Reduced posterior parietal cortex activation after training on a visual search task

Gaining experience on a cognitive task improves behavioral performance and is thought to enhance brain efficiency. Despite the body of literature already published on the effects of training on brain activation, less research has been carried out on visual search attention processes under well controlled conditions. Thirty-six healthy adults divided into trained and control groups completed a pre-post letter-based visual search task fMRI study in one day. Twelve letters were used as targets and ten as distractors. The trained group completed a training session (840 trials) with half the targets between scans. The effects of training were studied at the behavioral and brain levels by controlling for repetition effects using both between-subjects (trained vs. control groups) and within-subject (trained vs. untrained targets) controls. The trained participants reduced their response speed by 31% as a result of training, maintaining their accuracy scores, whereas the control group hardly changed. Neural results revealed that brain changes associated with visual search training were circumscribed to reduced activation in the posterior parietal cortex (PPC) when controlling for group, and they included inferior occipital areas when controlling for targets. The observed behavioral and brain changes are discussed in relation to automatic behavior development. The observed training-related decreases could be associated with increased neural efficiency in specific key regions for task performance.

[1]  J. Phillips,et al.  Automatic behaviour: Efficient not mindless , 2007, Brain Research Bulletin.

[2]  Matthew T. Kaufman,et al.  A category-free neural population supports evolving demands during decision-making , 2014, Nature Neuroscience.

[3]  M. Goldberg,et al.  Attention, intention, and priority in the parietal lobe. , 2010, Annual review of neuroscience.

[4]  M. W. Kristofferson,et al.  When visual search functions look like item recognition functions , 1973 .

[5]  Radoslaw Martin Cichy,et al.  Spatial attention enhances object coding in local and distributed representations of the lateral occipital complex , 2015, NeuroImage.

[6]  Hugh Garavan,et al.  Automaticity and Reestablishment of Executive ControlAn fMRI Study , 2006, Journal of Cognitive Neuroscience.

[7]  M. W. Kristofferson When item recognition and visual search functions are similar , 1972 .

[8]  Jonas Larsson,et al.  fMRI repetition suppression: neuronal adaptation or stimulus expectation? , 2012, Cerebral cortex.

[9]  U. Neisser Decision-time without reaction-time: Experiments in visual scanning. , 1963 .

[10]  U NEISSER,et al.  Searching for Ten Targets Simultaneously , 1963, Perceptual and motor skills.

[11]  Michael B. Miller,et al.  The principled control of false positives in neuroimaging. , 2009, Social cognitive and affective neuroscience.

[12]  Marc A. Sullivan,et al.  Practice and working memory effects in building procedural skill. , 1989 .

[13]  Camarin E. Rolle,et al.  Video game training enhances cognitive control in older adults , 2013, Nature.

[14]  Patrick Rabbitt,et al.  Improvement, Learning and Retention of Skill at Visual Search , 1979 .

[15]  J. Duncan Cooperating brain systems in selective perception and action. , 1996 .

[16]  Noelia Ventura-Campos,et al.  Functional Connectivity Between Superior Parietal Lobule and Primary Visual Cortex "at Rest" Predicts Visual Search Efficiency , 2015, Brain Connect..

[17]  M. Lindquist The Statistical Analysis of fMRI Data. , 2008, 0906.3662.

[18]  W. Schneider,et al.  Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning. , 2005, Brain research. Cognitive brain research.

[19]  J. Bisley The neural basis of visual attention , 2011, The Journal of physiology.

[20]  R. Poldrack Imaging Brain Plasticity: Conceptual and Methodological Issues— A Theoretical Review , 2000, NeuroImage.

[21]  Leslie G. Ungerleider,et al.  Mechanisms of visual attention in the human cortex. , 2000, Annual review of neuroscience.

[22]  Walter Schneider,et al.  Controlled & automatic processing: behavior, theory, and biological mechanisms , 2003, Cogn. Sci..

[23]  D. Eckstein,et al.  Rule-Selection and Action-Selection have a Shared Neuroanatomical Basis in the Human Prefrontal and Parietal Cortex , 2008, Cerebral cortex.

[24]  Gustavo Deco,et al.  The neurodynamics of visual search , 2006 .

[25]  C. Bundesen A theory of visual attention. , 1990, Psychological review.

[26]  R. Desimone,et al.  Neural mechanisms for visual memory and their role in attention. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[27]  M. Eimer The neural basis of attentional control in visual search , 2014, Trends in Cognitive Sciences.

[28]  J. Duncan,et al.  Visual search and stimulus similarity. , 1989, Psychological review.

[29]  R. Shiffrin,et al.  Controlled and automatic human information processing: I , 1977 .

[30]  Walter Schneider,et al.  The Brain’s Learning and Control Architecture , 2012 .

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

[32]  M. Posner Chronometric explorations of mind : the third Paul M. Fitts lectures, delivered at the University of Michigan, September 1976 , 1978 .

[33]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[34]  R. Ptak The Frontoparietal Attention Network of the Human Brain , 2012, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[35]  K. Grill-Spector,et al.  fMR-adaptation: a tool for studying the functional properties of human cortical neurons. , 2001, Acta psychologica.

[36]  K J Friston,et al.  The predictive value of changes in effective connectivity for human learning. , 1999, Science.

[37]  Nicolas Y. Masse,et al.  Task-specific versus generalized mnemonic representations in parietal and prefrontal cortices , 2015, Nature Neuroscience.

[38]  G. Logan Toward an instance theory of automatization. , 1988 .

[39]  B. Postle,et al.  The cognitive neuroscience of working memory. , 2007, Annual review of psychology.

[40]  A. D. Fisk,et al.  Degree of consistent training: Improvements in search performance and automatic process development , 1982, Perception & psychophysics.

[41]  P. T. Fox,et al.  Positron emission tomographic studies of the cortical anatomy of single-word processing , 1988, Nature.

[42]  S. Petersen,et al.  Practice-related changes in human brain functional anatomy during nonmotor learning. , 1994, Cerebral cortex.

[43]  S. Kastner,et al.  From Behavior to Neural Dynamics: An Integrated Theory of Attention , 2015, Neuron.

[44]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

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

[46]  F. Gregory Ashby,et al.  Cortical and striatal contributions to automaticity in information-integration categorization , 2011, NeuroImage.

[47]  M. Posner,et al.  Attention and cognitive control. , 1975 .

[48]  W. Prinz Locus of the effect of specific practice in continuous visual search , 1979 .

[49]  S Lehéricy,et al.  The visual word form area: spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients. , 2000, Brain : a journal of neurology.

[50]  A. Mecklinger,et al.  Separating intra-modal and across-modal training effects in visual working memory: an fMRI investigation. , 2011, Cerebral cortex.

[51]  A. Kelly,et al.  Human functional neuroimaging of brain changes associated with practice. , 2005, Cerebral cortex.

[52]  Hugh Garavan,et al.  Practice‐related functional activation changes in a working memory task , 2000, Microscopy research and technique.

[53]  Ikuko Mukai,et al.  Behavioral/systems/cognitive Activations in Visual and Attention-related Areas Predict and Correlate with the Degree of Perceptual Learning , 2022 .

[54]  Stefanie I. Becker,et al.  Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI , 2014, NeuroImage.

[55]  Edward F. Ester,et al.  Parietal and Frontal Cortex Encode Stimulus-Specific Mnemonic Representations during Visual Working Memory , 2015, Neuron.

[56]  Amir Amedi,et al.  Origins of the specialization for letters and numbers in ventral occipitotemporal cortex , 2015, Trends in Cognitive Sciences.

[57]  David J. Freedman,et al.  Experience-dependent representation of visual categories in parietal cortex , 2006, Nature.

[58]  Alex Martin,et al.  Properties and mechanisms of perceptual priming , 1998, Current Opinion in Neurobiology.

[59]  E. Rolls,et al.  Attention, short-term memory, and action selection: A unifying theory , 2005, Progress in Neurobiology.

[60]  Sygal Amitay,et al.  The Effects of Stimulus Variability on the Perceptual Learning of Speech and Non-Speech Stimuli , 2015, PloS one.

[61]  D. Mumford,et al.  Neural activity in early visual cortex reflects behavioral experience and higher-order perceptual saliency , 2002, Nature Neuroscience.