Altered Regional Brain Communities during High Order Cognitive Processes: Relation to Vigilance Decrement

Understanding modular organization between brain regions can provide deeper insight into the complex neural mechanisms associated with processes like vigilance decrement. Distinct but interacting modules in brain connectivity networks have been known to support integration of specific mechanisms relevant in high-order cognitive processes. To investigate the neuronal mechanisms associated with vigilance decrement, we conducted an experiment where the participants performed a driving task. EEG graph metrics within communities, like clustering coefficient (Cintra), efficiency (Eintra), density (Dintra), and between communities, like intermodule density (Dinter), were computed from the source-localized surface brain signals. Further, we also calculated the nodal out degree to investigate the difference in information flow in the brain during vigilance decrement. Increase in the intermodule density, Dinter, was observed from the left fronto-parietal cluster to the right temporo-parietal cluster. Moreover, significant reduction in the intramodule metrics, Eintra and Cintra was observed in the right temporo- parietal cluster. Thus, our findings signify a flexible topographical architecture to compensate the hub disruption effect caused due to decline in vigilance.

[1]  W. De Clercq,et al.  Automatic Removal of Ocular Artifacts in the EEG without an EOG Reference Channel , 2006, Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006.

[2]  W. Klimesch Alpha-band oscillations, attention, and controlled access to stored information , 2012, Trends in Cognitive Sciences.

[3]  L.A. Baccald,et al.  Generalized Partial Directed Coherence , 2007, 2007 15th International Conference on Digital Signal Processing.

[4]  M. Husain,et al.  The functional role of the inferior parietal lobe in the dorsal and ventral stream dichotomy , 2009, Neuropsychologia.

[5]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[6]  Yong He,et al.  BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics , 2013, PloS one.

[7]  W. Helton,et al.  Dissociative tendencies and right-hemisphere processing load: Effects on vigilance performance , 2011, Consciousness and Cognition.

[8]  Olaf Sporns,et al.  Network attributes for segregation and integration in the human brain , 2013, Current Opinion in Neurobiology.

[9]  A. Bezerianos,et al.  Functional cortical connectivity analysis of mental fatigue unmasks hemispheric asymmetry and changes in small-world networks , 2014, Brain and Cognition.

[10]  Richard F. Betzel,et al.  Modular Brain Networks. , 2016, Annual review of psychology.

[11]  Indu P. Bodala,et al.  Measuring vigilance decrement using computer vision assisted eye tracking in dynamic naturalistic environments , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[12]  John Duncan,et al.  The role of the right inferior frontal gyrus: inhibition and attentional control , 2010, NeuroImage.

[13]  M. Bar,et al.  The role of the parahippocampal cortex in cognition , 2013, Trends in Cognitive Sciences.

[14]  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.

[15]  Yu Chen,et al.  The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study , 2017, NeuroImage.

[16]  Ioannis Tarnanas,et al.  Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs) , 2017, Front. Neuroinform..

[17]  Danielle S. Bassett,et al.  Multi-scale brain networks , 2016, NeuroImage.

[18]  Santo Fortunato,et al.  Consensus clustering in complex networks , 2012, Scientific Reports.

[19]  Maxym Myroshnychenko,et al.  Rich-Club Organization in Effective Connectivity among Cortical Neurons , 2016, The Journal of Neuroscience.

[20]  Min Zhao,et al.  The Reorganization of Human Brain Networks Modulated by Driving Mental Fatigue , 2017, IEEE Journal of Biomedical and Health Informatics.

[21]  Yu Sun,et al.  Fronto‐Parietal Subnetworks Flexibility Compensates For Cognitive Decline Due To Mental Fatigue , 2018, Human brain mapping.

[22]  Roberto D. Pascual-Marqui,et al.  Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization , 2007, 0710.3341.