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.
Abstract 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.
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.
In 2770 individuals, we used principal component analysis (PCA) to identify a multivariate signature of cortical thickness patterns and relate it to relevant system‐level variables in individuals with bipolar disorders and healthy controls. This method systematically outperformed previous K‐means clustering in the same sample in terms of model fit, and differentiation between individuals. PCA provided a superior method for studying individual differences in brain structure for psychiatric illnesses.
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.
•Stress increases from No to Predictable to Unpredictable threat (NPU-conditions).•DlPFC activity to faces in NPU-conditions follows the stress pattern.•DlPFC activity is interpreted as emotion regulation of faces in NPU-conditions.•Preferred processing of fearful faces is not affected by NPU-conditions.•When faces don't predict threat, processing of facial expressions remains adaptive.
•Threat predictability influences prefrontal cortical face processing.•Unpredictability of threat leads to increased prefrontal emotion regulation.•Phobic patients reveal decreased parietal emotional ...processing.
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.
While individuals with bipolar disorder are assumed to recover between mood episodes, some nevertheless experience lingering subsyndromal symptoms and suffer from cognitive and functional ...impairments. Here, we propose that these enduring impairments may be linked to aberrations in brain networks. To test this, we conducted a resting-state functional magnetic resonance imaging (fMRI) study and used network-based statistic to compare functional connectivity between euthymic individuals with bipolar disorder (N = 96) and healthy control individuals (N = 61) both within and between resting-state networks. We also investigated the association of functional connectivity with lingering psychomotor symptoms and illness severity in bipolar disorder. We found stronger functional connectivity between the somatomotor network and the frontoparietal network in individuals with bipolar disorder compared with healthy controls, but weaker functional connectivity within the somatomotor network as well as between the somatomotor and the visual network. Results remained after adjusting for antipsychotic medication. No significant association with psychomotor performance and illness severity was found. We conclude that stronger functional connectivity between the somatomotor and frontoparietal network might be associated with lingering symptoms in bipolar euthymia. Dysconnectivity within the somatomotor network might relate to psychomotor symptoms beyond the impact of medication. Our findings contribute to the sparse field of somatomotor network aberrancies in bipolar disorder and may present a potential target for brain stimulation treatment.
•Functional connectivity differs between euthymic bipolar disorder and controls.•The functional connectivity between somatomotor and frontoparietal network was higher in bipolar disorder.•The functional connectivity of the somatomotor network was lower in bipolar disorder.
