Functional brain connectivity and cognition: effects of adult age and task demands

Previous neuroimaging research has documented that patterns of intrinsic (resting state) functional connectivity (FC) among brain regions covary with individual measures of cognitive performance. Here, we examined the relation between intrinsic FC and a reaction time (RT) measure of performance, as a function of age group and task demands. We obtained filtered, event-related functional magnetic resonance imaging data, and RT measures of visual search performance, from 21 younger adults (19-29 years old) and 21 healthy, older adults (60-87 years old). Age-related decline occurred in the connectivity strength in multiple brain regions, consistent with previous findings. Among 8 pairs of regions, across somatomotor, orbitofrontal, and subcortical networks, increasing FC was associated with faster responding (lower RT). Relative to younger adults, older adults exhibited a lower strength of this RT-connectivity relation and greater disruption of this relation by a salient but irrelevant display item (color singleton distractor). Age-related differences in the covariation of intrinsic FC and cognitive performance vary as a function of task demands.

[1]  G. Glover,et al.  Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control , 2007, The Journal of Neuroscience.

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

[3]  Mary E. Meyerand,et al.  Support vector machine classification and characterization of age-related reorganization of functional brain networks , 2012, NeuroImage.

[4]  S. Rombouts,et al.  Reduced resting-state brain activity in the "default network" in normal aging. , 2008, Cerebral cortex.

[5]  J. Morris,et al.  Functional deactivations: Change with age and dementia of the Alzheimer type , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[6]  C. Grady,et al.  Age differences in the frontoparietal cognitive control network: Implications for distractibility , 2012, Neuropsychologia.

[7]  M. Greicius,et al.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.

[8]  Thad A. Polk,et al.  Human Neuroscience , 2022 .

[9]  C. Grady,et al.  Age differences in default and reward networks during processing of personally relevant information , 2012, Neuropsychologia.

[10]  Agnieszka Z. Burzynska,et al.  Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. , 2012, Biochimica et biophysica acta.

[11]  Jonathan D. Cohen,et al.  Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster‐Size Threshold , 1995, Magnetic resonance in medicine.

[12]  Archana Venkataraman,et al.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. , 2010, Journal of neurophysiology.

[13]  D. Leopold,et al.  Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest , 2008, Human brain mapping.

[14]  Wenjun Li,et al.  A method to determine the necessity for global signal regression in resting‐state fMRI studies , 2012, Magnetic resonance in medicine.

[15]  J. Wolfe,et al.  Changing your mind: on the contributions of top-down and bottom-up guidance in visual search for feature singletons. , 2003, Journal of experimental psychology. Human perception and performance.

[16]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[17]  S Makeig,et al.  Analysis of fMRI data by blind separation into independent spatial components , 1998, Human brain mapping.

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

[19]  K. Walhovd,et al.  Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences , 2010, Reviews in the neurosciences.

[20]  R. Cabeza,et al.  Neuroimaging of Healthy Cognitive Aging , 2011 .

[21]  Andrew B. Leber,et al.  It’s under control: Top-down search strategies can override attentional capture , 2006, Psychonomic bulletin & review.

[22]  T. Salthouse.  Speed of behavior and its implications for cog-nition , 1985 .

[23]  Katherine A. Johnson,et al.  Sustained attention, attentional selectivity, and attentional capacity across the lifespan , 2012, Attention, Perception, & Psychophysics.

[24]  David H. Salat,et al.  The Declining Infrastructure of the Aging Brain , 2011, Brain Connect..

[25]  Danny J. J. Wang,et al.  Loss of Coherence of Low Frequency Fluctuations of BOLD FMRI in Visual Cortex of Healthy Aged Subjects , 2011, The open neuroimaging journal.

[26]  M. Corbetta,et al.  Individual variability in functional connectivity predicts performance of a perceptual task , 2012, Proceedings of the National Academy of Sciences.

[27]  Allen W. Song,et al.  Measurement of spontaneous signal fluctuations in fMRI: adult age differences in intrinsic functional connectivity , 2009, Brain Structure and Function.

[28]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[29]  Evan Fletcher,et al.  Influence of functional connectivity and structural MRI measures on episodic memory , 2012, Neurobiology of Aging.

[30]  Denise C. Park,et al.  Handbook of the Psychology of Aging , 1979 .

[31]  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.

[32]  Vince D. Calhoun,et al.  Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices , 2012, Front. Hum. Neurosci..

[33]  Justin L. Vincent,et al.  Intrinsic Fluctuations within Cortical Systems Account for Intertrial Variability in Human Behavior , 2007, Neuron.

[34]  Paul T. Costa,et al.  Recent advances in psychology and aging , 2004 .

[35]  Pierluigi Nicotera,et al.  Ageing, Neuronal Connectivity and Brain Disorders: An Unsolved Ripple Effect , 2011, Molecular Neurobiology.

[36]  David J. Madden,et al.  Age-related changes in visual attention , 2003 .

[37]  M. Corbetta,et al.  Quantitative analysis of attention and detection signals during visual search. , 2003, Journal of neurophysiology.

[38]  Efstathios D. Gennatas,et al.  Predicting Regional Neurodegeneration from the Healthy Brain Functional Connectome , 2012, Neuron.

[39]  N. Volkow,et al.  Aging and Functional Brain Networks , 2011, Molecular Psychiatry.

[40]  C. Luo,et al.  The heterogeneity of aging brain: altered functional connectivity in default mode network in older adults during verbal fluency tests. , 2012, Chinese medical journal.

[41]  M. Greicius,et al.  Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity , 2009, Brain Structure and Function.

[42]  Abraham Z. Snyder,et al.  A method for using blocked and event-related fMRI data to study “resting state” functional connectivity , 2007, NeuroImage.

[43]  Rex E. Jung,et al.  A Baseline for the Multivariate Comparison of Resting-State Networks , 2011, Front. Syst. Neurosci..

[44]  Jeffrey S. Anderson,et al.  Connectivity Gradients Between the Default Mode and Attention Control Networks , 2011, Brain Connect..

[45]  Julia Spaniol,et al.  Age-related increase in top-down activation of visual features , 2007, Quarterly journal of experimental psychology.

[46]  Justin L. Vincent,et al.  Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. , 2008, Journal of neurophysiology.

[47]  Jeroen van der Grond,et al.  Imaging the default mode network in aging and dementia. , 2012, Biochimica et biophysica acta.

[48]  Justin L. Vincent,et al.  Distinct brain networks for adaptive and stable task control in humans , 2007, Proceedings of the National Academy of Sciences.

[49]  John A. E. Anderson,et al.  A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. , 2010, Cerebral cortex.

[50]  David J. Madden,et al.  Aging and Visual Attention , 2007, Current directions in psychological science.

[51]  Jessica A. Turner,et al.  Behavioral Interpretations of Intrinsic Connectivity Networks , 2011, Journal of Cognitive Neuroscience.

[52]  D J Madden,et al.  Adult age differences in visual search accuracy: attentional guidance and target detectability. , 1999, Psychology and aging.

[53]  David J. Madden,et al.  Searching from the Top Down: Ageing and Attentional Guidance during Singleton Detection , 2005, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[54]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[55]  D. Plude,et al.  Aging, selective attention, and feature integration. , 1989, Psychology and aging.

[56]  R. Fisher.  014: On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample. , 1921 .

[57]  Keith A. Johnson,et al.  Disruption of Functional Connectivity in Clinically Normal Older Adults Harboring Amyloid Burden , 2009, The Journal of Neuroscience.

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

[59]  M. V. D. Heuvel,et al.  Exploring the brain network: A review on resting-state fMRI functional connectivity , 2010, European Neuropsychopharmacology.

[60]  N. Raz.  The Aging Brain Observed in Vivo: Differential Changes and Their Modifiers. , 2005 .

[61]  Abraham Z. Snyder,et al.  A default mode of brain function: A brief history of an evolving idea , 2007, NeuroImage.

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

[63]  Justin L. Vincent,et al.  Disruption of Large-Scale Brain Systems in Advanced Aging , 2007, Neuron.

[64]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[65]  G. Busatto,et al.  Resting-state functional connectivity in normal brain aging , 2013, Neuroscience & Biobehavioral Reviews.

[66]  Erlend Hodneland,et al.  Cortico-striatal connectivity and cognition in normal aging: A combined DTI and resting state fMRI study , 2011, NeuroImage.

[67]  A. Shmuel,et al.  Sustained Negative BOLD, Blood Flow and Oxygen Consumption Response and Its Coupling to the Positive Response in the Human Brain , 2002, Neuron.

[68]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[69]  E. Bullmore,et al.  Neurophysiological architecture of functional magnetic resonance images of human brain. , 2005, Cerebral cortex.

[70]  B. Hommel,et al.  Visual search across the life span. , 2004, Developmental psychology.

[71]  Abimbola Farinde,et al.  The Beck Depression Inventory , 2013 .

[72]  C. Grady.  Cognitive Neuroscience of Aging , 2008, Annals of the New York Academy of Sciences.

[73]  Rainer Goebel,et al.  Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI. , 2008, Magnetic resonance imaging.