Decreased spectral entropy modulation in patients with schizophrenia during a P300 task

Repetitive active and passive cognitive stimulations induce EEG changes in patients with Rett syndrome

BACKGROUND

Despite being considered a rare disease, Rett syndrome is a leading cause of profound cognitive impairment in females. This study explores game-based cognitive stimulation to enhance attention during learning tasks, offering an alternative treatment perspective.

METHODS

Fifteen diagnosed Rett syndrome girls participated in four 24-minute sessions, including a 5-minute initial resting state recording. Primary indicators for analysis included relative power and spectral entropy.

RESULTS

Significant findings indicated variations among conditions (resting state, active task, passive task) in response to stimulation. Notably, over four days, evolution occurred, characterized by decreasing delta power and increasing theta and beta power. Topographic maps confirmed these shifts, highlighting affected brain areas. Linear regression emphasized the most significant impact on the first day, with subsequent shifts towards higher frequencies, particularly during the resting state. By the fourth day, resting-state patterns resembled those during cognitive activities.

CONCLUSION

Findings suggest cognitive stimulation induces substantial EEG spectral changes, potentially linked to cognitive enhancements in Rett syndrome. The shift towards higher frequency bands and increased spectral entropy align with enhanced brain activation during cognitive sessions, underscoring the potential of cognitive stimulation therapies and calling for further research to optimize abilities in individuals with Rett syndrome.

IMPACT

Game-based cognitive stimulation induces substantial EEG changes in individuals with Rett syndrome, enhancing cognitive functions, notably attention during learning. This study conducts a distinctive examination, assessing the habituation paradigm through the combination of game-based cognitive stimulation and learning, providing valuable insights into enhancing attention in Rett syndrome. Impacting understanding of cognitive processes in Rett syndrome, this research reveals significant EEG variations during tasks, emphasizing the potential of cognitive stimulation for attention enhancement and the need for further research in tailored interventions.

Relation between task-related activity modulation and cortical inhibitory function in schizophrenia and healthy controls: a TMS-EEG study

Schizophrenia has been associated with a reduced task-related modulation of cortical activity assessed through electroencephalography (EEG). However, to the best of our knowledge, no study so far has assessed the underpinnings of this decreased EEG modulation in schizophrenia. A possible substrate of these findings could be a decreased inhibitory function, a replicated finding in the field. In this pilot study, our aim was to explore the association between EEG modulation during a cognitive task and the inhibitory system function in vivo in a sample including healthy controls and patients with schizophrenia. We hypothesized that the replicated decreased task-related activity modulation during a cognitive task in schizophrenia would be related to a hypofunction of the inhibitory system. For this purpose, 27 healthy controls and 22 patients with schizophrenia (including 13 first episodes) performed a 3-condition auditory oddball task from which the spectral entropy modulation was calculated. In addition, cortical reactivity-as an index of the inhibitory function-was assessed by the administration of 75 monophasic transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex. Our results replicated the task-related cortical activity modulation deficit in schizophrenia patients. Moreover, schizophrenia patients showed higher cortical reactivity following transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex compared to healthy controls. Cortical reactivity was inversely associated with EEG modulation, supporting the idea that a hypofunction of the inhibitory system could hamper the task-related modulation of EEG activity.

Functional network properties in schizophrenia and bipolar disorder assessed with high-density electroencephalography

BACKGROUND

The study of the cortical functional network properties in schizophrenia (SZ) may benefit from the use of graph theory parameters applied to high-density electroencephalography (EEG). Connectivity Strength (CS) assesses global synchrony of the network, and Shannon Graph Complexity (SGC) summarizes the network distribution of link weights and allows distinguishing between primary and secondary pathways. Their joint use may help in understanding the underpinnings of the functional network hyperactivation and task-related hypomodulation previously described in psychoses.

METHODS

We used 64-sensor EEG recordings during a P300 oddball task in 128 SZ patients (96 chronic, CR, and 32 first episodes, FE), as well as 46 bipolar disorder (BD) patients, and 92 healthy controls (HC). Pre-stimulus and modulation (task-response minus pre-stimulus windows values) of CS and SGC were assessed in the theta band (4-8 Hz) and the broadband (4-70 Hz).

RESULTS

Compared to HC, SZ patients (CR and FE) showed significantly higher pre-stimulus CS values in the broadband, and both SZ and BD patients showed lower theta-band CS modulation. SGC modulation values, both theta-band and broadband, were also abnormally reduced in CR patients. Statistically significant relationships were found in the theta band between SGC modulation and both CS pre-stimulus and modulation values in patients. CS altered measures in patients were additionally related to their cognitive outcome and negative symptoms. A primary role of antipsychotics in these results was ruled out.

CONCLUSIONS

Our results linking SGC and CS alterations in psychotic patients supported a hyperactive and hypomodulatory network mainly involving connections in secondary pathways.

Corollary Discharge Dysfunction as a Possible Substrate of Anomalous Self-experiences in Schizophrenia

BACKGROUND AND HYPOTHESIS

Corollary discharge mechanism suppresses the conscious auditory sensory perception of self-generated speech and attenuates electrophysiological markers such as the auditory N1 Event-Related Potential (ERP) during Electroencephalographic (EEG) recordings. This phenomenon contributes to self-identification and seems to be altered in people with schizophrenia. Therefore, its alteration could be related to the anomalous self-experiences (ASEs) frequently found in these patients.

STUDY DESIGN

To analyze corollary discharge dysfunction as a possible substrate of ASEs, we recorded EEG ERP from 43 participants with schizophrenia and 43 healthy controls and scored ASEs with the 'Inventory of Psychotic-Like Anomalous Self-Experiences' (IPASE). Positive and negative symptoms were also scored with the 'Positive and Negative Syndrome Scale for Schizophrenia' (PANSS) and with the 'Brief Negative Symptom Scale' (BNSS) respectively. The N1 components were elicited by two task conditions: (1) concurrent listening to self-pronounced vowels (talk condition) and (2) subsequent non-concurrent listening to the same previously self-uttered vowels (listen condition).

STUDY RESULTS

The amplitude of the N1 component elicited by the talk condition was lower compared to the listen condition in people with schizophrenia and healthy controls. However, the difference in N1 amplitude between both conditions was significantly higher in controls than in schizophrenia patients. The values of these differences in patients correlated significantly and negatively with the IPASE, PANSS, and BNSS scores.

CONCLUSIONS

These results corroborate previous data relating auditory N1 ERP amplitude with altered corollary discharge mechanisms in schizophrenia and support corollary discharge dysfunction as a possible underpinning of ASEs in this illness.

Electroencephalography for the Study of the Auditory P300 Evoked Potential and Derived Measurements

Electroencephalography (EEG) is a widely used tool in neuropsychiatry research. The most used measurements in EEG are the amplitude and latency of the cortical electrophysiological activity in response to stimulus, known as evoked potentials. Besides potentials, time/frequency analysis is also used to obtain information on global fluctuations of the recordings, which evoked potentials do not provide. Time/frequency analysis results in different values known as derived measures. In this work, a brief introduction to evoked potentials and time/frequency analyses in schizophrenia is given, focusing on P300, noise power, and spectral entropy. Finally, a detailed description is given on how to obtain EEG recordings, evoked potentials, and derived measures.

Relation between EEG resting-state power and modulation of P300 task-related activity in theta band in schizophrenia

There is some consistency in previous EEG findings that patients with schizophrenia have increased resting-state cortical activity. Furthermore, in previous work, we have provided evidence that there is a deficit in the modulation of bioelectrical activity during the performance of a P300 task in schizophrenia. Our hypothesis here is that a basal hyperactivation would be related with altered ability to change or modulate cortical activity during a cognitive task. However, no study so far, to the best of our knowledge, has studied the association between resting-state activity and task-related modulation. With this aim, we used a dual EEG paradigm (resting state and oddball task for elicitation of the P300 evoked potential) in a sample of patients with schizophrenia (n = 100), which included a subgroup of patients with first episode psychosis (n = 30), as well as a group of healthy controls (n = 93). The study measures were absolute power for resting-state; and spectral entropy (SE) and connectivity strength (CS) for P300-task data, whose modulation had been previously found to be altered in schizophrenia. Following the literature on P300, we focused our study on the theta frequency band. As expected, our results showed an increase in resting state activity and altered task-related modulation. Moreover, we found an inverse relationship between the amount of resting-state activity and modulation of task-related activity. Our results confirm our hypothesis and support the idea that a greater amount of resting theta-band synchrony could hamper the modulation of signal regularity (quantified by SE) and activity density (measured by CS) during the P300 task performance. This association was found in both patients and controls, suggesting the existence of a common mechanism and a possible ceiling effect in schizophrenia patients in relation to a decreased inhibitory function that limits their cortical reactivity to the task.

Cognitive stimulation has potential for brain activation in individuals with Rett syndrome

BACKGROUND

Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS.

METHODS

Twenty female children diagnosed with RS were included in the analysis. Girls with RS conducted a cognitive task using an eye-tracker designed to evaluate access and choice skills. EEG data were acquired during the experimental procedure including two 10-min baseline stages before and after the task. Topographical changes of several EEG spectral markers including absolute and relative powers, Brain Symmetry Index and entropy were assessed.

RESULTS

Topographic significance probability maps suggested statistical decreases on delta activity and increases on beta rhythm associated with the cognitive task. Entropy increased during and after the task, likely related to more complex brain activity. A significant positive interaction was obtained between Brain Symmetry Index and age showing that the improvement of interhemispheric symmetry was higher in younger girls (5-10 years).

CONCLUSIONS

According to our findings, significant alterations of brain rhythms were observed during and after cognitive stimulation, suggesting that cognitive stimulation may have effects on brain activity beyond the stimulation period. Finally, our promising results also showed an increase brain symmetry that was especially relevant for the younger group. This could suggest an interaction of the eye-tracking cognitive task; however, further studies in this field are needed to assess the relation between brain asymmetries and age.

Schizophrenia induces abnormal frequency-dependent patterns of dynamic brain network reconfiguration during an auditory oddball task

OBJECTIVE

Schizophrenia is a psychiatric disorder that has been shown to disturb the dynamic top-down processing of sensory information. Various imaging techniques have revealed abnormalities in brain activity associated with this disorder, both locally and between cerebral regions. However, there is increasing interest in investigating dynamic network response to novel and relevant events at the network level during an attention-demanding task with high-temporal-resolution techniques. The aim of the work was: (i) to test the capacity of a novel algorithm to detect recurrent brain meta-states from auditory oddball task recordings; and (ii) to evaluate how the dynamic activation and behavior of the aforementioned meta-states were altered in schizophrenia, since it has been shown to impair top-down processing of sensory information.

APPROACH

A novel unsupervised method for the detection of brain meta-states based on recurrence plots and community detection algorithms, previously tested on resting-state data, was used on auditory oddball task recordings. Brain meta-states and several properties related to their activation during target trials in the task were extracted from electroencephalography (EEG) data from patients with schizophrenia and cognitively healthy controls.

MAIN RESULTS

The methodology successfully detected meta-states during an auditory oddball task, and they appeared to show both frequency-dependent time-locked and non-time-locked activity with respect to the stimulus onset. Moreover, patients with schizophrenia displayed higher network diversity, and showed more sluggish meta-state transitions, reflected in increased dwell times, less complex meta-state sequences, decreased meta-state space speed, and abnormal ratio of negative meta-state correlations.

SIGNIFICANCE

Abnormal cognition in schizophrenia is also reflected in decreased brain flexibility at the dynamic network level, which may hamper top-down processing, possibly indicating impaired decision-making linked to dysfunctional predictive coding. Moreover, the results showed the ability of the methodology to find meaningful and task-relevant changes in dynamic connectivity and pathology-related group differences.

Shoulder electromyography-based indicators to assess manifestation of muscle fatigue during laboratory-simulated manual handling task

Muscle fatigue is a risk factor for developing shoulder musculoskeletal disorders. The aim of this study was to identify shoulder electromyographic indicators that are most indicative of muscle fatigue during a laboratory simulated manual handling task. Thirty-two participants were equipped with electromyographic electrodes on 10 shoulder muscles and moved boxes for 45-minutes. The modified rate of perceived exertion (mRPE) was assessed every 5-minutes and multivariate linear regressions were performed between myoelectric manifestation of fatigue (MMF) and the mRPE scores. During a manual handling task representative of industry working conditions, spectral entropy, median frequency, and mobility were the electromyographic indicators that explained the largest percentage of the mRPE. Overall, the deltoids, biceps and upper trapezius were the muscles that most often showed significant changes over time in their electromyographic indicators. The combination of these three indicators may improve the accuracy for the assessment of MMF during manual handling. Practitioner Summary: To date, muscle fatigue has primarily been assessed during tasks done to exhaustion, which are not representative of typical working conditions. During a manual handling task representative of industry working conditions, EMG-derived spectral entropy, and median frequency, both extracted from time-frequency analysis, and mobility extracted from time domain, were the best indicators of the manifestation of muscle fatigue.

Search for schizophrenia and bipolar biotypes using functional network properties

INTRODUCTION

Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements.

METHODS

A clustering analysis was performed using the electroencephalogram-based network parameters derived from graph-theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons.

RESULTS

We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path-length, and lower small-world index compared to controls. The modulation of clustering coefficient and path-length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients´ clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation.

CONCLUSION

These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.

Influence of PICALM and CLU risk variants on beta EEG activity in Alzheimer's disease patients

PICALM and CLU genes have been linked to alterations in brain biochemical processes that may have an impact on Alzheimer’s disease (AD) development and neurophysiological dynamics. The aim of this study is to analyze the relationship between the electroencephalographic (EEG) activity and the PICALM and CLU alleles described as conferring risk or protective effects on AD patients and healthy controls. For this purpose, EEG activity was acquired from: 18 AD patients and 12 controls carrying risk alleles of both PICALM and CLU genes, and 35 AD patients and 12 controls carrying both protective alleles. Relative power (RP) in the conventional EEG frequency bands (delta, theta, alpha, beta, and gamma) was computed to quantify the brain activity at source level. In addition, spatial entropy (SE) was calculated in each band to characterize the regional distribution of the RP values throughout the brain. Statistically significant differences in global RP and SE at beta band (p-values < 0.05, Mann–Whitney U-test) were found between genotypes in the AD group. Furthermore, RP showed statistically significant differences in 58 cortical regions out of the 68 analyzed in AD. No statistically significant differences were found in the control group at any frequency band. Our results suggest that PICALM and CLU AD-inducing genotypes are involved in physiological processes related to disruption in beta power, which may be associated with physiological disturbances such as alterations in beta-amyloid and neurotransmitter metabolism.

Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia

Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.

Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis

Schizophrenia and bipolar disorder include patients with different characteristics, which may hamper the definition of biomarkers. One of the dimensions with greater heterogeneity among these patients is cognition. Recent studies support the identification of different patients' subgroups along the cognitive domain using cluster analysis. Our aim was to validate clusters defined on the basis of patients' cognitive status and to assess its relation with demographic, clinical and biological measurements. We hypothesized that subgroups characterized by different cognitive profiles would show differences in an array of biological data. Cognitive data from 198 patients (127 with chronic schizophrenia, 42 first episodes of schizophrenia and 29 bipolar patients) were analyzed by a K-means cluster approach and were compared on several clinical and biological variables. We also included 155 healthy controls for further comparisons. A two-cluster solution was selected, including a severely impaired group and a moderately impaired group. The severely impaired group was associated with higher illness duration and symptoms scores, lower thalamus and hippocampus volume, lower frontal connectivity and basal hypersynchrony in comparison to controls and the moderately impaired group. Moreover, both patients' groups showed lower cortical thickness and smaller functional connectivity modulation than healthy controls. This study supports the existence of different cognitive subgroups within the psychoses with different neurobiological underpinnings.

Deficits of entropy modulation of the EEG: A biomarker for altered function in schizophrenia and bipolar disorder?

BACKGROUND

The synchronized activity of distributed neural assemblies — reflected in the electroencephalogram (EEG) — underpins mental function. In schizophrenia, modulation deficits of EEG spectral content during a P300 task have been replicated. The effects of treatment, chronicity and specificity in these deficits and their possible relationship with anatomic connectivity remain to be explored.

METHODS

We assessed spectral entropy modulation of the EEG during a P300 task in 79 patients with schizophrenia (of those, 31 werein their first episode), 29 patients with bipolar disorder and 48 healthy controls. Spectral entropy values summarize EEG characteristics by quantifying the irregularity of spectral content. In a subsample, we calculated the network architecture of structural connectivity using diffusion tensor imaging and graph-theory parameters.

RESULTS

We found significant spectral entropy modulation deficits with task performance in patients with chronic or first-episode schizophrenia and in patients with bipolar disorder, without significant pre-stimulus spectral entropy differences. The deficits were unrelated to treatment doses, and spectral entropy modulation did not differ between patients taking or not taking antipsychotics, lithium, benzodiazepines or antidepressants. Structural connectivity values were unrelated to spectral entropy modulation. In patients with schizophrenia, spectral entropy modulation was inversely related to negative symptoms and directly related to verbal memory.

LIMITATIONS

All patients were taking medication. Patients with bipolar disorder were euthymic and chronic. The cross-sectional nature of this study prevented a more thorough analysis of state versus trait criteria for spectral entropy changes.

CONCLUSION

Spectral entropy modulation with task performance is decreased in patients with schizophrenia and bipolar disorder. This deficit was not an effect of psychopharmacological treatment or structural connectivity and might reflect a deficit in the synchronization of the neural assemblies that underlie cognitive activity.

Identificacion of MRI-based psychosis subtypes: Replication and refinement

The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.

Connectivity strength of the EEG functional network in schizophrenia and bipolar disorder

The application of graph theory measures in the study of functional brain networks allows for the description of their general properties and their alterations in mental illness. Among these measures, connectivity strength (CS) estimates the degree of functional connectivity of the whole network. Previous studies in schizophrenia patients have reported higher baseline CS values and modulation deficits in EEG spectral properties during cognitive activity. The specificity of these alterations and their relationships with pharmacological treatments remain unknown. Therefore, in the present study, we assessed functional CS on EEG-based brain networks in 79 schizophrenia and 29 bipolar patients in addition to 63 healthy controls. The subjects performed a P300 task during the EEG recordings from which the pre-stimulus and the task-related modulation CS values were computed in the global and theta bands. These values were compared between the groups and between the patients who had and had not received different treatments. The global band pre-stimulus CS was significantly higher in the schizophrenia group compared with the bipolar and control groups. Theta band CS modulation was decreased in schizophrenia and bipolar patients. Treatment with antipsychotics, lithium, benzodiazepines, and anticonvulsants did not significantly alter these CS values. The first-episode and chronic schizophrenia patients did not show significant differences in CS values. Higher global band pre-stimulus CS values were associated with worse general cognition in schizophrenia patients. These data support increased connectivity in the whole-brain network that is specific to schizophrenia and suggest a general hyper-synchronized basal state that might hamper cognition in this syndrome.

Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals

Our aim is to explore if cognitive challenge combined with objective physiology can reveal abnormal frontal alpha event-related desynchronization (ERD), in early Alzheimer's disease (AD). We used quantitative electroencephalography (qEEG) to investigate brain activities during N-back working memory (WM) processing at two different load conditions (N = 0 or 2) in an aging cohort. We studied 60-100 year old participants, with normal cognition, and who fits one of two subgroups from cerebrospinal fluid (CSF) proteins: cognitively healthy (CH) with normal amyloid/tau ratio (CH-NAT, n = 10) or pathological amyloid/tau ratio (CH-PAT, n = 14). We recorded behavioral performances, and analyzed alpha power and alpha spectral entropy (SE) at three occasions: during the resting state, and at event-related desynchronization (ERD) [250 ~ 750 ms] during 0-back and 2-back. During 0-back WM testing, the behavioral performance was similar between the two groups, however, qEEG notably differentiated CH-PATs from CH-NATs on the simple, 0-back testing: Alpha ERD decreased from baseline only in the parietal region in CH-NATs, while it decreased in all brain regions in CH-PATs. Alpha SE did not change in CH-NATs, but was increased from baseline in the CH-PATs in frontal and left lateral regions (p<0.01), and was higher in the frontal region (p<0.01) of CH-PATs compared to CH-NATs. The alpha ERD and SE analyses suggest there is frontal lobe dysfunction during WM processing in the CH-PAT stage. Additional power and correlations with behavioral performance were also explored. This study provide pilot information to further evaluate whether this biomarker has clinical significance.

Altered predictive capability of the brain network EEG model in schizophrenia during cognition

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia.

EEG Multiscale Complexity in Schizophrenia During Picture Naming

Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.

Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.

Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).

Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.

Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.

Deception Decreases Brain Complexity

Extensive evidence suggests the feasibility of lie detection using electroencephalograms (EEGs). However, it is largely unknown whether there are any differences in the nonlinear features of EEGs between guilty and innocent subjects. In this study, we proposed a complexity-based method to distinguish lying from truth telling. A total of 35 participants were randomly divided into two groups, and their EEG signals were recorded with 14 electrodes. Averages for sequential sets of five trials were first calculated for the probe responses within each subject. Next, a common wavelet entropy (WE) measure and an improved one were used to quantify complexity from each five-trial average. The results show that for both measures, the WE values in the guilty subjects are statistically lower than those in the innocent subjects for most of the 14 electrodes. More importantly, using the improved measure, the difference in WE between the two groups of subjects significantly increases for 11 brain regions compared with the values from the common measure. Finally, the highest balanced classification accuracy, 89.64%, is achieved when using the combined WE feature vector in five brain regions from the sites of Pz, P3, C4, Cz, and C3. Our findings indicate that the lying task elicits a more ordered brain activity in some specific brain regions than the task of telling the truth. This study not only demonstrates that improved WE measurements could be a powerful quantitative index for detecting lying but also sheds light on the brain mechanisms underlying deceptive behaviors.

Exploring non-stationarity patterns in schizophrenia: neural reorganization abnormalities in the alpha band

OBJECTIVE

The aim of this paper was to characterize brain non-stationarity during an auditory oddball task in schizophrenia (SCH). The level of non-stationarity was measured in the baseline and response windows of relevant tones in SCH patients and healthy controls.

APPROACH

Event-related potentials were recorded from 28 SCH patients and 51 controls. Non-stationarity was estimated in the conventional electroencephalography frequency bands by means of Kullback-Leibler divergence (KLD). Relative power (RP) was also computed to assess a possible complementarity with KLD.

MAIN RESULTS

Results showed a widespread statistically significant increase in the level of non-stationarity from baseline to response in all frequency bands for both groups. Statistically significant differences in non-stationarity were found between SCH patients and controls in beta-2 and in the alpha band. SCH patients showed more non-stationarity in the left parieto-occipital region during the baseline window in the beta-2 band. A leave-one-out cross validation classification study with feature selection based on binary stepwise logistic regression to discriminate between SCH patients and controls provided a positive predictive value of 72.73% and negative predictive value of 78.95%.

SIGNIFICANCE

KLD can characterize transient neural reorganization during an attentional task in response to novelty and relevance. Our findings suggest anomalous reorganization of neural dynamics in SCH during an oddball task. The abnormal frequency-dependent modulation found in SCH patients during relevant tones is in agreement with the hypothesis of aberrant salience detection in SCH. The increase in non-stationarity in the alpha band during the active task supports the notion that this band is involved in top-down processing. The baseline differences in the beta-2 band suggest that hyperactivation of the default mode network during attention tasks may be related to SCH symptoms. Furthermore, the classification improved when features from both KLD and RP were used, supporting the idea that these measures can be complementary.

Deficit of entropy modulation of the EEG in schizophrenia associated to cognitive performance and symptoms. A replication study

Spectral entropy (SE) is a measurement from information theory field that provides an estimation of EEG regularity and may be useful as a summary of its spectral properties. Previous studies using small samples reported a deficit of EEG entropy modulation in schizophrenia during cognitive activity. The present study is aimed at replicating this finding in a larger sample, to explore its cognitive and clinical correlates and to discard antipsychotic treatment as the main source of that deficit. We included 64 schizophrenia patients (21 first episodes, FE) and 65 healthy controls. We computed SE during performance of an odd-ball paradigm, at the windows prior (-300 to 0ms) and following (150 to 450ms) stimulus presentation. Modulation of SE was defined as the difference between post- and pre-stimulus windows. In comparison to controls, patients showed a deficit of SE modulation over frontal and central regions, also shown by FE patients. Baseline SE did not differ between patients and controls. Modulation deficit was directly associated with cognitive deficits and negative symptoms, and inversely with positive symptoms. SE modulation was not related to antipsychotic doses. Patients also showed a smaller change of median frequency (i.e., smaller slowing of oscillatory activity) of the EEG from pre- to post-stimulus windows. These results support that a deficit of fast modulation contributes to cognitive deficits and symptoms in schizophrenia patients.

Relations between structural and EEG-based graph metrics in healthy controls and schizophrenia patients

Our aim was to assess structural and functional networks in schizophrenia patients; and the possible prediction of the latter based on the former. The possible dependence of functional network properties on structural alterations has not been analyzed in schizophrenia. We applied averaged path-length (PL), clustering coefficient, and density (D) measurements to data from diffusion magnetic resonance and electroencephalography in 39 schizophrenia patients and 79 controls. Functional data were collected for the global and theta frequency bands during an odd-ball task, prior to stimulus delivery and at the corresponding processing window. Connectivity matrices were constructed from tractography and registered cortical segmentations (structural) and phase-locking values (functional). Both groups showed a significant electroencephalographic task-related modulation (change between prestimulus and response windows) in the global and theta bands. Patients showed larger structural PL and prestimulus density in the global and theta bands, and lower PL task-related modulation in the theta band. Structural network values predicted prestimulus global band values in controls and global band task-related modulation in patients. Abnormal functional values found in patients (prestimulus density in the global and theta bands and task-related modulation in the theta band) were not predicted by structural data in this group. Structural and functional network abnormalities respectively predicted cognitive performance and positive symptoms in patients. Taken together, the alterations in the structural and functional theta networks in the patients and the lack of significant relations between these alterations, suggest that these types of network abnormalities exist in different groups of schizophrenia patients.

Deficits of entropy modulation in schizophrenia are predicted by functional connectivity strength in the theta band and structural clustering

Spectral entropy (SE) allows comparing task-related modulation of electroencephalogram (EEG) between patients and controls, i.e. spectral changes of the EEG associated to task performance. A SE modulation deficit has been replicated in different schizophrenia samples. To investigate the underpinnings of SE modulation deficits in schizophrenia, we applied graph-theory to EEG recordings during a P300 task and fractional anisotropy (FA) data from diffusion tensor imaging in 48 patients (23 first episodes) and 87 healthy controls. Functional connectivity was assessed from phase-locking values among sensors in the theta band, and structural connectivity was based on FA values for the tracts connecting pairs of regions. From those data, averaged clustering coefficient (CLC), characteristic path-length (PL) and connectivity strength (CS, also known as density) were calculated for both functional and structural networks. The corresponding functional modulation values were calculated as the difference in SE and CLC, PL and CS between the pre-stimulus and response windows during the task. The results revealed a higher functional CS in the pre-stimulus window in patients, predictive of smaller modulation of SE in this group. The amount of increase in theta CS from pre-stimulus to response related to SE modulation in patients and controls. Structural CLC was associated with SE modulation in the patients. SE modulation was predictive of negative symptoms, whereas CLC and PL modulation was associated with cognitive performance in the patients. These results support that a hyperactive functional connectivity and/or structural connective deficits in the patients hamper the dynamical modulation of connectivity underlying cognition.

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Functional connectivity strength and structural clustering properties were associated to the deficit in SE modulation in schizophrenia.

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Functional connectivity strength in the theta band was larger in the baseline in the patients.

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A hyperactive pre-stimulus state hampers the capacity for adequately modulating neural activity across the brain in schizophrenia.

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The possible basis for that problem may be investigated to identify therapeutic targets.

Oxiracetam or fastigial nucleus stimulation reduces cognitive injury at high altitude

BACKGROUND

Cognitive impairment is common in people travelling to high altitude. Oxiracetam and electrical stimulation of cerebellar fastigial nucleus may have beneficial impacts. This study was to investigate the effects of preconditioning with Oxiracetam or fastigial nucleus stimulation (FNS) on cognitive decline following the ascension to high altitude.

METHODS

The study was conducted on 60 male military voluntary members who were divided into control group, Oxiracetam group, and fastigial nucleus stimulation group. Transcranial doppler sonography, auditory evoked potential, electroencephalogram (EEG), and cognitive assessments were performed.

RESULTS

People could still suffer cognitive dysfunction at 4,000 m high altitude despite that they have lived at 1,800 m altitude for several years. The 4,000 m altitude environment also prolonged P300 and N200 latencies. Both Oxiracetam and FNS improved cognitive function, reduced the prolonged latencies of Event Related Potentials (P300 and N200), decreased the average velocity of brain arteries, and enhanced EEG power spectral entropy at 4,000 m altitude.

CONCLUSIONS

Neurophysiological evidences suggest the underlying mechanism of cognitive impairments. Both Oxiracetam and FNS can reduce cognitive decline post arrival at high altitude. They could be a potential pretreatment method for cognitive dysfunction resulted from high altitude.

Novel measure of the weigh distribution balance on the brain network: graph complexity applied to schizophrenia

The aim of this study was to assess brain complexity dynamics in schizophrenia (SCH) patients during an auditory oddball task. For this task, we applied a novel graph measure based on the balance of the node weights distribution. Previous studies applied complexity parameters that were strongly dependent on network topology. This could bias the results, as well as making correction techniques, such as surrogating process, necessary. In the present study, we applied a novel graph complexity measure derived from the information theory: Shannon Graph Complexity (SGC). Complexity patterns from electroencephalographic recordings of 20 healthy controls and 20 SCH patients during an auditory oddball task were analyzed. Results showed a significantly more pronounced decrease of SGC for controls than for SCH patients during the cognitive task. These findings suggest an important change in the brain configuration towards a more balanced network, mainly in the connections related to long-range interactions. Since these changes are significantly more pronounced in controls, a deficit in the neural network reorganization can be associated with SCH. In addition, an accuracy of 72.5% was obtained using a receiver operating characteristic curve with a leave-one-out cross-validation procedure. The independence of network topology has been demonstrated by the novel complexity measure proposed in this study, therefore, it complements traditional graph measures as a means to characterize brain networks.

Analysis of the non-stationarity of neural activity during an auditory oddball task in schizophrenia

The aim of this study was to characterize brain dynamics during an auditory oddball task. For this purpose, a measure of the non-stationarity of a given time-frequency representation (TFR) was applied to electroencephalographic (EEG) signals. EEG activity was acquired from 20 schizophrenic (SCH) patients and 20 healthy controls while they underwent a three-stimulus auditory oddball task. The Degree of Stationarity (DS), a measure of the non-stationarity of the TFR, was computed using the continuous wavelet transform. DS was calculated for both the baseline [-300 0] ms and active task [150 550] ms windows of a P300 auditory oddball task. Results showed a statistically significant increase (p<;0.05) in non-stationarity for controls during the cognitive task in the central region, while less widespread statistically significant differences were obtained for SCH patients, especially in the beta-2 and gamma bands. Our findings support the relevance of DS as a means to study cerebral processing in SCH. Furthermore, the lack of statistically significant changes in DS for SCH patients suggests an abnormal reorganization of neural dynamics during an oddball task.

Association between electroencephalographic modulation, psychotic-like experiences and cognitive performance in the general population

AIM

An association between deficit of electroencephalographic (EEG) modulation during an odd-ball task and psychotic symptoms has been described in clinical samples, in agreement with the proposed role for altered salience in psychosis. To discard the possible influence of medication, the relationship between psychotic-like experiences and EEG modulation in the general population was explored.

METHODS

EEG and psychotic-like experiences were assessed in 194 healthy subjects during a P300 paradigm. EEG modulation was assessed as changes from pre-stimulus to response windows in spectral entropy (SE, a measurement of signal irregularity), median frequency (MF, a quantifier of the frequency distribution of oscillatory activity) and theta, alpha, beta-1, beta-2 and gamma relative power (RP, a summary of the distribution of spectral components).

RESULTS

A significant widespread decrease in SE and MF from baseline to response was found, with a significant increase in RP for theta and a decrease for higher frequency bands, supporting an increase in EEG regularity and a slowing of brain oscillations during the response. Furthermore, a significant association was found between SE modulation and distress of negative psychotic-like experiences, as well as between verbal memory and RP modulation for beta-1. Performance in verbal fluency was associated with the increase in theta RP during the response.

CONCLUSION

EEG irregularity of healthy subjects decreased at the expense of a larger contribution of theta RP and a decreased contribution of fast frequency bands. Subjects with smaller modulation showed poorer cognitive scores and greater distress of negative psychotic-like experiences.

Abnormal Neural Oscillations in Schizophrenia Assessed by Spectral Power Ratio of MEG During Word Processing

This study investigated spectral power of neural oscillations associated with word processing in schizophrenia. Magnetoencephalography (MEG) data were acquired from 12 schizophrenia patients and 10 healthy controls during a visual word processing task. Two spectral power ratio (SPR) feature sets: the band power ratio (BPR) and the window power ratio (WPR) were extracted from MEG data in five frequency bands, four time windows of word processing, and at locations covering whole head. Cluster-based nonparametric permutation tests were employed to identify SPRs that show significant between-group difference. Machine learning based feature selection and classification techniques were then employed to select optimal combinations of the significant SPR features, and distinguish schizophrenia patients from healthy controls. We identified three BPR clusters and three WPR clusters that show significant oscillation power difference between groups. These include the theta/delta, alpha/delta and beta/delta BPRs during base-to-encode and encode time windows, and the beta band WPR from base to encode and from encode to post-encode windows. Based on two WPR and one BPR features combined, over 95% cross-validation classification accuracy was achieved using three different linear classifiers separately. These features may have potential as quantitative markers that discriminate schizophrenia patients and healthy controls; however, this needs further validation on larger samples.

Noise power associated with decreased task-induced variability of brain electrical activity in schizophrenia

In schizophrenia, both increased baseline metabolic and electroencephalographic (EEG) activities as well as decreased task-related modulation of neural dynamics have been reported. Noise power (NP) can measure the background EEG activity during task performance, and Shannon entropy (SE) is useful for quantifying the global modulation of EEG activity with a high temporal resolution. In this study, we have assessed the possible relationship between increased NP in theta and gamma bands and decreased SE modulation in 24 patients with schizophrenia and 26 controls over the parietal and central regions during a P300 task. SE modulation was calculated as the change from baseline to the active epoch (i.e., 150-550 ms following the target stimulus onset). Patients with schizophrenia displayed statistically significant higher NP values and lower SE modulation than healthy controls. We found a significant association between gamma NP and SE in all of the participants. Specifically, a NP increase in the gamma band was followed by a decrease in SE change. These results support the notion that an excess of gamma activity, unlocked to the task being performed, is accompanied by a decreased modulation of EEG activity in schizophrenia.

Auditory P3a and P3b neural generators in schizophrenia: An adaptive sLORETA P300 localization approach

The present study investigates the neural substrates underlying cognitive processing in schizophrenia (Sz) patients. To this end, an auditory 3-stimulus oddball paradigm was used to identify P3a and P3b components, elicited by rare-distractor and rare-target tones, respectively. Event-related potentials (ERP) were recorded from 31 Sz patients and 38 healthy controls. The P3a and P3b brain-source generators were identified by time-averaging of low-resolution brain electromagnetic tomography (LORETA) current density images. In contrast with the commonly used fixed window of interest (WOI), we proposed to apply an adaptive WOI, which takes into account subjects' P300 latency variability. Our results showed different P3a and P3b source activation patterns in both groups. P3b sources included frontal, parietal and limbic lobes, whereas P3a response generators were localized over bilateral frontal and superior temporal regions. These areas have been related to the discrimination of auditory stimulus and to the inhibition (P3a) or the initiation (P3b) of motor response in a cognitive task. In addition, differences in source localization between Sz and control groups were observed. Sz patients showed lower P3b source activity in bilateral frontal structures and the cingulate. P3a generators were less widespread for Sz patients than for controls in right superior, medial and middle frontal gyrus. Our findings suggest that target and distractor processing involves distinct attentional subsystems, both being altered in Sz. Hence, the study of neuroelectric brain information can provide further insights to understand cognitive processes and underlying mechanisms in Sz.

Decreased entropy modulation of EEG response to novelty and relevance in schizophrenia during a P300 task

The analysis of the interaction between novelty and relevance may be of interest to test the aberrant salience hypothesis of schizophrenia (SCH). In comparison with other neuroimaging techniques, such as functional magnetic resonance imaging, electroencephalography (EEG) provides high temporal resolution. Therefore, EEG is useful to analyze transient dynamics in neural activity, even in the range of milliseconds. In this study, EEG activity from 31 patients with SCH and 38 controls was analyzed using Shannon spectral entropy (SE) and median frequency (MF). The aim of the study was to quantify differences between distractor (i.e., novelty) and target (i.e., novelty and relevance) tones in an auditory oddball paradigm. Healthy controls displayed a larger SE decrease in response to target stimulus than in response to distractor tones. SE decrease was accompanied by a significant and widespread reduction of MF (i.e., a significant slowing of EEG activity). In comparison with controls, patients showed a significant reduction of changes in SE in response to both target and distractor tones. These differences were also observed in patients that only received a minimal treatment prior to EEG recording. Furthermore, significant changes in SE were inversely correlated to positive and total symptoms severity for SCH patients. Our findings support the notion that SCH is associated with a reduced response to both novelty and relevance during an auditory P300 task.

ANALYSIS OF SURFACE EMG SIGNALS UNDER FATIGUE AND NON-FATIGUE CONDITIONS USING B-DISTRIBUTION BASED QUADRATIC TIME FREQUENCY DISTRIBUTION

In this paper, an attempt has been made to analyze surface electromyography (sEMG) signals under non-fatigue and fatigue conditions using time-frequency based features. The sEMG signals are recorded from biceps brachii muscle of 50 healthy volunteers under well-defined protocol. The pre-processed signals are divided into six equal epochs. The first and last segments are considered as non-fatigue and fatigue zones respectively. Further, these signals are subjected to B-distribution based quadratic time-frequency distribution (TFD). Time frequency based features such as instantaneous median frequency (IMDF) and instantaneous mean frequency (IMNF) are extracted. The expression of spectral entropy is modified to obtain instantaneous spectral entropy (ISPEn) from the time-frequency spectrum. The results show that all the extracted features are distinct in both conditions. It is also observed that the values of all features are higher in non-fatigue zone compared to fatigue condition. It appears that this method is useful in analysing various neuromuscular conditions using sEMG signals.

A comparative study of event-related coupling patterns during an auditory oddball task in schizophrenia

OBJECTIVE

The aim of this research is to explore the coupling patterns of brain dynamics during an auditory oddball task in schizophrenia (SCH).

APPROACH

Event-related electroencephalographic (ERP) activity was recorded from 20 SCH patients and 20 healthy controls. The coupling changes between auditory response and pre-stimulus baseline were calculated in conventional EEG frequency bands (theta, alpha, beta-1, beta-2 and gamma), using three coupling measures: coherence, phase-locking value and Euclidean distance.

MAIN RESULTS

Our results showed a statistically significant increase from baseline to response in theta coupling and a statistically significant decrease in beta-2 coupling in controls. No statistically significant changes were observed in SCH patients.

SIGNIFICANCE

Our findings support the aberrant salience hypothesis, since SCH patients failed to change their coupling dynamics between stimulus response and baseline when performing an auditory cognitive task. This result may reflect an impaired communication among neural areas, which may be related to abnormal cognitive functions.

Analysis of progression of fatigue conditions in biceps brachii muscles using surface electromyography signals and complexity based features

Muscle fatigue is a neuromuscular condition where muscle performance decreases due to sustained or intense contraction. It is experienced by both normal and abnormal subjects. In this work, an attempt has been made to analyze the progression of muscle fatigue in biceps brachii muscles using surface electromyography (sEMG) signals. The sEMG signals are recorded from fifty healthy volunteers during dynamic contractions under well defined protocol. The acquired signals are preprocessed and segmented in to six equal parts for further analysis. The features, such as activity, mobility, complexity, sample entropy and spectral entropy are extracted from all six zones. The results are found showing that the extracted features except complexity feature have significant variations in differentiating non-fatigue and fatigue zone respectively. Thus, it appears that, these features are useful in automated analysis of various neuromuscular activities in normal and pathological conditions.