Interneuron cell types are fit to function

Kepecs, Ádám; Fishell, Gord

doi:10.1038/nature12983

Cited by 999 publications

(1,006 citation statements)

References 125 publications

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“…We argue that STSP may have evolved of necessity to enable more complex computations in local circuits. The existence of STSP is furthermore expected, since the nodes of biological neuronal networks are made up of dozens of different cell types [70][71][72]. Presumably, these different cell types need to be governed by distinct synaptic plasticity learning rules, because activity patterns and excitabilities vary tremendously with cell type.…”

Section: Discussionmentioning

confidence: 99%

“…Although a natural next step in computer modeling might seem to require incorporating considerably more detail, our review highlights just how much detail there is. For every cell type -and there is a lot of them [70][71][72] -there is a corresponding multiplicity of STSP learning rules and short-term dynamics. Yet, to understand the brain and synaptic diseases such as autism, anxiety, or epilepsy [81], it appears that we have no choice but to grapple with STSP.…”

Section: Discussionmentioning

confidence: 99%

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Synapse-type-specific plasticity in local circuits

Larsen

Sjöström

2015

Current Opinion in Neurobiology

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Neuroscientists spent decades debating whether synaptic plasticity was presynaptically or postsynaptically expressed. It was eventually concluded that plasticity depends on many factors, including cell type. More recently, it has become increasingly clear that plasticity is regulated at an even finer grained level; it is specific to the synapse type, a concept we denote synapse-typespecific plasticity (STSP). Here, we review recent developments in the field of STSP, discussing both long-term and short-term variants and with particular emphasis on neocortical function. As there are dozens of neocortical cell types, there is a multiplicity of forms of STSP, the vast majority of which have never been explored. We argue that to understand the brain and synaptic diseases, we have to grapple with STSP.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Synapse-type-specific plasticity in local circuits

Larsen

Sjöström

2015

Current Opinion in Neurobiology

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“…Taken together, one plausible scenario consistent with currently available evidence is that disinhibition induced by ketamine results from a reduction of NMDAR dependent excitation of dendrite-targeting interneurons. This prediction can be tested using cell-type specific genetic tools (Kepecs andFishell 2014, Higley 2014) in future animal experiments.…”

Section: Biophysically-based Neural Circuit Modeling: Understanding Amentioning

confidence: 99%

Computational Psychiatry

2016

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Psychiatric disorders such as autism and schizophrenia arise from abnormalities in brain systems that underlie cognitive, emotional and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically-realistic modeling bridging cellular and synaptic mechanisms with behavior, model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field. © 2014 Elsevier Inc. All rights reserved. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Neither Dr. Wang nor Dr. Krystal has any financial interests relevant to the advancement of computational psychiatry. to and engage with psychiatric research. Second, it will be important to develop a cadre of young psychiatrists who learn computational modeling, lest computational psychiatry.

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“…In contrast, small amplitude and slower AMPA-mediated currents at feedback synapses facilitate integration of convergent inputs onto pyramidal neurons. The motif of feedforward inhibition not only balances excitation but influences circuit gain and dynamics (Kepecs and Fishell 2014). We can only speculate what effects diverse feedforward inhibition might have on the processing of visual signals in feedforward and feedback circuits.…”

Section: Synaptic Organization Of Feedforward and Feedback Connectionsmentioning

confidence: 99%

The Network for Intracortical Communication in Mouse Visual Cortex

Burkhalter¹

2016

Micro-, Meso- And Macro-Connectomics of the Brain

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New techniques for identifying cell types, tracing their synaptic partners, imaging and manipulating their activity in behaving organisms have made mice a widely used model for linking brain circuits to behavior. Most behaviors are tied to vision: identifying objects, guiding movements of body parts, navigating through the environment, and even social interactions. Reason enough to focus on the mouse visual cortex. To find our way around in the occipital cortex, we needed a map. We took a classic approach and traced in the same animal the outputs from multiple retinotopic sites of primary visual cortex (V1) and compared the relative location of projections in the extrastriate cortex. We found nine extrastriate maps and showed by single unit recordings that each of the connectional maps contained visually responsive neurons whose receptive fields were mapped in orderly fashion and completely covered the visual field. Remarkably, a tiny region of one sixth of a dime contained a two-to three-times larger number of areas than the highly developed somatosensory and auditory cortices. By tracing the connections, we found that each of the ten visual areas projected to 25-35 cortical targets and interconnected virtually all of the areas reciprocally with one another. Although the binary graph density of the connection matrix was nearly complete, the connection strengths between areas within the ventral and dorsal cortex differed, indicating that the information from V1 flowed into distinct but interconnected streams. Unit recordings and calcium imaging studies showed that the ventral and dorsal streams processed different spatiotemporal information, which aligned with known properties of streams in primates. Analyses of the laminar patterns of interareal projections showed that areas were organized at multiple levels, suggesting that each stream represented a processing hierarchy.

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Interneuron cell types are fit to function

Cited by 999 publications

References 125 publications

Synapse-type-specific plasticity in local circuits

Synapse-type-specific plasticity in local circuits

Computational Psychiatry

The Network for Intracortical Communication in Mouse Visual Cortex

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