scholarly journals Human personality reflects spatio-temporal and time-frequency EEG structure

2018 ◽  
Author(s):  
Anastasia E. Runnova ◽  
Vladimir A. Maksimenko ◽  
Maksim O. Zhuravlev ◽  
Pavel Protasov ◽  
Roman Kulanin ◽  
...  
Keyword(s):  
Brain Activity ◽  
Human Action ◽  
Personality Factor ◽  
Human Personality ◽  
Time Frequency ◽  
Electrical Brain Activity ◽  
Oscillatory Pattern ◽  
Neuronal Network Dynamics ◽  
Spatio Temporal ◽  
The Brain

AbstractThe brain controls all physiological processes in the organism and regulates its interaction with the external environment. The way the brain solves mental tasks is determined by individual human features, which are reflected in neuronal network dynamics, and therefore can be detected in neurophysiological data. Every human action is associated with a unique brain activity (motor-related, cognitive, etc.) represented by a specific oscillatory pattern in a multichannel electroencephalogram (EEG). The connection between neurophysiological processes and personal mental characteristics is manifested when using simple psycho-diagnostic tests (Schulte tables) in order to study the attention span. The analysis of spatio-temporal and time-frequency structures of the multichannel EEG using the Schulte tables allows us to divide subjects into three groups depending on their neural activity. The personality multi-factor profile of every participant can be individually described based on both the Sixteen Personality Factor Questionnaire (16PF) and a personal interview with an experienced psychologist. The correlation of the EEG-based personality classification with individual multi-factor profiles provides a possibility to identify human personality by analyzing electrical brain activity. The obtained results are of great interest for testing human personality and creating automatized intelligent programs that employ simple tests and EEG measurements for an objective estimation of human personality features.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

Neural Dynamics of Context-Sensitive Adjustments in Cognitive Flexibility

2022 ◽  
pp. 1-13
Author(s):  
Audrey Siqi-Liu ◽  
Tobias Egner ◽  
Marty G. Woldorff
Keyword(s):  
Cognitive Flexibility ◽  
Switch Cost ◽  
Brain Activity ◽  
Alpha Power ◽  
Time Frequency ◽  
Context Sensitive ◽  
Electrical Brain Activity ◽  
Strong Focus ◽  
Current Task ◽  
Neural Underpinnings

Abstract To adaptively interact with the uncertainties of daily life, we must match our level of cognitive flexibility to contextual demands—being more flexible when frequent shifting between different tasks is required and more stable when the current task requires a strong focus of attention. Such cognitive flexibility adjustments in response to changing contextual demands have been observed in cued task-switching paradigms, where the performance cost incurred by switching versus repeating tasks (switch cost) scales inversely with the proportion of switches (PS) within a block of trials. However, the neural underpinnings of these adjustments in cognitive flexibility are not well understood. Here, we recorded 64-channel EEG measures of electrical brain activity as participants switched between letter and digit categorization tasks in varying PS contexts, from which we extracted ERPs elicited by the task cue and alpha power differences during the cue-to-target interval and the resting precue period. The temporal resolution of the EEG allowed us to test whether contextual adjustments in cognitive flexibility are mediated by tonic changes in processing mode or by changes in phasic, task cue-triggered processes. We observed reliable modulation of behavioral switch cost by PS context that was mirrored in both cue-evoked ERP and time–frequency effects but not by blockwide precue EEG changes. These results indicate that different levels of cognitive flexibility are instantiated after the presentation of task cues, rather than by being maintained as a tonic state throughout low- or high-switch contexts.

Is Artistic Composition in Abstract Art Detected Automatically?

2021 ◽  
pp. 102-106
Author(s):  
Claudia Menzel ◽  
Gyula Kovács ◽  
Gregor U. Hayn-Leichsenring ◽  
Christoph Redies
Keyword(s):  
Human Brain ◽  
Significant Role ◽  
Mismatch Negativity ◽  
Brain Activity ◽  
Perceptual Processing ◽  
Abstract Art ◽  
Electrical Brain Activity ◽  
Image Set ◽  
The Brain

Most artists who create abstract paintings place the pictorial elements not at random, but arrange them intentionally in a specific artistic composition. This arrangement results in a pattern of image properties that differs from image versions in which the same pictorial elements are randomly shuffled. In the article under discussion, the original abstract paintings of the author’s image set were rated as more ordered and harmonious but less interesting than their shuffled counterparts. The authors tested whether the human brain distinguishes between these original and shuffled images by recording electrical brain activity in a particular paradigm that evokes a so-called visual mismatch negativity. The results revealed that the brain detects the differences between the two types of images fast and automatically. These findings are in line with models that postulate a significant role of early (low-level) perceptual processing of formal image properties in aesthetic evaluations.

scholarly journals Neuronal avalanches and time-frequency representations in stimulus-evoked activity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Oshrit Arviv ◽  
Abraham Goldstein ◽  
Oren Shriki
Keyword(s):  
Brain Activity ◽  
Branching Processes ◽  
Temporal Scale ◽  
Current Debate ◽  
Scale Invariant ◽  
Time Frequency ◽  
Evoked Activity ◽  
Neuronal Avalanche ◽  
Neuronal Avalanches ◽  
The Brain

Abstract Neuronal avalanches are a hallmark feature of critical dynamics in the brain. While the theoretical framework of a critical branching processes is generally accepted for describing avalanches during ongoing brain activity, there is a current debate about the corresponding dynamical description during stimulus-evoked activity. As the brain activity evoked by external stimuli considerably varies in magnitude across time, it is not clear whether the parameters that govern the neuronal avalanche analysis (a threshold or a temporal scale) should be adaptively altered to accommodate these changes. Here, the relationship between neuronal avalanches and time-frequency representations of stimulus-evoked activity is explored. We show that neuronal avalanche metrics, calculated under a fixed threshold and temporal scale, reflect genuine changes in the underlying dynamics. In particular, event-related synchronization and de-synchronization are shown to align with variations in the power-law exponents of avalanche size distributions and the branching parameter (neural gain), as well as in the spatio-temporal spreading of avalanches. Nonetheless, the scale-invariant behavior associated with avalanches is shown to be a robust feature of healthy brain dynamics, preserved across various periods of stimulus-evoked activity and frequency bands. Taken together, the combined results suggest that throughout stimulus-evoked responses the operating point of the dynamics may drift within an extended-critical-like region.

Auditory modulation of oscillatory activity in extra-striate visual cortex and its contribution to audio–visual multisensory integration: A human intracranial EEG study

2012 ◽  
Vol 25 (0) ◽  
pp. 198
Author(s):  
Manuel R. Mercier ◽  
John J. Foxe ◽  
Ian C. Fiebelkorn ◽  
John S. Butler ◽  
Theodore H. Schwartz ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Multisensory Integration ◽  
Multisensory Processing ◽  
Brain Activity ◽  
Visual Stimuli ◽  
Additive Model ◽  
Oscillatory Activity ◽  
Time Frequency ◽  
Electrical Brain Activity ◽  
Sensory Cortices

Investigations have traditionally focused on activity in the sensory cortices as a function of their respective sensory inputs. However, converging evidence from multisensory research has shown that neural activity in a given sensory region can be modulated by stimulation of other so-called ancillary sensory systems. Both electrophysiology and functional imaging support the occurrence of multisensory processing in human sensory cortex based on the latency of multisensory effects and their precise anatomical localization. Still, due to inherent methodological limitations, direct evidence of the precise mechanisms by which multisensory integration occurs within human sensory cortices is lacking. Using intracranial recordings in epileptic patients () undergoing presurgical evaluation, we investigated the neurophysiological basis of multisensory integration in visual cortex. Subdural electrical brain activity was recorded while patients performed a simple detection task of randomly ordered Auditory alone (A), Visual alone (V) and Audio–Visual stimuli (AV). We then performed time-frequency analysis: first we investigated each condition separately to evaluate responses compared to baseline, then we indexed multisensory integration using both the maximum criterion model (AV vs. V) and the additive model (AV vs. A+V). Our results show that auditory input significantly modulates neuronal activity in visual cortex by resetting the phase of ongoing oscillatory activity. This in turn leads to multisensory integration when auditory and visual stimuli are simultaneously presented.

Statistical Evaluation of Polygraphic Investigations of Pentoxifylline

1976 ◽  
Vol 4 (4) ◽  
pp. 211-222 ◽  
Author(s):  
U J Jovanović
Keyword(s):  
Blood Pressure ◽  
Beneficial Effect ◽  
Statistical Evaluation ◽  
Brain Activity ◽  
Metabolic Effects ◽  
Electrical Brain Activity ◽  
Wave Patterns ◽  
The Brain ◽  
Electrical Skin ◽  
Stimulation Of

Changes in the electro-encephalogram, and in the electro-oculogram electromyogram, ECG, blood supply, blood pressure, electrical skin activity and neurological/psychiatric findings, were investigated in 100 patients given single administrations of 200 mg of pentoxifylline (BL 191). It is concluded from the changes in the EEG wave patterns that pentoxifylline produces a beneficial effect on the cerebral processes contributing to bio-electrical brain activity. Pentoxifylline can be classed as a substance with microcirculatory/metabolic effects on the brain, which lead to stimulation of psychomotor behaviour.

Induced Theta Activity as a Biomarker for a Morbid Effect of Alcoholism on the Brain in Long-Term Abstinent Alcoholics

2013 ◽  
Vol 27 (2) ◽  
pp. 76-83 ◽  
Author(s):  
Casey S. Gilmore ◽  
George Fein
Keyword(s):  
Brain Function ◽  
Target Stimulus ◽  
Brain Activity ◽  
Theta Activity ◽  
Theta Oscillations ◽  
Time Frequency ◽  
Related Information ◽  
The Relationship ◽  
The Brain

Event-related, target stimulus-phase-locked (evoked) brain activity in both the time and time-frequency (TF) domains (the P3b ERP; evoked theta oscillations) has been shown to be reduced in alcoholics. Recently, studies have suggested that there is alcohol-related information in the non-stimulus-phase-locked (induced) theta TF activity. We applied TF analysis to target stimulus event-related EEG recorded during an oddball task from 41 long-term abstinent alcoholics (LTAA) and 74 nonalcoholic controls (NAC) to investigate the relationship between P3b, evoked theta, and induced theta activity. Results showed that an event-related synchronization (ERS) of induced theta (1) was larger in LTAA compared to NAC, and (2) was sensitive to differences between LTAA and NAC groups that was independent of the differences accounted for by P3b amplitude or evoked theta. These findings suggest that increased induced theta ERS may likely be a biomarker for a morbid effect of alcohol abuse on brain function.

Spatio-temporal properties of the brain activity during visual infrequent target detection: a neuromagnetic study

NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 895
Author(s):  
Sunao Iwaki ◽  
Naoya Hirata ◽  
Mitsuo Tonoike ◽  
Masahiko Yamaguchi ◽  
Isao Kaetsu
Keyword(s):  
Target Detection ◽  
Brain Activity ◽  
Temporal Properties ◽  
Spatio Temporal ◽  
The Brain

Non-Linear Mechanisms in the Brain

1998 ◽  
Vol 53 (7-8) ◽  
pp. 677-685 ◽  
Author(s):  
Gottfried Mayer-Kress
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
External Noise ◽  
Neuronal System ◽  
Neuron Models ◽  
General Role ◽  
Non Linear ◽  
Spatio Temporal ◽  
The Brain

Abstract Non-linear dynamical models of brain activity can describe the spontaneous emergence of large-scale coherent structures both in a temporal and spatial domain. We discuss a number of discrete time dynamical neuron models that illustrate some of the mechanisms involved. Of special interest is the phenomenon of spatio-temporal stochastic resonance in which co­herent structures emerge as a result of the interaction of the neuronal system with external noise at a given level punitive data. We then discuss the general role of stochastic noise in brain dynamics and how similar concepts can be studied in the context of networks of con­nected brains on the Internet.

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