Cognitive robotics for the modelling of cognitive dysfunctions: A study on unilateral spatial neglect

© 2015 IEEE. Damage to the posterior parietal cortex (PPC) can cause patients to fail to orient toward, explore, and respond to stimuli on the contralesional side of the space. PPC is thought to play a crucial role in the computation of sensorimotor transformations that is in linking sensation to action. Indeed, this disorder, known as Unilateral Spatial Neglect (USN), can compromise visual, auditory, tactile, and olfactory modalities and may involve personal, extra-personal, and imaginal space [1], [2]. For this reason, USN describes a collection of behavioural symptoms in which patients appear to ignore, forget, or turn away from contralesional space [3]. Given the complexity of the disease and the difficulties to study human patients affected by USN, because of their impairments, several computer simulation studies were carried out via artificial neural networks in which damage to the connection weights was also found to yield neglect-related behaviour [4]-[6]

Studying the Evolutionary Basis of Emotions Through Adaptive Neuroagents: Preliminary Settings and Results

We propose a method to investigate the adaptive and evolutionary function of emotions and affective states, in our case of ancestral fear - using Artificial Life and Evolutionary Robotics techniques. For this purpose, we developed a hybrid software-hardware capable to train artificial neuroagents equipped with a sensory-motor apparatus inspired on the iCub humanoid robot features. We trained populations of these agents throughout a genetic algorithm to perform a well-known neuropsychological task adapted to study emotional phenomena. The robots learnt to discriminate stressful emotional conditions (coping with “dangerous” stimuli) and no-stress conditions. Varying the network structures, the experimental conditions and comparing the outcomes we were able to delineate a very initial snapshot of behavioral and neural prerequisite for emotional-based actions. On the other hand, we have to stress that the main contribution we brought is setting-up a methodology to support future studies on emotions in natural and artificial agents

Brain networks of visuospatial attention and their disruption in visual neglect

Visual neglect is a multi-component syndrome including prominent attentional disorders. Research on the functional mechanisms of neglect is now moving from the description of dissociations in patients' performance to the identification of the possible component deficits and of their interaction with compensatory strategies. In recent years, the dissection of attentional deficits in neglect has progressed in parallel with increasing comprehension of the anatomy and function of large-scale brain networks implicated in attentional processes. This review focuses on the anatomy and putative functions of attentional circuits in the brain, mainly subserved by fronto-parietal networks, with a peculiar although not yet completely elucidated role for the right hemisphere. Recent results are discussed concerning the influence of a non-spatial attentional function, phasic alertness, on conscious perception in normal participants and on conflict resolution in neglect patients. The rapid rate of expansion of our knowledge of these systems raises hopes for the development of effective strategies to improve the functioning of the attentional networks in brain-damaged patients

Modeling orienting behavior and its disorders with "ecological" neural networks

Computational modeling is a useful tool for spelling out hypotheses in cognitive neuroscience and testing their predictions in artificial systems. Here we describe a series of simulations involving neural networks that learned to perform their task by self-organizing their internal connections. The networks controlled artificial agents with an orienting eye and an arm. Agents saw objects with various shapes and locations and learned to press a key appropriate to their shape. The results showed the following: (1) Despite being able to see the entire visual scene without moving their eye, agents learned to orient their eye toward a peripherally presented object. (2) Neural networks whose hidden layers were previously partitioned into units dedicated to eye orienting and units dedicated to arm movements learned the identification task faster and more accurately than did nonmodular networks. (3) Nonetheless, even nonmodular networks developed a similar functional segregation through self-organization of their hidden layer. (4) After partial disconnection of the hidden layer from the input layer, the lesioned agents continued to respond accurately to single stimuli, wherever they occurred, but on double simultaneous stimulation they oriented toward and responded only to the right-sided stimulus, thus simulating extinction/neglect. These results stress the generality of the advantages provided by orienting processes. Hard-wired modularity, reminiscent of the distinct cortical visual streams in the primate brain, provided further evolutionary advantages. Finally, disconnection is likely to be a mechanism of primary importance in the pathogenesis of neglect and extinction symptoms, consistent with recent evidence from animal studies and brain-damaged patients