Emotion Detection using EEG Signals in Image and Video Processing: A Survey DOI Creative Commons

Poorani Nivetha .R -,

DR.S.Batmavady -

International Journal For Multidisciplinary Research, Год журнала: 2024, Номер 6(4)

Опубликована: Авг. 31, 2024

Brain serves as the body's processing of knowledge and management centre. The central nervous system directly produces ElectroEncephaloGram (EEG) physiological signals, which are strongly associated with human emotions. In upcoming years, there will be an increase in interest for identifying emotion using brain waves by EEG (ElectroEncephaloGraphy) signals. It takes efficient effective signal feature extraction techniques detection emotions from biological Current approaches gather valuable information a fixed number ElectroEncephaloGraphy channels utilizing variety methodologies. This work analyses different difficulties problems signals identification provides comprehensive summary several contemporary approaches. Pre-processing, extraction, categorization first steps process recognizing main goal this survey is to sought enhance signal-based ability comparing all novel adaptive channel selection technique that recognize distinct changes activities varies between individuals emotional states.

Язык: Английский

Stimulation Parameters Recruit Distinct Cortico-Cortical Pathways: Insights from Microstate Analysis on TMS-Evoked Potentials DOI Creative Commons
Delia Lucarelli, Giacomo Guidali, Dominika Šulcová

и другие.

Brain Topography, Год журнала: 2025, Номер 38(3)

Опубликована: Март 28, 2025

Abstract Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) represent an innovative measure for examining brain connectivity and developing biomarkers of psychiatric conditions. Minimizing TEP variability across studies participants, which may stem from methodological choices, is therefore vital. By combining classic peak analysis microstate investigation, we tested how TMS pulse waveform current direction affect cortico-cortical circuit engagement when targeting the primary motor cortex (M1). We aim to disentangle whether changing these parameters affects degree activation same neural circuitry or lead changes in pathways through induced spreads. Thirty-two healthy participants underwent a TMS-EEG experiment (monophasic, biphasic) (posterior-anterior, anterior-posterior, latero-medial) were manipulated. assessed latency amplitude M1-TEP components employed analyses test differences topographies. Results revealed that strongly influenced components’ but had weaker role over their latencies. Microstate showed monophasic stimulations changed pattern evoked microstates at early latencies, as well duration global field power. This study shows pulses modulate cortical sources contributing signals, activating populations paths more selectively. Biphasic reduces associated with be better suited blind anatomical information.

Язык: Английский

Процитировано

1
Current State of EEG/ERP Microstate Research DOI Creative Commons
Christoph M. Michel, Lucie Bréchet, Bastian Schiller

и другие.

Brain Topography, Год журнала: 2024, Номер 37(2), С. 169 - 180

Опубликована: Фев. 13, 2024

The analysis of EEG microstates for investigating rapid whole-brain network dynamics during rest and tasks has become a standard practice in the research community, leading to substantial increase publications across various affective, cognitive, social clinical neuroscience domains. Recognizing growing significance this analytical method, authors aim provide microstate community with comprehensive discussion on methodological standards, unresolved questions, functional relevance microstates. In August 2022, conference was hosted Bern, Switzerland, which brought together many researchers from 19 countries. During conference, gave scientific presentations engaged roundtable discussions aiming at establishing steps toward standardizing methods. Encouraged by conference's success, special issue launched Brain Topography compile current state-of-the-art research, encompassing advancements, experimental findings, applications. call submissions garnered 48 contributions worldwide, spanning reviews, meta-analyses, tutorials, studies. Following rigorous peer-review process, 33 papers were accepted whose findings we will comprehensively discuss Editorial.

Язык: Английский

Процитировано

9
Infant EEG microstate dynamics relate to fine-grained patterns of infant attention during naturalistic play with caregivers DOI Creative Commons
Armen Bagdasarov,

Sarah Markert,

Michael S. Gaffrey

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(11)

Опубликована: Март 13, 2025

As infants grow, they develop greater attentional control during interactions with others, shifting from patterns of attention primarily driven by caregivers (exogenous) to those that are also self-directed (endogenous). The ability endogenously infancy is thought reflect ongoing brain development and influenced joint between infant caregiver. However, whether measures caregiver behavior infant–caregiver relate activity unknown key for informing developmental models control. Using data 43 dyads, we quantified visual dyadic, head-mounted eye tracking play associated them the duration EEG microstate D/4 measured rest. Importantly, a scalp potential topography organization function attention-related networks. We found positively infant-led rate but did not associate caregiver-led rate, suggesting coordination may be critical neurobiological control, or vice versa. Further, negatively shift sustained duration, increased stability maturation its underlying neural substrates. Together, our findings provide insights into how abilities spatial temporal dynamics activity.

Язык: Английский

Процитировано

0
Early Audiovisual Integration in Target Processing Under Continuous Noise: Behavioral and EEG Evidence DOI
Junjie Wang,

Mingkun Guo,

Jie Zhang

и другие.

Neuropsychologia, Год журнала: 2025, Номер unknown, С. 109128 - 109128

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Self-related thought alterations associated with intrinsic brain dysfunction in mild cognitive impairment DOI Creative Commons
Povilas Tarailis,

Kim Lory,

Paul G. Unschuld

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 10, 2025

Abstract The subjective experience of self-awareness is attributed to the human capacity for introspective thought during periods mind-wandering. However, how this cognitive function impacted in individuals with mild impairment (MCI) still needs be better understood. To address gap, we investigated alterations self-referential thinking a cohort 30 MCI patients, comparing them 60 healthy old-aged and younger controls. patients exhibited notable decline overall function, as evidenced by significantly lower scores on Montreal Cognitive Assessment (MoCA), particular deficits Memory subscore Index Score (MIS). Employing Amsterdam Resting-State Questionnaire (ARSQ) assess mind-wandering, observed diminished self-related thoughts relating personal past experiences future among patients. Notably, using high-density electroencephalography (hdEEG) microstate analysis, detected reduced neural activity C associated older relative controls, an increase A compared This aberrant temporal was localized within brain regions implicated episodic autobiographical memory default mode network. Our results highlight link between impaired mind-wandering ability dysfunction intrinsic networks underscoring its implications disruptions sense self clinical population.

Язык: Английский

Процитировано

0
Emotion Detection using EEG Signals in Image and Video Processing: A Survey DOI Creative Commons

Poorani Nivetha .R -,

DR.S.Batmavady -

International Journal For Multidisciplinary Research, Год журнала: 2024, Номер 6(4)

Опубликована: Авг. 31, 2024

Brain serves as the body's processing of knowledge and management centre. The central nervous system directly produces ElectroEncephaloGram (EEG) physiological signals, which are strongly associated with human emotions. In upcoming years, there will be an increase in interest for identifying emotion using brain waves by EEG (ElectroEncephaloGraphy) signals. It takes efficient effective signal feature extraction techniques detection emotions from biological Current approaches gather valuable information a fixed number ElectroEncephaloGraphy channels utilizing variety methodologies. This work analyses different difficulties problems signals identification provides comprehensive summary several contemporary approaches. Pre-processing, extraction, categorization first steps process recognizing main goal this survey is to sought enhance signal-based ability comparing all novel adaptive channel selection technique that recognize distinct changes activities varies between individuals emotional states.

Язык: Английский

Процитировано

0