Distinct functional and structural neural underpinnings of working memory

ABSTRACT Working memory (WM), the short‐term abstraction and manipulation of information, is an essential neurocognitive process in daily functioning. Few studies have concurrently examined the functional and structural neural correlates of WM and the current study did so to characterize both overlapping and unique associations. Participants were a large sample of adults from the Human Connectome Project (N=1064; 54% female) who completed an in‐scanner visual N‐back WM task. The results indicate a clear dissociation between BOLD activation during the WM task and brain structure in relation to performance. In particular, while activation in the middle frontal gyrus was positively associated with WM performance, cortical thickness in this region was inversely associated with performance. Additional unique associations with WM were BOLD activation in superior parietal lobule, cingulate, and fusiform gyrus and gray matter volume in the orbitofrontal cortex and cuneus. Across findings, substantially larger effects were observed for functional associations relative to structural associations. These results provide further evidence implicating frontoparietal subunits of the brain in WM. Moreover, these findings reveal the distinct, and in some cases opposing, roles of brain structure and neural activation in WM, highlighting the lack of homology between structure and function in relation to cognition. HIGHLIGHTSInvestigation of the functional and structural neural correlates of working memory.Measured by a visual N‐Back task in a large adult sample (N=1064).Larger associations for BOLD signal relative to morphometry.Lack of homology between structure and function in relation to cognition.Dissociation especially notable for middle frontal gyrus.

[1]  Stephen M Rao,et al.  Cognitive dysfunction in multiple sclerosis: a review of recent developments. , 2003, Current opinion in neurology.

[2]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[3]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[4]  Kathryn M. McMillan,et al.  N‐back working memory paradigm: A meta‐analysis of normative functional neuroimaging studies , 2005, Human brain mapping.

[5]  Adam J. Woods,et al.  Frontal Structural Neural Correlates of Working Memory Performance in Older Adults , 2017, Front. Aging Neurosci..

[6]  Stefan Gazdzinski,et al.  Cortical thickness, surface area, and volume of the brain reward system in alcohol dependence: relationships to relapse and extended abstinence. , 2011, Alcoholism, clinical and experimental research.

[7]  Ronald A. Cohen,et al.  Imaging phonological similarity effects on verbal working memory , 2008, Neuropsychologia.

[8]  Andrew R. A. Conway,et al.  Variation in working memory , 2008 .

[9]  R. Buckner,et al.  Functional-Anatomic Fractionation of the Brain's Default Network , 2010, Neuron.

[10]  D. Bowers,et al.  Is the n-back task a valid neuropsychological measure for assessing working memory? , 2009, Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists.

[11]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[12]  J. Binder,et al.  A Parametric Manipulation of Factors Affecting Task-induced Deactivation in Functional Neuroimaging , 2003, Journal of Cognitive Neuroscience.

[13]  Edward E. Smith,et al.  Working Memory: A View from Neuroimaging , 1997, Cognitive Psychology.

[14]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

[15]  Kimberly L. Ray,et al.  Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions , 2012, Cognitive, affective & behavioral neuroscience.

[16]  E. Tanabe,et al.  65-152 Working memory dysfunction in schizophrenia , 1997, Biological Psychiatry.

[17]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[18]  Antonio Fernández-Bouzas,et al.  Reduced right frontal cortical thickness in children, adolescents and adults with ADHD and its correlation to clinical variables: a cross-sectional study. , 2010, Journal of psychiatric research.

[19]  Paul F. Hill,et al.  Remember the Future: Working Memory Training Decreases Delay Discounting Among Stimulant Addicts , 2011, Biological Psychiatry.

[20]  T. Vangberg,et al.  How Does the Accuracy of Intracranial Volume Measurements Affect Normalized Brain Volumes? Sample Size Estimates Based on 966 Subjects from the HUNT MRI Cohort , 2015, American Journal of Neuroradiology.

[21]  S. Hogg-Johnson,et al.  A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. , 2005, Journal of the American Academy of Child and Adolescent Psychiatry.

[22]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[23]  D. Hommer,et al.  Delay Discounting Correlates with Proportional Lateral Frontal Cortex Volumes , 2009, Biological Psychiatry.

[24]  Thomas S. Redick,et al.  Complex span and n-back measures of working memory: A meta-analysis , 2013, Psychonomic bulletin & review.

[25]  S. Tapert,et al.  BOLD response to working memory not related to cortical thickness during early adolescence , 2013, Brain Research.

[26]  Roberto Cabeza,et al.  Aging Gracefully: Compensatory Brain Activity in High-Performing Older Adults , 2002, NeuroImage.

[27]  Hidenao Fukuyama,et al.  The neural basis of executive function in working memory: an fMRI study based on individual differences , 2004, NeuroImage.

[28]  E. Miller,et al.  The prefontral cortex and cognitive control , 2000, Nature Reviews Neuroscience.

[29]  A. Meyer-Lindenberg,et al.  Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume? , 2012, Neurobiology of Aging.

[30]  R. Gur,et al.  Working memory deficit as a core neuropsychological dysfunction in schizophrenia. , 2003, The American journal of psychiatry.

[31]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[32]  J. A. Pruszynski,et al.  Neural correlates , 2023 .

[33]  Nash Unsworth,et al.  Exploring the Relations Among Executive Functions, Fluid Intelligence, and Personality , 2009 .

[34]  Abraham Z. Snyder,et al.  Human Connectome Project informatics: Quality control, database services, and data visualization , 2013, NeuroImage.

[35]  F. Q. Ribeiro.  The meta-analysis , 2017, Brazilian journal of otorhinolaryngology.

[36]  Ayse Pinar Saygin,et al.  Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data , 2006, NeuroImage.

[37]  L. Nyberg,et al.  Neural correlates of variable working memory load across adult age and skill: dissociative patterns within the fronto-parietal network. , 2009, Scandinavian journal of psychology.

[38]  Murat Yücel,et al.  Brain development during adolescence: A mixed‐longitudinal investigation of cortical thickness, surface area, and volume , 2016, Human brain mapping.

[39]  T. Klingberg,et al.  Increased prefrontal and parietal activity after training of working memory , 2004, Nature Neuroscience.

[40]  Stephen M. Rao,et al.  Cognitive dysfunction in multiple sclerosis: a review of recent developments. , 2003, Current opinion in neurology.

[41]  Edward E. Smith,et al.  Neuroimaging studies of working memory: , 2003, Cognitive, affective & behavioral neuroscience.

[42]  E. Miller,et al.  THE PREFRONTAL CORTEX AND COGNITIVE CONTROL , 2000 .

[43]  R. Hari,et al.  Coinciding early activation of the human primary visual cortex and anteromedial cuneus , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[44]  Andrew R. A. Conway,et al.  Journal of Experimental Psychology : General Neural Mechanisms of Interference Control Underlie the Relationship Between Fluid Intelligence and Working Memory Span , 2011 .

[45]  D. Salat,et al.  Greater orbital prefrontal volume selectively predicts worse working memory performance in older adults. , 2002, Cerebral cortex.

[46]  B. Price,et al.  Memory dysfunction. , 2005, The New England journal of medicine.

[47]  Jason M. Chein,et al.  Domain-general mechanisms of complex working memory span , 2011, NeuroImage.

[48]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[49]  Todd Lencz,et al.  Volume Reduction in Prefrontal Gray Matter in Unsuccessful Criminal Psychopaths , 2005, Biological Psychiatry.

[50]  S. Jaeggi,et al.  The concurrent validity of the N-back task as a working memory measure , 2010, Memory.

[51]  S. Frangou,et al.  Structural brain correlates of response inhibition in Bipolar Disorder I , 2008, Journal of psychopharmacology.

[52]  A. Raine,et al.  Reduced prefrontal gray matter volume and reduced autonomic activity in antisocial personality disorder. , 2000, Archives of general psychiatry.

[53]  Jeffrey M. Spielberg,et al.  A Longitudinal Study: Changes in Cortical Thickness and Surface Area during Pubertal Maturation , 2015, PloS one.

[54]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[55]  Andrew R. A. Conway,et al.  Working memory, attention control, and the N-back task: a question of construct validity. , 2007, Journal of experimental psychology. Learning, memory, and cognition.

[56]  Stephen M. Rao,et al.  Memory Dysfunction in Multiple Sclerosis: Its Relation to Working Memory, Semantic Encoding, and Implicit Learning. , 1993 .

[57]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[58]  T. Salthouse,et al.  Decomposing adult age differences in working memory. , 1991 .

[59]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[60]  Yasuyuki Taki,et al.  Working Memory Training Using Mental Calculation Impacts Regional Gray Matter of the Frontal and Parietal Regions , 2011, PloS one.

[61]  Klaus Oberauer,et al.  Individual differences in working memory capacity and reasoning ability , 2007 .

[62]  Robert J. Ogg,et al.  Clinical utility of the N-back task in functional neuroimaging studies of working memory , 2014, Journal of clinical and experimental neuropsychology.

[63]  Christopher L. Asplund,et al.  Functional Specialization and Flexibility in Human Association Cortex. , 2016, Cerebral cortex.