Rebordering the borders created by multidisciplinary sciences: A study

Emergence of “Glass ceiling” like phenomena in the minds of professionals doing research in a multidisciplinary subject needs to be studied. For an example, computational neurosciences(CNS) comprises of neurology, cognitive science, psychology, computer science, physics, mathematics, information technology, radiology, anthropology, sociology, and biology. When a specialist doing research in a multidisciplinary science like computational neuroscience, know less about other disciplines. This at times leads to tension among the members of the multidisciplinary group. This may create an environment where some members feel excluded. This may also lead to a power structure among different professionals. In case of CNS, the biological scientists feel the computational and engineering sciences may use their mathematical power to control them. On the other hand the engineering scientists feel they need to learn more about biology to understand CNS. The highly technical medical specialist such as Electro physiologists were also feeling like the biologists. As computational neurosciences gaining more importance, it is important to understand the interaction among the scientists from different disciplines and its effect on the development of discipline. The present paper is an attempt to study the dynamics of the members of the multidisciplinary group, who have done their short course on CNS.Multidisciplinary Research, Computational Neuroscience, interaction, education, research

A Synergistic Antiobesity Effect by a Combination of Capsinoids and Cold Temperature Through Promoting Beige Adipocyte Biogenesis.

Beige adipocytes emerge postnatally within the white adipose tissue in response to certain environmental cues, such as chronic cold exposure. Because of its highly recruitable nature and relevance to adult humans, beige adipocytes have gained much attention as an attractive cellular target for antiobesity therapy. However, molecular circuits that preferentially promote beige adipocyte biogenesis remain poorly understood. We report that a combination of mild cold exposure at 17°C and capsinoids, a nonpungent analog of capsaicin, synergistically and preferentially promotes beige adipocyte biogenesis and ameliorates diet-induced obesity. Gain- and loss-of-function studies show that the combination of capsinoids and cold exposure synergistically promotes beige adipocyte development through the β2-adrenoceptor signaling pathway. This synergistic effect on beige adipocyte biogenesis occurs through an increased half-life of PRDM16, a dominant transcriptional regulator of brown/beige adipocyte development. We document a previously unappreciated molecular circuit that controls beige adipocyte biogenesis and suggest a plausible approach to increase whole-body energy expenditure by combining dietary components and environmental cues

The science of psychoanalysis

For psychoanalysis to qualify as scientific psychology, it needs to generate data that can evidentially support theoretical claims. Its methods, therefore, must at least be capable of correcting for biases produced in the data during the process of generating it; and we must be able to use the data in sound forms of inference and reasoning. Critics of psychoanalysis have claimed that it fails on both counts, and thus whatever warrant its claims have derive from other sources. In this article, I discuss three key objections, and then consider their implications together with recent developments in the generation and testing of psychoanalytic theory. The first and most famous is that of ‘suggestion’; if it sticks, clinical data may be biased in a way that renders all inferences from them unreliable. The second, sometimes confused with the first, questions whether the data are or can be used to provide genuine tests of theoretical hypotheses. The third will require us to consider the question of how psychology can reliably infer motives from behavior. I argue that the clinical method of psychoanalysis is defensible against these objections in relation to the psychodynamic model of mind, but not wider metapsychological and etiological claims. Nevertheless, the claim of psychoanalysis to be a science would be strengthened if awareness of the methodological pitfalls and means to avoid them, and alternative theories and their evidence bases, were more widespread. This may require changes in the education of psychoanalysts

Appetitive and Aversive Goal Values Are Encoded in the Medial Orbitofrontal Cortex at the Time of Decision Making

An essential feature of choice is the assignment of goal values (GVs) to the different options under consideration at the time of decision making. This computation is done when choosing among appetitive and aversive items. Several groups have studied the location of GV computations for appetitive stimuli, but the problem of valuation in aversive contexts at the time of decision making has been ignored. Thus, although dissociations between appetitive and aversive components of value signals have been shown in other domains such as anticipatory and outcome values, it is not known whether appetitive and aversive GVs are computed in similar brain regions or in separate ones. We investigated this question using two different functional magnetic resonance imaging studies while human subjects placed real bids in an economic auction for the right to eat/avoid eating liked/disliked foods. We found that activity in a common area of the medial orbitofrontal cortex and the dorsolateral prefrontal cortex correlated with both appetitive and aversive GVs. These findings suggest that these regions might form part of a common network

Structure Learning in Coupled Dynamical Systems and Dynamic Causal Modelling

Identifying a coupled dynamical system out of many plausible candidates, each of which could serve as the underlying generator of some observed measurements, is a profoundly ill posed problem that commonly arises when modelling real world phenomena. In this review, we detail a set of statistical procedures for inferring the structure of nonlinear coupled dynamical systems (structure learning), which has proved useful in neuroscience research. A key focus here is the comparison of competing models of (ie, hypotheses about) network architectures and implicit coupling functions in terms of their Bayesian model evidence. These methods are collectively referred to as dynamical casual modelling (DCM). We focus on a relatively new approach that is proving remarkably useful; namely, Bayesian model reduction (BMR), which enables rapid evaluation and comparison of models that differ in their network architecture. We illustrate the usefulness of these techniques through modelling neurovascular coupling (cellular pathways linking neuronal and vascular systems), whose function is an active focus of research in neurobiology and the imaging of coupled neuronal systems

Donald J. Reis, MD: Research Mentor Extraordinaire

Donald J. Reis, M.D., the late internationally reknowned neuroscientist, had a special talent for mentoring researchers early in their academic careers. His “hands-on” approach to laboratory investigation, his extraoridinary patience with novice researchers, his commitment to the scientific method, and his enthusiastic approach to the art of neuroscience all combined to make him the ideal mentor for many budding academics over the past four decades. The beauty of his scientific legacy is that he loved to each research. The following tribute is personal from one whose career was changed by a great mentor.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44283/1/10571_2004_Article_467228.pd