Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear.

Methods: Youth from the Adolescent Brain and Cognitive Development^SM Study (ages 9-10 years at baseline) with a resting-state fMRI scan and mental health data were eligible for inclusion. Internalizing subscale scores from the Brief Problem Monitor - Youth Form were combined across two years of follow-up to generate a cumulative measure of internalizing symptoms. The total sample (n = 6521) was split into a large discovery dataset and a smaller validation dataset. Brain-behavior associations of resting-state functional connectivity (RSFC) with internalizing symptoms were estimated in the discovery dataset. The weighted contributions of each functional connection were aggregated using multivariate statistics to generate a polyneuro risk score (PNRS). The predictive power of the PNRS was evaluated in the validation dataset.

Results: The PNRS explained 10.73% of the observed variance in internalizing symptom scores in the validation dataset. Model performance peaked when the top 2% functional connections identified in the discovery dataset (ranked by absolute β-weight) were retained. The RSFC networks that were implicated most prominently were the default mode, dorsal attention, and cingulo-parietal networks. These findings were significant (p < 1*10^-6) as accounted for by permutation testing (n = 7000).

Conclusions: These results suggest that the neural phenotype associated with internalizing symptoms during adolescence is functionally distributed. The PNRS approach is a novel method for capturing relationships between RSFC and behavior.

Background: A developing theory and recent research suggest that heightened reactivity to uncertain stressors or threats may be an important individual difference factor that facilitates excessive drinking as a means of avoidance-based coping and characterizes individuals with current and past alcohol use disorder (AUD). Neuroimaging studies of unpredictable threat processing have repeatedly demonstrated activation of the anterior insula (AIC), anteromedial (AM) thalamus and dorsal anterior cingulate cortex (dACC). The present study aimed to understand how these three regions function as a network during anticipation of unpredictable threat (and predictable threat).

Methods: Participants were 43 young adults (aged 21-30) with AUD and 26 healthy controls. Functional magnetic resonance imaging and dynamic causal modeling were used to study inter-regional effective connectivities and predictable and unpredictable threat-related modulations thereof within this network. Parametric empirical Bayesian modeling was used to conduct between-group comparisons in effective connectivities.

Results: During unpredictable threat trials, the increased projection from the right AM thalamus to the right AIC was significantly present only in the AUD group. This directional influence was stronger among individuals who on average consumed more drinks per week. As expected, we found no group differences in modulatory changes to effective connectivities during predictable threat trials.

Conclusions: To our knowledge, this is the first study to examine directional interactions between key frontolimbic regions during anticipation of unpredictable and predictable threat and demonstrate the importance of 'bottom-up' thalamic-insular projections during unpredictable threat processing in AUD. Prospective studies are warranted to determine whether this association may be causal.

Background: People with psychosis and mood disorders experience disruptions in working memory; however, the underlying mechanism remains unknown. We focused on two potential mechanisms: first, poor attentional engagement should be associated with elevated levels of pre-stimulus alpha-band activity within the EEG, whereas impaired working memory encoding should be associated with reduced post-stimulus alpha suppression.

Methods: We collected EEG data from 68 people with schizophrenia, 43 people with bipolar disorder with a history of psychosis, and 53 people with major depressive disorder, as well as 90 healthy comparison subjects (HCS), while they completed a spatial working memory task. We quantified attention lapsing, memory precision, and memory capacity from the behavioral responses, and we quantified alpha using both traditional wavelet analysis as well as a novel approach for isolating oscillatory alpha power from aperiodic elements of the EEG signal.

Results: We found that (1) greater pre-stimulus alpha power estimated using traditional wavelet analysis predicted behavioral errors; (2) post-stimulus alpha suppression was reduced in the patient groups; and (3) reduced suppression was associated with lower likelihood of memory storage. However, we also observed that pre-stimulus alpha was larger among HCS compared to patients, and single-trial analyses showed that it was the aperiodic elements of the pre-stimulus EEG-not oscillatory alpha-that predicted behavioral errors.

Discussion: These results suggest that working memory impairments in serious mental illness primarily reflect an impairment in the post-stimulus encoding processes rather than reduced attentional engagement prior to stimulus onset.

Background: Individuals with schizophrenia (SZ) experience impairments in social cognition that contribute to poor functional outcomes. However, mechanisms of social cognitive dysfunction in SZ remain poorly understood, which impedes the design of novel interventions to improve outcomes. This pre-registered project (https://doi.org/10.17605/OSF.IO/JH5FC) examines the representation of social cognition in the brain's functional architecture across early and chronic SZ.

Methods: The study contains two parts: a confirmatory and an exploratory portion. In the confirmatory portion, we identified resting-state connectivity disruptions evident in early and chronic SZ. We performed a connectivity analysis using regions associated with social cognitive dysfunction in early and chronic SZ to test whether aberrant connectivity observed in chronic SZ (N=47; HC=52) was also present in early SZ (N=71, HC=47). In the exploratory portion, we assessed the out-of-sample generalizability and precision of predictive models of social cognition. We used machine learning to predict social cognition and established generalizability with out-of-sample testing and confound control.

Results: Results reveal decreases between left inferior frontal gyrus and intraparietal sulcus in early and chronic SZ, which are significantly associated with social and general cognition and global functioning in chronic SZ and with general cognition and global functioning in early SZ. Predictive modeling reveals the importance of out-of-sample evaluation and confound control.

Conclusion: This work provides insights into the functional architecture in early and chronic SZ and suggests that IFG-IPS connectivity could be a prognostic biomarker of social impairments and a target for future interventions (e.g. neuromodulation) focused on improved social functioning.

Introduction: Neurodegenerative diseases require collaborative, multi-site research to comprehensively grasp their complex and diverse pathological progression, yet there is caution in aggregating global data due to data heterogeneity. The current study investigates brain structure across stages of Alzheimer's disease (AD), and how relationships vary across sources of heterogeneity.

Methods: Using 6 international datasets(n>27,000), associations of structural neuroimaging markers were investigated in relation to the AD continuum via meta-analysis. We investigated whether associations varied across elements of MRI acquisition, study design and populations.

Results: Modest differences in associations were found dependent on how data were acquired, however patterns were similar. Preliminary results suggest neuroimaging marker-AD relationships differ across ethnic groups.

Discussion: Diversity in data offers unique insights into the neural substrate of AD, however harmonised processing and transparency of data collection is needed. Global collaborations should embrace inherent heterogeneity that exists within the data and quantify its contribution to research findings at the meta-analytical stage.

Theta burst stimulation (TBS) is a non-invasive brain stimulation technique that can modulate neural activity. The effect of TBS on regions beyond the motor cortex remains unclear. With increased interest in applying TBS to non-motor regions for research and clinical purposes, these effects must be understood and characterised. We synthesised the electrophysiological effects of a single session of TBS, as indexed by electroencephalography (EEG) and concurrent transcranial magnetic stimulation and EEG (TMS-EEG), in non-clinical participants. We reviewed 79 studies that administered either continuous TBS (cTBS) or intermittent TBS (iTBS) protocols. Broadly, cTBS suppressed and iTBS facilitated evoked response component amplitudes. Response to TBS as measured by spectral power and connectivity was much more variable. Variability increased in the presence of task stimuli. There was a large degree of heterogeneity in the research methodology across studies. Additionally, the effect of individual differences on TBS response is insufficiently investigated. Future research investigating the effects of TBS as measured by EEG must consider methodological and individual factors that may affect TBS outcomes.

Background: Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) causes long-lasting cognitive deficits associated with altered functional connectivity. Eigenvector centrality (EC) mapping represents a powerful new method for data-driven voxel-wise and time-resolved estimation of network importance - beyond changes in classical 'static' functional connectivity.

Methods: To assess changes in functional brain network organization, we applied EC mapping in 73 patients with NMDARE and 73 matched healthy controls. Areas with significant group differences were further investigated using (i) spatial clustering analyses, (ii) time series correlation to assess synchronicity between the hippocampus and cortical brain regions, and (iii) correlation with cognitive and clinical parameters.

Results: Dynamic, time-resolved EC showed significantly higher variability in 13 cortical areas (p_(FWE)<0.05) in patients with NMDARE compared to HC. Areas with dynamic EC group differences were spatially organized in centrality clusters resembling resting-state networks. Importantly, variability of dynamic EC in the frontotemporal cluster was associated with impaired verbal episodic memory in patients (r=-0.25, p=0.037). EC synchronicity between the hippocampus and the medial prefrontal cortex was reduced in patients compared to HC (p_(FWE)<0.05, t_(max)=3.76), and associated with verbal episodic memory in patients (r=0.28, p=0.019). Static EC analyses showed group differences in only one brain region (left intracalcarine cortex).

Conclusions: Widespread changes in network dynamics and reduced hippocampal-medial prefrontal synchronicity were associated with verbal episodic memory deficits and may thus represent a functional neural correlate of cognitive dysfunction in NMDARE. Importantly, dynamic EC detected substantially more network alterations than traditional static approaches, highlighting the potential of this method to explain long-term deficits in NMDARE.

Background: Social motivation is crucial for healthy interpersonal connections and is impaired in a subset of the general population and across many psychiatric disorders. However, compared to nonsocial (e.g., monetary) motivation, social motivation has been understudied in quantitative behavioral work, especially regarding willingness to exert social effort. We developed a novel social effort discounting task, paired with a monetary task to examine motivational specificity. We expected social task performance would relate to general motivation also show selective relationships with self-reported avoidance tendencies and with sociality.

Methods: An analyzed sample of 397 participants performed the social and nonsocial effort discounting task online, along with self-report measures of various aspects of motivation and psychiatric symptomatology.

Results: Social and nonsocial task motivation correlated strongly (rho=0.71 p<0.001). Both social and nonsocial task motivation related similarly to self-reported general motivation (social ß=0.16; nonsocial ß=0.13) and to self-reported approach motivation (social ß=0.14; nonsocial ß=0.11), with this common effect captured by a significant main effect across social and nonsocial conditions. Significant condition interaction effects supported a selective relationship of social task motivation with self-reported sociality and also with avoidance motivation.

Conclusions: Our novel social effort discounting task revealed both domain-general and social-specific components of motivation. In combination with other measures, this approach can facilitate further investigation of common and dissociable neurobehavioral mechanisms, in order to better characterize normative and pathological variation and develop personalized interventions targeting specific contributors to social impairment.

Background: Human learning unfolds under uncertainty. Uncertainty is heterogeneous with different forms exerting distinct influences on learning. While one can be uncertain about what to do to maximize rewarding outcomes, known as policy uncertainty, one can also be uncertain about general world knowledge, known as epistemic uncertainty. In complex and naturalistic environments such as the social world, adaptive learning may hinge on striking a balance between attending to and resolving each type of uncertainty. Prior work illustrates that people with anxiety-those with increased threat and uncertainty sensitivity-learn less from aversive outcomes, particularly as outcomes become more uncertain. How does a learner adaptively trade-off between attending to these distinct sources of uncertainty to successfully learn about their social environment?

Methods: We developed a novel eye-tracking method to capture highly granular estimates of policy and epistemic uncertainty based on gaze patterns and pupil diameter (a physiological estimate of arousal) RESULTS: These empirically derived uncertainty measures reveal that humans (N = 94) flexibly switch between resolving policy and epistemic uncertainty to adaptively learn about which individuals can be trusted and which should be avoided. However, those with increased anxiety (N = 49) do not flexibly switch between resolving policy and epistemic uncertainty, and instead express less uncertainty overall CONCLUSIONS: Combining modeling and eye-tracking techniques, we show that altered learning in people with anxiety emerges from an insensitivity to policy uncertainty and rigid choice policies, leading to maladaptive behaviors with untrustworthy people.

Background: While the amygdala receives early tau deposition in Alzheimer's disease (AD) and is involved in social and emotional processing, the relationship between amygdalar tau and early neuropsychiatric symptoms in AD is unknown. We sought to determine whether focal tau binding in the amygdala and abnormal amygdalar connectivity were detectable in a preclinical AD cohort and identify relationships between these and self-reported mood symptoms.

Methods: We examined n=598 individuals (n=347 amyloid-positive (58% female), n=251 amyloid-negative (62% female); subset into tau PET and fMRI cohorts) from the A4 Study. In the tau PET cohort, we used amygdalar segmentations to examine representative nuclei from three functional divisions of the amygdala. We analyzed between-group differences in division-specific tau binding in the amygdala in preclinical AD. We conducted seed-based functional connectivity analyses from each division in the fMRI cohort. Finally, we conducted exploratory post-hoc correlation analyses between neuroimaging biomarkers of interest and anxiety and depression scores.

Results: Amyloid-positive individuals demonstrated increased tau binding in medial and lateral amygdala, and tau binding in these regions was associated with mood symptoms. Across amygdalar divisions, amyloid-positive individuals had relatively higher regional connectivity from amygdala to other temporal regions, insula, and orbitofrontal cortex, but medial amygdala to retrosplenial cortex was lower. Medial amygdala to retrosplenial connectivity was negatively associated with anxiety symptoms, as was retrosplenial tau.

Conclusions: Our findings suggest that preclinical tau deposition in the amygdala and associated changes in functional connectivity may relate to early mood symptoms in AD.