EEG Alpha Asymmetry, Depression, and Cognitive Functioning

Gotlib, Ian H.; Ranganath, Charan; Rosenfeld, J. Peter

doi:10.1080/026999398379673

Cited by 389 publications

(294 citation statements)

References 47 publications

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“…This stage is associated to initial periods of learning where subjects divide the attention focus with differentiated elements of the task and the environment 2 , leading to reduced motor coordination, increased number of mistakes and execution time. As observed in the results, such increase in symmetry suggests changes in the representation of neuronal activity at the prefrontal cortex, as noticed by other investigations 18,20 . The prefrontal cortex integrates with the limbic associative cortex, connecting directly to limbic structures as the amigdala and the cingulate cortex.…”

Section: Discussionsupporting

confidence: 75%

Motor learning processes: an electrophysiologic perspective

Velasques

Ferreira

Teixeira

et al. 2007

Arq. Neuro-Psiquiatr.

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-The goal of the present study was to investigate electrophysiologic, qEEG, changes when individuals were exposed to a motor task. Subjects' brain electrical activity was analyzed before and after the typewriting training task. For the neurophysiological variable asymmetry, a paired t-test was performed to compare each moment, pre and post-task, in the beta bands. The findings showed a change for the qEEG variable in each scalp site, F3/F4; C3/C4 and P3/P4. These results suggest an adaptation of pre-frontal, sensory-motor and parietal cortex, as a consequence of the typewriting training.KEY WORDS: sensory-motor integration, procedural learning, qEEG. Processos de aprendizagem motora: uma perspectiva eletrofisiológicaRESUMO -O objetivo do presente estudo foi investigar mudanças eletrofisiológicas através do EEGq quando indivíduos são expostos a uma tarefa motora. A atividade elétrica no córtex dos sujeitos foi analisada antes e após o treinamento da tarefa motora. Para a variável neurofisiológica assimetria, um teste t foi implementado para comparar cada momento, pré e pós-tarefa, na banda beta. Os achados demonstraram mudança em assimetria para as seguintes regiões no escalpo: F3/F4, C3/C4 e P3/P4. Estes resultados sugerem uma adaptação das regiões pré-frontal, somatosensorial e parietal como conseqüência do treinamento de datilografia. PALAVRAS-CHAVE: integração sensório-motora, memória de procedimento, EEGq. Velasques -Rua Paula Brito 350 / 1102 -20541-190 Rio de Janeiro RJ -Brasil. E-mail: bruna_velasques@yahoo.com.br To maintain stability at a highly dynamic environment, the central nervous system (CNS) is in constant activity. It continuously receives external sensory stimuli, many specifi cally required to maintain motor performance [1][2][3] . Many studies have demonstrated that precision during the motor gesture is increased as consequence of motor learning 4,5 . Motor learning promotes a gradual minimization of task errors, an increase in coordination, agility and movement execution 6 . Dra. Bruna BrandãoDifferent mechanisms take part in the complexity of motor learning which involves various levels of cortical structures, such as: pre frontal areas related to decision making, contralateral primary motor cortex 7 , ipsilateral primary motor cortex, supplementary motor area, pre motor area, primary sensory areas 8 , and the parietal region responsible for information integration processes. The different functional components and the plastic reorganization of the CNS have lead to investigations objecting the examination of neurofunctional phenomena involving motor learning 9 .Hence, this study aimed at investigating how participative is the learning of a motor task in the cortex organizational mapping. For that, we used quantitative electroencephalography (qEEG) to detect neural changes during the motor learning process 10 . Beta activity was specifi cally investigated, since it is responsive to movements and electro-stimulation of limbs 11,12 .

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Section: Discussionsupporting

confidence: 75%

Motor learning processes: an electrophysiologic perspective

Velasques

Ferreira

Teixeira

et al. 2007

Arq. Neuro-Psiquiatr.

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“…First, the time waves of EEG data were pre-processed using thresholding method to remove movement artifacts (such as eye movement/blinking), in which data that are found to have amplitudes of more than 80 µV are discarded from the study (Gotlib et al, 1998). Second, a 6 th order bandpass Butterworth filter (with forward reverse filtering algorithm) was used to extract the frequency range of 1-49 Hz.…”

Section: Signal Preprocessingmentioning

confidence: 99%

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

Yuvaraj

Murugappan

Ibrahim

et al. 2014

International Journal of Psychophysiology

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In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded as electroencephalograph (EEG) to discover the links between emotional states and brain activity.This study utilized machine-learning algorithms to categorize emotional states in PD patients compared with healthy controls (HC) using EEG. Twenty non-demented PD patients and 20 healthy age-, gender-, and education level-matched controls viewed happiness, sadness, fear, anger, surprise, and disgust emotional stimuli while fourteen-channel EEG was being recorded.Multi-modal stimulus (combination of audio and visual) was used to evoke the emotions. To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach to track the trajectory of emotion changes with manifold learning. From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis; (b) higher frequency bands (alpha, beta and gamma) play a more important role in emotion activities than lower frequency bands (delta and theta) in both the groups and; (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning. This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders.

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“…Second, studies measuring resting brain electrical activity have reported that depression is characterized by relatively reduced activity over left prefrontal regions (e.g., Gotlib et al, 1998;Henriques and Davidson, 1991;Thibodeau et al, 2006) that are assumed to play an important role in approach-related affect (Davidson, 1998). Interestingly, resting activity within left prefrontal regions has been linked to individuals' propensity to respond to rewardrelated cues , providing convergent evidence that depressed subjects might display reduced hedonic capacity.…”

Section: Introductionmentioning

confidence: 99%

Reduced hedonic capacity in major depressive disorder: Evidence from a probabilistic reward task

Pizzagalli

Iosifescu

Hallett

et al. 2008

Journal of Psychiatric Research

628

659

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Objective-Anhedonia, the lack of reactivity to pleasurable stimuli, is a cardinal feature of depression that has received renewed interest as a potential endophenotype of this debilitating disease. The goal of the present study was to test the hypothesis that individuals with major depression are characterized by blunted reward responsiveness, particularly when anhedonic symptoms are prominent.Methods-A probabilistic reward task rooted within signal-detection theory was utilized to objectively assess hedonic capacity in 23 unmedicated subjects meeting DSM-IV criteria for major depressive disorder (MDD) and 25 matched control subjects recruited from the community. Hedonic capacity was defined as reward responsiveness -i.e., the participants' propensity to modulate behavior as a function of reward.Results-Compared to controls, MDD subjects showed significantly reduced reward responsiveness. Trial-by-trial probability analyses revealed that MDD subjects, while responsive to delivery of single rewards, were impaired at integrating reinforcement history over time and expressing a response bias toward a more frequently rewarded cue in the absence of immediate reward. This selective impairment correlated with self-reported anhedonic symptoms, even after considering anxiety symptoms and general distress.Conclusions-These findings indicate that MDD is characterized by an impaired tendency to modulate behavior as a function of prior reinforcements, and provides initial clues about which aspects of hedonic processing might be dysfunctional in depression.

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EEG Alpha Asymmetry, Depression, and Cognitive Functioning

Cited by 389 publications

References 47 publications

Motor learning processes: an electrophysiologic perspective

Motor learning processes: an electrophysiologic perspective

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

Reduced hedonic capacity in major depressive disorder: Evidence from a probabilistic reward task

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