Methods and Approaches for Characterizing Learning Related Changes Observed in functional MRI Data — A Review

Brain imaging data have so far revealed a wealth of information about neuronal circuits involved in higher mental functions like memory, attention, emotion, language etc. Our efforts are toward understanding the learning related effects in brain activity during the acquisition of visuo-motor sequential skills. The aim of this paper is to survey various methods and approaches of analysis that allow the characterization of learning related changes in fMRI data. Traditional imaging analysis using the Statistical Parametric Map (SPM) approach averages out temporal changes and presents overall differences between different stages of learning. We outline other potential approaches for revealing learning effects such as statistical time series analysis, modelling of haemodynamic response function and independent component analysis. We present example case studies from our visuo-motor sequence learning experiments to describe application of SPM and statistical time series analyses. Our review highlights that the problem of characterizing learning induced changes in fMRI data remains an interesting and challenging open research problem

A Multi-disciplinary Approach to the Investigation of Aspects of Serial Order in Cognition

Serial order processing or Sequence processing underlies many human activities such as speech, language, skill learning, planning, problem solving, etc. Investigating the\ud neural bases of sequence processing enables us to understand serial order in cognition and helps us building intelligent devices. In the current paper, various\ud cognitive issues related to sequence processing will be discussed with examples. Some of the issues are: distributed versus local representation, pre-wired versus\ud adaptive origins of representation, implicit versus explicit learning, fixed/flat versus hierarchical organization, timing aspects, order information embedded in sequences, primacy versus recency in list learning and aspects of sequence perception such as recognition, recall and generation. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, theoretical frameworks based on Markov models and Reinforcement Learning paradigm will be presented. These theoretical ideas are useful for studying sequential phenomena in a principled way

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes

Social mindfulness and prosociality vary across the globe

Humans are social animals, but not everyone will be mindful of others to the same extent. Individual differences have been found, but would social mindfulness also be shaped by one’s location in the world? Expecting cross-national differences to exist, we examined if and how social mindfulness differs across countries. At little to no material cost, social mindfulness typically entails small acts of attention or kindness. Even though fairly common, such low-cost cooperation has received little empirical attention. Measuring social mindfulness across 31 samples from industrialized countries and regions (n = 8,354), we found considerable variation. Among selected country-level variables, greater social mindfulness was most strongly associated with countries’ better general performance on environmental protection. Together, our findings contribute to the literature on prosociality by targeting the kind of everyday cooperation that is more focused on communicating benevolence than on providing material benefits

Is loss-aversion magnitude-dependent? Measuring prospective affective judgments regarding gains and losses

Prospect Theory proposed that the (dis)utility of losses is always more than gains due to a phenomena called ‘loss-aversion’, a result obtained in multiple later studies over the years. However, some researchers found reversed or no loss-aversion for affective judgments of small monetary amounts but, those findings have been argued to stem from the way gains versus losses were measured. Thus, it was not clear whether loss-aversion does not show with affective judgments for smaller magnitudes, or it is a measurement error. This paper addresses the debate concerning loss-aversion (in the prospect theoretic sense) and judgments about the intensity of gains and losses. We measured affective prospective judgments for monetary amounts using measurement scales that have been argued to be suitable for measuring loss-aversion and hence rule out any explanations regarding measurement. Both in a gambling scenario (Experiments 1 and 2) and in the context of fluctuating prices (Experiments 3a and 3b), potential losses never loomed larger than gains for low magnitudes, indicating that it is not simply a measurement error. Moreover, for the same participant, loss aversion was observable at high magnitudes. Further, we show that loss-aversion disappears even for higher monetary values, if contextually an even larger anchor is provided. The results imply that Prospect Theory’s value function is contextually dependent on magnitudes

Neuroinformatics Tools for Functional MRI: Experimental Design and Data Analysis

Neuroimaging in vivo is becoming popular from the last two decades. The primary quest of neuroimaging is to better-understanding the functions of various brain areas pertaining to various cognitive processes of interest. Though there are several neuroimaging techniques available currently, the functional Magnetic Resonance Imaging (fMRI) is playing an important role in the field of Imaging Neuroscience. In this paper an introduction to fMRI, the issues related to experimental design and analysis will be presented. This paper also discusses some of the neuroinformatics tools available for fMRI research

Bad to worse: Striatal coding of the relative value of painful decisions

The majority of decision-related research has focused on how the brain computes decisions over outcomes that are positive in expectation. However, much less is known about how the brain integrates information when all possible outcomes in a decision are negative. To study decision-making over negative outcomes, we used fMRI along with a task in which participants had to accept or reject 50/50 lotteries that could result in more or fewer electric shocks compared to a reference amount. We hypothesized that behaviorally, participants would treat fewer shocks from the reference amount as a gain, and more shocks from the reference amount as a loss. Furthermore, we hypothesized that this would be reflected by a greater BOLD response to the prospect of fewer shocks in regions typically associated with gain, including the ventral striatum and orbitofrontal cortex. The behavioral data suggest that participants in our study viewed all outcomes as losses, despite our attempt to induce a status quo. We find that the ventral striatum showed an increase in BOLD response to better potential gambles (i.e., fewer expected shocks). This lends evidence to the idea that the ventral striatum is not solely responsible for reward processing but that it might also signal the relative value of an expected outcome or action, regardless of whether the outcome is entirely appetitive or aversive. We also find a greater response to worse gambles in regions previously associated with aversive valuation, suggesting an opposing but simultaneous valuation signal to that conveyed by the striatum

Bad to worse:Striatal coding of the relative value of painful decisions

The majority of decision-related research has focused on how the brain computes decisions over outcomes that are positive in expectation. However, much less is known about how the brain integrates information when all possible outcomes in a decision are negative. To study decision-making over negative outcomes, we used fMRI along with a task in which participants had to accept or reject 50/50 lotteries that could result in more or fewer electric shocks compared to a reference amount. We hypothesized that behaviorally, participants would treat fewer shocks from the reference amount as a gain, and more shocks from the reference amount as a loss. Furthermore, we hypothesized that this would be reflected by a greater BOLD response to the prospect of fewer shocks in regions typically associated with gain, including the ventral striatum and orbitofrontal cortex. The behavioral data suggest that participants in our study viewed all outcomes as losses, despite our attempt to induce a status quo. We find that the ventral striatum showed an increase in BOLD response to better potential gambles (i.e., fewer expected shocks). This lends evidence to the idea that the ventral striatum is not solely responsible for reward processing but that it might also signal the relative value of an expected outcome or action, regardless of whether the outcome is entirely appetitive or aversive. We also find a greater response to worse gambles in regions previously associated with aversive valuation, suggesting an opposing but simultaneous valuation signal to that conveyed by the striatum

Influence of pharmacological and epigenetic factors to suppress neurotrophic factors and enhance neural plasticity in stress and mood disorders

© 2019, Springer Nature B.V. Stress-induced major depression and mood disorders are characterized by behavioural abnormalities and psychiatric illness, leading to disability and immature mortality worldwide. Neurobiological mechanisms of stress and mood disorders are discussed considering recent findings, and challenges to enhance pharmacological effects of antidepressant, and mood stabilizers. Pharmacological enhancement of ketamine and scopolamine regulates depression at the molecular level, increasing synaptic plasticity in prefrontal regions. Blood-derived neurotrophic factors facilitate mood-deficit symptoms. Epigenetic factors maintain stress-resilience in hippocampal region. Regulation of neurotrophic factors blockades stress, and enhances neuronal survival though it paralyzes limbic regions. Molecular agents and neurotrophic factors also control behavioral and synaptic plasticity in addiction and stress disorders. Future research on neuronal dynamics and cellular actions can be directed to obtain the etiology of synaptic dysregulation in mood disorder and stress. For the first time, the current review contributes to the literature of synaptic plasticity representing the role of epigenetic mechanisms and glucocorticoid receptors to predict depression and anxiety in clinical conditions