Provincial and connector qualities of somatosensory brain network hubs in bipolar disorder.

Brain network hubs are highly connected brain regions serving as important relay stations for information integration. Recent studies have linked mental disorders to impaired hub function. Provincial hubs mainly integrate information within their own brain network, while connector hubs share information between different brain networks. This study used a novel time-varying analysis to investigate whether hubs aberrantly follow the trajectory of other brain networks than their own. The aim was to characterize brain hub functioning in clinically remitted bipolar patients. We analyzed resting-state functional magnetic resonance imaging data from 96 euthymic individuals with bipolar disorder and 61 healthy control individuals. We characterized different hub qualities within the somatomotor network. We found that the somatomotor network comprised mainly provincial hubs in healthy controls. Conversely, in bipolar disorder patients, hubs in the primary somatosensory cortex displayed weaker provincial and stronger connector hub function. Furthermore, hubs in bipolar disorder showed weaker allegiances with their own brain network and followed the trajectories of the limbic, salience, dorsal attention, and frontoparietal network. We suggest that these hub aberrancies contribute to previously shown functional connectivity alterations in bipolar disorder and may thus constitute the neural substrate to persistently impaired sensory integration despite clinical remission.

Impact of NPSR1 gene variation on the neural correlates of phasic and sustained fear in spider phobia-an imaging genetics and independent replication approach.

The functional neuropeptide S receptor 1 (NPSR1) gene A/T variant (rs324981) is associated with fear processing. We investigated the impact of NPSR1 genotype on fear processing and on symptom reduction following treatment in individuals with spider phobia. A replication approach was applied [discovery sample: Münster (MS) nMS = 104; replication sample Würzburg (WZ) nWZ = 81]. Participants were genotyped for NPSR1 rs324981 [T-allele carriers (risk) versus AA homozygotes (no-risk)]. A sustained and phasic fear paradigm was applied during functional magnetic resonance imaging. A one-session virtual reality exposure treatment was conducted. Change of symptom severity from pre to post treatment and within session fear reduction were assessed. T-allele carriers in the discovery sample displayed lower anterior cingulate cortex (ACC) activation compared to AA homozygotes independent of condition. For sustained fear, this effect was replicated within a small cluster and medium effect size. No association with symptom reduction was found. Within-session fear reduction was negatively associated with ACC activation in T-allele carriers in the discovery sample. NPSR1 rs324981 genotype might be associated with fear processing in the ACC in spider phobia. Interpretation as potential risk-increasing function of the NPSR1 rs324981 T-allele via impaired top-down control of limbic structures remains speculative. Potential association with symptom reduction warrants further research.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Mania-related effects on structural brain changes in bipolar disorder - a narrative review of the evidence.

Cross-sectional neuroimaging studies show that bipolar disorder is associated with structural brain abnormalities, predominantly observed in prefrontal and temporal cortex, cingulate gyrus, and subcortical regions. However, longitudinal studies are needed to elucidate whether these abnormalities presage disease onset or are consequences of disease processes, and to identify potential contributing factors. Here, we narratively review and summarize longitudinal structural magnetic resonance imaging studies that relate imaging outcomes to manic episodes. First, we conclude that longitudinal brain imaging studies suggest an association of bipolar disorder with aberrant brain changes, including both deviant decreases and increases in morphometric measures. Second, we conclude that manic episodes have been related to accelerated cortical volume and thickness decreases, with the most consistent findings occurring in prefrontal brain areas. Importantly, evidence also suggests that in contrast to healthy controls, who in general show age-related cortical decline, brain metrics remain stable or increase during euthymic periods in bipolar disorder patients, potentially reflecting structural recovering mechanisms. The findings stress the importance of preventing manic episodes. We further propose a model of prefrontal cortical trajectories in relation to the occurrence of manic episodes. Finally, we discuss potential mechanisms at play, remaining limitations, and future directions.

Commonalities and differences in the neural substrates of threat predictability in panic disorder and specific phobia.

Different degrees of threat predictability are thought to induce either phasic fear or sustained anxiety. Maladaptive, sustained anxious apprehension is thought to result in overgeneralization of anxiety and thereby to contribute to the development of anxiety disorders. Therefore, differences in threat predictability have been associated with pathological states of anxiety with specific phobia (SP) representing phasic fear as heightened response to predictable threat, while panic disorder (PD) is characterized by sustained anxiety (unpredictable threat) and, as a consequence, overgeneralization of fear. The present study aimed to delineate commonalities and differences in the neural substrates of the impact of threat predictability on affective processing in these two anxiety disorders. Twenty PD patients, 20 SP patients and 20 non-anxious control subjects were investigated with an adapted NPU-design (no, predictable, unpredictable threat) using whole-head magnetoencephalography (MEG). Group independent neural activity in the right dlPFC increased with decreasing threat predictability. PD patients showed a sustained hyperactivation of the vmPFC under threat and safety conditions. The magnitude of hyperactivation was inversely correlated with PDs subjective arousal and anxiety sensitivity. Both PD and SP patients revealed decreased parietal processing of affective stimuli. Findings indicate overgeneralization between threat and safety conditions and increased need for emotion regulation via the vmPFC in PD, but not SP patients. Both anxiety disorders showed decreased activation in parietal networks possibly indicating attentional avoidance of affective stimuli. Present results complement findings from fear conditioning studies and underline overgeneralization of fear, particularly in PD.

Healthy individuals maintain adaptive stimulus evaluation under predictable and unpredictable threat.

The anxiety inducing paradigms such as the threat-of-shock paradigm have provided ample data on the emotional processing of predictable and unpredictable threat, but little is known about the processing of aversive, threat-irrelevant stimuli in these paradigms. We investigated how the predictability of threat influences the neural visual processing of threat-irrelevant fearful and neutral faces. Thirty-two healthy individuals participated in an NPU-threat test, consisting of a safe or neutral condition (N) and a predictable (P) as well as an unpredictable (U) threat condition, using audio-visual threat stimuli. In all NPU-conditions, we registered participants' brain responses to threat-irrelevant faces via magnetoencephalography. The data showed that increasing unpredictability of threat evoked increasing emotion regulation during face processing predominantly in dorsolateral prefrontal cortex regions during an early to mid-latency time interval. Importantly, we obtained only main effects but no significant interaction of facial expression and conditions of different threat predictability, neither in behavioral nor in neural data. Healthy individuals with average trait anxiety are thus able to maintain adaptive stimulus evaluation processes under predictable and unpredictable threat conditions.

Prepare for scare-Impact of threat predictability on affective visual processing in spider phobia.

The visual processing of emotional faces is influenced by individual's level of stress and anxiety. Valence unspecific affective processing is expected to be influenced by predictability of threat. Using a design of phasic fear (predictable threat), sustained anxiety (unpredictable threat) and safety (no threat), we investigated the magnetoencephalographic correlates and temporal dynamics of emotional face processing in a sample of phobic patients. Compared to non-anxious controls, phobic individuals revealed decreased parietal emotional attention processes during affective processing at mid-latency and late processing stages. While control subjects showed increasing parietal processing of the facial stimuli in line with decreasing threat predictability, phobic subjects revealed the opposite pattern. Decreasing threat predictability also led to increasing neural activity in the orbitofrontal and dorsolateral prefrontal cortex at mid-latency stages. Additionally, unpredictability of threat lead to higher subjective discomfort compared to predictability of threat and no threat safety condition. Our findings indicate that visual processing of emotional information is influenced by both stress induction and pathologic anxiety.

Impact of electroconvulsive therapy on magnetoencephalographic correlates of dysfunctional emotional processing in major depression.

In major depressive disorder (MDD), electrophysiological and imaging studies provide evidence for a reduced neural activity in parietal and dorsolateral prefrontal regions. In the present study, neural correlates and temporal dynamics of visual affective perception have been investigated in patients with unipolar depression in a pre/post treatment design using magnetoencephalography (MEG). Nineteen in-patients and 19 balanced healthy controls passed MEG measurement while passively viewing pleasant, unpleasant and neutral pictures. After a 4-week treatment with electroconvulsive therapy or 4-week waiting period without intervention respectively, 16 of these patients and their 16 corresponding controls participated in a second MEG measurement. Before treatment neural source estimations of magnetic fields evoked by the emotional scenes revealed a general bilateral parietal hypoactivation in depressed patients compared to controls predominately at early and mid-latency time intervals. Successful ECT treatment, as reflected by a decline in clinical scores (Hamilton Depression Scale; HAMD) led to a normalization of this distinct parietal hypoactivation. Effective treatment was also accompanied by relatively increased neural activation at right temporo-parietal regions. The present study indicates dysfunctional parietal information processing and attention processes towards emotional stimuli in MDD patients which can be returned to normal by ECT treatment. Since convergent neural hypoactivations and treatment effects have recently been shown in MDD patients before and after pharmacological therapy, this electrophysiological correlate might serve as a biomarker for objective treatment evaluation and thereby potentially advance treatment options and support the prediction of individual treatment responses.