Fábio Theoto Rocha

The Brain as a Distributed Intelligent Processing System: An EEG Study

Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis.

Neurodynamics of an election

Variables influencing decision-making in real settings, as in the case of voting decisions, are uncontrollable and in many times even unknown to the experimenter. In this case, the experimenter has to study the intention to decide (vote) as close as possible in time to the moment of the real decision (election day). Here, we investigated the brain activity associated with the voting intention declared 1 week before the election day of the Brazilian Firearms Control Referendum about prohibiting the commerce of firearms. Two alliances arose in the Congress to run the campaigns for YES (for the prohibition of firearm commerce) and NO (against the prohibition of firearm commerce) voting. Time constraints imposed by the necessity of studying a reasonable number (here, 32) of voters during a very short time (5 days) made the EEG the tool of choice for recording the brain activity associated with voting decision. Recent fMRI and EEG studies have shown decision-making as a process due to the enrollment of defined neuronal networks. In this work, a special EEG technique is applied to study the topology of the voting decision-making networks and is compared to the results of standard ERP procedures. The results show that voting decision-making enrolled networks in charge of calculating the benefits and risks of the decision of prohibiting or allowing firearm commerce and that the topology of such networks was vote- (i.e., YES/NO-) sensitive.

A NEUROECONOMIC MODELING OF ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD)

In this paper we present a new neuroeconomics model for decision-making applied to the Attention-Deficit/Hyperactivity Disorder (ADHD). The model is based on the hypothesis that decision-making is dependent on the evaluation of expected rewards and risks assessed simultaneously in two decision spaces: the personal (PDS) and the interpersonal emotional spaces (IDS). Motivation to act is triggered by necessities identified in PDS or IDS. The adequacy of an action in fulfilling a given necessity is assumed to be dependent on the expected reward and risk evaluated in the decision spaces. Conflict generated by expected reward and risk influences the easiness (cognitive effort) and the future perspective of the decision-making. Finally, the willingness (not) to act is proposed to be a function of the expected reward (or risk), adequacy, easiness and future perspective. The two most frequent clinical forms are ADHD hyperactive(AD/HDhyp) and ADHD inattentive(AD/HDdin). AD/HDhyp behavior is hypothesized to be a consequence of experiencing high rewarding expectancies for short periods of time, low risk evaluation, and short future perspective for decision-making. AD/HDin is hypothesized to be a consequence of experiencing high rewarding expectancies for long periods of time, low risk evaluation, and long future perspective for decision-making.

Studying the satisfaction of patients on the outcome of an aesthetic dermatological filler treatment

Background  Many factors contribute to extend productive life in the modern world. Competition makes people worry about physical appearance, mostly in respect to facial and skin aging. This has motivated new developments in cosmetic dermatology and the need of evaluating patient satisfaction with the new proposed treatments. Poll questionnaire has been used for such evaluation, and the analysis of the electroencephalogram (EEG) mapping obtained while the patient answers the satisfaction questionnaire may render the results less subjective.

Mental retadation: a MRI study of 146 Brazilian children

We report results of a magnetic ressonance imaging (MRI) study of 146 Brazilian children, whose intelligence quotient scored less than 70. 50% of MRI examinations did not exhibit any signal of structural lesion (N group), whereas a focal thinning at the junction of the body and splenium of the corpus callosum; ventricular asymmetry; periventricular leukomalacia; gliosis and arachnoid cysts were among the most frequent findings in the remaining of subjects (L group). Maternal stress and altered blood pressure were the most frequent findings in the pre-natal history of both N and L children. Familial antecedents of mental deficiency were reported in 30% of both groups, whereas familiar history of alcoholism was important in N group (60% in N versus 0% in L groups). Neuropsychomotor development was delayed in 80% of the children in both groups. Aggressiveness is the most frequent finding in the post-natal children history.

Brain Activity of the Investor's Stock Market Financial Decision

Using electroencephalogram technologies (EEG) to map the brain, this investigation is among the first to analyze if the same brain circuits are used when making buying, selling, or holding stock decisions and if different circuits are used when market conditions change such as in a growing market or a high volatility market. Two groups of 20 volunteers were used. One group initiated the trading process in a market with steadily increasing prices and then moved to a high volatility market, and the second group started trading in a high volatility market and then in a growing market. Results are quite innovative in the area of finance: brain mapping associated with such decisions differs between these two groups, and also when buying, selling, or holding decisions were made. These results clearly demonstrate that people may use different reasoning strategies to make financial decisions depending on their trading experience.

Brain activity and medical diagnosis: an EEG study

BackgroundDespite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression AnalysisResultsThe principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making.ConclusionsPCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Moral Dilemma Judgment Revisited: A Loreta Analysis

Recent neuroscience investigations on moral judgment have provided useful information about how brain processes such complex decision making. All these studies so were fMRI investigations and therefore constrained by the poor resolution of this technique. Recent advances in electroencephalography (EEG) analysis provided by Low Resolution Tomogray (Loreta), Principal Component (PCA), Correlation and Regression Analysis improved EEG spatial resolution and make EEG a very useful technique in decision-making studies. Here, we reinvestigate previously fMRI study of personal (PD) and impersonal (ID) moral dilemma judgment, taking profit of these new EEG analysis improvements. Compared to the previous fMRI results, Loreta and PCA revealed a much greater number of cortical areas involved in dilemma judgment, whose temporal and spatial distribution were different for ID compared to PD. Regression analysis showed that activity at some cortical areas favors action implementation, while activity at some other areas opposes it. All these results are discussed from the utilitarian point of view that proposes adequacy of human action being dependent upon how much pleasure and fear/pain they are associated. Another finding of the present paper is that whenever final temporal details of the decision making process is desired, EEG becomes the tool of choice.

A Neuromarketing Study of Consumer Satisfaction

The interest of marketing science in using neuroscience techniques to understand the consumer’s thought processes, dates back to the 1970s, when EEG data were recorded while subjects were watching TV commercials. Recently, fMRI was used to study the neural correlates of culturally based brands and neural predictors of purchases. These studies have discovered important properties of the neural circuits that are associated with consumer decision-making process and satisfaction. Here, EEG brain mapping was used to study the dynamics of the brain activity associated with these processes. The present study validated the EEG technology as an adequate neuromarketing tool and shows that consumer’s satisfaction evaluation with the aesthetical dermatological treatment involved the activation of neural circuits involved with facial beauty evaluation.

Brain Mapping and Interpretation of Reading Processing in Children Using EEG and Multivariate Statistical Analysis

Difficulties in learning to read may have a number of causes and children tend to experience on the phonological route the most common disturbance in this cognitive task. Using two sample groups of children with and without reading difficulties and their corresponding EEG signals captured during the reading processing, we describe in this work a set of techniques that investigates such disturbance by generating whole brain mappings based on the entropy of each EEG electrode and non-supervised and supervised multivariate statistical analyses. Our experimental results have clearly showed specific neural organizations well suited to interpreting the word/phrase reading processing in these children. We believe that these techniques might become an effective computational tool in helping the diagnostic process of children with learning disabilities.