Literature DB >> 33454832

Individual versus task differences in slow potential generators.

Luis F H Basile1,2, João R Sato3, Henrique A Pasquini4, Bruna Velasques5, Pedro Ribeiro5, Renato Anghinah6.   

Abstract

Average slow potentials (SPs) can be computed from any voluntary task, minimally involving attention to anticipated stimuli. Their topography when recorded by large electrode arrays even during simple tasks is complex, multifocal, and its generators appear to be equally multifocal and highly variable across subjects. Various sources of noise of course contaminate such averages and must contribute to the topographic complexity. Here, we report a study in which the non-averaged SP band (0 to 1 Hz) was analyzed by independent components (ICA), from 256 channel recordings of 18 subjects, during four task conditions (resting, visual attention, CPT, and Stroop). We intended to verify whether the replicable SP generators (between two separate day sessions) modeled as current density reconstruction on structural MRI sets were individual-specific, and if putative task-related differences were systematic across subjects. Typically, 3 ICA components (out of 10) explained SPs in each task and subject, and their combined generators were highly variable across subjects: although some occipito-temporal and medial temporal areas contained generators in most subjects; the overall patterns were obviously variable, with no single area common to all 18 subjects. Linear regression modeling to compare combined generators (from all ICA components) between tasks and sessions showed significantly higher correlations between the four tasks than between sessions for each task. Moreover, it was clear that no common task-specific areas could be seen across subjects. Those results represent one more instance in which individual case analyses favor the hypothesis of individual-specific patterns of cortical activity, regardless of task conditions. We discuss this hypothesis with respect to results from the beta band, from individual-case fMRI studies, and its corroboration by functional neurosurgery and the neuropsychology of focal lesions.

Entities:  

Keywords:  Cortical physiology; Current density reconstruction; Individual variability; Slow potentials

Year:  2021        PMID: 33454832     DOI: 10.1007/s10072-021-05062-z

Source DB:  PubMed          Journal:  Neurol Sci        ISSN: 1590-1874            Impact factor:   3.307


  13 in total

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2.  Neurophysiological signature of effective anticipatory task-set control: a task-switching investigation.

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Review 3.  A two-level model of interindividual anatomo-functional variability of the brain and its implications for neurosurgery.

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Journal:  Cortex       Date:  2016-01-29       Impact factor: 4.027

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Authors:  Luis F H Basile; João R Sato; Henrique A Pasquini; Bruna Velasques; Pedro Ribeiro; Renato Anghinah
Journal:  Brain Struct Funct       Date:  2017-11-28       Impact factor: 3.270

5.  Reliability of functional MR imaging with word-generation tasks for mapping Broca's area.

Authors:  J H Brannen; B Badie; C H Moritz; M Quigley; M E Meyerand; V M Haughton
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Journal:  Neuroimage       Date:  2013-05-16       Impact factor: 6.556

7.  What is common to brain activity evoked by the perception of visual and auditory filled durations? A study with MEG and EEG co-recordings.

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Journal:  Brain Res Cogn Brain Res       Date:  2004-10

8.  Widespread Brain Areas Engaged during a Classical Auditory Streaming Task Revealed by Intracranial EEG.

Authors:  Andrew R Dykstra; Eric Halgren; Thomas Thesen; Chad E Carlson; Werner Doyle; Joseph R Madsen; Emad N Eskandar; Sydney S Cash
Journal:  Front Hum Neurosci       Date:  2011-08-03       Impact factor: 3.169

9.  Individual topographic variability is inherent to cortical physiology but task-related differences may be noise.

Authors:  Luis F H Basile; João R Sato; Henrique A Pasquini; Mirna D Lozano; Mariana P Nucci; Bruna Velasques; Pedro Ribeiro; Renato T Ramos; Renato Anghinah; Renato Anghina
Journal:  PLoS One       Date:  2015-05-26       Impact factor: 3.240

10.  Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

Authors:  Emily S Finn; Xilin Shen; Dustin Scheinost; Monica D Rosenberg; Jessica Huang; Marvin M Chun; Xenophon Papademetris; R Todd Constable
Journal:  Nat Neurosci       Date:  2015-10-12       Impact factor: 24.884

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