Literature DB >> 16806546

Individual variability in brain activations associated with episodic retrieval: a role for large-scale databases.

Michael B Miller1, John Darrell Van Horn.   

Abstract

The localization of brain functions using neuroimaging techniques is commonly dependent on statistical analyses of groups of subjects in order to identify sites of activation, particularly in studies of episodic memory. Exclusive reliance on group analysis may be to the detriment of understanding the true underlying cognitive nature of brain activations. In this overview, we found that the patterns of brain activity associated with episodic retrieval are very distinct for individual subjects from the patterns of brain activity at the group level. These differences appear to go beyond the relatively small variations due to cyctoarchitectonic differences or spatial normalization. We review evidence that individual patterns of brain activity vary widely across subjects and are reliable over time despite extensive variability. We suggest that varied but reliable individual patterns of significant brain activity may be indicative of different cognitive strategies used to produce a recognition response. We argue that individual analyses in conjunction with group analyses are likely to be critical in fully understanding the relationship between retrieval processes and underlying neural systems.

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Year:  2006        PMID: 16806546     DOI: 10.1016/j.ijpsycho.2006.03.019

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  15 in total

1.  Group analysis and the subject factor in functional magnetic resonance imaging: analysis of fifty right-handed healthy subjects in a semantic language task.

Authors:  Mohamed L Seghier; François Lazeyras; Alan J Pegna; Jean-Marie Annoni; Asaid Khateb
Journal:  Hum Brain Mapp       Date:  2008-04       Impact factor: 5.038

2.  Individual Variability in Brain Activity: A Nuisance or an Opportunity?

Authors:  John Darrell Van Horn; Scott T Grafton; Michael B Miller
Journal:  Brain Imaging Behav       Date:  2008-12-01       Impact factor: 3.978

Review 3.  Building a Science of Individual Differences from fMRI.

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Journal:  Trends Cogn Sci       Date:  2016-04-30       Impact factor: 20.229

4.  Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm.

Authors:  Swathi P Iyer; Izhak Shafran; David Grayson; Kathleen Gates; Joel T Nigg; Damien A Fair
Journal:  Neuroimage       Date:  2013-03-07       Impact factor: 6.556

5.  Intracranial markers of conscious face perception in humans.

Authors:  Fabiano Baroni; Jochem van Kempen; Hiroto Kawasaki; Christopher K Kovach; Hiroyuki Oya; Matthew A Howard; Ralph Adolphs; Naotsugu Tsuchiya
Journal:  Neuroimage       Date:  2017-09-04       Impact factor: 6.556

6.  Unique and persistent individual patterns of brain activity across different memory retrieval tasks.

Authors:  Michael B Miller; Christa-Lynn Donovan; John D Van Horn; Elaine German; Peter Sokol-Hessner; George L Wolford
Journal:  Neuroimage       Date:  2009-06-21       Impact factor: 6.556

7.  Lateralization is predicted by reduced coupling from the left to right prefrontal cortex during semantic decisions on written words.

Authors:  Mohamed L Seghier; Goulven Josse; Alexander P Leff; Cathy J Price
Journal:  Cereb Cortex       Date:  2010-11-25       Impact factor: 5.357

8.  Effect of age on variability in the production of text-based global inferences.

Authors:  Lynne J Williams; Joseph P Dunlop; Hervé Abdi
Journal:  PLoS One       Date:  2012-05-08       Impact factor: 3.240

9.  Inter-subject variability in the use of two different neuronal networks for reading aloud familiar words.

Authors:  M L Seghier; H L Lee; T Schofield; C L Ellis; C J Price
Journal:  Neuroimage       Date:  2008-05-28       Impact factor: 6.556

10.  Dissociating functional brain networks by decoding the between-subject variability.

Authors:  Mohamed L Seghier; Cathy J Price
Journal:  Neuroimage       Date:  2008-12-25       Impact factor: 6.556

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