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Nigam S, Pojoga S, Dragoi V. Synergistic Coding of Visual Information in Columnar Networks. Neuron 2019; 104:402-411.e4. [PMID: 31399280 DOI: 10.1016/j.neuron.2019.07.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 05/17/2019] [Accepted: 07/09/2019] [Indexed: 11/23/2022]
Abstract
Incoming stimuli are encoded collectively by populations of cortical neurons, which transmit information by using a neural code thought to be predominantly redundant. Redundant coding is widely believed to reflect a design choice whereby neurons with overlapping receptive fields sample environmental stimuli to convey similar information. Here, we performed multi-electrode laminar recordings in awake monkey V1 to report significant synergistic interactions between nearby neurons within a cortical column. These interactions are clustered non-randomly across cortical layers to form synergy and redundancy hubs. Homogeneous sub-populations comprising synergy hubs decode stimulus information significantly better compared to redundancy hubs or heterogeneous sub-populations. Mechanistically, synergistic interactions emerge from the stimulus dependence of correlated activity between neurons. Our findings suggest a refinement of the prevailing ideas regarding coding schemes in sensory cortex: columnar populations can efficiently encode information due to synergistic interactions even when receptive fields overlap and shared noise between cells is high.
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Senzai Y, Fernandez-Ruiz A, Buzsáki G. Layer-Specific Physiological Features and Interlaminar Interactions in the Primary Visual Cortex of the Mouse. Neuron 2019; 101:500-513.e5. [PMID: 30635232 PMCID: PMC6367010 DOI: 10.1016/j.neuron.2018.12.009] [Citation(s) in RCA: 116] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 11/27/2018] [Accepted: 12/04/2018] [Indexed: 12/01/2022]
Abstract
The relationship between mesoscopic local field potentials (LFPs) and single-neuron firing in the multi-layered neocortex is poorly understood. Simultaneous recordings from all layers in the primary visual cortex (V1) of the behaving mouse revealed functionally defined layers in V1. The depth of maximum spike power and sink-source distributions of LFPs provided consistent laminar landmarks across animals. Coherence of gamma oscillations (30-100 Hz) and spike-LFP coupling identified six physiological layers and further sublayers. Firing rates, burstiness, and other electrophysiological features of neurons displayed unique layer and brain state dependence. Spike transmission strength from layer 2/3 cells to layer 5 pyramidal cells and interneurons was stronger during waking compared with non-REM sleep but stronger during non-REM sleep among deep-layer excitatory neurons. A subset of deep-layer neurons was active exclusively in the DOWN state of non-REM sleep. These results bridge mesoscopic LFPs and single-neuron interactions with laminar structure in V1.
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Affiliation(s)
- Yuta Senzai
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA
| | - Antonio Fernandez-Ruiz
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA
| | - György Buzsáki
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA; Department of Neurology, Langone Medical Center, New York University, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
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Funk CM, Honjoh S, Rodriguez AV, Cirelli C, Tononi G. Local Slow Waves in Superficial Layers of Primary Cortical Areas during REM Sleep. Curr Biol 2016; 26:396-403. [PMID: 26804554 DOI: 10.1016/j.cub.2015.11.062] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 11/15/2015] [Accepted: 11/24/2015] [Indexed: 12/15/2022]
Abstract
Sleep is traditionally constituted of two global behavioral states, non-rapid eye movement (NREM) and rapid eye movement (REM), characterized by quiescence and reduced responsiveness to sensory stimuli [1]. NREM sleep is distinguished by slow waves and spindles throughout the cerebral cortex and REM sleep by an "activated," low-voltage fast electroencephalogram (EEG) paradoxically similar to that of wake, accompanied by rapid eye movements and muscle atonia. However, recent evidence has shown that cortical activity patterns during wake and NREM sleep are not as global as previously thought. Local slow waves can appear in various cortical regions in both awake humans [2] and rodents [3-5]. Intracranial recordings in humans [6] and rodents [4, 7] have shown that NREM sleep slow waves most often involve only a subset of brain regions that varies from wave to wave rather than occurring near synchronously across all cortical areas. Moreover, some cortical areas can transiently "wake up" [8] in an otherwise sleeping brain. Yet until now, cortical activity during REM sleep was thought to be homogenously wake-like. We show here, using local laminar recordings in freely moving mice, that slow waves occur regularly during REM sleep, but only in primary sensory and motor areas and mostly in layer 4, the main target of relay thalamic inputs, and layer 3. This finding may help explain why, during REM sleep, we remain disconnected from the environment even though the bulk of the cortex shows wake-like, paradoxical activation.
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Affiliation(s)
- Chadd M Funk
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, USA; Medical Scientist Training Program, University of Wisconsin-Madison, Health Sciences Learning Center, 750 Highland Avenue, Madison, WI 53705, USA; Neuroscience Training Program, University of Wisconsin-Madison, 9531 WIMR II, 1111 Highland Avenue, Madison, WI 53705, USA
| | - Sakiko Honjoh
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, USA
| | - Alexander V Rodriguez
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, USA; Neuroscience Training Program, University of Wisconsin-Madison, 9531 WIMR II, 1111 Highland Avenue, Madison, WI 53705, USA
| | - Chiara Cirelli
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, USA.
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, USA.
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Harvey MA, Valentiniene S, Roland PE. Cortical Membrane Potential Dynamics and Laminar Firing during Object Motion. Front Syst Neurosci 2009; 3:7. [PMID: 19753323 PMCID: PMC2742661 DOI: 10.3389/neuro.06.007.2009] [Citation(s) in RCA: 14] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2009] [Accepted: 07/24/2009] [Indexed: 11/13/2022] Open
Abstract
When an object is introduced moving in the visual field of view, the object maps with different delays in each of the six cortical layers in many visual areas by mechanisms that are poorly understood. We combined voltage sensitive dye (VSD) recordings with laminar recordings of action potentials in visual areas 17, 18, 19 and 21 in ferrets exposed to stationary and moving bars. At the area 17/18 border a moving bar first elicited an ON response in layer 4 and then ON responses in supragranular and infragranular layers, identical to a stationary bar. Shortly after, the moving bar mapped as moving synchronous peak firing across layers. Complex dynamics evolved including feedback from areas 19/21, the computation of a spatially restricted pre-depolarization (SRP), and firing in the direction of cortical motion prior to the mapping of the bar. After 350 ms, the representations of the bar (peak firing and peak VSD signal) in areas 19/21 and 17/18 moved over the cortex in phase. The dynamics comprise putative mechanisms for automatic saliency of novel moving objects, coherent mapping of moving objects across layers and areas, and planning of catch-up saccades.
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Affiliation(s)
- Michael A Harvey
- Brain Research, Department of Neuroscience, Karolinska Institute Stockholm, Sweden
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