ICe - Capítulos de Livros

URI Permanente para esta coleçãohttps://repositorio.ufrn.br/handle/1/11745

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Brain development and maturation in the context of learning
(2022) Cachia, Arnaud; Ribeiro, Sidarta Tollendal Gomes; Chiao, Joan Y.; Friston, Karl; Hillman, Charles H.; Linzarini, Adriano; Lipina, Sebastian J.; Howard-Jones, Paul; Dubois, Jessica; Jay, Thérèse; Bihan, Denis Le; 0000-0001-9325-9545
The goal of this chapter is to present and discuss the educational implications of basic and applied research on the mechanisms underlying brain development and learning. This chapter first provides the basic principles of neuroscience for education, with a focus on the general principles of brain function and organization, standard brain imaging methods to investigate the learning and the developing brain, the neural processes involved in cognitive development and learning, and sex differences and similarities in the brain and cognition. It then details with concrete examples how biological processes – including sleep, exercise, nutrition, trauma, poverty, deprivation, threat and academic stress – can influence the brain and learning. The chapter concludes by outlining misconceptions about neuroscience, or ‘neuromyths’, and the importance for education of debunking them
Computational Tracking of Mental Health in Youth: Latin American Contributions to a Low-Cost and Effective Solution for Early Psychiatric Diagnosis
(2016-06) Mota, Natalia Bezerra; Copelli, Mauro; Ribeiro, Sidarta Tollendal Gomes
The early onset of mental disorders can lead to serious cognitive damage, and timely interventions are needed in order to prevent them. In patients of low socioeconomic status, as is common in Latin America, it can be hard to identify children at risk. Here, we briefly introduce the problem by reviewing the scarce epidemiological data from Latin America regarding the onset of mental disorders, and discussing the difficulties associated with early diagnosis. Then we present computational psychiatry, a new field to which we and other Latin American researchers have contributed methods particularly relevant for the quantitative investigation of psychopathologies manifested during childhood. We focus on new technologies that help to identify mental disease and provide prodromal evaluation, so as to promote early differential diagnosis and intervention. To conclude, we discuss the application of these methods to clinical and educational practice. A comprehensive and quantitative characterization of verbal behavior in children, from hospitals and laboratories to homes and schools, may lead to more effective pedagogical and medical intervention
Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
(2018) Mota, Natália Bezerra; Copelli, Mauro; Ribeiro, Sidarta Tollendal Gomes
In the past ten years, graph theory has been widely employed in the study of natural and technological phenomena. The representation of the relationships among the units of a network allow for a quantitative analysis of its overall structure, beyond what can be understood by considering only a few units. Here we discuss the application of graph theory to psychiatric diagnosis of psychoses and dementias. The aim is to quantify the flow of thoughts of psychiatric patients, as expressed by verbal reports of dream or waking events. This flow of thoughts is hard to measure but is at the roots of psychiatry as well as psychoanalysis. To this end, speech graphs were initially designed with nodes representing lexemes and edges representing the temporal sequence between consecutive words, leading to directed multigraphs. In a subsequent study, individual words were considered as nodes and their temporal sequence as edges; this simplification allowed for the automatization of the process, effected by the free software Speech Graphs. Using this approach, one can calculate local and global attributes that characterize the network structure, such as the total number of nodes and edges, the number of nodes present in the largest connected and the largest strongly connected components, measures of recurrence such as loops of 1, 2, and 3 nodes, parallel and repeated edges, and global measures such as the average degree, density, diameter, average shortest path, and clustering coefficient. Using these network attributes we were able to automatically sort schizophrenia and bipolar patients undergoing psychosis, and also to separate these psychotic patients from subjects without psychosis, with more than 90% sensitivity and specificity. In addition to the use of the method for strictly clinical purposes, we found that differences in the content of the verbal reports correspond to structural differences at the graph level. When reporting a dream, healthy subjects without psychosis and psychotic subjects with bipolar disorder produced more complex graphs than when reporting waking activities of the previous day; this difference was not observed in psychotic subjects with schizophrenia, which produced equally poor reports irrespective of the content. As a consequence, graphs of dream reports were more efficient for the differential diagnosis of psychosis than graphs of daily reports. Based on these results we can conclude that graphs from dream reports are more informative about mental states, echoing the psychoanalytic notion that dreams are a privileged window into thought.
Theta-Gamma Cross-Frequency Analyses (Hippocampus)
(2018) Scheffer-Teixeira, Robson; Tort, Adriano Bretanha Lopes
Brain oscillations of different frequencies can coexist and influence each other. A cross-frequency interaction occurs when a feature from one oscillation (i.e., instantaneous amplitude, phase, or frequency) depends on a feature from another oscillation at a distinct frequency. These phenomena have been collectively called cross-frequency coupling (CFC). There are multiple types of CFC, such as phase-amplitude coupling, amplitude-amplitude coupling, and n:m phase-locking. Several metrics have been devised to quantify CFC.
Whole organisms or pure compounds? entourage effect versus drug specificity
(2018-04-29) Ribeiro, Sidarta Tollendal Gomes
As the therapeutic use of sacred plants and fungi becomes increasingly accepted by Western medicine, a tug of war has been taking place between those who advocate the traditional consumption of whole organisms and those who defend exclusively the utilization of purified compounds. The attempt to reduce organisms to single active principles is challenged by the sheer complexity of traditional medicine. Ayahuasca, for example, is a concoction of at least two plant species containing multiple psychoactive substances with complex interactions. Similarly, cannabis contains dozens of psychoactive substances whose specific combinations in different strains correspond to different types of therapeutic and cognitive effects. The “entourage effect” refers to the synergistic effects of the multiple compounds present in whole organisms, which may potentiate clinical efficacy while attenuating side effects. In opposition to this view, mainstream pharmacology is adamant about the need to use purified substances, presumably more specific and safe. In this chapter, I will review the evidence on both sides to discuss the scientific, economic, and political implications of this controversy. The evidence indicates that it is time to embrace the therapeutic complexity of psychedelics.

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