Inhibition of Inhibition in Visual Cortex: The Logic of Connections Between Molecularly Distinct Interneurons

By C. Pfeffer, Mingshan Xue, Miao He, Z. J. Huang, Massimo Scanziani. Nature Neuroscience, 2013

1,355 citations recorded by the source corpus.

Cortical inhibitory neurons contact each other to form a network of inhibitory synaptic connections. Our knowledge of the connectivity pattern underlying this inhibitory network is, however, still incomplete. Here we describe a simple and complementary interaction scheme between three large, molecularly distinct interneuron populations in mouse visual cortex: parvalbumin-expressing interneurons strongly inhibit one another but provide little inhibition to other populations. In contrast, somatostatin-expressing interneurons avoid inhibiting one another yet strongly inhibit all other populations. Finally, vasoactive intestinal peptide–expressing interneurons preferentially inhibit somatostatin-expressing interneurons. This scheme occurs in supragranular and infragranular layers, suggesting that inhibitory networks operate similarly at the input and output of the visual cortex. Thus, as the specificity of connections between excitatory neurons forms the basis for the cortical canonical circuit, the scheme described here outlines a standard connectivity pattern among cortical inhibitory neurons.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/ac65837a4eda310de7be68c25c2a2bfe1b79da54

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Citations in the corpus

Adult Mouse Cortical Cell Taxonomy by Single Cell Transcriptomics (2016, positive): “As previously reported 25, 78 , we find that Sst-IRES-Cre does express in a small number of cells that we classify into a Pvalb type (Fig.”
Towards deep learning with segregated dendrites (2016, background): “Furthermore, distal dendrite targeting neurons can themselves can be rapidly inhibited in response to temporally precise neuromodulatory inputs (Pi et al., 2013; Pfeffer et al., 2013; Karnani et al., 2016; Hangya et al., 2015; Brombas et al., 2014).”
Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework (2016, background): “…of excitatory and inhibitory neuronal morphology and physiology, their layer and type-specific distribution and connectivity [49, 50], and domain-specific (e.g., dendritic versus somatic) targeting of excitatory pyramidal cells by interneurons [23, 25, 27, 51] in the brain are taken into account.”
Gamma-band synchronization in the neocortex: novel analysis methods and their application to sensory and motivational systems (2013, background): “However, the SOM+ cells do not possess these mutual inhibitory connections, and do not receive a strong projection from the FS PV+ basket cells (Pfeffer et al., 2013).”
Principles of connectivity among morphologically defined cell types in adult neocortex (2015, neutral): “In contrast to what has been reported in optogenetic studies [SOM neurons avoid each other (28)], there is a high connectivity between SOM MCs and SOM non-MCs.”
Neural Elements for Predictive Coding (2016, background): “Neurochemical and genetic (transcriptomic) criteria identify three cardinal families of interneurons – GABAergic inhibitory cells – defined by the mutually exclusive expression of three markers, namely parvalbumin (PV – a calcium binding protein), somatostatin (SST – a peptide co-transmitter), or 5H”
Plasticity during Sleep Is Linked to Specific Regulation of Cortical Circuit Activity (2017, background): “At the circuit level, mutual inhibition between PV+ and SOM+ cells might help balance the cell’s excitability along its somatodendritic axis (Pfeffer et al., 2013; Wolff et al., 2014), and at the network level global downscaling during REM sleep following SWS might be considered to also counter…”