Resolving the Electroencephalographic Correlates of Rapid Goal-Directed Chunking in the Frontal-Parietal Network

Previous studies have revealed a specific role of the prefrontal-parietal network in rapid goal-directed chunking (RGDC), which dissociates prefrontal activity related to chunking from parietal working memory demands. However, it remains unknown how the prefrontal and parietal cortices collaborate to accomplish RGDC. To this end, a novel experimental design was used that presented Chinese characters in a chunking task, testing eighteen undergraduate students (9 females, mean age = 22.4 years) while recoding the electroencephalogram (EEG). In the experiment, radical-level chunking was accomplished in a timely stringent way (RT = 1485 ms, SD = 371 ms), whereas the stroke-level chunking was accomplished less coherently (RT = 3278 ms, SD = 1083 ms). By comparing the differences between radical-level chunking vs. stroke-level chunking, we were able to dissociate the chunking processes in the radical-level chunking condition within the analyzed time window (−200 to 1300 ms). The chunking processes resulted in an early increase of gamma band synchronization over parietal and occipital cortices, followed by enhanced power in the beta-gamma band (25–38 Hz) over frontal areas. We suggest that the posterior rhythmic activities in the gamma band may underlie the processes that are directly associated with perceptual manipulations of chunking, while the subsequent beta-gamma activation over frontal areas appears to reflect a post-evaluation process such as reinforcement of the selected rules over alternative solutions, which may be an important characteristic of goal-directed chunking.

[1]  Hong Li,et al.  Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making. , 2016, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[2]  Maxime J Parent,et al.  Movement chunking during sequence learning is a dopamine-dependant process: a study conducted in Parkinson’s disease , 2010, Experimental Brain Research.

[3]  Adrian M Owen,et al.  A common prefrontal-parietal network for mnemonic and mathematical recoding strategies within working memory. , 2007, Cerebral cortex.

[4]  O. Bertrand,et al.  Oscillatory gamma activity in humans and its role in object representation , 1999, Trends in Cognitive Sciences.

[5]  Werner Lutzenberger,et al.  Words and pseudowords elicit distinct patterns of 30-Hz EEG responses in humans , 1994, Neuroscience Letters.

[6]  Lars Kai Hansen,et al.  Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG , 2006, NeuroImage.

[7]  Eduardo Martínez-Montes,et al.  Identifying Complex Brain Networks Using Penalized Regression Methods , 2008, Journal of biological physics.

[8]  Xin Jin,et al.  Basal Ganglia Subcircuits Distinctively Encode the Parsing and Concatenation of Action Sequences , 2014, Nature Neuroscience.

[9]  A Keil,et al.  Human large-scale oscillatory brain activity during an operant shaping procedure. , 2001, Brain research. Cognitive brain research.

[10]  Pei Sun,et al.  Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation , 2018, NeuroImage.

[11]  A. Seth,et al.  Consciousness and the Prefrontal Parietal Network: Insights from Attention, Working Memory, and Chunking , 2012, Front. Psychology.

[12]  Antoni Rodríguez-Fornells,et al.  Brain oscillatory activity associated with task switching and feedback processing , 2011, Cognitive, Affective, & Behavioral Neuroscience.

[13]  Kazuhisa Niki,et al.  Perceptual contributions to problem solving: Chunk decomposition of Chinese characters , 2006, Brain Research Bulletin.

[14]  A. Engel,et al.  Cognitive functions of gamma-band activity: memory match and utilization , 2004, Trends in Cognitive Sciences.

[15]  Francisco del Pozo,et al.  Dynamic gamma frequency feedback coupling between higher and lower order visual cortices underlies perceptual completion in humans , 2014, NeuroImage.

[16]  J. Hogan Restructuring revisited , 2012 .

[17]  LiLi Wu,et al.  Effective connectivity of dorsal and ventral visual pathways in chunk decomposition , 2010, Science China Life Sciences.

[18]  F. Varela,et al.  Perception's shadow: long-distance synchronization of human brain activity , 1999, Nature.

[19]  J. Mumford,et al.  Greater Neural Pattern Similarity Across Repetitions Is Associated with Better Memory , 2010, Science.

[20]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.

[21]  R. Verleger,et al.  Parafac and go/no-go: disentangling CNV return from the P3 complex by trilinear component analysis. , 2013, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[22]  Ronald W. Langacker,et al.  Nouns and Verbs , 1987 .

[23]  Hermann J Müller,et al.  Object maintenance beyond their visible parts in working memory 1 , 2018 .

[24]  Satu Palva,et al.  Gamma Oscillations Underlie the Maintenance of Feature-Specific Information and the Contents of Visual Working Memory. , 2015, Cerebral cortex.

[25]  Jing Luo,et al.  How perceptual processes help to generate new meaning: An EEG study of chunk decomposition in Chinese characters , 2009, Brain Research.

[26]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[27]  H. Simon,et al.  Perception in chess , 1973 .

[28]  S. Ohlsson Restructuring revisited: I. Summary and critique of the Gestalt theory of problem solving. , 1984 .

[29]  Nai Ding,et al.  Perceptual integration rapidly activates dorsal visual pathway to guide local processing in early visual areas , 2017, PLoS biology.

[30]  G. A. Miller THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[31]  Richard C. Anderson,et al.  Visual Chunking Skills of Hong Kong Children , 2005 .

[32]  W. Singer,et al.  Neuronal assemblies: necessity, signature and detectability , 1997, Trends in Cognitive Sciences.

[33]  Eric Walden,et al.  Rule activation and ventromedial prefrontal engagement support accurate stopping in self-paced learning , 2017, NeuroImage.

[34]  J Gross,et al.  REPRINTS , 1962, The Lancet.

[35]  Hong Li,et al.  Chunk decomposition contributes to forming new mental representations: An ERP study , 2015, Neuroscience Letters.

[36]  J. Pine,et al.  Chunking mechanisms in human learning , 2001, Trends in Cognitive Sciences.

[37]  F Pulvermüller,et al.  Nouns and verbs in the intact brain: evidence from event-related potentials and high-frequency cortical responses. , 1999, Cerebral cortex.

[38]  Andrzej Cichocki,et al.  Smooth PARAFAC Decomposition for Tensor Completion , 2015, IEEE Transactions on Signal Processing.

[39]  John J. B. Allen,et al.  EEG phase synchrony differences across visual perception conditions may depend on recording and analysis methods , 2005, Clinical Neurophysiology.

[40]  L. Tan,et al.  Reading depends on writing, in Chinese. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Jing Luo,et al.  The role of chunk tightness and chunk familiarity in problem solving: Evidence from ERPs and fMRI , 2013, Human brain mapping.

[42]  Maxime Levesque,et al.  Motor sequence learning in primate: Role of the D2 receptor in movement chunking during consolidation , 2009, Behavioural Brain Research.

[43]  S. Ohlsson,et al.  Constraint relaxation and chunk decomposition in insight problem solving , 1999 .

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

[45]  Jing Luo,et al.  Probing the Cognitive Mechanism of Mental Representational Change During Chunk Decomposition: A Parametric fMRI Study. , 2016, Cerebral cortex.

[46]  H. Semlitsch,et al.  A solution for reliable and valid reduction of ocular artifacts, applied to the P300 ERP. , 1986, Psychophysiology.

[47]  Eric L. Denovellis,et al.  Synchronous Oscillatory Neural Ensembles for Rules in the Prefrontal Cortex , 2012, Neuron.

[48]  Frank Konietschke,et al.  A wild bootstrap approach for nonparametric repeated measurements , 2017, Comput. Stat. Data Anal..

[49]  S. Ohlsson Information-processing explanations of insight and related phenomena , 1992 .

[50]  A. Rodríguez-Fornells,et al.  Neuroscience and Biobehavioral Reviews the Role of High-frequency Oscillatory Activity in Reward Processing and Learning , 2022 .

[51]  A. Osman,et al.  On the locus of speed-accuracy trade-off in reaction time: inferences from the lateralized readiness potential. , 2004, Journal of experimental psychology. General.

[52]  B. Postle,et al.  Superior Parietal Cortex Is Critical for the Manipulation of Information in Working Memory , 2009, The Journal of Neuroscience.

[53]  Carsten Nicolas Boehler,et al.  Binding 3-D Object Perception in the Human Visual Cortex , 2008, Journal of Cognitive Neuroscience.

[54]  J. Edwards,et al.  Motor sequence chunking is impaired by basal ganglia stroke , 2009, Neurobiology of Learning and Memory.

[55]  Jin Fan,et al.  The neural basis of novelty and appropriateness in processing of creative chunk decomposition , 2015, NeuroImage.

[56]  Matthias M. Müller,et al.  Human Gamma Band Activity and Perception of a Gestalt , 1999, The Journal of Neuroscience.

[57]  J. Kaiser,et al.  Induced Gamma-Band Activity and Human Brain Function , 2003, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[58]  A. Engel,et al.  Beta-band oscillations—signalling the status quo? , 2010, Current Opinion in Neurobiology.

[59]  Xiao-Jing Wang Neurophysiological and computational principles of cortical rhythms in cognition. , 2010, Physiological reviews.

[60]  Ernest Mas-Herrero,et al.  Beta oscillations and reward processing: Coupling oscillatory activity and hemodynamic responses , 2015, NeuroImage.

[61]  Lars Kai Hansen,et al.  ERPWAVELAB A toolbox for multi-channel analysis of time–frequency transformed event related potentials , 2007, Journal of Neuroscience Methods.

[62]  G. A. Miller The magical number seven plus or minus two: some limits on our capacity for processing information. , 1956, Psychological review.

[63]  C M Krause,et al.  Automatic auditory word perception as measured by 40 Hz EEG responses. , 1998, Electroencephalography and clinical neurophysiology.