Attention and Pattern Consciousness Reorganize the Cortical Topography of Event-Related Potential Correlates of Visual Sequential Learning

Statistical or sequential learning (SL) involves comprehending environmental patterns in which some items precede other items with a given likelihood. SL is thought to occur without attention or consciousness (or explicit knowledge) of the learned patterns and thus is sometimes considered to be implicit learning. However, this assumption is still debatable (Daltrozzo & Conway, 2014). We examined the role of selective attention and pattern consciousness (PC) in SL using event-related potentials (ERP) with healthy adults. Thirty-four participants (27 females, 18-49 years) performed a Flanker task to assess their level of selective attention, followed by a visual SL task while ERPs were recorded. Participants’ level of PC was assessed via a questionnaire. In the SL task, participants viewed a sequence of different stimuli on the screen and were instructed to press a button as fast as possible, when they saw a target stimulus. They were unaware that: 1.) two predictor items were embedded in the sequence and 2.) the items predicted target occurrence with high or low probability. ERPs were timelocked to predictor onsets. The mean ERP between 200 and 700ms post-predictor onset revealed an interaction between target occurrence probability, PC, attention, and two scalp topographic factors. Post-hoc tests indicated that higher attention was related to a more rostral left lateralized effect under high PC and a left lateralization of SL ERP effects under low PC. These neural findings suggest that both attention and PC modulate SL.

[1]  Morten H. Christiansen,et al.  Similar neural correlates for language and sequential learning: Evidence from event-related brain potentials , 2012, Language and cognitive processes.

[2]  P. Perruchet,et al.  Implicit learning and statistical learning: one phenomenon, two approaches , 2006, Trends in Cognitive Sciences.

[3]  M. Goldsmith,et al.  Statistical Learning by 8-Month-Old Infants , 1996 .

[4]  K. Lashley The problem of serial order in behavior , 1951 .

[5]  Christopher M. Conway,et al.  Exploring the neurodevelopment of visual statistical learning using event-related brain potentials , 2015, Brain Research.

[6]  M. Eimer,et al.  A dissociation between selective attention and conscious awareness in the representation of temporal order information , 2015, Consciousness and Cognition.

[7]  Christopher M. Conway,et al.  Implicit statistical learning in language processing: Word predictability is the key , 2010, Cognition.

[8]  Hilde Haider,et al.  The transition from implicit to explicit representations in incidental learning situations: more evidence from high-frequency EEG coupling , 2011, Experimental Brain Research.

[9]  Toral Burghoff,et al.  Linear-Mixed Models—A Practical Guide Using Statistical Software, Second Edition. B. T. West, K. B. Welch, and A. T. Galecki. (2015). Boca Raton, FL: Taylor and Francis/CRC Press. 440 pages, ISBN-10: 1466560991, ISBN-13: 978–1466560994. , 2016 .

[10]  N. Kraus,et al.  Musical Experience and the Aging Auditory System: Implications for Cognitive Abilities and Hearing Speech in Noise , 2011, PloS one.

[11]  Christopher M. Conway,et al.  The Effect of Music Experience on Auditory Sequential Learning: An ERP Study , 2014, CogSci.

[12]  M. Fenske,et al.  Modulation of focused attention by faces expressing emotion: evidence from flanker tasks. , 2003, Emotion.

[13]  F. K. Berrien,et al.  The effects of noise. , 1946, Psychological bulletin.

[14]  C. Eriksen,et al.  Effects of noise letters upon the identification of a target letter in a nonsearch task , 1974 .

[15]  Julia Uddén,et al.  A rostro-caudal gradient of structured sequence processing in the left inferior frontal gyrus , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[16]  E. Viding,et al.  Load theory of selective attention and cognitive control. , 2004, Journal of experimental psychology. General.

[17]  B. Scholl,et al.  The Automaticity of Visual Statistical Learning Statistical Learning , 2005 .

[18]  Christopher M. Conway,et al.  Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us? , 2014, Front. Hum. Neurosci..

[19]  N. Kraus,et al.  Musical experience shapes top-down auditory mechanisms: Evidence from masking and auditory attention performance , 2010, Hearing Research.

[20]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[21]  B. Kotchoubey,et al.  The N400 and Late Positive Complex (LPC) Effects Reflect Controlled Rather than Automatic Mechanisms of Sentence Processing , 2012, Brain sciences.

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

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