1
|
Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. Perirhinal cortex learns a predictive map of the task environment. Nat Commun 2024; 15:5544. [PMID: 38956015 PMCID: PMC11219840 DOI: 10.1038/s41467-024-47365-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 03/25/2024] [Indexed: 07/04/2024] Open
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
Collapse
Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA.
| |
Collapse
|
2
|
Ostojic S, Fusi S. Computational role of structure in neural activity and connectivity. Trends Cogn Sci 2024; 28:677-690. [PMID: 38553340 DOI: 10.1016/j.tics.2024.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 07/05/2024]
Abstract
One major challenge of neuroscience is identifying structure in seemingly disorganized neural activity. Different types of structure have different computational implications that can help neuroscientists understand the functional role of a particular brain area. Here, we outline a unified approach to characterize structure by inspecting the representational geometry and the modularity properties of the recorded activity and show that a similar approach can also reveal structure in connectivity. We start by setting up a general framework for determining geometry and modularity in activity and connectivity and relating these properties with computations performed by the network. We then use this framework to review the types of structure found in recent studies of model networks performing three classes of computations.
Collapse
Affiliation(s)
- Srdjan Ostojic
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL Research University, 75005 Paris, France.
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Department of Neuroscience, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA
| |
Collapse
|
3
|
Chang YT, Finkel EA, Xu D, O'Connor DH. Rule-based modulation of a sensorimotor transformation across cortical areas. eLife 2024; 12:RP92620. [PMID: 38842277 PMCID: PMC11156468 DOI: 10.7554/elife.92620] [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] [Indexed: 06/07/2024] Open
Abstract
Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes and uses rule information to guide behavior. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task where they switched between two rules: licking in response to tactile stimuli while rejecting visual stimuli, or vice versa. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, single-neuron activity distinguished between the two rules both prior to and in response to the tactile stimulus. We hypothesized that neural populations in these areas would show rule-dependent preparatory states, which would shape the subsequent sensory processing and behavior. This hypothesis was supported for the motor cortical areas (MM and ALM) by findings that (1) the current task rule could be decoded from pre-stimulus population activity; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states impaired task performance. Our findings indicate that flexible action selection in response to sensory input can occur via configuration of preparatory states in the motor cortex.
Collapse
Affiliation(s)
- Yi-Ting Chang
- Solomon H. Snyder Department of Neuroscience, Kavli Neuroscience Discovery Institute, Brain Science Institute, Johns Hopkins University School of MedicineBaltimoreUnited States
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
| | - Eric A Finkel
- Solomon H. Snyder Department of Neuroscience, Kavli Neuroscience Discovery Institute, Brain Science Institute, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Duo Xu
- Solomon H. Snyder Department of Neuroscience, Kavli Neuroscience Discovery Institute, Brain Science Institute, Johns Hopkins University School of MedicineBaltimoreUnited States
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
| | - Daniel H O'Connor
- Solomon H. Snyder Department of Neuroscience, Kavli Neuroscience Discovery Institute, Brain Science Institute, Johns Hopkins University School of MedicineBaltimoreUnited States
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
| |
Collapse
|
4
|
Zhu M, Kuhlman SJ, Barth AL. Transient enhancement of stimulus-evoked activity in neocortex during sensory learning. Learn Mem 2024; 31:a053870. [PMID: 38955432 PMCID: PMC11261211 DOI: 10.1101/lm.053870.123] [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: 09/15/2023] [Accepted: 05/07/2024] [Indexed: 07/04/2024]
Abstract
Synaptic potentiation has been linked to learning in sensory cortex, but the connection between this potentiation and increased sensory-evoked neural activity is not clear. Here, we used longitudinal in vivo Ca2+ imaging in the barrel cortex of awake mice to test the hypothesis that increased excitatory synaptic strength during the learning of a whisker-dependent sensory-association task would be correlated with enhanced stimulus-evoked firing. To isolate stimulus-evoked responses from dynamic, task-related activity, imaging was performed outside of the training context. Although prior studies indicate that multiwhisker stimuli drive robust subthreshold activity, we observed sparse activation of L2/3 pyramidal (Pyr) neurons in both control and trained mice. Despite evidence for excitatory synaptic strengthening at thalamocortical and intracortical synapses in this brain area at the onset of learning-indeed, under our imaging conditions thalamocortical axons were robustly activated-we observed that L2/3 Pyr neurons in somatosensory (barrel) cortex displayed only modest increases in stimulus-evoked activity that were concentrated at the onset of training. Activity renormalized over longer training periods. In contrast, when stimuli and rewards were uncoupled in a pseudotraining paradigm, stimulus-evoked activity in L2/3 Pyr neurons was significantly suppressed. These findings indicate that sensory-association training but not sensory stimulation without coupled rewards may briefly enhance sensory-evoked activity, a phenomenon that might help link sensory input to behavioral outcomes at the onset of learning.
Collapse
Affiliation(s)
- Mo Zhu
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Sandra J Kuhlman
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Alison L Barth
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| |
Collapse
|
5
|
Chang YT, Finkel EA, Xu D, O'Connor DH. Rule-based modulation of a sensorimotor transformation across cortical areas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.21.554194. [PMID: 37662301 PMCID: PMC10473613 DOI: 10.1101/2023.08.21.554194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes rule information and uses this information to guide behavioral responses to sensory stimuli. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task in which they switched between two rules in different blocks of trials: licking in response to tactile stimuli applied to a whisker while rejecting visual stimuli, or licking to visual stimuli while rejecting the tactile stimuli. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, the single-trial activity of individual neurons distinguished between the two rules both prior to and in response to the tactile stimulus. Variable rule-dependent responses to identical stimuli could in principle occur via appropriate configuration of pre-stimulus preparatory states of a neural population, which would shape the subsequent response. We hypothesized that neural populations in S1, S2, MM and ALM would show preparatory activity states that were set in a rule-dependent manner to cause processing of sensory information according to the current rule. This hypothesis was supported for the motor cortical areas by findings that (1) the current task rule could be decoded from pre-stimulus population activity in ALM and MM; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states within ALM and MM impaired task performance. Our findings indicate that flexible selection of an appropriate action in response to a sensory input can occur via configuration of preparatory states in the motor cortex.
Collapse
|
6
|
Taub DG, Jiang Q, Pietrafesa F, Su J, Carroll A, Greene C, Blanchard MR, Jain A, El-Rifai M, Callen A, Yager K, Chung C, He Z, Chen C, Woolf CJ. The secondary somatosensory cortex gates mechanical and heat sensitivity. Nat Commun 2024; 15:1289. [PMID: 38346995 PMCID: PMC10861531 DOI: 10.1038/s41467-024-45729-7] [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: 06/13/2023] [Accepted: 02/01/2024] [Indexed: 02/15/2024] Open
Abstract
The cerebral cortex is vital for the processing and perception of sensory stimuli. In the somatosensory axis, information is received primarily by two distinct regions, the primary (S1) and secondary (S2) somatosensory cortices. Top-down circuits stemming from S1 can modulate mechanical and cooling but not heat stimuli such that circuit inhibition causes blunted perception. This suggests that responsiveness to particular somatosensory stimuli occurs in a modality specific fashion and we sought to determine additional cortical substrates. In this work, we identify in a mouse model that inhibition of S2 output increases mechanical and heat, but not cooling sensitivity, in contrast to S1. Combining 2-photon anatomical reconstruction with chemogenetic inhibition of specific S2 circuits, we discover that S2 projections to the secondary motor cortex (M2) govern mechanical and heat sensitivity without affecting motor performance or anxiety. Taken together, we show that S2 is an essential cortical structure that governs mechanical and heat sensitivity.
Collapse
Affiliation(s)
- Daniel G Taub
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Qiufen Jiang
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Francesca Pietrafesa
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Junfeng Su
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Aloe Carroll
- College of Sciences, Northeastern University, Boston, MA, USA
| | - Caitlin Greene
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Aakanksha Jain
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Mahmoud El-Rifai
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Alexis Callen
- Morrissey College of Arts and Sciences, Boston College, Chestnut Hill, MA, USA
| | - Katherine Yager
- Morrissey College of Arts and Sciences, Boston College, Chestnut Hill, MA, USA
| | - Clara Chung
- Department of Neuroscience, Boston University, Boston, MA, USA
| | - Zhigang He
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Chinfei Chen
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Clifford J Woolf
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
7
|
Ryan L, Sun-Yan A, Laughton M, Peron S. Cortical circuitry mediating interareal touch signal amplification. Cell Rep 2023; 42:113532. [PMID: 38064338 PMCID: PMC10842872 DOI: 10.1016/j.celrep.2023.113532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/29/2023] [Accepted: 11/16/2023] [Indexed: 12/19/2023] Open
Abstract
Sensory cortical areas are organized into topographic maps representing the sensory epithelium. Interareal projections typically connect topographically matched subregions across areas. Because matched subregions process the same stimulus, their interaction is central to many computations. Here, we ask how topographically matched subregions of primary and secondary vibrissal somatosensory cortices (vS1 and vS2) interact during active touch. Volumetric calcium imaging in mice palpating an object with two whiskers revealed a sparse population of highly responsive, broadly tuned touch neurons especially pronounced in layer 2 of both areas. These rare neurons exhibited elevated synchrony and carried most touch-evoked activity in both directions. Lesioning the subregion of either area responding to the spared whiskers degraded touch responses in the unlesioned area, with whisker-specific vS1 lesions degrading whisker-specific vS2 touch responses. Thus, a sparse population of broadly tuned touch neurons dominates vS1-vS2 communication in both directions, and topographically matched vS1 and vS2 subregions recurrently amplify whisker touch activity.
Collapse
Affiliation(s)
- Lauren Ryan
- Center for Neural Science, New York University, 4 Washington Place, Rm. 621, New York, NY 10003, USA
| | - Andrew Sun-Yan
- Center for Neural Science, New York University, 4 Washington Place, Rm. 621, New York, NY 10003, USA
| | - Maya Laughton
- Center for Neural Science, New York University, 4 Washington Place, Rm. 621, New York, NY 10003, USA
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Place, Rm. 621, New York, NY 10003, USA.
| |
Collapse
|
8
|
Bai P, Liu Y, Yang L, Ding W, Mondal P, Sang N, Liu G, Lu X, Ho TT, Zhou Y, Wu R, Birar VC, Wilks MQ, Tanzi RE, Lin H, Zhang C, Li W, Shen S, Wang C. Development and Pharmacochemical Characterization Discover a Novel Brain-Permeable HDAC11-Selective Inhibitor with Therapeutic Potential by Regulating Neuroinflammation in Mice. J Med Chem 2023; 66:16075-16090. [PMID: 37972387 DOI: 10.1021/acs.jmedchem.3c01491] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Recent studies have shown that the epigenetic protein histone deacetylase 11 (HDAC11) is highly expressed in the brain and critically modulates neuroimmune functions, making it a potential therapeutic target for neurological disorders. Herein, we report the development of PB94, which is a novel HDAC11 inhibitor. PB94 exhibited potency and selectivity against HDAC11 with IC50 = 108 nM and >40-fold selectivity over other HDAC isoforms. Pharmacokinetic/pharmacodynamic evaluation indicated that PB94 possesses promising drug-like properties. Additionally, PB94 was radiolabeled with carbon-11 as [11C]PB94 for positron emission tomography (PET), which revealed significant brain uptake and metabolic properties suitable for drug development in live animals. Furthermore, we demonstrated that neuropathic pain was associated with brain upregulation of HDAC11 and that pharmacological inhibition of HDAC11 by PB94 ameliorated neuropathic pain in a mouse model. Collectively, our findings support further development of PB94 as a selective HDAC11 inhibitor for neurological indications, including pain.
Collapse
Affiliation(s)
- Ping Bai
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Institute of Respiratory Health, Targeted Tracer Research and Development Laboratory, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan 610041, China
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Chengdu, Sichuan 610041, China
| | - Yan Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Liuyue Yang
- Department of Anesthesia, Critical Care and Pain Medicine Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Weihua Ding
- Department of Anesthesia, Critical Care and Pain Medicine Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Prasenjit Mondal
- Genetics and Aging Research Unit, McCance Center for Brain Health, MassGeneral Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 114 16th Street, Charlestown, Massachusetts 02129, United States
| | - Na Sang
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Institute of Respiratory Health, Targeted Tracer Research and Development Laboratory, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan 610041, China
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Chengdu, Sichuan 610041, China
| | - Gang Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, People's Republic of China
| | - Xiaoxia Lu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, People's Republic of China
| | - Thanh Tu Ho
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Yanting Zhou
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Institute of Respiratory Health, Targeted Tracer Research and Development Laboratory, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan 610041, China
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Chengdu, Sichuan 610041, China
| | - Rui Wu
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Institute of Respiratory Health, Targeted Tracer Research and Development Laboratory, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan 610041, China
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Chengdu, Sichuan 610041, China
| | - Vishal C Birar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Moses Q Wilks
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit, McCance Center for Brain Health, MassGeneral Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 114 16th Street, Charlestown, Massachusetts 02129, United States
| | - Hening Lin
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
- Howard Hughes Medical Institute; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Can Zhang
- Genetics and Aging Research Unit, McCance Center for Brain Health, MassGeneral Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 114 16th Street, Charlestown, Massachusetts 02129, United States
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Institute of Respiratory Health, Targeted Tracer Research and Development Laboratory, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan 610041, China
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Chengdu, Sichuan 610041, China
| | - Shiqian Shen
- Department of Anesthesia, Critical Care and Pain Medicine Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Changning Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| |
Collapse
|
9
|
Chia XW, Tan JK, Ang LF, Kamigaki T, Makino H. Emergence of cortical network motifs for short-term memory during learning. Nat Commun 2023; 14:6869. [PMID: 37898638 PMCID: PMC10613236 DOI: 10.1038/s41467-023-42609-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 10/16/2023] [Indexed: 10/30/2023] Open
Abstract
Learning of adaptive behaviors requires the refinement of coordinated activity across multiple brain regions. However, how neural communications develop during learning remains poorly understood. Here, using two-photon calcium imaging, we simultaneously recorded the activity of layer 2/3 excitatory neurons in eight regions of the mouse dorsal cortex during learning of a delayed-response task. Across learning, while global functional connectivity became sparser, there emerged a subnetwork comprising of neurons in the anterior lateral motor cortex (ALM) and posterior parietal cortex (PPC). Neurons in this subnetwork shared a similar choice code during action preparation and formed recurrent functional connectivity across learning. Suppression of PPC activity disrupted choice selectivity in ALM and impaired task performance. Recurrent neural networks reconstructed from ALM activity revealed that PPC-ALM interactions rendered choice-related attractor dynamics more stable. Thus, learning constructs cortical network motifs by recruiting specific inter-areal communication channels to promote efficient and robust sensorimotor transformation.
Collapse
Affiliation(s)
- Xin Wei Chia
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Jian Kwang Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Lee Fang Ang
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Tsukasa Kamigaki
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Hiroshi Makino
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
| |
Collapse
|
10
|
Safaai H, Wang AY, Kira S, Malerba SB, Panzeri S, Harvey CD. Specialized structure of neural population codes in parietal cortex outputs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.24.554635. [PMID: 37662297 PMCID: PMC10473762 DOI: 10.1101/2023.08.24.554635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Do cortical neurons that send axonal projections to the same target area form specialized population codes for transmitting information? We used calcium imaging in mouse posterior parietal cortex (PPC), retrograde labeling, and statistical multivariate models to address this question during a delayed match-to-sample task. We found that PPC broadcasts sensory, choice, and locomotion signals widely, but sensory information is enriched in the output to anterior cingulate cortex. Neurons projecting to the same area have elevated pairwise activity correlations. These correlations are structured as information-limiting and information-enhancing interaction networks that collectively enhance information levels. This network structure is unique to sub-populations projecting to the same target and strikingly absent in surrounding neural populations with unidentified projections. Furthermore, this structure is only present when mice make correct, but not incorrect, behavioral choices. Therefore, cortical neurons comprising an output pathway form uniquely structured population codes that enhance information transmission to guide accurate behavior.
Collapse
Affiliation(s)
- Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, USA
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alice Y. Wang
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Simone Blanco Malerba
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | | |
Collapse
|
11
|
Taub DG, Jiang Q, Pietrafesa F, Su J, Greene C, Blanchard MR, Jain A, El-Rifai M, Callen A, Yager K, Chung C, He Z, Chen C, Woolf CJ. The Secondary Somatosensory Cortex Gates Mechanical and Thermal Sensitivity. RESEARCH SQUARE 2023:rs.3.rs-2976953. [PMID: 37461707 PMCID: PMC10350168 DOI: 10.21203/rs.3.rs-2976953/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/23/2023]
Abstract
The cerebral cortex is vital for the perception and processing of sensory stimuli. In the somatosensory axis, information is received by two distinct regions, the primary (S1) and secondary (S2) somatosensory cortices. Top-down circuits stemming from S1 can modulate mechanical and cooling but not heat stimuli such that circuit inhibition causes blunted mechanical and cooling perception. Using optogenetics and chemogenetics, we find that in contrast to S1, an inhibition of S2 output increases mechanical and heat, but not cooling sensitivity. Combining 2-photon anatomical reconstruction with chemogenetic inhibition of specific S2 circuits, we discover that S2 projections to the secondary motor cortex (M2) govern mechanical and thermal sensitivity without affecting motor or cognitive function. This suggests that while S2, like S1, encodes specific sensory information, that S2 operates through quite distinct neural substrates to modulate responsiveness to particular somatosensory stimuli and that somatosensory cortical encoding occurs in a largely parallel fashion.
Collapse
Affiliation(s)
- Daniel G. Taub
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Qiufen Jiang
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Francesca Pietrafesa
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Junfeng Su
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Caitlin Greene
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | | | - Aakanksha Jain
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Mahmoud El-Rifai
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alexis Callen
- Morrissey College of Arts and Sciences, Boston College, Chestnut Hill, MA, USA
| | - Katherine Yager
- Morrissey College of Arts and Sciences, Boston College, Chestnut Hill, MA, USA
| | - Clara Chung
- Department of Neuroscience, Boston University, Boston, MA, USA
| | - Zhigang He
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Chinfei Chen
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Clifford J. Woolf
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
12
|
Ryan L, Sun-Yan A, Laughton M, Peron S. Cortical circuitry mediating inter-areal touch signal amplification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.06.543886. [PMID: 37333308 PMCID: PMC10274616 DOI: 10.1101/2023.06.06.543886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Sensory cortical areas are often organized into topographic maps which represent the sensory epithelium1,2. Individual areas are richly interconnected3, in many cases via reciprocal projections that respect the topography of the underlying map4,5. Because topographically matched cortical patches process the same stimulus, their interaction is likely central to many neural computations6-10. Here, we ask how topographically matched subregions of primary and secondary vibrissal somatosensory cortices (vS1 and vS2) interact during whisker touch. In the mouse, whisker touch-responsive neurons are topographically organized in both vS1 and vS2. Both areas receive thalamic touch input and are topographically interconnected4. Volumetric calcium imaging in mice actively palpating an object with two whiskers revealed a sparse population of highly active, broadly tuned touch neurons responsive to both whiskers. These neurons were especially pronounced in superficial layer 2 in both areas. Despite their rarity, these neurons served as the main conduits of touch-evoked activity between vS1 and vS2 and exhibited elevated synchrony. Focal lesions of the whisker touch-responsive region in vS1 or vS2 degraded touch responses in the unlesioned area, with whisker-specific vS1 lesions degrading whisker-specific vS2 touch responses. Thus, a sparse and superficial population of broadly tuned touch neurons recurrently amplifies touch responses across vS1 and vS2.
Collapse
Affiliation(s)
- Lauren Ryan
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Andrew Sun-Yan
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Maya Laughton
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| |
Collapse
|
13
|
Taub DG, Jiang Q, Pietrafesa F, Su J, Greene C, Blanchard MR, Jain A, El-Rifai M, Callen A, Yager K, Chung C, He Z, Chen C, Woolf CJ. The Secondary Somatosensory Cortex Gates Mechanical and Thermal Sensitivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.19.541449. [PMID: 37293011 PMCID: PMC10245795 DOI: 10.1101/2023.05.19.541449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The cerebral cortex is vital for the perception and processing of sensory stimuli. In the somatosensory axis, information is received by two distinct regions, the primary (S1) and secondary (S2) somatosensory cortices. Top-down circuits stemming from S1 can modulate mechanical and cooling but not heat stimuli such that circuit inhibition causes blunted mechanical and cooling perception. Using optogenetics and chemogenetics, we find that in contrast to S1, an inhibition of S2 output increases mechanical and heat, but not cooling sensitivity. Combining 2-photon anatomical reconstruction with chemogenetic inhibition of specific S2 circuits, we discover that S2 projections to the secondary motor cortex (M2) govern mechanical and thermal sensitivity without affecting motor or cognitive function. This suggests that while S2, like S1, encodes specific sensory information, that S2 operates through quite distinct neural substrates to modulate responsiveness to particular somatosensory stimuli and that somatosensory cortical encoding occurs in a largely parallel fashion.
Collapse
|
14
|
Lee C, Côté SL, Raman N, Chaudhary H, Mercado BC, Chen SX. Whole-brain mapping of long-range inputs to the VIP-expressing inhibitory neurons in the primary motor cortex. Front Neural Circuits 2023; 17:1093066. [PMID: 37275468 PMCID: PMC10237295 DOI: 10.3389/fncir.2023.1093066] [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: 11/08/2022] [Accepted: 05/05/2023] [Indexed: 06/07/2023] Open
Abstract
The primary motor cortex (MOp) is an important site for motor skill learning. Interestingly, neurons in MOp possess reward-related activity, presumably to facilitate reward-based motor learning. While pyramidal neurons (PNs) and different subtypes of GABAergic inhibitory interneurons (INs) in MOp all undergo cell-type specific plastic changes during motor learning, the vasoactive intestinal peptide-expressing inhibitory interneurons (VIP-INs) in MOp have been shown to preferentially respond to reward and play a critical role in the early phases of motor learning by triggering local circuit plasticity. To understand how VIP-INs might integrate various streams of information, such as sensory, pre-motor, and reward-related inputs, to regulate local plasticity in MOp, we performed monosynaptic rabies tracing experiments and employed an automated cell counting pipeline to generate a comprehensive map of brain-wide inputs to VIP-INs in MOp. We then compared this input profile to the brain-wide inputs to somatostatin-expressing inhibitory interneurons (SST-INs) and parvalbumin-expressing inhibitory interneurons (PV-INs) in MOp. We found that while all cell types received major inputs from sensory, motor, and prefrontal cortical regions, as well as from various thalamic nuclei, VIP-INs received more inputs from the orbital frontal cortex (ORB) - a region associated with reinforcement learning and value predictions. Our findings provide insight on how the brain leverages microcircuit motifs by both integrating and partitioning different streams of long-range input to modulate local circuit activity and plasticity.
Collapse
Affiliation(s)
- Candice Lee
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Sandrine L. Côté
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Nima Raman
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Hritvic Chaudhary
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Bryan C. Mercado
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Simon X. Chen
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
- Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, Canada
- Center for Neural Dynamics, University of Ottawa, Ottawa, ON, Canada
| |
Collapse
|
15
|
Kira S, Safaai H, Morcos AS, Panzeri S, Harvey CD. A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions. Nat Commun 2023; 14:2121. [PMID: 37055431 PMCID: PMC10102117 DOI: 10.1038/s41467-023-37804-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/30/2023] [Indexed: 04/15/2023] Open
Abstract
Decision-making requires flexibility to rapidly switch one's actions in response to sensory stimuli depending on information stored in memory. We identified cortical areas and neural activity patterns underlying this flexibility during virtual navigation, where mice switched navigation toward or away from a visual cue depending on its match to a remembered cue. Optogenetics screening identified V1, posterior parietal cortex (PPC), and retrosplenial cortex (RSC) as necessary for accurate decisions. Calcium imaging revealed neurons that can mediate rapid navigation switches by encoding a mixture of a current and remembered visual cue. These mixed selectivity neurons emerged through task learning and predicted the mouse's choices by forming efficient population codes before correct, but not incorrect, choices. They were distributed across posterior cortex, even V1, and were densest in RSC and sparsest in PPC. We propose flexibility in navigation decisions arises from neurons that mix visual and memory information within a visual-parietal-retrosplenial network.
Collapse
Affiliation(s)
- Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ari S Morcos
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | | |
Collapse
|
16
|
Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. PERIRHINAL CORTEX LEARNS A PREDICTIVE MAP (INTERNAL MODEL) OF THE TASK ENVIRONMENT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.532214. [PMID: 36993645 PMCID: PMC10055158 DOI: 10.1101/2023.03.17.532214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chemogenetic inactivation demonstrated that Prh is involved in task learning. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that expand in a retrospective manner and generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
Collapse
Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston MA 02215, USA
| |
Collapse
|
17
|
Banerjee A, Wang BA, Teutsch J, Helmchen F, Pleger B. Analogous cognitive strategies for tactile learning in the rodent and human brain. Prog Neurobiol 2023; 222:102401. [PMID: 36608783 DOI: 10.1016/j.pneurobio.2023.102401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 12/21/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
Evolution has molded individual species' sensory capacities and abilities. In rodents, who mostly inhabit dark tunnels and burrows, the whisker-based somatosensory system has developed as the dominant sensory modality, essential for environmental exploration and spatial navigation. In contrast, humans rely more on visual and auditory inputs when collecting information from their surrounding sensory space in everyday life. As a result of such species-specific differences in sensory dominance, cognitive relevance and capacities, the evidence for analogous sensory-cognitive mechanisms across species remains sparse. However, recent research in rodents and humans yielded surprisingly comparable processing rules for detecting tactile stimuli, integrating touch information into percepts, and goal-directed rule learning. Here, we review how the brain, across species, harnesses such processing rules to establish decision-making during tactile learning, following canonical circuits from the thalamus and the primary somatosensory cortex up to the frontal cortex. We discuss concordances between empirical and computational evidence from micro- and mesoscopic circuit studies in rodents to findings from macroscopic imaging in humans. Furthermore, we discuss the relevance and challenges for future cross-species research in addressing mutual context-dependent evaluation processes underpinning perceptual learning.
Collapse
Affiliation(s)
- Abhishek Banerjee
- Adaptive Decisions Lab, Biosciences Institute, Newcastle University, United Kingdom.
| | - Bin A Wang
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Germany; Collaborative Research Centre 874 "Integration and Representation of Sensory Processes", Ruhr University Bochum, Germany.
| | - Jasper Teutsch
- Adaptive Decisions Lab, Biosciences Institute, Newcastle University, United Kingdom
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zürich, Switzerland
| | - Burkhard Pleger
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Germany; Collaborative Research Centre 874 "Integration and Representation of Sensory Processes", Ruhr University Bochum, Germany
| |
Collapse
|
18
|
English G, Ghasemi Nejad N, Sommerfelt M, Yanik MF, von der Behrens W. Bayesian surprise shapes neural responses in somatosensory cortical circuits. Cell Rep 2023; 42:112009. [PMID: 36701237 DOI: 10.1016/j.celrep.2023.112009] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 09/16/2022] [Accepted: 12/31/2022] [Indexed: 01/26/2023] Open
Abstract
Numerous psychophysical studies show that Bayesian inference governs sensory decision-making; however, the specific neural circuitry underlying this probabilistic mechanism remains unclear. We record extracellular neural activity along the somatosensory pathway of mice while delivering sensory stimulation paradigms designed to isolate the response to the surprise generated by Bayesian inference. Our results demonstrate that laminar cortical circuits in early sensory areas encode Bayesian surprise. Systematic sensitivity to surprise is not identified in the somatosensory thalamus, rather emerging in the primary (S1) and secondary (S2) somatosensory cortices. Multiunit spiking activity and evoked potentials in layer 6 of these regions exhibit the highest sensitivity to surprise. Gamma power in S1 layer 2/3 exhibits an NMDAR-dependent scaling with surprise, as does alpha power in layers 2/3 and 6 of S2. These results show a precise spatiotemporal neural representation of Bayesian surprise and suggest that Bayesian inference is a fundamental component of cortical processing.
Collapse
Affiliation(s)
- Gwendolyn English
- Institute of Neuroinformatics, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland; ZNZ Neuroscience Center Zurich, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland.
| | - Newsha Ghasemi Nejad
- Institute of Neuroinformatics, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland; ZNZ Neuroscience Center Zurich, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland
| | - Marcel Sommerfelt
- Institute of Neuroinformatics, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland
| | - Mehmet Fatih Yanik
- Institute of Neuroinformatics, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland; ZNZ Neuroscience Center Zurich, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland
| | - Wolfger von der Behrens
- Institute of Neuroinformatics, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland; ZNZ Neuroscience Center Zurich, ETH Zurich & University of Zurich, 8057 Zurich, Switzerland.
| |
Collapse
|
19
|
Lu J, Chen B, Levy M, Xu P, Han BX, Takatoh J, Thompson PM, He Z, Prevosto V, Wang F. Somatosensory cortical signature of facial nociception and vibrotactile touch-induced analgesia. SCIENCE ADVANCES 2022; 8:eabn6530. [PMID: 36383651 PMCID: PMC9668294 DOI: 10.1126/sciadv.abn6530] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Pain relief by vibrotactile touch is a common human experience. Previous neurophysiological investigations of its underlying mechanism in animals focused on spinal circuits, while human studies suggested the involvement of supraspinal pathways. Here, we examine the role of primary somatosensory cortex (S1) in touch-induced mechanical and heat analgesia. We found that, in mice, vibrotactile reafferent signals from self-generated whisking significantly reduce facial nociception, which is abolished by specifically blocking touch transmission from thalamus to the barrel cortex (S1B). Using a signal separation algorithm that can decompose calcium signals into sensory-evoked, whisking, or face-wiping responses, we found that the presence of whisking altered nociceptive signal processing in S1B neurons. Analysis of S1B population dynamics revealed that whisking pushes the transition of the neural state induced by noxious stimuli toward the outcome of non-nocifensive actions. Thus, S1B integrates facial tactile and noxious signals to enable touch-mediated analgesia.
Collapse
Affiliation(s)
- Jinghao Lu
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Bin Chen
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Manuel Levy
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Peng Xu
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bao-Xia Han
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Jun Takatoh
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - P. M. Thompson
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Zhigang He
- Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Vincent Prevosto
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Fan Wang
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| |
Collapse
|
20
|
Machado TA, Kauvar IV, Deisseroth K. Multiregion neuronal activity: the forest and the trees. Nat Rev Neurosci 2022; 23:683-704. [PMID: 36192596 PMCID: PMC10327445 DOI: 10.1038/s41583-022-00634-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2022] [Indexed: 12/12/2022]
Abstract
The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.
Collapse
Affiliation(s)
- Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
| |
Collapse
|
21
|
Buetfering C, Zhang Z, Pitsiani M, Smallridge J, Boven E, McElligott S, Häusser M. Behaviorally relevant decision coding in primary somatosensory cortex neurons. Nat Neurosci 2022; 25:1225-1236. [PMID: 36042310 PMCID: PMC7613627 DOI: 10.1038/s41593-022-01151-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 07/21/2022] [Indexed: 11/20/2022]
Abstract
Primary sensory cortex is thought to process incoming sensory information, while decision variables important for driving behavior are assumed to arise downstream in the processing hierarchy. Here, we used population two-photon calcium imaging and targeted two-photon optogenetic stimulation of neurons in layer 2/3 of mouse primary somatosensory cortex (S1) during a texture discrimination task to test for the presence of decision signals and probe their behavioral relevance. Small but distinct populations of neurons carried information about the stimulus irrespective of the behavioral outcome (stimulus neurons), or about the choice irrespective of the presented stimulus (decision neurons). Decision neurons show categorical coding that develops during learning, and lack a conclusive decision signal in Miss trials. All-optical photostimulation of decision neurons during behavior improves behavioral performance, establishing a causal role in driving behavior. The fact that stimulus and decision neurons are intermingled challenges the idea of S1 as a purely sensory area, and causal perturbation suggests a direct involvement of S1 decision neurons in the decision-making process.
Collapse
Affiliation(s)
- Christina Buetfering
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
- Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
| | - Zihui Zhang
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Margarita Pitsiani
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - John Smallridge
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
- Neurophenomenology of Consciousness Laboratory, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Ellen Boven
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
- School of Physiology, Pharmacology and Neuroscience, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Sacha McElligott
- 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
|
22
|
Voitov I, Mrsic-Flogel TD. Cortical feedback loops bind distributed representations of working memory. Nature 2022; 608:381-389. [PMID: 35896749 PMCID: PMC9365695 DOI: 10.1038/s41586-022-05014-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 06/22/2022] [Indexed: 11/16/2022]
Abstract
Working memory—the brain’s ability to internalize information and use it flexibly to guide behaviour—is an essential component of cognition. Although activity related to working memory has been observed in several brain regions1–3, how neural populations actually represent working memory4–7 and the mechanisms by which this activity is maintained8–12 remain unclear13–15. Here we describe the neural implementation of visual working memory in mice alternating between a delayed non-match-to-sample task and a simple discrimination task that does not require working memory but has identical stimulus, movement and reward statistics. Transient optogenetic inactivations revealed that distributed areas of the neocortex were required selectively for the maintenance of working memory. Population activity in visual area AM and premotor area M2 during the delay period was dominated by orderly low-dimensional dynamics16,17 that were, however, independent of working memory. Instead, working memory representations were embedded in high-dimensional population activity, present in both cortical areas, persisted throughout the inter-stimulus delay period, and predicted behavioural responses during the working memory task. To test whether the distributed nature of working memory was dependent on reciprocal interactions between cortical regions18–20, we silenced one cortical area (AM or M2) while recording the feedback it received from the other. Transient inactivation of either area led to the selective disruption of inter-areal communication of working memory. Therefore, reciprocally interconnected cortical areas maintain bound high-dimensional representations of working memory. Experiments in mice alternating between a visual working memory task and a task that is independent of working memory provide insight into the neural representation of working memory and the distributed nature of its maintenance.
Collapse
Affiliation(s)
- Ivan Voitov
- Sainsbury Wellcome Centre, University College London, London, UK. .,Biozentrum, University of Basel, Basel, Switzerland.
| | | |
Collapse
|
23
|
Skorput AGJ, Gore R, Schorn R, Riedl MS, Marron Fernandez de Velasco E, Hadlich B, Kitto KF, Fairbanks CA, Vulchanova L. Targeting the somatosensory system with AAV9 and AAV2retro viral vectors. PLoS One 2022; 17:e0264938. [PMID: 35271639 PMCID: PMC8912232 DOI: 10.1371/journal.pone.0264938] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 02/19/2022] [Indexed: 12/17/2022] Open
Abstract
Adeno-associated viral (AAV) vectors allow for site-specific and time-dependent genetic manipulation of neurons. However, for successful implementation of AAV vectors, major consideration must be given to the selection of viral serotype and route of delivery for efficient gene transfer into the cell type being investigated. Here we compare the transduction pattern of neurons in the somatosensory system following injection of AAV9 or AAV2retro in the parabrachial complex of the midbrain, the spinal cord dorsal horn, the intrathecal space, and the colon. Transduction was evaluated based on Cre-dependent expression of tdTomato in transgenic reporter mice, following delivery of AAV9 or AAV2retro carrying identical constructs that drive the expression of Cre/GFP. The pattern of distribution of tdTomato expression indicated notable differences in the access of the two AAV serotypes to primary afferent neurons via peripheral delivery in the colon and to spinal projections neurons via intracranial delivery within the parabrachial complex. Additionally, our results highlight the superior sensitivity of detection of neuronal transduction based on reporter expression relative to expression of viral products.
Collapse
Affiliation(s)
- Alexander G. J. Skorput
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Reshma Gore
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Rachel Schorn
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Maureen S. Riedl
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | | | - Bailey Hadlich
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Kelley F. Kitto
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Carolyn A. Fairbanks
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Pharmacology, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Pharmaceutics, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Lucy Vulchanova
- Department of Neuroscience, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America
- * E-mail:
| |
Collapse
|
24
|
Asanza V, Peláez E, Loayza F, Lorente-Leyva LL, Peluffo-Ordóñez DH. Identification of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview. SENSORS (BASEL, SWITZERLAND) 2022; 22:2028. [PMID: 35271175 PMCID: PMC8914806 DOI: 10.3390/s22052028] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 02/11/2022] [Accepted: 02/23/2022] [Indexed: 02/01/2023]
Abstract
Recent engineering and neuroscience applications have led to the development of brain-computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy.
Collapse
Affiliation(s)
- Víctor Asanza
- Facultad de Ingeniería en Electricidad y Computación, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo km 30.5 Vía Perimetral, Guayaquil P.O. Box 09-01-5863, Ecuador;
| | - Enrique Peláez
- Facultad de Ingeniería en Electricidad y Computación, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo km 30.5 Vía Perimetral, Guayaquil P.O. Box 09-01-5863, Ecuador;
| | - Francis Loayza
- Neuroimaging and Bioengineering Laboratory (LNB), Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo km 30.5 Vía Perimetral, Guayaquil P.O. Box 09-01-5863, Ecuador;
| | | | - Diego H. Peluffo-Ordóñez
- Faculty of Engineering, Corporación Universitaria Autónoma de Nariño, Pasto 520001, Colombia;
- Modeling, Simulation and Data Analysis (MSDA) Research Program, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco
| |
Collapse
|
25
|
Condylis C, Ghanbari A, Manjrekar N, Bistrong K, Yao S, Yao Z, Nguyen TN, Zeng H, Tasic B, Chen JL. Dense functional and molecular readout of a circuit hub in sensory cortex. Science 2022; 375:eabl5981. [PMID: 34990233 DOI: 10.1126/science.abl5981] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Although single-cell transcriptomics of the neocortex has uncovered more than 300 putative cell types, whether this molecular classification predicts distinct functional roles is unclear. We combined two-photon calcium imaging with spatial transcriptomics to functionally and molecularly investigate cortical circuits. We characterized behavior-related responses across major neuronal subclasses in layers 2 or 3 of the primary somatosensory cortex as mice performed a tactile working memory task. We identified an excitatory intratelencephalic cell type, Baz1a, that exhibits high tactile feature selectivity. Baz1a neurons homeostatically maintain stimulus responsiveness during altered experience and show persistent enrichment of subsets of immediately early genes. Functional and anatomical connectivity reveals that Baz1a neurons residing in upper portions of layers 2 or 3 preferentially innervate somatostatin-expressing inhibitory neurons. This motif defines a circuit hub that orchestrates local sensory processing in superficial layers of the neocortex.
Collapse
Affiliation(s)
- Cameron Condylis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA
| | - Abed Ghanbari
- Department of Biology, Boston University, Boston, MA 02215, USA
| | | | - Karina Bistrong
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA.,Department of Biology, Boston University, Boston, MA 02215, USA.,Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA
| |
Collapse
|
26
|
Kim TH, Schnitzer MJ. Fluorescence imaging of large-scale neural ensemble dynamics. Cell 2022; 185:9-41. [PMID: 34995519 PMCID: PMC8849612 DOI: 10.1016/j.cell.2021.12.007] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/14/2022]
Abstract
Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.
Collapse
Affiliation(s)
- Tony Hyun Kim
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| |
Collapse
|
27
|
Huang C, Zeldenrust F, Celikel T. Cortical Representation of Touch in Silico. Neuroinformatics 2022; 20:1013-1039. [PMID: 35486347 PMCID: PMC9588483 DOI: 10.1007/s12021-022-09576-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2022] [Indexed: 12/31/2022]
Abstract
With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.
Collapse
Affiliation(s)
- Chao Huang
- grid.9647.c0000 0004 7669 9786Department of Biology, University of Leipzig, Leipzig, Germany
| | - Fleur Zeldenrust
- grid.5590.90000000122931605Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Tansu Celikel
- grid.5590.90000000122931605Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands ,grid.213917.f0000 0001 2097 4943School of Psychology, Georgia Institute of Technology, Atlanta, GA USA
| |
Collapse
|
28
|
Hypothesis testing, attention, and 'Same'-'Different' judgments. Cogn Psychol 2021; 132:101443. [PMID: 34856532 DOI: 10.1016/j.cogpsych.2021.101443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 10/15/2021] [Accepted: 10/23/2021] [Indexed: 11/03/2022]
Abstract
Logic and common sense say that judging two stimuli as "same" is the converse of judging them as "different". Empirically, however, 'Same'-'Different' judgment data are anomalous in two major ways. The fast-'Same' effect violates the expectation that 'Same' reaction time (RT) should be predictable by extrapolating from 'Different' RT. The criterion effect violates the expectation that RTs measured when sameness is defined by a conjunction of matching attributes should predict RTs measured when sameness is defined by a disjunction of matching attributes. The two criteria are symmetrical, yet empirically they differ greatly, disjunctive judgments being by far the slower of the two. This study sought the sources of these two effects. With the aid of a cue, a selective-comparison method deconfounded the contributions of stimulus encoding and comparisons to the two effects. The results were paradoxical. Each additional irrelevant (uncued) letter in a random string incremented RT for conjunctive judgments as much as an additional relevant letter did. Yet irrelevant letters were not compared and relevant letters had to be compared. These results appeared again in a second experiment that used words as stimuli. Contrary to intuition, a distinct comparison mechanism-the heart of relative judgment models-is not necessary in judgments of sameness and difference. It is shown here that encoding can carry out the comparison function without the operation of a separate comparison mechanism. Attention mediates the process by selecting from the set of stimulus alternatives, thereby partitioning the set into the 'Same' and 'Different' subsets. The fast-'Same' and criterion effects result from a structural limitation on what attention can select at any one time. With attention mediating the task, 'Same'-'Different' judgments become, in effect, the outcome of a testing of a hypothesis, bridging the distinction between absolute stimulus identification and relative judgments.
Collapse
|
29
|
Clough M, Chen IA, Park SW, Ahrens AM, Stirman JN, Smith SL, Chen JL. Flexible simultaneous mesoscale two-photon imaging of neural activity at high speeds. Nat Commun 2021; 12:6638. [PMID: 34789730 PMCID: PMC8599611 DOI: 10.1038/s41467-021-26737-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 10/05/2021] [Indexed: 12/02/2022] Open
Abstract
Understanding brain function requires monitoring local and global brain dynamics. Two-photon imaging of the brain across mesoscopic scales has presented trade-offs between imaging area and acquisition speed. We describe a flexible cellular resolution two-photon microscope capable of simultaneous video rate acquisition of four independently targetable brain regions spanning an approximate five-millimeter field of view. With this system, we demonstrate the ability to measure calcium activity across mouse sensorimotor cortex at behaviorally relevant timescales.
Collapse
Affiliation(s)
- Mitchell Clough
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Ichun Anderson Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Seong-Wook Park
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Allison M Ahrens
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Jeffrey N Stirman
- Neuroscience Center, University of North Carolina School of Medicine, Chapel Hill, NC, 27599, USA
| | - Spencer L Smith
- Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
| |
Collapse
|
30
|
Voltage-Sensitive Dye versus Intrinsic Signal Optical Imaging: Comparison of Tactile Responses in Primary and Secondary Somatosensory Cortices of Rats. Brain Sci 2021; 11:brainsci11101294. [PMID: 34679359 PMCID: PMC8533871 DOI: 10.3390/brainsci11101294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 09/24/2021] [Accepted: 09/27/2021] [Indexed: 11/21/2022] Open
Abstract
Studies using functional magnetic resonance imaging assume that hemodynamic responses have roughly linear relationships with underlying neural activity. However, to accurately investigate the neurovascular transfer function and compare its variability across brain regions, it is necessary to obtain full-field imaging of both electrophysiological and hemodynamic responses under various stimulus conditions with superior spatiotemporal resolution. Optical imaging combined with voltage-sensitive dye (VSD) and intrinsic signals (IS) is a powerful tool to address this issue. We performed VSD and IS imaging in the primary (S1) and secondary (S2) somatosensory cortices of rats to obtain optical maps of whisker-evoked responses. There were characteristic differences in sensory responses between the S1 and S2 cortices: VSD imaging revealed more localized excitatory and stronger inhibitory neural activity in S1 than in S2. IS imaging revealed stronger metabolic responses in S1 than in S2. We calculated the degree of response to compare the sensory responses between cortical regions and found that the ratio of the degree of response of S2 to S1 was similar, irrespective of whether the ratio was determined by VSD or IS imaging. These results suggest that neurovascular coupling does not vary between the S1 and S2 cortices.
Collapse
|
31
|
Harrell ER, Renard A, Bathellier B. Fast cortical dynamics encode tactile grating orientation during active touch. SCIENCE ADVANCES 2021; 7:eabf7096. [PMID: 34516895 PMCID: PMC8442870 DOI: 10.1126/sciadv.abf7096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Touch-based object recognition relies on perception of compositional tactile features like roughness, shape, and surface orientation. However, besides roughness, it remains unclear how these different tactile features are encoded by neural activity that is linked with perception. Here, we establish a cortex-dependent perceptual task in which mice discriminate tactile gratings on the basis of orientation using only their whiskers. Multielectrode recordings in the barrel cortex reveal weak orientation tuning in average firing rates (500-ms time scale) during grating exploration despite high levels of cortical activity. Just before decision, orientation information extracted from fast cortical dynamics (100-ms time scale) more closely resembles concurrent psychophysical measurements than single neuron orientation tuning curves. This temporal code conveys both stimulus and choice/action-related information, suggesting that fast cortical dynamics during exploration of a tactile object both reflect the physical stimulus and affect the decision.
Collapse
Affiliation(s)
- Evan R. Harrell
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
- Corresponding author. (E.R.H.); (B.B.)
| | - Anthony Renard
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
| | - Brice Bathellier
- Department for Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), UMR9197 CNRS/University Paris Sud CNRS, Building 32/33, 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
- Institut Pasteur, INSERM, Institut de l’Audition, 63 rue de Charenton, F-75012 Paris, France
- Corresponding author. (E.R.H.); (B.B.)
| |
Collapse
|
32
|
Zhao YJ, Kay KN, Tian Y, Ku Y. Sensory Recruitment Revisited: Ipsilateral V1 Involved in Visual Working Memory. Cereb Cortex 2021; 32:1470-1479. [PMID: 34476462 DOI: 10.1093/cercor/bhab300] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 11/12/2022] Open
Abstract
The "sensory recruitment hypothesis" posits an essential role of sensory cortices in working memory, beyond the well-accepted frontoparietal areas. Yet, this hypothesis has recently been challenged. In the present study, participants performed a delayed orientation recall task while high-spatial-resolution 3 T functional magnetic resonance imaging (fMRI) signals were measured in posterior cortices. A multivariate inverted encoding model approach was used to decode remembered orientations based on blood oxygen level-dependent fMRI signals from visual cortices during the delay period. We found that not only did activity in the contralateral primary visual cortex (V1) retain high-fidelity representations of the visual stimuli, but activity in the ipsilateral V1 also contained such orientation tuning. Moreover, although the encoded tuning was faded in the contralateral V1 during the late delay period, tuning information in the ipsilateral V1 remained sustained. Furthermore, the ipsilateral representation was presented in secondary visual cortex (V2) as well, but not in other higher-level visual areas. These results thus supported the sensory recruitment hypothesis and extended it to the ipsilateral sensory areas, which indicated the distributed involvement of visual areas in visual working memory.
Collapse
Affiliation(s)
- Yi-Jie Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.,Center for Brain and Mental Well-being, Department of Psychology, Sun Yat-sen University, Guangzhou 510006, China.,Peng Cheng Laboratory, Shenzhen 518055, China.,School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Kendrick N Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Yonghong Tian
- Peng Cheng Laboratory, Shenzhen 518055, China.,School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China
| | - Yixuan Ku
- Center for Brain and Mental Well-being, Department of Psychology, Sun Yat-sen University, Guangzhou 510006, China.,Peng Cheng Laboratory, Shenzhen 518055, China
| |
Collapse
|
33
|
Hwang EJ, Sato TR, Sato TK. A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network. Front Neural Circuits 2021; 15:691314. [PMID: 34475815 PMCID: PMC8406690 DOI: 10.3389/fncir.2021.691314] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/21/2021] [Indexed: 11/25/2022] Open
Abstract
Goal-directed behavior often involves temporal separation and flexible context-dependent association between sensory input and motor output. The control of goal-directed behavior is proposed to lie in the frontoparietal network, but the computational architecture of this network remains elusive. Based on recent rodent studies that measured and manipulated projection neurons in the frontoparietal network together with findings from earlier primate studies, we propose a canonical scheme of information flows in this network. The parietofrontal pathway transmits the spatial information of a sensory stimulus or internal motor bias to drive motor programs in the frontal areas. This pathway might consist of multiple parallel connections, each controlling distinct motor effectors. The frontoparietal pathway sends the spatial information of cognitively processed motor plans through multiple parallel connections. Each of these connections could support distinct spatial functions that use the motor target information, including attention allocation, multi-body part coordination, and forward estimation of movement state (i.e., forward models). The parallel pathways in the frontoparietal network enable dynamic interactions between regions that are tuned for specific goal-directed behaviors. This scheme offers a promising framework within which the computational architecture of the frontoparietal network and the underlying circuit mechanisms can be delineated in a systematic way, providing a holistic understanding of information processing in this network. Clarifying this network may also improve the diagnosis and treatment of behavioral deficits associated with dysfunctional frontoparietal connectivity in various neurological disorders including Alzheimer's disease.
Collapse
Affiliation(s)
- Eun Jung Hwang
- Stanson Toshok Center for Brain Function and Repair, Brain Science Institute, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
- Cell Biology and Anatomy, Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
| | - Takashi R. Sato
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States
| | - Tatsuo K. Sato
- Department of Physiology, Monash University, Clayton, VIC, Australia
- Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
- PRESTO, Japan Science and Technology Agency, Kawaguchi, Japan
| |
Collapse
|
34
|
Circuit mechanisms for cortical plasticity and learning. Semin Cell Dev Biol 2021; 125:68-75. [PMID: 34332885 DOI: 10.1016/j.semcdb.2021.07.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/15/2021] [Accepted: 07/16/2021] [Indexed: 11/22/2022]
Abstract
The cerebral cortex integrates sensory information with emotional states and internal representations to produce coherent percepts, form associations, and execute voluntary actions. For the cortex to optimize perception, its neuronal network needs to dynamically retrieve and encode new information. Over the last few decades, research has started to provide insight into how the cortex serves these functions. Building on classical Hebbian plasticity models, the latest hypotheses hold that throughout experience and learning, streams of feedforward, feedback, and modulatory information operate in selective and coordinated manners to alter the strength of synapses and ultimately change the response properties of cortical neurons. Here, we describe cortical plasticity mechanisms that involve the concerted action of feedforward and long-range feedback input onto pyramidal neurons as well as the implication of local disinhibitory circuit motifs in this process.
Collapse
|
35
|
Rossi-Pool R, Zainos A, Alvarez M, Diaz-deLeon G, Romo R. A continuum of invariant sensory and behavioral-context perceptual coding in secondary somatosensory cortex. Nat Commun 2021; 12:2000. [PMID: 33790301 PMCID: PMC8012659 DOI: 10.1038/s41467-021-22321-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 03/08/2021] [Indexed: 11/08/2022] Open
Abstract
A crucial role of cortical networks is the conversion of sensory inputs into perception. In the cortical somatosensory network, neurons of the primary somatosensory cortex (S1) show invariant sensory responses, while frontal lobe neuronal activity correlates with the animal's perceptual behavior. Here, we report that in the secondary somatosensory cortex (S2), neurons with invariant sensory responses coexist with neurons whose responses correlate with perceptual behavior. Importantly, the vast majority of the neurons fall along a continuum of combined sensory and categorical dynamics. Furthermore, during a non-demanding control task, the sensory responses remain unaltered while the sensory information exhibits an increase. However, perceptual responses and the associated categorical information decrease, implicating a task context-dependent processing mechanism. Conclusively, S2 neurons exhibit intriguing dynamics that are intermediate between those of S1 and frontal lobe. Our results contribute relevant evidence about the role that S2 plays in the conversion of touch into perception.
Collapse
Affiliation(s)
- Román Rossi-Pool
- Instituto de Fisiología Celular─Neurociencias, Universidad Nacional Autónoma de México, Mexico City, Mexico.
| | - Antonio Zainos
- Instituto de Fisiología Celular─Neurociencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Manuel Alvarez
- Instituto de Fisiología Celular─Neurociencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Gabriel Diaz-deLeon
- Instituto de Fisiología Celular─Neurociencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ranulfo Romo
- Instituto de Fisiología Celular─Neurociencias, Universidad Nacional Autónoma de México, Mexico City, Mexico.
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.
- El Colegio Nacional, Mexico City, Mexico.
| |
Collapse
|
36
|
Bale MR, Bitzidou M, Giusto E, Kinghorn P, Maravall M. Sequence Learning Induces Selectivity to Multiple Task Parameters in Mouse Somatosensory Cortex. Curr Biol 2021; 31:473-485.e5. [PMID: 33186553 PMCID: PMC7883307 DOI: 10.1016/j.cub.2020.10.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/01/2020] [Accepted: 10/20/2020] [Indexed: 11/20/2022]
Abstract
Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.
Collapse
Affiliation(s)
- Michael R Bale
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Malamati Bitzidou
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Elena Giusto
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Paul Kinghorn
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Miguel Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.
| |
Collapse
|
37
|
Invariant timescale hierarchy across the cortical somatosensory network. Proc Natl Acad Sci U S A 2021; 118:2021843118. [PMID: 33431695 PMCID: PMC7826380 DOI: 10.1073/pnas.2021843118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The ability of cortical networks to integrate information from different sources is essential for cognitive processes. On one hand, sensory areas exhibit fast dynamics often phase-locked to stimulation; on the other hand, frontal lobe areas with slow response latencies to stimuli must integrate and maintain information for longer periods. Thus, cortical areas may require different timescales depending on their functional role. Studying the cortical somatosensory network while monkeys discriminated between two vibrotactile stimulus patterns, we found that a hierarchical order could be established across cortical areas based on their intrinsic timescales. Further, even though subareas (areas 3b, 1, and 2) of the primary somatosensory (S1) cortex exhibit analogous firing rate responses, a clear differentiation was observed in their timescales. Importantly, we observed that this inherent timescale hierarchy was invariant between task contexts (demanding vs. nondemanding). Even if task context severely affected neural coding in cortical areas downstream to S1, their timescales remained unaffected. Moreover, we found that these time constants were invariant across neurons with different latencies or coding. Although neurons had completely different dynamics, they all exhibited comparable timescales within each cortical area. Our results suggest that this measure is demonstrative of an inherent characteristic of each cortical area, is not a dynamical feature of individual neurons, and does not depend on task demands.
Collapse
|
38
|
Kang B, Druckmann S. Approaches to inferring multi-regional interactions from simultaneous population recordings: Inferring multi-regional interactions from simultaneous population recordings. Curr Opin Neurobiol 2020; 65:108-119. [PMID: 33227602 PMCID: PMC7853322 DOI: 10.1016/j.conb.2020.10.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 09/28/2020] [Accepted: 10/03/2020] [Indexed: 12/20/2022]
Abstract
Most past studies of neural representations and dynamics have focused on recordings from single brain areas. However, growing evidence of brain-wide, parallel representations of cognitive variables suggests that analyzing neural representations and dynamics in individual brain areas can benefit from understanding the context of multi-regional interactions that support them. Moreover, perturbation experiments revealed that the manner in which these parallel representations interact with each other can differ dramatically across different pairs of brain areas. Recent advances in recording technology offer a potentially powerful substrate to study how multi-regional interactions coordinate neural representations in individual brain areas and dictate behavior on a single-trial basis through simultaneous recordings of multiple brain areas. We review pragmatic approaches to studying multi-regional interactions and illustrate them in the concrete context of a rodent delayed response task paradigm.
Collapse
Affiliation(s)
- Byungwoo Kang
- Dept. of Neurobiology, Stanford University, Stanford, CA, United States; Physics Department, Stanford University, Stanford, CA, United States
| | - Shaul Druckmann
- Dept. of Neurobiology, Stanford University, Stanford, CA, United States.
| |
Collapse
|
39
|
Crochet S. Match Making in Sensory Cortex. Neuron 2020; 106:363-365. [PMID: 32380049 DOI: 10.1016/j.neuron.2020.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Cortical sensory areas are supposed to encode immediate sensory inputs. In this issue of Neuron, Condylis et al. (2020) show that they can also recall information about a past event when in need of comparing two temporally segregated sensory inputs.
Collapse
Affiliation(s)
- Sylvain Crochet
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; Institut National de la Santé et de la Recherche Médicale (INSERM), France.
| |
Collapse
|
40
|
Sato TK. Long-range connections enrich cortical computations. Neurosci Res 2020; 162:1-12. [PMID: 32470355 DOI: 10.1016/j.neures.2020.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 04/28/2020] [Accepted: 05/15/2020] [Indexed: 10/24/2022]
Abstract
The cerebral cortex can perform powerful computations, including those involved in higher cognitive functions. Cortical processing for such computations is executed by local circuits and is further enriched by long-range connectivity. This connectivity is activated under specific conditions and modulates local processing, providing flexibility in the computational performance of the cortex. For instance, long-range connectivity in the primary visual cortex exerts facilitatory impacts when the cortex is silent but suppressive impacts when the cortex is strongly sensory-stimulated. These dual impacts can be captured by a divisive gain control model. Recent methodological advances such as optogenetics, anatomical tracing, and two-photon microscopy have enabled neuroscientists to probe the circuit and synaptic bases of long-range connectivity in detail. Here, I review a series of evidence indicating essential roles of long-range connectivity in visual and hierarchical processing involving numerous cortical areas. I also describe an overview of the challenges encountered in investigating underlying synaptic mechanisms and highlight recent technical approaches that may overcome these difficulties and provide new insights into synaptic mechanisms for cortical processing involving long-range connectivity.
Collapse
Affiliation(s)
- Tatsuo K Sato
- Dept. of Physiology, Neuroscience Program, Biomedicine Discovery Inst., Monash University, Clayton, VIC 3800, Australia; PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan.
| |
Collapse
|