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Background Functional connectivity between the left dorsolateral prefrontal cortex (DLPFC) and subgenual cingulate (sgACC) may serve as a biomarker for transcranial magnetic stimulation (rTMS) treatment response. The first aim was to establish whether this finding is veridical or artifactually induced by the pre-processing method. Furthermore, alternative biomarkers were identified and the clinical utility for personalized medicine was examined. Methods Resting-state fMRI data were collected in medication-refractory depressed patients (n = 70, 16 males) before undergoing neuronavigated left DLPFC rTMS. Seed-based analyses were performed with and without global signal regression pre-processing to identify biomarkers of short-term and long-term treatment response. Receiver Operating Characteristic curve and supervised machine learning analyses were applied to assess the clinical utility of these biomarkers for the classification of categorical rTMS response. Results Regardless of the pre-processing method, DLPFC-sgACC connectivity was not associated with treatment outcome. Instead, poorer connectivity between the sgACC and three clusters (peak locations: frontal pole, superior parietal lobule, occipital cortex) and DLPFC-central opercular cortex were observed in long-term nonresponders. The identified connections could serve as acceptable to excellent markers. Combining the features using supervised machine learning reached accuracy rates of 95.35% (CI=82.94–100.00) and 88.89% (CI=63.96–100.00) in the cross-validation and test dataset, respectively. Limitations The sample size was moderate, and features for machine learning were based on group differences. Conclusions Long-term nonresponders showed greater disrupted connectivity in regions involving the central executive network. Our findings may aid the development of personalized medicine for medication-refractory depression.

This article describes a dataset that was generated as part of the article: Personalized prediction of transcranial magnetic stimulation clinical response in patients with treatment-refractory depression using neuroimaging biomarkers and machine learning (DOI: 10.1016/j.jad.2021.04.081). We collected resting-state functional Magnetic Resonance Imaging data from 70 medication-refractory depressed subjects before undergoing four weeks of repetitive transcranial magnetic stimulation targeting the left dorsolateral prefrontal cortex. The data presented here include information about the seed-based analyses such as regions of interest, individual/group functional connectivity maps and contrast maps. The contrast maps are controlled for age, gender, duration of the current depressive episode, duration since the first depressive episode, and symptom scores. Demographics, clinical characteristics, and categorical treatment response variables are reported as well. Further, the individual connectivity values of the identified neuroimaging biomarkers of long-term clinical response were used as features in the support vector machine models are presented in combination with the trained classifiers of the support vector machine models. Post hoc analyses that were not published in the original analyses are presented as well. Finally, the R or MATLAB code scripts for all figures published in the co-submitted paper are included.

Helene Janine Hopman, Hiu Ying Choy, Wing Sze Ho, Hanna Lu, Wing Ho Oscar Wong, Sau Man Sandra Chan Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of ChinaCorrespondence: Helene Janine HopmanDepartment of Psychiatry, The Chinese University of Hong Kong, Unit L, 19/F, Kings Wing Plaza 1, 3 on Kwan Street, Shek Mun, New Territories, Hong Kong, Hong Kong Special Administrative Region of ChinaTel +852 55971622Email hjhopman@cuhk.edu.hkPurpose: The cognitive neuropsychological model of depression suggests that the cognitive deficits observed in depressed subjects are the result of attenuated top-down cognitive control resulting in increased bottom-up emotional processing. Remediation of cognitive impairments in cold cognition has been proposed as a valuable treatment for depression. The study aimed to examine the effects of clinical response to repetitive transcranial magnetic stimulation (rTMS) on cold cognition over the course of 8 weeks in medication-refractory depressed subjects.Materials and Methods: Twenty-two medication-refractory depressed subjects received twenty sessions of high-frequency rTMS targeting the left dorsolateral prefrontal cortex, one of the key nodes of the cognitive control network. Cold cognition and antidepressant treatment response were monitored at baseline, week 2, 4 and 8. Clinical response was defined as ≥ 50% reduction in Montgomery-Åsberg Depression Rating Scale score at week 8. Longitudinal changes in cold cognition were modeled using (generalized) linear mixed models. It was hypothesized that the excitatory effects of rTMS would improve cognition in the domains of executive function, memory, and attention. Additionally, responders were expected to show larger cognitive improvements than nonresponders.Results: A decrease in median latency was observed on a task that measured executive function, irrespective of treatment response status. Further, responders showed significantly larger improvements in A-Prime (the ability to detect target sequences) on a sustained attention task. Post hoc analysis indicated higher levels of rumination in non-responders.Conclusion: Our findings suggest that distractions during tasks with low perceptual complexity affected nonresponders disproportionately possibly due to higher rumination levels. Overall, cold cognition in medication-resistant depressed subjects was minimally affected by rTMS, substantiating the safety of rTMS treatment.Limitations: The sample size was small, and the study did not include a control group.Keywords: depression, neurostimulation, cognitive impairments, attention, executive function, memory

By predicting sensory consequences of actions, humans can distinguish self-generated sensory inputs from those that are elicited externally. This is one mechanism by which we achieve a subjective sense of agency over our actions. Corollary discharge (CD) signals—“copies” of motor signals sent to sensory areas—permit such predictions, and CD abnormalities are a hypothesized mechanism for the agency disruptions in schizophrenia that characterize a subset of symptoms. Indeed, behavioral evidence of altered CD, including in the oculomotor system, has been observed in schizophrenia patients. A pathway projecting from the superior colliculus to the frontal eye fields (FEFs) via the mediodorsal thalamus (MD) conveys oculomotor CD associated with saccadic eye movements in nonhuman primates. This animal work provides a promising translational framework in which to investigate CD abnormalities in clinical populations. In the current study, we examined whether structural connectivity of this MD–FEF pathway relates to oculomotor CD functioning in schizophrenia. Twenty-two schizophrenia patients and 24 healthy control participants of both sexes underwent diffusion tensor imaging, and a large subset performed a trans-saccadic perceptual task that yields measures of CD. Using probabilistic tractography, we identified anatomical connections between FEF and MD and extracted indices of microstructural integrity. Patients exhibited compromised microstructural integrity in the MD–FEF pathway, which was correlated with greater oculomotor CD abnormalities and more severe psychotic symptoms. These data reinforce the role of the MD–FEF pathway in transmitting oculomotor CD signals and suggest that disturbances in this pathway may relate to psychotic symptom manifestation in patients.SIGNIFICANCE STATEMENTPeople with schizophrenia sometimes experience abnormalities in a sense of agency, which may stem from abnormal sensory predictions about their own actions. Consistent with this notion, the current study found reduced structural connectivity in patients with schizophrenia in a specific brain pathway found to transmit such sensorimotor prediction signals in nonhuman primates. Reduced structural connectivity was correlated with behavioral evidence for impaired sensorimotor predictions and psychotic symptoms.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.