Effects of working memory training on functional connectivity and cerebral blood flow during rest

Working memory (WM) training (WMT) alters the task-related brain activity and structure of the external attention system (EAS). We investigated whether WMT also alters resting-state brain mechanisms, which are assumed to reflect intrinsic brain activity and connectivity. Our study subjects were subjected to a 4-week WMT program and brain scans before and after the intervention for determining changes of functional connectivity and regional cerebral blood flow during rest (resting-FC/resting-rCBF). Compared with no-intervention, WMT (a) increased resting-FC between the medial prefrontal cortex (mPFC) and precuneus, which are key nodes of the default mode network (DMN), (b) decreased resting-FC between mPFC and the right posterior parietal cortex/right lateral prefrontal cortex (LPFC), which are key nodes of the EAS, and (c) increased resting-rCBF in the right LPFC. However, the training-related decreases in resting-FC between the key DMN node and the nodes of EAS were only observed when the whole brain signal was regressed out in individual analyses, and these changes were not observed when the whole brain signal was not regressed out in individual analyses. Further analyses indicated that these differences may be mediated by a weak but a widespread increase in resting-FC between the nodes of EAS and activity of multiple bilateral areas across the brain. These results showed that WMT induces plasticity in neural mechanisms involving DMN and the EAS during rest and indicated that intrinsic brain activity and connectivity can be affected by cognitive training.

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

[2]  R. C. Collins,et al.  Metabolic anatomy of brain: A comparison of regional capillary density, glucose metabolism, and enzyme activities , 1989, The Journal of comparative neurology.

[3]  J. Gabrieli,et al.  Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia , 2009, Proceedings of the National Academy of Sciences.

[4]  J B Poline,et al.  The neural system that bridges reward and cognition in humans: An fMRI study , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Christian Gaser,et al.  Gray Matter Increase Induced by Practice Correlates with Task-Specific Activation: A Combined Functional and Morphometric Magnetic Resonance Imaging Study , 2008, The Journal of Neuroscience.

[6]  Yasuyuki Taki,et al.  The association between resting functional connectivity and creativity. , 2012, Cerebral cortex.

[7]  Yasuyuki Taki,et al.  Regional gray matter volume of dopaminergic system associate with creativity: Evidence from voxel-based morphometry , 2010, NeuroImage.

[8]  Jun Li,et al.  Brain spontaneous functional connectivity and intelligence , 2008, NeuroImage.

[9]  Yasuyuki Taki,et al.  Regional gray matter density associated with emotional intelligence: Evidence from voxel‐based morphometry , 2011, Human brain mapping.

[10]  Yasuyuki Taki,et al.  Failing to deactivate: The association between brain activity during a working memory task and creativity , 2011, NeuroImage.

[11]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[12]  Justin L. Vincent,et al.  Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Hiroshi Fukuda,et al.  Correlation between gray matter density‐adjusted brain perfusion and age using brain MR images of 202 healthy children , 2011, Human brain mapping.

[14]  T. Klingberg Training and plasticity of working memory , 2010, Trends in Cognitive Sciences.

[15]  W. Greenough,et al.  Differential rearing effects on rat visual cortex synapses. III. Neuronal and glial nuclei, boutons, dendrites, and capillaries , 1987, Brain Research.

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

[17]  C. S. Green,et al.  Action video game modifies visual selective attention , 2003, Nature.

[18]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[19]  D. Weinberger,et al.  Physiologic dysfunction of dorsolateral prefrontal cortex in schizophrenia. I. Regional cerebral blood flow evidence. , 1986, Archives of general psychiatry.

[20]  H. Forssberg,et al.  Computerized training of working memory in children with ADHD--a randomized, controlled trial. , 2005, Journal of the American Academy of Child and Adolescent Psychiatry.

[21]  N. Schuff,et al.  Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience. , 2005, Radiology.

[22]  Lars Bäckman,et al.  Transfer of Learning After Updating Training Mediated by the Striatum , 2008, Science.

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

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

[25]  Bogdan Draganski,et al.  Neuroplasticity: Changes in grey matter induced by training , 2004, Nature.

[26]  箱田 裕司,et al.  集団用ストループ・逆ストループテスト 反応様式, 順序, 練習の効果 , 1990 .

[27]  M. Corbetta,et al.  Learning sculpts the spontaneous activity of the resting human brain , 2009, Proceedings of the National Academy of Sciences.

[28]  A. Baddeley Working memory: looking back and looking forward , 2003, Nature Reviews Neuroscience.

[29]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[30]  Esben Thade Petersen,et al.  Model‐free arterial spin labeling quantification approach for perfusion MRI , 2006, Magnetic resonance in medicine.

[31]  A Wingfield,et al.  Does the capacity of working memory change with age? , 1988, Experimental aging research.

[32]  Takashi Kusumi,et al.  Effect of Critical Thinking Disposition on Interpretation of Controversial Issues : Evaluating Evidences and Drawing Conclusions , 2004 .

[33]  Daniel S. Margulies,et al.  Long-term effects of motor training on resting-state networks and underlying brain structure , 2011, NeuroImage.

[34]  Thomas E. Nichols,et al.  Nonstationary cluster-size inference with random field and permutation methods , 2004, NeuroImage.

[35]  A. Beech,et al.  Individual differences in negative priming: relations with schizotypal personality traits. , 1987, British journal of psychology.

[36]  A. Philalithis,et al.  Variations in prevalence of attention deficit hyperactivity disorder worldwide , 2006, European Journal of Pediatrics.

[37]  H. Forssberg,et al.  Changes in Cortical Dopamine D1 Receptor Binding Associated with Cognitive Training , 2009, NeuroImage.

[38]  B. Oken Placebo effects: clinical aspects and neurobiology. , 2008, Brain : a journal of neurology.

[39]  Hans Forssberg,et al.  Visuo-Spatial Working Memory Span: A Sensitive Measure of Cognitive Deficits in Children With ADHD , 2004, Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence.

[40]  Karl J. Friston,et al.  Detecting Activations in PET and fMRI: Levels of Inference and Power , 1996, NeuroImage.

[41]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[42]  Ramon Casanova,et al.  Biological parametric mapping: A statistical toolbox for multimodality brain image analysis , 2007, NeuroImage.

[43]  P. Reber,et al.  Correction of off resonance‐related distortion in echo‐planar imaging using EPI‐based field maps , 1998, Magnetic resonance in medicine.

[44]  Christian Büchel,et al.  Changes in Gray Matter Induced by Learning—Revisited , 2008, PloS one.

[45]  Yasuyuki Taki,et al.  Effects of Working Memory Training on Cognitive Functions and Neural Systems , 2010, Reviews in the neurosciences.

[46]  Edwin M. Robertson,et al.  The Resting Human Brain and Motor Learning , 2009, Current Biology.

[47]  M. Schölvinck,et al.  Neural basis of global resting-state fMRI activity , 2010, Proceedings of the National Academy of Sciences.

[48]  Beatriz Luna,et al.  Spatial Working Memory Deficits in Autism , 2007, Journal of autism and developmental disorders.

[49]  David Krech,et al.  Increases in cortical depth and glia numbers in rats subjected to enriched environment , 1966, The Journal of comparative neurology.

[50]  S. Debener,et al.  Default-mode brain dysfunction in mental disorders: A systematic review , 2009, Neuroscience & Biobehavioral Reviews.

[51]  X Golay,et al.  Non-invasive Measurement of Perfusion: a Critical Review of Arterial Spin Labelling Techniques , 2022 .

[52]  H. Forssberg,et al.  Training of Working Memory in Children With ADHD , 2002 .

[53]  B. Oken,et al.  Expectancy effect: Impact of pill administration on cognitive performance in healthy seniors , 2008, Journal of clinical and experimental neuropsychology.

[54]  裕司 箱田,et al.  逆ストループ干渉と精神分裂病 集団用ストループ・逆ストループテストを用いた考察 , 1993 .

[55]  M. Posner,et al.  Short-term meditation training improves attention and self-regulation , 2007, Proceedings of the National Academy of Sciences.

[56]  Kathryn M. McMillan,et al.  A comparison of label‐based review and ALE meta‐analysis in the Stroop task , 2005, Human brain mapping.

[57]  Wilkin Chau,et al.  An Empirical Comparison of SPM Preprocessing Parameters to the Analysis of fMRI Data , 2002, NeuroImage.

[58]  Yasuyuki Taki,et al.  White matter structures associated with creativity: Evidence from diffusion tensor imaging , 2010, NeuroImage.

[59]  Y. Hakoda,et al.  [Schizophrenia and reverse-Stroop interference in the group version of the Stroop and reverse-Stroop test]. , 1993, Shinrigaku kenkyu : The Japanese journal of psychology.

[60]  Yasuyuki Taki,et al.  Effects of Training of Processing Speed on Neural Systems , 2011, The Journal of Neuroscience.

[61]  Klaus P. Ebmeier,et al.  Pattern of impaired working memory during major depression. , 2006, Journal of affective disorders.

[62]  P. Goldman-Rakic Working memory dysfunction in schizophrenia. , 1994, The Journal of neuropsychiatry and clinical neurosciences.

[63]  Thomas S. Redick,et al.  No evidence of intelligence improvement after working memory training: a randomized, placebo-controlled study. , 2013, Journal of experimental psychology. General.

[64]  Susanne M. Jaeggi,et al.  Improving fluid intelligence with training on working memory: a meta-analysis , 2008, Psychonomic Bulletin & Review.

[65]  Yasuyuki Taki,et al.  Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity , 2011, PloS one.

[66]  P. Skudlarski,et al.  Brain Connectivity Related to Working Memory Performance , 2006, The Journal of Neuroscience.

[67]  L. Berkman,et al.  Social Disengagement and Incident Cognitive Decline in Community-Dwelling Elderly Persons , 1999, Annals of Internal Medicine.

[68]  J. Raven,et al.  Manual for Raven's progressive matrices and vocabulary scales , 1962 .

[69]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[70]  Adrian Furnham,et al.  The relationship between psychoticism, trait-creativity and the attentional mechanism of cognitive inhibition , 1996 .

[71]  Dost Öngür,et al.  Anticorrelations in resting state networks without global signal regression , 2012, NeuroImage.

[72]  J. Callicott,et al.  Age-related alterations in default mode network: Impact on working memory performance , 2010, Neurobiology of Aging.

[73]  Ryuta Kawashima,et al.  Reading and solving arithmetic problems improves cognitive functions of normal aged people: a randomized controlled study , 2008, AGE.

[74]  G. A. Mendelsohn,et al.  Associative and attentional processes in creative performance1 , 1976 .

[75]  Thomas E. Nichols,et al.  Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.

[76]  Yasuyuki Taki,et al.  Training of Working Memory Impacts Structural Connectivity , 2010, The Journal of Neuroscience.

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

[78]  Kevin Murphy,et al.  The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? , 2009, NeuroImage.

[79]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[80]  H. Forssberg,et al.  Changes in Cortical Dopamine D1 Receptor Binding Associated with Cognitive Training , 2009, NeuroImage.

[81]  Karl J. Friston,et al.  Decreases in Regional Cerebral Blood Flow with Normal Aging , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[82]  V. Stenger Technical considerations for BOLD fMRI of the orbitofrontal cortex , 2006 .