Literature DB >> 25698735

Mapping of functionally characterized cell classes onto canonical circuit operations in primate prefrontal cortex.

Salva Ardid1, Martin Vinck2, Daniel Kaping3, Susanna Marquez3, Stefan Everling4, Thilo Womelsdorf5.   

Abstract

Microcircuits are composed of multiple cell classes that likely serve unique circuit operations. But how cell classes map onto circuit functions is largely unknown, particularly for primate prefrontal cortex during actual goal-directed behavior. One difficulty in this quest is to reliably distinguish cell classes in extracellular recordings of action potentials. Here we surmount this issue and report that spike shape and neural firing variability provide reliable markers to segregate seven functional classes of prefrontal cells in macaques engaged in an attention task. We delineate an unbiased clustering protocol that identifies four broad spiking (BS) putative pyramidal cell classes and three narrow spiking (NS) putative inhibitory cell classes dissociated by how sparse, bursty, or regular they fire. We speculate that these functional classes map onto canonical circuit functions. First, two BS classes show sparse, bursty firing, and phase synchronize their spiking to 3-7 Hz (theta) and 12-20 Hz (beta) frequency bands of the local field potential (LFP). These properties make cells flexibly responsive to network activation at varying frequencies. Second, one NS and two BS cell classes show regular firing and higher rate with only marginal synchronization preference. These properties are akin to setting tonically the excitation and inhibition balance. Finally, two NS classes fired irregularly and synchronized to either theta or beta LFP fluctuations, tuning them potentially to frequency-specific subnetworks. These results suggest that a limited set of functional cell classes emerges in macaque prefrontal cortex (PFC) during attentional engagement to not only represent information, but to subserve basic circuit operations.
Copyright © 2015 the authors 0270-6474/15/352975-17$15.00/0.

Keywords:  anterior cingulate cortex; cell types; clustering; nonhuman primates; synchronization; variability

Mesh:

Year:  2015        PMID: 25698735      PMCID: PMC6605590          DOI: 10.1523/JNEUROSCI.2700-14.2015

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  29 in total

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Journal:  J Neurosci       Date:  2018-05-23       Impact factor: 6.167

2.  Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform.

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3.  Theta-gamma coordination between anterior cingulate and prefrontal cortex indexes correct attention shifts.

Authors:  Benjamin Voloh; Taufik A Valiante; Stefan Everling; Thilo Womelsdorf
Journal:  Proc Natl Acad Sci U S A       Date:  2015-06-22       Impact factor: 11.205

4.  Distinct Properties of Layer 3 Pyramidal Neurons from Prefrontal and Parietal Areas of the Monkey Neocortex.

Authors:  Guillermo González-Burgos; Takeaki Miyamae; Yosef Krimer; Yelena Gulchina; Diego E Pafundo; Olga Krimer; Holly Bazmi; Dominique Arion; John F Enwright; Kenneth N Fish; David A Lewis
Journal:  J Neurosci       Date:  2019-07-24       Impact factor: 6.167

5.  Fast spiking interneuron activity in primate striatum tracks learning of attention cues.

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6.  Adaptive spike-artifact removal from local field potentials uncovers prominent beta and gamma band neuronal synchronization.

Authors:  Kianoush Banaie Boroujeni; Paul Tiesinga; Thilo Womelsdorf
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7.  Dynamics of excitatory and inhibitory networks are differentially altered by selective attention.

Authors:  Adam C Snyder; Michael J Morais; Matthew A Smith
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8.  Prefrontal and anterior cingulate cortex neurons encode attentional targets even when they do not apparently bias behavior.

Authors:  Stephanie Westendorff; Daniel Kaping; Stefan Everling; Thilo Womelsdorf
Journal:  J Neurophysiol       Date:  2016-05-18       Impact factor: 2.714

9.  Cell-Type Specific Burst Firing Interacts with Theta and Beta Activity in Prefrontal Cortex During Attention States.

Authors:  B Voloh; T Womelsdorf
Journal:  Cereb Cortex       Date:  2018-12-01       Impact factor: 5.357

10.  A cortical model with multi-layers to study visual attentional modulation of neurons at the synaptic level.

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Journal:  Cogn Neurodyn       Date:  2019-05-23       Impact factor: 5.082

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