Reproducibility of Results
Research Papers
Showing 6 of 10Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).
View Full Paper →Reliability of Electroencephalogram-Based Individual Markers - Case Study
The aim of this study was to evaluate individual level of natural variability of electroencephalogram (EEG) based markers. Three linear: alpha power variability, spectral asymmetry index, relative gamma power and three nonlinear methods: Higuchi's fractal dimension, detrended fluctuation analysis, and Lempel-Ziv complexity were selected. The markers were evaluated over 15 sessions acquired in 14 months. The results indicate that individual natural variability for five of the selected markers is lower compared to differences between healthy and depressed groups of subjects in our previous studies. The results of the current study suggest that EEG based markers can be applied for evaluation of disturbances in brain activity at individual level.Clinical Relevance-The indicated stability in the current study of widely used EEG-based markers at individual level suggests a promising opportunity to apply EEG as a novel method in diagnoses of brain mental disorders in clinical practice.
View Full Paper →Current practices in clinical neurofeedback with functional MRI-Analysis of a survey using the TIDieR checklist
BACKGROUND: A core principle of creating a scientific evidence base is that results can be replicated in independent experiments and in health intervention research. The TIDieR (Template for Intervention Description and Replication) checklist has been developed to aid in summarising key items needed when reporting clinical trials and other well designed evaluations of complex interventions in order that findings can be replicated or built on reliably. Neurofeedback (NF) using functional MRI (fMRI) is a multicomponent intervention that should be considered a complex intervention. The TIDieR checklist (with minor modification to increase applicability in this context) was distributed to NF researchers as a survey of current practice in the design and conduct of clinical studies. The aim was to document practice and convergence between research groups, highlighting areas for discussion and providing a basis for recommendations for harmonisation and standardisation. METHODS: The TIDieR checklist was interpreted and expanded (21 questions) to make it applicable to neurofeedback research studies. Using the web-based Bristol Online Survey (BOS) tool, the revised checklist was disseminated to researchers in the BRAINTRAIN European research collaborative network (supported by the European Commission) and others in the fMRI-neurofeedback community. RESULTS: There were 16 responses to the survey. Responses were reported under eight main headings which covered the six domains of the TIDieR checklist: What, Why, When, How, Where and Who. CONCLUSIONS: This piece of work provides encouraging insight into the ability to be able to map neuroimaging interventions to a structured framework for reporting purposes. Regardless of the considerable variability of design components, all studies could be described in standard terms of diagnostic groups, dose/duration, targeted areas/signals, and psychological strategies and learning models. Recommendations are made which include providing detailed rationale of intervention design in study protocols.
View Full Paper →Finding Parameters around the Abdomen for a Vibrotactile System: Healthy and Patients with Parkinson's Disease
Freezing of Gait (FOG) is one of the most disabling gait disorders in Parkinson's Disease (PD), for which the efficacy of the medication is reduced, highlighting the use of non-pharmacological solutions. In particular, patients present less difficulties in overcoming FOG when using feedback and especially with Biofeedback Systems. In this study it is intended to detect the frequency threshold and the minimum interval of perception of the vibrotactile feedback, through a proposed wearable system, a waistband. Experimental tests were carried out that considered a temporal, spatial and spatiotemporal context, for which 15 healthy and 15 PD patients participated. It was detected as threshold frequency 180 Hz and for minimum interval of vibration perception 250 ms. The identification of this threshold frequency and this interval will allow us to select the frequency and the minimum interval of vibration to be used in a Vibrotactile Biofeedback Device for patients with PD, in order to help them to overcome FOG.
View Full Paper →Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging
The individual alpha peak frequency (IAPF) of the human electroencephalography (EEG) typically experiences slowing with increasing age. Despite this hallmark change, studies that investigate modulations of conventional EEG alpha power and connectivity by aging and age-related neuropathology neglect to account for intergroup differences in IAPF. To investigate the relationship of age-related IAPF slowing with EEG power and connectivity, we recorded eyes-closed resting-state EEG in 37 young adults and 32 older adults. We replicated the finding of a slowed IAPF in older adults. IAPF values were significantly correlated with the frequency of maximum global connectivity and the means of their distributions did not differ, suggesting that connectivity was highest at the IAPF. Older adults expressed reduced global EEG power and connectivity at the conventional upper alpha band (10-12 Hz) compared with young adults. By contrast, groups had equivalent power and connectivity at the IAPF. The results suggest that conventional spectral boundaries may be biased against older adults or any group with a slowed IAPF. We conclude that investigations of alpha activity in aging and age-related neuropathology should be adapted to the IAPF of the individual and that previous findings should be interpreted with caution. EEG in the dominant alpha range may be unsuitable for examining cortico-cortical connectivity due to its subcortical origins.
View Full Paper →Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback
Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.
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