy. One longstanding method of assessing the false discovery rate (FDR) of spike sorting - the rate at which spikes are misassigned to the wrong cluster - has been the rate of inter-spike-interval (ISI) violations. Despite their near ubiquitous usage in spike sorting, our understanding of how exactly ISI violations relate to FDR, as well as best practices for using ISI violations as a quality metric, remain limited. Here, we describe an analytical solution that can be used to predict FDR from ISI violation rate. We test this model in silico through Monte Carlo simulation, and apply it to publicly available spike-sorted electrophysiology datasets. We find that the relationship between ISI violation rate and FDR is highly nonlinear, with additional dependencies on firing rate, the correlation in activity between neurons, and contaminant neuron count. Predicted median FDRs in public datasets were found to range from 3.1% to 50.0%. We find that stochasticity in the occurrence of ISI violations as well as uncertainty in cluster-specific parameters make it difficult to predict FDR for single clusters with high confidence, but that FDR can be estimated accurately across a population of clusters. Our findings will help the growing community of researchers using extracellular electrophysiology assess spike sorting accuracy in a principled manner.
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Affiliation(s)
- Jack P. Vincent
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
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18
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Do J, Jung MW, Lee D. Automating licking bias correction in a two-choice delayed match-to-sample task to accelerate learning. Sci Rep 2023; 13:22768. [PMID: 38123637 PMCID: PMC10733387 DOI: 10.1038/s41598-023-49862-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 12/12/2023] [Indexed: 12/23/2023] Open
Abstract
Animals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse's biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse's mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse's side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.
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Affiliation(s)
- Jongrok Do
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Min Whan Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea.
| | - Doyun Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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19
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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] [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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20
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Suzuki M, Pennartz CMA, Aru J. How deep is the brain? The shallow brain hypothesis. Nat Rev Neurosci 2023; 24:778-791. [PMID: 37891398 DOI: 10.1038/s41583-023-00756-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/25/2023] [Indexed: 10/29/2023]
Abstract
Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.
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Affiliation(s)
- Mototaka Suzuki
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
| | - Cyriel M A Pennartz
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
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21
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Guzulaitis R, Palmer LM. A thalamocortical pathway controlling impulsive behavior. Trends Neurosci 2023; 46:1018-1024. [PMID: 37778915 DOI: 10.1016/j.tins.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/14/2023] [Accepted: 09/08/2023] [Indexed: 10/03/2023]
Abstract
Planning and anticipating motor actions enables movements to be quickly and accurately executed. However, if anticipation is not properly controlled, it can lead to premature impulsive actions. Impulsive behavior is defined as actions that are poorly conceived and are often risky and inappropriate. Historically, impulsive behavior was thought to be primarily controlled by the frontal cortex and basal ganglia. More recently, two additional brain regions, the ventromedial (VM) thalamus and the anterior lateral motor cortex (ALM), have been shown to have an important role in mice. Here, we explore this newly discovered role of the thalamocortical pathway and suggest cellular mechanisms that may be involved in driving the cortical activity that contributes to impulsive behavior.
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Affiliation(s)
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3010, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC 3010, Australia.
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22
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Thomas A, Yang W, Wang C, Tipparaju SL, Chen G, Sullivan B, Swiekatowski K, Tatam M, Gerfen C, Li N. Superior colliculus bidirectionally modulates choice activity in frontal cortex. Nat Commun 2023; 14:7358. [PMID: 37963894 PMCID: PMC10645979 DOI: 10.1038/s41467-023-43252-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 11/03/2023] [Indexed: 11/16/2023] Open
Abstract
Action selection occurs through competition between potential choice options. Neural correlates of choice competition are observed across frontal cortex and downstream superior colliculus (SC) during decision-making, yet how these regions interact to mediate choice competition remains unresolved. Here we report that SC can bidirectionally modulate choice competition and drive choice activity in frontal cortex. In the mouse, topographically matched regions of frontal cortex and SC formed a descending motor pathway for directional licking and a re-entrant loop via the thalamus. During decision-making, distinct neuronal populations in both frontal cortex and SC encoded opposing lick directions and exhibited competitive interactions. SC GABAergic neurons encoded ipsilateral choice and locally inhibited glutamatergic neurons that encoded contralateral choice. Activating or suppressing these cell types could bidirectionally drive choice activity in frontal cortex. These results thus identify SC as a major locus to modulate choice competition within the broader action selection network.
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Affiliation(s)
- Alyse Thomas
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Weiguo Yang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Catherine Wang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | | | - Guang Chen
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Brennan Sullivan
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Kylie Swiekatowski
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Mahima Tatam
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Charles Gerfen
- Section on Neuroanatomy, National Institute of Mental Health, Bethesda, MD, USA
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
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23
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Mountoufaris G, Nair A, Yang B, Kim DW, Anderson DJ. Neuropeptide Signaling is Required to Implement a Line Attractor Encoding a Persistent Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.01.565073. [PMID: 37961374 PMCID: PMC10635056 DOI: 10.1101/2023.11.01.565073] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1 + neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.
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24
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Maristany de Las Casas E, Takahashi N. Synaptic crossroads: navigating the circuits of movement. Trends Neurosci 2023; 46:895-897. [PMID: 37690954 PMCID: PMC10591950 DOI: 10.1016/j.tins.2023.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/17/2023] [Indexed: 09/12/2023]
Abstract
The anterior lateral motor area (ALM) is crucial in preparing and executing voluntary movements through its diverse neuronal subpopulations that target different subcortical areas. A recent study by Xu et al. utilized an elaborate viral tracing strategy in mice to provide comprehensive whole-brain maps of monosynaptic inputs to the major descending pathways of ALM.
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Affiliation(s)
| | - Naoya Takahashi
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, 33000 Bordeaux, France.
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25
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Zhu J, Hasanbegović H, Liu LD, Gao Z, Li N. Activity map of a cortico-cerebellar loop underlying motor planning. Nat Neurosci 2023; 26:1916-1928. [PMID: 37814026 PMCID: PMC10620095 DOI: 10.1038/s41593-023-01453-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 09/06/2023] [Indexed: 10/11/2023]
Abstract
The neocortex and cerebellum interact to mediate cognitive functions. It remains unknown how the two structures organize into functional networks to mediate specific behaviors. Here we delineate activity supporting motor planning in relation to the mesoscale cortico-cerebellar connectome. In mice planning directional licking based on short-term memory, preparatory activity instructing future movement depends on the anterior lateral motor cortex (ALM) and the cerebellum. Transneuronal tracing revealed divergent and largely open-loop connectivity between the ALM and distributed regions of the cerebellum. A cerebellum-wide survey of neuronal activity revealed enriched preparatory activity in hotspot regions with conjunctive input-output connectivity to the ALM. Perturbation experiments show that the conjunction regions were required for maintaining preparatory activity and correct subsequent movement. Other cerebellar regions contributed little to motor planning despite input or output connectivity to the ALM. These results identify a functional cortico-cerebellar loop and suggest the cerebellar cortex selectively establishes reciprocal cortico-cerebellar communications to orchestrate motor planning.
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Affiliation(s)
- Jia Zhu
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | | | - Liu D Liu
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Zhenyu Gao
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands.
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
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26
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Windolf C, Yu H, Paulk AC, Meszéna D, Muñoz W, Boussard J, Hardstone R, Caprara I, Jamali M, Kfir Y, Xu D, Chung JE, Sellers KK, Ye Z, Shaker J, Lebedeva A, Raghavan M, Trautmann E, Melin M, Couto J, Garcia S, Coughlin B, Horváth C, Fiáth R, Ulbert I, Movshon JA, Shadlen MN, Churchland MM, Churchland AK, Steinmetz NA, Chang EF, Schweitzer JS, Williams ZM, Cash SS, Paninski L, Varol E. DREDge: robust motion correction for high-density extracellular recordings across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.24.563768. [PMID: 37961359 PMCID: PMC10634799 DOI: 10.1101/2023.10.24.563768] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.
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Affiliation(s)
- Charlie Windolf
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Han Yu
- Zuckerman Institute, Columbia University
- Department of Electrical Engineering, Columbia University
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Domokos Meszéna
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - William Muñoz
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Julien Boussard
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Richard Hardstone
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Irene Caprara
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Mohsen Jamali
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Yoav Kfir
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Duo Xu
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jason E Chung
- Department of Neurological Surgery, University of California San Francisco
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Zhiwen Ye
- Department of Biological Structure, University of Washington
| | - Jordan Shaker
- Department of Biological Structure, University of Washington
| | | | | | - Eric Trautmann
- Department of Neuroscience, Columbia University Medical Center
- Zuckerman Institute, Columbia University
- Grossman Center for the Statistics of Mind, Columbia University
| | - Max Melin
- David Geffen School of Medicine, University of California Los Angeles
| | - João Couto
- David Geffen School of Medicine, University of California Los Angeles
| | - Samuel Garcia
- Centre National de la Recherche Scientifique, Centre de Recherche en Neurosciences de Lyon
| | - Brian Coughlin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Csaba Horváth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | | | - Michael N Shadlen
- Zuckerman Institute, Columbia University
- Howard Hughes Medical Institute
| | | | - Anne K Churchland
- David Geffen School of Medicine, University of California Los Angeles
| | | | - Edward F Chang
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jeffrey S Schweitzer
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Liam Paninski
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Neuroscience, Columbia University Medical Center
- Grossman Center for the Statistics of Mind, Columbia University
| | - Erdem Varol
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Computer Science & Engineering, New York University
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Verhein JR, Vyas S, Shenoy KV. Methylphenidate modulates motor cortical dynamics and behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.15.562405. [PMID: 37905157 PMCID: PMC10614820 DOI: 10.1101/2023.10.15.562405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Methylphenidate (MPH, brand: Ritalin) is a common stimulant used both medically and non-medically. Though typically prescribed for its cognitive effects, MPH also affects movement. While it is known that MPH noncompetitively blocks the reuptake of catecholamines through inhibition of dopamine and norepinephrine transporters, a critical step in exploring how it affects behavior is to understand how MPH directly affects neural activity. This would establish an electrophysiological mechanism of action for MPH. Since we now have biologically-grounded network-level hypotheses regarding how populations of motor cortical neurons plan and execute movements, there is a unique opportunity to make testable predictions regarding how systemic MPH administration - a pharmacological perturbation - might affect neural activity in motor cortex. To that end, we administered clinically-relevant doses of MPH to Rhesus monkeys as they performed an instructed-delay reaching task. Concomitantly, we measured neural activity from dorsal premotor and primary motor cortex. Consistent with our predictions, we found dose-dependent and significant effects on reaction time, trial-by-trial variability, and movement speed. We confirmed our hypotheses that changes in reaction time and variability were accompanied by previously established population-level changes in motor cortical preparatory activity and the condition-independent signal that precedes movements. We expected changes in speed to be a result of changes in the amplitude of motor cortical dynamics and/or a translation of those dynamics in activity space. Instead, our data are consistent with a mechanism whereby the neuromodulatory effect of MPH is to increase the gain and/or the signal-to-noise of motor cortical dynamics during reaching. Continued work in this domain to better understand the brain-wide electrophysiological mechanism of action of MPH and other psychoactive drugs could facilitate more targeted treatments for a host of cognitive-motor disorders.
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Affiliation(s)
- Jessica R Verhein
- Medical Scientist Training Program, Stanford School of Medicine, Stanford University, Stanford, CA
- Neurosciences Graduate Program, Stanford School of Medicine, Stanford University, Stanford, CA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA
- Current affiliations: Psychiatry Research Residency Training Program, University of California, San Francisco, San Francisco, CA
| | - Saurabh Vyas
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
| | - Krishna V Shenoy
- Neurosciences Graduate Program, Stanford School of Medicine, Stanford University, Stanford, CA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
- Department of Electrical Engineering, Stanford University, Stanford, CA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA
- Department of Neurobiology, Stanford University, Stanford, CA
- Bio-X Program, Stanford University, Stanford, CA
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28
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Das A, Holden S, Borovicka J, Icardi J, O'Niel A, Chaklai A, Patel D, Patel R, Kaech Petrie S, Raber J, Dana H. Large-scale recording of neuronal activity in freely-moving mice at cellular resolution. Nat Commun 2023; 14:6399. [PMID: 37828016 PMCID: PMC10570384 DOI: 10.1038/s41467-023-42083-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 09/28/2023] [Indexed: 10/14/2023] Open
Abstract
Current methods for recording large-scale neuronal activity from behaving mice at single-cell resolution require either fixing the mouse head under a microscope or attachment of a recording device to the animal's skull. Both of these options significantly affect the animal behavior and hence also the recorded brain activity patterns. Here, we introduce a different method to acquire snapshots of single-cell cortical activity maps from freely-moving mice using a calcium sensor called CaMPARI. CaMPARI has a unique property of irreversibly changing its color from green to red inside active neurons when illuminated with 400 nm light. We capitalize on this property to demonstrate cortex-wide activity recording without any head fixation, tethering, or attachment of a miniaturized device to the mouse's head. Multiple cortical regions were recorded while the mouse was performing a battery of behavioral and cognitive tests. We identified task-dependent activity patterns across motor and somatosensory cortices, with significant differences across sub-regions of the motor cortex and correlations across several activity patterns and task parameters. This CaMPARI-based recording method expands the capabilities of recording neuronal activity from freely-moving and behaving mice under minimally-restrictive experimental conditions and provides large-scale volumetric data that are currently not accessible otherwise.
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Affiliation(s)
- Aniruddha Das
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Sarah Holden
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Julie Borovicka
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Jacob Icardi
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Abigail O'Niel
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Ariel Chaklai
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Davina Patel
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Rushik Patel
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | | | - Jacob Raber
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
- Departments of Neurology and Radiation Medicine, Division of Neuroscience, ONPRC, Oregon Health and Science University, Portland, OR, USA
| | - Hod Dana
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
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29
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Feitosa JA, Casseb RF, Camargo A, Brandao AF, Li LM, Castellano G. Graph analysis of cortical reorganization after virtual reality-based rehabilitation following stroke: a pilot randomized study. Front Neurol 2023; 14:1241639. [PMID: 37869147 PMCID: PMC10587561 DOI: 10.3389/fneur.2023.1241639] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 09/22/2023] [Indexed: 10/24/2023] Open
Abstract
Introduction Stroke is the leading cause of functional disability worldwide. With the increase of the global population, motor rehabilitation of stroke survivors is of ever-increasing importance. In the last decade, virtual reality (VR) technologies for rehabilitation have been extensively studied, to be used instead of or together with conventional treatments such as physiotherapy or occupational therapy. The aim of this work was to evaluate the GestureCollection VR-based rehabilitation tool in terms of the brain changes and clinical outcomes of the patients. Methods Two groups of chronic patients underwent a rehabilitation treatment with (experimental) or without (control) complementation with GestureCollection. Functional magnetic resonance imaging exams and clinical assessments were performed before and after the treatment. A functional connectivity graph-based analysis was used to assess differences between the connections and in the network parameters strength and clustering coefficient. Results Patients in both groups showed improvement in clinical scales, but there were more increases in functional connectivity in the experimental group than in the control group. Discussion The experimental group presented changes in the connections between the frontoparietal and the somatomotor networks, associative cerebellum and basal ganglia, which are regions associated with reward-based motor learning. On the other hand, the control group also had results in the somatomotor network, in its ipsilateral connections with the thalamus and with the motor cerebellum, which are regions more related to a purely mechanical activity. Thus, the use of the GestureCollection system was successfully shown to promote neuroplasticity in several motor-related areas.
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Affiliation(s)
- Jamille Almeida Feitosa
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
| | - Raphael Fernandes Casseb
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Alline Camargo
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Alexandre Fonseca Brandao
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
| | - Li Min Li
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Gabriela Castellano
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
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30
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Cui F, Zhao L, Lu M, Liu R, Lv Q, Lin D, Li K, Zhang Y, Wang Y, Wang Y, Wang L, Tan Z, Tu Y, Zou Y. Functional and structural brain reorganization in patients with ischemic stroke: a multimodality MRI fusion study. Cereb Cortex 2023; 33:10453-10462. [PMID: 37566914 DOI: 10.1093/cercor/bhad295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 08/13/2023] Open
Abstract
Understanding how structural and functional reorganization occurs is crucial for stroke diagnosis and prognosis. Previous magnetic resonance imaging (MRI) studies focused on the analyses of a single modality and demonstrated abnormalities in both lesion regions and their associated distal regions. However, the relationships of multimodality alterations and their associations with poststroke motor deficits are still unclear. In this study, 71 hemiplegia patients and 41 matched healthy controls (HCs) were recruited and underwent MRI examination at baseline and at 2-week follow-up sessions. A multimodal fusion approach (multimodal canonical correlation analysis + joint independent component analysis), with amplitude of low-frequency fluctuation (ALFF) and gray matter volume (GMV) as features, was used to extract the co-altered patterns of brain structure and function. Then compared the changes in patients' brain structure and function between baseline and follow-up sessions. Compared with HCs, the brain structure and function of stroke patients decreased synchronously in the local lesions and their associated distal regions. Damage to structure and function in the local lesion regions was associated with motor function. After 2 weeks, ALFF in the local lesion regions was increased, while GMV did not improve. Taken together, the brain structure and function in the local lesions and their associated distal regions were damaged synchronously after ischemic stroke, while during motor recovery, the 2 modalities were changed separately.
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Affiliation(s)
- Fangyuan Cui
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Lei Zhao
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, No.16 Lincui Road, Chaoyang District, Beijing 100101, China
| | - Mengxin Lu
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
- Department of Traditional Chinese Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 South Gongti Road, Chaoyang District, Beijing 100020, China
| | - Ruoyi Liu
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
- Department of Traditional Chinese Medicine, Cangzhou Central Hospital, No.16 Xinhua West Road, Cangzhou, Hebei 061000, China
| | - Qiuyi Lv
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Dan Lin
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Kuangshi Li
- 5Department of Rehabilitation, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Yong Zhang
- 5Department of Rehabilitation, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Yahui Wang
- Department of Rehabilitation Medicine, Beijing Tsinghua Changgung Hospital, No.168 Litang Road, Changping District, Beijing 102218, China
| | - Yue Wang
- Department of Protology, China-Japan Friendship Hospital, No.2 East Yinghua Road, Chaoyang District, Beijing 100029, China
| | - Liping Wang
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Zhongjian Tan
- Department of Radiology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
| | - Yiheng Tu
- Department of Psychology, University of Chinese Academy of Sciences, No.19 Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Yihuai Zou
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China
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31
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Mangin EN, Chen J, Lin J, Li N. Behavioral measurements of motor readiness in mice. Curr Biol 2023; 33:3610-3624.e4. [PMID: 37582373 PMCID: PMC10529875 DOI: 10.1016/j.cub.2023.07.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 05/09/2023] [Accepted: 07/18/2023] [Indexed: 08/17/2023]
Abstract
Motor planning facilitates rapid and precise execution of volitional movements. Although motor planning has been classically studied in humans and monkeys, the mouse has become an increasingly popular model system to study neural mechanisms of motor planning. It remains yet untested whether mice and primates share common behavioral features of motor planning. We combined videography and a delayed response task paradigm in an autonomous behavioral system to measure motor planning in non-body-restrained mice. Motor planning resulted in both reaction time (RT) savings and increased movement accuracy, replicating classic effects in primates. We found that motor planning was reflected in task-relevant body features. Both the specific actions prepared and the degree of motor readiness could be read out online during motor planning. The online readout further revealed behavioral evidence of simultaneous preparation for multiple actions under uncertain conditions. These results validate the mouse as a model to study motor planning, demonstrate body feature movements as a powerful real-time readout of motor readiness, and offer behavioral evidence that motor planning can be a parallel process that permits rapid selection of multiple prepared actions.
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Affiliation(s)
- Elise N Mangin
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jian Chen
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jing Lin
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA.
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32
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Majumder S, Hirokawa K, Yang Z, Paletzki R, Gerfen CR, Fontolan L, Romani S, Jain A, Yasuda R, Inagaki HK. Cell-type-specific plasticity shapes neocortical dynamics for motor learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.09.552699. [PMID: 37609277 PMCID: PMC10441538 DOI: 10.1101/2023.08.09.552699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.
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Affiliation(s)
- Shouvik Majumder
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Koichi Hirokawa
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Zidan Yang
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ronald Paletzki
- National Institute of Mental Health, Bethesda, MD 20814, USA
| | | | - Lorenzo Fontolan
- Turing Centre for Living Systems, Aix- Marseille University, INSERM, INMED U1249, Marseille, France
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Sandro Romani
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Anant Jain
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ryohei Yasuda
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
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33
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Alonso-Martínez C, Rubio-Teves M, Porrero C, Clascá F. Cerebellar and basal ganglia inputs define three main nuclei in the mouse ventral motor thalamus. Front Neuroanat 2023; 17:1242839. [PMID: 37645018 PMCID: PMC10461449 DOI: 10.3389/fnana.2023.1242839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 07/27/2023] [Indexed: 08/31/2023] Open
Abstract
The thalamus is a central link between cortical and subcortical brain motor systems. Axons from the deep nuclei of the cerebellum (DCN), or the output nuclei of the basal ganglia system (substantia nigra reticulata, SNr; and internal pallidum GPi/ENT) monosynaptically innervate the thalamus, prominently some nuclei of the ventral nuclear group. In turn, axons from these ventral nuclei innervate the motor and premotor areas of the cortex, where their input is critical for planning, execution and learning of rapid and precise movements. Mice have in recent years become a widely used model in motor system research. However, information on the distribution of cerebellar and basal ganglia inputs in the rodent thalamus remains poorly defined. Here, we mapped the distribution of inputs from DCN, SNr, and GPi/ENT to the ventral nuclei of the mouse thalamus. Immunolabeling for glutamatergic and GABAergic neurotransmission markers delineated two distinct main territories, characterized each by the presence of large vesicular glutamate transporter type 2 (vGLUT2) puncta or vesicular GABA transporter (vGAT) puncta. Anterograde labeling of axons from DCN revealed that they reach virtually all parts of the ventral nuclei, albeit its axonal varicosities (putative boutons) in the vGAT-rich sector are consistently smaller than those in the vGLUT2-rich sector. In contrast, the SNr axons innervate the whole vGAT-rich sector, but not the vGLUT2-rich sector. The GPi/ENT axons were found to innervate only a small zone of the vGAT-rich sector which is also targeted by the other two input systems. Because inputs fundamentally define thalamic cell functioning, we propose a new delineation of the mouse ventral motor nuclei that is consistent with the distribution of DCN, SNr and GPi/ENT inputs and resembles the general layout of the ventral motor nuclei in primates.
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Affiliation(s)
| | | | - César Porrero
- Department of Anatomy and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain
| | - Francisco Clascá
- Department of Anatomy and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain
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34
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Noel JP, Bockbrader M, Colachis S, Solca M, Orepic P, Ganzer PD, Haggard P, Rezai A, Blanke O, Serino A. Human primary motor cortex indexes the onset of subjective intention in brain-machine-interface mediated actions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.550067. [PMID: 37547006 PMCID: PMC10401963 DOI: 10.1101/2023.07.21.550067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Self-initiated behavior is accompanied by the experience of willing our actions. Here, we leverage the unique opportunity to examine the full intentional chain - from will (W) to action (A) to environmental effects (E) - in a tetraplegic person fitted with a primary motor cortex (M1) brain machine interface (BMI) generating hand movements via neuromuscular electrical stimulation (NMES). This combined BMI-NMES approach allowed us to selectively manipulate each element of the intentional chain (W, A, and E) while performing extra-cellular recordings and probing subjective experience. Our results reveal single-cell, multi-unit, and population-level dynamics in human M1 that encode W and may predict its subjective onset. Further, we show that the proficiency of a neural decoder in M1 reflects the degree of W-A binding, tracking the participant's subjective experience of intention in (near) real time. These results point to M1 as a critical node in forming the subjective experience of intention and demonstrate the relevance of intention-related signals for translational neuroprosthetics.
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Affiliation(s)
- Jean-Paul Noel
- Center for Neural Science, New York University, New York City, New York, U.S.A
| | - Marcia Bockbrader
- Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, Ohio, U.S.A
| | - Sam Colachis
- Medical Devices and Neuromodulation, Battelle Memorial Institute, Columbus, Ohio, U.S.A
| | - Marco Solca
- Neuro-X Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Pavo Orepic
- Neuro-X Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Patrick D. Ganzer
- Department of Biomedical Engineering, University of Miami, Miami, Florida, USA
| | - Patrick Haggard
- Institute of Cognitive Neuroscience, University College London, London, U.K
| | - Ali Rezai
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, U.S.A
| | - Olaf Blanke
- Neuro-X Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Department of Clinical Neurosciences, University Hospital, Geneva, Switzerland
| | - Andrea Serino
- MySpace Lab, Department of Clinical Neuroscience, University Hospital Lausanne (CHUV), Lausanne, Switzerland
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35
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Wiegert JS, Spehr M, Hanganu-Opatz IL. Systems neuroscience: A box full of tools to illuminate the black box of the brain. PLoS Biol 2023; 21:e3002221. [PMID: 37498809 PMCID: PMC10374051 DOI: 10.1371/journal.pbio.3002221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/29/2023] Open
Abstract
Investigation of brain function has been fueled by an accelerating development of novel technologies and tools. This Perspective looks at the unprecedented neurotechnological progress of the past 2 decades and discusses future strategies to elucidate brain function.
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Affiliation(s)
- J Simon Wiegert
- Department of Neurophysiology, MCTN, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marc Spehr
- Department of Chemosensation, Institute of Biology II, RWTH Aachen University, Aachen, Germany
| | - Ileana L Hanganu-Opatz
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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36
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Arthur BJ, Kim CM, Chen S, Preibisch S, Darshan R. A scalable implementation of the recursive least-squares algorithm for training spiking neural networks. Front Neuroinform 2023; 17:1099510. [PMID: 37441157 PMCID: PMC10333503 DOI: 10.3389/fninf.2023.1099510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 06/05/2023] [Indexed: 07/15/2023] Open
Abstract
Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1,000 times faster than an unoptimized reference CPU implementation. We demonstrate the code's utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.
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Affiliation(s)
- Benjamin J. Arthur
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Christopher M. Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
- Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Ran Darshan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
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37
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Windolf C, Paulk AC, Kfir Y, Trautmann E, Meszéna D, Muñoz W, Caprara I, Jamali M, Boussard J, Williams ZM, Cash SS, Paninski L, Varol E. ROBUST ONLINE MULTIBAND DRIFT ESTIMATION IN ELECTROPHYSIOLOGY DATA. PROCEEDINGS OF THE ... IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. ICASSP (CONFERENCE) 2023; 2023:10.1109/icassp49357.2023.10095487. [PMID: 37388234 PMCID: PMC10308877 DOI: 10.1109/icassp49357.2023.10095487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
High-density electrophysiology probes have opened new possibilities for systems neuroscience in human and non-human animals, but probe motion poses a challenge for downstream analyses, particularly in human recordings. We improve on the state of the art for tracking this motion with four major contributions. First, we extend previous decentralized methods to use multiband information, leveraging the local field potential (LFP) in addition to spikes. Second, we show that the LFP-based approach enables registration at sub-second temporal resolution. Third, we introduce an efficient online motion tracking algorithm, enabling the method to scale up to longer and higher-resolution recordings, and possibly facilitating real-time applications. Finally, we improve the robustness of the approach by introducing a structure-aware objective and simple methods for adaptive parameter selection. Together, these advances enable fully automated scalable registration of challenging datasets from human and mouse.
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Affiliation(s)
- Charlie Windolf
- Department of Statistics
- Zuckerman Institute
- Columbia University
| | - Angelique C Paulk
- Department of Neurology
- Center for Neurotechnology and Neurorecovery
- Massachusetts General Hospital
- Harvard Medical School
| | - Yoav Kfir
- Department of Neurosurgery
- Massachusetts General Hospital
- Harvard Medical School
| | | | - Domokos Meszéna
- Department of Neurology
- Center for Neurotechnology and Neurorecovery
- Massachusetts General Hospital
- Harvard Medical School
| | - William Muñoz
- Department of Neurosurgery
- Massachusetts General Hospital
- Harvard Medical School
| | - Irene Caprara
- Department of Neurosurgery
- Massachusetts General Hospital
- Harvard Medical School
| | - Mohsen Jamali
- Department of Neurosurgery
- Massachusetts General Hospital
- Harvard Medical School
| | - Julien Boussard
- Department of Statistics
- Zuckerman Institute
- Columbia University
| | - Ziv M Williams
- Department of Neurosurgery
- Massachusetts General Hospital
- Harvard Medical School
| | - Sydney S Cash
- Department of Neurology
- Center for Neurotechnology and Neurorecovery
- Massachusetts General Hospital
- Harvard Medical School
| | - Liam Paninski
- Department of Statistics
- Zuckerman Institute
- Columbia University
| | - Erdem Varol
- Department of Statistics
- Department of Computer Science & Engineering
- Zuckerman Institute
- Columbia University
- New York University
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38
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Bachschmid-Romano L, Hatsopoulos NG, Brunel N. Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex. eLife 2023; 12:77690. [PMID: 37166452 PMCID: PMC10174693 DOI: 10.7554/elife.77690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 03/09/2023] [Indexed: 05/12/2023] Open
Abstract
The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central open questions that need to be answered to understand the neural substrates of motor control. We develop a recurrent neural network model that recapitulates the temporal evolution of neuronal activity recorded from the primary motor cortex of a macaque monkey during an instructed delayed-reach task. In particular, it reproduces the observed dynamic patterns of covariation between neural activity and the direction of motion. We explore the hypothesis that the observed dynamics emerges from a synaptic connectivity structure that depends on the preferred directions of neurons in both preparatory and movement-related epochs, and we constrain the strength of both synaptic connectivity and external input parameters from data. While the model can reproduce neural activity for multiple combinations of the feedforward and recurrent connections, the solution that requires minimum external inputs is one where the observed patterns of covariance are shaped by external inputs during movement preparation, while they are dominated by strong direction-specific recurrent connectivity during movement execution. Our model also demonstrates that the way in which single-neuron tuning properties change over time can explain the level of orthogonality of preparatory and movement-related subspaces.
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Affiliation(s)
| | - Nicholas G Hatsopoulos
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States
- Committee on Computational Neuroscience, University of Chicago, Chicago, United States
| | - Nicolas Brunel
- Department of Neurobiology, Duke University, Durham, United States
- Department of Physics, Duke University, Durham, United States
- Duke Institute for Brain Sciences, Duke University, Durham, United States
- Center for Cognitive Neuroscience, Duke University, Durham, United States
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39
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Thomas A, Yang W, Wang C, Tipparaju SL, Chen G, Sullivan B, Swiekatowski K, Tatam M, Gerfen C, Li N. Superior colliculus cell types bidirectionally modulate choice activity in frontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.22.537884. [PMID: 37162880 PMCID: PMC10168218 DOI: 10.1101/2023.04.22.537884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Action selection occurs through competition between potential choice options. Neural correlates of choice competition are observed across frontal cortex and downstream superior colliculus (SC) during decision-making, yet how these regions interact to mediate choice competition remains unresolved. Here we report that cell types within SC can bidirectionally modulate choice competition and drive choice activity in frontal cortex. In the mouse, topographically matched regions of frontal cortex and SC formed a descending motor pathway for directional licking and a re-entrant loop via the thalamus. During decision-making, distinct neuronal populations in both frontal cortex and SC encoded opposing lick directions and exhibited push-pull dynamics. SC GABAergic neurons encoded ipsilateral choice and glutamatergic neurons encoded contralateral choice, and activating or suppressing these cell types could bidirectionally drive push-pull choice activity in frontal cortex. These results thus identify SC as a major locus to modulate choice competition within the broader action selection network.
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Affiliation(s)
- Alyse Thomas
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | - Weiguo Yang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | - Catherine Wang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | | | - Guang Chen
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | - Brennan Sullivan
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | | | - Mahima Tatam
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
| | - Charles Gerfen
- Section on Neuroanatomy, National Institute of Mental Health, Bethesda, MD
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
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40
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Worley A, Kirby A, Luks S, Samardzic T, Ellison B, Broom L, Latremoliere A, VanderHorst VG. Contrasting walking styles map to discrete neural substrates in the mouse brainstem. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.19.537568. [PMID: 37131768 PMCID: PMC10153272 DOI: 10.1101/2023.04.19.537568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Walking is a slow gait which is particularly adaptable to meet internal or external needs and is prone to maladaptive alterations that lead to gait disorders. Alterations can affect speed, but also style (the way one walks). While slowed speed may signify the presence of a problem, style represents the hallmark essential for clinical classification of gait disorders. However, it has been challenging to objectively capture key stylistic features while uncovering neural substrates driving these features. Here we revealed brainstem hotspots that drive strikingly different walking styles by employing an unbiased mapping assay that combines quantitative walking signatures with focal, cell type specific activation. We found that activation of inhibitory neurons that mapped to the ventromedial caudal pons induced slow motion-like style. Activation of excitatory neurons that mapped to the ventromedial upper medulla induced shuffle-like style. Contrasting shifts in walking signatures distinguished these styles. Activation of inhibitory and excitatory neurons outside these territories or of serotonergic neurons modulated walking speed, but without walking signature shifts. Consistent with their contrasting modulatory actions, hotspots for slow-motion and shuffle-like gaits preferentially innervated different substrates. These findings lay the basis for new avenues to study mechanisms underlying (mal)adaptive walking styles and gait disorders. Graphical abstract
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41
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Libedinsky C. Comparing representations and computations in single neurons versus neural networks. Trends Cogn Sci 2023; 27:517-527. [PMID: 37005114 DOI: 10.1016/j.tics.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 04/03/2023]
Abstract
Single-neuron-level explanations have been the gold standard in neuroscience for decades. Recently, however, neural-network-level explanations have become increasingly popular. This increase in popularity is driven by the fact that the analysis of neural networks can solve problems that cannot be addressed by analyzing neurons independently. In this opinion article, I argue that while both frameworks employ the same general logic to link physical and mental phenomena, in many cases the neural network framework provides better explanatory objects to understand representations and computations related to mental phenomena. I discuss what constitutes a mechanistic explanation in neural systems, provide examples, and conclude by highlighting a number of the challenges and considerations associated with the use of analyses of neural networks to study brain function.
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42
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Moll FW, Kranz D, Corredera Asensio A, Elmaleh M, Ackert-Smith LA, Long MA. Thalamus drives vocal onsets in the zebra finch courtship song. Nature 2023; 616:132-136. [PMID: 36949189 DOI: 10.1038/s41586-023-05818-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 02/09/2023] [Indexed: 03/24/2023]
Abstract
While motor cortical circuits contain information related to specific movement parameters1, long-range inputs also have a critical role in action execution2,3. Thalamic projections can shape premotor activity2-6 and have been suggested7 to mediate the selection of short, stereotyped actions comprising more complex behaviours8. However, the mechanisms by which thalamus interacts with motor cortical circuits to execute such movement sequences remain unknown. Here we find that thalamic drive engages a specific subpopulation of premotor neurons within the zebra finch song nucleus HVC (proper name) and that these inputs are critical for the progression between vocal motor elements (that is, 'syllables'). In vivo two-photon imaging of thalamic axons in HVC showed robust song-related activity, and online perturbations of thalamic function caused song to be truncated at syllable boundaries. We used thalamic stimulation to identify a sparse set of thalamically driven neurons within HVC, representing ~15% of the premotor neurons within that network. Unexpectedly, this population of putative thalamorecipient neurons is robustly active immediately preceding syllable onset, leading to the possibility that thalamic input can initiate individual song components through selectively targeting these 'starter cells'. Our findings highlight the motor thalamus as a director of cortical dynamics in the context of an ethologically relevant behavioural sequence.
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Affiliation(s)
- Felix W Moll
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
- Animal Physiology, Institute of Neurobiology, University of Tübingen, Tübingen, Germany
| | - Devorah Kranz
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Ariadna Corredera Asensio
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Margot Elmaleh
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Lyn A Ackert-Smith
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Michael A Long
- NYU Neuroscience Institute and Department of Otolaryngology, New York University Langone Medical Center, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
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43
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Birdsong sequences initiated by a small cluster of cells in the brain. Nature 2023:10.1038/d41586-023-00447-w. [PMID: 36949128 DOI: 10.1038/d41586-023-00447-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
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44
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Cortical Patterns Shift from Sequence Feature Separation during Planning to Integration during Motor Execution. J Neurosci 2023; 43:1742-1756. [PMID: 36725321 PMCID: PMC10010461 DOI: 10.1523/jneurosci.1628-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 02/03/2023] Open
Abstract
Performing sequences of movements from memory and adapting them to changing task demands is a hallmark of skilled human behavior, from handwriting to playing a musical instrument. Prior studies showed a fine-grained tuning of cortical primary motor, premotor, and parietal regions to motor sequences: from the low-level specification of individual movements to high-level sequence features, such as sequence order and timing. However, it is not known how tuning in these regions unfolds dynamically across planning and execution. To address this, we trained 24 healthy right-handed human participants (14 females, 10 males) to produce four five-element finger press sequences with a particular finger order and timing structure in a delayed sequence production paradigm entirely from memory. Local cortical fMRI patterns during preparation and production phases were extracted from separate No-Go and Go trials, respectively, to tease out activity related to these perimovement phases. During sequence planning, premotor and parietal areas increased tuning to movement order or timing, regardless of their combinations. In contrast, patterns reflecting the unique integration of sequence features emerged in these regions during execution only, alongside timing-specific tuning in the ventral premotor, supplementary motor, and superior parietal areas. This was in line with the participants' behavioral transfer of trained timing, but not of order to new sequence feature combinations. Our findings suggest a general informational state shift from high-level feature separation to low-level feature integration within cortical regions for movement execution. Recompiling sequence features trial-by-trial during planning may enable flexible last-minute adjustment before movement initiation.SIGNIFICANCE STATEMENT Musicians and athletes can modify the timing and order of movements in a sequence trial-by-trial, allowing for a vast repertoire of flexible behaviors. How does the brain put together these high-level sequence features into an integrated whole? We found that, trial-by-trial, the control of sequence features undergoes a state shift from separation during planning to integration during execution across a network of motor-related cortical areas. These findings have implications for understanding the hierarchical control of skilled movement sequences, as well as how information in brain areas unfolds across planning and execution.
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45
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Borgognon S, Rouiller EM. Loss of Motor Cortical Inputs to the Red Nucleus after CNS Disorders in Nonhuman Primates. J Neurosci 2023; 43:1682-1691. [PMID: 36693756 PMCID: PMC10010457 DOI: 10.1523/jneurosci.1942-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/14/2022] [Accepted: 01/13/2023] [Indexed: 01/25/2023] Open
Abstract
The premotor (PM) and primary motor (M1) cortical areas broadcast voluntary motor commands through multiple neuronal pathways, including the corticorubral projection that reaches the red nucleus (RN). However, the respective contribution of M1 and PM to corticorubral projections as well as changes induced by motor disorders or injuries are not known in nonhuman primates. Here, we quantified the density and topography of axonal endings of the corticorubral pathway in RN in intact monkeys, as well as in monkeys subjected to either cervical spinal cord injury (SCI), Parkinson's disease (PD)-like symptoms or primary motor cortex injury (MCI). Twenty adult macaque monkeys of either sex were injected with the biotinylated dextran amine anterograde tracer either in PM or in M1. We developed a semiautomated algorithm to reliably detect and count axonal boutons within the magnocellular and parvocellular (pRN) subdivisions of RN. In intact monkeys, PM and M1 preferentially target the medial part of the ipsilateral pRN, reflecting its somatotopic organization. Projection of PM to the ipsilateral pRN is denser than that of M1, matching previous observations for the corticotectal, corticoreticular, and corticosubthalamic projections (Fregosi et al., 2018, 2019; Borgognon et al., 2020). In all three types of motor disorders, there was a uniform and strong decrease (near loss) of the corticorubral projections from PM and M1. The RN may contribute to functional recovery after SCI, PD, and MCI, by reducing direct cortical influence. This reduction possibly privileges direct access to the final output motor system, via emphasis on the direct corticospinal projection.SIGNIFICANCE STATEMENT We measured the corticorubral projection density arising from the PM or the M1 cortices in adult macaques. The premotor cortex sent denser corticorubral projections than the primary motor cortex, as previously observed for the corticotectal, corticoreticular, and corticosubthalamic projections. The premotor cortex may thus exert more influence than primary motor cortex onto subcortical structures. We next asked whether the corticorubral motor projections undergo lesion-dependent plasticity after either cervical spinal cord injury, Parkinson's disease-like symptoms, or primary motor cortex lesion. In all three types of pathology, there was a strong decrease of the corticorubral motor projection density, suggesting that the red nucleus may contribute to functional recovery after such motor system disorders based on a reduced direct cortical influence.
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Affiliation(s)
- Simon Borgognon
- Center for the Neural Basis of Cognition, Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
- Department of Neurosciences and Movement Sciences, Section of Medicine, Faculty of Science and Medicine, University of Fribourg, CH-1700 Fribourg, Switzerland
- Center for Neuroprosthetics and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Eric M Rouiller
- Department of Neurosciences and Movement Sciences, Section of Medicine, Faculty of Science and Medicine, University of Fribourg, CH-1700 Fribourg, Switzerland
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46
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Mangin EN, Chen J, Lin J, Li N. Behavioral measurements of motor readiness in mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.03.527054. [PMID: 36778494 PMCID: PMC9915731 DOI: 10.1101/2023.02.03.527054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Motor planning facilitates rapid and precise execution of volitional movements. Although motor planning has been classically studied in humans and monkeys, the mouse has become an increasingly popular model system to study neural mechanisms of motor planning. It remains yet untested whether mice and primates share common behavioral features of motor planning. We combined videography and a delayed response task paradigm in an autonomous behavioral system to measure motor planning in non-body- restrained mice. Motor planning resulted in both reaction time savings and increased movement accuracy, replicating classic effects in primates. We found that motor planning was reflected in task-relevant body features. Both the specific actions prepared and the degree of motor readiness could be read out online during motor planning. The online readout further revealed behavioral evidence of simultaneous preparation for multiple actions under uncertain conditions. These results validate the mouse as a model to study motor planning, demonstrate body feature movements as a powerful real-time readout of motor readiness, and offer behavioral evidence that motor planning can be a parallel process that permits rapid selection of multiple prepared actions.
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Affiliation(s)
| | - Jian Chen
- Department of Neuroscience, Baylor College of Medicine
| | - Jing Lin
- Department of Neuroscience, Baylor College of Medicine
| | - Nuo Li
- Department of Neuroscience, Baylor College of Medicine
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47
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West TO, Duchet B, Farmer SF, Friston KJ, Cagnan H. When do bursts matter in the primary motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states. Prog Neurobiol 2023; 221:102397. [PMID: 36565984 PMCID: PMC7614511 DOI: 10.1016/j.pneurobio.2022.102397] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/04/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Brain activity exhibits significant temporal structure that is not well captured in the power spectrum. Recently, attention has shifted to characterising the properties of intermittencies in rhythmic neural activity (i.e. bursts), yet the mechanisms that regulate them are unknown. Here, we present evidence from electrocorticography recordings made over the motor cortex to show that the statistics of bursts, such as duration or amplitude, in the beta frequency (14-30 Hz) band, significantly aid the classification of motor states such as rest, movement preparation, execution, and imagery. These features reflect nonlinearities not detectable in the power spectrum, with states increasing in nonlinearity from movement execution to preparation to rest. Further, we show using a computational model of the cortical microcircuit, constrained to account for burst features, that modulations of laminar specific inhibitory interneurons are responsible for the temporal organisation of activity. Finally, we show that the temporal characteristics of spontaneous activity can be used to infer the balance of cortical integration between incoming sensory information and endogenous activity. Critically, we contribute to the understanding of how transient brain rhythms may underwrite cortical processing, which in turn, could inform novel approaches for brain state classification, and modulation with novel brain-computer interfaces.
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Affiliation(s)
- Timothy O West
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, UK; Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK.
| | - Benoit Duchet
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, UK
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, UK; Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
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48
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The deep cerebellar nuclei to striatum disynaptic connection contributes to skilled forelimb movement. Cell Rep 2023; 42:112000. [PMID: 36656714 DOI: 10.1016/j.celrep.2023.112000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 12/20/2022] [Accepted: 01/04/2023] [Indexed: 01/20/2023] Open
Abstract
Cerebellar-thalamo-striatal synaptic communication has been implicated in a wide range of behaviors, including goal-directed actions, and is altered in cerebellar dystonia. However, its detailed connectivity through the thalamus and its contribution to the execution of forelimb movements is unclear. Here, we use trans-synaptic and retrograde tracing, ex vivo slice recordings, and optogenetic inhibitions during the execution of unidirectional or sequential joystick displacements to demonstrate that the deep cerebellar nuclei (DCN) influence the dorsal striatum with a very high probability. We show that this mainly occurs through the centrolateral (CL), parafascicular (PF), and ventrolateral (VL) nuclei of the thalamus, observing that the DCN→VL and DCN→CL pathways contribute to the execution of unidirectional forelimb displacements while the DCN→PF and DCN→thalamo→striatal pathways contribute to the appropriate execution of forelimb reaching and sequential displacements. These findings highlight specific contributions of the different cerebellar-thalamo-striatal paths to the control of skilled forelimb movement.
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49
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Yang W, Kanodia H, Arber S. Structural and functional map for forelimb movement phases between cortex and medulla. Cell 2023; 186:162-177.e18. [PMID: 36608651 PMCID: PMC9842395 DOI: 10.1016/j.cell.2022.12.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/10/2022] [Accepted: 12/05/2022] [Indexed: 01/07/2023]
Abstract
The cortex influences movement by widespread top-down projections to many nervous system regions. Skilled forelimb movements require brainstem circuitry in the medulla; however, the logic of cortical interactions with these neurons remains unexplored. Here, we reveal a fine-grained anatomical and functional map between anterior cortex (AC) and medulla in mice. Distinct cortical regions generate three-dimensional synaptic columns tiling the lateral medulla, topographically matching the dorso-ventral positions of postsynaptic neurons tuned to distinct forelimb action phases. Although medial AC (MAC) terminates ventrally and connects to forelimb-reaching-tuned neurons and its silencing impairs reaching, lateral AC (LAC) influences dorsally positioned neurons tuned to food handling, and its silencing impairs handling. Cortico-medullary neurons also extend collaterals to other subcortical structures through a segregated channel interaction logic. Our findings reveal a precise alignment between cortical location, its function, and specific forelimb-action-tuned medulla neurons, thereby clarifying interaction principles between these two key structures and beyond.
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Affiliation(s)
- Wuzhou Yang
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Harsh Kanodia
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Silvia Arber
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland,Corresponding author
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Lin C, Ridder MC, Sah P. The PPN and motor control: Preclinical studies to deep brain stimulation for Parkinson's disease. Front Neural Circuits 2023; 17:1095441. [PMID: 36925563 PMCID: PMC10011138 DOI: 10.3389/fncir.2023.1095441] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/31/2023] [Indexed: 03/04/2023] Open
Abstract
The pedunculopontine nucleus (PPN) is the major part of the mesencephalic locomotor region, involved in the control of gait and locomotion. The PPN contains glutamatergic, cholinergic, and GABAergic neurons that all make local connections, but also have long-range ascending and descending connections. While initially thought of as a region only involved in gait and locomotion, recent evidence is showing that this structure also participates in decision-making to initiate movement. Clinically, the PPN has been used as a target for deep brain stimulation to manage freezing of gait in late Parkinson's disease. In this review, we will discuss current thinking on the role of the PPN in locomotor control. We will focus on the cytoarchitecture and functional connectivity of the PPN in relationship to motor control.
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Affiliation(s)
- Caixia Lin
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia.,Joint Centre for Neuroscience and Neural Engineering, and Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
| | - Margreet C Ridder
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Pankaj Sah
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia.,Joint Centre for Neuroscience and Neural Engineering, and Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong Province, China
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