Can We Predict Who Will Respond to Neurofeedback? A Review of the Inefficacy Problem and Existing Predictors for Successful EEG Neurofeedback Learning.

Despite the success of neurofeedback treatment in many cases, the variability in the efficacy of the treatment is high, and some studies report that a significant proportion of subjects does not benefit from it. Quantifying the extent of this problem is difficult, as many studies do not report the variability among subjects. Nonetheless, the ability to identify in advance those subjects who are - or who are not - likely to benefit from neurofeedback is an important issue, which is only now starting to gain attention. Here, we review the problem of inefficacy in neurofeedback treatment as well as possible psychological and neurophysiological predictors for successful treatment. A possible explanation for treatment ineffectiveness lies in the necessity to adapt the treatment protocol to the individual subject. We therefore discuss the use of personalized neurofeedback protocols as a potential way to reduce the inefficacy problem.

Attentional bias in clinical depression and anxiety: The impact of emotional and non-emotional distracting information.

Both anxiety and major depression disorder (MDD) were reported to involve a maladaptive selective attention mechanism, associated with bias toward negative stimuli. Previous studies investigated attentional bias using distractors that required processing as part of task settings, and therefore, in our view, these distractors should be regarded as task-relevant. Here, we applied a unique task that used peripheral distractors that presented emotional and spatial information simultaneously. Notably, the emotional information was not associated in any way to the task, and thus was task-irrelevant. The spatial information, however, was task-relevant as it corresponded with task instructions. Corroborating previous findings, anxious patients showed attentional bias toward negative information. MDD patients showed no indication of this bias. Spatial information influenced all groups similarly. These results indicate that anxiety, but not MDD, is associated with an inherent negative information bias, further illustrating that the two closely related disorders are characterized by different processing patterns.

Quality of sleep in escitalopram-treated female patients with panic disorder.

OBJECTIVE: The purpose of this study was to assess the development of the night-activity rhythm and quality of sleep during escitalopram treatment of patients suffering from panic disorder. METHODS: Fifteen women with panic disorder were included and followed-up over a 5-week study period during treatment with escitalopram. An age-matched control group of 15 women were also assessed for 1 week. Motor activity was continuously measured with an electronic wrist device (Actiwatch), sleep was assessed with the Pittsburgh sleep quality index (PSQI) and patients were clinically assessed with the panic and agoraphobic scale (P&A), the global assessment of functioning (GAF) score, the Hamilton depression and anxiety scales (HAM-D, HAM-A) and the clinical global impression (CGI) score. RESULTS: There was a statistically significant difference on the self-rated PSQI between the panic disorder patients and the control group. This difference disappeared after 4 weeks of treatment with escitalopram. There was no statistically significant difference of the objective measurements of the Actiwatch between the patients and the control group. In addition, no statistically significant changes were found in the actigraphy measurements at the beginning and the end of the treatment period for patients with panic disorder. CONCLUSIONS: Patients with panic disorder rate their sleep worse than healthy controls. Treatment with escitalopram improved the subjective quality of sleep, whereas objective measures remained unchanged during treatment.

Effects of adjunctive antidepressant therapy with quetiapine on clinical outcome, quality of sleep and daytime motor activity in patients with treatment-resistant depression.

OBJECTIVE: To investigate the effects of antidepressant therapy plus quetiapine on major depression, motor activity, daytime sleepiness and quality of sleep. METHODS: Patients (N = 27) with major depressive disorder received a standard antidepressant treatment (Venlafaxine, Escitalopram) plus flexible dose of quetiapine. Patients' depression was monitored with HAM-D-21, motor activity was continuously measured with actigraphy and sleep parameters with the Pittsburgh Sleep Quality Index (PSQI) over 4 weeks. RESULTS: Whereas depression, quality of sleep and daytime sleepiness showed a significant improvement over 4 weeks, change of daytime motor activity was significant only between the wash out period and the last 2 days of the study. Repeated measures of variance indicate an independent influence of quetiapine on improved depression, motor activity and sleep. While we found only a mild decrease of daytime sleepiness during the first week of treatment, the further decline of daytime sleepiness got significant after 2 weeks of treatment with quetiapine, even at high mean daily doses and despite the sedative effects of quetiapine. CONCLUSIONS: Antidepressant treatment plus quetiapine is possibly a suitable treatment strategy to improve clinical depression, quality of sleep and motor activity. Future research is needed to understand the pharmacological interactions between antidepressants and quetiapine in major depression.

A case series on the development of rest-activity rhythm and quality of sleep in patients hospitalized for treatment of uni- or bipolar depression: a potential role for quetiapine.

Objectives. To assess the development of the rest-activity rhythm and quality of sleep during course of treatment of patients with major depressive episode receiving antidepressant treatment plus quetiapine. Methods. Ten patients with major depressive episode were followed over 4 weeks. Motor activity was measured with actigraphy, sleep with the Pittsburgh Sleep Quality Index (PSQI), and depression was followed with HAM-D-21 and BDI. Correlations and associations were calculated with non-parametric statistical tests. Results. Circadian motor activity improved during the 4 weeks treatment period only for daytime-related motor activity (M10), but not for night-time-related motor activity (L5). Patients with statistically significant higher sleep efficiency scores and sleep fraction on the actigraph after week 1 showed clinical improvement on the HAM-D score after week 4. Patients with good sleep efficiency at week 1 (assessed by PSQI) showed statistically significant clinical improvement of depression after week 4. Conclusions. Various sleep parameters at week 1 of treatment seem to be predictive for treatment outcome of depression after week 4. Actigraphy and subjective sleep assessment with PSQI are useful tools to predict treatment outcome of depression. The positive effects of quetiapine on motor activity and sleep show the clinical significance of our findings.

Nonlinear analysis of RR interval in euthymic bipolar disorder.

BACKGROUND: The bipolar affective disorder is long been speculated to have an autonomic involvement. Nonlinear analysis of heart rate variability has recently been shown to be a reliable noninvasive test for quantitative assessment of the central sympathovagal interaction that modulates cardiovascular autonomic function. METHODS: We studied 32 euthymic bipolar patients and 24 controls. A high-resolution electrocardiogram was obtained during complete rest. Nonlinear analysis (Poincare plot, largest Lyaponuv exponent, minimal embedding dimension, symbolic dynamic) was used. RESULTS: There wasn't a statistically significant difference in the nonlinear analysis of the heart rate variability, between the euthymic bipolar patients and controls, in the rest situation. CONCLUSION: The nonlinear analysis of heart rate variability didn't support the notation that there is a disturbance in the autonomic nerves system of bipolar patients in the euthymic state.

Dynamic analysis of inter-words time intervals: a method to analyze the structure of communicative signals.

Speech analyses are usually focused on words as signifiers ignoring inter-words time intervals (IWIs), which are related to the 'form' of speech, rather than to its 'content'. Applying the method of power spectrum analysis to inter-vocalizations time intervals of bird singing, underlying periodic processes were detected. In contrast, human IWIs revealed non-periodicity, which may be random or chaotic. To differentiate between these two possibilities, the non-linear dynamic methods of unstable periodic orbits and correlation dimension were applied to show that IWIs are characterized by a low dimensional chaotic attractor. Its correlation dimension of 3.2 +/- 1.1 suggests a minimum number of four variables underlying the system. The methods developed in the present communication can be further applied: (a) for the measurement of specific alterations in the processes underlying the form of speech in human disorders, i.e., schizophrenia, (b) for the assessment of normal and pathological developmental aspects of speech processes in children; (c) for comparing communicative signals between humans and other species.