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Crandall SR, Patrick SL, Cruikshank SJ, Connors BW. Infrabarrels Are Layer 6 Circuit Modules in the Barrel Cortex that Link Long-Range Inputs and Outputs. Cell Rep 2018; 21:3065-3078. [PMID: 29241536 DOI: 10.1016/j.celrep.2017.11.049] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Revised: 10/11/2017] [Accepted: 11/14/2017] [Indexed: 10/18/2022] Open
Abstract
The rodent somatosensory cortex includes well-defined examples of cortical columns-the barrel columns-that extend throughout the cortical depth and are defined by discrete clusters of neurons in layer 4 (L4) called barrels. Using the cell-type-specific Ntsr1-Cre mouse line, we found that L6 contains infrabarrels, readily identifiable units that align with the L4 barrels. Corticothalamic (CT) neurons and their local axons cluster within the infrabarrels, whereas corticocortical (CC) neurons are densest between infrabarrels. Optogenetic experiments showed that CC cells received robust input from somatosensory thalamic nuclei, whereas CT cells received much weaker thalamic inputs. We also found that CT neurons are intrinsically less excitable, revealing that both synaptic and intrinsic mechanisms contribute to the low firing rates of CT neurons often reported in vivo. In summary, infrabarrels are discrete cortical circuit modules containing two partially separated excitatory networks that link long-distance thalamic inputs with specific outputs.
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Affiliation(s)
- Shane R Crandall
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, RI 02912, USA.
| | - Saundra L Patrick
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, RI 02912, USA
| | - Scott J Cruikshank
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, RI 02912, USA
| | - Barry W Connors
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, RI 02912, USA
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Chanauria N, Bharmauria V, Bachatene L, Cattan S, Rouat J, Molotchnikoff S. Comparative effects of adaptation on layers II-III and V-VI neurons in cat V1. Eur J Neurosci 2016; 44:3094-3104. [PMID: 27740707 DOI: 10.1111/ejn.13439] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 10/04/2016] [Accepted: 10/06/2016] [Indexed: 12/23/2022]
Abstract
V1 is fundamentally grouped into columns that descend from layers II-III to V-VI. Neurons inherent to visual cortex are capable of adapting to changes in the incoming stimuli that drive the cortical plasticity. A principle feature called orientation selectivity can be altered by the presentation of non-optimal stimulus called 'adapter'. When triggered, LGN cells impinge upon layer IV and further relay the information to deeper layers via layers II-III. Using different adaptation protocols, neuronal plasticity can be investigated. Superficial neurons in area V1 are well acknowledged to exhibit attraction and repulsion by shifting their tuning peaks when challenged by a non-optimal stimulus called 'adapter'. Layers V-VI neurons in spite of partnering layers II-III neurons in cortical computation have not been explored simultaneously toward adaptation. We believe that adaptation not only affects cells specific to a layer but modifies the entire column. In this study, through simultaneous multiunit recordings in anesthetized cats using a multichannel depth electrode, we show for the first time how layers V-VI neurons (1000-1200 μm) along with layers II-III neurons (300-500 μm) exhibit plasticity in response to adaptation. Our results demonstrate that superficial and deeper layer neurons react synonymously toward adapter by exhibiting similar behavioral properties. The neurons displayed similar amplitude of shift and maintained equivalent sharpness of Gaussian tuning peaks before and the following adaptation. It appears that a similar mechanism, belonging to all layers, is responsible for the analog outcome of the neurons' experience with adapter.
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Affiliation(s)
- Nayan Chanauria
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
| | - Vishal Bharmauria
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,The Visuomotor Neuroscience Lab, Centre for Vision Research, Faculty of Health, York University, Toronto, ON, Canada
| | - Lyes Bachatene
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Sciences (CHUS), SNAIL
- Sherbrooke Neuro Analysis and Imaging Lab, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Sarah Cattan
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
| | - Jean Rouat
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,Département de Génie Électrique et Génie Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Stéphane Molotchnikoff
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
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