scholarly journals Decoding Personality Trait Measures from Resting EEG: An Exploratory Report

2019 ◽  
Author(s):  
Hayley Jach ◽  
Daniel Feuerriegel ◽  
Luke Smillie
Keyword(s):  
Big Five ◽  
Personality Trait ◽  
Spectral Power ◽  
Power Spectra ◽  
Task Completion ◽  
Support Vector ◽  
Alpha Power ◽  
Emotional States ◽  
Exploratory Research ◽  
Beta Power

Can personality be predicted from oscillatory patterns produced by the brain at rest? To date, relatively few electroencephalographic (EEG) studies have yielded consistent relations between personality trait measures and spectral power, suggesting that new exploratory research may help develop targeted hypotheses about how neural processes associated with EEG activity may relate to personality differences. We used multivariate pattern analysis to decode personality scores (i.e., Big Five traits) from resting EEG frequency power spectra. Up to 8 minutes of EEG data was recorded per participant prior to completing an unrelated task (N = 168, Mage = 23.51, 57% female) and, in a subset of participants, after task completion (N = 96, Mage = 23.22, 52% female), measuring the resting state with open and closed eyes. Linear support vector regression with 10-fold cross validation was performed using the power from 62 scalp electrodes within 1 Hz frequency bins from 1-30 Hz. One Big Five trait, agreeableness, could be decoded from EEG power ranging from 8-19 Hz, and this was consistent across all four recording periods. Neuroticism was decodable using data within the 3-6 Hz range, albeit less consistently. Posterior alpha power negatively correlated with agreeableness, whereas parietal beta power positively correlated with agreeableness. We suggest methods to draw from our results and develop targeted future hypotheses, such as linking to individual alpha frequency and incorporating self-reported emotional states. Our open dataset can be harnessed to reproduce results or investigate new research questions concerning the biological basis of personality.

scholarly journals Elevations in EEG Power Spectra During the Recall of Sport Failure Amongst University Athletes

2020 ◽  
Author(s):  
Laura Ceccarelli ◽  
Ryan Jeffrey Giuliano
Keyword(s):  
Acute Stress ◽  
Power Spectra ◽  
Self Esteem ◽  
Recall Task ◽  
Alpha Power ◽  
Self Compassion ◽  
Beta Power ◽  
Eeg Power ◽  
High Beta ◽  
University Athletes

Previously, we showed that university athletes demonstrate cardiac reactivity resembling an acute stress response while recalling a previous sport failure. Athletes who reported higher levels of self- compassion showed greater elevation of parasympathetic nervous system reactivity during recall of failure, and also showed more adaptive behavioural reactions, less maladaptive thoughts, and less negative affect during the task. Here, we analyzed changes in power spectra of the electroencephalogram (EEG) before, during, and after the recall of a previous sports failure, and whether individual differences in self-compassion or related constructs impact EEG changes during recall. Significant reactivity to, and recovery from, the recall task was observed across all EEG bandwidths: delta power decreased, and theta, low alpha, high alpha, low beta, and high beta power all increased from baseline to recall. Analogous EEG power changes were observed during recovery: delta power increased, while theta, low alpha, high alpha, low beta, and high beta power all decreased to baseline levels. Large gender differences were observed, with females generally showing greater EEG power across bandwidths during all phases of the experiment. Higher levels of self-compassion were associated with reduced theta power at baseline and during the recovery phase. Reactivity and recovery scores of EEG power were associated with self-reported self-esteem in the low alpha band: individuals reporting higher self-esteem showed greater increases in low alpha power during the recall task and greater decreases in low alpha power during recovery. These results are amongst the first to examine EEG power changes during experiences of acute stress and may have implications for improving how athletes recover from failures in sporting events.

Eeg Spectral Analysis in Schizophrenia

1980 ◽  
Vol 136 (5) ◽  
pp. 445-455 ◽  
Author(s):  
G. W. Fenton ◽  
P. B. C. Fenwick ◽  
J. Dollimore ◽  
T. L. Dunn ◽  
S. R. Hirsch
Keyword(s):  
Power Spectra ◽  
Alpha Power ◽  
Eeg Spectral Analysis ◽  
Eyes Closed ◽  
Beta Power ◽  
Eyes Open ◽  
Schizophrenic Patients ◽  
Patient Groups ◽  
Schizophrenic Group ◽  
Normal Controls

SummaryFour channels of EEG (T4-T6, P4-02, T3-T5, P3-01) were recorded from several groups of control subjects and schizophrenia patients on analogue tape. They were later digitized and analysed by computer; power spectra were computed for 30 second epochs of EEG per channel; eyes closed, eyes open. No difference between normal controls and neurotic in-patients was apparent. An acute schizophrenic group had less alpha power, this change being confined largely to the temporal areas. A chronic outpatient sample showed less alpha and beta power, while chronic long-stay schizophrenic patients had an excess of delta power. The changes in both chronic patient groups were diffuse rather than local.

scholarly journals Detection of electroencephalographic, electromyographic, and cardiac variations during wake-sleep transition through change point analysis

Salud Mental ◽  
2018 ◽  
Vol 41 (1) ◽  
pp. 17-23
Author(s):  
Erik Leonardo Mateos-Salgado ◽  
◽  
Fructuoso Ayala-Guerrero
Keyword(s):  
Change Point ◽  
Repeated Measures ◽  
Spectral Power ◽  
Change Point Analysis ◽  
Alpha Power ◽  
Sinus Arrhythmia ◽  
Repeated Measures Anova ◽  
Point Analysis ◽  
Beta Power ◽  
Sleep Transition

Introduction. Wake-sleep transition is a continuous, gradual process of change. Most studies evaluating electroencephalogram spectral power during this transition have used variance analysis (ANOVA). However, using this type of analysis does not allow one to detect specific changes in the statistical properties of a time series. Objective. To determine whether change point analysis (CPA) makes it possible to identify and characterize electroencephalographic, electromyographic, and cardiac changes during the wake-sleep transition through a cross-sectional study. Method. The study included 18 healthy volunteers (12 women and six men), from which polysomnography data were obtained during a two-minute transition. Heart rate, respiratory sinus arrhythmia, electroencephalogram spectral power, as well as electromyographic median and mean frequency and electromyographic root mean square were calculated in five-second segments. These segments were analyzed using repeated measures ANOVA, and CPA focused individually and for the group as a whole. Results. Repeated measures ANOVA and CPA by group found decreased levels of alpha and beta power and beta/delta index during wakefulness, and increased theta and delta power levels during sleep. CPA by individual found that only alpha power changed in all participants and failed to identify a specific moment when all the variables studied changed simultaneously. Discussion and conclusion. We consider that CPA provides additional information to statistical analyses such as ANOVA for the specific location of physiological changes during sleep-wake transition.

Polysomnographic Findings in Nights Preceding a Migraine Attack

Cephalalgia ◽  
2001 ◽  
Vol 21 (1) ◽  
pp. 31-37 ◽  
Author(s):  
R Göder ◽  
G Fritzer ◽  
A Kapsokalyvas ◽  
P Kropp ◽  
U Niederberger ◽  
...  
Keyword(s):  
Slow Wave Sleep ◽  
Power Spectra ◽  
Cortical Activation ◽  
Alpha Power ◽  
Sleep Regulation ◽  
Beta Power ◽  
Rem Density ◽  
Sleep Parameters ◽  
Sleep Alterations ◽  
Electroencephalogram Eeg

Sleep recordings were performed in eight patients to analyse sleep alterations preceding migraine attacks. Polysomnographic recordings from nights before an attack were compared with nights without following migraine. We analysed standard sleep parameters and electroencephalogram (EEG) power spectra. The main findings preceding migraine attacks were a significant decrease in the number of arousals, a decrease in rapid eye movement (REM) density, a significant decrease of beta power in the slow wave sleep, and a decrease of alpha power during the first REM period. The results suggest a decrease in cortical activation during sleep preceding migraine attacks. According to the models of sleep regulation, alterations in the function of aminergic or cholinergic brainstem nuclei have to be discussed.

scholarly journals Characterizing the middle-age neurophysiology using EEG/MEG

2021 ◽  
Author(s):  
Justyna Gula ◽  
Victoria Moiseeva ◽  
Maria Herrojo Ruiz ◽  
Marinella Cappelletti
Keyword(s):  
Resting State ◽  
Middle Age ◽  
Spectral Power ◽  
Structure And Function ◽  
Alpha Power ◽  
Behavioral Measures ◽  
Inflection Points ◽  
Beta Power ◽  
Brain Structure And Function ◽  
And Function

Middle adulthood - the period of life between 40 and 60 years of age - is accompanied by important physical and emotional changes, as well as cognitive and neuronal ones. Nevertheless, middle age is often overlooked in neuroscience under the assumption that this is a time of relative stability, although cognitive decline, as well as changes in brain structure and function are well-established by the age of 60. Here we characterized the middle-aged brain in the context of healthy younger and older adults by assessing resting-state electrophysiological and neuromagnetic activity in two different samples (N = 179, 631). Alpha and beta oscillations - two key ageing signatures - were analyzed in terms of spectral power and burst events. While posterior alpha power and burst rate features changed linearly with age, similarly to behavioral measures, sensorimotor beta power and burst rate properties varied non-linearly, with inflection points during middle age. The findings suggest that ageing is characterized by distinct spatial and temporal brain dynamics, some critically arising in middle age.

scholarly journals Cortical Activity During Postural Recovery in Response to Predictable and Unpredictable Perturbations in Healthy Young and Older Adults: A Quantitative EEG Assessment

2021 ◽  
Vol 12 (2) ◽  
pp. 291-300
Author(s):  
Zahra Saadat ◽  
◽  
Ehsan Sinaei ◽  
Soraya Pirouzi ◽  
Mohsen Ghofrani ◽  
...  
Keyword(s):  
Older Adults ◽  
Spectral Power ◽  
Late Phase ◽  
Cortical Activity ◽  
Cortical Activation ◽  
Alpha Power ◽  
Older Individuals ◽  
External Perturbations ◽  
Beta Power ◽  
Postural Recovery

Introduction: To investigate the effects of predictable and unpredictable external perturbations on cortical activity in healthy young and older adults. Methods: Twenty healthy older and 19 healthy young adults were exposed to predictable and unpredictable external perturbations, and their cortical activity upon postural recovery was measured using a 32-channel quantitative encephalography. The absolute spectral power and coherence z-scores of cortical waves were analyzed through a 3-way mixed ANOVA. Results: During postural recovery from predictable perturbations, older adults exhibited higher frontoparietal beta power and higher alpha and beta coherence during the late-phase recovery than the young individuals. After unpredictable perturbations, the older group showed lower alpha power in the early phase and higher beta power in the late phase as compared to the young group. Results for the group × time and group × location interactions in the older group showed a higher alpha and beta coherence over the late phase, a higher alpha coherence in F3−P3 and F4−P4 regions, and a higher beta coherence in the F4−P4 region compared to the younger group. Conclusion: Our results revealed that the cortical activation after external perturbations increases with aging, particularly in frontoparietal areas. A shift from automatic (subcortical level) to attentional (cortical level) processing may reflect the contribution of attentional resources for postural recovery from an external threat in older individuals.

scholarly journals Common and Distinct Roles of Frontal Midline Theta and Occipital Alpha Oscillations in Coding Temporal Intervals and Spatial Distances

2021 ◽  
pp. 1-17
Author(s):  
Mingli Liang ◽  
Jingyi Zheng ◽  
Eve Isham ◽  
Arne Ekstrom
Keyword(s):  
Power Spectra ◽  
Temporal Coding ◽  
Temporal Information ◽  
Spatial Distance ◽  
Common Mechanism ◽  
Alpha Power ◽  
Long Distance ◽  
Distance Information ◽  
Temporal Duration ◽  
Beta Power

Abstract Judging how far something is and how long it takes to get there is critical to memory and navigation. Yet, the neural codes for spatial and temporal information remain unclear, particularly the involvement of neural oscillations in maintaining such codes. To address these issues, we designed an immersive virtual reality environment containing teleporters that displace participants to a different location after entry. Upon exiting the teleporters, participants made judgments from two given options regarding either the distance they had traveled (spatial distance condition) or the duration they had spent inside the teleporters (temporal duration condition). We wirelessly recorded scalp EEG while participants navigated in the virtual environment by physically walking on an omnidirectional treadmill and traveling through teleporters. An exploratory analysis revealed significantly higher alpha and beta power for short-distance versus long-distance traversals, whereas the contrast also revealed significantly higher frontal midline delta–theta–alpha power and global beta power increases for short versus long temporal duration teleportation. Analyses of occipital alpha instantaneous frequencies revealed their sensitivity for both spatial distances and temporal durations, suggesting a novel and common mechanism for both spatial and temporal coding. We further examined the resolution of distance and temporal coding by classifying discretized distance bins and 250-msec time bins based on multivariate patterns of 2- to 30-Hz power spectra, finding evidence that oscillations code fine-scale time and distance information. Together, these findings support partially independent coding schemes for spatial and temporal information, suggesting that low-frequency oscillations play important roles in coding both space and time.

scholarly journals EEG Measures of Value-Directed Strategic Processing in Older Adults With and Without Mild Cognitive Impairment

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 292-293
Author(s):  
Lydia Nguyen ◽  
Shraddha Shende ◽  
Daniel Llano ◽  
Raksha Mudar
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Aging ◽  
Spectral Power ◽  
Group Differences ◽  
Cognitive Resources ◽  
Alpha Power ◽  
Strategic Processing ◽  
Unique Word

Abstract Value-directed strategic processing is important for daily functioning. It allows selective processing of important information and inhibition of irrelevant information. This ability is relatively preserved in normal cognitive aging, but it is unclear if mild cognitive impairment (MCI) affects strategic processing and its underlying neurophysiological mechanisms. The current study examined behavioral and EEG spectral power differences between 16 cognitively normal older adults (CNOA; mean age: 74.5 ± 4.0 years) and 16 individuals with MCI (mean age: 77.1 ± 4.3 years) linked to a value-directed strategic processing task. The task used five unique word lists where words were assigned high- or low-value based on letter case and were presented sequentially while EEG was recorded. Participants were instructed to recall as many words as possible after each list to maximize their score. Results revealed no group differences in recall of low-value words, but individuals with MCI recalled significantly fewer high-value words and total number of words relative to CNOA. Group differences were observed in theta and alpha bands for low-value words, with greater synchronized theta power for CNOA than MCI and greater desynchronized alpha power for MCI than CNOA. Collectively, these findings demonstrate that more effortful neural processing of low-value words in the MCI group, relative to the CNOA group, allowed them to match their behavioral performance to the CNOA group. Individuals with MCI appear to utilize more cognitive resources to inhibit low-value information and might show memory-related benefits if taught strategies to focus on high-value information processing.

scholarly journals Neurophysiological and behavioural effects of conventional and high definition tDCS

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fabio Masina ◽  
Giorgio Arcara ◽  
Eleonora Galletti ◽  
Isabella Cinque ◽  
Luciano Gamberini ◽  
...  
Keyword(s):  
Response Times ◽  
Power Reduction ◽  
Alpha Power ◽  
High Definition ◽  
Mixed Effect ◽  
State Dependency ◽  
Mixed Effect Models ◽  
Beta Power ◽  
Neurophysiological Data ◽  
Spectrum Density

AbstractHigh-definition transcranial direct current stimulation (HD-tDCS) seems to overcome a drawback of traditional bipolar tDCS: the wide-spread diffusion of the electric field. Nevertheless, most of the differences that characterise the two techniques are based on mathematical simulations and not on real, behavioural and neurophysiological, data. The study aims to compare a widespread tDCS montage (i.e., a Conventional bipolar montage with extracephalic return electrode) and HD-tDCS, investigating differences both at a behavioural level, in terms of dexterity performance, and a neurophysiological level, as modifications of alpha and beta power as measured with EEG. Thirty participants took part in three sessions, one for each montage: Conventional tDCS, HD-tDCS, and sham. In all the conditions, the anode was placed over C4, while the cathode/s placed according to the montage. At baseline, during, and after each stimulation condition, dexterity was assessed with a Finger Tapping Task. In addition, resting-state EEG was recorded at baseline and after the stimulation. Power spectrum density was calculated, selecting two frequency bands: alpha (8–12 Hz) and beta (18–22 Hz). Linear mixed effect models (LMMs) were used to analyse the modulation induced by tDCS. To evaluate differences among the montages and consider state-dependency phenomenon, the post-stimulation measurements were covariate-adjusted for baseline levels. We observed that HD-tDCS induced an alpha power reduction in participants with lower alpha at baseline. Conversely, Conventional tDCS induced a beta power reduction in participants with higher beta at baseline. Furthermore, data showed a trend towards a behavioural effect of HD-tDCS in participants with lower beta at baseline showing faster response times. Conventional and HD-tDCS distinctively modulated cortical activity. The study highlights the importance of considering state-dependency to determine the effects of tDCS on individuals.

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