Literature DB >> 34903668

Theta activity paradoxically boosts gamma and ripple frequency sensitivity in prefrontal interneurons.

Ricardo Martins Merino1,2,3,4,5, Carolina Leon-Pinzon1,2,3,5, Walter Stühmer3,5, Martin Möck6, Jochen F Staiger6, Fred Wolf1,2,3,5,7,8, Andreas Neef9,2,3,5,7,8.   

Abstract

Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background input's statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons' sensitivity to gamma and ripple frequencies. We developed a time-resolved dynamic gain analysis and revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms, and to contribute substantially to theta-gamma cross-frequency coupling.

Entities:  

Keywords:  cross-frequency coupling; dynamic gain; information encoding; interneuron

Mesh:

Year:  2021        PMID: 34903668      PMCID: PMC8713793          DOI: 10.1073/pnas.2114549118

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   12.779


  28 in total

1.  Fast global oscillations in networks of integrate-and-fire neurons with low firing rates.

Authors:  N Brunel; V Hakim
Journal:  Neural Comput       Date:  1999-10-01       Impact factor: 2.026

2.  Distinct frequency preferences of different types of rat hippocampal neurones in response to oscillatory input currents.

Authors:  F G Pike; R S Goddard; J M Suckling; P Ganter; N Kasthuri; O Paulsen
Journal:  J Physiol       Date:  2000-11-15       Impact factor: 5.182

3.  The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro.

Authors:  Harold Köndgen; Caroline Geisler; Stefano Fusi; Xiao-Jing Wang; Hans-Rudolf Lüscher; Michele Giugliano
Journal:  Cereb Cortex       Date:  2008-02-09       Impact factor: 5.357

Review 4.  Inhibitory interneurons and their circuit motifs in the many layers of the barrel cortex.

Authors:  Dirk Feldmeyer; Guanxiao Qi; Vishalini Emmenegger; Jochen F Staiger
Journal:  Neuroscience       Date:  2017-05-18       Impact factor: 3.590

5.  Synchronized activity between the ventral hippocampus and the medial prefrontal cortex during anxiety.

Authors:  Avishek Adhikari; Mihir A Topiwala; Joshua A Gordon
Journal:  Neuron       Date:  2010-01-28       Impact factor: 17.173

Review 6.  The θ-γ neural code.

Authors:  John E Lisman; Ole Jensen
Journal:  Neuron       Date:  2013-03-20       Impact factor: 17.173

Review 7.  Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations.

Authors:  Thomas Klausberger; Peter Somogyi
Journal:  Science       Date:  2008-07-04       Impact factor: 47.728

8.  Cortical gamma band synchronization through somatostatin interneurons.

Authors:  Julia Veit; Richard Hakim; Monika P Jadi; Terrence J Sejnowski; Hillel Adesnik
Journal:  Nat Neurosci       Date:  2017-05-08       Impact factor: 24.884

Review 9.  The Cortical States of Wakefulness.

Authors:  James F A Poulet; Sylvain Crochet
Journal:  Front Syst Neurosci       Date:  2019-01-08

Review 10.  Neurosystems: brain rhythms and cognitive processing.

Authors:  Jonathan Cannon; Michelle M McCarthy; Shane Lee; Jung Lee; Christoph Börgers; Miles A Whittington; Nancy Kopell
Journal:  Eur J Neurosci       Date:  2013-12-13       Impact factor: 3.386

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