Interdisciplinary Approaches in Psychiatric Research: From Neural Dynamics to Clinical Applications in Schizophrenia.

This editorial explores the dynamic psychiatric research field by focusing on interdisciplinary approaches to understand the complexity of mental disorders by placing particular emphasis on schizophrenia. It highlights the need to integrate findings from diverse scientific disciplines, such as neuroscience, computational modeling and genomics, to unravel the multifaceted nature of these conditions. The potential of interdisciplinary research to transform our knowledge and the treatment of psychiatric disorders is underscored by moving beyond traditional models and developing more nuanced frameworks to more effectively address these complexities.

FDI: A MATLAB tool for computing the fractal dimension index of sources reconstructed from EEG data.

Background: The fractal dimension (FD) is a valuable tool for analysing the complexity of neural structures and functions in the human brain. To assess the spatiotemporal complexity of brain activations derived from electroencephalogram (EEG) signals, the fractal dimension index (FDI) was developed. This measure integrates two distinct complexity metrics: 1) integration FD, which calculates the FD of the spatiotemporal coordinates of all significantly active EEG sources (4DFD); and 2) differentiation FD, determined by the complexity of the temporal evolution of the spatial distribution of cortical activations (3DFD), estimated via the Higuchi FD [HFD(3DFD)].

Advances in Understanding Fractals in Affective and Anxiety Disorders.

In this chapter, we review the research that has applied fractal measures to the study of the most common psychological disorders, that is, affective and anxiety disorders. Early studies focused on heart rate, but diverse measures have also been examined, from variations in subjective mood, or hand movements, to electroencephalogram or magnetoencephalogram data. In general, abnormal fractal dynamics in different physiological and behavioural outcomes have been observed in mental disorders.

Mutual information of multiple rhythms in schizophrenia.

Interactions between different cortical rhythms, such as slow and fast oscillations, have been hypothesized to underlie many cognitive functions. In patients diagnosed with schizophrenia, there is some evidence indicating that the interplay between slow and fast oscillations might be impaired or disrupted. In this study, we investigated multiple oscillatory interactions in schizophrenia using a novel approach based on information theory.

Examining Neural Connectivity in Schizophrenia Using Task-Based EEG: A Graph Theory Approach.

Schizophrenia (SZ) is a complex disorder characterized by a range of symptoms and behaviors that have significant consequences for individuals, families, and society in general. Electroencephalography (EEG) is a valuable tool for understanding the neural dynamics and functional abnormalities associated with schizophrenia. Research studies utilizing EEG have identified specific patterns of brain activity in individuals diagnosed with schizophrenia that may reflect disturbances in neural synchronization and information processing in cortical circuits.

Fractal dimension analysis of resting state functional networks in schizophrenia from EEG signals.

Fractal dimension (FD) has been revealed as a very useful tool in analyzing the changes in brain dynamics present in many neurological disorders. The fractal dimension index (FDI) is a measure of the spatiotemporal complexity of brain activations extracted from EEG signals induced by transcranial magnetic stimulation. In this study, we assess whether the FDI methodology can be also useful for analyzing resting state EEG signals, by characterizing the brain dynamic changes in different functional networks affected by schizophrenia, a mental disorder associated with dysfunction in the information flow dynamics in the spontaneous brain networks.

Integration-segregation dynamics in functional networks of individuals diagnosed with schizophrenia.

Schizophrenia has been associated with dysfunction in information integration/segregation dynamics. One of the neural networks whose role has been most investigated in schizophrenia is the default mode network (DMN). In this study, we have explored the possible alteration of integration and segregation dynamics in individuals diagnosed with schizophrenia with respect to healthy controls, based on the study of the topological properties of the graphs derived from the functional connectivity between the nodes of the DMN in the resting state.

Alpha and gamma EEG coherence during on-task and mind wandering states in schizophrenia.

Objective: Electroencephalographic (EEG) coherence is one of the most relevant physiological measures used to detect abnormalities in patients with schizophrenia. The present study applies a task-related EEG coherence approach to understand cognitive processing in patients with schizophrenia and healthy controls.

Methods: EEG coherence for alpha and gamma frequency bands was analyzed in a group of patients with schizophrenia and a group of healthy controls during the performance of an ecological task of sustained attention.

Examining Motor Anticipation in Handwriting as an Indicator of Motor Dysfunction in Schizophrenia.

Dysfunction in motor skills can be linked to alterations in motor processing, such as the anticipation of forthcoming graphomotor sequences. We expected that the difficulties in motor processing in schizophrenia would be reflected in a decrease of motor anticipation. In handwriting, motor anticipation concerns the ability to write a letter while processing information on how to produce the following letters.

Effects of pre-exposure and post-exposure of the context in habituation of the retraction response in earthworms (Lumbricidae).

The context specificity of habituation has been demonstrated in earthworms. After the habituation of the retraction response to a light, a recovery of the response was observed when subjects are re-habituated in a different context. Some theories assume that an association between the context and the unconditioned stimulus could underlie this result.

Local Oscillatory Brain Dynamics of Mind Wandering in Schizophrenia.

A number of studies have focused on brain dynamics underlying mind wandering (MW) states in healthy people. However, there is limited understanding of how the oscillatory dynamics accompanying MW states and task-focused states are characterized in clinical populations. In this study, we explored EEG local synchrony of MW associated with schizophrenia, under the premise that changes in attention that arise during MW are associated with a different pattern of brain activity.

Mutual Information of Multiple Rhythms for EEG Signals.

Electroencephalograms (EEG) are one of the most commonly used measures to study brain functioning at a macroscopic level. The structure of the EEG time series is composed of many neural rhythms interacting at different spatiotemporal scales. This interaction is often named as cross frequency coupling, and consists of transient couplings between various parameters of different rhythms.

Contextual specificity of habituation in earthworms.

This article reports the context specificity of habituation in earthworms ( family). Using earthworms as subjects-which are typically sensitive to odors-the present study sought to evaluate the context specificity of habituation by giving subjects repeated exposures to a bright light in one odorous context, after which they were presented again with the same stimulus in a different context. The recovery of responding in this second context was higher in the group where the odor of this context was different, in comparison with a control group for which the context was the same.

Differential Effects of Simulated Cortical Network Lesions on Synchrony and EEG Complexity.

Brain function has been proposed to arise as a result of the coordinated activity between distributed brain areas. An important issue in the study of brain activity is the characterization of the synchrony among these areas and the resulting complexity of the system. However, the variety of ways to define and, hence, measure brain synchrony and complexity has sometimes led to inconsistent results.

Neurocomputational Model of EEG Complexity during Mind Wandering.

Mind wandering (MW) can be understood as a transient state in which attention drifts from an external task to internal self-generated thoughts. MW has been associated with the activation of the Default Mode Network (DMN). In addition, it has been shown that the activity of the DMN is anti-correlated with activation in brain networks related to the processing of external events (e.

Effect of the average delay and mean connectivity of the Kuramoto model on the complexity of the output electroencephalograms.

Cognitive functions result from the interplay of distributed brain areas operating in large-scale networks. These networks can be modelled with a number of parameters that represent their underlying dynamics. One particularly fruitful model to simulate key aspects of the large-scale brain networks is the Kuramoto model, which simulates the phase evolution of several weakly coupled oscillators that represent the mean oscillatory behavior of different cortical regions.

Multiscale Lempel-Ziv complexity for EEG measures.

Objective: To demonstrate that the classical calculation of Lempel-Ziv complexity (LZC) has an important limitation when applied to EEGs with rapid rhythms, and to propose a multiscale approach that overcomes this limitation.

Methods: We have evaluated, both with simulated and real EEGs, whether LZC calculation neglects functional characteristics of rapid EEG rhythms. In addition, we have proposed a procedure to obtain multiple binarization sequences that yield a spectrum of LZC, and we have explored whether complexity would be better captured using this computation.

Selective intentional forgetting in adolescents with social anxiety disorder.

Anxiety in young adults has recently been linked to reduced capacities to inhibit the processing of non-affective perceptual distractors. However, no previous research has addressed the relationship between social anxiety disorder (SAD) and the ability to intentionally inhibit no longer relevant memories. In an experimental study with adolescents diagnosed with SAD and matched nonclinical controls, a selective directed forgetting procedure was used to assess the extent to which anxious individuals showed lower memory impairment for to-be-forgotten information than their non-anxious counterparts.