Neural Differentiation of Expected Reward and Risk in Human Subcortical Structures

In decision-making under uncertainty, economic studies emphasize the importance of risk in addition to expected reward. Studies in neuroscience focus on expected reward and learning rather than risk. We combined functional imaging with a simple gambling task to vary expected reward and risk simultaneously and in an uncorrelated manner. Drawing on financial decision theory, we modeled expected reward as mathematical expectation of reward, and risk as reward variance. Activations in dopaminoceptive structures correlated with both mathematical parameters. These activations differentiated spatially and temporally. Temporally, the activation related to expected reward was immediate, while the activation related to risk was delayed. Analyses confirmed that our paradigm minimized confounds from learning, motivation, and salience. These results suggest that the primary task of the dopaminergic system is to convey signals of upcoming stochastic rewards, such as expected reward and risk, beyond its role in learning, motivation, and salience. © 2006 Elsevier Inc. All rights reserved

The narrative profile in Williams syndrome: There is more to storytelling than just telling a story

Williams Syndrome (WS) is a neurodevelopmental disorder that is characterized by a distinctive neurocognitive and behavioural phenotype, where relative cognitive strengths (e.g., language, narrative production, and face processing) coexist with severe deficits in other cognitive domains (e.g., visual-spatial processing). By using a new scoring system, this study aimed to explore structural (coherence), process (complexity) and content (multiplicity) aspects of fictional narrative production in WS, taking typical development as reference. In this way, it aimed at providing more evidence on the narrative profile of WS, complementing previous studies. Results showed that narratives in individuals with WS are significantly less coherent, diverse and complex relative to controls. Contrasting with typically developing controls' reliance on structural coherence, individuals with WS tend to rely more on the diversity of narrative content as a major narrative device. Additionally, these participants seem to compensate their deficiencies in narrative ability by relying on some social markers of the narrative, such as the emotional commitment with the story telling (i.e., evaluative commitment). Together, these findings bring additional support for the dissociation between expressive/social and cognitive/metacognitive aspects of narrative production in WS

A Neural Model of Human Object Recognition Development

Abstract. The human capability of recognizing objects visually is here held to be a function emerging as result of interactions between epigenetic influences and basic neural plasticity mechanisms. The model here proposed simulates the development of the main neural processes of the visual system giving rise to the higher function of recognizing objects. It is a hierarchy of artificial neural maps, mainly based on the LISSOM architecture, achieving self-organization through simulated intercortical lateral connections.

Plasticity and nativism: Towards a resolution of an apparent paradox

Abstract: Recent research in brain development and cognitive development leads to an apparent paradox. One set of recent experiments suggests that infants are well-endowed with sophisticated mechanisms for analyzing the world; another set of recent experiments suggests that brain development is extremely flexible. In this paper, I review various ways of resolving the implicit tension between the two, and close with a proposal for a novel computational approach to reconciling nativism with developmental flexibility.

How Brains Make Mental Models

Abstract. Many psychologists, philosophers, and computer scientist have written about mental models, but have remained vague about the nature of such models. Do they consist of propositions, concepts, rules, images, or some other kind of mental representation? This paper will argue that a unified account can be achieved by understanding mental models as representations consisting of patterns of activation in populations of neurons. The fertility of this account will be illustrated by showing its applicability to causal reasoning and the generation of novel concepts in scientific discovery and technological innovation. I will also discuss the implications of this view of mental models for evaluating claims that cognition is embodied.