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. Despite the disparity of variables measured, fractal analysis has shown high sensitivity in discriminating patients from healthy controls. However, and because of this heterogeneity in measures, the results are not straightforward, and more studies are needed in this promising line.

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. This method allowed us to investigate interactions from a new perspective, where two or more rhythm interactions could be analyzed at the same time. We calculated the mutual information of multiple rhythms (MIMR) for EEG segments registered in resting state. Following previous studies, we focused on rhythm interactions between theta, alpha, and gamma. The results showed that, in general, MIMR was higher in patients than in controls for alpha-gamma and theta-gamma couplings. This finding of an increased coupling between slow and fast rhythms in schizophrenia may indicate complex interactions in the Default Mode Network (DMN) related to hyperactivation of internally guided cognition.

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. Considering the temporal dynamics of functional connectivity provides a more comprehensive understanding of brain networks' organization and how they change during different cognitive states. This temporal perspective would enhance our understanding of the underlying mechanisms of schizophrenia. In the present study, we will use measures based on graph theory to obtain dynamic and static indicators in order to evaluate differences in the functional connectivity of individuals diagnosed with SZ and healthy controls using an ecologically valid task. At the static level, patients showed alterations in their ability to segregate information, particularly in the default mode network (DMN). As for dynamic measures, patients showed reduced values in most metrics (segregation, integration, centrality, and resilience), reflecting a reduced number of dynamic states of brain networks. Our results show the utility of combining static and dynamic indicators of functional connectivity from EEG sensors.

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. We analyzed 31 resting-state EEG records of 150 s belonging to 20 healthy subjects (HC group) and 11 schizophrenia patients (SCZ group). Brain activations at each time sample were established by a thresholding process applied on the 15,002 sources modeled from the EEG signal. FDI was then computed individually in each resting-state functional network, averaging all the FDI values obtained using a sliding window of 1 s in the epoch. Compared to the HC group, significant lower values of FDI were obtained in the SCZ group for the auditory network (p < 0.05), the dorsal attention network (p < 0.05), and the salience network (p < 0.05). We found strong negative correlations (p < 0.01) between psychopathological scores and FDI in all resting-state networks analyzed, except the visual network. A receiver operating characteristic curve analysis also revealed that the FDI of the salience network performed very well as a potential feature for classifiers of schizophrenia, obtaining an area under curve value of 0.83. These results suggest that FDI is a promising method for assessing the complexity of the brain dynamics in different regions of interest, and from long resting-state EEG signals. Regarding the specific changes associated with schizophrenia in the dynamics of the spontaneous brain networks, FDI distinguished between patients and healthy subjects, and correlated to clinical variables.

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. Our results indicate that the patients show a diminution of the modularity of the DMN and a higher global efficiency, in sparse graphs. Our data emphasise the interest in studying temporal changes in network measures and are compatible with the hypothesis of randomization of functional networks in schizophrenia.

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. We compared EEG coherence when participants presented externally directed cognitive states (On-Task) and when they presented cognitive distraction episodes (Mind-Wandering). RESULTS: Results reflect cortical differences between groups (higher coherence for schizophrenia in the frontocentral and fronto-temporal regions, and higher coherence for healthy-controls in the postero-central regions), especially in the On-Task condition for the alpha band, compared to Mind-Wandering episodes. Few individual differences in gamma coherence were found. CONCLUSIONS: The current study provides evidence of neurophysiological differences underlying different cognitive states in schizophrenia and healthy controls. SIGNIFICANCE: Differences between groups may reflect inhibitory processes necessary for the successful processing of information, especially in the alpha band, given its role in cortical inhibition processes. Patients may activate compensatory inhibitory mechanisms when performing the task, reflected in increased coherence in fronto-temporal regions.

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. It is essential for fast and smooth handwriting, that is, for the automation of graphomotor gestures. In this study, we examined motor anticipation by comparing the kinematic characteristics of the first l in the bigrams ll and ln written on a digitiser. Previous studies indicated that the downstroke duration of the first l is modulated by the anticipation of the local constraints of the following letter. Twenty-four adult individuals with diagnosis of schizophrenia and 24 healthy adults participated in the study. The classic measures of duration (sec), trajectory (cm), and dysfluency (velocity peaks) were used for the kinematic analysis of the upstroke (US) and downstroke (DS). In the control group, the duration of the downstroke of the l was longer in ln than ll (US: ln = ll; DS: ln > ll) whereas no differences were found for the group with schizophrenia. Likewise, the control group showed a longer DS trajectory for the l of ln than ll in downstrokes, while the group of patients failed to show this effect. These results suggest that the motor alterations in patients with schizophrenia could also affect their ability for motor anticipation.

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. A series of experiments were conducted in order to test this issue. We assessed the potential disruptive effects of post-exposure (extinction effect) and pre-exposure of the context (latent inhibition effect) on the establishment of a context-US association. A recovery of response during subsequent rehabituation test was expected. The results of Experiment 1 showed that the extinction was effective, the post-exposure of the context after habituation produced a recovery of the retraction response. This result was replicated in Experiment 2 where the post-exposure condition was compared with a pre-exposure one. However, the pre-exposure to the context did not result in a recovery of the response in the rehabituation test, but also produced a general decrement on the response during the habituation training, that it has been interpreted as decrement in context's salience. In summary, these results suggest the involvement of associative and nonassociative processes in habituation learning.

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. To this end, we measured the power of EEG oscillations in different frequency bands, recorded while participants watched short video clips. In the group of participants diagnosed with schizophrenia, the power in MW states was significantly lower than during task-focused states, mainly in the frontal and posterior regions. However, in the group of healthy controls, the differences in power between the task-focused and MW states occurred exclusively in the posterior region. Furthermore, the power of the frequency bands during MW and during episodes of task-focused attention correlated with cognitive variables such as processing speed and working memory. These findings on dynamic changes of local synchronization in different frequency bands and areas of the cortex can improve our understanding of mental disorders, such as schizophrenia.

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. This coupling has been hypothesized to be a basic mechanism involved in cognitive functions. There are several methods to measure cross frequency coupling between two rhythms but no single method has been selected as the gold standard. Current methods only serve to explore two rhythms at a time, are computationally demanding, and impose assumptions about the nature of the signal. Here we present a new approach based on Information Theory in which we can characterize the interaction of more than two rhythms in a given EEG time series. It estimates the mutual information of multiple rhythms (MIMR) extracted from the original signal. We tested this measure using simulated and real empirical data. We simulated signals composed of three frequencies and background noise. When the coupling between each frequency component was manipulated, we found a significant variation in the MIMR. In addition, we found that MIMR was sensitive to real EEG time series collected with open vs. closed eyes, and intra-cortical recordings from epileptic and non-epileptic signals registered at different regions of the brain. MIMR is presented as a tool to explore multiple rhythms, easy to compute and without a priori assumptions.

Contextual specificity of habituation in earthworms.

This article reports the context specificity of habituation in earthworms (Lumbricidae 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. To provide further support for these findings, a second experiment was run using a within-subject design where all subjects were trained in both of the conditions. In this case, in addition to the light, vibration was used as a second stimulus. The subjects again displayed a higher increase in responding in the condition where the context was different (in odor) in comparison with the case in which the context was the same, thus replicating the results obtained in the first experiment. We discuss the implications of these results in the light of current data and learning theories. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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. Here, we study the relationship between synchrony and commonly used complexity estimators of electroencephalogram (EEG) activity and we explore how simulated lesions in anatomically based cortical networks would affect key functional measures of activity. We explored this question using different types of neural network lesions while the brain dynamics was modeled with a time-delayed set of 66 Kuramoto oscillators. Each oscillator modeled a region of the cortex (node), and the connectivity and spatial location between different areas informed the creation of a network structure (edges). Each type of lesion consisted on successive lesions of nodes or edges during the simulation of the neural dynamics. For each type of lesion, we measured the synchrony among oscillators and three complexity estimators (Higuchi's Fractal Dimension, Sample Entropy and Lempel-Ziv Complexity) of the simulated EEGs. We found a general negative correlation between EEG complexity metrics and synchrony but Sample Entropy and Lempel-Ziv showed a positive correlation with synchrony when the edges of the network were deleted. This suggests an intricate relationship between synchrony of the system and its estimated complexity. Hence, complexity seems to depend on the multiple states of interaction between the oscillators of the system. Our results can contribute to the interpretation of the functional meaning of EEG complexity.

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.g., Salience network, SN). In this study, we present a mean field model based on weakly coupled Kuramoto oscillators. We simulated the oscillatory activity of the entire brain and explored the role of the interaction between the nodes from the DMN and SN in MW states. External stimulation was added to the network model in two opposite conditions. Stimuli could be presented when oscillators in the SN showed more internal coherence (synchrony) than in the DMN, or, on the contrary, when the coherence in the SN was lower than in the DMN. The resulting phases of the oscillators were analyzed and used to simulate EEG signals. Our results showed that the structural complexity from both simulated and real data was higher when the model was stimulated during periods in which DMN was more coherent than the SN. Overall, our results provided a plausible mechanistic explanation to MW as a state in which high coherence in the DMN partially suppresses the capacity of the system to process external stimuli.

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. RESULTS: In our simulated signals, classical LZC did not capture modulations of a rapid component when a slower component of more amplitude was included in the signal. In real EEGs from healthy participants with eyes closed and eyes open, classical LZC calculation failed to show any difference between these two conditions. However, a multiscale LZC showed that complexity was lower for eyes closed than for eyes open conditions. CONCLUSIONS: As hypothesized, our new approximation captures the complexity of series with fast components masked by slower rhythms. SIGNIFICANCE: The method we introduce significantly improves LZC calculation, and it allows a better characterization of complexity of EEG signals.

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. Here, we inspected the dependency of two widespread nonlinear complexity markers, Sample Entropy (SampEn) and Lempel-Ziv Complexity (LZC), on EEG activity generated with a Kuramoto phase model where the time delay and connectivity strength among oscillators varied. We also added different levels of noise to the electroencephalogram (EEG) signals. Our results indicated that both complexity metrics reflected the changes in the delays and global synchrony levels, but we found that SampEn was slightly more sensitive to the state transition and its results were less affected by the presence of noise. These results help in the effort to understand the dynamics of EEG recordings and their relationship to large-scale networks.

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. The results revealed that while the nonclinical sample group demonstrated the ability to selectively forget when instructed, the anxious adolescents demonstrated good memory for to-be-forgotten material and therefore failed to forget. Interestingly, more severe SAD symptomatology inversely predicted a degree of forgetting. We conclude that the main difference between socially anxious and non-anxious participants is specifically related to the ability to intentionally forget and could reflect cognitive functioning that is associated with vulnerability to anxiety. Impairment of the ability to make unwanted memories less retrievable could prompt some individuals to initiate or maintain anxiety disorders. Future psychological treatments could benefit from including modules on memory control training.

Memory dynamics and decision making in younger and older adults

El objetivo principal de esta investigación fue estudiar si los cambios en accesibilidad de la información en la memoria influyen en las elecciones de las personas mayores de la misma forma que en los jóvenes. Para ello, adaptamos el paradigma de práctica en la recuperación para producir variaciones en la accesibilidad de la información en la memoria sobre la que posteriormente se tomaban decisiones. Basándonos en resultados previos, esperábamos obtener olvido inducido por la recuperación (OIR) y sesgo en la elección en los participantes jóvenes y en los mayores después de haber realizado práctica en la recuperación de algunos de los atributos estudiados sobre una alternativa de elección. Además, comparamos la ejecución de ambos grupos de edad en una condición experimental en la que la práctica en la recuperación fue reemplazada por práctica en lectura de los mismos atributos. Los resultados demostraron que aunque los dos grupos de edad mostraban OIR después de realizar la práctica en la recuperación, el sesgo en la decisión sólo se observaba en los participantes jóvenes. Curiosamente, ni los mayores ni los jóvenes mostraron olvido ni sesgo en la elección en la condición de práctica en lectura. Estos resultados amplían los encontrados previamente y sugieren que, bajo ciertas circunstancias, las personas mayores pueden tomar mejores decisiones que las más jóvenes(AU)

The main aim of this research was to study whether memory dynamics influence older people’s choices to the same extent as younger’s ones. To do so, we adapted the retrieval-practice paradigm to produce variations in memory accessibility of information on which decisions were made later. Based on previous results, we expected to observe retrieval-induced forgetting (RIF) and choice bias in younger and older participants after they engaged in retrieval practice of some studied attributes. In addition, we aimed to compare both age groups’ performance in an experimental condition in which retrieval practice was replaced by reading aloud practice of the same studied items. The results indicated that whereas both age groups showed RIF after performing retrieval practice, biased decisions were observed only in the younger participants. Interestingly, neither older nor younger people showed memory impairment or choice bias in the condition of reading practice. These results extend previous findings and support the idea that, under specific circumstances, elderly people may make better choices than younger people(AU)

Procesos de decisión con tiempo autoadministrado y limitado: ¿una respuesta adaptativa a la similitud, al formato y a la experiencia? / Decision processes with self-administered and limited time: an adaptative response to similarity, format and experience?

El objetivo principal de este trabajo es estudiar el posible efecto de la interacción entre variables de la tarea, de la persona y del contexto sobre el esfuerzo cognitivo y sobre la estrategia de decisión en tareas de elección multiatributo con dos alternativas. Con esta finalidad se realizaron dos experimentos en los que se manipularon simultáneamente el Formato de presentación de la información, la Similitud entre las alternativas del conjunto de elección y la Experiencia de los participantes con las tareas en condiciones de tiempo autoadministrado (Experimento 1) y en condiciones de presión de tiempo (Experimento 2). Los resultados de ambos experimentos ponen de manifiesto que la interacción entre las variables de interés afecta al esfuerzo cognitivo, medido a través de indicadores directos de la actividad, y que este efecto es diferente en función de la disponibilidad temporal para realizar las tareas. No obstante, el esfuerzo cognitivo evaluado a través de autoinfomes fue, en ambos experimentos, bastante bajo, lo que podría explicar la ausencia de cambios en las estrategias de decisión desplegadas por los participantes. (AU)

Efecto de las estrategias de decisión sobre el esfuerzo cognitivo / Estrategy choice effect on cognitive effort

Las personas disponemos de una amplia variedad de estrategias de decisión que difieren en el esfuerzo cognitivo que requieren y en la calidad de las decisiones que proporcionan. La teoría costes-beneficios propone que la estrategia que se utiliza en una situación concreta depende del balance entre el esfuerzo requerido y la calidad de la decisión resultante (Payne, Bettman y Johnson, 1993ª, 1993b). es este estudio comparamos, en tareas de elección con dos alternativas y cinco dimensiones, el esfuerzo cognitivo necesario para emplear la estrategia de igual ponderación (EIP), en la que el procesamiento de la información se basa en las alternativas y la estrategia de la suma de las diferencias (ESD), en la que el procesamiento se basa en los atributos. Los resultados obtenidos, muestran que el esfuerzo cognitivo es menor cuando se utiliza la EIP frente a cuando los sujetos usan la ESD (AU)

People have a wide variety of decision strategies. These strategies differ in the cognitive effort that is required and in the quality of the decisions that they yield. Some theories propose that the selection of the decision rule that will be used in specific situation, depend on the balance between the required effort and the quality of the resulting decision (Payne, Bettman and Johnson, 1993a, 1993b). In this study we compared the cognitive effort that is necessary to use the Equal weigh rule (EW) and additive difference rule (AD) in choice tasks with two alternatives and five dimensions. The results obtained support the hypothesis that different decision strategies require different amount of effort. Specifically, to use EW is less costly than AD in decision task with a reduced number of alternatives (AU)