Apathy in depression: An arterial spin labeling perfusion MRI study.

INTRODUCTION: Apathy, as defined as a deficit in goal-directed behaviors, is a critical clinical dimension in depression associated with chronic impairment. Little is known about its cerebral perfusion specificities in depression. To explore neurovascular mechanisms underpinning apathy in depression by pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI). METHODS: Perfusion imaging analysis was performed on 90 depressed patients included in a prospective study between November 2014 and February 2017. Imaging data included anatomical 3D T1-weighted and perfusion pCASL sequences. A multiple regression analysis relating the quantified cerebral blood flow (CBF) in different regions of interest defined from the FreeSurfer atlas, to the Apathy Evaluation Scale (AES) total score was conducted. RESULTS: After confound adjustment (demographics, disease and clinical characteristics) and correction for multiple comparisons, we observed a strong negative relationship between the CBF in the left anterior cingulate cortex (ACC) and the AES score (standardized beta = -0.74, corrected p value = 0.0008). CONCLUSION: Our results emphasized the left ACC as a key region involved in apathy severity in a population of depressed participants. Perfusion correlates of apathy in depression evidenced in this study may contribute to characterize different phenotypes of depression.

Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression.

BACKGROUND: The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown. METHODS: We collected qualitative semantic and phonemic VFT scores along with grey and white matter anatomical MRI of depressed (n = 26) and healthy controls (HC, n = 25) women. Qualitative VFT variables are the "clustering score" (i.e. the ability to produce words within subcategories) and the "switching score" (i.e. the ability to switch between clusters). The clustering and switching scores were automatically calculated using a data-driven approach. Brain measures were cortical thickness (CT) and fractional anisotropy (FA). We tested for associations between CT, FA and qualitative VFT variables within each group. RESULTS: Patients had reduced switching VFT scores compared to HC. Thicker cortex was associated with better switching score in semantic VFT bilaterally in the frontal (superior, rostral middle and inferior gyri), parietal (inferior parietal lobule including the supramarginal gyri), temporal (transverse and fusiform gyri) and occipital (lingual gyri) lobes in the depressed group. Positive association between FA and the switching score in semantic VFT was retrieved in depressed patients within the corpus callosum, right inferior fronto-occipital fasciculus, right superior longitudinal fasciculus extending to the anterior thalamic radiation (all p < 0.05, corrected). CONCLUSION: Together, these results suggest that automatic qualitative VFT scores are associated with brain anatomy and reinforce its potential use as a surrogate for depression cerebral bases.

Structural abnormalities associated with poor outcome of a major depressive episode: The role of thalamus.

An identification of precise biomarkers contributing to poor outcome of a major depressive episode (MDE) has the potential to improve therapeutic strategies by reducing time to symptomatic relief. In a cross-sectional volumetric study with a 6 month clinical follow-up, we performed baseline brain grey matter volume analysis between 2 groups based on illness improvement: 27 MDD patients in the "responder" (R) group (Clinical Global Impression- Improvement (CGI-I) score ≤ 2) and 30 in the "non-responder" (NR) group (CGI-I > 2), using a Voxel Based-Morphometry analysis. NR had significantly smaller Grey Matter (GM) volume in the bilateral thalami, in precentral gyrus, middle temporal gyrus, precuneus and middle cingulum compared to R at baseline. Additionally, they exhibited significant greater GM volume increase in the left anterior lobe of cerebellum and posterior cingulate cortex. The latter result was not significant when participants with bipolar disorder were excluded from the analysis. NR group had higher baseline anxiety scores. Our study has pointed out the role of thalamus in prognosis of MDE. These findings highlight the involvement of emotion regulation in the outcome of MDE. The present study provides a step towards the understanding of neurobiological processes of treatment resistant depression.

EEG neurofeedback research: A fertile ground for psychiatry?

The clinical efficacy of neurofeedback is still a matter of debate. This paper analyzes the factors that should be taken into account in a transdisciplinary approach to evaluate the use of EEG NFB as a therapeutic tool in psychiatry. Neurofeedback is a neurocognitive therapy based on human-computer interaction that enables subjects to train voluntarily and modify functional biomarkers that are related to a defined mental disorder. We investigate three kinds of factors related to this definition of neurofeedback. We focus this article on EEG NFB. The first part of the paper investigates neurophysiological factors underlying the brain mechanisms driving NFB training and learning to modify a functional biomarker voluntarily. Two kinds of neuroplasticity involved in neurofeedback are analyzed: Hebbian neuroplasticity, i.e. long-term modification of neural membrane excitability and/or synaptic potentiation, and homeostatic neuroplasticity, i.e. homeostasis attempts to stabilize network activity. The second part investigates psychophysiological factors related to the targeted biomarker. It is demonstrated that neurofeedback involves clearly defining which kind of relationship between EEG biomarkers and clinical dimensions (symptoms or cognitive processes) is to be targeted. A nomenclature of accurate EEG biomarkers is proposed in the form of a short EEG encyclopedia (EEGcopia). The third part investigates human-computer interaction factors for optimizing NFB training and learning during the closed loop interaction. A model is proposed to summarize the different features that should be controlled to optimize learning. The need for accurate and reliable metrics of training and learning in line with human-computer interaction is also emphasized, including targeted biomarkers and neuroplasticity. All these factors related to neurofeedback show that it can be considered as a fertile ground for innovative research in psychiatry.

Making psychiatric semiology great again: A semiologic, not nosologic challenge.

This article analyzes whether psychiatric disorders can be considered different from non-psychiatric disorders on a nosologic or semiologic point of view. The supposed difference between psychiatric and non-psychiatric disorders relates to the fact that the individuation of psychiatric disorders seems more complex than for non-psychiatric disorders. This individuation process can be related to nosologic and semiologic considerations. The first part of the article analyzes whether the ways of constructing classifications of psychiatric disorders are different than for non-psychiatric disorders. The ways of establishing the boundaries between the normal and the pathologic, and of classifying the signs and symptoms in different categories of disorder, are analyzed. Rather than highlighting the specificity of psychiatric disorders, nosologic investigation reveals conceptual notions that apply to the entire field of medicine when we seek to establish the boundaries between the normal and the pathologic and between different disorders. Psychiatry is thus very important in medicine because it exemplifies the inherent problem of the construction of cognitive schemes imposed on clinical and scientific medical information to delineate a classification of disorders and increase its comprehensibility and utility. The second part of this article assesses whether the clinical manifestations of psychiatric disorders (semiology) are specific to the point that they are entities that are different from non-psychiatric disorders. The attribution of clinical manifestations in the different classifications (Research Diagnostic Criteria, Diagnostic Statistic Manual, Research Domain Criteria) is analyzed. Then the two principal models on signs and symptoms, i.e. the latent variable model and the causal network model, are assessed. Unlike nosologic investigation, semiologic analysis is able to reveal specific psychiatric features in a patient. The challenge, therefore, is to better define and classify signs and symptoms in psychiatry based on a dual and mutually interactive biological and psychological perspective, and to incorporate semiologic psychiatry into an integrative, multilevel and multisystem brain and cognitive approach.

Neurofeedback: One of today's techniques in psychiatry?

OBJECTIVES: 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. METHOD: 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: 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). CONCLUSION: 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.

Manic switches induced by antidepressants: an umbrella review comparing randomized controlled trials and observational studies.

OBJECTIVE: We aimed to explore whether the prevalence of manic switch was underestimated in randomized controlled trials (RCTs) compared to observational studies (OSs). METHOD: Meta-analyses and simple and systematic reviews were identified by two reviewers in a blinded, standardized manner. All relevant references were extracted to include RCTs and OSs that provided data about manic switch prevalence after antidepressant treatment for a major depressive episode. The primary outcome was manic switch prevalence in the different arms of each study. A meta-regression was conducted to quantify the impact of certain variables on manic switch prevalence. RESULTS: A total of 57 papers (35 RCTs and 22 OSs) were included in the main analysis. RCTs underestimated the rate of manic switch [0.53 (0.32-0.87)]. Overestimated prevalence was related to imipraminics [1.85 (1.22-2.79)]; to serotonin-norepinephrine reuptake inhibitors [1.74 (1.06-2.86)]; and to other classes of drugs [1.58 (1.08-2.31)], compared to placebo treatment. The prevalence of manic switch was lower among adults than among children [0.2 (0.07-0.59)]; and higher [20.58 (8.41-50.31)] in case of bipolar disorder. CONCLUSION: Our results highlight an underestimation of the rates of manic switch under antidepressants in RCTs compared to the rates observed in observational studies.

Use of very-high-dose olanzapine in treatment-resistant schizophrenia.

Schizophrenia is a chronic illness with a progressive course that can be marked by resistance to antipsychotic treatment. This can make therapeutic support challenging for the practitioner, with results that are partial and unsatisfactory. In the literature, treatment with high-dose olanzapine (>20mg/day) appears to be a good alternative to clozapine, the gold standard for treatment-resistant schizophrenia. In the present observational prospective study, we studied the clinical and biological profiles of patients treated with olanzapine doses up to 100mg/day. In total, 50 patients were clinically and biologically assessed. We found a linear relationship between oral dose and serum concentration (Pearson's r=0.83, p<0.001) with effects of tobacco (p<0.05) and of coffee and tea consumption (p<0.01). Tolerance seemed to be good regardless of dose. No link was found between concentration and efficiency. Despite a nonexhaustive assessment of pharmacokinetic parameters, not least pharmacogenetic data (e.g., genotyping of cytochrome P450-1A2 or glycoprotein P Abcb1a), pharmacokinetic aspects alone cannot account for why the disease may sometimes be resistant to 20mg of olanzapine but respond to higher doses. A nuclear imaging study exploring brain occupancy by high-dose olanzapine, coupled with the abovementioned pharmacokinetic assessment, may prove a relevant experimental paradigm for studying the pathophysiological mechanisms of resistant schizophrenia.