Literature DB >> 17418956

Variability in neuronal activity in primate cortex during working memory tasks.

M Shafi1, Y Zhou, J Quintana, C Chow, J Fuster, M Bodner.   

Abstract

Persistent elevated neuronal activity has been identified as the neuronal correlate of working memory. It is generally assumed in the literature and in computational and theoretical models of working memory that memory-cell activity is stable and replicable; however, this assumption may be an artifact of the averaging of data collected across trials, and needs experimental verification. In this study, we introduce a classification scheme to characterize the firing frequency trends of cells recorded from the cortex of monkeys during performance of working memory tasks. We examine the frequency statistics and variability of firing during baseline and memory periods. We also study the behavior of cells on individual trials and across trials, and explore the stability of cellular firing during the memory period. We find that cells from different firing-trend classes possess markedly different statistics. We also find that individual cells show substantial variability in their firing behavior across trials, and that firing frequency also varies markedly over the course of a single trial. Finally, the average frequency distribution is wider, the magnitude of the frequency increases from baseline to memory smaller, and the magnitude of frequency decreases larger than is generally assumed. These results may serve as a guide in the evaluation of current theories of the cortical mechanisms of working memory.

Mesh:

Year:  2007        PMID: 17418956     DOI: 10.1016/j.neuroscience.2006.12.072

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  90 in total

Review 1.  Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory.

Authors:  Joel Zylberberg; Ben W Strowbridge
Journal:  Annu Rev Neurosci       Date:  2017-07-25       Impact factor: 12.449

Review 2.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

3.  Spiking neurons that keep the rhythm.

Authors:  Jean-Philippe Thivierge; Paul Cisek
Journal:  J Comput Neurosci       Date:  2010-10-01       Impact factor: 1.621

4.  Cognitive symptoms facilitatory for diagnoses in neuropsychiatric disorders: executive functions and locus of control.

Authors:  Trevor Archer; Richard M Kostrzewa; Richard J Beninger; Tomas Palomo
Journal:  Neurotox Res       Date:  2008-10       Impact factor: 3.911

5.  Physical principles for scalable neural recording.

Authors:  Adam H Marblestone; Bradley M Zamft; Yael G Maguire; Mikhail G Shapiro; Thaddeus R Cybulski; Joshua I Glaser; Dario Amodei; P Benjamin Stranges; Reza Kalhor; David A Dalrymple; Dongjin Seo; Elad Alon; Michel M Maharbiz; Jose M Carmena; Jan M Rabaey; Edward S Boyden; George M Church; Konrad P Kording
Journal:  Front Comput Neurosci       Date:  2013-10-21       Impact factor: 2.380

Review 6.  The log-dynamic brain: how skewed distributions affect network operations.

Authors:  György Buzsáki; Kenji Mizuseki
Journal:  Nat Rev Neurosci       Date:  2014-02-26       Impact factor: 34.870

7.  Common rules guide comparisons of speed and direction of motion in the dorsolateral prefrontal cortex.

Authors:  Cory R Hussar; Tatiana Pasternak
Journal:  J Neurosci       Date:  2013-01-16       Impact factor: 6.167

Review 8.  Comparing the prefrontal cortex of rats and primates: insights from electrophysiology.

Authors:  Jeremy K Seamans; Christopher C Lapish; Daniel Durstewitz
Journal:  Neurotox Res       Date:  2008-10       Impact factor: 3.911

9.  Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Authors:  Ulises Pereira; Nicolas Brunel
Journal:  Neuron       Date:  2018-06-14       Impact factor: 17.173

Review 10.  Working Memory 2.0.

Authors:  Earl K Miller; Mikael Lundqvist; André M Bastos
Journal:  Neuron       Date:  2018-10-24       Impact factor: 17.173

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