Estimating the Quality of Electroconvulsive Therapy Induced Seizures Using Decision Tree and Fuzzy Inference System Classifiers

Electroconvulsive therapy (ECT) is an effective and widely used treatment for major depressive disorder, in which a brief electric current is passed through the brain to trigger a brief seizure. This study aims to identify seizure quality rating by utilizing a set of seizure parameters. We used 750 ECT EEG recordings in this experiment. Four seizure related parameters, (time of slowing, regularity, stereotypy and post-ictal suppression) are used as inputs to two classifiers, decision tree and fuzzy inference system (FIS), to predict seizure quality ratings. The two classifiers produced encouraging results with error rate of 0.31 and 0.25 for FIS and decision tree, respectively. The classification results show that the four seizure parameters provide relevant information about the rating of seizure quality. Automatic scoring of seizure quality may be beneficial to clinicians working in this field

Assessing neurophysiological changes associated with combined transcranial direct current stimulation and cognitive-emotional training for treatment-resistant depression

Transcranial direct current stimulation (tDCS), a form of non‐invasive brain stimulation, is a promising treatment for depression. Recent research suggests that tDCS efficacy can be augmented using concurrent cognitive‐emotional training (CET). However, the neurophysiological changes associated with this combined intervention remain to be elucidated. We therefore examined the effects of tDCS combined with CET using electroencephalography (EEG). A total of 20 participants with treatment‐resistant depression took part in this open‐label study and received 18 sessions over 6 weeks of tDCS and concurrent CET. Resting‐state and task‐related EEG during a 3‐back working memory task were acquired at baseline and immediately following the treatment course. Results showed an improvement in mood and working memory accuracy, but not response time, following the intervention. We did not find significant effects of the intervention on resting‐state power spectral density (frontal theta and alpha asymmetry), time–frequency power (alpha event‐related desynchronisation and theta event‐related synchronisation) or event‐related potentials (P2 and P3 components). We therefore identified little evidence of neurophysiological changes associated with treatment using tDCS and concurrent CET, despite significant improvements in mood and near‐transfer effects of cognitive training to working memory accuracy. Further research incorporating a sham‐controlled group may be necessary to identify the neurophysiological effects of the intervention

Effects of High-Definition Transcranial Direct Current Stimulation (HD-tDCS) of the Intraparietal Sulcus and Dorsolateral Prefrontal Cortex on Working Memory and Divided Attention

Objective: There is a need to elucidate the underlying neural mechanisms subserving working memory and divided attention functioning. Recent neuroimaging studies provide evidence for anatomical co-localization of both functions. In the present study we used a functional intervention, whereby we applied a novel type of focalised, non-invasive brain stimulation, High-Definition transcranial Direct Current Stimulation (HD-tDCS), to the regions subserving these processes, the left intraparietal sulcus (IPS) and left dorsolateral prefrontal cortex (LDLPFC). Our aim was therefore to modulate activity in these regions using HD-tDCS and thereby assess their relevance for working memory, divided attention and their shared sub-processes.Method: 78 participants were evenly randomized to one of three conditions in a single blind, parallel group study design. Anodal or sham HD-tDCS was applied to either the left IPS or LDLPFC while participants completed a verbal working memory task, a divided attention task, and two tasks measuring subcomponents of working memory (updating and maintenance).Results: Focalised stimulation of the IPS and LDLPFC did not significantly modulate performance compared to sham stimulation. However, moderate effect sizes were obtained for at least one HD-tDCS condition relative to sham for all tasks, warranting further research into the functional importance of the IPS in subserving these abilities.Conclusions: The current results may be useful for informing future tDCS studies for modulating working memory and divided attention functioning

Behavioural and neurophysiological differences in working memory function of depressed patients and healthy controls

OBJECTIVE: Major depressive disorder (MDD) is associated with deficits in working memory. Several cognitive subprocesses interact to produce working memory, including attention, encoding, maintenance and manipulation. We sought to clarify the contribution of functional deficits in these subprocesses in MDD by varying cognitive load during a working memory task. METHODS: 41 depressed participants and 41 age and gender-matched healthy controls performed the n-back working memory task at three levels of difficulty (0-, 1-, and 2-back) in a pregistered study. We assessed response times, accuracy, and event-related electroencephalography (EEG), including P2 and P3 amplitudes, and frontal theta power (4-8 Hz). RESULTS: MDD participants had prolonged response times and more positive frontal P3 amplitudes (i.e., Fz) relative to controls, mainly in the most difficult 2-back condition. Working memory accuracy, P2 amplitudes and frontal theta event-related synchronisation did not differ between groups at any level of task difficulty. CONCLUSIONS: Depression is associated with generalized psychomotor slowing of working memory processes, and may involve compensatory hyperactivity in frontal and parietal regions. SIGNIFICANCE: These findings provide insights into MDD working memory deficits, indicating that depressed individuals dedicate greater levels of cortical processing and cognitive resources to achieve comparable working memory performance to controls

Estimating the Quality of Electroconvulsive Therapy Induced Seizures Using Decision Tree and Fuzzy Inference System Classifiers

© 2018 IEEE. Electroconvulsive therapy (ECT) is an effective and widely used treatment for major depressive disorder, in which a brief electric current is passed through the brain to trigger a brief seizure. This study aims to identify seizure quality rating by utilizing a set of seizure parameters. We used 750 ECT EEG recordings in this experiment. Four seizure related parameters, (time of slowing, regularity, stereotypy and post-ictal suppression) are used as inputs to two classifiers, decision tree and fuzzy inference system (FIS), to predict seizure quality ratings. The two classifiers produced encouraging results with error rate of 0.31 and 0.25 for FIS and decision tree, respectively. The classification results show that the four seizure parameters provide relevant information about the rating of seizure quality. Automatic scoring of seizure quality may be beneficial to clinicians working in this field

Development of the Ketamine Side Effect Tool (KSET)

Background: Currently, no specific, systematic assessment tool for the monitoring and reporting of ketamine-related side effects exists. Our aim was to develop a comprehensive Ketamine Side Effect Tool (KSET) to capture acute and longer-term side effects associated with repeated ketamine treatments. Methods: Informed by systematic review data and clinical research, we drafted a list of the most commonly reported side effects. Face and content validation were obtained via feedback from collaborators with expertise in psychiatry and anaesthetics, clinical trial piloting and a modified Delphi Technique involving ten international experts. Results: The final version consisted of four forms that collect information at time points: screening, baseline, immediately after a single treatment, and longer-term follow-up. Instructions were developed to guide users and promote consistent utilisation. Limitations: Further evaluation of feasibility, construct validity and reliability is required, and is planned across multiple international sites. Conclusions: The structured Ketamine Side Effect Tool (KSET) was developed, with confirmation of content and face validity via a Delphi consensus process. This tool is timely, given the paucity of data regarding ketamine's safety, tolerability and abuse potential over the longer term, and its recent adoption internationally as a clinical treatment for depression. Although based on data from depression studies, the KSET has potential applicability for ketamine (or derivatives) used in other medical disorders, including chronic pain. We recommend its utilisation for both research and clinical scenarios, including data registries

The Ketamine Side Effect Tool (KSET):A comprehensive measurement-based safety tool for ketamine treatment in psychiatry

Objectives: On a background of the rapidly expanding clinical use of ketamine and esketamine for treatment of depression and other conditions, we examined safety monitoring, seeking to identify knowledge gaps relevant to clinical practice. Methods: An international group of psychiatrists discussed the issue of safety of ketamine and esketamine and came to a consensus on key safety gaps. Results: There is no standard safety monitoring for off-label generic ketamine. For intranasal esketamine, each jurisdiction providing regulatory approval may specify monitoring. Treatment is often provided beyond the period for which safety has been demonstrated, with no agreed framework for monitoring of longer term side effects for either generic ketamine or intranasal esketamine. Limitations: The KSET has established face and content validity, however it has not been validated against other measures of safety. Conclusions: We recommend the Ketamine Side Effect Tool (KSET) as a comprehensive safety monitoring tool for acute and longer term side effects

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms