Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: To progress adolescent mental health research beyond our present achievements-a complex account of brain and environmental risk factors without understanding neurobiological embedding in the environment-we need methods to uncover relationships between the developing brain and real-world environmental experiences.

Methods: We investigated associations between brain function, environments, and emotional and behavioral problems using participants from the Adolescent Brain Cognitive Development (ABCD) Study (n = 2401 female). We applied manifold learning, a promising technique for uncovering latent structure from high-dimensional biomedical data such as functional magnetic resonance imaging. Specifically, we developed exogenous PHATE (potential of heat-diffusion for affinity-based trajectory embedding) (E-PHATE) to model brain-environment interactions. We used E-PHATE embeddings of participants' brain activation during emotional and cognitive processing tasks to predict individual differences in cognition and emotional and behavioral problems both cross-sectionally and longitudinally.

Results: E-PHATE embeddings of participants' brain activation and environments at baseline showed moderate-to-large associations with total, externalizing, and internalizing problems at baseline, across several subcortical regions and large-scale cortical networks, compared with the zero-to-small effects achieved by voxelwise data or common low-dimensional embedding methods. E-PHATE embeddings of the brain and environment at baseline were also related to emotional and behavioral problems 2 years later. These longitudinal predictions showed a consistent moderate effect in the frontoparietal and attention networks.

Conclusions: The embedding of the adolescent brain in the environment yields enriched insight into emotional and behavioral problems. Using E-PHATE, we demonstrated how the harmonization of cutting-edge computational methods with longstanding developmental theories advances the detection and prediction of adolescent emotional and behavioral problems.

Background: Adolescents raised in families with different maternal and paternal parenting combinations exhibit variations in neurocognition and psychopathology; however, whether neural differences exist remains unexplored. This study used a longitudinal twin sample to delineate how different parenting combinations influence adolescent brain structure and to elucidate the genetic contribution.

Methods: A cohort of 216 twins participated in parenting assessments during early adolescence and underwent magnetic resonance imaging scanning during middle adolescence. We utilized latent profile analysis to distinguish between various maternal and paternal parenting profiles and subsequently investigated their influences on brain anatomy. Biometric analysis was applied to assess genetic influences on brain structure, and associations with internalizing symptoms were explored.

Results: In early adolescence, 4 parenting profiles emerged, which were characterized by levels of harshness and hostility in one or both parents. Compared with adolescents in "catparent" families (low harshness/hostility in both parents), those raised in "tigermom" families (harsh/hostile mother only) exhibited a smaller nucleus accumbens volume and larger temporal cortex surface area; those in "tigerdad" families demonstrated larger thalamus volumes; and those in "tigerparent" families displayed smaller volumes in the midanterior corpus callosum. Genetic risk factors contributed significantly to the observed brain structural heterogeneity and internalizing symptoms. However, the influences of parenting profiles and brain structure on internalizing symptoms were not significant.

Conclusions: The findings underscore distinct brain structural features linked to maternal and paternal parenting combinations, particularly in terms of subcortical volume and cortical surface area. This study suggests an interdependent role of maternal and paternal parenting in shaping adolescent neurodevelopment.

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Background: Restricted scan path mode is hypothesized to explain abnormal scanning patterns in patients with schizophrenia. Here, we calculated entropy scores (drawing on gaze data to measure the statistical randomness of eye movements) to quantify how strategical and random participants were when processing image stimuli.

Methods: Eighty-six patients with first-episode schizophrenia (FES), 124 individuals at clinical high risk (CHR) for psychosis, and 115 healthy control participants (HCs) completed an eye-tracking examination while freely viewing 35 static images (each presented for 10 seconds) and cognitive assessments. We compared group differences in the overall entropy score, as well as entropy scores under various conditions. We also investigated the correlations between entropy scores and symptoms and cognitive function.

Results: Increased overall entropy scores were noted in the FES and CHR groups compared with the HC group, and these differences were already apparent within 0 to 2.5 seconds. In addition, the CHR group exhibited higher entropy than the HC group when viewing low-meaning images. Moreover, the entropy within 0 to 2.5 seconds showed significant correlations with negative symptoms in the FES group, attention/vigilance scores in the CHR group, and speed of processing and attention/vigilance scores across all 3 groups.

Conclusions: The results indicate that individuals with FES and those at CHR scanned pictures more randomly and less strategically than HCs. These patterns also correlated with clinical symptoms and neurocognition. The current study highlights the potential of the eye movement entropy measure as a neurophysiological marker for early psychosis.

Background: Risk for bipolar disorder (BD) is increased among individuals with a family history or subthreshold mood symptoms. However, the brain structural developments associated with these BD risks remain unknown.

Methods: This longitudinal cohort study examined the brain gray matter volume (GMV) developmental features of familial and symptomatic risks for BD and their associations with participants' global function levels. We recruited unaffected BD offspring with (n = 26, 14 female, mean ± SD age = 14.9 ± 2.9 years) or without (n = 35, 19 female, age = 15.3 ± 2.7 years) subthreshold manic or depressive symptoms and unaffected non-BD offspring with (n = 49, 30 female, age = 14.5 ± 2.2 years) or without (n = 68, 37 female, age = 15.0 ± 2.3 years) symptoms. The offspring had no mood disorder diagnosis prior to the study. The average follow-up duration was 2.63 ± 1.63 years.

Results: At baseline, we found significant interactive effects of familial risk and subthreshold symptoms that indicated that the symptomatic offspring exhibited markedly large GMV in the brain affective and cognitive circuitries. During follow-up, the combined group of BD offspring (symptomatic and nonsymptomatic) displayed a more accelerated GMV decrease than BD nonoffspring in the hippocampus and anterior cingulate cortex. In contrast, the combined group of symptomatic participants (offspring and nonoffspring) displayed a slower GMV decrease than nonsymptomatic participants in the ventromedial prefrontal cortex. Larger GMV at baseline and accelerated GMV decrease during follow-up prospectively and longitudinally predicted positive global function changes. All results survived multiple testing correction.

Conclusions: These findings indicated that familial and symptomatic risks of BD are associated with distinct brain structural developments and unraveled key brain developmental features of particularly vulnerable high-risk individuals to subsequent functional deterioration.

Background: Nonsuicidal self-injury (NSSI) behavior is significantly prevalent in both adolescents and psychiatric populations, particularly in individuals with major depressive disorder. NSSI can be considered a result of risky decision making in response to negative emotions, where individuals choose self-harm over other less harmful alternatives, suggesting a potential decision-making deficit in those engaging in NSSI. This study delves into the complex relationship between NSSI and depression severity in decision making and its cognitive underpinnings.

Methods: We assessed decision behaviors in 57 patients with major depressive disorder and NSSI, 42 patients with major depressive disorder without NSSI, and 142 healthy control participants using the Balloon Analog Risk Task, which involves risk taking, learning, and exploration in uncertain scenarios. Using computational modeling, we dissected the nuanced cognitive dimensions influencing decision behaviors. A novel statistical method was developed to elucidate interaction effects between NSSI and depression severity.

Results: Contrary to common perceptions, we found that individuals with NSSI behaviors were typically more risk averse. There was also a complex interaction between NSSI and depression severity in shaping risk-taking behaviors. As depressive symptoms intensified, the individuals with NSSI began to perceive less risk and behave more randomly.

Conclusions: This research provides new insights into the cognitive aspects of NSSI and depression, highlighting the importance of considering the influence of comorbid mental disorders when investigating the cognitive underpinnings of such behaviors, especially in the context of prevalent cross-diagnostic phenomena such as NSSI behaviors.