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Brain Sciences
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Mood: Cognition, Brain, and Behavior
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Mood: Cognition, Brain, and Behavior

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Social Cognitive and Affective Neuroscience".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 7386

Special Issue Editor

Dr. Éric Laurent

E-Mail Website
Guest Editor
Department of Psychology, Laboratory for Integrative Research in Neuroscience and Cognitive Psychology (LINC), Université Bourgogne Franche-Comté, Besançon, France
Interests: cognition; mood; affective processing

Special Issue Information

Dear Colleagues,

Mood is a diffuse affective state—associated with negative or positive valence—whose antecedents are related to a widely distributed network of factors, and whose manifestation is more durable than that of emotion. Sometimes, people are unable to evoke specific causes for their current mood. Thus, we need to improve our understanding of the complex “ecology” of mood. This topic has long been of interest to scholars and physicians, mainly because mood disorders can be debilitating and are associated with a major risk of suicide. Recently, social cognitive and affective neuroscience and psychology have considered the normal side of mood variation, as it can also significantly contribute to modification of brain, cognitive, and behavioral activities.

This Special Issue should represent both traditional and more recent trends in the study of mood. It will gather research on mood in all its forms (normal or pathological). This includes fluctuations in normal mood (measured and/or induced) as well as bipolar and depressive disorders, among others. Contributions linking mood to behavior and/or cognition, brain activity and/or structures, environment, fatigue, genetics, health, or hormones, are of particular interest. The approaches developed can emerge from neuroscience, neurology, psychiatry, psychology, and related fields. We are also eager to publish research concerning emotions, provided the authors explain in their article how they conceive the relationships between emotion and mood, and how their research could inform the literature concerning normal mood or mood disorders.

Original research (experimental, clinical, translational…), critical and systematic reviews, meta-analyses, and methodological notes will all be considered. If in doubt about the suitability of your work to this issue, please do not hesitate to email Dr. Éric Laurent.

Dr. Éric Laurent
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cognition
  • depression
  • emotion
  • mood disorders
  • normal mood

Published Papers (4 papers)

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Research

20 pages, 2102 KiB  
Article
The Influence of Green Product Type, Message Framing, and Anticipated Pride on Green Consumption Behavior: An Event-Related Potential (ERP) Study
by Guanfei Zhang, Jin Li, Min Tan and Yiping Zhong
Brain Sci. 2023, 13(10), 1427; https://doi.org/10.3390/brainsci13101427 - 07 Oct 2023
Viewed by 1146
Abstract
Different types of green products require different marketing approaches to promote individual green purchasing behaviors. Previous studies have focused only on the effects of message framing on the promotion of different types of green products; however, little is known about the role of [...] Read more.
Different types of green products require different marketing approaches to promote individual green purchasing behaviors. Previous studies have focused only on the effects of message framing on the promotion of different types of green products; however, little is known about the role of underlying emotions. Using event-related potentials (ERPs), this study investigated the neural responses to message framings and anticipated pride in green product types to assess their level of influence on green consumption. Participants in this study were randomly assigned to the anticipated pride versus control groups, and asked to make green consumption decisions involving different types (self- vs. other-interested) of green products, utilizing both gain and loss framing. The behavioral results demonstrated that participants in the anticipated pride group made more green product purchase choices than those in the control group. The ERP results showed that within the loss framing of the control group, other-interested green products induced larger N400 and smaller late positive potential (LPP) amplitudes than self-interested green products, whereas the results showed the opposite trend for the anticipated pride group. These results indicate that although individuals might have biases in their motivation that lead them to focus on self-interested green products, anticipating pride reduces cognitive conflicts and increases their motivation to focus on other-interested green products in the context of loss. Full article
(This article belongs to the Special Issue Mood: Cognition, Brain, and Behavior)
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18 pages, 2192 KiB  
Article
Self-Relevance Moderates the Relationship between Depressive Symptoms and Corrugator Activity during the Imagination of Personal Episodic Events
by Leonard Faul, Jane M. Rothrock and Kevin S. LaBar
Brain Sci. 2023, 13(6), 843; https://doi.org/10.3390/brainsci13060843 - 23 May 2023
Viewed by 1336
Abstract
Accumulating evidence suggests depression is associated with blunted reactivity to positive and negative stimuli, known as emotion context insensitivity (ECI). However, ECI is not consistently observed in the literature, suggesting moderators that influence its presence. We propose self-relevance as one such moderator, with [...] Read more.
Accumulating evidence suggests depression is associated with blunted reactivity to positive and negative stimuli, known as emotion context insensitivity (ECI). However, ECI is not consistently observed in the literature, suggesting moderators that influence its presence. We propose self-relevance as one such moderator, with ECI most apparent when self-relevance is low. We examined this proposal by measuring self-report and facial electromyography (EMG) from the corrugator muscle while participants (n = 81) imagined hypothetical scenarios with varying self-relevance and recalled autobiographical memories. Increased depressive symptoms on the Center for Epidemiologic Studies Depression Scale were associated with less differentiated arousal and self-relevance ratings between happy, neutral, and sad scenarios. EMG analyses further revealed that individuals with high depressive symptoms exhibited blunted corrugator reactivity (reduced differentiation) for sad, neutral, and happy scenarios with low self-relevance, while corrugator reactivity remained sensitive to valence for highly self-relevant scenarios. By comparison, in individuals with low depressive symptoms, corrugator activity differentiated valence regardless of stimulus self-relevance. Supporting a role for self-relevance in shaping ECI, we observed no depression-related differences in emotional reactivity when participants recalled highly self-relevant happy or sad autobiographical memories. Our findings suggest ECI is primarily associated with blunted reactivity towards material deemed low in self-relevance. Full article
(This article belongs to the Special Issue Mood: Cognition, Brain, and Behavior)
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10 pages, 1339 KiB  
Article
A Mid-Cycle Rise in Positive and Drop in Negative Moods among Healthy Young Women: A Pilot Study
by Ivana Hromatko and Una Mikac
Brain Sci. 2023, 13(1), 105; https://doi.org/10.3390/brainsci13010105 - 05 Jan 2023
Cited by 1 | Viewed by 2300
Abstract
Clinically oriented studies of mood as a function of the menstrual cycle mainly address the negative moods in the premenstrual phase of the cycle. However, a periovulatory increase in positive emotions and motivations related to reproduction has also been noted. Thus, it has [...] Read more.
Clinically oriented studies of mood as a function of the menstrual cycle mainly address the negative moods in the premenstrual phase of the cycle. However, a periovulatory increase in positive emotions and motivations related to reproduction has also been noted. Thus, it has been suggested that the drop in mood during the luteal phase of the menstrual cycle might be a byproduct of elevated positive moods occurring mid-cycle. The aim of this prospective study was to compare both the positive and negative dimensions of mood across the menstrual cycle. A group of 60 healthy, normally cycling women assessed their mood throughout three phases of their menstrual cycles: the early follicular (low estradiol and progesterone), the late follicular (fertile phase; high estradiol, low progesterone) and the mid-luteal phase (high levels of both estradiol and progesterone). Repeated MANOVA evaluations showed a significant increase in positive (friendly, cheerful, focused, active) and a significant decrease in negative (anxious, depressed, fatigued, hostile) dimensions of mood mid-cycle, i.e., during the late follicular phase (η2 = 0.072–0.174, p < 0.05). Contrary to the widespread belief that negative moods are characteristic of the luteal phase (preceding the onset of the next cycle), the post hoc Bonferroni tests showed that none of the mood dimensions differed between the mid-luteal and early follicular phases of the cycle. The results held when controlling for relationship status and order of testing. This pattern of fluctuations is in accordance with the ovulatory-shift hypothesis, i.e., the notion that the emotions of attraction rise during a short window during which the conception is likely. Full article
(This article belongs to the Special Issue Mood: Cognition, Brain, and Behavior)
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15 pages, 4089 KiB  
Article
Emotional Brain Network Community Division Study Based on an Improved Immunogenetic Algorithm
by Renjie Zhao, Tao Zhang, Shichao Zhou and Liya Huang
Brain Sci. 2022, 12(9), 1159; https://doi.org/10.3390/brainsci12091159 - 30 Aug 2022
Cited by 1 | Viewed by 1529
Abstract
Emotion analysis has emerged as one of the most prominent study areas in the field of Brain Computer Interface (BCI) due to the critical role that the human brain plays in the creation of human emotions. In this study, a Multi-objective Immunogenetic Community [...] Read more.
Emotion analysis has emerged as one of the most prominent study areas in the field of Brain Computer Interface (BCI) due to the critical role that the human brain plays in the creation of human emotions. In this study, a Multi-objective Immunogenetic Community Division Algorithm Based on Memetic Framework (MFMICD) was suggested to study different emotions from the perspective of brain networks. To improve convergence and accuracy, MFMICD incorporates the unique immunity operator based on the traditional genetic algorithm and combines it with the taboo search algorithm. Based on this approach, we examined how the structure of people’s brain networks alters in response to different emotions using the electroencephalographic emotion database. The findings revealed that, in positive emotional states, more brain regions are engaged in emotion dominance, the information exchange between local modules is more frequent, and various emotions cause more varied patterns of brain area interactions than in negative brain states. A brief analysis of the connections between different emotions and brain regions shows that MFMICD is reliable in dividing emotional brain functional networks into communities. Full article
(This article belongs to the Special Issue Mood: Cognition, Brain, and Behavior)
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