I am a MD/PhD postdoctoral scholar from Rennes in France. Before arriving in Stanford, I worked in both clinical and research fields. I leaded a unit specialized in neuropsychiatric treatment resistant disorders (mainly depression, Parkinson Disease with psychiatric comorbidities and obsessive-compulsive disorder) with two residents. In this unit, I used and coordinated neuromodulations techniques such as repetititive Trancranial Magnetic Stimulation, Electroconvulsive therapy, and Deep Brain Stimulation. In the research part of my activity, my work focused on biomarkers of poor outcome of depressive disorder using clinical/neuropsychological/brain imaging assessments. In addition, I conducted research on neurofeedback applied to depression. Apart to be involved in the national coordination of this topic for psychiatric diseases (Neurofeedback section of French Association of Biological Psychiatry and Neuropsychopharmacology, I was actively involved in the development of a new generation of brain-computer interface therapies based on joint bimodal EEG-fMRI neurofeedback. In this project, I leaded the clinical research applying this new technology to depression. I am very interested in working on biomarkers of neuropsychiatric disorders and the development of personalized-targeting neuromodulation techniques.

Stanford Advisors

All Publications

  • Multimodal brain imaging connectivity analyses of emotional and motivational deficits in depression among women. Journal of psychiatry & neuroscience : JPN Robert, G. n., Bannier, E. n., Comte, M. n., Domain, L. n., Corouge, I. n., Dondaine, T. n., Batail, J. M., Ferre, J. C., Fakra, E. n., Drapier, D. n. 2021; 46 (2): E303–E312


    Major depressive disorder (MDD) is characterized by impaired cortical-subcortical functional connectivity. Apathy adds to functional impairment, but its cerebral basis in MDD remains unknown. Our objective was to describe impairments in functional connectivity during emotional processing in MDD (with varying levels of congruency and attention), and to determine their correlation with apathy.We used the Variable Attention Affective Task during functional MRI, followed by diffusion-weighted MRI, to assess 55 right-handed women (30 with MDD and 25 healthy controls) between September 2012 and February 2015. We estimated functional connectivity using generalized psychophysiologic interaction and anatomic connectivity with tract-based spatial statistics. We measured apathy using the Apathy Evaluation Scale.We found decreased functional connectivity between the left amygdala and the left anterior cingulate cortex (ACC) during negative stimuli in participants with MDD (t54 = 4.2; p = 0.035, family-wise error [FWE]-corrected). During high-attention stimuli, participants with MDD showed reduced functional connectivity between the right dorsolateral prefrontal cortex (dlPFC) and the right ACC (t54 = 4.06, pFWE = 0.02), but greater functional connectivity between the right dlPFC and the right amygdala (t54 = 3.35, p = 0.048). Apathy was associated with increased functional connectivity between the right dlPFC and the right ACC during high-attention stimuli (t28 = 5.2, p = 0.01) and increased fractional anisotropy in the right posterior cerebellum, the anterior and posterior cingulum and the bilateral internal capsule (all pFWE < 0.05).Limitations included a moderate sample size, concomitant antidepressant therapy and no directed connectivity.We found that MDD was associated with impairments in cortical-subcortical functional connectivity during negative stimuli that might alter the recruitment of networks engaged in attention. Apathy-related features suggested networks similar to those observed in degenerative disorders, but possible different mechanisms.

    View details for DOI 10.1503/jpn.200074

    View details for PubMedID 33844485

  • Structural abnormalities associated with poor outcome of a major depressive episode: The role of thalamus. Psychiatry research. Neuroimaging Batail, J. M., Coloigner, J. n., Soulas, M. n., Robert, G. n., Barillot, C. n., Drapier, D. n. 2020; 305: 111158


    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.

    View details for DOI 10.1016/j.pscychresns.2020.111158

    View details for PubMedID 32889511

  • Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK Micoulaud-Franchi, J., Batail, J., Fovet, T., Philip, P., Cermolacce, M., Jaumard-Hakoun, A., Vialatte, F. 2019; 44 (3): 151–72


    This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

    View details for DOI 10.1007/s10484-019-09440-4

    View details for Web of Science ID 000479258300001

    View details for PubMedID 31098793

  • EEG neurofeedback research: A fertile ground for psychiatry? ENCEPHALE-REVUE DE PSYCHIATRIE CLINIQUE BIOLOGIQUE ET THERAPEUTIQUE Batail, J., Bioulac, S., Cabestaing, F., Daudet, C., Drapier, D., Fouillen, M., Fovet, T., Hakoun, A., Jardri, R., Jeunet, C., Lotte, F., Maby, E., Mattout, J., Medani, T., Micoulaud-Franchi, J., Mladenovic, J., Perronet, L., Pillette, L., Ros, T., Vialatte, F., NExT Grp 2019; 45 (3): 245–55


    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.

    View details for DOI 10.1016/j.encep.2019.02.001

    View details for Web of Science ID 000523601100010

    View details for PubMedID 30885442

  • Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects NEUROPHYSIOLOGIE CLINIQUE-CLINICAL NEUROPHYSIOLOGY Jeunet, C., Glize, B., McGonigal, A., Batail, J., Micoulaud-Franchi, J. 2019; 49 (2): 125–36


    Many Brain Computer Interface (BCI) and neurofeedback studies have investigated the impact of sensorimotor rhythm (SMR) self-regulation training procedures on motor skills enhancement in healthy subjects and patients with motor disabilities. This critical review aims first to introduce the different definitions of SMR EEG target in BCI/Neurofeedback studies and to summarize the background from neurophysiological and neuroplasticity studies that led to SMR being considered as reliable and valid EEG targets to improve motor skills through BCI/neurofeedback procedures. The second objective of this review is to introduce the main findings regarding SMR BCI/neurofeedback in healthy subjects. Third, the main findings regarding BCI/neurofeedback efficiency in patients with hypokinetic activities (in particular, motor deficit following stroke) as well as in patients with hyperkinetic activities (in particular, Attention Deficit Hyperactivity Disorder, ADHD) will be introduced. Due to a range of limitations, a clear association between SMR BCI/neurofeedback training and enhanced motor skills has yet to be established. However, SMR BCI/neurofeedback appears promising, and highlights many important challenges for clinical neurophysiology with regards to therapeutic approaches using BCI/neurofeedback.

    View details for DOI 10.1016/j.neucli.2018.10.068

    View details for Web of Science ID 000465158000007

    View details for PubMedID 30414824

  • Towards a physiological approach to semiology in psychiatry. Part 2: Perspectives offered by systemic biology ANNALES MEDICO-PSYCHOLOGIQUES Dumas, G., Cermolacce, M., Batail, J., Quiles, C., Micoulaud-Franchi, J. 2019; 177 (3): 289–94
  • Towards a physiological approach to semiology in psychiatry. Part 1: Approaches DRC, DSM, RDOC ET HITOP ANNALES MEDICO-PSYCHOLOGIQUES Micoulaud-Franchi, J., Quiles, C., Batail, J., Daudet, C., Cermolacce, M., Dumas, G. 2019; 177 (3): 282–88
  • White matter abnormalities in depression: A categorical and phenotypic diffusion MRI study NEUROIMAGE-CLINICAL Coloigner, J., Batail, J., Commowick, O., Corouge, I., Robert, G., Barillot, C., Drapier, D. 2019; 22: 101710


    Mood depressive disorder is one of the most disabling chronic diseases with a high rate of everyday life disability that affects 350 million people around the world. Recent advances in neuroimaging have reported widespread structural abnormalities, suggesting a dysfunctional frontal-limbic circuit involved in the pathophysiological mechanisms of depression. However, a variety of different white matter regions has been implicated and is sought to suffer from lack of reproducibility of such categorical-based biomarkers. These inconsistent results might be attributed to various factors: actual categorical definition of depression as well as clinical phenotype variability. In this study, we 1/ examined WM changes in a large cohort (114 patients) compared to a healthy control group and 2/ sought to identify specific WM alterations in relation to specific depressive phenotypes such as anhedonia (i.e. lack of pleasure), anxiety and psychomotor retardation -three core symptoms involved in depression. Consistent with previous studies, reduced white matter was observed in the genu of the corpus callosum extending to the inferior fasciculus and posterior thalamic radiation, confirming a frontal-limbic circuit abnormality. Our analysis also reported other patterns of increased fractional anisotropy and axial diffusivity as well as decreased apparent diffusion coefficient and radial diffusivity in the splenium of the corpus callosum and posterior limb of the internal capsule. Moreover, a positive correlation between FA and anhedonia was found in the superior longitudinal fasciculus as well as a negative correlation in the cingulum. Then, the analysis of the anxiety and diffusion metric revealed that increased anxiety was associated with greater FA values in genu and splenium of corpus callosum, anterior corona radiata and posterior thalamic radiation. Finally, the motor retardation analysis showed a correlation between increased Widlöcher depressive retardation scale scores and reduced FA in the body and genu of the corpus callosum, fornix, and superior striatum. Through this twofold approach (categorical and phenotypic), this study has underlined the need to move forward to a symptom-based research area of biomarkers, which help to understand the pathophysiology of mood depressive disorders and to stratify precise phenotypes of depression with targeted therapeutic strategies.

    View details for DOI 10.1016/j.nicl.2019.101710

    View details for Web of Science ID 000470123000115

    View details for PubMedID 30849644

    View details for PubMedCentralID PMC6406626

  • Apathy alters emotional arousal in chronic schizophrenia JOURNAL OF PSYCHIATRY & NEUROSCIENCE Dondaine, T., Philippot, P., Batail, J., Le Jeune, F., Sauleau, P., Drapier, S., Verin, M., Millet, B., Drapier, D., Robert, G. 2019; 44 (1): 54–61


    Within the heterogeneity of schizophrenia, apathy constitutes an independent cluster of negative symptoms associated with poor outcomes. Attempts to identify an emotional deficit in patients who have schizophrenia with negative symptoms have yielded mixed results, and studies that focus on the relationship between apathy and emotional disorders are lacking.We set out to remedy this shortcoming using a validated battery of film excerpts to induce positive and negative emotions in patients with chronic schizophrenia with (n = 20) or without (n = 20) apathy, and in controls (n = 20) comparable for age, sex and socioeconomic status. We assessed emotions using an innovative but validated technique to evaluate tonic and phasic electrodermal activity and subjective feelings using a standardized visual analogue scale.Using a qualitative measure of apathy, we did not find a specific decrease in tonic activity during the induction of positive emotions. However, we did observe that patients with apathy showed reduced tonic activity independent of valence (i.e., for both positive and negative emotions) compared with controls and patients without apathy. Moreover, the quantitative measure of apathy (Apathy Evaluation Scale) was the only significant factor, explaining 24% of the variance in tonic activity during induction of positive emotions after controlling for confounding factors.Electrodermal activity was the only physiologic measure we acquired. We induced several emotions sequentially that might have overlapped with each other, but we added an emotional "washout" period and randomized the order of each film excerpt to limit this possibility.Taken together, these results suggest that apathy in schizophrenia could impair tonic activity during positive emotions. Treatments aimed at enhancing positive emotions may help alleviate apathy in schizophrenia.

    View details for DOI 10.1503/jpn.170172

    View details for Web of Science ID 000454309700006

    View details for PubMedID 30277457

  • Making psychiatric semiology great again: A semiologic, not nosologic challenge ENCEPHALE-REVUE DE PSYCHIATRIE CLINIQUE BIOLOGIQUE ET THERAPEUTIQUE Micoulaud-Franchi, J., Quiles, C., Batail, J., Lancon, C., Masson, M., Dumas, G., Cermolacce, M. 2018; 44 (4): 343–53


    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.

    View details for DOI 10.1016/j.encep.2018.01.007

    View details for Web of Science ID 000448628200008

    View details for PubMedID 29885784

  • Using Recent BCI Literature to Deepen our Understanding of Clinical Neurofeedback: A Short Review NEUROSCIENCE Jeunet, C., Lotte, F., Batail, J., Philip, P., Franchi, J. 2018; 378: 225–33


    In their recent paper, Alkoby et al. (2017) provide the readership with an extensive and very insightful review of the factors influencing NeuroFeedback (NF) performance. These factors are drawn from both the NF literature and the Brain-Computer Interface (BCI) literature. Our short review aims to complement Alkoby et al.'s review by reporting recent additions to the BCI literature. The object of this paper is to highlight this literature and discuss its potential relevance and usefulness to better understand the processes underlying NF and further improve the design of clinical trials assessing NF efficacy. Indeed, we are convinced that while NF and BCI are fundamentally different in many ways, both the BCI and NF communities could reach compelling achievements by building upon one another. By reviewing the recent BCI literature, we identified three types of factors that influence BCI performance: task-specific, cognitive/motivational and technology-acceptance-related factors. Since BCIs and NF share a common goal (i.e., learning to modulate specific neurophysiological patterns), similar cognitive and neurophysiological processes are likely to be involved during the training process. Thus, the literature on BCI training may help (1) to deepen our understanding of neurofeedback training processes and (2) to understand the variables that influence the clinical efficacy of NF. This may help to properly assess and/or control the influence of these variables during randomized controlled trials.

    View details for DOI 10.1016/j.neuroscience.2018.03.013

    View details for Web of Science ID 000432742500017

    View details for PubMedID 29572165

  • High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia SCHIZOPHRENIA BULLETIN Dollfus, S., Jaafari, N., Guillin, O., Trojak, B., Plaze, M., Saba, G., Nauczyciel, C., Larmurier, A., Chastan, N., Meille, V., Krebs, M., Ayache, S. S., Lefaucheur, J., Razafimandimby, A., Leroux, E., Morello, R., Batail, J., Brazo, P., Lafay, N., Wassouf, I., Harika-Germaneau, G., Guillevin, R., Guillevin, C., Gerardin, E., Rotharmel, M., Crepon, B., Gaillard, R., Delmas, C., Fouldrin, G., Laurent, G., Nathou, C., Etard, O. 2018; 44 (3): 505–14


    Despite extensive testing, the efficacy of low-frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) of temporo-parietal targets for the treatment of auditory verbal hallucinations (AVH) in patients with schizophrenia is still controversial, but promising results have been reported with both high-frequency and neuronavigated rTMS. Here, we report a double-blind sham-controlled study to assess the efficacy of high-frequency (20 Hz) rTMS applied over a precise anatomical site in the left temporal region using neuronavigation.Fifty-nine of 74 randomized patients with schizophrenia or schizoaffective disorders (DSM-IV R) were treated with rTMS or sham treatment and fully evaluated over 4 weeks. The rTMS target was determined by morphological MRI at the crossing between the projection of the ascending branch of the left lateral sulcus and the superior temporal sulcus (STS).The primary outcome was response to treatment, defined as a 30% decrease of the Auditory Hallucinations Rating Scale (AHRS) frequency item, observed at 2 successive evaluations. While there was no difference in primary outcome between the treatment groups, the percentages of patients showing a decrease of more than 30% of AHRS score (secondary outcome) did differ between the active (34.6%) and sham groups (9.1%) (P = .016) at day 14.This controlled study reports negative results on the primary outcome but demonstrates a transient effect of 20 Hz rTMS guided by neuronavigation and targeted on an accurate anatomical site for the treatment of AVHs in schizophrenia patients.

    View details for DOI 10.1093/schbul/sbx127

    View details for Web of Science ID 000429473800008

    View details for PubMedID 29897597

    View details for PubMedCentralID PMC5890503

  • Apathy and depression: Which clinical specificities? Personalized Medicine In Psychiatry Batail, J., Pallaric, J., Guillery, M., Gadoullet, J., Sauleau, P., Le Jeune, F., Vérin, M., Robert, G., Drapier, D. 2018; 7-8: 21-26
  • On assessing neurofeedback effects: should double-blind replace neurophysiological mechanisms? BRAIN Fovet, T., Micoulaud-Franchi, J., Vialatte, F., Lotte, F., Daudet, C., Batail, J., Mattout, J., Wood, G., Jardri, R., Enriquez-Geppert, S., Ros, T. 2017; 140: e63

    View details for DOI 10.1093/brain/awx211

    View details for Web of Science ID 000414358500003

    View details for PubMedID 28969378

  • A randomised cross-over study assessing the "blue pyjama syndrome" in major depressive episode. Scientific reports Delmas, H., Batail, J., Falissard, B., Robert, G., Rangé, M., Brousse, S., Soulabaille, J., Drapier, D., Naudet, F. 2017; 7 (1): 2629-?


    This paper introduces a "blue pyjama syndrome" (whereby wearing hospital pyjamas results in an exaggerated impression of severity). We performed a 5-day, prospective, randomized, cross-over study in a French mood disorder unit for inpatients. At Day 1 (D1) and Day 5 (D5), two 5-minute video interviews were recorded with patients in pyjamas or in day clothes (the sequence was randomly allocated). Psychiatrists unaware of the study objective assessed the videos and scored their clinical global impressions (CGI, with scores ranging from 1 to 7). Of 30 participants with major depressive episode selected for inclusion, 26 participants (69% women) provided useable data for an evaluation by 10 psychiatrists. Pyjamas significantly increased the psychiatrists' CGI ratings of disease severity by 0·65 [0·27; 1·02] points. The psychiatrists' global impressions also rated patients as significantly less severe at D5 in comparison with D1 by -0·66 [-1·03; -0·29] points. The "blue pyjama syndrome" is in the same order of magnitude as the difference observed after a week of hospitalisation. This potentially calls into question the reliability and validity of observer ratings of depression.

    View details for DOI 10.1038/s41598-017-02411-x

    View details for PubMedID 28572626

  • Neurofeedback: One of today's techniques in psychiatry? ENCEPHALE-REVUE DE PSYCHIATRIE CLINIQUE BIOLOGIQUE ET THERAPEUTIQUE Arns, M., Batail, J., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., Fovet, T., Jardri, R., Le-Van-Quyen, M., Lotte, F., Mehler, D., Micoulaud-Franchi, J., Purper-Ouakil, D., Vialatte, F., NExT Grp 2017; 43 (2): 135–45


    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.

    View details for DOI 10.1016/j.encep.2016.11.003

    View details for Web of Science ID 000402445100008

    View details for PubMedID 28041692

  • Manic switches induced by antidepressants: an umbrella review comparing randomized controlled trials and observational studies. Acta psychiatrica Scandinavica Allain, N., Leven, C., Falissard, B., Allain, J., Batail, J., Polard, E., Montastruc, F., Drapier, D., Naudet, F. 2017; 135 (2): 106-116


    We aimed to explore whether the prevalence of manic switch was underestimated in randomized controlled trials (RCTs) compared to observational studies (OSs).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.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.Our results highlight an underestimation of the rates of manic switch under antidepressants in RCTs compared to the rates observed in observational studies.

    View details for DOI 10.1111/acps.12672

    View details for PubMedID 27878807

  • Use of very-high-dose olanzapine in treatment-resistant schizophrenia SCHIZOPHRENIA RESEARCH Batail, J., Langree, B., Robert, G., Bleher, S., Verdier, M., Bellissant, E., Millet, B., Drapier, D. 2014; 159 (2-3): 411–14


    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.

    View details for DOI 10.1016/j.schres.2014.09.020

    View details for Web of Science ID 000345229200025

    View details for PubMedID 25278103