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

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

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

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

The Effect of Wealth Shocks on Loss Aversion: Behavior and Neural Correlates

Kahneman and Tversky (1979) first demonstrated that when individuals decide whether or not to accept a gamble, potential losses receive more weight than possible gains in the decision. This phenomenon is referred to as loss aversion. We investigated how loss aversion in risky financial decisions is influenced by sudden changes to wealth, employing both behavioral and neurobiological measures. We implemented an fMRI experimental paradigm, based on that employed by Tom et al. (2007). There are two treatments, called RANDOM and CONTINGENT. In RANDOM, the baseline setting, the changes to wealth, referred to as wealth shocks in economics, are independent of the actual choices participants make. Under CONTINGENT, we induce the belief that the changes in income are a consequence of subjects' own decisions. The magnitudes and sequence of the shocks to wealth are identical between the CONTINGENT and RANDOM treatments. We investigated whether more loss aversion existed in one treatment than another. The behavioral results showed significantly greater loss aversion in CONTINGENT compared to RANDOM after a negative wealth shock. No differences were observed in the response to positive shocks. The fMRI results revealed a neural loss aversion network, comprising the bilateral striatum, amygdala and dorsal anterior cingulate cortex that was common to the CONTINGENT and RANDOM tasks. However, the ventral prefrontal cortex, primary somatosensory cortex and superior occipital cortex, showed greater activation in response to a negative change in wealth due to individual's own decisions than when the change was exogenous. These results indicate that striatum activation correlates with loss aversion independently of the source of the shock, and that the ventral prefrontal cortex (vPFC) codes the experimental manipulation of agency in one's actions influencing loss aversion

The Effect of Wealth Shocks on Loss Aversion: Behavior and Neural Correlates

Kahneman and Tversky (1979) first demonstrated that when individuals decide whether or not to accept a gamble, potential losses receive more weight than possible gains in the decision. This phenomenon is referred to as loss aversion. We investigated how loss aversion in risky financial decisions is influenced by sudden changes to wealth, employing both behavioral and neurobiological measures. We implemented an fMRI experimental paradigm, based on that employed by Tom et al. (2007). There are two treatments, called RANDOM and CONTINGENT. In RANDOM, the baseline setting, the changes to wealth, referred to as wealth shocks in economics, are independent of the actual choices participants make. Under CONTINGENT, we induce the belief that the changes in income are a consequence of subjects' own decisions. The magnitudes and sequence of the shocks to wealth are identical between the CONTINGENT and RANDOM treatments. We investigated whether more loss aversion existed in one treatment than another. The behavioral results showed significantly greater loss aversion in CONTINGENT compared to RANDOM after a negative wealth shock. No differences were observed in the response to positive shocks. The fMRI results revealed a neural loss aversion network, comprising the bilateral striatum, amygdala and dorsal anterior cingulate cortex that was common to the CONTINGENT and RANDOM tasks. However, the ventral prefrontal cortex, primary somatosensory cortex and superior occipital cortex, showed greater activation in response to a negative change in wealth due to individual's own decisions than when the change was exogenous. These results indicate that striatum activation correlates with loss aversion independently of the source of the shock, and that the ventral prefrontal cortex (vPFC) codes the experimental manipulation of agency in one's actions influencing loss aversion.University Grants Commission (UGC), Government of India, Centre of Excellence Grant; Comision Nacional de Investigacion Cientifica y Tecnologica de Chile (Conicyt) through Fondo Nacional de Desarrollo Cientifico y Tecnologico, Fondecyt Regular [1171313, 1171320]; BMBF [01DQ13004]; Proyectos de Investigacion Interdisciplinaria, Vicerrectoria de Investigacion (VRI), Pontificia Universidad Catolica de Chile [15/2013]; CONICYT-PCHA/Magister Nacional [2014-22140196]; CONICYT-PIA Anillo [ACT1416, ACT1414]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]