Obsessive Compulsive Disorder
obsessive compulsive disorder
How inclusive and diverse is non-invasive brain stimulation in the treatment of psychiatric disorders?
How inclusive and diverse is non-invasive brain stimulation in the treatment of psychiatric disorders?Indira Tendolkar, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry. Mental illness is associated with a huge socioeconomic burden worldwide, with annual costs only in the Netherlands of €22 billion. Over two decades of cognitive and affective neuroscience research with modern tools of neuroimaging and neurophysiology in humans have given us a wealth of information about neural circuits underlying the main symptom domains of psychiatric disorders and their remediation. Neuromodulation entails the alteration of these neural circuits through invasive (e.g., DBS) or non-invasive (e.g., TMS) techniques with the aim of improving symptoms and/or functions and enhancing neuroplasticity. In my talk, I will focus on neuromodulation studies using repetitive transcranial magnetic stimulation (rTMS) as a relatively safe, noninvasive method, which can be performed simultaneously with neurocognitive interventions. Using the examples of two chronifying mental illnesses, namely obsessive compulsive disorders and major depressive disorder (MDD), I will review the concept of "state dependent" effects of rTMS and highlight how simultaneous or sequential cognitive interventions could help optimize rTMS therapy by providing further control of ongoing neural activity in targeted neural networks. Hardly any attention has been paid to diversity aspects in the studies. By including studies from low- and middle income countries, I will discuss the potential of non-invasive brain stimulation from a transcultural perspective.
Delineating Reward/Avoidance Decision Process in the Impulsive-compulsive Spectrum Disorders through a Probabilistic Reversal Learning Task
Impulsivity and compulsivity are behavioural traits that underlie many aspects of decision-making and form the characteristic symptoms of Obsessive Compulsive Disorder (OCD) and Gambling Disorder (GD). The neural underpinnings of aspects of reward and avoidance learning under the expression of these traits and symptoms are only partially understood. " "The present study combined behavioural modelling and neuroimaging technique to examine brain activity associated with critical phases of reward and loss processing in OCD and GD. " "Forty-two healthy controls (HC), forty OCD and twenty-three GD participants were recruited in our study to complete a two-session reinforcement learning (RL) task featuring a “probability switch (PS)” with imaging scanning. Finally, 39 HC (20F/19M, 34 yrs +/- 9.47), 28 OCD (14F/14M, 32.11 yrs ±9.53) and 16 GD (4F/12M, 35.53yrs ± 12.20) were included with both behavioural and imaging data available. The functional imaging was conducted by using 3.0-T SIEMENS MAGNETOM Skyra syngo MR D13C at Monash Biomedical Imaging. Each volume compromised 34 coronal slices of 3 mm thickness with 2000 ms TR and 30 ms TE. A total of 479 volumes were acquired for each participant in each session in an interleaved-ascending manner. " " The standard Q-learning model was fitted to the observed behavioural data and the Bayesian model was used for the parameter estimation. Imaging analysis was conducted using SPM12 (Welcome Department of Imaging Neuroscience, London, United Kingdom) in the Matlab (R2015b) environment. The pre-processing commenced with the slice timing, realignment, normalization to MNI space according to T1-weighted image and smoothing with a 8 mm Gaussian kernel. " " The frontostriatal brain circuit including the putamen and medial orbitofrontal (mOFC) were significantly more active in response to receiving reward and avoiding punishment compared to receiving an aversive outcome and missing reward at 0.001 with FWE correction at cluster level; While the right insula showed greater activation in response to missing rewards and receiving punishment. Compared to healthy participants, GD patients showed significantly lower activation in the left superior frontal and posterior cingulum at 0.001 for the gain omission. " " The reward prediction error (PE) signal was found positively correlated with the activation at several clusters expanding across cortical and subcortical region including the striatum, cingulate, bilateral insula, thalamus and superior frontal at 0.001 with FWE correction at cluster level. The GD patients showed a trend of decreased reward PE response in the right precentral extending to left posterior cingulate compared to controls at 0.05 with FWE correction. " " The aversive PE signal was negatively correlated with brain activity in regions including bilateral thalamus, hippocampus, insula and striatum at 0.001 with FWE correction. Compared with the control group, GD group showed an increased aversive PE activation in the cluster encompassing right thalamus and right hippocampus, and also the right middle frontal extending to the right anterior cingulum at 0.005 with FWE correction. " " Through the reversal learning task, the study provided a further support of the dissociable brain circuits for distinct phases of reward and avoidance learning. Also, the OCD and GD is characterised by aberrant patterns of reward and avoidance processing.