EEG affective modelling for dysphoria understanding

Dysphoria is a state of dissatisfaction, restlessness or fidgeting. It is a state of feeling unwell in relation to mental and emotional discomfort. If this state is not carefully handled, it may lead to depression, anxiety, and stress. To date, 21-item instruments of Depression, Anxiety and Stress Scale (DASS) is employed to measure dysphoria. Although DASS provides a quantitative assessment of the human affective state, it is subjected to interpretation. To complicate matters, pre-cursor emotion and pre-emotion of the participants can result in biasness of the DASS report. Hence, a more direct method in measuring human affective state by analyzing the brain pattern is proposed. The approach can also address the dynamic affective state which is needed in detecting dysphoria. Brain waves pattern are collected using the electroencephalogram (EEG) device and used as the input to analyze the underlying emotion. In this paper, relevant features were extracted using Mel-frequency cepstral coefficients (MFCC) and classified with Multi-Layer Perceptron (MLP). The experimental results show potential of differentiating between positive and negative emotion with comparable accuracy. Subsequently, it is envisaged that the proposed model can be extended as a tool that can be used to measure stress and anxiety in work places and education institutions

Early detection of dysphoria using electroencephalogram affective modelling

Dysphoria is a trigger point for maladjusted individuals who cannot cope with disappointments and crushed expectations, resulting in negative emotions if it is not detected early. Individuals who suffer from dysphoria tend to deny their mental state. They try to hide, suppress, or ignore the symptoms, making one feel worse, unwanted, and unloved. Psychologists and psychiatrists identify dysphoria using standardized instruments like questionnaires and interviews. These methods can boast a high success rate. However, the limited number of trained psychologists and psychiatrists and the small number of health institutions focused on mental health limit access to early detection. In addition, the negative connotation and taboo about dysphoria discourage the public from openly seeking help. An alternative approach to collecting ‘pure’ data is proposed in this paper. The brain signals are captured using the electroencephalogram as the input to the machine learning approach to detect negative emotions. It was observed from the experimental results that participants who scored severe dysphoria recorded ‘fear’ emotion even before stimuli were presented during the eyes-close phase. This finding is crucial to further understanding the effect of dysphoria and can be used to study the correlation between dysphoria and negative emotions

Dysphoria detection using EEG signals

Dysphoria is a state faced when one experienced disappointment. If it is not handled properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the individual who experienced dysphoria are in-denial because dysphoria is always being associated with negative connotations such as incompetency to handle pressure, weak personality and lack of will power. To date, there is no accurate instrument to measure dysphoria except using questionnaire by psychologists, such as: Depression, Anxiety and Stress Scale (DASS) and Nepean Dysphoria Scale (NDS-24). Participants may suppress or exaggerate their answers resulting in misdiagnosis. In this work, a theoretical Dysphoria Model of Affect (DMoA) is developed for dysphoria detection. Based on the hypothesis that dysphoria is related to negative emotion, the input from brain signal is captured using electroencephalogram (EEG) device to detect negative emotions. The results from analyzing the EEG signals were compared with DASS and NDS questionnaires for correlation analysis. It is observed that the proposed DMoA approach can identify negative emotions ranging from 55% to 77% accuracy. In addition, the NDS questionnaire seems to provide better distinction for dysphoria as compared to DASS and is similar to the result yielded by DMoA in detecting dysphoria. Thus, DMoA approach can be used as an alternative for early dysphoria detection to assist early intervention in identifying the patients’ mental states. Subsequently, DMoA approach can be implemented as another possible solution for early detection of dysphoria thus providing an enhancement to the present NDS instruments providing psychologists and psychiatrists with a quantitative tool for better analysis of the patients’ state

Inhibitory Processing of Sad Facial Expressions and Depression Vulnerability

Depression vulnerability has been frequently linked to selective attention biases, but these biases may partly result from an inhibitory deficit for processing depressive information (Joormann, 2004). Reduced inhibition when encountering sad interpersonal information (e.g., faces) could lead to greater associative processing, deeper encoding among related depressive content in memory, increased rumination, and perhaps could promote depressive episodes. Inhibition and selective attention can be examined through behavioral and psychophysiological indicators, including the N200, P300a, and P300b ERP components. The present study examined whether groups traditionally at risk of depression would show inhibitory deficits for depressive facial expressions as compared to a low-risk group. A 2 x 2 design yielded four groups with two levels of current dysphoria status (yes/no) and history of depression (yes/no), enabling comparisons of relative risk. Each participant completed two visual oddball tasks. In the experimental task, participants responded or inhibited a response to infrequently presented sad or happy target faces in the context of frequently presented neutral faces. In the non-affective control task, participants responded only to faces that fit into one of three broad age groupings. Behavioral (e.g., reaction times, response errors), psychophysiological (ERP components), and self-report (e.g., rumination) measures relevant to selective attention and inhibition were analyzed. Between- and within-groups contrasts were conducted to reveal whether at-risk groups exhibit attentional bias and inhibitory deficiency specific to depressive information. Also, the study examined whether different operationalizations of depression risk evince common or distinct mechanisms of vulnerability. Across the full sample, previous depression was associated with greater P3b amplitude for sad target faces than happy target faces, in contrast with the depression naïve group. However in males, only the combination of previous depression and current dysphoria were linked to elevated P3s following sad targets. Evidence for a sad affect inhibition deficit was limited to dysphoric females' increased errors of commission following sad distracter faces. Results suggest that specific operationalizations of risk may be characterized by an attentional bias toward depressive facial affect in the social environment, which could promote additional depressogenic cognition and social behavior. Theoretical ramifications regarding gender and state versus trait vulnerability are also discussed

Non-invasive Stimulation of the Cerebellum in Health and Disease

The cerebellum is linked to motor, cognitive and affective functions. Anatomically, the cerebellum is part of an interconnected network including a wide range of other brain structures. This chapter reviews ways in which non-invasive stimulation has been used to activate or inhibit these circuits and how this has contributed to our understanding of cerebellar function in both motor and non-motor domains. The utility of non-invasive stimulation of the cerebellum in the treatment of neurological and psychiatric diseases (Parkinson’s disease, cerebellar ataxia, stroke, depression and schizophrenia) is discussed. The chapter concludes with consideration of the challenges that must be overcome if non-invasive cerebellar stimulation is to be adopted in a wider clinical setting

Global and localized network characteristics of the resting brain predict and adapt to foreign language learning in older adults

Resting brain (rs) activity has been shown to be a reliable predictor of the level of foreign language (L2) proficiency younger adults can achieve in a given time-period. Since rs properties change over the lifespan, we investigated whether L2 attainment in older adults (aged 64–74 years) is also predicted by individual differences in rs activity, and to what extent rs activity itself changes as a function of L2 proficiency. To assess how neuronal assemblies communicate at specific frequencies to facilitate L2 development, we examined localized and global measures (Minimum Spanning Trees) of connectivity. Results showed that central organization within the beta band (~ 13–29.5 Hz) predicted measures of L2 complexity, fluency and accuracy, with the latter additionally predicted by a left-lateralized centro-parietal beta network. In contrast, reduced connectivity in a right-lateralized alpha (~ 7.5–12.5 Hz) network predicted development of L2 complexity. As accuracy improved, so did central organization in beta, whereas fluency improvements were reflected in localized changes within an interhemispheric beta network. Our findings highlight the importance of global and localized network efficiency and the role of beta oscillations for L2 learning and suggest plasticity even in the ageing brain. We interpret the findings against the background of networks identified in socio-cognitive processes

Research Methods in Cognition and Emotion

In this chapter we critically survey research methods used in the field of cognition and emotion. Research on cognition and emotion addresses a great variety of topics, which include the ways in which emotional states influence cognitive processes, the role of cognition in producing emotion, and folk categories and knowledge of emotion. So great is this variety that a brief chapter cannot address all the research methods that have contributed to the expansion of knowledge that has occurred in recent years; there are too many methods, and many are relevant only to particular specialized topics. Specialized research methods are discussed throughout this volume in the chapters devoted to the relevant topics. In this chapter we restrict our attention to methodological issues that span the field of cognition and emotion, yet are in some way unique to it. Not surprisingly, these are the issues and methods that have to do with emotion itself

The neuroscience of sadness: A multidisciplinary synthesis and collaborative review

Sadness is typically characterized by raised inner eyebrows, lowered corners of the mouth, reduced walking speed, and slumped posture. Ancient subcortical circuitry provides a neuroanatomical foundation, extending from dorsal periaqueductal grey to subgenual anterior cingulate, the latter of which is now a treatment target in disorders of sadness. Electrophysiological studies further emphasize a role for reduced left relative to right frontal asymmetry in sadness, underpinning interest in the transcranial stimulation of left dorsolateral prefrontal cortex as an antidepressant target. Neuroimaging studies – including meta-analyses – indicate that sadness is associated with reduced cortical activation, which may contribute to reduced parasympathetic inhibitory control over medullary cardioacceleratory circuits. Reduced cardiac control may – in part – contribute to epidemiological reports of reduced life expectancy in affective disorders, effects equivalent to heavy smoking. We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary, working at different levels of the phylogenetic hierarchy.Fil: Arias, Juan A.. Swansea University; Reino Unido. Universidad de Santiago de Compostela; EspañaFil: Williams, Claire. Swansea University; Reino UnidoFil: Raghvani, Rashmi. Swansea University; Reino UnidoFil: Aghajani, Moji. No especifíca;Fil: Baez, Sandra. Universidad de los Andes; ColombiaFil: Belzung, Catherine. Universite de Tours; FranciaFil: Booij, Linda. Concordia University Montreal; CanadáFil: Busatto, Geraldo. Universidade de Sao Paulo; BrasilFil: Chiarella, Julian. Concordia University Montreal; CanadáFil: Fu, Cynthia. University Of East London; Reino UnidoFil: Ibañez, Agustin Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina. Universidad Adolfo Ibañez; Chile. Universidad Autónoma del Caribe; ColombiaFil: Liddell, Belinda J.. University of New South Wales; AustraliaFil: Lowe, Leroy. No especifíca;Fil: Penninx, Brenda W.J.H.. No especifíca;Fil: Rosa, Pedro. Universidade de Sao Paulo; BrasilFil: Kemp, Andrew H.. Universidade de Sao Paulo; Brasil. Swansea University; Reino Unid

Neural basis of positive and negative emotion regulation in remitted depression

The recurrent nature of Major Depressive Disorder (MDD) necessitates a better understanding of mechanisms facilitating relapse. MDD has often been associated with abnormal emotion regulation, underpinned by aberrant interactions between the prefrontal cortex and subcortical areas. We assessed whether neural regulation abnormalities remain after remission and relate to emotion regulation problems in daily life. At the baseline measurement of a randomized controlled trial, an emotion regulation task was performed during fMRI scanning by 46 remitted recurrent (rrMDD) patients and 24 healthy controls. We assessed both fMRI peak activity and the temporal dynamics of the neural response during passive attendance and explicit regulation of positive and negative emotions. Furthermore, we assessed regulation strategy use in daily life using questionnaires, and attentional biases using a modified attentional dot-probe task. RrMDD patients showed lower activation and different temporal dynamics in occipital, parietal, and prefrontal brain regions during passive attendance of emotional material compared to healthy controls. During explicit downregulation of negative emotions, no group differences were found. However, during explicit upregulation of positive emotions, rrMDD patients showed a different neural response over time in the insula. Behaviourally, rrMDD patients were characterized by dysfunctional regulation strategies in daily life. Within rrMDD patients, rumination was associated with activation within a limbic- prefrontal network. After remission, immediate emotional processing seems unaffected, but regulatory abnormalities remain, especially uninstructed and in daily life. Abnormal insula activation during positive upregulation suggests decreased monitoring of positive emotions. The relation between inadequate rumination and brain activity during emotion regulation suggests that regulation of both positive and negative affect is important in understanding neurocognitive underpinnings of resilience

The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project

Sadness is typically characterized by raised inner eyebrows, lowered corners of the mouth, reduced walking speed, and slumped posture. Ancient subcortical circuitry provides a neuroanatomical foundation, extending from dorsal periaqueductal grey to subgenual anterior cingulate, the latter of which is now a treatment target in disorders of sadness. Electrophysiological studies further emphasize a role for reduced left relative to right frontal asymmetry in sadness, underpinning interest in the transcranial stimulation of left dorsolateral prefrontal cortex as an antidepressant target. Neuroimaging studies – including meta-analyses – indicate that sadness is associated with reduced cortical activation, which may contribute to reduced parasympathetic inhibitory control over medullary cardioacceleratory circuits. Reduced cardiac control may – in part – contribute to epidemiological reports of reduced life expectancy in affective disorders, effects equivalent to heavy smoking. We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary, working at different levels of the phylogenetic hierarchy