Luís Alfredo V. de Carvalho

The acceptance of virtual reality devices for cognitive rehabilitation: a report of positive results with schizophrenia

This study presents a process of virtual environment development supported by a cognitive model that is specific to cognitive deficits of diverse disorders or traumatic brain injury, and evaluates the acceptance of computer devices by a group of schizophrenic patients. The subjects that participated in this experiment accepted to work with computers and immersive glasses and demonstrated a high level of interest in the proposed tasks. No problems of illness have been observed. This experiment indicated that further research projects must be carried out to verify the value of virtual reality technology for cognitive rehabilitation of psychiatric patients. The results of the current study represent a small but necessary step in the realization of that potential.

A GENETIC ALGORITHM APPLIED TO COMPOSITE ELASTIC PARAMETERS IDENTIFICATION

The aim of this work is to present a technique to identify elastic parameters of composite materials. The identification is based on model updating involving an optimization process in which the objective function is defined as the difference between analytical natural frequencies and their experimental counterparts. Such analytical natural frequencies are obtained by means of the finite element method while the experimental ones are obtained by standard modal tests. The optimization problem is solved by a genetic algorithm (GA), which does not require the cost function gradient avoiding the expensive eigenvectors computation presents in gradient methods. The proposed technique is assessed by a number of different tests.

Creativity and delusions: the dopaminergic modulation of cortical maps

Since little is still known about fundamental brain mechanisms associated to thought, its different manifestations are usually classified in an oversimplified way into normal and abnormal, like delusional and disorganized thought or creative thinking. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, and the existence of semantic maps in the human brain, we developed a self-organizing neural network model to unify different thought processes into a single neurocomputational substrate. We performed simulations varying dopaminergic modulation and observed the total patterns that emerged at the resulting semantic map, assuming that these correspond to thought. The model thus shows how normal and abnormal thinking are generated, and that there are no clear borders between their different manifestations. Actually, a continuum of different qualitative reasoning, ranging from delusion to disorganized thought, and passing through normal and creative thinking, seems to be more plausible.

Generalized memory associativity in a network model for the neuroses

We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freuds idea that consciousness is related to symbolic and linguistic memory activity in the brain. We have introduced a generalization of the Boltzmann machine to model memory associativity. Model behavior is illustrated with simulations and some of its properties are analyzed with methods from statistical mechanics.

A Workflow Scheduling Algorithm for Optimizing Energy-Efficient Grid Resources Usage

Grid computing represents the main solution to integrate distributed and heterogeneous resources in global scale. However, the infrastructure necessary for maintaining a global grid in production is huge. Such fact has led to excessive power consumption. On the other hand, most green strategies for data centers are DVS (Dynamic Voltage Scaling)-based and become difficult to implement them in global grids. This paper proposes the HGreen heuristic (Heavier Tasks on Maximum Green Resource) and defines a workflow scheduling algorithm in order to implement it on global grids. HGreen algorithm aims to prioritize energy-efficient resources and explores workflow application profiles. Simulation results have shown that the proposed algorithm can significantly reduce the power consumption in global grids.

A graph model for the evolution of specificity in humoral immunity

The immune system protects the body against health-threatening entities, known as antigens, through very complex interactions involving the antigens and the systems own entities. One remarkable feature resulting from such interactions is the immune systems ability to improve its capability to fight antigens commonly found in the individuals environment. This adaptation process is called the evolution of specificity. In this paper, we introduce a new mathematical model for the evolution of specificity in humoral immunity, based on Jernes functional, or idiotypic, network. The evolution of specificity is modeled as the dynamic updating of connection weights in a dynamic graph whose nodes are related to the networks idiotypes. At the core of this weight-updating mechanism are the increase in specificity caused by clonal selection and the decrease in specificity due to the insertion of uncorrelated idiotypes by the bone marrow. As we demonstrate through numerous computer experiments, for appropriate choices of parameters the new model correctly reproduces, in qualitative terms, several immune functions.

Radiation therapy for feline cutaneous squamous cell carcinoma using a hypofractionated protocol

The objective of this paper was to evaluate the efficacy of a hypofractionated radiation protocol for feline facial squamous cell carcinoma (SCC). Twenty-five histologically confirmed SCCs in 15 cats were treated with four fractions of 7.6–10 Gy each, with 1 week intervals. The equipment used was a linear accelerator Clinac 2100 delivering electron beam of 4 or 6 MeV, and a bolus of 5 or 10 mm was used in all lesions. Of the lesions, 44% were staged as T4, 16% as T3, 8% as T2 and 32% as T1. Of the irradiated lesions, 40% had complete response, 12% had partial response and 48% had no response (NR) to the treatment. For T1 tumors, 62.5% had complete remission. Mean overall survival time was 224 days. Owners requested euthanasia of cats having NR to the treatment. Mean disease free time was 271 days. Side effects observed were skin erythema, epilation, ulceration and conjunctivitis, which were graded according to Veterinary Radiation Therapy Oncology Group (VRTOG) toxicity criteria. Response rates found in this study (52%) were lower when compared to other protocols, probably due to technique differences, such as fractionation schedule, bolus thickness and energy penetration depth. However, the hypofractionated radiation protocol was considered safe for feline facial SCC. Modifications of this protocol are being planned with the objective of improving the cure rates in the future.

Employing Multi-agents in 3-D Game for Cognitive Stimulation

Multi-agents are increasingly gaining the attention of researchers and developers of virtual games. The agents can control the user performance, adapting the interface and automatically changing the difficulty level of tasks. The objective of this paper is to describe the development of a game that combines the technologies of Virtual Reality and Multi-Agent. This system aims at improving the cognitive functions in patients with neuropsychiatric disorders. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

Memory Functioning in Psychopathology

The mental pathology known as neurosis, its aetiology, and the development of symptoms are described in terms of their relation to memory function. We propose, based on a neural network model, that neurotic behavior may be understood as an associative memory process in the brain, and that the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The model is illustrated through a computer simulation implementation. We relate the sensitivity to temperature and the adaptive capabilities of our model, with the sensitivity of cortical map modulation to the catecholamines (norepinephrine and dopamine). The signal-to-noise ratio regulated by these substances influence thought associativity, suggesting a continuum from psychotic functioning through to normal and neurotic behavior and creativity.

Attentional Focus Modulated by Mesothalamic Dopamine: Consequences in Parkinson’s Disease and Attention Deficit Hyperactivity Disorder

In this work, we propose a mathematical model that describes how the mesothalamic dopamine pathway modulates the attentional focus via the thalamocortical loop, and how mesothalamic dopamine alterations can promote inattention symptoms in patients with Parkinson’s disease (PD) and attention deficit hyperactivity disorder (ADHD). We model the thalamocortical loop with a neuronal network where each thalamic neuron is described by a system of coupled differential equations reflecting neurophysiological properties. The computational simulations reflect neurochemical features of PD and ADHD. Our results suggest that the mesothalamic dopamine hypoactivity causes difficulties in attentional shifting. Conversely, the mesothalamic dopamine hyperactivity hinders the attentional focus consolidation. Furthermore, regardless of the amount of mesothalamic dopamine activity, the mesocortical dopamine hypoactivity leads to loss of attentional focus. Finally, we identify a unique neuronal mechanism underlying attention deficits in PD and ADHD and relate different inattention symptoms in ADHD to different dopaminergic levels in the brain circuit modeled.