Stable neural underpinnings of emotional cognition subgroups in patients newly diagnosed with bipolar disorder: A prospective fMRI study.

OBJECTIVES: This study aimed to investigate the neural underpinnings of emotional cognition subgroups in recently diagnosed patients with bipolar disorder (BD) and change over time over a 15-month follow-up period. METHODS: Patients and healthy controls (HC) underwent emotional and nonemotional cognitive assessments and functional magnetic resonance imaging (fMRI) at the baseline (BD n = 87; HC n = 65) and at 15-month follow-up (BD n = 44; HC n = 38). Neural activity during emotion reactivity and regulation in response to aversive pictures was assessed during fMRI. Patients were clustered into subgroups based on their emotional cognition and, with HC, were compared longitudinally on cognition and neural activity during emotion reactivity and regulation. RESULTS: Patients were optimally clustered into two subgroups: Subgroup 1 (n = 40, 46%) was characterized by heightened emotional reactivity in negative social scenarios, which persisted over time, but were otherwise cognitively intact. This subgroup exhibited stable left amygdala hyper-activity over time during emotion reactivity compared to subgroup 2. Subgroup 2 (n = 47, 54%) was characterized by global emotional cognitive impairments, including stable difficulties with emotion regulation over time. During emotion regulation across both time points, this group exhibited hypo-activity in the left dorsolateral prefrontal cortex. Additionally, patients in subgroup 2 had poorer nonemotional cognition, had more psychiatric hospital admissions and history of psychotic episodes than those in subgroup 1. CONCLUSIONS: Broad impairments in emotional cognition in approximately half of BD patients and associated nonemotional cognitive deficits may originate from insufficient recruitment of prefrontal resources, contributing to poorer clinical outcomes.

Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder.

BACKGROUND: There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS: In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS: At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION: Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

Effects of erythropoietin on cognitive impairment and prefrontal cortex activity across affective disorders: A randomized, double-blinded, placebo-controlled trial.

BACKGROUND: Persistent cognitive impairment is frequent across bipolar disorder (BD) and major depressive disorder (MDD), highlighting an urgent need for pro-cognitive treatments. AIM: This study investigated effects of erythropoietin (EPO) on cognitive impairment and dorsal prefrontal cortex (dPFC) activity in affective disorders. METHODS: In this randomized, double-blinded, placebo-controlled trial, cognitively impaired patients with remitted BD or MDD received 1 weekly recombinant human EPO (40,000 IU/mL) or saline infusion for a 12-week period. Assessments were conducted at baseline, after 2 weeks of treatment (week 3), immediately after treatment (week 13) and at 6-months follow-up. Participants underwent functional MRI during performance on a n-back working memory (WM) task at baseline and week 3, and for a subgroup 6 weeks post-treatment (week 18). The primary outcome was a cognitive composite score at week 13, whereas secondary outcomes comprised sustained attention and functioning. WM-related dPFC activity was a tertiary outcome. RESULTS: Data were analysed for 101 of the 103 included patients (EPO, n = 58; saline, n = 43). There were no effects of EPO over saline on any cognitive or functional outcomes or on WM-related dPFC activity. CONCLUSIONS: The absence of treatment-related changes in cognition and neural activity was unexpected and contrasts with multiple previous preclinical and clinical studies. It is possible that the lack of effects resulted from a recent change in the manufacturing process for EPO. Nevertheless, the findings support the validity of dPFC target engagement as a biomarker model for pro-cognitive effects, according to which treatments that do not improve cognition should not modulate dPFC activity. TRIAL REGISTRATIONS: EudraCT no.: 2016-004023-24; ClinicalTrials.gov identifier: NCT03315897.

CCH attack frequency reduction after psilocybin correlates with hypothalamic functional connectivity.

OBJECTIVE: To evaluate the feasibility and prophylactic effect of psilocybin as well as its effects on hypothalamic functional connectivity (FC) in patients with chronic cluster headache (CCH). BACKGROUND: CCH is an excruciating and difficult-to-treat disorder with incompletely understood pathophysiology, although hypothalamic dysfunction has been implicated. Psilocybin may have beneficial prophylactic effects, but clinical evidence is limited. METHODS: In this small open-label clinical trial, 10 patients with CCH were included and maintained headache diaries for 10 weeks. Patients received three doses of peroral psilocybin (0.14 mg/kg) on the first day of weeks five, six, and seven. The first 4 weeks served as baseline and the last 4 weeks as follow-up. Hypothalamic FC was determined using functional magnetic resonance imaging the day before the first psilocybin dose and 1 week after the last dose. RESULTS: The treatment was well tolerated. Attack frequency was reduced by mean (standard deviation) 31% (31) from baseline to follow-up (pFWER = 0.008). One patient experienced 21 weeks of complete remission. Changes in hypothalamic-diencephalic FC correlated negatively with a percent change in attack frequency (pFWER = 0.03, R = -0.81), implicating this neural pathway in treatment response. CONCLUSION: Our results indicate that psilocybin may have prophylactic potential and implicates the hypothalamus in possible treatment response. Further clinical studies are warranted.

Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness.

BACKGROUND: In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, whereas multimodal data from acute DoC are scarce. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging (i.e. CONNECT-ME; ClinicalTrials.gov identifier: NCT02644265) investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations. METHODS: We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123). Favorable outcome was defined as a modified Rankin Scale score ≤ 3, a cerebral performance category score ≤ 2, and a Glasgow Outcome Scale Extended score ≥ 4. EEG features included visual grading, automated spectral categorization, and support vector machine consciousness classifier. fMRI features included functional connectivity measures from six resting-state networks. Random forest and support vector machine were applied to EEG and fMRI features to predict outcomes. Here, random forest results are presented as areas under the curve (AUC) of receiver operating characteristic curves or accuracy. Cox proportional regression with in-hospital death as a competing risk was used to assess independent clinical predictors of time to favorable outcome. RESULTS: Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77-0.82]) and 12-month (AUC 0.74 [95% CI 0.71-0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69-0.78) both alone and when combined with some EEG features (accuracies 0.73-0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02-1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04-3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40-5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12-5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41-15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46-4.19]). CONCLUSIONS: Our results indicate that EEG and fMRI features and readily available clinical data predict short-term outcome of patients with acute DoC and that EEG also predicts 12-month outcome after ICU discharge.

Trajectory of reward-related abnormalities in unaffected relatives of patients with bipolar disorder - A longitudinal fMRI study.

First-degree relatives of patients with bipolar disorder are at heightened risk of mood episodes, which may be attributed to the existence of endophenotypes i.e., heritable (neuro)biological changes present in patients and their unaffected relatives (UR). In this longitudinal MRI study, we aim to investigate the trajectories of aberrant reward-related functional changes identified in UR vs healthy controls (HC). Sixty-eight UR and 65 HC of similar age and gender distribution underwent MRI at baseline while performing a card guessing task. Of these, 29 UR and 36 HC were investigated with the same protocol following a 16-month period in average. We first identified brain regions showing group differences in the neural response to expected value (EV) and reward prediction error (PE) at baseline and analyzed how the reward-related response in these regions changed over time in UR vs HC. Relative to HC at baseline, UR showed lower EV signal in the right ventrolateral prefrontal cortex (vlPFC) and paracingulate gyrus and lower PE signal in the left vlPFC and dorsomedial PFC. The trajectories of these abnormalities in UR showed a normalization of the prefrontal EV signals, whereas the PE signals which correlated with depressive symptoms remained stable over time. While the UR showed both blunted EV and PE signals, none of these abnormalities increased over time, which is consistent with the observed stable mood symptoms.

Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test-retest reliability of publicly available software packages.

Brain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to assess the biological age of the human brain. The difference between a person's chronological age and the estimated brain age is thought to reflect deviations from a normal aging trajectory, indicating a slower or accelerated biological aging process. Several pre-trained software packages for predicting brain age are publicly available. In this study, we perform a comparison of such packages with respect to (1) predictive accuracy, (2) test-retest reliability, and (3) the ability to track age progression over time. We evaluated the six brain age prediction packages: brainageR, DeepBrainNet, brainage, ENIGMA, pyment, and mccqrnn. The accuracy and test-retest reliability were assessed on MRI data from 372 healthy people aged between 18.4 and 86.2 years (mean 38.7 ± 17.5 years). All packages showed significant correlations between predicted brain age and chronological age (r = 0.66-0.97, p < 0.001), with pyment displaying the strongest correlation. The mean absolute error was between 3.56 (pyment) and 9.54 years (ENIGMA). brainageR, pyment, and mccqrnn were superior in terms of reliability (ICC values between 0.94-0.98), as well as predicting age progression over a longer time span. Of the six packages, pyment and brainageR consistently showed the highest accuracy and test-retest reliability.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD. METHOD: Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN). RESULTS: Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance. CONCLUSION: Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

Association between brain serotonin 4 receptor binding and reactivity to emotional faces in depressed and healthy individuals.

Brain serotonergic (5-HT) signaling is posited to modulate neural responses to emotional stimuli. Dysfunction in 5-HT signaling is implicated in major depressive disorder (MDD), a disorder associated with significant disturbances in emotion processing. In MDD, recent evidence points to altered 5-HT4 receptor (5-HT4R) levels, a promising target for antidepressant treatment. However, how these alterations influence neural processing of emotions in MDD remains poorly understood. This is the first study to examine the association between 5-HT4R binding and neural responses to emotions in patients with MDD and healthy controls. The study included one hundred and thirty-eight participants, comprising 88 outpatients with MDD from the NeuroPharm clinical trial (ClinicalTrials.gov identifier: NCT02869035) and 50 healthy controls. Participants underwent an [11C]SB207145 positron emission tomography (PET) scan to quantify 5-HT4R binding (BPND) and a functional magnetic resonance imaging (fMRI) scan during which they performed an emotional face matching task. We examined the association between regional 5-HT4R binding and corticolimbic responses to emotional faces using a linear latent variable model, including whether this association was moderated by depression status. We observed a positive correlation between 5-HT4R BPND and the corticolimbic response to emotional faces across participants (r = 0.20, p = 0.03). This association did not differ between groups (parameter estimate difference = 0.002, 95% CI = -0.008: 0.013, p = 0.72). Thus, in the largest PET/fMRI study of associations between serotonergic signaling and brain function, we found a positive association between 5-HT4R binding and neural responses to emotions that appear unaltered in MDD. Future clinical trials with novel pharmacological agents targeting 5-HT4R are needed to confirm whether they ameliorate emotion processing biases in MDD.

Association of neurocognitive function with psychiatric hospitalization and socio-demographic conditions in individuals with bipolar and major depressive disorders.

Background: Neurocognitive impairments are associated with poor clinical and employment outcomes in individuals with affective disorders. However, little is known about their associations with long-term clinical outcomes such as psychiatric hospitalizations, and with socio-demographic indicators other than employment. In the largest longitudinal study of neurocognition in affective disorders to date, we investigate the role of neurocognitive impairments on psychiatric hospitalizations and socio-demographic conditions. Methods: The study included 518 individuals with bipolar or major depressive disorder. Neurocognitive assessments covered executive function and verbal memory domains. Longitudinal data on psychiatric hospitalization and socio-demographic conditions (employment, cohabitation, and marital status) for up to 11 years were obtained using National population-based registers. The primary and secondary outcomes were psychiatric hospitalizations (n = 398) and worsening of socio-demographic conditions (n = 518), in the follow-up period since study inclusion, respectively. Cox regression models were used to examine the association of neurocognition with future psychiatric hospitalizations and the worsening of socio-demographic conditions. Findings: Clinically significant impairment in verbal memory (z-score ≤ -1; defined by the ISBD Cognition Task Force), but not in executive function, was associated with a higher risk of future hospitalization, when adjusted for age, sex, hospitalization in the year preceding inclusion, depression severity, diagnosis, and type of clinical trial (HR = 1.84, 95% CI:1.05-3.25, p = 0.034; n = 398). The results remained significant even after accounting for illness duration. Neurocognitive impairments were not associated with the worsening of socio-demographic conditions (p ≥ 0.17; n = 518). Interpretation: Promoting neurocognitive function, especially verbal memory, may mitigate the risk of future psychiatric hospitalization in individuals with affective disorders. Funding: Lundbeckfonden (R279-2018-1145).

Neural basis of memory impairments and relation to functional disability in fully or partially remitted patients with affective disorders.

Bipolar disorder (BD) and major depressive disorder (MDD) are associated with cognitive and functional impairment. Cognitive impairment is often associated with dorsal prefrontal cortex (dPFC) hypo-activity, but the neuronal correlates of functional disability is largely unknown. In this study, 91 patients with affective disorders in full or partial remission (BD, n = 67; MDD, n = 24) with objectively verified cognitive impairment and substantial functional disability underwent neuropsychological assessment and functional magnetic resonance imaging (fMRI) scan during which they completed a strategic picture-encoding task. For comparison, 36 matched healthy controls underwent an identical test protocol. Patients showed encoding-related hypo-activity in the dPFC compared to controls. In patients, lower right dlPFC activity was associated with poorer overall functioning and more antipsychotic drug use. In conclusion, memory impairments were underpinned by failure to recruit the dPFC during task performance which was associated with impaired functioning in fully or partially remitted patients with affective disorders. This aberrant neurocircuitry activity has implications for the design of future pro-cognitive interventions that aim to improve not only cognition but also real-world functioning.

Associations between aberrant working memory-related neural activity and cognitive impairments in somatically healthy, remitted patients with mood disorders.

BACKGROUND: Persistent cognitive deficits are prevalent in patients with bipolar disorder (BD) and unipolar disorder (UD), but treatments effectively targeting cognition in these mood disorders are lacking. This is partly due to poor insight into the neuronal underpinnings of cognitive deficits. METHODS: The aim of this functional magnetic resonance imaging (fMRI) study was to investigate the neuronal underpinnings of working memory (WM)-related deficits in somatically healthy, remitted patients with BD or UD (n = 66) with cognitive and functional impairments compared to 38 healthy controls (HC). The participants underwent neuropsychological testing and fMRI, while performing a visuospatial and a verbal N-back WM paradigm. RESULTS: Relative to HC, patients exhibited hypo-activity across dorsolateral prefrontal cortex as well as frontal and parietal nodes of the cognitive control network (CCN) and hyper-activity in left orbitofrontal cortex within the default mode network (DMN) during both visuospatial and verbal WM performance. Verbal WM-related response in the left posterior superior frontal gyrus (SFG) within CCN was lower in patients and correlated positively with out-of-scanner executive function performance across all participants. CONCLUSIONS: Our findings suggest that cognitive impairments across BD and UD are associated with insufficient recruitment of task-relevant regions in the CCN and down-regulation of task-irrelevant orbitofrontal activity within the DMN during task performance. Specifically, a lower recruitment of the left posterior SFG within CCN during verbal WM was associated with lower cognitive performance.

Resting-state connectivity and neural response to emotional images in patients with severe health anxiety: An fMRI study.

BACKGROUND: Severe health anxiety is a disorder characterized by a persistent preoccupation with one's health. In behavioral studies, biases in the processing of health-related stimuli (e.g., pictures, words) are consistently associated with health anxiety symptoms. The neural correlates of the observed behavioral abnormalities remain however poorly understood. METHODS: In this functional magnetic resonance imaging study, 22 treatment-seeking patients with severe health anxiety and 22 control participants performed a resting-state and a picture matching task. Immediately after the resting-state, participants completed a questionnaire quantifying their thoughts and feelings during rest along several dimensions. The picture task included images of health-related and neutral scenes and of disgusted and neutral faces. RESULTS: Compared to controls, patients with health anxiety showed increased functional connectivity in the dorsolateral prefrontal cortex within the left fronto-parietal resting-state network, which correlated positively with the self-reported thought dimensions of Self, Health Concern, and Thought Suppression. In the picture matching task, no significant group differences were found in the hypothesised regions (amygdala and insula) or at a whole-brain level in response to either health-related versus neural scenes or disgust versus neutral faces contrasts. LIMITATIONS: A relatively small sample size and that no information about patients declining to participate was obtained. CONCLUSIONS: Our findings suggest that behavioral biases in health anxiety may be related to aberrant left dorsolateral prefrontal cortex functional connectivity at rest. In contrast, the health anxiety patients did not show significant hyperactivations of amygdala and insula during processing of emotional stimuli, contrasting findings in other anxiety disorders.

Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study.

Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary centre cohort, diagnostic phase IIb study 'Consciousness in neurocritical care cohort study using EEG and fMRI' (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks was assessed. Next, we used EEG and fMRI data at study enrolment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel) to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS) at time of study enrolment and at ICU discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC patients (mean age, 50.0 ± 18 years, 43% female), 51 (59%) were ≤UWS and 36 (41%) were ≥ MCS at study enrolment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrolment and ICU discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrolment and ICU discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.

Psilocybin modulation of time-varying functional connectivity is associated with plasma psilocin and subjective effects.

BACKGROUND: Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects. AIM: Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans. METHODS: Fifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis. RESULTS: Fractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state partly associated with motion was positively associated with PPL and SDI. CONCLUSION: Our findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics.

Generalizability of treatment outcome prediction in major depressive disorder using structural MRI: A NeuroPharm study.

Brain morphology has been suggested to be predictive of drug treatment outcome in major depressive disorders (MDD). The current study aims at evaluating the performance of pretreatment structural brain magnetic resonance imaging (MRI) measures in predicting the outcome of a drug treatment of MDD in a large single-site cohort, and, importantly, to assess the generalizability of these findings in an independent cohort. The random forest, boosted trees, support vector machines and elastic net classifiers were evaluated in predicting treatment response and remission following an eight week drug treatment of MDD using structural brain measures derived with FastSurfer (FreeSurfer). Models were trained and tested within a nested cross-validation framework using the NeuroPharm dataset (n = 79, treatment: escitalopram); their generalizability was assessed using an independent clinical dataset, EMBARC (n = 64, treatment: sertraline). Prediction of antidepressant treatment response in the Neuropharm cohort was statistically significant for the random forest (p = 0.048), whereas none of the models could significantly predict remission. Furthermore, none of the models trained using the entire NeuroPharm dataset could significantly predict treatment outcome in the EMBARC dataset. Although our primary findings in the NeuroPharm cohort support some, but limited value in using pretreatment structural brain MRI to predict drug treatment outcome in MDD, the models did not generalize to an independent cohort suggesting limited clinical applicability. This study emphasizes the importance of assessing model generalizability for establishing clinical utility.

Case Report: Resting-State Brain-Networks After Near-Complete Hemispherectomy in Adulthood.

Objectives: Understanding the dynamics of reorganized network-level brain functions after hemispherectomy is important for treatment, prognostication, and rehabilitation of brain injury, but also for investigating questions of fundamental neurobehavioral interest: How does the brain promote consciousness despite loss of one hemisphere? Methods: We studied resting-state functional connectivity (RSFC) in a high-functioning middle-aged man 6 years after functional hemispherectomy following malignant middle cerebral artery infarction, and we compared results to RSFC in 20 healthy controls. Results: Our analysis indicates increased between-network connectivity for all seven networks examined in the patient's preserved hemisphere, compared to healthy controls, suggesting a shift toward increased between-network connectivity following near-complete loss of one hemisphere during adulthood. Conclusions: These data corroborate and extend recent findings of increased between-network connectivity in the remaining hemisphere after surgical hemispherectomy for intractable epilepsy during childhood. Our results support a neuroplasticity model with reorganization of distributed brain connectivity within the preserved hemisphere as part of the road to recovery after brain injury, as well as recovery of consciousness and cognitive functions, after hemispherectomy.

Emotional faces processing in major depressive disorder and prediction of antidepressant treatment response: A NeuroPharm study.

BACKGROUND: Major depressive disorder (MDD) is a prevalent neuropsychiatric illness for which it is important to resolve underlying brain mechanisms. Current treatments are often unsuccessful, precipitating a need to identify predictive markers. AIM: We evaluated (1) alterations in brain responses to an emotional faces functional magnetic resonance imaging (fMRI) paradigm in individuals with MDD, compared to controls, (2) whether pretreatment brain responses predicted antidepressant treatment response, and (3) pre-post change in brain responses following treatment. METHODS: Eighty-nine medication-free, depressed individuals and 115 healthy controls completed the fMRI paradigm. Depressed individuals completed a nonrandomized, open-label, 8-week treatment with escitalopram, including the option to switch to duloxetine after 4 weeks. We examined patient-control group differences in regional fMRI responses at baseline, whether baseline fMRI responses predicted treatment response at 8 weeks, including early life stress moderating effects, and change in fMRI responses in 36 depressed individuals rescanned following 8 weeks of treatment. RESULTS: Task reaction time was 5% slower in patients. Multiple brain regions showed significant task-related responses, but we observed no statistically significant patient-control group differences (Cohen's d < 0.35). Patient pretreatment brain responses did not predict antidepressant treatment response (area under the curve of the receiver operator characteristic (AUC-ROC) < 0.6) and brain responses were not statistically significantly changed after treatment (Cohen's d < 0.33). CONCLUSION: This represents the largest prediction study to date examining emotional faces fMRI features as predictors of antidepressant treatment response. Brain response to this fMRI emotional faces paradigm did not distinguish depressed individuals from healthy controls, nor was it predictive of antidepressant treatment response.Clinical Trial Registration: Site: https://clinicaltrials.gov, Trial Number: NCT02869035, Trial Title: Treatment Outcome in Major Depressive Disorder.

Brain serotonin transporter is associated with cognitive-affective biases in healthy individuals.

Cognitive affective biases describe the tendency to process negative information or positive information over the other. These biases can be modulated by changing extracellular serotonin (5-HT) levels in the brain, for example, by pharmacologically blocking and downregulating the 5-HT transporter (5-HTT), which remediates negative affective bias. This suggests that higher levels of 5-HTT are linked to a priority of negative information over positive, but this link remains to be tested in vivo in healthy individuals. We, therefore, evaluated the association between 5-HTT levels, as measured with [11 C]DASB positron emission tomography (PET), and affective biases, hypothesising that higher 5-HTT levels are associated with a more negative bias. We included 98 healthy individuals with measures of [11 C]DASB binding potential (BPND ) and affective biases using The Emotional Faces Identification Task by subtracting the per cent hit rate for happy from that of sad faces (EFITAB ). We evaluated the association between [11 C]DASB BPND and EFITAB in a linear latent variable model, with the latent variable (5-HTTLV ) modelled from [11 C]DASB BPND in the fronto-striatal and fronto-limbic networks implicated in affective cognition. We observed an inverse association between 5-HTTLV and EFITAB (ß = -8% EFITAB per unit 5-HTTLV , CI = -14% to -3%, p = .002). These findings show that higher 5-HTT levels are linked to a more negative bias in healthy individuals. High 5-HTT supposedly leads to high clearance of 5-HT, and thus, a negative bias could result from low extracellular 5-HT. Future studies must reveal if a similar inverse association exists in individuals with affective disorders.

Dorsal striatal dopamine induces fronto-cortical hypoactivity and attenuates anxiety and compulsive behaviors in rats.

Dorsal striatal dopamine transmission engages the cortico-striato-thalamo-cortical (CSTC) circuit, which is implicated in many neuropsychiatric diseases, including obsessive-compulsive disorder (OCD). Yet it is unknown if dorsal striatal dopamine hyperactivity is the cause or consequence of changes elsewhere in the CSTC circuit. Classical pharmacological and neurotoxic manipulations of the CSTC and other brain circuits suffer from various drawbacks related to off-target effects and adaptive changes. Chemogenetics, on the other hand, enables a highly selective targeting of specific neuronal populations within a given circuit. In this study, we developed a chemogenetic method for selective activation of dopamine neurons in the substantia nigra, which innervates the dorsal striatum in the rat. We used this model to investigate effects of targeted dopamine activation on CSTC circuit function, especially in fronto-cortical regions. We found that chemogenetic activation of these neurons increased movement (as expected with increased dopamine release), rearings and time spent in center, while also lower self-grooming. Furthermore, this activation increased prepulse inhibition of the startle response in females. Remarkably, we observed reduced [18F]FDG metabolism in the frontal cortex, following dopamine activation in the dorsal striatum, while total glutamate levels- in this region were increased. This result is in accord with clinical studies of increased [18F]FDG metabolism and lower glutamate levels in similar regions of the brain of people with OCD. Taken together, the present chemogenetic model adds a mechanistic basis with behavioral and translational relevance to prior clinical neuroimaging studies showing deficits in fronto-cortical glucose metabolism across a variety of clinical populations (e.g. addiction, risky decision-making, compulsivity or obesity).