Affordances of distractors and compatibility effects: a study with the computational model TRoPICALS

Seeing an object activates in the brain both visual and action codes. Crucial evidence supporting this view is offered by compatibility effect experiments (Ellis et al. (2007). J Exp Psychol: Hum Percept Perform): perception of an object can facilitate or interfere with the execution of an action (e.g. grasping) even when the viewer has no intention of interacting with the object. TRoPICALS (Caligiore et al. (2010). Psychol Rev) is a computational model developed to study compatibility effects. It provides a general hypothesis about the brain mechanisms underlying compatibility effects, suggesting that the top-down bias from prefrontal cortex (PFC), and its agreement or disagreement with the affordances of objects, plays a key role in such phenomena. Compatibility effects have been investigated in the presence of a distractor object in (Ellis et al. (2007). J Exp Psychol: Hum Percept Perform). The reaction times (RTs) results confirmed compatibility effects found in previous experiments without the distractor. Interestingly, results also showed an unexpected effect of the distractor: responding to a target with a grip compatible with the size of the distractor produced slower RTs in comparison to the incompatible case. Here we present an enhanced version of TRoPICALS that reproduces and explains these new results. This explanation is based on the idea according to which PFC might play a double role in its top-down guidance of action selection producing: (a) a positive bias in favor of the action requested by the experimental task; (b) a negative bias directed to inhibiting the action evoked by the distractor. The model also provides two testable predictions on the possible consequences on compatibilities effects of the target and distractor objects in Parkinsonian disease patients with damages of inhibitory circuits

The role of tactile input in learning to reach an object with one\u27s hand.

We have tried to understand when an artificial organism controlled by a neural network receives tactile input when its hand touches an object, the evolution of capacity to reach the object, compared to a condition in which the organism has no tactile input

Reti complesse e resistenze ai guasti

No abstract availabl

Vision, action and language unified through embodiment

Editorial of Psichological Research Special Issue "Vision, action and language unified through embodiment

Some adaptive advantages of the ability to make predictions

We describe some simple simulations showing two possible adaptive advantages of the ability to predict the consequences of one?s actions: predicted inputs can replace missing inputs and predicted success vs. failure can help deciding whether to actually executing a planned action or not. The neural networks controlling the organisms? behaviour include distinct modules whose connection weights are all genetically inherited and evolved using a genetic algorithm except those of the predictive module which are learned during life

Integrating reinforcement learning, equilibrium points and minimum variance to understand the development of reaching: a computational model

Despite the huge literature on reaching behaviour we still lack a clear idea about the motor control processes underlying its development in infants. This article contributes to overcome this gap by proposing a computational model based on three key hypotheses: (a) trial-anderror learning processes drive the progressive development of reaching; (b) the control of the movements based on equilibrium points allows the model to quickly find the initial approximate solution to the problem of gaining contact with the target objects; (c) the request of precision of the end-movement in the presence of muscular noise drives the progressive refinement of the reaching behaviour. The tests of the model, based on a two degrees of freedom simulated dynamical arm, show that it is capable of reproducing a large number of empirical findings, most deriving from longitudinal studies with children: the developmental trajectory of several dynamical and kinematic variables of reaching movements, the time evolution of submovements composing reaching, the progressive development of a bell-shaped speed profile, and the evolution of the management of redundant degrees of freedom. The model also produces testable predictions on several of these phenomena. Most of these empirical data have never been investigated by previous computational models and, more importantly, have never been accounted for by a unique model. In this respect, the analysis of the model functioning reveals that all these results are ultimately explained, sometimes in unexpected ways, by the same developmental trajectory emerging from the interplay of the three mentioned hypotheses: the model first quickly learns to perform coarse movements that assure a contact of the hand with the target (an achievement with great adaptive value), and then slowly refines the detailed control of the dynamical aspects of movement to increase accuracy

The hierarchical organisation of cortical and basal-ganglia systems: a computationally-informed review and integrated hypothesis

To suitably adapt to the challenges posed by reproduction and survival, animals need to learn to select when to perform different behaviours, to have internal criteria for guiding these learning processes, and to perform behaviours efficiently once selected. To implement these processes, their brain must be organised in a suitable hierarchical fashion. Here we briefly review two types of neural/behavioural/computational literatures, focussed respectively on cortex and on sub-cortical areas, and highlight their important limitations. Then we review two computational modelling works of the authors that exemplify the problems, brain areas, experiments, main concepts and limitations of the two research threads. Finally we propose a theoretical integration of the two views, showing how this allows to solve most of the problems found by the two accounts if taken in isolation. The overall picture that emerges is that the cortical and the basal ganglia systems form two highly-organised hierarchical systems working in close synergy and jointly solving all the challenges of choice, selection, and implementation needed to acquire and express adaptive behaviour

Compatibility effects and affordances: a neural-network computational model

No abstract availabl

La diffusione di tratti culturali tra reti di agenti artificiali

No abstract availabl