Connectivity analysis of novelty process in habitual short sleepers

Babajani‐Feremi, Abbas; Gumenyuk, Valentina; Roth, Thomas; Drake, Christopher L.; Soltanian-Zadeh, Hamid

doi:10.1016/j.neuroimage.2012.08.011

Cited by 4 publications

(1 citation statement)

References 64 publications

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“…Previous studies involving sleep deprivation have demonstrated that sleep loss affects the cognitive functions that rely on frontal lobe activity. 31,[51][52][53][54][55][56][57][58][59] Neurophysiologically, the frontal lobe has been shown to be an essential region in the generation of activity underlying the distraction potential. [60][61][62] Therefore, application of an auditory-distraction task in neurophysiological studies of night workers may add to the literature by providing evidence for normal and abnormal variation in frontal lobe activity in night workers.…”

Section: Discussionmentioning

confidence: 99%

Sleep Loss, Circadian Mismatch, and Abnormalities in Reorienting of Attention in Night Workers with Shift Work Disorder

Gumenyuk

Howard

Roth

et al. 2014

Sleep

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Section: Discussionmentioning

confidence: 99%

Sleep Loss, Circadian Mismatch, and Abnormalities in Reorienting of Attention in Night Workers with Shift Work Disorder

Gumenyuk

Howard

Roth

et al. 2014

Sleep

Self Cite

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Dynamic Causal Modeling (DCM) for EEG Approach to Neuroergonomics

Huang

Nam

2020

Neuroergonomics

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DCM, Conductance Based Models and Clinical Applications

Marreiros

Pinotsis

Brown

et al. 2015

Validating Neuro-Computational Models of Neurological and Psychiatric Disorders

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This chapter reviews some recent advances in dynamic causal modelling (DCM) of electrophysiology, in particular with respect to conductance based models and clinical applications. DCM addresses observed responses of complex neuronal systems by looking at the neuronal interactions that generate them and how these responses reflect the underlying neurobiology. DCM is a technique for inferring the biophysical properties of cortical sources and their directed connectivity based on distinct neuronal and observation models. The DCM framework uses mathematical formalisms of neural masses, neural fields and mean-fields as forward or generative models for observed neuronal activity. We here consider conductance based neural mass, mean-field and field models—and review their latest technical developments. We use dynamically rich conductance based models to generate responses in laminar-specific populations of excitatory and inhibitory cells. These models allow for the evaluation of neuronal connections and high-order statistics of neuronal states, using Bayesian estimation and inference. We also discuss recent clinical applications of DCM for convolution based neural mass models, in particular for the study of Parkinson’s disease. We present a study of data from Parkinsonian patients, and model the large-scale network changes underlying the pathological excess of beta oscillations that characterise the Parkinsonian state

show abstract

Connectivity analysis of novelty process in habitual short sleepers

Cited by 4 publications

References 64 publications

Sleep Loss, Circadian Mismatch, and Abnormalities in Reorienting of Attention in Night Workers with Shift Work Disorder

Sleep Loss, Circadian Mismatch, and Abnormalities in Reorienting of Attention in Night Workers with Shift Work Disorder

Dynamic Causal Modeling (DCM) for EEG Approach to Neuroergonomics

DCM, Conductance Based Models and Clinical Applications

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