Visual working memory capacity and stimulus categories: a behavioral and electrophysiological investigation

It has recently been suggested that visual working memory capacity may vary depending on the type of material that has to be memorized. Here, we use a delayed match-to-sample paradigm and event-related potentials (ERP) to investigate the neural correlates that are linked to these changes in capacity. A variable number of stimuli (1–4) were presented in each visual hemifield. Participants were required to selectively memorize the stimuli presented in one hemifield. Following memorization, a test stimulus was presented that had to be matched against the memorized item(s). Two types of stimuli were used: one set consisting of discretely different objects (discrete stimuli) and one set consisting of more continuous variations along a single dimension (continuous stimuli). Behavioral results indicate that memory capacity was much larger for the discrete stimuli, when compared with the continuous stimuli. This behavioral effect correlated with an increase in a contralateral negative slow wave ERP component that is known to be involved in memorization. We therefore conclude that the larger working memory capacity for discrete stimuli can be directly related to an increase in activity in visual areas and propose that this increase in visual activity is due to interactions with other, non-visual representations.

[1]  Maro G. Machizawa,et al.  Neural activity predicts individual differences in visual working memory capacity , 2004, Nature.

[2]  Matthew S. Peterson,et al.  Visual working memory capacity for objects from different categories: A face-specific maintenance effect , 2008, Cognition.

[3]  J. Theeuwes,et al.  Electrophysiological Evidence of the Capture of Visual Attention , 2006, Journal of Cognitive Neuroscience.

[4]  Edward K. Vogel,et al.  Event-Related Potential Measures of Visual Working Memory , 2006, Clinical EEG and neuroscience.

[5]  J. Grafman,et al.  Multiple visuospatial working memory buffers: Evidence from spatiotemporal patterns of brain activity , 1997, Neuropsychologia.

[6]  J. Kenemans,et al.  Removal of the ocular artifact from the EEG: a comparison of time and frequency domain methods with simulated and real data. , 1991, Psychophysiology.

[7]  H Pashler,et al.  Familiarity and visual change detection , 1988, Perception & psychophysics.

[8]  J. Duncan,et al.  Encoding Strategies Dissociate Prefrontal Activity from Working Memory Demand , 2003, Neuron.

[9]  Leslie G. Ungerleider,et al.  Transient and sustained activity in a distributed neural system for human working memory , 1997, Nature.

[10]  Maro G. Machizawa,et al.  Neural measures reveal individual differences in controlling access to working memory , 2005, Nature.

[11]  D. Talsma,et al.  Methods for the estimation and removal of artifacts and overlap in ERP data , 2004 .

[12]  M. D’Esposito Working memory. , 2008, Handbook of clinical neurology.

[13]  Hans-Jochen Heinze,et al.  Representations in human visual short-term memory: an event-related brain potential study , 1999, Neuroscience Letters.

[14]  Henrik Olsson,et al.  Binding feature dimensions in visual short-term memory. , 2009, Acta psychologica.

[15]  Kevin Dent,et al.  Verbal coding and the storage of form-position associations in visual-spatial short-term memory. , 2005, Acta psychologica.

[16]  N. Cowan The magical number 4 in short-term memory: A reconsideration of mental storage capacity , 2001, Behavioral and Brain Sciences.

[17]  G Mulder,et al.  Working memory processes show different degrees of lateralization: evidence from event-related potentials. , 2001, Psychophysiology.

[18]  Durk Talsma,et al.  Auto-adaptive averaging: detecting artifacts in event-related potential data using a fully automated procedure. , 2008, Psychophysiology.

[19]  Isabel Gauthier,et al.  A visual short-term memory advantage for objects of expertise. , 2009, Journal of experimental psychology. Human perception and performance.

[20]  A. Owen,et al.  Prefrontal cortical involvement in verbal encoding strategies , 2004, The European journal of neuroscience.

[21]  Durk Talsma,et al.  Procedures and Strategies for Optimizing the Signal-to-Noise Ratio in Event-Related Potential Data , 2009 .

[22]  Henrik Olsson,et al.  Visual memory needs categories. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Maro G. Machizawa,et al.  Electrophysiological Measures of Maintaining Representations in Visual Working Memory , 2007, Cortex.

[24]  Gijsbertus Mulder,et al.  ERP effects of spatial attention and display search with unilateral and bilateral stimulus displays , 1999, Biological Psychology.

[25]  Mowei Shen,et al.  Storing fine detailed information in visual working memory--evidence from event-related potentials. , 2009, Journal of vision.

[26]  Edward K. Vogel,et al.  The capacity of visual working memory for features and conjunctions , 1997, Nature.

[27]  Todd C. Handy,et al.  Brain Signal Analysis: Advances In Neuroelectric and Neuromagnetic Methods , 2011 .

[28]  Frédéric Gosselin,et al.  On the representation of words and nonwords in visual short-term memory: evidence from human electrophysiology. , 2009, Psychophysiology.

[29]  A. A. Wijers,et al.  An event-related brain potential correlate of visual short-term memory. , 1999, Neuroreport.

[30]  K. R. Ridderinkhof,et al.  Selective attention to spatial and non-spatial visual stimuli is affected differentially by age: effects on event-related brain potentials and performance data. , 2006, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[31]  M. Chun,et al.  Organization of visual short-term memory. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[32]  G. Woodman,et al.  Storage of features, conjunctions and objects in visual working memory. , 2001, Journal of experimental psychology. Human perception and performance.

[33]  Leslie G. Ungerleider,et al.  A neural system for human visual working memory. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Roy Luria,et al.  Visual Short-term Memory Capacity for Simple and Complex Objects , 2010, Journal of Cognitive Neuroscience.

[35]  P. Cavanagh,et al.  The Capacity of Visual Short-Term Memory is Set Both by Visual Information Load and by Number of Objects , 2004, Psychological science.

[36]  E. Vogel,et al.  PSYCHOLOGICAL SCIENCE Research Article Visual Working Memory Represents a Fixed Number of Items Regardless of Complexity , 2022 .

[37]  N. Cowan Visual and auditory working memory capacity , 1998, Trends in Cognitive Sciences.

[38]  Maro G. Machizawa,et al.  Capacity limit of visual short-term memory in human posterior parietal cortex , 2004 .

[39]  E. Vogel,et al.  Contralateral delay activity provides a neural measure of the number of representations in visual working memory. , 2010, Journal of neurophysiology.