EEG mapping of motivation

Zenodo (CERN European Organization for Nuclear Research), 2022

The proceedings contain papers presented at the 14th annual NeuroIS Retreat held June 14-16 2022. NeuroIS is a field in Information Systems (IS) that uses neuroscience and neurophysiological tools and knowledge to better understand the development, adoption, and impact of information and communication technologies (www.neurois.org). The NeuroIS Retreat is a leading academic conference for presenting research and development projects at the nexus of IS and neurobiology. This annual conference promotes the development of the NeuroIS field with activities primarily delivered by and for academics, though works often have a professional orientation. In 2009 the inaugural NeuroIS Retreat was held in Gmunden, Austria. Since then, the NeuroIS community has grown steadily, with subsequent annual Retreats in Gmunden from 2010-2017. Beginning in 2018, the conference is taking place in Vienna, Austria. Due to the Corona crisis, the organizers decided to host the NeuroIS Retreat virtually in 2020 and 2021. This year, the NeuroIS Retreat took place again in a physical face-to-face-format in Vienna. The NeuroIS Retreat provides a platform for scholars to discuss their studies and exchange ideas. A major goal is to provide feedback for scholars to advance their research papers toward high-quality journal publications. The organizing committee welcomes not only completed research, but also work in progress. The NeuroIS Retreat is known for its informal and constructive workshop atmosphere. Many NeuroIS presentations have evolved into publications in highly regarded academic journals. This year is the eighth time that we publish the proceedings in the form of an edited volume. A total of 35 research papers were accepted and are published in this volume, and we observe diversity in topics, theories, methods, and tools of the contributions in this book. The 2022 keynote presentation entitled "The Neurobiology of Trust: Benefits and Challenges for NeuroIS" is given by Frank Krueger, professor of systems social neuroscience at the School of Systems Biology at George Mason University (GMU), USA. Moreover, Jan vom Brocke, professor of information systems at the University of Liechtenstein, gives a hot topic talk entitled "From Neuro-adaptive Systems to Neuro-adaptive Processes: Opportunities of NeuroIS to Contribute to the Emerging Field of Process Science". Altogether, we are happy to see the ongoing progress in the NeuroIS field. Also, we can report that the NeuroIS Society, established in 2018 as a non-profit organization, has been developing well. We foresee a prosperous development of NeuroIS.

The rapid progress of neuroscience and the interdisciplinary collaboration between neuroscience and psychology have begun to provide valuable insights for understanding the dynamic and implicit nature of human motivation by identifying the in vivo neural mechanism of motivation. One of the fundamental questions in the field of the neuroscience of motivation is what neural mechanisms underlie the direction, intensity, and guidance of our motivation and subsequent actions. This prologue explains how neuroscience can contribute to the understanding of human motivation. To accomplish this purpose, we present what neuroscientific data look like, identify 13 key motivation-relevant brain structures, and introduce 3 key motivation-centric brain circuits À namely, the reward circuit, the value-based decision-making pathway, and the self-regulation/ self-control network.

In part 1 of this article, we describe an approach and methodology that bridges 2 worlds: the internal, subjective experience of emotions and thoughts, and the external world of brain electrical activity. Using a novel event-related brain activation imaging method, we demonstrate that within single trials, short-term mental processes, on the order of 100 ms, can be clearly related to observed brain activation in controlled experiments. We use an ipsative assessment validation process that combines selfreport with real-time EEG recordings to provide a combined picture of both the mental and the brain activity, during short-term reactions, emotions, and decisions regarding controlled information. Part 2 provides a detailed description of the emerging emotional decision-making model.

Brain Sciences, 2020

Dynamic and temporal facets of the various constructs that comprise motivation remain to be explored. Here, we adapted the Effort Expenditure for Reward Task, a well-known laboratory task used to evaluate motivation, to study the event-related potentials associated with reward processing. The Stimulus Preceding Negativity (SPN) and the P300 were utilized as motivation indicators with high density electroencephalography. The SPN was found to be more negative for difficult choices compared to easy choices, suggesting a greater level of motivation, at a neurophysiological level. The insula, a structure previously associated with both effort discounting and prediction error, was concomitantly activated during the generation of the SPN. Processing a gain significantly altered the amplitude of the P300 compared to an absence of gain, particularly on centroparietal electrodes. One of the generators of the P300 was located on the vmPFC, a cerebral structure involved in the choice between tw...

Neuroscience & Biobehavioral Reviews., 2020

As a part of a larger Affectome Project (http://neuroqualia.org/background.php) with an overarching goal of mapping and redefining biological substrates of feelings and emotions, we explored the neural underpinnings for the functions of motivation and emotion. Historically emotion and motivation have been placed into distinct neural circuits and examined separately. We propose a novel view of significant neural convergence of emotion and motivation, in contrast to conventional neural-based frameworks emphasizing segregation. Evidence from diverse research areas in emotion and motivation was reviewed, pinpointing key neural regions of overlap. The findings support important neural sharing between emotion and motivation, suggesting that these two functions are tightly intertwined with one another in the brain. Neural overlap does not necessarily imply continuous functional overlap. Even if identical brain regions/systems are activated for motivation and emotion, this activation may involve distinct and unique patterns of connection and information flow as the network shifts functionality. This review highlights the crucial importance of further research to explicate the patterns and modes of responding of these overlapping systems. 1. Section I. introduction, theoretical background, and approach Mapping the affectome requires linking feeling states to neural circuits and physiological processes. There is a global interdisciplinary working group collaborating on a project to unite diverse research areas and comprehensively map functional neural models for emotions and related feelings. The project has been labeled 'The Human Affectome Project' (see http://neuroqualia.org/index.php) and the diverse task-force includes researchers in psychology, neuropsychiatry, neu-roscience, economics, and computer science. This overarching goal of mapping the human affectome is being accomplished by having a number of research teams review and synthesize more specific affective neuroscience topics pertinent to the overall objectives. This task would be incomplete without a team that carefully examines the affective neuroscience literature to uncover potential relationships between brain networks underpinning emotion and motivation, which is the team authoring this article. The goal of the present review, therefore, is to carefully describe the neural systems subserving motivation and emotion in the brain, based on relevant animal research, human research on brain bases of motivation and emotion, and human research on the development of these neural systems. From these findings, we present a novel view that emphasizes integration of emotion and motivation, to the point that they merge into a single process and involve overlapping brain sub-strates. Neural research on the interface of these networks with neu-rological correlates of related cognitive and cultural processes is explored. In general, this model contributes to the literature by highlighting the interconnectedness of the neural systems underlying motivation and emotion, and proposing possible loci and neuro-transmitters that forge the interconnections between them. We then https://doi.

Computational intelligence and neuroscience, 2015

Recent findings suggest that specific neural correlates for the key elements of basic emotions do exist and can be identified by neuroimaging techniques. In this paper, electroencephalogram (EEG) is used to explore the markers for video-induced emotions. The problem is approached from a classifier perspective: the features that perform best in classifying person's valence and arousal while watching video clips with audiovisual emotional content are searched from a large feature set constructed from the EEG spectral powers of single channels as well as power differences between specific channel pairs. The feature selection is carried out using a sequential forward floating search method and is done separately for the classification of valence and arousal, both derived from the emotional keyword that the subject had chosen after seeing the clips. The proposed classifier-based approach reveals a clear association between the increased high-frequency (15-32 Hz) activity in the left ...

Trends in cognitive sciences, 2015

Goals and needs shape individuals' thinking, a phenomenon known as motivated cognition. We highlight research from social psychology and cognitive neuroscience that provides insight into the structure of motivated cognition. In addition to demonstrating its ubiquity, we suggest that motivated cognition is often effortless and pervades information processing.

Frontiers in Psychology, 2013

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulusaction association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously.The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

2014

For a commercial or advertisement to be considered good, it must capture the viewer’s attention and hold the viewer’s interest. The curiosity, flow, wonder, and excitement that interest then cues can be beneficial to advertisers and the product that they are selling. The goal of this study is to build a model that predicts levels of viewer interest in advertisements based on EEG, EOG and EMG signals. Participants of the experiment were Ateneo college students majoring in different courses and coming from different year levels. The resulting linear regression models per advertisement, with 10-fold cross-validation, had r-values ranging from -0.0332 to 0.4089 Additional features were engineered, creating another set of models with r-values ranging from -0.0021 to 0.4213. An additional linear regression with 5-fold studentlevel cross-validation was performed with an r-value of 0.129627. SVM classification with 10-fold cross validation was also used, with classifier accuracy reaching 66...

2018

We present a neuroimaging data set comprising behavioural, electroencephalographic (EEG), and functional magnetic resonance imaging (fMRI) data that were acquired from human subjects performing a perceptual decision making task. EEG data were acquired both independently and simultaneously with fMRI data. Potential data usages include the validation of biocomputational accounts of human perceptual decision making or the empirical validation of simultaneous EEG/fMRI data processing algorithms. The dataset is available from the Open Science Framework and organized according to the Brain Imaging Data Structure standard.