1
|
Shi K, Quass GL, Rogalla MM, Ford AN, Czarny JE, Apostolides PF. Population coding of time-varying sounds in the nonlemniscal inferior colliculus. J Neurophysiol 2024; 131:842-864. [PMID: 38505907 DOI: 10.1152/jn.00013.2024] [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: 01/10/2024] [Revised: 02/29/2024] [Accepted: 03/15/2024] [Indexed: 03/21/2024] Open
Abstract
The inferior colliculus (IC) of the midbrain is important for complex sound processing, such as discriminating conspecific vocalizations and human speech. The IC's nonlemniscal, dorsal "shell" region is likely important for this process, as neurons in these layers project to higher-order thalamic nuclei that subsequently funnel acoustic signals to the amygdala and nonprimary auditory cortices, forebrain circuits important for vocalization coding in a variety of mammals, including humans. However, the extent to which shell IC neurons transmit acoustic features necessary to discern vocalizations is less clear, owing to the technical difficulty of recording from neurons in the IC's superficial layers via traditional approaches. Here, we use two-photon Ca2+ imaging in mice of either sex to test how shell IC neuron populations encode the rate and depth of amplitude modulation, important sound cues for speech perception. Most shell IC neurons were broadly tuned, with a low neurometric discrimination of amplitude modulation rate; only a subset was highly selective to specific modulation rates. Nevertheless, neural network classifier trained on fluorescence data from shell IC neuron populations accurately classified amplitude modulation rate, and decoding accuracy was only marginally reduced when highly tuned neurons were omitted from training data. Rather, classifier accuracy increased monotonically with the modulation depth of the training data, such that classifiers trained on full-depth modulated sounds had median decoding errors of ∼0.2 octaves. Thus, shell IC neurons may transmit time-varying signals via a population code, with perhaps limited reliance on the discriminative capacity of any individual neuron.NEW & NOTEWORTHY The IC's shell layers originate a "nonlemniscal" pathway important for perceiving vocalization sounds. However, prior studies suggest that individual shell IC neurons are broadly tuned and have high response thresholds, implying a limited reliability of efferent signals. Using Ca2+ imaging, we show that amplitude modulation is accurately represented in the population activity of shell IC neurons. Thus, downstream targets can read out sounds' temporal envelopes from distributed rate codes transmitted by populations of broadly tuned neurons.
Collapse
Affiliation(s)
- Kaiwen Shi
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | - Gunnar L Quass
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | - Meike M Rogalla
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | - Alexander N Ford
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | - Jordyn E Czarny
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | - Pierre F Apostolides
- Department of Otolaryngology-Head & Neck Surgery, Kresge Hearing Research Institute, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan, United States
| |
Collapse
|
2
|
Keppler J. Laying the foundations for a theory of consciousness: the significance of critical brain dynamics for the formation of conscious states. Front Hum Neurosci 2024; 18:1379191. [PMID: 38736531 PMCID: PMC11082359 DOI: 10.3389/fnhum.2024.1379191] [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: 01/30/2024] [Accepted: 04/15/2024] [Indexed: 05/14/2024] Open
Abstract
Empirical evidence indicates that conscious states, distinguished by the presence of phenomenal qualities, are closely linked to synchronized neural activity patterns whose dynamical characteristics can be attributed to self-organized criticality and phase transitions. These findings imply that insight into the mechanism by which the brain controls phase transitions will provide a deeper understanding of the fundamental mechanism by which the brain manages to transcend the threshold of consciousness. This article aims to show that the initiation of phase transitions and the formation of synchronized activity patterns is due to the coupling of the brain to the zero-point field (ZPF), which plays a central role in quantum electrodynamics (QED). The ZPF stands for the presence of ubiquitous vacuum fluctuations of the electromagnetic field, represented by a spectrum of normal modes. With reference to QED-based model calculations, the details of the coupling mechanism are revealed, suggesting that critical brain dynamics is governed by the resonant interaction of the ZPF with the most abundant neurotransmitter glutamate. The pyramidal neurons in the cortical microcolumns turn out to be ideally suited to control this interaction. A direct consequence of resonant glutamate-ZPF coupling is the amplification of specific ZPF modes, which leads us to conclude that the ZPF is the key to the understanding of consciousness and that the distinctive feature of neurophysiological processes associated with conscious experience consists in modulating the ZPF. Postulating that the ZPF is an inherently sentient field and assuming that the spectrum of phenomenal qualities is represented by the normal modes of the ZPF, the significance of resonant glutamate-ZPF interaction for the formation of conscious states becomes apparent in that the amplification of specific ZPF modes is inextricably linked with the excitation of specific phenomenal qualities. This theory of consciousness, according to which phenomenal states arise through resonant amplification of zero-point modes, is given the acronym TRAZE. An experimental setup is specified that can be used to test a corollary of the theory, namely, the prediction that normally occurring conscious perceptions are absent under experimental conditions in which resonant glutamate-ZPF coupling is disrupted.
Collapse
|
3
|
Ford AN, Czarny JE, Rogalla MM, Quass GL, Apostolides PF. Auditory Corticofugal Neurons Transmit Auditory and Non-auditory Information During Behavior. J Neurosci 2024; 44:e1190232023. [PMID: 38123993 PMCID: PMC10869159 DOI: 10.1523/jneurosci.1190-23.2023] [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: 06/27/2023] [Revised: 11/08/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Layer 5 pyramidal neurons of sensory cortices project "corticofugal" axons to myriad sub-cortical targets, thereby broadcasting high-level signals important for perception and learning. Recent studies suggest dendritic Ca2+ spikes as key biophysical mechanisms supporting corticofugal neuron function: these long-lasting events drive burst firing, thereby initiating uniquely powerful signals to modulate sub-cortical representations and trigger learning-related plasticity. However, the behavioral relevance of corticofugal dendritic spikes is poorly understood. We shed light on this issue using 2-photon Ca2+ imaging of auditory corticofugal dendrites as mice of either sex engage in a GO/NO-GO sound-discrimination task. Unexpectedly, only a minority of dendritic spikes were triggered by behaviorally relevant sounds under our conditions. Task related dendritic activity instead mostly followed sound cue termination and co-occurred with mice's instrumental licking during the answer period of behavioral trials, irrespective of reward consumption. Temporally selective, optogenetic silencing of corticofugal neurons during the trial answer period impaired auditory discrimination learning. Thus, auditory corticofugal systems' contribution to learning and plasticity may be partially nonsensory in nature.
Collapse
Affiliation(s)
- Alexander N Ford
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Jordyn E Czarny
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Meike M Rogalla
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Gunnar L Quass
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Pierre F Apostolides
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan 48109
| |
Collapse
|
4
|
Gillon CJ, Pina JE, Lecoq JA, Ahmed R, Billeh YN, Caldejon S, Groblewski P, Henley TM, Kato I, Lee E, Luviano J, Mace K, Nayan C, Nguyen TV, North K, Perkins J, Seid S, Valley MT, Williford A, Bengio Y, Lillicrap TP, Richards BA, Zylberberg J. Responses to Pattern-Violating Visual Stimuli Evolve Differently Over Days in Somata and Distal Apical Dendrites. J Neurosci 2024; 44:e1009232023. [PMID: 37989593 PMCID: PMC10860604 DOI: 10.1523/jneurosci.1009-23.2023] [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: 05/30/2023] [Revised: 09/14/2023] [Accepted: 09/16/2023] [Indexed: 11/23/2023] Open
Abstract
Scientists have long conjectured that the neocortex learns patterns in sensory data to generate top-down predictions of upcoming stimuli. In line with this conjecture, different responses to pattern-matching vs pattern-violating visual stimuli have been observed in both spiking and somatic calcium imaging data. However, it remains unknown whether these pattern-violation signals are different between the distal apical dendrites, which are heavily targeted by top-down signals, and the somata, where bottom-up information is primarily integrated. Furthermore, it is unknown how responses to pattern-violating stimuli evolve over time as an animal gains more experience with them. Here, we address these unanswered questions by analyzing responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons tracked over multiple days in primary visual cortex of awake, behaving female and male mice. We use sequences of Gabor patches with patterns in their orientations to create pattern-matching and pattern-violating stimuli, and two-photon calcium imaging to record neuronal responses. Many neurons in both layers show large differences between their responses to pattern-matching and pattern-violating stimuli. Interestingly, these responses evolve in opposite directions in the somata and distal apical dendrites, with somata becoming less sensitive to pattern-violating stimuli and distal apical dendrites more sensitive. These differences between the somata and distal apical dendrites may be important for hierarchical computation of sensory predictions and learning, since these two compartments tend to receive bottom-up and top-down information, respectively.
Collapse
Affiliation(s)
- Colleen J Gillon
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada
- Mila, Montréal, Québec, Canada
| | - Jason E Pina
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | | | | | | | | | | | - Timothy M Henley
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | | | - Eric Lee
- Allen Institute, Seattle, Washington
| | | | - Kyla Mace
- Allen Institute, Seattle, Washington
| | | | | | - Kat North
- Allen Institute, Seattle, Washington
| | | | - Sam Seid
- Allen Institute, Seattle, Washington
| | | | | | - Yoshua Bengio
- Mila, Montréal, Québec, Canada
- Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Québec, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Timothy P Lillicrap
- DeepMind, Inc., London, United Kingdom
- Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, United Kingdom
| | - Blake A Richards
- Mila, Montréal, Québec, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
- School of Computer Science, McGill University, Montréal, Québec, Canada
- Department of Neurology & Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Joel Zylberberg
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
| |
Collapse
|
5
|
Francioni V, Tang VD, Brown NJ, Toloza EH, Harnett M. Vectorized instructive signals in cortical dendrites during a brain-computer interface task. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.03.565534. [PMID: 37961227 PMCID: PMC10635122 DOI: 10.1101/2023.11.03.565534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Backpropagation of error is the most widely used learning algorithm in artificial neural networks, forming the backbone of modern machine learning and artificial intelligence1,2. Backpropagation provides a solution to the credit assignment problem by vectorizing an error signal tailored to individual neurons. Recent theoretical models have suggested that neural circuits could implement backpropagation-like learning by semi-independently processing feedforward and feedback information streams in separate dendritic compartments3-7. This presents a compelling, but untested, hypothesis for how cortical circuits could solve credit assignment in the brain. We designed a neurofeedback brain-computer interface (BCI) task with an experimenter-defined reward function to evaluate the key requirements for dendrites to implement backpropagation-like learning. We trained mice to modulate the activity of two spatially intermingled populations (4 or 5 neurons each) of layer 5 pyramidal neurons in the retrosplenial cortex to rotate a visual grating towards a target orientation while we recorded GCaMP activity from somas and corresponding distal apical dendrites. We observed that the relative magnitudes of somatic versus dendritic signals could be predicted using the activity of the surrounding network and contained information about task-related variables that could serve as instructive signals, including reward and error. The signs of these putative teaching signals both depended on the causal role of individual neurons in the task and predicted changes in overall activity over the course of learning. These results provide the first biological evidence of a backpropagation-like solution to the credit assignment problem in the brain.
Collapse
Affiliation(s)
- Valerio Francioni
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Vincent D Tang
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Norma J. Brown
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Enrique H.S. Toloza
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Mark Harnett
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| |
Collapse
|
6
|
Neske GT, Cardin JA. Transthalamic input to higher-order cortex selectively conveys state information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.08.561424. [PMID: 37873181 PMCID: PMC10592671 DOI: 10.1101/2023.10.08.561424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Communication among different neocortical areas is largely thought to be mediated by long-range synaptic interactions between cortical neurons, with the thalamus providing only an initial relay of information from the sensory periphery. Higher-order thalamic nuclei receive strong synaptic inputs from the cortex and send robust projections back to other cortical areas, providing a distinct and potentially critical route for cortico-cortical communication. However, the relative contributions of corticocortical and thalamocortical inputs to higher-order cortical function remain unclear. Using imaging of cortical neurons and projection axon terminals in combination with optogenetic manipulations, we find that the higher-order visual thalamus of mice conveys a specialized stream of information to higher-order visual cortex. Whereas corticocortical projections from lower cortical areas convey robust visual information, higher-order thalamocortical projections convey strong behavioral state information. Together, these findings suggest a key role for higher-order thalamus in providing contextual signals that flexibly modulate sensory processing in higher-order cortex.
Collapse
Affiliation(s)
- Garrett T. Neske
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA
- Present address: Department of Physiology and Biophysics, State University of New York at Buffalo, Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY, USA
| | - Jessica A. Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA
| |
Collapse
|
7
|
Shi K, Quass GL, Rogalla MM, Ford AN, Czarny JE, Apostolides PF. Population coding of time-varying sounds in the non-lemniscal Inferior Colliculus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.14.553263. [PMID: 37645904 PMCID: PMC10461978 DOI: 10.1101/2023.08.14.553263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
The inferior colliculus (IC) of the midbrain is important for complex sound processing, such as discriminating conspecific vocalizations and human speech. The IC's non-lemniscal, dorsal "shell" region is likely important for this process, as neurons in these layers project to higher-order thalamic nuclei that subsequently funnel acoustic signals to the amygdala and non-primary auditory cortices; forebrain circuits important for vocalization coding in a variety of mammals, including humans. However, the extent to which shell IC neurons transmit acoustic features necessary to discern vocalizations is less clear, owing to the technical difficulty of recording from neurons in the IC's superficial layers via traditional approaches. Here we use 2-photon Ca2+ imaging in mice of either sex to test how shell IC neuron populations encode the rate and depth of amplitude modulation, important sound cues for speech perception. Most shell IC neurons were broadly tuned, with a low neurometric discrimination of amplitude modulation rate; only a subset were highly selective to specific modulation rates. Nevertheless, neural network classifier trained on fluorescence data from shell IC neuron populations accurately classified amplitude modulation rate, and decoding accuracy was only marginally reduced when highly tuned neurons were omitted from training data. Rather, classifier accuracy increased monotonically with the modulation depth of the training data, such that classifiers trained on full-depth modulated sounds had median decoding errors of ~0.2 octaves. Thus, shell IC neurons may transmit time-varying signals via a population code, with perhaps limited reliance on the discriminative capacity of any individual neuron.
Collapse
Affiliation(s)
- Kaiwen Shi
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
| | - Gunnar L. Quass
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
| | - Meike M. Rogalla
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
| | - Alexander N. Ford
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
| | - Jordyn E. Czarny
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
| | - Pierre F. Apostolides
- Kresge Hearing Research Institute, Department of Otolaryngology — Head & Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, 48109
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, 48109
| |
Collapse
|
8
|
Kastellakis G, Tasciotti S, Pandi I, Poirazi P. The dendritic engram. Front Behav Neurosci 2023; 17:1212139. [PMID: 37576932 PMCID: PMC10412934 DOI: 10.3389/fnbeh.2023.1212139] [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: 04/25/2023] [Accepted: 07/11/2023] [Indexed: 08/15/2023] Open
Abstract
Accumulating evidence from a wide range of studies, including behavioral, cellular, molecular and computational findings, support a key role of dendrites in the encoding and recall of new memories. Dendrites can integrate synaptic inputs in non-linear ways, provide the substrate for local protein synthesis and facilitate the orchestration of signaling pathways that regulate local synaptic plasticity. These capabilities allow them to act as a second layer of computation within the neuron and serve as the fundamental unit of plasticity. As such, dendrites are integral parts of the memory engram, namely the physical representation of memories in the brain and are increasingly studied during learning tasks. Here, we review experimental and computational studies that support a novel, dendritic view of the memory engram that is centered on non-linear dendritic branches as elementary memory units. We highlight the potential implications of dendritic engrams for the learning and memory field and discuss future research directions.
Collapse
Affiliation(s)
- George Kastellakis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
| | - Simone Tasciotti
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
- Department of Biology, University of Crete, Heraklion, Greece
| | - Ioanna Pandi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
- Department of Biology, University of Crete, Heraklion, Greece
| | - Panayiota Poirazi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
| |
Collapse
|
9
|
Wong-Campos JD, Park P, Davis H, Qi Y, Tian H, Itkis DG, Kim D, Grimm JB, Plutkis SE, Lavis L, Cohen AE. Voltage dynamics of dendritic integration and back-propagation in vivo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.25.542363. [PMID: 37292691 PMCID: PMC10245993 DOI: 10.1101/2023.05.25.542363] [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
Neurons integrate synaptic inputs within their dendrites and produce spiking outputs, which then propagate down the axon and back into the dendrites where they contribute to plasticity. Mapping the voltage dynamics in dendritic arbors of live animals is crucial for understanding neuronal computation and plasticity rules. Here we combine patterned channelrhodopsin activation with dual-plane structured illumination voltage imaging, for simultaneous perturbation and monitoring of dendritic and somatic voltage in Layer 2/3 pyramidal neurons in anesthetized and awake mice. We examined the integration of synaptic inputs and compared the dynamics of optogenetically evoked, spontaneous, and sensory-evoked back-propagating action potentials (bAPs). Our measurements revealed a broadly shared membrane voltage throughout the dendritic arbor, and few signatures of electrical compartmentalization among synaptic inputs. However, we observed spike rate acceleration-dependent propagation of bAPs into distal dendrites. We propose that this dendritic filtering of bAPs may play a critical role in activity-dependent plasticity.
Collapse
Affiliation(s)
- J David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hunter Davis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Daniel G Itkis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Doyeon Kim
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Jonathan B Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Sarah E Plutkis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Luke Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| |
Collapse
|
10
|
Fişek M, Herrmann D, Egea-Weiss A, Cloves M, Bauer L, Lee TY, Russell LE, Häusser M. Cortico-cortical feedback engages active dendrites in visual cortex. Nature 2023; 617:769-776. [PMID: 37138089 DOI: 10.1038/s41586-023-06007-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 03/23/2023] [Indexed: 05/05/2023]
Abstract
Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas1. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure-ground segmentation2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.
Collapse
Affiliation(s)
- Mehmet Fişek
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Dustin Herrmann
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Alexander Egea-Weiss
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Matilda Cloves
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lisa Bauer
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tai-Ying Lee
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lloyd E Russell
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| |
Collapse
|
11
|
Miranda M, Frasca M, Estrada E. Topologically induced suppression of explosive synchronization. CHAOS (WOODBURY, N.Y.) 2023; 33:2887742. [PMID: 37125934 DOI: 10.1063/5.0142418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/06/2023] [Indexed: 05/03/2023]
Abstract
Nowadays, explosive synchronization is a well-documented phenomenon consisting in a first-order transition that may coexist with classical synchronization. Typically, explosive synchronization occurs when the network structure is represented by the classical graph Laplacian, and the node frequency and its degree are correlated. Here, we answer the question on whether this phenomenon can be observed in networks when the oscillators are coupled via degree-biased Laplacian operators. We not only observe that this is the case but also that this new representation naturally controls the transition from explosive to standard synchronization in a network. We prove analytically that explosive synchronization emerges when using this theoretical setting in star-like networks. As soon as this star-like network is topologically converted into a network containing cycles, the explosive synchronization gives rise to classical synchronization. Finally, we hypothesize that this mechanism may play a role in switching from normal to explosive states in the brain, where explosive synchronization has been proposed to be related to some pathologies like epilepsy and fibromyalgia.
Collapse
Affiliation(s)
- Manuel Miranda
- Institute of Cross-Disciplinary Physics and Complex Systems, IFISC (UIB-CSIC), 07122 Palma de Mallorca, Spain
| | - Mattia Frasca
- Department of Electrical, Electronics and Computer Science Engineering, University of Catania, I-95125 Catania, Italy
- Istituto di Analisi dei Sistemi ed Informatica "A. Ruberti", Consiglio Nazionale delle Ricerche (IASI-CNR), 00185 Roma, Italy
| | - Ernesto Estrada
- Institute of Cross-Disciplinary Physics and Complex Systems, IFISC (UIB-CSIC), 07122 Palma de Mallorca, Spain
| |
Collapse
|
12
|
Moore JJ, Rashid SK, Johnson CD, Codrington N, Chklovskii DB, Basu J. Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. RESEARCH SQUARE 2023:rs.3.rs-2733660. [PMID: 37131789 PMCID: PMC10153397 DOI: 10.21203/rs.3.rs-2733660/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.
Collapse
Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Cara D. Johnson
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Naomi Codrington
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Dmitri B Chklovskii
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
| |
Collapse
|
13
|
Yin XY, Tang XH, Wang SX, Zhao YC, Jia M, Yang JJ, Ji MH, Shen JC. HMGB1 mediates synaptic loss and cognitive impairment in an animal model of sepsis-associated encephalopathy. J Neuroinflammation 2023; 20:69. [PMID: 36906561 PMCID: PMC10007818 DOI: 10.1186/s12974-023-02756-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 03/02/2023] [Indexed: 03/13/2023] Open
Abstract
BACKGROUND Microglial activation-mediated neuroinflammation is one of the essential pathogenic mechanisms of sepsis-associated encephalopathy (SAE). Mounting evidence suggests that high mobility group box-1 protein (HMGB1) plays a pivotal role in neuroinflammation and SAE, yet the mechanism by which HMGB1 induces cognitive impairment in SAE remains unclear. Therefore, this study aimed to investigate the mechanism of HMGB1 underlying cognitive impairment in SAE. METHODS An SAE model was established by cecal ligation and puncture (CLP); animals in the sham group underwent cecum exposure alone without ligation and perforation. Mice in the inflachromene (ICM) group were continuously injected with ICM intraperitoneally at a daily dose of 10 mg/kg for 9 days starting 1 h before the CLP operation. The open field, novel object recognition, and Y maze tests were performed on days 14-18 after surgery to assess locomotor activity and cognitive function. HMGB1 secretion, the state of microglia, and neuronal activity were measured by immunofluorescence. Golgi staining was performed to detect changes in neuronal morphology and dendritic spine density. In vitro electrophysiology was performed to detect changes in long-term potentiation (LTP) in the CA1 of the hippocampus. In vivo electrophysiology was performed to detect the changes in neural oscillation of the hippocampus. RESULTS CLP-induced cognitive impairment was accompanied by increased HMGB1 secretion and microglial activation. The phagocytic capacity of microglia was enhanced, resulting in aberrant pruning of excitatory synapses in the hippocampus. The loss of excitatory synapses reduced neuronal activity, impaired LTP, and decreased theta oscillation in the hippocampus. Inhibiting HMGB1 secretion by ICM treatment reversed these changes. CONCLUSIONS HMGB1 induces microglial activation, aberrant synaptic pruning, and neuron dysfunction in an animal model of SAE, leading to cognitive impairment. These results suggest that HMGB1 might be a target for SAE treatment.
Collapse
Affiliation(s)
- Xiao-Yu Yin
- Department of Anesthesiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China
| | - Xiao-Hui Tang
- Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China
| | - Shi-Xu Wang
- Department of Anesthesiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China
| | - Yong-Chang Zhao
- Department of Anesthesiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China
| | - Min Jia
- Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China
| | - Jian-Jun Yang
- Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China.
| | - Mu-Huo Ji
- Department of Anesthesiology, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, China.
| | - Jin-Chun Shen
- Department of Anesthesiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China.
| |
Collapse
|
14
|
Chen H, Li H, Ma T, Han S, Zhao Q. Biological function simulation in neuromorphic devices: from synapse and neuron to behavior. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2183712. [PMID: 36926202 PMCID: PMC10013381 DOI: 10.1080/14686996.2023.2183712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/06/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
As the boom of data storage and processing, brain-inspired computing provides an effective approach to solve the current problem. Various emerging materials and devices have been reported to promote the development of neuromorphic computing. Thereinto, the neuromorphic device represented by memristor has attracted extensive research due to its outstanding property to emulate the brain's functions from synaptic plasticity, sensory-memory neurons to some intelligent behaviors of living creatures. Herein, we mainly review the progress of these brain functions mimicked by neuromorphic devices, concentrating on synapse (i.e. various synaptic plasticity trigger by electricity and/or light), neurons (including the various sensory nervous system) and intelligent behaviors (such as conditioned reflex represented by Pavlov's dog experiment). Finally, some challenges and prospects related to neuromorphic devices are presented.
Collapse
Affiliation(s)
- Hui Chen
- Heart Center of Henan Provincial People’s Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, P. R. China
| | - Huilin Li
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Ting Ma
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Shuangshuang Han
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Qiuping Zhao
- Heart Center of Henan Provincial People’s Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, P. R. China
| |
Collapse
|
15
|
Mohan H, An X, Xu XH, Kondo H, Zhao S, Matho KS, Wang BS, Musall S, Mitra P, Huang ZJ. Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks. Nat Neurosci 2023; 26:481-494. [PMID: 36690901 PMCID: PMC10571488 DOI: 10.1038/s41593-022-01244-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 12/02/2022] [Indexed: 01/24/2023]
Abstract
The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection-neuron-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, during spontaneous movements and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of ITsPlxnD1 and PTsFezf2 in subnetwork nodes disrupted distinct components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and projection-neuron-type specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.
Collapse
Affiliation(s)
- Hemanth Mohan
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xu An
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - X Hermione Xu
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Hideki Kondo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Shengli Zhao
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | | | - Bor-Shuen Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Simon Musall
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Institute of Biological information Processing, Forschungszentrum Julich, Julich, Germany
| | - Partha Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Z Josh Huang
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
| |
Collapse
|
16
|
Jorratt P, Ricny J, Leibold C, Ovsepian SV. Endogenous Modulators of NMDA Receptor Control Dendritic Field Expansion of Cortical Neurons. Mol Neurobiol 2023; 60:1440-1452. [PMID: 36462136 PMCID: PMC9899188 DOI: 10.1007/s12035-022-03147-0] [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: 04/29/2022] [Accepted: 11/21/2022] [Indexed: 12/05/2022]
Abstract
Impairments of N-methyl-D-aspartate receptor (NMDAR) activity have been implicated in several neuropsychiatric disorders, with pharmacological inhibition of NMDAR-mediated currents and associated neurobehavioral changes considered as a model of schizophrenia. We analyzed the effects of brief and long-term exposure of rat cortical cultures to the most prevalent endogenous modulators of NMDAR (kynurenic acid, pregnenolone sulfate, spermidine, and zinc) on neuronal viability, stimulation-induced release of glutamate, and dendritic morphology with synaptic density. Both, glutamate release and neuronal viability studies revealed no difference between the test and control groups. No differences were also observed in the number of dendritic branching and length, or density of synaptic connections and neuronal soma size. Comparison of the extent of dendritic projections and branching patterns, however, revealed enhanced distal arborization with the expansion of the dendritic area under prolonged treatment of cultures with physiological concentrations of NMDAR modulators, with differences reaching significance in spermidine and pregnenolone sulfate tests. Measurements of the density of glutamatergic synapses showed consistency across all neuronal groups, except those treated with pregnenolone sulfate, which showed a reduction of PSD-95-positive elements. Overall, our data suggest that constitutive glutamatergic activity mediated by NMDAR controls the dendritic field expansion and can influence the integrative properties of cortical neurons.
Collapse
Affiliation(s)
- Pascal Jorratt
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.4491.80000 0004 1937 116XThird Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jan Ricny
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic
| | - Christian Leibold
- grid.5963.9Faculty of Biology and Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
| | - Saak V. Ovsepian
- grid.36316.310000 0001 0806 5472Faculty of Science and Engineering, University of Greenwich London, Chatham Maritime, Kent, ME4 4TB UK
| |
Collapse
|
17
|
Huang J, Liang S, Li L, Li X, Liao X, Hu Q, Zhang C, Jia H, Chen X, Wang M, Li R. Daily two-photon neuronal population imaging with targeted single-cell electrophysiology and subcellular imaging in auditory cortex of behaving mice. Front Cell Neurosci 2023; 17:1142267. [PMID: 36937184 PMCID: PMC10020347 DOI: 10.3389/fncel.2023.1142267] [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: 01/11/2023] [Accepted: 02/17/2023] [Indexed: 03/06/2023] Open
Abstract
Quantitative and mechanistic understanding of learning and long-term memory at the level of single neurons in living brains require highly demanding techniques. A specific need is to precisely label one cell whose firing output property is pinpointed amidst a functionally characterized large population of neurons through the learning process and then investigate the distribution and properties of dendritic inputs. Here, we disseminate an integrated method of daily two-photon neuronal population Ca2+ imaging through an auditory associative learning course, followed by targeted single-cell loose-patch recording and electroporation of plasmid for enhanced chronic Ca2+ imaging of dendritic spines in the targeted cell. Our method provides a unique solution to the demand, opening a solid path toward the hard-cores of how learning and long-term memory are physiologically carried out at the level of single neurons and synapses.
Collapse
Affiliation(s)
- Junjie Huang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
| | - Susu Liang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
| | - Longhui Li
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
| | - Xingyi Li
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
| | - Xiang Liao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
| | - Qianshuo Hu
- School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China
| | - Chunqing Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, China
| | - Hongbo Jia
- School of Physical Science and Technology, Advanced Institute for Brain and Intelligence, Guangxi University, Nanning, China
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute of Neuroscience and the SyNergy Cluster, Technical University Munich, Munich, Germany
| | - Xiaowei Chen
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, China
- Guangyang Bay Laboratory, Chongqing Institute for Brain and Intelligence, Chongqing, China
- Xiaowei Chen,
| | - Meng Wang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, China
- Meng Wang,
| | - Ruijie Li
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, China
- School of Physical Science and Technology, Advanced Institute for Brain and Intelligence, Guangxi University, Nanning, China
- *Correspondence: Ruijie Li,
| |
Collapse
|
18
|
Gooch HM, Bluett T, Perumal MB, Vo HD, Fletcher LN, Papacostas J, Jeffree RL, Wood M, Colditz MJ, McMillen J, Tsahtsarlis T, Amato D, Campbell R, Gillinder L, Williams SR. High-fidelity dendritic sodium spike generation in human layer 2/3 neocortical pyramidal neurons. Cell Rep 2022; 41:111500. [DOI: 10.1016/j.celrep.2022.111500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/22/2022] [Accepted: 09/21/2022] [Indexed: 11/03/2022] Open
|
19
|
Brombas A, Zhou X, Williams SR. Light-evoked dendritic spikes in sustained but not transient rabbit retinal ganglion cells. Neuron 2022; 110:2802-2814.e3. [PMID: 35803269 DOI: 10.1016/j.neuron.2022.06.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/27/2022] [Accepted: 06/07/2022] [Indexed: 10/17/2022]
Abstract
Dendritic computations have a central role in neuronal function, but it is unknown how cell-class heterogeneity of dendritic electrical excitability shapes physiologically engaged neuronal and circuit computations. To address this, we examined dendritic integration in closely related classes of retinal ganglion cells (GCs) using simultaneous somato-dendritic electrical recording techniques in a functionally intact circuit. Simultaneous recordings revealed sustained OFF-GCs generated powerful dendritic spikes in response to visual input that drove action potential firing. In contrast, the dendrites of transient OFF-GCs were passive and did not generate dendritic spikes. Dendritic spike generation allowed sustained, but not transient, OFF-GCs to signal into action potential output the local motion of visual stimuli to produce a continuous wave of action potential firing in adjacent cells as images moved across the retina. Conversely, this representation was highly fragmented in transient OFF-GCs. Thus, a heterogeneity of dendritic excitability defines the computations executed by classes of GCs.
Collapse
Affiliation(s)
- Arne Brombas
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Xiangyu Zhou
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Stephen R Williams
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia.
| |
Collapse
|
20
|
Moore JJ, Robert V, Rashid SK, Basu J. Assessing Local and Branch-specific Activity in Dendrites. Neuroscience 2022; 489:143-164. [PMID: 34756987 PMCID: PMC9125998 DOI: 10.1016/j.neuroscience.2021.10.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 10/09/2021] [Accepted: 10/21/2021] [Indexed: 01/12/2023]
Abstract
Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.
Collapse
Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Vincent Robert
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA.
| |
Collapse
|
21
|
Keijser J, Sprekeler H. Optimizing interneuron circuits for compartment-specific feedback inhibition. PLoS Comput Biol 2022; 18:e1009933. [PMID: 35482670 PMCID: PMC9049365 DOI: 10.1371/journal.pcbi.1009933] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/18/2022] [Indexed: 12/02/2022] Open
Abstract
Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent advances in training spiking network models, we optimized the connectivity and short-term plasticity of interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons. Over the course of the optimization, the interneurons diversified into two classes that resembled parvalbumin (PV) and somatostatin (SST) expressing interneurons. Using simulations and mathematical analyses, we show that the resulting circuit can be understood as a neural decoder that inverts the nonlinear biophysical computations performed within the pyramidal cells. Our model provides a proof of concept for studying structure-function relations in cortical circuits by a combination of gradient-based optimization and biologically plausible phenomenological models. The brain contains billions of nerve cells—neurons—that can be classified into different types depending on their shape, connectivity and activity. A particularly diverse group of neurons is that of inhibitory neurons, named after their suppressive effect on neural activity. Presumably, their diverse properties allow inhibitory neurons to fulfil different functions, but what these functions are is currently unclear. In this paper, we investigated if a particular function can explain the existence and properties of the two most common inhibitory cell classes: The need to regulate activity in different physical parts (compartments) of the neurons they target. We investigated this function in a computer model, using optimization to find the neuron properties best-suited for compartment-specific inhibition. Our key result is that after the optimization, model neurons largely fell into two classes that resembled the two types of biological neurons. In particular, the optimized neurons were connected to only one compartment of other neurons. This suggests that the diversity of inhibitory neurons is well suited for compartment-specific inhibition. In the future, our approach of optimizing neural properties might be used to investigate other functions (or dysfunctions) of neuron diversity.
Collapse
Affiliation(s)
- Joram Keijser
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
- * E-mail:
| | - Henning Sprekeler
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| |
Collapse
|
22
|
d'Aquin S, Szonyi A, Mahn M, Krabbe S, Gründemann J, Lüthi A. Compartmentalized dendritic plasticity during associative learning. Science 2022; 376:eabf7052. [PMID: 35420958 DOI: 10.1126/science.abf7052] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Experience-dependent changes in behavior are mediated by long-term functional modifications in brain circuits. Activity-dependent plasticity of synaptic input is a major underlying cellular process. Although we have a detailed understanding of synaptic and dendritic plasticity in vitro, little is known about the functional and plastic properties of active dendrites in behaving animals. Using deep brain two-photon Ca2+ imaging, we investigated how sensory responses in amygdala principal neurons develop upon classical fear conditioning, a form of associative learning. Fear conditioning induced differential plasticity in dendrites and somas regulated by compartment-specific inhibition. Our results indicate that learning-induced plasticity can be uncoupled between soma and dendrites, reflecting distinct synaptic and microcircuit-level mechanisms that increase the computational capacity of amygdala circuits.
Collapse
Affiliation(s)
- Simon d'Aquin
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Andras Szonyi
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary
| | - Mathias Mahn
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Sabine Krabbe
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Jan Gründemann
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Andreas Lüthi
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,University of Basel, Basel, Switzerland
| |
Collapse
|
23
|
Otor Y, Achvat S, Cermak N, Benisty H, Abboud M, Barak O, Schiller Y, Poleg-Polsky A, Schiller J. Dynamic compartmental computations in tuft dendrites of layer 5 neurons during motor behavior. Science 2022; 376:267-275. [PMID: 35420959 DOI: 10.1126/science.abn1421] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Tuft dendrites of layer 5 pyramidal neurons form specialized compartments important for motor learning and performance, yet their computational capabilities remain unclear. Structural-functional mapping of the tuft tree from the motor cortex during motor tasks revealed two morphologically distinct populations of layer 5 pyramidal tract neurons (PTNs) that exhibit specific tuft computational properties. Early bifurcating and large nexus PTNs showed marked tuft functional compartmentalization, representing different motor variable combinations within and between their two tuft hemi-trees. By contrast, late bifurcating and smaller nexus PTNs showed synchronous tuft activation. Dendritic structure and dynamic recruitment of the N-methyl-d-aspartate (NMDA)-spiking mechanism explained the differential compartmentalization patterns. Our findings support a morphologically dependent framework for motor computations, in which independent amplification units can be combinatorically recruited to represent different motor sequences within the same tree.
Collapse
Affiliation(s)
- Yara Otor
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Shay Achvat
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Nathan Cermak
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Hadas Benisty
- Yale University School of Medicine; Bethany, CT, USA
| | - Maisan Abboud
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Omri Barak
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Yitzhak Schiller
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| | - Alon Poleg-Polsky
- Department of Physiology and Biophysics; University of Colorado School of Medicine, 12800 East 19th Avenue MS8307, Aurora, CO 8004, USA
| | - Jackie Schiller
- Department of Physiology, Technion Medical School, Bat-Galim, Haifa 31096, Israel
| |
Collapse
|
24
|
Landau AT, Park P, Wong-Campos JD, Tian H, Cohen AE, Sabatini BL. Dendritic branch structure compartmentalizes voltage-dependent calcium influx in cortical layer 2/3 pyramidal cells. eLife 2022; 11:76993. [PMID: 35319464 PMCID: PMC8979587 DOI: 10.7554/elife.76993] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/22/2022] [Indexed: 11/13/2022] Open
Abstract
Back-propagating action potentials (bAPs) regulate synaptic plasticity by evoking voltage-dependent calcium influx throughout dendrites. Attenuation of bAP amplitude in distal dendritic compartments alters plasticity in a location-specific manner by reducing bAP-dependent calcium influx. However, it is not known if neurons exhibit branch-specific variability in bAP-dependent calcium signals, independent of distance-dependent attenuation. Here, we reveal that bAPs fail to evoke calcium influx through voltage-gated calcium channels (VGCCs) in a specific population of dendritic branches in mouse cortical layer 2/3 pyramidal cells, despite evoking substantial VGCC-mediated calcium influx in sister branches. These branches contain VGCCs and successfully propagate bAPs in the absence of synaptic input; nevertheless, they fail to exhibit bAP-evoked calcium influx due to a branch-specific reduction in bAP amplitude. We demonstrate that these branches have more elaborate branch structure compared to sister branches, which causes a local reduction in electrotonic impedance and bAP amplitude. Finally, we show that bAPs still amplify synaptically-mediated calcium influx in these branches because of differences in the voltage-dependence and kinetics of VGCCs and NMDA-type glutamate receptors. Branch-specific compartmentalization of bAP-dependent calcium signals may provide a mechanism for neurons to diversify synaptic tuning across the dendritic tree.
Collapse
Affiliation(s)
- Andrew T Landau
- Department of Neurobiology, Howard Hughes Medical Institute, Harvard Medical School, Boston, United States
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - J David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Bernardo L Sabatini
- Department of Neurobiology, Howard Hughes Medical Institute, Harvard Medical School, Boston, United States
| |
Collapse
|
25
|
Rolotti SV, Blockus H, Sparks FT, Priestley JB, Losonczy A. Reorganization of CA1 dendritic dynamics by hippocampal sharp-wave ripples during learning. Neuron 2022; 110:977-991.e4. [PMID: 35041805 PMCID: PMC8930454 DOI: 10.1016/j.neuron.2021.12.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/23/2021] [Accepted: 12/10/2021] [Indexed: 12/17/2022]
Abstract
The hippocampus plays a critical role in memory consolidation, mediated by coordinated network activity during sharp-wave ripple (SWR) events. Despite the link between SWRs and hippocampal plasticity, little is known about how network state affects information processing in dendrites, the primary sites of synaptic input integration and plasticity. Here, we monitored somatic and basal dendritic activity in CA1 pyramidal cells in behaving mice using longitudinal two-photon calcium imaging integrated with simultaneous local field potential recordings. We found immobility was associated with an increase in dendritic activity concentrated during SWRs. Coincident dendritic and somatic activity during SWRs predicted increased coupling during subsequent exploration of a novel environment. In contrast, somatic-dendritic coupling and SWR recruitment varied with cells' tuning distance to reward location during a goal-learning task. Our results connect SWRs with the stabilization of information processing within CA1 neurons and suggest that these mechanisms may be dynamically biased by behavioral demands.
Collapse
Affiliation(s)
- Sebi V Rolotti
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA.
| | - Heike Blockus
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Fraser T Sparks
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - James B Priestley
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
| |
Collapse
|
26
|
Almeida VN. The neural hierarchy of consciousness. Neuropsychologia 2022; 169:108202. [PMID: 35271856 DOI: 10.1016/j.neuropsychologia.2022.108202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 02/25/2022] [Accepted: 03/01/2022] [Indexed: 01/08/2023]
Abstract
The chief undertaking in the studies of consciousness is that of unravelling "the minimal set of neural processes that are together sufficient for the conscious experience of a particular content - the neural correlates of consciousness". To this day, this crusade remains at an impasse, with a clash of two main theories: consciousness may arise either in a graded and cortically-localised fashion, or in an all-or-none and widespread one. In spite of the long-lasting theoretical debates, neurophysiological theories of consciousness have been mostly dissociated from them. Herein, a theoretical review will be put forth with the aim to change that. In its first half, we will cover the hard available evidence on the neurophysiology of consciousness, whereas in its second half we will weave a series of considerations on both theories and substantiate a novel take on conscious awareness: the levels of processing approach, partitioning the conscious architecture into lower- and higher-order, graded and nonlinear.
Collapse
Affiliation(s)
- Victor N Almeida
- Faculdade de Letras, Universidade Federal de Minas Gerais (UFMG), Av. Pres. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31270-901, Brazil.
| |
Collapse
|
27
|
Kirchner JH, Gjorgjieva J. Emergence of synaptic organization and computation in dendrites. NEUROFORUM 2022; 28:21-30. [PMID: 35881644 PMCID: PMC8887907 DOI: 10.1515/nf-2021-0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Single neurons in the brain exhibit astounding computational capabilities, which gradually emerge throughout development and enable them to become integrated into complex neural circuits. These capabilities derive in part from the precise arrangement of synaptic inputs on the neurons' dendrites. While the full computational benefits of this arrangement are still unknown, a picture emerges in which synapses organize according to their functional properties across multiple spatial scales. In particular, on the local scale (tens of microns), excitatory synaptic inputs tend to form clusters according to their functional similarity, whereas on the scale of individual dendrites or the entire tree, synaptic inputs exhibit dendritic maps where excitatory synapse function varies smoothly with location on the tree. The development of this organization is supported by inhibitory synapses, which are carefully interleaved with excitatory synapses and can flexibly modulate activity and plasticity of excitatory synapses. Here, we summarize recent experimental and theoretical research on the developmental emergence of this synaptic organization and its impact on neural computations.
Collapse
Affiliation(s)
- Jan H. Kirchner
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Max-von-Laue-Str. 4, 60438Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, 85354Freising, Germany
| | - Julijana Gjorgjieva
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Max-von-Laue-Str. 4, 60438Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, 85354Freising, Germany
| |
Collapse
|
28
|
Larkum ME, Wu J, Duverdin SA, Gidon A. The guide to dendritic spikes of the mammalian cortex in vitro and in vivo. Neuroscience 2022; 489:15-33. [PMID: 35182699 DOI: 10.1016/j.neuroscience.2022.02.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 02/01/2022] [Accepted: 02/10/2022] [Indexed: 12/23/2022]
Abstract
Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.
Collapse
Affiliation(s)
- Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Cluster, Charité - Universitätsmedizin Berlin, Germany
| | - Jiameng Wu
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Sarah A Duverdin
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Albert Gidon
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| |
Collapse
|
29
|
Barnes SJ, Keller GB, Keck T. Homeostatic regulation through strengthening of neuronal network-correlated synaptic inputs. eLife 2022; 11:81958. [PMID: 36515269 PMCID: PMC9803349 DOI: 10.7554/elife.81958] [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: 07/18/2022] [Accepted: 11/30/2022] [Indexed: 12/15/2022] Open
Abstract
Homeostatic regulation is essential for stable neuronal function. Several synaptic mechanisms of homeostatic plasticity have been described, but the functional properties of synapses involved in homeostasis are unknown. We used longitudinal two-photon functional imaging of dendritic spine calcium signals in visual and retrosplenial cortices of awake adult mice to quantify the sensory deprivation-induced changes in the responses of functionally identified spines. We found that spines whose activity selectively correlated with intrinsic network activity underwent tumor necrosis factor alpha (TNF-α)-dependent homeostatic increases in their response amplitudes, but spines identified as responsive to sensory stimulation did not. We observed an increase in the global sensory-evoked responses following sensory deprivation, despite the fact that the identified sensory inputs did not strengthen. Instead, global sensory-evoked responses correlated with the strength of network-correlated inputs. Our results suggest that homeostatic regulation of global responses is mediated through changes to intrinsic network-correlated inputs rather than changes to identified sensory inputs thought to drive sensory processing.
Collapse
Affiliation(s)
- Samuel J Barnes
- Department of Brain Sciences, Division of Neuroscience, Imperial College London, Hammersmith Hospital CampusLondonUnited Kingdom,UK Dementia Research Institute at Imperial CollegeLondonUnited Kingdom
| | - Georg B Keller
- Friedrich Miescher Institute for Biomedical ResearchBaselSwitzerland
| | - Tara Keck
- Department of Neuroscience, Physiology and Pharmacology, University College LondonLondonUnited Kingdom
| |
Collapse
|
30
|
Suzuki M, Aru J, Larkum ME. Double-μPeriscope, a tool for multilayer optical recordings, optogenetic stimulations or both. eLife 2021; 10:e72894. [PMID: 34878406 PMCID: PMC8654370 DOI: 10.7554/elife.72894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 11/29/2021] [Indexed: 11/28/2022] Open
Abstract
Intelligent behavior and cognitive functions in mammals depend on cortical microcircuits made up of a variety of excitatory and inhibitory cells that form a forest-like complex across six layers. Mechanistic understanding of cortical microcircuits requires both manipulation and monitoring of multiple layers and interactions between them. However, existing techniques are limited as to simultaneous monitoring and stimulation at different depths without damaging a large volume of cortical tissue. Here, we present a relatively simple and versatile method for delivering light to any two cortical layers simultaneously. The method uses a tiny optical probe consisting of two microprisms mounted on a single shaft. We demonstrate the versatility of the probe in three sets of experiments: first, two distinct cortical layers were optogenetically and independently manipulated; second, one layer was stimulated while the activity of another layer was monitored; third, the activity of thalamic axons distributed in two distinct cortical layers was simultaneously monitored in awake mice. Its simple-design, versatility, small-size, and low-cost allow the probe to be applied widely to address important biological questions.
Collapse
Affiliation(s)
- Mototaka Suzuki
- Institute of Biology, Humboldt University of BerlinBerlinGermany
| | - Jaan Aru
- Institute of Biology, Humboldt University of BerlinBerlinGermany
- Institute of Computer Science, University of TartuTartuEstonia
| | - Matthew E Larkum
- Institute of Biology, Humboldt University of BerlinBerlinGermany
| |
Collapse
|
31
|
Corticospinal populations broadcast complex motor signals to coordinated spinal and striatal circuits. Nat Neurosci 2021; 24:1721-1732. [PMID: 34737448 PMCID: PMC8639707 DOI: 10.1038/s41593-021-00939-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 09/10/2021] [Indexed: 11/23/2022]
Abstract
Many models of motor control emphasize the role of sensorimotor cortex in movement, principally through the projections that corticospinal neurons (CSNs) make to the spinal cord. Additionally, CSNs possess expansive supraspinal axon collaterals, the functional organization of which is largely unknown. Using anatomical and electrophysiological circuit-mapping techniques in the mouse, we reveal dorsolateral striatum as the preeminent target of CSN collateral innervation. We found that this innervation is biased so that CSNs targeting different striatal pathways show biased targeting of spinal cord circuits. Contrary to more conventional perspectives, CSNs encode not only individual movements, but also information related to the onset and offset of motor sequences. Furthermore, similar activity patterns are broadcast by CSN populations targeting different striatal circuits. Our results reveal a logic of coordinated connectivity between forebrain and spinal circuits, where separate CSN modules broadcast similarly complex information to downstream circuits, suggesting that differences in postsynaptic connectivity dictate motor specificity.
Collapse
|
32
|
Goetz L, Roth A, Häusser M. Active dendrites enable strong but sparse inputs to determine orientation selectivity. Proc Natl Acad Sci U S A 2021; 118:e2017339118. [PMID: 34301882 PMCID: PMC8325157 DOI: 10.1073/pnas.2017339118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.
Collapse
Affiliation(s)
- Lea Goetz
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Arnd Roth
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| |
Collapse
|
33
|
Stuyt G, Godenzini L, Palmer LM. Local and Global Dynamics of Dendritic Activity in the Pyramidal Neuron. Neuroscience 2021; 489:176-184. [PMID: 34280492 DOI: 10.1016/j.neuroscience.2021.07.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 12/22/2022]
Abstract
There has been increasing interest in the measurement and comparison of activity across compartments of the pyramidal neuron. Dendritic activity can occur both locally, on a single dendritic segment, or globally, involving multiple compartments of the single neuron. Little is known about how these dendritic dynamics shape and contribute to information processing and behavior. Although it has been difficult to characterize local and global activity in vivo due to the technical challenge of simultaneously recording from the entire dendritic arbor and soma, the rise of calcium imaging has driven the increased feasibility and interest of these experiments. However, the distinction between local and global activity made by calcium imaging requires careful consideration. In this review we describe local and global activity, discuss the difficulties and caveats of this distinction, and present the evidence of local and global activity in information processing and behavior.
Collapse
Affiliation(s)
- George Stuyt
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Luca Godenzini
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia.
| |
Collapse
|
34
|
Trautmann EM, O'Shea DJ, Sun X, Marshel JH, Crow A, Hsueh B, Vesuna S, Cofer L, Bohner G, Allen W, Kauvar I, Quirin S, MacDougall M, Chen Y, Whitmire MP, Ramakrishnan C, Sahani M, Seidemann E, Ryu SI, Deisseroth K, Shenoy KV. Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface. Nat Commun 2021; 12:3689. [PMID: 34140486 PMCID: PMC8211867 DOI: 10.1038/s41467-021-23884-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 05/19/2021] [Indexed: 02/05/2023] Open
Abstract
Calcium imaging is a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of fundamental principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon imaging of neuronal calcium signals from macaques engaged in a motor task. By imaging apical dendrites, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signalswhich successfully decoded movement direction online. By fusing two-photon functional imaging with CLARITY volumetric imaging, we verified that many imaged dendrites which contributed to oBCI decoding originated from layer 5 output neurons, including a putative Betz cell. This approach establishes new opportunities for studying motor control and designing BCIs via two photon imaging.
Collapse
Affiliation(s)
- Eric M Trautmann
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
| | - Daniel J O'Shea
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
| | - Xulu Sun
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - James H Marshel
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Ailey Crow
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Brian Hsueh
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA
| | - Sam Vesuna
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Lucas Cofer
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Gergő Bohner
- Gatsby Computational Neuroscience Unit, University College London, London, UK
| | - Will Allen
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA
| | - Isaac Kauvar
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA
| | - Sean Quirin
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Yuzhi Chen
- Center for Perceptual Systems, University of Texas, Austin, TX, USA
- Department of Psychology, University of Texas, Austin, TX, USA
- Department of Neuroscience, University of Texas, Austin, TX, USA
| | - Matthew P Whitmire
- Center for Perceptual Systems, University of Texas, Austin, TX, USA
- Department of Psychology, University of Texas, Austin, TX, USA
- Department of Neuroscience, University of Texas, Austin, TX, USA
| | | | - Maneesh Sahani
- Gatsby Computational Neuroscience Unit, University College London, London, UK
| | - Eyal Seidemann
- Center for Perceptual Systems, University of Texas, Austin, TX, USA
- Department of Psychology, University of Texas, Austin, TX, USA
- Department of Neuroscience, University of Texas, Austin, TX, USA
| | - Stephen I Ryu
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Palo Alto Medical Foundation, Palo Alto, CA, USA
| | - Karl Deisseroth
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA.
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
| | - Krishna V Shenoy
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
- Department of Neurobiology, Stanford University, Stanford, CA, USA.
| |
Collapse
|
35
|
Francioni V, Harnett MT. Rethinking Single Neuron Electrical Compartmentalization: Dendritic Contributions to Network Computation In Vivo. Neuroscience 2021; 489:185-199. [PMID: 34116137 DOI: 10.1016/j.neuroscience.2021.05.038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/11/2021] [Accepted: 05/29/2021] [Indexed: 12/15/2022]
Abstract
Decades of experimental and theoretical work support a now well-established theory that active dendritic processing contributes to the computational power of individual neurons. This theory is based on the high degree of electrical compartmentalization observed in the dendrites of single neurons in ex vivo preparations. Compartmentalization allows dendrites to conduct semi-independent operations on their inputs before final integration and output at the axon, producing a "network-in-a-neuron." However, recent in vivo functional imaging experiments in mouse cortex have reported surprisingly little evidence for strong dendritic compartmentalization. In this review, we contextualize these new findings and discuss their impact on the future of the field. Specifically, we consider how highly coordinated, and thus less compartmentalized, activity in soma and dendrites can contribute to cortical computations including nonlinear mixed selectivity, prediction/expectation, multiplexing, and credit assignment.
Collapse
Affiliation(s)
- Valerio Francioni
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Mark T Harnett
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| |
Collapse
|
36
|
Roth Y. QLCA and Entangled States as Single-Neuron Activity Generators. Front Comput Neurosci 2021; 15:600075. [PMID: 34149386 PMCID: PMC8206504 DOI: 10.3389/fncom.2021.600075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 04/16/2021] [Indexed: 11/15/2022] Open
Abstract
Each neuron in the central nervous system has many dendrites, which provide input information through impulses. Assuming that a neuron's decision to continue or stop firing is made by rules applied to the dendrites' inputs, we associate neuron activity with a quantum like-cellular automaton (QLCA) concepts. Following a previous study that related the CA description with entangled states, we provide a quantum-like description of neuron activity. After reviewing and presenting the entanglement concept expressed by QLCA terminology, we propose a model that relates quantum-like measurement to consciousness. Then, we present a toy model that reviews the QLCA theory, which is adapted to our terminology. The study also focuses on implementing QLCA formalism to describe a single neuron activity.
Collapse
Affiliation(s)
- Yehuda Roth
- Oranim Academic College, Science Department, Kiryat Tiv'on, Israel
| |
Collapse
|
37
|
Duan CA, Pan Y, Ma G, Zhou T, Zhang S, Xu NL. A cortico-collicular pathway for motor planning in a memory-dependent perceptual decision task. Nat Commun 2021; 12:2727. [PMID: 33976124 PMCID: PMC8113349 DOI: 10.1038/s41467-021-22547-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 03/19/2021] [Indexed: 11/09/2022] Open
Abstract
Survival in a dynamic environment requires animals to plan future actions based on past sensory evidence, known as motor planning. However, the neuronal circuits underlying this crucial brain function remain elusive. Here, we employ projection-specific imaging and perturbation methods to investigate the direct pathway linking two key nodes in the motor planning network, the secondary motor cortex (M2) and the midbrain superior colliculus (SC), in mice performing a memory-dependent perceptual decision task. We find dynamic coding of choice information in SC-projecting M2 neurons during motor planning and execution, and disruption of this information by inhibiting M2 terminals in SC selectively impaired decision maintenance. Furthermore, we show that while both excitatory and inhibitory SC neurons receive synaptic inputs from M2, these SC subpopulations display differential temporal patterns in choice coding during behavior. Our results reveal the dynamic recruitment of the premotor-collicular pathway as a circuit mechanism for motor planning. Duan, Pan et al. find that the premotor cortex cooperates with the midbrain superior colliculus via direct projections to implement decision maintenance. These results reveal mechanisms of cortico-collicular interaction during cognition and action in a pathway- and cell-type-specific manner.
Collapse
Affiliation(s)
- Chunyu A Duan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
| | - Yuxin Pan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Guofen Ma
- Collaborative Innovation Center for Brain Science, Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Taotao Zhou
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Siyu Zhang
- Collaborative Innovation Center for Brain Science, Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ning-Long Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China. .,University of Chinese Academy of Sciences, Beijing, China. .,Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
| |
Collapse
|
38
|
Temporally multiplexed dual-plane imaging of neural activity with four-dimensional precision. Neurosci Res 2021; 171:9-18. [PMID: 33607170 DOI: 10.1016/j.neures.2021.02.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 02/05/2021] [Accepted: 02/07/2021] [Indexed: 11/20/2022]
Abstract
Spatiotemporal patterns of neural activity generate brain functions, such as perception, memory, and behavior. Four-dimensional (4-D: x, y, z, t) analyses of such neural activity will facilitate understanding of brain functions. However, conventional two-photon microscope systems observe single-plane brain tissue alone at a time with cellular resolution. It faces a trade-off between the spatial resolution in the x-, y-, and z-axes and the temporal resolution by a limited point-by-point scan speed. To overcome this trade-off in 4-D imaging, we developed a holographic two-photon microscope for dual-plane imaging. A spatial light modulator (SLM) provided an additional focal plane at a different depth. Temporal multiplexing of split lasers with an optical chopper allowed fast imaging of two different focal planes. We simultaneously recorded the activities of neurons on layers 2/3 and 5 of the cerebral cortex in awake mice in vivo. The present study demonstrated the proof-of-concept of dual-plane two-photon imaging of neural circuits by using the temporally multiplexed SLM-based microscope. The temporally multiplexed holographic microscope, combined with in vivo labeling with genetically encoded probes, enabled 4-D imaging and analysis of neural activities at cellular resolution and physiological timescales. Large-scale 4-D imaging and analysis will facilitate studies of not only the nervous system but also of various biological systems.
Collapse
|
39
|
Doron G, Shin JN, Takahashi N, Drüke M, Bocklisch C, Skenderi S, de Mont L, Toumazou M, Ledderose J, Brecht M, Naud R, Larkum ME. Perirhinal input to neocortical layer 1 controls learning. Science 2021; 370:370/6523/eaaz3136. [PMID: 33335033 DOI: 10.1126/science.aaz3136] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 08/27/2020] [Accepted: 10/23/2020] [Indexed: 12/28/2022]
Abstract
Hippocampal output influences memory formation in the neocortex, but this process is poorly understood because the precise anatomical location and the underlying cellular mechanisms remain elusive. Here, we show that perirhinal input, predominantly to sensory cortical layer 1 (L1), controls hippocampal-dependent associative learning in rodents. This process was marked by the emergence of distinct firing responses in defined subpopulations of layer 5 (L5) pyramidal neurons whose tuft dendrites receive perirhinal inputs in L1. Learning correlated with burst firing and the enhancement of dendritic excitability, and it was suppressed by disruption of dendritic activity. Furthermore, bursts, but not regular spike trains, were sufficient to retrieve learned behavior. We conclude that hippocampal information arriving at L5 tuft dendrites in neocortical L1 mediates memory formation in the neocortex.
Collapse
Affiliation(s)
- Guy Doron
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany.
| | - Jiyun N Shin
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Naoya Takahashi
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Moritz Drüke
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Christina Bocklisch
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Salina Skenderi
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Lisa de Mont
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Maria Toumazou
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Julia Ledderose
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany
| | - Michael Brecht
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, D-10115 Berlin, Germany.,NeuroCure Cluster, Charité - Universitätsmedizin Berlin, D-10117 Berlin, Germany
| | - Richard Naud
- University of Ottawa Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada.,Department of Physics, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, D-10117 Berlin, Germany. .,NeuroCure Cluster, Charité - Universitätsmedizin Berlin, D-10117 Berlin, Germany
| |
Collapse
|
40
|
Flossmann T, Rochefort NL. Spatial navigation signals in rodent visual cortex. Curr Opin Neurobiol 2020; 67:163-173. [PMID: 33360769 DOI: 10.1016/j.conb.2020.11.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022]
Abstract
During navigation, animals integrate sensory information with body movements to guide actions. The impact of both navigational and movement-related signals on cortical visual information processing remains largely unknown. We review recent studies in awake rodents that have revealed navigation-related signals in the primary visual cortex (V1) including speed, distance travelled and head-orienting movements. Both cortical and subcortical inputs convey self-motion related information to V1 neurons: for example, top-down inputs from secondary motor and retrosplenial cortices convey information about head movements and spatial expectations. Within V1, subtypes of inhibitory neurons are critical for the integration of navigation-related and visual signals. We conclude with potential functional roles of navigation-related signals in V1 including gain control, motor error signals and predictive coding.
Collapse
Affiliation(s)
- Tom Flossmann
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom.
| |
Collapse
|
41
|
Yang JQ, Wang R, Ren Y, Mao JY, Wang ZP, Zhou Y, Han ST. Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2020; 32:e2003610. [PMID: 33165986 DOI: 10.1002/adma.202003610] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/27/2020] [Indexed: 06/11/2023]
Abstract
The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike-based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain-like computing.
Collapse
Affiliation(s)
- Jia-Qin Yang
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ruopeng Wang
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yi Ren
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Jing-Yu Mao
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Zhan-Peng Wang
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Su-Ting Han
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| |
Collapse
|
42
|
Popescu IR, Le KQ, Ducote AL, Li JE, Leland AE, Mostany R. Increased intrinsic excitability and decreased synaptic inhibition in aged somatosensory cortex pyramidal neurons. Neurobiol Aging 2020; 98:88-98. [PMID: 33249377 DOI: 10.1016/j.neurobiolaging.2020.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 09/02/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022]
Abstract
Sensorimotor performance declines during advanced age, partially due to deficits in somatosensory acuity. Cortical receptive field expansion contributes to somatosensory deficits, suggesting increased excitability or decreased inhibition in primary somatosensory cortex (S1) pyramidal neurons. To ascertain changes in excitability and inhibition, we measured both properties in neurons from vibrissal S1 in brain slices from young and aged mice. Because adapting and non-adapting neurons-the principal pyramidal types in layer 5 (L5)-differ in intrinsic properties and inhibitory inputs, we determined age-dependent changes according to neuron type. We found an age-dependent increase in intrinsic excitability in adapting neurons, caused by a decrease in action potential threshold. Surprisingly, in non-adapting neurons we found both an increase in excitability caused by increased input resistance, and a decrease in synaptic inhibition. Spike frequency adaptation, already small in non-adapting neurons, was further reduced by aging, whereas sag, a manifestation of Ih, was increased. Therefore, aging caused both decreased inhibition and increased intrinsic excitability, but these effects were specific to pyramidal neuron type.
Collapse
Affiliation(s)
- Ion R Popescu
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA.
| | - Kathy Q Le
- Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | - Alexis L Ducote
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA; Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | - Jennifer E Li
- Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | | | - Ricardo Mostany
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA; Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| |
Collapse
|
43
|
Mueller M, Egger V. Dendritic integration in olfactory bulb granule cells upon simultaneous multispine activation: Low thresholds for nonlocal spiking activity. PLoS Biol 2020; 18:e3000873. [PMID: 32966273 PMCID: PMC7535128 DOI: 10.1371/journal.pbio.3000873] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 10/05/2020] [Accepted: 08/24/2020] [Indexed: 11/18/2022] Open
Abstract
The inhibitory axonless olfactory bulb granule cells form reciprocal dendrodendritic synapses with mitral and tufted cells via large spines, mediating recurrent and lateral inhibition. As a case in point for dendritic transmitter release, rat granule cell dendrites are highly excitable, featuring local Na+ spine spikes and global Ca2+- and Na+-spikes. To investigate the transition from local to global signaling, we performed holographic, simultaneous 2-photon uncaging of glutamate at up to 12 granule cell spines, along with whole-cell recording and dendritic 2-photon Ca2+ imaging in acute juvenile rat brain slices. Coactivation of less than 10 reciprocal spines was sufficient to generate diverse regenerative signals that included regional dendritic Ca2+-spikes and dendritic Na+-spikes (D-spikes). Global Na+-spikes could be triggered in one third of granule cells. Individual spines and dendritic segments sensed the respective signal transitions as increments in Ca2+ entry. Dendritic integration as monitored by the somatic membrane potential was mostly linear until a threshold number of spines was activated, at which often D-spikes along with supralinear summation set in. As to the mechanisms supporting active integration, NMDA receptors (NMDARs) strongly contributed to all aspects of supralinearity, followed by dendritic voltage-gated Na+- and Ca2+-channels, whereas local Na+ spine spikes, as well as morphological variables, barely mattered. Because of the low numbers of coactive spines required to trigger dendritic Ca2+ signals and thus possibly lateral release of GABA onto mitral and tufted cells, we predict that thresholds for granule cell-mediated bulbar lateral inhibition are low. Moreover, D-spikes could provide a plausible substrate for granule cell-mediated gamma oscillations.
Collapse
Affiliation(s)
- Max Mueller
- Neurophysiology, Institute of Zoology, Universität Regensburg, Regensburg, Germany
| | - Veronica Egger
- Neurophysiology, Institute of Zoology, Universität Regensburg, Regensburg, Germany
| |
Collapse
|
44
|
Qin Z, Chen C, He S, Wang Y, Tam KF, Ip NY, Qu JY. Adaptive optics two-photon endomicroscopy enables deep-brain imaging at synaptic resolution over large volumes. SCIENCE ADVANCES 2020; 6:6/40/eabc6521. [PMID: 32998883 PMCID: PMC7527232 DOI: 10.1126/sciadv.abc6521] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/11/2020] [Indexed: 05/02/2023]
Abstract
Optical deep-brain imaging in vivo at high resolution has remained a great challenge over the decades. Two-photon endomicroscopy provides a minimally invasive approach to image buried brain structures, once it is integrated with a gradient refractive index (GRIN) lens embedded in the brain. However, its imaging resolution and field of view are compromised by the intrinsic aberrations of the GRIN lens. Here, we develop a two-photon endomicroscopy by adding adaptive optics based on direct wavefront sensing, which enables recovery of diffraction-limited resolution in deep-brain imaging. A new precompensation strategy plays a critical role to correct aberrations over large volumes and achieve rapid random-access multiplane imaging. We investigate the neuronal plasticity in the hippocampus, a critical deep brain structure, and reveal the relationship between the somatic and dendritic activity of pyramidal neurons.
Collapse
Affiliation(s)
- Zhongya Qin
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Congping Chen
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Sicong He
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| | - Ye Wang
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Kam Fai Tam
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Nancy Y Ip
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China.
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P.R. China
| | - Jianan Y Qu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China.
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, P. R. China
| |
Collapse
|
45
|
Aru J, Suzuki M, Larkum ME. Cellular Mechanisms of Conscious Processing. Trends Cogn Sci 2020; 24:814-825. [PMID: 32855048 DOI: 10.1016/j.tics.2020.07.006] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/16/2020] [Accepted: 07/21/2020] [Indexed: 01/08/2023]
Abstract
Recent breakthroughs in neurobiology indicate that the time is ripe to understand how cellular-level mechanisms are related to conscious experience. Here, we highlight the biophysical properties of pyramidal cells, which allow them to act as gates that control the evolution of global activation patterns. In conscious states, this cellular mechanism enables complex sustained dynamics within the thalamocortical system, whereas during unconscious states, such signal propagation is prohibited. We suggest that the hallmark of conscious processing is the flexible integration of bottom-up and top-down data streams at the cellular level. This cellular integration mechanism provides the foundation for Dendritic Information Theory, a novel neurobiological theory of consciousness.
Collapse
Affiliation(s)
- Jaan Aru
- Institute of Biology, Humboldt University of Berlin, Berlin, Germany; Institute of Computer Science, University of Tartu, Tartu, Estonia.
| | - Mototaka Suzuki
- Institute of Biology, Humboldt University of Berlin, Berlin, Germany
| | - Matthew E Larkum
- Institute of Biology, Humboldt University of Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin, Berlin, Germany.
| |
Collapse
|
46
|
Inhibitory plasticity in layer 1 - dynamic gatekeeper of neocortical associations. Curr Opin Neurobiol 2020; 67:26-33. [PMID: 32818814 DOI: 10.1016/j.conb.2020.06.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 06/24/2020] [Accepted: 06/25/2020] [Indexed: 11/22/2022]
Abstract
Neocortical layer 1 is a major site of convergence for a variety of brain wide afferents carrying experience-dependent top-down information, which are integrated and processed in the apical tuft dendrites of pyramidal cells. Two types of local inhibitory interneurons, Martinotti cells and layer 1 interneurons, dominantly shape dendritic integration, and work from recent years has significantly advanced our understanding of the role of these interneurons in circuit plasticity and learning. Both cell types instruct plasticity in local pyramidal cells, and are themselves subject to robust plastic changes. Despite these similarities, the emerging hypothesis is that they fulfill different, and potentially opposite roles, as they receive different inputs, employ distinct inhibitory dynamics and are implicated in different behavioral contexts.
Collapse
|
47
|
Takahashi N, Ebner C, Sigl-Glöckner J, Moberg S, Nierwetberg S, Larkum ME. Active dendritic currents gate descending cortical outputs in perception. Nat Neurosci 2020; 23:1277-1285. [DOI: 10.1038/s41593-020-0677-8] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 06/23/2020] [Indexed: 12/27/2022]
|
48
|
A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2020; 2020:2710561. [PMID: 32405292 PMCID: PMC7201754 DOI: 10.1155/2020/2710561] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 11/12/2019] [Accepted: 12/30/2019] [Indexed: 11/24/2022]
Abstract
A dendritic neuron model with adaptive synapses (DMASs) based on differential evolution (DE) algorithm training is proposed. According to the signal transmission order, a DNM can be divided into four parts: the synaptic layer, dendritic layer, membrane layer, and somatic cell layer. It can be converted to a logic circuit that is easily implemented on hardware by removing useless synapses and dendrites after training. This logic circuit can be designed to solve complex nonlinear problems using only four basic logical devices: comparators, AND (conjunction), OR (disjunction), and NOT (negation). To obtain a faster and better solution, we adopt the most popular DE for DMAS training. We have chosen five classification datasets from the UCI Machine Learning Repository for an experiment. We analyze and discuss the experimental results in terms of the correct rate, convergence rate, ROC curve, and the cross-validation and then compare the results with a dendritic neuron model trained by the backpropagation algorithm (BP-DNM) and a neural network trained by the backpropagation algorithm (BPNN). The analysis results show that the DE-DMAS shows better performance in all aspects.
Collapse
|
49
|
Voigts J, Harnett MT. Somatic and Dendritic Encoding of Spatial Variables in Retrosplenial Cortex Differs during 2D Navigation. Neuron 2020; 105:237-245.e4. [PMID: 31759808 PMCID: PMC6981016 DOI: 10.1016/j.neuron.2019.10.016] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 08/14/2019] [Accepted: 10/09/2019] [Indexed: 12/21/2022]
Abstract
Active amplification of organized synaptic inputs in dendrites can endow individual neurons with the ability to perform complex computations. However, whether dendrites in behaving animals perform independent local computations is not known. Such activity may be particularly important for complex behavior, where neurons integrate multiple streams of information. Head-restrained imaging has yielded important insights into cellular and circuit function, but this approach limits behavior and the underlying computations. We describe a method for full-featured 2-photon imaging in awake mice during free locomotion with volitional head rotation. We examine head direction and position encoding in simultaneously imaged apical tuft dendrites and their respective cell bodies in retrosplenial cortex, an area that encodes multi-modal navigational information. Activity in dendrites was not determined solely by somatic activity but reflected distinct navigational variables, fulfilling the requirements for dendritic computation. Our approach provides a foundation for studying sub-cellular processes during complex behaviors.
Collapse
Affiliation(s)
- Jakob Voigts
- Department of Brain & Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mark T Harnett
- Department of Brain & Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| |
Collapse
|
50
|
Francioni V, Padamsey Z, Rochefort NL. High and asymmetric somato-dendritic coupling of V1 layer 5 neurons independent of visual stimulation and locomotion. eLife 2019; 8:e49145. [PMID: 31880536 PMCID: PMC6974354 DOI: 10.7554/elife.49145] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 12/22/2019] [Indexed: 12/28/2022] Open
Abstract
Active dendrites impact sensory processing and behaviour. However, it remains unclear how active dendritic integration relates to somatic output in vivo. We imaged semi-simultaneously GCaMP6s signals in the soma, trunk and distal tuft dendrites of layer 5 pyramidal neurons in the awake mouse primary visual cortex. We found that apical tuft signals were dominated by widespread, highly correlated calcium transients throughout the tuft. While these signals were highly coupled to trunk and somatic transients, the frequency of calcium transients was found to decrease in a distance-dependent manner from soma to tuft. Ex vivo recordings suggest that low-frequency back-propagating action potentials underlie the distance-dependent loss of signals, while coupled somato-dendritic signals can be triggered by high-frequency somatic bursts or strong apical tuft depolarization. Visual stimulation and locomotion increased neuronal activity without affecting somato-dendritic coupling. High, asymmetric somato-dendritic coupling is therefore a widespread feature of layer 5 neurons activity in vivo.
Collapse
Affiliation(s)
- Valerio Francioni
- Centre for Discovery Brain Sciences, Edinburgh Medical School, Biomedical SciencesUniversity of EdinburghEdinburghUnited Kingdom
- Simons Initiative for the Developing BrainUniversity of EdinburghEdinburghUnited Kingdom
| | - Zahid Padamsey
- Centre for Discovery Brain Sciences, Edinburgh Medical School, Biomedical SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, Edinburgh Medical School, Biomedical SciencesUniversity of EdinburghEdinburghUnited Kingdom
- Simons Initiative for the Developing BrainUniversity of EdinburghEdinburghUnited Kingdom
| |
Collapse
|