Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the ...existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
Purpose Motor symptoms of patients suffering from Parkinson’s disease (PD) are currently mainly treated with dopaminergic pharmacology, and where indicated, with deep brain stimulation. In the last ...decades, a substantial body of literature has described neurophysiological correlates related to both motor symptoms and treatment effects. These mechanistic insights allow, at least theoretically, for precise targeting of neural processes responsible for PD motor symptoms. Materials and methods Literature search was conducted to identify electrophysiological and hemodynamic signals that may serve as neural targets for future neurofeedback training protocols. Results In particular alpha, beta and gamma oscillations over the motor cortex show high potential as neural targets for electrophysiological neurofeedback training. Hemodynamic functional magnetic resonance imaging (fMRI) with higher spatial resolution provides additional insights about network activity between cortical and subcortical brain regions in response to established treatments. fMRI based neurofeedback training (NFT) further allows targeting involved networks. Hemodynamic functional near infrared spectroscopy (fNIRS) may be a suitable transfer technology for more and cost-efficient hemodynamic NFT. Conclusions This scoping review presents summarises neural markers that may be promising for NFT interventions that are informed by validated neural circuit models. Recommendations for best practice in study design and reporting are provided, highlighting the importance of adequate control conditions and statistical power.
Major depressive disorder (MDD) and type 2 diabetes mellitus (T2D) are known to share clinical comorbidity and to have genetic overlap. Besides their shared genetics, both diseases seem to be ...associated with alterations in brain structural connectivity and impaired cognitive performance, but little is known about the mechanisms by which genetic risk of T2D might affect brain structure and function and if they do, how these effects could contribute to the disease course of MDD.
This study explores the association of polygenic risk for T2D with structural brain connectome topology and cognitive performance in 434 nondiabetic patients with MDD and 539 healthy control subjects.
Polygenic risk score for T2D across MDD patients and healthy control subjects was found to be associated with reduced global fractional anisotropy, a marker of white matter microstructure, an effect found to be predominantly present in MDD-related fronto-temporo-parietal connections. A mediation analysis further suggests that this fractional anisotropy variation may mediate the association between polygenic risk score and cognitive performance.
Our findings provide preliminary evidence of a polygenic risk for T2D to be linked to brain structural connectivity and cognition in patients with MDD and healthy control subjects, even in the absence of a direct T2D diagnosis. This suggests an effect of T2D genetic risk on white matter integrity, which may mediate an association of genetic risk for diabetes and cognitive impairments.
Statistical hypothesis tests for which the null hypothesis cannot be rejected ("null findings") are often seen as negative outcomes in the life and social sciences and are thus scarcely published. ...Null findings can, however, bear important insights about the validity of theories and hypotheses. In fact, the tendency to publish mainly significant findings is considered a key reason for failures to replicate previous studies in various fields, including psychology. In this editorial, we discuss the relevance of non-significant results in psychological research, and provide a short overview of statistical methods that render these results more informative. Considering the circumstances of limited time and research resources that students often face, we close with recommendations for more efficient research designs.
Dysphagia is a relevant symptom in Parkinson's disease, whose pathophysiology is poorly understood. It is mainly attributed to degeneration of brainstem nuclei. However, alterations in the cortical ...contribution to deglutition control in the course of Parkinson's disease have not been investigated. Here, we sought to determine the patterns of cortical swallowing processing in patients with Parkinson's disease with and without dysphagia. Swallowing function in patients was objectively assessed with fiberoptic endoscopic evaluation. Swallow-related cortical activation was measured using whole-head magnetoencephalography in 10 dysphagic and 10 non-dysphagic patients with Parkinson's disease and a healthy control group during self-paced swallowing. Data were analysed applying synthetic aperture magnetometry, and group analyses were done using a permutation test. Compared with healthy subjects, a strong decrease of cortical swallowing activation was found in all patients. It was most prominent in participants with manifest dysphagia. Non-dysphagic patients with Parkinson's disease showed a pronounced shift of peak activation towards lateral parts of the premotor, motor and inferolateral parietal cortex with reduced activation of the supplementary motor area. This pattern was not found in dysphagic patients with Parkinson's disease. We conclude that in Parkinson's disease, not only brainstem and basal ganglia circuits, but also cortical areas modulate swallowing function in a clinically relevant way. Our results point towards adaptive cerebral changes in swallowing to compensate for deficient motor pathways. Recruitment of better preserved parallel motor loops driven by sensory afferent input seems to maintain swallowing function until progressing neurodegeneration exceeds beyond the means of this adaptive strategy, resulting in manifestation of dysphagia.
Neurofeedback is a technique that aims to teach a subject to regulate a brain parameter measured by a technical interface to modulate his/her related brain and cognitive activities. However, the use ...of neurofeedback as a therapeutic tool for psychiatric disorders remains controversial. The aim of this review is to summarize and to comment the level of evidence of electroencephalogram (EEG) neurofeedback and real-time functional magnetic resonance imaging (fMRI) neurofeedback for therapeutic application in psychiatry.
Literature on neurofeedback and mental disorders but also on brain computer interfaces (BCI) used in the field of neurocognitive science has been considered by the group of expert of the Neurofeedback evaluation & training (NExT) section of the French Association of biological psychiatry and neuropsychopharmacology (AFPBN).
Results show a potential efficacy of EEG-neurofeedback in the treatment of attentional-deficit/hyperactivity disorder (ADHD) in children, even if this is still debated. For other mental disorders, there is too limited research to warrant the use of EEG-neurofeedback in clinical practice. Regarding fMRI neurofeedback, the level of evidence remains too weak, for now, to justify clinical use. The literature review highlights various unclear points, such as indications (psychiatric disorders, pathophysiologic rationale), protocols (brain signals targeted, learning characteristics) and techniques (EEG, fMRI, signal processing).
The field of neurofeedback involves psychiatrists, neurophysiologists and researchers in the field of brain computer interfaces. Future studies should determine the criteria for optimizing neurofeedback sessions. A better understanding of the learning processes underpinning neurofeedback could be a key element to develop the use of this technique in clinical practice.
Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of ...schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, p
= 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, p
= 0.024), but not BD (r = 0.166, p
= 0.205) or MDD (r = -0.274, p
= 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, p
= 0.006), BD (rho = -0.672, p
= 0.009), and MDD (rho = -0.692, p
= 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.
PDF
