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Jézéquel J, Condomitti G, Kroon T, Hamid F, Sanalidou S, Garcés T, Maeso P, Balia M, Hu Z, Sahara S, Rico B. Cadherins orchestrate specific patterns of perisomatic inhibition onto distinct pyramidal cell populations. Nat Commun 2025; 16:4481. [PMID: 40368888 PMCID: PMC12078473 DOI: 10.1038/s41467-025-59635-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2024] [Accepted: 04/28/2025] [Indexed: 05/16/2025] Open
Abstract
GABAergic interneurons were thought to regulate excitatory networks by establishing unselective connections onto diverse pyramidal cell populations, but recent studies demonstrate the existence of a cell type-specific inhibitory connectome. How and when interneurons establish precise connectivity patterns among intermingled populations of excitatory neurons remains enigmatic. We explore the molecular mechanisms orchestrating the emergence of cell type-specific inhibition in the mouse cerebral cortex. We demonstrate that layer 5 intra- (L5 IT) and extra-telencephalic (L5 ET) neurons express unique transcriptional programs, allowing them to shape parvalbumin- (PV+) and cholecystokinin-positive (CCK+) interneuron wiring. We identified Cdh12 and Cdh13, two cadherin superfamily members, as underpinnings of cell type- and input-specific inhibitory patterns of L5 pyramidal cell populations. Multiplex monosynaptic tracing revealed a minimal overlap between IT and ET presynaptic inhibitory networks and suggests that different PV+ basket cell populations innervate distinct L5 pyramidal cell types. Here, we unravel the contribution of cadherins in shaping cell-type-specific cortical interneuron wiring.
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Affiliation(s)
- Julie Jézéquel
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Giuseppe Condomitti
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Tim Kroon
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Fursham Hamid
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Stella Sanalidou
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Teresa Garcés
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Patricia Maeso
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Maddalena Balia
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Zhaohui Hu
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Setsuko Sahara
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Beatriz Rico
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom.
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2
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Neske GT, Cardin JA. Higher-order thalamic input to cortex selectively conveys state information. Cell Rep 2025; 44:115292. [PMID: 39937647 PMCID: PMC11920878 DOI: 10.1016/j.celrep.2025.115292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 10/09/2024] [Accepted: 01/17/2025] [Indexed: 02/14/2025] Open
Abstract
Communication among neocortical areas is largely thought to be mediated by long-range synaptic interactions between cortical neurons, with the thalamus providing only an initial relay of information from the sensory periphery. Higher-order thalamic nuclei receive strong synaptic inputs from the cortex and send robust projections back to other cortical areas, providing a distinct and potentially critical route for corticocortical communication. However, the relative contributions of corticocortical and thalamocortical inputs to higher-order cortical function remain unclear. Using imaging of neurons and axon terminals in combination with optogenetic manipulations, we find that the higher-order visual thalamus of mice has a unique impact on the posterior medial visual cortex (PM). Whereas corticocortical projections from lower cortical areas convey robust visual information to PM, higher-order thalamocortical projections convey information about global arousal state. Together, these findings suggest a key role for the higher-order thalamus in providing contextual signals that may flexibly modulate cortical sensory processing.
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Affiliation(s)
- Garrett T Neske
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA.
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Han X, Bonin V. Higher-order cortical and thalamic pathways shape visual processing streams in the mouse cortex. Curr Biol 2024; 34:5671-5684.e6. [PMID: 39566501 DOI: 10.1016/j.cub.2024.10.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/21/2024] [Accepted: 10/17/2024] [Indexed: 11/22/2024]
Abstract
Mammalian visual functions rely on distributed processing across interconnected cortical and subcortical regions. In higher-order visual areas (HVAs), visual features are processed in specialized streams that integrate feedforward and higher-order inputs from intracortical and thalamocortical pathways. However, the precise circuit organization responsible for HVA specialization remains unclear. We investigated the cellular architecture of primary visual cortex (V1) and higher-order visual pathways in the mouse, focusing on their roles in shaping visual representations. Using in vivo functional imaging and neural circuit tracing, we found that HVAs preferentially receive inputs from both V1 and higher-order pathways tuned to similar spatiotemporal properties, with the strongest selectivity seen in layer 2/3 neurons. These neurons exhibit target-specific tuning and sublaminar specificity in their projections, reflecting cell-type-specific visual information flow. In contrast, HVA layer 5 pathways nonspecifically broadcast visual signals across cortical areas, suggesting a role in distributing HVA outputs. Additionally, thalamocortical pathways from the lateral posterior thalamic nucleus (LP) provide highly specific, nearly non-overlapping visual inputs to HVAs, complementing intracortical inputs and contributing to input functional diversity. Our findings suggest that the convergence of laminar and cell-type-specific pathways V1 and higher-order intracortical and thalamocortical pathways plays a key role in shaping the functional specialization and diversity of HVAs.
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Affiliation(s)
- Xu Han
- Neuro-Electronics Research Flanders, 3000 Leuven, Belgium; KU Leuven, Department of Biology & Leuven Brain Institute, 3000 Leuven, Belgium; VIB, 3000 Leuven, Belgium.
| | - Vincent Bonin
- Neuro-Electronics Research Flanders, 3000 Leuven, Belgium; KU Leuven, Department of Biology & Leuven Brain Institute, 3000 Leuven, Belgium; VIB, 3000 Leuven, Belgium.
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4
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Park SB, Lur G. Repeated exposure to multiple concurrent stressors alters visual processing in the adult posterior parietal cortex. Neurobiol Stress 2024; 31:100660. [PMID: 39100726 PMCID: PMC11296072 DOI: 10.1016/j.ynstr.2024.100660] [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: 03/29/2024] [Revised: 06/25/2024] [Accepted: 06/29/2024] [Indexed: 08/06/2024] Open
Abstract
Chronic stress is well known to erode cognitive functions. Yet, our understanding of how repeated stress exposure impacts one of the fundamental bases of cognition: sensory processing, remains limited. The posterior parietal cortex (PPC) is a high order visual region, known for its role in visually guided decision making, multimodal integration, attention, and working memory. Here, we used functional measures to determine how repeated exposure to multiple concurrent stressors (RMS) affects sensory processing in the PPC in adult male mice. A longitudinal experimental design, repeatedly surveying the same population of neurons using in vivo two-photon imaging, revealed that RMS disrupts the balanced turnover of visually responsive cells in layer 2/3 of the PPC. Across the population, RMS-induced changes in visual responsiveness followed a bimodal distribution suggesting idiosyncratic stress effects. In cells that maintained their responsiveness across recording sessions, we found that stress reduced visual response magnitudes and feature selectivity. While we did not observe stress-induced elimination of excitatory synapses, noise correlation statistics indicated that RMS altered visual input to the neuronal population. The impact of RMS was restricted to visually evoked responses and was not evident in neuronal activity associated with locomotion onset. Together, our results indicate that despite no apparent synaptic reorganization, stress exposure in adulthood can disrupt sensory processing in the PPC, with the effects showing remarkable individual variation.
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Affiliation(s)
- Soo Bin Park
- Department of Neurobiology and Behavior, University of California, Irvine, CA USA, 92697
| | - Gyorgy Lur
- Department of Neurobiology and Behavior, University of California, Irvine, CA USA, 92697
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5
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Su C, Mendes-Platt RF, Alonso JM, Swadlow HA, Bereshpolova Y. Visual Corticotectal Neurons in Awake Rabbits: Receptive Fields and Driving Monosynaptic Thalamocortical Inputs. J Neurosci 2024; 44:e1945232024. [PMID: 38485258 PMCID: PMC11079980 DOI: 10.1523/jneurosci.1945-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/25/2024] [Accepted: 02/27/2024] [Indexed: 03/26/2024] Open
Abstract
The superior colliculus receives powerful synaptic inputs from corticotectal neurons in the visual cortex. The function of these corticotectal neurons remains largely unknown due to a limited understanding of their response properties and connectivity. Here, we use antidromic methods to identify corticotectal neurons in awake male and female rabbits, and measure their axonal conduction times, thalamic inputs and receptive field properties. All corticotectal neurons responded to sinusoidal drifting gratings with a nonlinear (nonsinusoidal) increase in mean firing rate but showed pronounced differences in their ON-OFF receptive field structures that we classified into three groups, Cx, S2, and S1. Cx receptive fields had highly overlapping ON and OFF subfields as classical complex cells, S2 had largely separated ON and OFF subfields as classical simple cells, and S1 had a single ON or OFF subfield. Thus, all corticotectal neurons are homogeneous in their nonlinear spatial summation but very heterogeneous in their spatial integration of ON and OFF inputs. The Cx type had the fastest conducting axons, the highest spontaneous activity, and the strongest and fastest visual responses. The S2 type had the highest orientation selectivity, and the S1 type had the slowest conducting axons. Moreover, our cross-correlation analyses found that a subpopulation of corticotectal neurons with very fast conducting axons and high spontaneous firing rates (largely "Cx" type) receives monosynaptic input from retinotopically aligned thalamic neurons. This previously unrecognized fast-conducting thalamic-mediated corticotectal pathway may provide specialized information to superior colliculus and prime recipient neurons for subsequent corticotectal or retinal synaptic input.
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Affiliation(s)
- Chuyi Su
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
| | | | - Jose-Manuel Alonso
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Harvey A Swadlow
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Yulia Bereshpolova
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
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6
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Liu J, He Y, Lavoie A, Bouvier G, Liu BH. A direction-selective cortico-brainstem pathway adaptively modulates innate behaviors. Nat Commun 2023; 14:8467. [PMID: 38123558 PMCID: PMC10733370 DOI: 10.1038/s41467-023-42910-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 10/25/2023] [Indexed: 12/23/2023] Open
Abstract
Sensory cortices modulate innate behaviors through corticofugal projections targeting phylogenetically-old brainstem nuclei. However, the principles behind the functional connectivity of these projections remain poorly understood. Here, we show that in mice visual cortical neurons projecting to the optic-tract and dorsal-terminal nuclei (NOT-DTN) possess distinct response properties and anatomical connectivity, supporting the adaption of an essential innate eye movement, the optokinetic reflex (OKR). We find that these corticofugal neurons are enriched in specific visual areas, and they prefer temporo-nasal visual motion, matching the direction bias of downstream NOT-DTN neurons. Remarkably, continuous OKR stimulation selectively enhances the activity of these temporo-nasally biased cortical neurons, which can efficiently promote OKR plasticity. Lastly, we demonstrate that silencing downstream NOT-DTN neurons, which project specifically to the inferior olive-a key structure in oculomotor plasticity, impairs the cortical modulation of OKR and OKR plasticity. Our results unveil a direction-selective cortico-brainstem pathway that adaptively modulates innate behaviors.
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Affiliation(s)
- Jiashu Liu
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, L5L 1C6, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, M5S 3G5, Canada
| | - Yingtian He
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, L5L 1C6, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, M5S 3G5, Canada
| | - Andreanne Lavoie
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, L5L 1C6, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, M5S 3G5, Canada
| | - Guy Bouvier
- Université Paris-Saclay, CNRS, Institut des Neurosciences Paris-Saclay, 91400, Saclay, France
| | - Bao-Hua Liu
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, L5L 1C6, Canada.
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, M5S 3G5, Canada.
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Neske GT, Cardin JA. Transthalamic input to higher-order cortex selectively conveys state information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.08.561424. [PMID: 37873181 PMCID: PMC10592671 DOI: 10.1101/2023.10.08.561424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Communication among different neocortical areas is largely thought to be mediated by long-range synaptic interactions between cortical neurons, with the thalamus providing only an initial relay of information from the sensory periphery. Higher-order thalamic nuclei receive strong synaptic inputs from the cortex and send robust projections back to other cortical areas, providing a distinct and potentially critical route for cortico-cortical communication. However, the relative contributions of corticocortical and thalamocortical inputs to higher-order cortical function remain unclear. Using imaging of cortical neurons and projection axon terminals in combination with optogenetic manipulations, we find that the higher-order visual thalamus of mice conveys a specialized stream of information to higher-order visual cortex. Whereas corticocortical projections from lower cortical areas convey robust visual information, higher-order thalamocortical projections convey strong behavioral state information. Together, these findings suggest a key role for higher-order thalamus in providing contextual signals that flexibly modulate sensory processing in higher-order cortex.
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Affiliation(s)
- Garrett T. Neske
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA
- Present address: Department of Physiology and Biophysics, State University of New York at Buffalo, Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY, USA
| | - Jessica A. Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Neuroscience Institute, Yale University, New Haven, CT, USA
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. Cell Rep 2023; 42:113088. [PMID: 37682710 PMCID: PMC10618959 DOI: 10.1016/j.celrep.2023.113088] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/12/2023] [Accepted: 08/17/2023] [Indexed: 09/10/2023] Open
Abstract
Cortical circuit function is regulated by extensively interconnected, diverse populations of GABAergic interneurons that may play key roles in shaping circuit operation according to behavioral context. A specialized population of interneurons that co-express vasoactive intestinal peptides (VIP-INs) are activated during arousal and innervate other INs and pyramidal neurons (PNs). Although state-dependent modulation of VIP-INs has been extensively studied, their role in regulating sensory processing is less well understood. We examined the impact of VIP-INs in the primary visual cortex of awake behaving mice. Loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing INs (SST-INs) but not PNs. In contrast, reduced VIP-IN activity globally disrupts visual feature selectivity for stimulus size. Moreover, the impact of VIP-INs on perceptual behavior varies with context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA.
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Kong C, Wang Y, Xiao G. Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice. Front Cell Neurosci 2023; 17:1238777. [PMID: 37817884 PMCID: PMC10560757 DOI: 10.3389/fncel.2023.1238777] [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: 06/12/2023] [Accepted: 09/05/2023] [Indexed: 10/12/2023] Open
Abstract
Introduction The visual cortex is a key region in the mouse brain, responsible for processing visual information. Comprised of six distinct layers, each with unique neuronal types and connections, the visual cortex exhibits diverse decoding properties across its layers. This study aimed to investigate the relationship between visual stimulus decoding properties and the cortical layers of the visual cortex while considering how this relationship varies across different decoders and brain regions. Methods This study reached the above conclusions by analyzing two publicly available datasets obtained through two-photon microscopy of visual cortex neuronal responses. Various types of decoders were tested for visual cortex decoding. Results Our findings indicate that the decoding accuracy of neuronal populations with consistent sizes varies among visual cortical layers for visual stimuli such as drift gratings and natural images. In particular, layer 4 neurons in VISp exhibited significantly higher decoding accuracy for visual stimulus identity compared to other layers. However, in VISm, the decoding accuracy of neuronal populations with the same size in layer 2/3 was higher than that in layer 4, despite the overall accuracy being lower than that in VISp and VISl. Furthermore, SVM surpassed other decoders in terms of accuracy, with the variation in decoding performance across layers being consistent among decoders. Additionally, we found that the difference in decoding accuracy across different imaging depths was not associated with the mean orientation selectivity index (OSI) and the mean direction selectivity index (DSI) neurons, but showed a significant positive correlation with the mean reliability and mean signal-to-noise ratio (SNR) of each layer's neuron population. Discussion These findings lend new insights into the decoding properties of the visual cortex, highlighting the role of different cortical layers and decoders in determining decoding accuracy. The correlations identified between decoding accuracy and factors such as reliability and SNR pave the way for more nuanced understandings of visual cortex functioning.
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Affiliation(s)
- Chui Kong
- School of Information Science and Technology, Fudan University, Shanghai, China
- Department of Communication Science and Engineering, Fudan University, Shanghai, China
| | - Yangzhen Wang
- School of Information Science and Technology, Fudan University, Shanghai, China
- Department of Automation, Tsinghua University, Beijing, China
| | - Guihua Xiao
- School of Information Science and Technology, Fudan University, Shanghai, China
- Department of Automation, Tsinghua University, Beijing, China
- BNRist, Tsinghua University, Beijing, China
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10
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.14.532664. [PMID: 37162871 PMCID: PMC10168200 DOI: 10.1101/2023.03.14.532664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Local cortical circuit function is regulated by diverse populations of GABAergic interneurons with distinct properties and extensive interconnectivity. Inhibitory-to-inhibitory interactions between interneuron populations may play key roles in shaping circuit operation according to behavioral context. A specialized population of GABAergic interneurons that co-express vasoactive intestinal peptide (VIP-INs) are activated during arousal and locomotion and innervate other local interneurons and pyramidal neurons. Although modulation of VIP-IN activity by behavioral state has been extensively studied, their role in regulating information processing and selectivity is less well understood. Using a combination of cellular imaging, short and long-term manipulation, and perceptual behavior, we examined the impact of VIP-INs on their synaptic target populations in the primary visual cortex of awake behaving mice. We find that loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing interneurons (SST-INs) but not pyramidal neurons (PNs). In contrast, reduced VIP-IN activity disrupts visual feature selectivity for stimulus size in both populations. Inhibitory-to inhibitory interactions thus directly shape the selectivity of GABAergic interneurons for sensory stimuli. Moreover, the impact of VIP-IN activity on perceptual behavior varies with visual context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical circuit activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
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11
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Mohan H, An X, Xu XH, Kondo H, Zhao S, Matho KS, Wang BS, Musall S, Mitra P, Huang ZJ. Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks. Nat Neurosci 2023; 26:481-494. [PMID: 36690901 PMCID: PMC10571488 DOI: 10.1038/s41593-022-01244-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 12/02/2022] [Indexed: 01/24/2023]
Abstract
The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection-neuron-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, during spontaneous movements and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of ITsPlxnD1 and PTsFezf2 in subnetwork nodes disrupted distinct components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and projection-neuron-type specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.
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Affiliation(s)
- Hemanth Mohan
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xu An
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - X Hermione Xu
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Hideki Kondo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Shengli Zhao
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | | | - Bor-Shuen Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Simon Musall
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Institute of Biological information Processing, Forschungszentrum Julich, Julich, Germany
| | - Partha Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Z Josh Huang
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
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12
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Wang H, Dey O, Lagos WN, Callaway EM. Diversity in spatial frequency, temporal frequency, and speed tuning across mouse visual cortical areas and layers. J Comp Neurol 2022; 530:3226-3247. [PMID: 36070574 PMCID: PMC9588602 DOI: 10.1002/cne.25404] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 08/15/2022] [Accepted: 08/18/2022] [Indexed: 11/06/2022]
Abstract
The mouse visual system consists of several visual cortical areas thought to be specialized for different visual features and/or tasks. Previous studies have revealed differences between primary visual cortex (V1) and other higher visual areas, namely, anterolateral (AL) and posteromedial (PM), and their tuning preferences for spatial and temporal frequency. However, these differences have primarily been characterized using methods that are biased toward superficial layers of cortex, such as two-photon calcium imaging. Fewer studies have investigated cell types in deeper layers of these areas and their tuning preferences. Because superficial versus deep-layer neurons and different types of deep-layer neurons are known to have different feedforward and feedback inputs and outputs, comparing the tuning preferences of these groups is important for understanding cortical visual information processing. In this study, we used extracellular electrophysiology and two-photon calcium imaging targeted toward two different layer 5 cell classes to characterize their tuning properties in V1, AL, and PM. We find that deep-layer neurons, similar to superficial layer neurons, are also specialized for different spatial and temporal frequencies, with the strongest differences between AL and V1, and AL and PM, but not V1 and PM. However, we note that the deep-layer neuron populations preferred a larger range of SFs and TFs compared to previous studies. We also find that extratelencephalically projecting layer 5 neurons are more direction selective than intratelencephalically projecting layer 5 neurons.
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Affiliation(s)
- Helen Wang
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Oyshi Dey
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Willian N. Lagos
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Edward M. Callaway
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
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13
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Rindner DJ, Proddutur A, Lur G. Cell-type-specific integration of feedforward and feedback synaptic inputs in the posterior parietal cortex. Neuron 2022; 110:3760-3773.e5. [PMID: 36087582 PMCID: PMC9671855 DOI: 10.1016/j.neuron.2022.08.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 07/19/2022] [Accepted: 08/16/2022] [Indexed: 12/15/2022]
Abstract
The integration of feedforward (sensory) and feedback (top-down) neuronal signals is a principal function of the neocortex. Yet, we have limited insight into how these information streams are combined by individual neurons. Using a two-color optogenetic strategy, we found that layer 5 pyramidal neurons in the posterior parietal cortex receive monosynaptic dual innervation, combining sensory inputs with top-down signals. Subclasses of layer 5 pyramidal neurons integrated these synapses with distinct temporal dynamics. Specifically, regular spiking cells exhibited supralinear enhancement of delayed-but not coincident-inputs, while intrinsic burst-firing neurons selectively boosted coincident synaptic events. These subthreshold integration characteristics translated to a nonlinear summation of action potential firing. Complementing electrophysiology with computational modeling, we found that distinct integration profiles arose from a cell-type-specific interaction of ionic mechanisms and feedforward inhibition. These data provide insight into the cellular properties that guide the nonlinear interaction of distinct long-range afferents in the neocortex.
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Affiliation(s)
- Daniel J Rindner
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Archana Proddutur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Gyorgy Lur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA.
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14
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Tuning instability of non-columnar neurons in the salt-and-pepper whisker map in somatosensory cortex. Nat Commun 2022; 13:6611. [PMID: 36329010 PMCID: PMC9633707 DOI: 10.1038/s41467-022-34261-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
Rodent sensory cortex contains salt-and-pepper maps of sensory features, whose structure is not fully known. Here we investigated the structure of the salt-and-pepper whisker somatotopic map among L2/3 pyramidal neurons in somatosensory cortex, in awake mice performing one-vs-all whisker discrimination. Neurons tuned for columnar (CW) and non-columnar (non-CW) whiskers were spatially intermixed, with co-tuned neurons forming local (20 µm) clusters. Whisker tuning was markedly unstable in expert mice, with 35-46% of pyramidal cells significantly shifting tuning over 5-18 days. Tuning instability was highly concentrated in non-CW tuned neurons, and thus was structured in the map. Instability of non-CW neurons was unchanged during chronic whisker paralysis and when mice discriminated individual whiskers, suggesting it is an inherent feature. Thus, L2/3 combines two distinct components: a stable columnar framework of CW-tuned cells that may promote spatial perceptual stability, plus an intermixed, non-columnar surround with highly unstable tuning.
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15
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Zhou W, Ke S, Li W, Yuan J, Li X, Jin R, Jia X, Jiang T, Dai Z, He G, Fang Z, Shi L, Zhang Q, Gong H, Luo Q, Sun W, Li A, Li P. Mapping the Function of Whole-Brain Projection at the Single Neuron Level. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2202553. [PMID: 36228099 PMCID: PMC9685445 DOI: 10.1002/advs.202202553] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Axonal projection conveys neural information. The divergent and diverse projections of individual neurons imply the complexity of information flow. It is necessary to investigate the relationship between the projection and functional information at the single neuron level for understanding the rules of neural circuit assembly, but a gap remains due to a lack of methods to map the function to whole-brain projection. Here an approach is developed to bridge two-photon calcium imaging in vivo with high-resolution whole-brain imaging based on sparse labeling with the genetically encoded calcium indicator GCaMP6. Reliable whole-brain projections are captured by the high-definition fluorescent micro-optical sectioning tomography (HD-fMOST). A cross-modality cell matching is performed and the functional annotation of whole-brain projection at the single-neuron level (FAWPS) is obtained. Applying it to the layer 2/3 (L2/3) neurons in mouse visual cortex, the relationship is investigated between functional preferences and axonal projection features. The functional preference of projection motifs and the correlation between axonal length in MOs and neuronal orientation selectivity, suggest that projection motif-defined neurons form a functionally specific information flow, and the projection strength in specific targets relates to the information clarity. This pipeline provides a new way to understand the principle of neuronal information transmission.
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Affiliation(s)
- Wei Zhou
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Shanshan Ke
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Wenwei Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Jing Yuan
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Xiangning Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Rui Jin
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Xueyan Jia
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Tao Jiang
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Zimin Dai
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Guannan He
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Zhiwei Fang
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Liang Shi
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Qi Zhang
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
| | - Hui Gong
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical EngineeringHainan UniversityHaikou570228China
| | - Wenzhi Sun
- Chinese Institute for Brain ResearchBeijing102206China
- School of Basic Medical SciencesCapital Medical UniversityBeijing100069China
| | - Anan Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
| | - Pengcheng Li
- Britton Chance Center and MoE Key Laboratory for Biomedical PhotonicsWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and ImagingChinese Academy of Medical SciencesHUST‐Suzhou Institute for BrainsmaticsJITRISuzhou215100China
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16
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Moberg S, Takahashi N. Neocortical layer 5 subclasses: From cellular properties to roles in behavior. Front Synaptic Neurosci 2022; 14:1006773. [PMID: 36387773 PMCID: PMC9650089 DOI: 10.3389/fnsyn.2022.1006773] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/28/2022] [Indexed: 09/08/2024] Open
Abstract
Layer 5 (L5) serves as the main output layer of cortical structures, where long-range projecting pyramidal neurons broadcast the columnar output to other cortical and extracortical regions of the brain. L5 pyramidal neurons are grouped into two subclasses based on their projection targets; while intratelencephalic (IT) neurons project to cortical areas and the striatum, extratelencephalic (ET) neurons project to subcortical areas such as the thalamus, midbrain, and brainstem. Each L5 subclass possesses distinct morphological and electrophysiological properties and is incorporated into a unique synaptic network. Thanks to recent advances in genetic tools and methodologies, it has now become possible to distinguish between the two subclasses in the living brain. There is increasing evidence indicating that each subclass plays a unique role in sensory processing, decision-making, and learning. This review first summarizes the anatomical and physiological properties as well as the neuromodulation of IT and ET neurons in the rodent neocortex, and then reviews recent literature on their roles in sensory processing and rodent behavior. Our ultimate goal is to provide a comprehensive understanding of the role of each subclass in cortical function by examining their operational regimes based on their cellular properties.
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Affiliation(s)
- Sara Moberg
- Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Naoya Takahashi
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, Bordeaux, France
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17
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Campagnola L, Seeman SC, Chartrand T, Kim L, Hoggarth A, Gamlin C, Ito S, Trinh J, Davoudian P, Radaelli C, Kim MH, Hage T, Braun T, Alfiler L, Andrade J, Bohn P, Dalley R, Henry A, Kebede S, Mukora A, Sandman D, Williams G, Larsen R, Teeter C, Daigle TL, Berry K, Dotson N, Enstrom R, Gorham M, Hupp M, Lee SD, Ngo K, Nicovich PR, Potekhina L, Ransford S, Gary A, Goldy J, McMillen D, Pham T, Tieu M, Siverts L, Walker M, Farrell C, Schroedter M, Slaughterbeck C, Cobb C, Ellenbogen R, Gwinn RP, Keene CD, Ko AL, Ojemann JG, Silbergeld DL, Carey D, Casper T, Crichton K, Clark M, Dee N, Ellingwood L, Gloe J, Kroll M, Sulc J, Tung H, Wadhwani K, Brouner K, Egdorf T, Maxwell M, McGraw M, Pom CA, Ruiz A, Bomben J, Feng D, Hejazinia N, Shi S, Szafer A, Wakeman W, Phillips J, Bernard A, Esposito L, D’Orazi FD, Sunkin S, Smith K, Tasic B, Arkhipov A, Sorensen S, Lein E, Koch C, Murphy G, Zeng H, Jarsky T. Local connectivity and synaptic dynamics in mouse and human neocortex. Science 2022; 375:eabj5861. [PMID: 35271334 PMCID: PMC9970277 DOI: 10.1126/science.abj5861] [Citation(s) in RCA: 159] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.
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Affiliation(s)
| | | | | | - Lisa Kim
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Clare Gamlin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Shinya Ito
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Travis Hage
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Phillip Bohn
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Alex Henry
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Sara Kebede
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Alice Mukora
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | - Kyla Berry
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Nadia Dotson
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Madie Hupp
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Kiet Ngo
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | - Charles Cobb
- The Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA, USA
| | - Richard Ellenbogen
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Ryder P Gwinn
- Epilepsy Surgery and Functional Neurosurgery, Swedish Neuroscience Institute, Seattle, WA, USA
| | - C. Dirk Keene
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Andrew L Ko
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA,Regional Epilepsy Center at Harborview Medical Center, Seattle, WA, USA
| | - Jeffrey G Ojemann
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA,Regional Epilepsy Center at Harborview Medical Center, Seattle, WA, USA
| | - Daniel L Silbergeld
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Daniel Carey
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Medea McGraw
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - David Feng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Shu Shi
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Aaron Szafer
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Amy Bernard
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Susan Sunkin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Gabe Murphy
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Jarsky
- Allen Institute for Brain Science, Seattle, WA, USA,Corresponding author:
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18
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Zhaoping L. Parallel Advantage: Further Evidence for Bottom-up Saliency Computation by Human Primary Visual Cortex. Perception 2022; 51:60-69. [PMID: 35025626 PMCID: PMC8938995 DOI: 10.1177/03010066211062583] [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] [Indexed: 11/15/2022]
Abstract
Finding a target among uniformly oriented non-targets is typically faster when this target is perpendicular, rather than parallel, to the non-targets. The V1 Saliency Hypothesis (V1SH), that neurons in the primary visual cortex (V1) signal saliency for exogenous attentional attraction, predicts exactly the opposite in a special case: each target or non-target comprises two equally sized disks displaced from each other by 1.2 disk diameters center-to-center along a line defining its orientation. A target has two white or two black disks. Each non-target has one white disk and one black disk, and thus, unlike the target, activates V1 neurons less when its orientation is parallel rather than perpendicular to the neurons' preferred orientations. When the target is parallel, rather than perpendicular, to the uniformly oriented non-targets, the target's evoked V1 response escapes V1's iso-orientation surround suppression, making the target more salient. I present behavioral observations confirming this prediction.
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Affiliation(s)
- Li Zhaoping
- University of Tübingen, 28328Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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19
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Cheung V, Chung P, Bjorni M, Shvareva VA, Lopez YC, Feinberg EH. Virally encoded connectivity transgenic overlay RNA sequencing (VECTORseq) defines projection neurons involved in sensorimotor integration. Cell Rep 2021; 37:110131. [PMID: 34936877 PMCID: PMC8719358 DOI: 10.1016/j.celrep.2021.110131] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/26/2021] [Accepted: 11/22/2021] [Indexed: 02/05/2023] Open
Abstract
Behavior arises from concerted activity throughout the brain. Consequently, a major focus of modern neuroscience is defining the physiology and behavioral roles of projection neurons linking different brain areas. Single-cell RNA sequencing has facilitated these efforts by revealing molecular determinants of cellular physiology and markers that enable genetically targeted perturbations such as optogenetics, but existing methods for sequencing defined projection populations are low throughput, painstaking, and costly. We developed a straightforward, multiplexed approach, virally encoded connectivity transgenic overlay RNA sequencing (VECTORseq). VECTORseq repurposes commercial retrogradely infecting viruses typically used to express functional transgenes (e.g., recombinases and fluorescent proteins) by treating viral transgene mRNA as barcodes within single-cell datasets. VECTORseq is compatible with different viral families, resolves multiple populations with different projection targets in one sequencing run, and identifies cortical and subcortical excitatory and inhibitory projection populations. Our study provides a roadmap for high-throughput identification of neuronal subtypes based on connectivity.
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Affiliation(s)
- Victoria Cheung
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA.
| | - Philip Chung
- Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA 98195, USA
| | - Max Bjorni
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Varvara A Shvareva
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yesenia C Lopez
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Evan H Feinberg
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA.
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20
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Schneider M, Broggini AC, Dann B, Tzanou A, Uran C, Sheshadri S, Scherberger H, Vinck M. A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power. Neuron 2021; 109:4050-4067.e12. [PMID: 34637706 PMCID: PMC8691951 DOI: 10.1016/j.neuron.2021.09.037] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 07/14/2021] [Accepted: 09/17/2021] [Indexed: 11/21/2022]
Abstract
Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.
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Affiliation(s)
- Marius Schneider
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | | | - Athanasia Tzanou
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Swathi Sheshadri
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Hansjörg Scherberger
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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21
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Resulaj A. Projections of the Mouse Primary Visual Cortex. Front Neural Circuits 2021; 15:751331. [PMID: 34867213 PMCID: PMC8641241 DOI: 10.3389/fncir.2021.751331] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/28/2021] [Indexed: 11/13/2022] Open
Abstract
Lesion or damage to the primary visual cortex (V1) results in a profound loss of visual perception in humans. Similarly, in mice, optogenetic silencing of V1 profoundly impairs discrimination of orientated gratings. V1 is thought to have such a critical role in perception in part due to its position in the visual processing hierarchy. It is the first brain area in the neocortex to receive visual input, and it distributes this information to more than 18 brain areas. Here I review recent advances in our understanding of the organization and function of the V1 projections in the mouse. This progress is in part due to new anatomical and viral techniques that allow for efficient labeling of projection neurons. In the final part of the review, I conclude by highlighting challenges and opportunities for future research.
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Affiliation(s)
- Arbora Resulaj
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, Canada.,Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
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22
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Yi JH, Choe SY, Jung MW. Variations in Commissural Input Processing Across Different Types of Cortical Projection Neurons. Cereb Cortex 2021; 32:2508-2520. [PMID: 34607355 DOI: 10.1093/cercor/bhab361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 09/02/2021] [Accepted: 09/03/2021] [Indexed: 11/14/2022] Open
Abstract
To understand how incoming cortical inputs are processed by different types of cortical projection neurons in the medial prefrontal cortex, we compared intrinsic physiological properties of and commissural excitatory/inhibitory influences on layer 5 intratelencephalic (IT), layer 5 pyramidal tract (PT), and layers 2/3 IT projection neurons. We found that intrinsic physiological properties and commissural synaptic transmission varied across the three types of projection neurons. The rank order of intrinsic excitability was layer 5 PT > layer 5 IT > layers 2/3 IT neurons. Commissural connectivity was higher in layers 2/3 than layer 5 projection neurons, but commissural excitatory influence was stronger on layer 5 than layers 2/3 pyramidal neurons. Paired-pulse ratio was also greater in PT than IT neurons. These results indicate that commissural inputs activate deep layer PT neurons most preferentially and superficial layer IT neurons least preferentially. Deep layer PT neurons might faithfully transmit cortical input signals to downstream subcortical structures for reliable control of behavior, whereas superficial layer IT neurons might integrate cortical input signals from diverse sources in support of higher-order cognitive functions.
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Affiliation(s)
- Jee Hyun Yi
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
| | - Seo Yeon Choe
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
| | - Min Whan Jung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea.,Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
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23
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Speed A, Haider B. Probing mechanisms of visual spatial attention in mice. Trends Neurosci 2021; 44:822-836. [PMID: 34446296 PMCID: PMC8484049 DOI: 10.1016/j.tins.2021.07.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 11/25/2022]
Abstract
The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.
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Affiliation(s)
- Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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24
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Bae JW, Jeong H, Yoon YJ, Bae CM, Lee H, Paik SB, Jung MW. Parallel processing of working memory and temporal information by distinct types of cortical projection neurons. Nat Commun 2021; 12:4352. [PMID: 34272368 PMCID: PMC8285375 DOI: 10.1038/s41467-021-24565-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 06/18/2021] [Indexed: 02/06/2023] Open
Abstract
It is unclear how different types of cortical projection neurons work together to support diverse cortical functions. We examined the discharge characteristics and inactivation effects of intratelencephalic (IT) and pyramidal tract (PT) neurons-two major types of cortical excitatory neurons that project to cortical and subcortical structures, respectively-in the deep layer of the medial prefrontal cortex in mice performing a delayed response task. We found stronger target-dependent firing of IT than PT neurons during the delay period. We also found the inactivation of IT neurons, but not PT neurons, impairs behavioral performance. In contrast, PT neurons carry more temporal information than IT neurons during the delay period. Our results indicate a division of labor between IT and PT projection neurons in the prefrontal cortex for the maintenance of working memory and for tracking the passage of time, respectively.
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Affiliation(s)
- Jung Won Bae
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Huijeong Jeong
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, Korea
| | - Young Ju Yoon
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Chan Mee Bae
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, Korea
| | - Hyeonsu Lee
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Se-Bum Paik
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Min Whan Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, Korea.
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25
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Niell CM, Scanziani M. How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model. Annu Rev Neurosci 2021; 44:517-546. [PMID: 33914591 PMCID: PMC9925090 DOI: 10.1146/annurev-neuro-102320-085825] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.
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Affiliation(s)
- Cristopher M. Niell
- Department of Biology and Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, USA
| | - Massimo Scanziani
- Department of Physiology and Howard Hughes Medical Institute, University of California San Francisco, San Francisco, California 94158, USA;
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26
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Bauer R, Clowry GJ, Kaiser M. Creative Destruction: A Basic Computational Model of Cortical Layer Formation. Cereb Cortex 2021; 31:3237-3253. [PMID: 33625496 PMCID: PMC8196252 DOI: 10.1093/cercor/bhab003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 12/23/2020] [Accepted: 12/23/2020] [Indexed: 12/13/2022] Open
Abstract
One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus, and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multiscale, agent-based model, comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure. Importantly, apoptosis allows for changing the thickness of one layer without automatically affecting other layers. Therefore, apoptosis increases the flexibility for evolutionary change in layer architecture. Notably, slightly changed gene regulatory dynamics recapitulate the characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.
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Affiliation(s)
- Roman Bauer
- Department of Computer Science, University of Surrey, Guildford, GU2 7XH, UK
| | - Gavin J Clowry
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Marcus Kaiser
- School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- Precision Imaging Beacon, School of Medicine, University of Nottingham, Nottingham NG7 2UH, UK
- Rui Jin Hospital, Shanghai Jiao Tong University, Shanghai 200025, China
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27
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Puścian A, Benisty H, Higley MJ. NMDAR-Dependent Emergence of Behavioral Representation in Primary Visual Cortex. Cell Rep 2021; 32:107970. [PMID: 32726633 DOI: 10.1016/j.celrep.2020.107970] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 01/28/2020] [Accepted: 07/08/2020] [Indexed: 10/23/2022] Open
Abstract
Although neocortical sensory areas are generally thought to faithfully represent external stimuli, cortical networks exhibit considerable functional plasticity, allowing them to modify their output to reflect ongoing behavioral demands. We apply longitudinal 2-photon imaging of activity in the primary visual cortex (V1) of mice learning a conditioned eyeblink task to investigate the dynamic representations of task-relevant information. We find that, although all V1 neurons robustly and stably encode visual input, pyramidal cells and parvalbumin-expressing interneurons exhibit experience-dependent emergence of accurate behavioral representations during learning. The functional plasticity driving performance-predictive activity requires cell-autonomous expression of NMDA-type glutamate receptors. Our findings demonstrate that accurate encoding of behavioral output is not inherent to V1 but develops during learning to support visual task performance.
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Affiliation(s)
- Alicja Puścian
- Department of Neuroscience, Kavli Institute of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA; Nencki-EMBL Partnership for Neural Plasticity and Brain Disorders - BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Pasteur 3 Street, 02-093 Warsaw, Poland.
| | - Hadas Benisty
- Department of Neuroscience, Kavli Institute of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.
| | - Michael J Higley
- Department of Neuroscience, Kavli Institute of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.
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28
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Ruediger S, Scanziani M. Learning speed and detection sensitivity controlled by distinct cortico-fugal neurons in visual cortex. eLife 2020; 9:e59247. [PMID: 33284107 PMCID: PMC7748414 DOI: 10.7554/elife.59247] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 12/06/2020] [Indexed: 12/22/2022] Open
Abstract
Vertebrates can change their behavior upon detection of visual stimuli according to the outcome their actions produce. Such goal-directed behavior involves evolutionary conserved brain structures like the striatum and optic tectum, which receive ascending visual input from the periphery. In mammals, however, these structures also receive descending visual input from visual cortex (VC), via neurons that give rise to cortico-fugal projections. The function of cortico-fugal neurons in visually guided, goal-directed behavior remains unclear. Here, we address the impact of two populations of cortico-fugal neurons in mouse VC in the learning and performance of a visual detection task. We show that the ablation of striatal projecting neurons reduces learning speed, whereas the ablation of superior colliculus projecting neurons does not impact learning but reduces detection sensitivity. This functional dissociation between distinct cortico-fugal neurons in controlling learning speed and detection sensitivity suggests an adaptive contribution of cortico-fugal pathways even in simple goal-directed behavior.
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Affiliation(s)
- Sarah Ruediger
- Center for Neural Circuits and Behavior, Neurobiology Section and Department of Neuroscience, University of California, San DiegoLa JollaUnited States
- Department of Physiology, University of California, San FranciscoSan FranciscoUnited States
- Howard Hughes Medical Institute, University of California, San FranciscoSan FranciscoUnited States
| | - Massimo Scanziani
- Center for Neural Circuits and Behavior, Neurobiology Section and Department of Neuroscience, University of California, San DiegoLa JollaUnited States
- Department of Physiology, University of California, San FranciscoSan FranciscoUnited States
- Howard Hughes Medical Institute, University of California, San FranciscoSan FranciscoUnited States
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29
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Popescu IR, Le KQ, Ducote AL, Li JE, Leland AE, Mostany R. Increased intrinsic excitability and decreased synaptic inhibition in aged somatosensory cortex pyramidal neurons. Neurobiol Aging 2020; 98:88-98. [PMID: 33249377 DOI: 10.1016/j.neurobiolaging.2020.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 09/02/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022]
Abstract
Sensorimotor performance declines during advanced age, partially due to deficits in somatosensory acuity. Cortical receptive field expansion contributes to somatosensory deficits, suggesting increased excitability or decreased inhibition in primary somatosensory cortex (S1) pyramidal neurons. To ascertain changes in excitability and inhibition, we measured both properties in neurons from vibrissal S1 in brain slices from young and aged mice. Because adapting and non-adapting neurons-the principal pyramidal types in layer 5 (L5)-differ in intrinsic properties and inhibitory inputs, we determined age-dependent changes according to neuron type. We found an age-dependent increase in intrinsic excitability in adapting neurons, caused by a decrease in action potential threshold. Surprisingly, in non-adapting neurons we found both an increase in excitability caused by increased input resistance, and a decrease in synaptic inhibition. Spike frequency adaptation, already small in non-adapting neurons, was further reduced by aging, whereas sag, a manifestation of Ih, was increased. Therefore, aging caused both decreased inhibition and increased intrinsic excitability, but these effects were specific to pyramidal neuron type.
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Affiliation(s)
- Ion R Popescu
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA.
| | - Kathy Q Le
- Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | - Alexis L Ducote
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA; Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | - Jennifer E Li
- Tulane Brain Institute, Tulane University, New Orleans, LA, USA
| | | | - Ricardo Mostany
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA; Tulane Brain Institute, Tulane University, New Orleans, LA, USA
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30
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Hagihara KM, Ishikawa AW, Yoshimura Y, Tagawa Y, Ohki K. Long-Range Interhemispheric Projection Neurons Show Biased Response Properties and Fine-Scale Local Subnetworks in Mouse Visual Cortex. Cereb Cortex 2020; 31:1307-1315. [PMID: 33063102 DOI: 10.1093/cercor/bhaa297] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 08/20/2020] [Accepted: 09/08/2020] [Indexed: 12/24/2022] Open
Abstract
Integration of information processed separately in distributed brain regions is essential for brain functions. This integration is enabled by long-range projection neurons, and further, concerted interactions between long-range projections and local microcircuits are crucial. It is not well known, however, how this interaction is implemented in cortical circuits. Here, to decipher this logic, using callosal projection neurons (CPNs) in layer 2/3 of the mouse visual cortex as a model of long-range projections, we found that CPNs exhibited distinct response properties and fine-scale local connectivity patterns. In vivo 2-photon calcium imaging revealed that CPNs showed a higher ipsilateral (to their somata) eye preference, and that CPN pairs showed stronger signal/noise correlation than random pairs. Slice recordings showed CPNs were preferentially connected to CPNs, demonstrating the existence of projection target-dependent fine-scale subnetworks. Collectively, our results suggest that long-range projection target predicts response properties and local connectivity of cortical projection neurons.
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Affiliation(s)
- Kenta M Hagihara
- Department of Molecular Physiology, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan.,Friedrich Miescher Institute for Biomedical Research, Basel 4058, Switzerland
| | - Ayako Wendy Ishikawa
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8585, Japan.,Department of Physiological Sciences, The Graduate University for Advanced Studies, Okazaki 444-8585, Japan.,Keio University School of Medicine, Shinanomachi, Shinjuku-ku, 160-8582, Japan
| | - Yumiko Yoshimura
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8585, Japan.,Department of Physiological Sciences, The Graduate University for Advanced Studies, Okazaki 444-8585, Japan
| | - Yoshiaki Tagawa
- Department of Biophysics, Kyoto University Graduate School of Science, Kyoto 606-8502, Japan.,Department of Physiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8544, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Kenichi Ohki
- Department of Molecular Physiology, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan.,Department of Physiology, The University of Tokyo School of Medicine, Tokyo 113-0033, Japan.,International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo School of Medicine, Tokyo 113-0033, Japan.,Institute for AI and Beyond, The University of Tokyo School of Medicine, Tokyo 113-0033, Japan
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31
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Zhang Y, Zhang X. Portrait of visual cortical circuits for generating neural oscillation dynamics. Cogn Neurodyn 2020; 15:3-16. [PMID: 34109010 DOI: 10.1007/s11571-020-09623-4] [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: 12/30/2019] [Revised: 07/17/2020] [Accepted: 07/24/2020] [Indexed: 11/30/2022] Open
Abstract
The mouse primary visual cortex (V1) has emerged as a classical system to study neural circuit mechanisms underlying visual function and plasticity. A variety of efferent-afferent neuronal connections exists within the V1 and between the V1 and higher visual cortical areas or thalamic nuclei, indicating that the V1 system is more than a mere receiver in information processing. Sensory representations in the V1 are dynamically correlated with neural activity oscillations that are distributed across different cortical layers in an input-dependent manner. Circuits consisting of excitatory pyramidal cells (PCs) and inhibitory interneurons (INs) are the basis for generating neural oscillations. In general, INs are clustered with their adjacent PCs to form specific microcircuits that gate or filter the neural information. The interaction between these two cell populations has to be coordinated within a local circuit in order to preserve neural coding schemes and maintain excitation-inhibition (E-I) balance. Phasic alternations of the E-I balance can dynamically regulate temporal rhythms of neural oscillation. Accumulating experimental evidence suggests that the two major sub-types of INs, parvalbumin-expressing (PV+) cells and somatostatin-expressing (SOM+) INs, are active in controlling slow and fast oscillations, respectively, in the mouse V1. The review summarizes recent experimental findings on elucidating cellular or circuitry mechanisms for the generation of neural oscillations with distinct rhythms in either developing or matured mouse V1, mainly focusing on visual relaying circuits and distinct local inhibitory circuits.
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Affiliation(s)
- Yuan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
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32
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Hamodi AS, Martinez Sabino A, Fitzgerald ND, Moschou D, Crair MC. Transverse sinus injections drive robust whole-brain expression of transgenes. eLife 2020; 9:e53639. [PMID: 32420870 PMCID: PMC7266618 DOI: 10.7554/elife.53639] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 05/18/2020] [Indexed: 11/13/2022] Open
Abstract
Convenient, efficient and fast whole-brain delivery of transgenes presents a persistent experimental challenge in neuroscience. Recent advances demonstrate whole-brain gene delivery by retro-orbital injection of virus, but slow and sparse expression and the large injection volumes required make this approach cumbersome, especially for developmental studies. We developed a novel method for efficient gene delivery across the central nervous system in neonatal mice and rats starting as early as P1 and persisting into adulthood. The method employs transverse sinus injections of 2-4 μL of AAV9 at P0. Here, we describe how to use this method to label and/or genetically manipulate cells in the neonatal rat and mouse brain. The protocol is fast, simple, can be readily adopted by any laboratory, and utilizes the widely available AAV9 capsid. The procedure is adaptable for diverse experimental applications ranging from biochemistry, anatomical and functional mapping, gene expression, silencing, and editing.
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Affiliation(s)
- Ali S Hamodi
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
| | - Aude Martinez Sabino
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
- University of Technology of CompiègneCompiègneFrance
| | | | - Dionysia Moschou
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
| | - Michael C Crair
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
- Department of Ophthalmology and Visual Science, Yale School of MedicineNew HavenUnited States
- Kavli Institute for Neuroscience, Yale School of MedicineNew HavenUnited States
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33
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Saleem AB. Two stream hypothesis of visual processing for navigation in mouse. Curr Opin Neurobiol 2020; 64:70-78. [PMID: 32294570 DOI: 10.1016/j.conb.2020.03.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/17/2020] [Accepted: 03/20/2020] [Indexed: 12/11/2022]
Abstract
Vision research has traditionally been studied in stationary subjects observing stimuli, and rarely during navigation. Recent research using virtual reality environments for mice has revealed that responses even in the primary visual cortex are modulated by spatial context - identical scenes presented in different positions of a room can elicit different responses. Here, we review these results and discuss how information from visual areas can reach navigational areas of the brain. Based on the observation that mouse higher visual areas cover different parts of the visual field, we propose that spatial signals are processed along two-streams based on visual field coverage. Specifically, this hypothesis suggests that landmark related signals are processed by areas biased to the central field, and self-motion related signals are processed by areas biased to the peripheral field.
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Affiliation(s)
- Aman B Saleem
- UCL Institute of Behavioural Neurosciences, Department of Experimental Psychology, University College London, London, WC1H 0AP, UK.
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34
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Deciphering Pyramidal Neuron Diversity: Delineating Perceptual Functions of Projection-Defined Neuronal Types. Neuron 2020; 105:209-211. [PMID: 31972143 DOI: 10.1016/j.neuron.2019.12.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Axonal projection patterns are increasingly recognized as a defining feature for neuronal classification. How could such structural distinctions be linked to functions? In this issue of Neuron, Tang and Higley (2020) disambiguate behavior-level functions of two projection-defined subtypes of cortical projection neurons.
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35
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Tang L, Higley MJ. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior. Neuron 2020; 105:346-354.e5. [PMID: 31757603 PMCID: PMC6981039 DOI: 10.1016/j.neuron.2019.10.014] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 09/03/2019] [Accepted: 10/07/2019] [Indexed: 10/25/2022]
Abstract
Neocortical sensory areas are thought to act as distribution hubs, transmitting information about the external environment to downstream areas. Within primary visual cortex, various populations of pyramidal neurons (PNs) send axonal projections to distinct targets, suggesting multiple cellular networks may be independently engaged during behavior. We investigated whether PN subpopulations differentially support visual detection by training mice on a novel eyeblink conditioning task. Applying 2-photon calcium imaging and optogenetic manipulation of anatomically defined PNs, we show that layer 5 corticopontine neurons strongly encode sensory and motor task information and are selectively necessary for performance. Our findings support a model in which target-specific cortical subnetworks form the basis for adaptive behavior by directing relevant information to distinct brain areas. Overall, this work highlights the potential for neurons to form physically interspersed but functionally segregated networks capable of parallel, independent control of perception and behavior.
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Affiliation(s)
- Lan Tang
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Michael J Higley
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.
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36
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Suzuki T, Morimoto N, Akaike A, Osakada F. Multiplex Neural Circuit Tracing With G-Deleted Rabies Viral Vectors. Front Neural Circuits 2020; 13:77. [PMID: 31998081 PMCID: PMC6967742 DOI: 10.3389/fncir.2019.00077] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 11/14/2019] [Indexed: 12/26/2022] Open
Abstract
Neural circuits interconnect to organize large-scale networks that generate perception, cognition, memory, and behavior. Information in the nervous system is processed both through parallel, independent circuits and through intermixing circuits. Analyzing the interaction between circuits is particularly indispensable for elucidating how the brain functions. Monosynaptic circuit tracing with glycoprotein (G) gene-deleted rabies viral vectors (RVΔG) comprises a powerful approach for studying the structure and function of neural circuits. Pseudotyping of RVΔG with the foreign envelope EnvA permits expression of transgenes such as fluorescent proteins, genetically-encoded sensors, or optogenetic tools in cells expressing TVA, a cognate receptor for EnvA. Trans-complementation with rabies virus glycoproteins (RV-G) enables trans-synaptic labeling of input neurons directly connected to the starter neurons expressing both TVA and RV-G. However, it remains challenging to simultaneously map neuronal connections from multiple cell populations and their interactions between intermixing circuits solely with the EnvA/TVA-mediated RV tracing system in a single animal. To overcome this limitation, here, we multiplexed RVΔG circuit tracing by optimizing distinct viral envelopes (oEnvX) and their corresponding receptors (oTVX). Based on the EnvB/TVB and EnvE/DR46-TVB systems derived from the avian sarcoma leukosis virus (ASLV), we developed optimized TVB receptors with lower or higher affinity (oTVB-L or oTVB-H) and the chimeric envelope oEnvB, as well as an optimized TVE receptor with higher affinity (oTVE-H) and its chimeric envelope oEnvE. We demonstrated independence of RVΔG infection between the oEnvA/oTVA, oEnvB/oTVB, and oEnvE/oTVE systems and in vivo proof-of-concept for multiplex circuit tracing from two distinct classes of layer 5 neurons targeting either other cortical or subcortical areas. We also successfully labeled common input of the lateral geniculate nucleus to both cortico-cortical layer 5 neurons and inhibitory neurons of the mouse V1 with multiplex RVΔG tracing. These oEnvA/oTVA, oEnvB/oTVB, and oEnvE/oTVE systems allow for differential labeling of distinct circuits to uncover the mechanisms underlying parallel processing through independent circuits and integrated processing through interaction between circuits in the brain.
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Affiliation(s)
- Toshiaki Suzuki
- Laboratory of Cellular Pharmacology, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan
| | - Nao Morimoto
- Laboratory of Cellular Pharmacology, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan.,Laboratory of Neural Information Processing, Institute for Advanced Research, Nagoya University, Nagoya, Japan
| | - Akinori Akaike
- Laboratory of Cellular Pharmacology, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan
| | - Fumitaka Osakada
- Laboratory of Cellular Pharmacology, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan.,Laboratory of Neural Information Processing, Institute for Advanced Research, Nagoya University, Nagoya, Japan.,Institute of Nano-Life-Systems, Institutes of Innovation for Future Society, Nagoya University, Nagoya, Japan.,PRESTO/CREST, Japan Science and Technology Agency, Saitama, Japan
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Barson D, Hamodi AS, Shen X, Lur G, Constable RT, Cardin JA, Crair MC, Higley MJ. Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits. Nat Methods 2019; 17:107-113. [PMID: 31686040 PMCID: PMC6946863 DOI: 10.1038/s41592-019-0625-2] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 09/30/2019] [Indexed: 12/20/2022]
Abstract
Spontaneous and sensory-evoked activity propagates across varying spatial scales in the mammalian cortex, but technical challenges have limited conceptual links between the function of local neuronal circuits and brain-wide network dynamics. We present a method for simultaneous cellular-resolution two-photon calcium imaging of a local microcircuit and mesoscopic widefield calcium imaging of the entire cortical mantle in awake mice. Our multi-scale approach employs an orthogonal axis design where the mesoscopic objective is oriented above the brain and the two-photon objective is oriented horizontally, with imaging performed through a microprism. We also introduce a viral method for robust and widespread gene delivery in the mouse brain. These approaches allow us to identify the behavioral state-dependent functional connectivity of pyramidal neurons and vasoactive intestinal peptide (VIP)-expressing interneurons with long-range cortical networks. Our novel imaging system provides a powerful strategy for investigating cortical architecture across a wide range of spatial scales. Further information on research design is available in the Life Sciences Reporting Summary linked to this article.
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Affiliation(s)
- Daniel Barson
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA.,MD/PhD Program, Yale School of Medicine, New Haven, CT, USA
| | - Ali S Hamodi
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Gyorgy Lur
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA.,Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.,Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Jessica A Cardin
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA.
| | - Michael J Higley
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA. .,Program in Cellular Neuroscience, Neurodegeneration and Repair, New Haven, CT, USA.
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38
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Tripp B. Approximating the Architecture of Visual Cortex in a Convolutional Network. Neural Comput 2019; 31:1551-1591. [PMID: 31260392 DOI: 10.1162/neco_a_01211] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Deep convolutional neural networks (CNNs) have certain structural, mechanistic, representational, and functional parallels with primate visual cortex and also many differences. However, perhaps some of the differences can be reconciled. This study develops a cortex-like CNN architecture, via (1) a loss function that quantifies the consistency of a CNN architecture with neural data from tract tracing, cell reconstruction, and electrophysiology studies; (2) a hyperparameter-optimization approach for reducing this loss, and (3) heuristics for organizing units into convolutional-layer grids. The optimized hyperparameters are consistent with neural data. The cortex-like architecture differs from typical CNN architectures. In particular, it has longer skip connections, larger kernels and strides, and qualitatively different connection sparsity. Importantly, layers of the cortex-like network have one-to-one correspondences with cortical neuron populations. This should allow unambiguous comparison of model and brain representations in the future and, consequently, more precise measurement of progress toward more biologically realistic deep networks.
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Affiliation(s)
- Bryan Tripp
- Department of Systems Design Engineering and Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1
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39
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Holst GL, Stoy W, Yang B, Kolb I, Kodandaramaiah SB, Li L, Knoblich U, Zeng H, Haider B, Boyden ES, Forest CR. Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex. J Neurophysiol 2019; 121:2341-2357. [PMID: 30969898 DOI: 10.1152/jn.00738.2018] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.
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Affiliation(s)
- Gregory L Holst
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - William Stoy
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Bo Yang
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Ilya Kolb
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | | | - Lu Li
- Allen Institute for Brain Science , Seattle, Washington
| | - Ulf Knoblich
- Allen Institute for Brain Science , Seattle, Washington
| | - Hongkui Zeng
- Allen Institute for Brain Science , Seattle, Washington
| | - Bilal Haider
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Edward S Boyden
- Media Arts and Sciences, Massachusetts Institute of Technology , Cambridge, Massachusetts.,McGovern Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.,Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
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40
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Kannan M, Vasan G, Pieribone VA. Optimizing Strategies for Developing Genetically Encoded Voltage Indicators. Front Cell Neurosci 2019; 13:53. [PMID: 30863283 PMCID: PMC6399427 DOI: 10.3389/fncel.2019.00053] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 02/04/2019] [Indexed: 01/23/2023] Open
Abstract
Genetically encoded optical indicators of neuronal activity enable unambiguous recordings of input-output activity patterns from identified cells in intact circuits. Among them, genetically encoded voltage indicators (GEVIs) offer additional advantages over calcium indicators as they are direct sensors of membrane potential and can adeptly report subthreshold events and hyperpolarization. Here, we outline the major GEVI designs and give an account of properties that need to be carefully optimized during indicator engineering. While designing the ideal GEVI, one should keep in mind aspects such as membrane localization, signal size, signal-to-noise ratio, kinetics and voltage dependence of optical responses. Using ArcLight and derivatives as prototypes, we delineate how a probe should be optimized for the former properties and developed along other areas in a need-based manner. Finally, we present an overview of the GEVI engineering process and lend an insight into their discovery, delivery and diagnosis.
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Affiliation(s)
- Madhuvanthi Kannan
- The John B. Pierce Laboratory, New Haven, CT, United States.,Department of Cellular and Molecular Physiology, Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Ganesh Vasan
- The John B. Pierce Laboratory, New Haven, CT, United States.,Department of Cellular and Molecular Physiology, Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Vincent A Pieribone
- The John B. Pierce Laboratory, New Haven, CT, United States.,Department of Cellular and Molecular Physiology, Yale School of Medicine, Yale University, New Haven, CT, United States.,Department of Neuroscience, Yale School of Medicine, Yale University, New Haven, CT, United States
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41
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Synaptic mechanisms underlying the intense firing of neocortical layer 5B pyramidal neurons in response to cortico-cortical inputs. Brain Struct Funct 2019; 224:1403-1416. [PMID: 30756190 PMCID: PMC6509071 DOI: 10.1007/s00429-019-01842-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 01/30/2019] [Indexed: 11/23/2022]
Abstract
In the neocortex, large layer 5B pyramidal neurons implement a high-density firing code. In contrast, other subtypes of pyramidal neurons, including those in layer 2/3, are functionally characterized by their sparse firing rate. Here, we investigate the synaptic basis of this behavior by comparing the properties of the postsynaptic responses evoked by cortical inputs in layer 5B and layer 2/3 pyramidal neurons in vitro. We demonstrate that a major determinant of the larger responsiveness of layer 5B with respect to layer 2/3 pyramidal neurons is the different properties in their inhibitory postsynaptic currents (IPSCs): layer 5B pyramidal neurons have IPSCs of lower amplitude and the temporal delay between the excitatory and inhibitory synaptic components is also larger in these cells. Our data also suggest that this difference depends on the lower gain of the cortical response of layer 5 parvalbumin-positive fast-spiking (PV-FS) interneurons with respect to PV-FS cells from layer 2/3. We propose that, while superficial PV-FS interneurons are well suited to provide a powerful feed-forward inhibitory control of pyramidal neuron responses, layer 5 PV-FS interneurons are mainly engaged in a feedback inhibitory loop and only after a substantial recruitment of surrounding pyramidal cells do they respond to an external input.
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42
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Functional imaging of visual cortical layers and subplate in awake mice with optimized three-photon microscopy. Nat Commun 2019; 10:177. [PMID: 30635577 PMCID: PMC6329792 DOI: 10.1038/s41467-018-08179-6] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 12/13/2018] [Indexed: 01/02/2023] Open
Abstract
Two-photon microscopy is used to image neuronal activity, but has severe limitations for studying deeper cortical layers. Here, we developed a custom three-photon microscope optimized to image a vertical column of the cerebral cortex > 1 mm in depth in awake mice with low (<20 mW) average laser power. Our measurements of physiological responses and tissue-damage thresholds define pulse parameters and safety limits for damage-free three-photon imaging. We image functional visual responses of neurons expressing GCaMP6s across all layers of the primary visual cortex (V1) and in the subplate. These recordings reveal diverse visual selectivity in deep layers: layer 5 neurons are more broadly tuned to visual stimuli, whereas mean orientation selectivity of layer 6 neurons is slightly sharper, compared to neurons in other layers. Subplate neurons, located in the white matter below cortical layer 6 and characterized here for the first time, show low visual responsivity and broad orientation selectivity. Two-photon microscopy is a powerful tool for studying neuronal activity but cannot easily image deeper cortical layers. Here, the authors design a custom microscope for three-photon microscopy and use it to reveal response properties of layer 5, 6, and subplate visual cortical neurons.
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43
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Segregated Subnetworks of Intracortical Projection Neurons in Primary Visual Cortex. Neuron 2018; 100:1313-1321.e6. [DOI: 10.1016/j.neuron.2018.10.023] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 08/13/2018] [Accepted: 10/11/2018] [Indexed: 11/23/2022]
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44
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Experience-Dependent Development of Feature-Selective Synchronization in the Primary Visual Cortex. J Neurosci 2018; 38:7852-7869. [PMID: 30064994 DOI: 10.1523/jneurosci.0027-18.2018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 07/24/2018] [Accepted: 07/24/2018] [Indexed: 11/21/2022] Open
Abstract
Early visual experience is essential for the maturation of visual functions in which the primary visual cortex plays crucial roles. The extraction of visual features based on response selectivity of individual neurons, a fundamental process in the cortex, is basically established by eye opening in rodents, suggesting that visual experience is required for the development of neural functions other than feature extraction. Here, we show that synchronized firing, which is important for visual information processing, occurs selectively in adjacent neurons sharing similar orientation or spatial frequency preferences in layers 2-4 (upper layer) of rat visual cortex. This feature-selective spike synchrony was rudimentary when the eyes opened and became prominent during the first few weeks after eye opening only in the presence of pattern vision. In contrast, synchronization in layers 5-6 (lower layer) was almost independent of orientation similarity and more weakly dependent on spatial frequency similarity compared with upper layer synchrony. Lower layer synchronization was strengthened during development after eye opening independently of visual experience as a whole. However, the feature selectivity of synchronization was regulated by visual inputs, whereas the inputs without contours were sufficient for this regulation. Therefore, we speculate that feature-selective synchronization in the upper layer may convey detailed information on visual objects to the higher-order cortex, whereas weakly feature-selective synchronization in the lower layer may covey rather rough visual information to the subcortical areas or higher-order cortex. A major role of visual experience may be to establish the specific neural circuits underlying highly feature-selective synchronization.SIGNIFICANCE STATEMENT The neuronal mechanisms underlying experience-dependent improvement of visual functions still remain unresolved. In this study, we investigated whether early visual experience contributes to the development of synchronized neural firing in the primary visual cortex, which plays important roles in visual information processing. We found that synchronized firing depends more remarkably on the similarity of preferred visual stimuli in the upper than lower layer neurons. Pattern vision during development was required for the establishment of spike synchrony in the upper but not the lower layer. These findings provide a new view regarding the role of sensory experience in the functional development of the cortex and the differences in the modes of information processing in the upper and lower cortical layers.
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45
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Cang J, Savier E, Barchini J, Liu X. Visual Function, Organization, and Development of the Mouse Superior Colliculus. Annu Rev Vis Sci 2018; 4:239-262. [PMID: 29852095 DOI: 10.1146/annurev-vision-091517-034142] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The superior colliculus (SC) is the most prominent visual center in mice. Studies over the past decade have greatly advanced our understanding of the function, organization, and development of the mouse SC, which has rapidly become a popular model in vision research. These studies have described the diverse and cell-type-specific visual response properties in the mouse SC, revealed their laminar and topographic organizations, and linked the mouse SC and downstream pathways with visually guided behaviors. Here, we summarize these findings, compare them with the rich literature of SC studies in other species, and highlight important gaps and exciting future directions. Given its clear importance in mouse vision and the available modern neuroscience tools, the mouse SC holds great promise for understanding the cellular, circuit, and developmental mechanisms that underlie visual processing, sensorimotor transformation, and, ultimately, behavior.
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Affiliation(s)
- Jianhua Cang
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, Virginia 22904, USA;
| | - Elise Savier
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, Virginia 22904, USA;
| | - Jad Barchini
- Department of Functional Architecture and Development of Cerebral Cortex, Max Planck Florida Institute for Neuroscience, Jupiter, Florida 33458, USA
| | - Xiaorong Liu
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, Virginia 22904, USA;
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46
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Specialized Subpopulations of Deep-Layer Pyramidal Neurons in the Neocortex: Bridging Cellular Properties to Functional Consequences. J Neurosci 2018; 38:5441-5455. [PMID: 29798890 DOI: 10.1523/jneurosci.0150-18.2018] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/09/2018] [Accepted: 05/11/2018] [Indexed: 12/25/2022] Open
Abstract
Neocortical pyramidal neurons with somata in layers 5 and 6 are among the most visually striking and enigmatic neurons in the brain. These deep-layer pyramidal neurons (DLPNs) integrate a plethora of cortical and extracortical synaptic inputs along their impressive dendritic arbors. The pattern of cortical output to both local and long-distance targets is sculpted by the unique physiological properties of specific DLPN subpopulations. Here we revisit two broad DLPN subpopulations: those that send their axons within the telencephalon (intratelencephalic neurons) and those that project to additional target areas outside the telencephalon (extratelencephalic neurons). While neuroscientists across many subdisciplines have characterized the intrinsic and synaptic physiological properties of DLPN subpopulations, our increasing ability to selectively target and manipulate these output neuron subtypes advances our understanding of their distinct functional contributions. This Viewpoints article summarizes our current knowledge about DLPNs and highlights recent work elucidating the functional differences between DLPN subpopulations.
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47
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Dowding I, Haufe S. Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics. Front Hum Neurosci 2018; 12:103. [PMID: 29615885 PMCID: PMC5867457 DOI: 10.3389/fnhum.2018.00103] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 03/05/2018] [Indexed: 11/13/2022] Open
Abstract
Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This "naive" approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment.
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Affiliation(s)
- Irene Dowding
- Machine Learning Group, Technische Universität Berlin, Berlin, Germany
| | - Stefan Haufe
- Machine Learning Group, Technische Universität Berlin, Berlin, Germany
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48
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Jaepel J, Hübener M, Bonhoeffer T, Rose T. Lateral geniculate neurons projecting to primary visual cortex show ocular dominance plasticity in adult mice. Nat Neurosci 2017; 20:1708-1714. [PMID: 29184207 DOI: 10.1038/s41593-017-0021-0] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 10/12/2017] [Indexed: 01/11/2023]
Abstract
Experience-dependent plasticity in the mature visual system is widely considered to be cortical. Using chronic two-photon Ca2+ imaging of thalamic afferents in layer 1 of binocular visual cortex, we provide evidence against this tenet: the respective dorsal lateral geniculate nucleus (dLGN) cells showed pronounced ocular dominance (OD) shifts after monocular deprivation in adult mice. Most (86%), but not all, of dLGN cell boutons were monocular during normal visual experience. Following deprivation, initially deprived-eye-dominated boutons reduced or lost their visual responsiveness to that eye and frequently became responsive to the non-deprived eye. This cannot be explained by eye-specific cortical changes propagating to dLGN via cortico-thalamic feedback because the shift in dLGN responses was largely resistant to cortical inactivation using the GABAA receptor agonist muscimol. Our data suggest that OD shifts observed in the binocular visual cortex of adult mice may at least partially reflect plasticity of eye-specific inputs onto dLGN neurons.
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Affiliation(s)
- Juliane Jaepel
- Synapses - Circuits - Plasticity, Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Mark Hübener
- Synapses - Circuits - Plasticity, Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Tobias Bonhoeffer
- Synapses - Circuits - Plasticity, Max Planck Institute of Neurobiology, Martinsried, Germany.
| | - Tobias Rose
- Synapses - Circuits - Plasticity, Max Planck Institute of Neurobiology, Martinsried, Germany.
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49
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Rojas-Piloni G, Guest JM, Egger R, Johnson AS, Sakmann B, Oberlaender M. Relationships between structure, in vivo function and long-range axonal target of cortical pyramidal tract neurons. Nat Commun 2017; 8:870. [PMID: 29021587 PMCID: PMC5636900 DOI: 10.1038/s41467-017-00971-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 08/09/2017] [Indexed: 11/09/2022] Open
Abstract
Pyramidal tract neurons (PTs) represent the major output cell type of the neocortex. To investigate principles of how the results of cortical processing are broadcasted to different downstream targets thus requires experimental approaches, which provide access to the in vivo electrophysiology of PTs, whose subcortical target regions are identified. On the example of rat barrel cortex (vS1), we illustrate that retrograde tracer injections into multiple subcortical structures allow identifying the long-range axonal targets of individual in vivo recorded PTs. Here we report that soma depth and dendritic path lengths within each cortical layer of vS1, as well as spiking patterns during both periods of ongoing activity and during sensory stimulation, reflect the respective subcortical target regions of PTs. We show that these cellular properties result in a structure-function parameter space that allows predicting a PT's subcortical target region, without the need to inject multiple retrograde tracers.The major output cell type of the neocortex - pyramidal tract neurons (PTs) - send axonal projections to various subcortical areas. Here the authors combined in vivo recordings, retrograde tracings, and reconstructions of PTs in rat somatosensory cortex to show that PT structure and activity can predict specific subcortical targets.
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Affiliation(s)
- Gerardo Rojas-Piloni
- Digital Neuroanatomy, Max Planck Florida Institute of Neuroscience, 1 Max-Planck-Way, Jupiter, FL, 33458, USA.,Departamento de Neurobiología del Desarrollo y Neurofisiología, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Boulevard Juriquilla 3001, Campus UNAM-Juriquilla, Querétaro, 76230, Mexico
| | - Jason M Guest
- Digital Neuroanatomy, Max Planck Florida Institute of Neuroscience, 1 Max-Planck-Way, Jupiter, FL, 33458, USA.,Max Planck Group: In Silico Brain Sciences, Center of Advanced European Studies and Research, Ludwig-Erhard-Allee 2, Bonn, 53175, Germany.,Bernstein Group: Computational Neuroanatomy, Max Planck Institute for Biological Cybernetics, Spemannstr. 38-44, Tübingen, 72076, Germany
| | - Robert Egger
- Bernstein Group: Computational Neuroanatomy, Max Planck Institute for Biological Cybernetics, Spemannstr. 38-44, Tübingen, 72076, Germany
| | - Andrew S Johnson
- Digital Neuroanatomy, Max Planck Florida Institute of Neuroscience, 1 Max-Planck-Way, Jupiter, FL, 33458, USA
| | - Bert Sakmann
- Digital Neuroanatomy, Max Planck Florida Institute of Neuroscience, 1 Max-Planck-Way, Jupiter, FL, 33458, USA
| | - Marcel Oberlaender
- Digital Neuroanatomy, Max Planck Florida Institute of Neuroscience, 1 Max-Planck-Way, Jupiter, FL, 33458, USA. .,Max Planck Group: In Silico Brain Sciences, Center of Advanced European Studies and Research, Ludwig-Erhard-Allee 2, Bonn, 53175, Germany. .,Bernstein Group: Computational Neuroanatomy, Max Planck Institute for Biological Cybernetics, Spemannstr. 38-44, Tübingen, 72076, Germany.
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50
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Bale MR, Maravall M. Organization of sensory feature selectivity in the whisker system. Neuroscience 2017; 368:70-80. [PMID: 28918260 PMCID: PMC5798594 DOI: 10.1016/j.neuroscience.2017.09.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Revised: 08/25/2017] [Accepted: 09/05/2017] [Indexed: 12/14/2022]
Abstract
Neurons in the whisker system are selective to spatial and dynamical properties – features – of sensory stimuli. At each stage of the pathway, different neurons encode distinct features, generating a rich population representation. Whisker touch is robustly represented; neurons respond to touch-driven fast fluctuations in forces at the whisker base. Cortical neurons have more complex and context-dependent selectivity than subcortical, e.g., to collective whisker motion. Understanding how these signals are integrated to construct whisker-mediated percepts requires further research.
Our sensory receptors are faced with an onslaught of different environmental inputs. Each sensory event or encounter with an object involves a distinct combination of physical energy sources impinging upon receptors. In the rodent whisker system, each primary afferent neuron located in the trigeminal ganglion innervates and responds to a single whisker and encodes a distinct set of physical stimulus properties – features – corresponding to changes in whisker angle and shape and the consequent forces acting on the whisker follicle. Here we review the nature of the features encoded by successive stages of processing along the whisker pathway. At each stage different neurons respond to distinct features, such that the population as a whole represents diverse properties. Different neuronal types also have distinct feature selectivity. Thus, neurons at the same stage of processing and responding to the same whisker nevertheless play different roles in representing objects contacted by the whisker. This diversity, combined with the precise timing and high reliability of responses, enables populations at each stage to represent a wide range of stimuli. Cortical neurons respond to more complex stimulus properties – such as correlated motion across whiskers – than those at early subcortical stages. Temporal integration along the pathway is comparatively weak: neurons up to barrel cortex (BC) are sensitive mainly to fast (tens of milliseconds) fluctuations in whisker motion. The topographic organization of whisker sensitivity is paralleled by systematic organization of neuronal selectivity to certain other physical features, but selectivity to touch and to dynamic stimulus properties is distributed in “salt-and-pepper” fashion.
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Affiliation(s)
- Michael R Bale
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom
| | - Miguel Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom.
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