シンポジウム
39 大規模ネットワークとしての皮質機能解明へ向けたトランスレーショナルパラダイム
39 Translational paradigms for cortical function as a large-scale network
座長：中井 信裕（神戸大学）・毛内 拡（お茶の水女子大学） |
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| 2022年6月30日 9:02～9:22 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-01
A transcriptomic axis predicts state modulation of cortical interneurons
*Kenneth Harris(1)
1. UCL Institute of Neurology
Keyword: cortex, transcriptomics
Transcriptomics has revealed the exquisite diversity of cortical inhibitory neurons, but it is not known whether these fine molecular subtypes have correspondingly diverse activity patterns in the living brain. Here, we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, but that this diversity is organized by a single factor: position along their main axis of transcriptomic variation. We combined in vivo 2-photon calcium imaging of mouse V1 with a novel transcriptomic method to identify mRNAs for 72 selected genes in ex vivo slices. We used previously-defined transcriptomic clusters (Tasic et al, Nature 2018) to classify inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 Families, 11 Types, and 35 Subtypes. Visual responses differed significantly only across Families, with the Sncg Family showing notable suppression by visual stimuli. Modulation by brain state differed at all hierarchical levels, but a cell type’s brain state modulation and correlations with simultaneously recorded cells could be largely predicted from a single transcriptomic axis, the first transcriptomic principal component. Inhibitory Subtypes that fired more in resting, oscillatory brain states had narrower spikes, lower input resistance, weaker adaptation, and less axon in layer 1 as determined in vitro (Gouwens et al Cell 2020); Subtypes firing more during arousal had the opposite properties. The former Subtypes express more inhibitory cholinergic receptors, and the latter more excitatory cholinergic receptors in single-cell data. Thus, a simple principle may largely explain how diverse inhibitory V1 Subtypes shape state-dependent cortical processing. | | 2022年6月30日 9:22～9:40 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-02
低コントラストの視覚弁別を可能にする神経活動
Neuronal activity supporting orientation discrimination at low contrast
*木村 梨絵(1,2,3,4)、大木 研一(1,5,4)、吉村 由美子(2,3)
1. 東京大学大学院医学系研究科、2. 生理学研究所、3. 総合研究大学院大学、4. Beyond AI 研究推進機構、5. ニューロインテリジェンス国際研究機構
*Rie Kimura(1,2,3,4), Kenichi Ohki(1,5,4), Yumiko Yoshimura(2,3)
1. Grad Sch Med, Univ of Tokyo, Tokyo, Japan, 2. NIPS, Okazaki, 3. SOKENDAI, Okazaki, 4. Institute for AI and Beyond, Tokyo, 5. WPI-IRCN, Tokyo
Keyword: VISUAL CORTEX, CONTRAST PREFERENCE, ORIENTATION DISCRIMINATION, MULTIPLE SINGLE-UNIT RECORDING
Animals can often perceive familiar vague visual objects. We explored this neuronal mechanism using multiple single-unit recordings from deep layers of the primary visual cortex (V1) of head-restrained rats. The rats learned to push or pull a lever, respectively, depending on whether presented visual stimuli were vertical or horizontal. During this orientation discrimination task, we found that the firing rates of a subset of neurons increased by reducing the luminance contrast. The low-contrast preference was commonly observed in both wide-spiking (putative excitatory) and narrow-spiking (inhibitory) neurons. These low contrast-preferring neurons were rare during passive-viewing without training or anesthesia after training. The neurons responded more strongly to preferred orientations in correct-choice than incorrect-choice trials, while high contrast-preferring neurons did not. At single-neuron and population levels, low contrast-preferring neurons efficiently represented low-contrast orientations. Following training, excitation was enhanced irrespective of stimulus contrast, and the phase synchronization of spikes to the beta oscillations, appearing strikingly at high contrast, was stronger in putative inhibitory than excitatory neurons. The change in excitation and inhibition balance might contribute to low-contrast preference. Taken together, low-contrast preference in V1 activity is strengthened in an experience-dependent manner, which may enable a consistent perception of familiar objects with any contrast. The flexible information representation could make our sensation stable and effective. | | 2022年6月30日 9:40～10:00 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-03
Neural Dynamics of Working Memory
*Timothy Buschman(1,2)
1. Princeton Neuroscience Institute, Princeton University, 2. Department of Psychology, Princeton University
Keyword: working memory, cognitive control, neural dynamics, attention
Cognitive control guides behavior by controlling what, where, and how information is represented in the brain. Perhaps the most well-studied form of cognitive control has been ‘attention’, which controls how external sensory stimuli are represented in the brain. In contrast, the neural mechanisms controlling the selection of representations held ‘in mind’, in working memory, are unknown. In this talk, I will present evidence that prefrontal cortex controls working memory by selectively enhancing and transforming the contents of working memory. To show this, we trained monkeys to switch between two tasks, requiring them to either select an item from a set of items held in working memory or attend to one stimulus from a set of visual stimuli. Simultaneous neural recordings in prefrontal, parietal, and visual cortex found prefrontal cortex played a primary role in selecting an item from working memory, representing selection before parietal and visual cortex. Surprisingly, the same representation that controlled selection also directed attention to an external stimulus, suggesting prefrontal cortex may act as a domain-general controller. Furthermore, we found that selection acted on memory representations by strengthening the selected item and transforming it in a task-dependent manner. Before selection, when both items were relevant to the task, the identity of each item was represented equally in two independent subspaces of neural activity. After selection, the representation of only the selected item was strengthened and transformed into a new subspace that was used to guide the animal’s behavioral report. Together, our results show how prefrontal cortex controls working memory, selectively enhancing and transforming memories to support behavior. | | 2022年6月30日 10:00～10:18 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-04
Corticostriatal control of spontaneous behaviors
*Dana Rubi Levy(1), Rockwell Anyoha(1), David Sabatini(1), Sandeep Robert Datta(1)
1. Department of Neurobiology, Harvard Medical School
Keyword: striatum, motor cortex, spontaneous behavior
Corticostriatal circuits play a crucial role in controlling voluntary actions. While the performance of learned motor skills is attributed mainly to the striatum, motor cortex activity controls the learning process of a new task. However, in contrast to overly trained motor habits, naturalistic behaviors require flexibility in moment-to-moment action selection that might crucially require ongoing cortical modulation of motor sequences and striatal activity. Yet, the function of motor cortex in sequencing unrestrained behaviors remains unclear. Here, we explore the role of primary and secondary motor cortices in controlling the execution of naturalistic, task-free exploratory behaviors of mice. To understand the composition of spontaneous response patterns, we track the 3D pose dynamics of freely behaving mice and utilize Motion Sequencing (Moseq), an unsupervised machine learning algorithm, to parse behavior into meaningful sub-second motor motifs. Using cortical manipulations, neural recordings, and introduction of ethological environmental challenges, we describe the role of motor cortex in guiding ongoing performance of spontaneous behavior. To mimic cortical dysfunction during skill learning under naturalistic conditions, we also manipulated the motor cortex during early stages in development and studied the effect on adult phenotype. Taken together, through adopting an ethological perspective and a developmental approach, our results shed new light on corticostriatal modulation of ongoing behavior. | | 2022年6月30日 10:18～10:38 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-05
Cortical control of voluntary movements
*Takaki Komiyama(1)
1. Neurobiology Section and Dept of Neurosciences, Univ of California San Diego, La Jolla, CA, USA
Keyword: Motor learning, Motor cortex, Dendritic spines, Two-photon imaging
Cortical control of voluntary movements Takaki Komiyama University of California San Diego Learning and generating adaptive body movements is a fundamental function of the brain. This function is controlled by a motor circuit distributed across brain areas. In particular the motor cortex is a central locus where changes take place during motor skill learning, especially during early phases of learning. During motor learning, reproducible spatiotemporal activity patterns emerge in an ensemble of neurons in the L2/3 of the motor cortex. Furthermore, large-scale cortical networks also refine their activity patterns during learning, forming reproducible cortex-wide activity patterns dedicated to the generation of the learned movement. These activity changes accompany changes at the synaptic level, where dendritic spines located in the apical tufts of L2/3 neurons undergo reorganizations. The spatiotemporal specificity of the plasticity of excitatory synapses is regulated by cell-type specific plasticity of inhibitory neurons. Our recent results indicate that excitatory synapse plasticity shows fine scale spatial and functional specificity. Specifically, our data indicate that the potentiation of clustered, pre-existing spines showing task-related activity creates a micro-environment of plasticity within the apical dendrites, wherein multiple filopodia sample the nearby neuropil, and successful connections are then selected for survival based on co-activity with nearby task-related spines that ultimately matures to signal the learned movement. Furthermore, we found that the new spines synapse with axons previously unrepresented in these dendritic domains. Thus, learning involves the binding of new information streams into functional synaptic clusters to subserve the learned behaviors. | | 2022年6月30日 10:38～10:56 ラグナガーデンホテル 羽衣：中 第9会場
1S09m-06
行動変遷時におけるASDモデルマウスの皮質機能ネットワーク動態異常
Abnormal dynamics of cortical functional networks during behavioral transitions in a mouse model of autism
*中井 信裕(1,3)、佐藤 正晃(2,3)、内匠 透(1,3)
1. 神戸大学大学院医学研究科、2. 北海道大学医学研究院、3. 理化学研究所脳神経科学研究センター
*Nobuhiro Nakai(1,3), Masaaki Sato(2,3), Toru Takumi(1,3)
1. Grad Sch Med, Kobe University, Kobe, Japan, 2. Faculty of Medicine, Hokkaido University, Sapporo, Japan, 3. CBS, Wako, RIKEN
Keyword: Virtual reality, Functional connectivity, Network dynamics, Autism spectrum disorder
Impairments of voluntary movements are observed in individuals with autism spectrum disorder (ASD). Initiation and termination of voluntary behavior engages multiple coordinated processing of motor and sensory signals but reconfiguration of large-scale functional networks behind such dynamic behavioral changes remains to be fully elucidated especially in ASD. In this study, we sought to elucidate the rapid reorganization of functional cortical networks during locomotion, focusing on behavioral state transitions between locomotion (i.e., running) and rest conditions, in normal and ASD model mice. We monitored the mouse cortical activity during exploration behavior in the virtual reality (VR) by transcranial wide-field calcium imaging. In our VR system, the mouse is allowed to freely explore a virtual open arena, which represents voluntary locomotion behavior. Pair-wise correlation of cortical area activity was then calculated to represent the state of cortical functional network dynamics. Using graph theoretical analysis of functional connectivity (FC), we found cortical functional networks undergo rapid transitions between an integrated mode characterized by significant decorrelation among motor areas and correlation among sensory areas during rest and a more segregated mode characterized by decorrelation among sensory areas during locomotion. Absence of visual feedback elicited insufficient exploration and lack of long-range and cross-modal FC from visual cortex. Furthermore, a model mouse for ASD with 15q duplication exhibited peculiar FC patterns involving hyperconnectivity of secondary motor areas, as further supported by highly accurate machine learning genotype classification. Our findings thus point to importance of the motor areas in cortical FC defects during spontaneous behavioral switching in autism. | |
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