Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

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 with 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 that social task performance would relate to general motivation and 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 (ρ = 0.71, p < .001). Both social and nonsocial task motivation related similarly to self-reported general motivation (social, β = 0.16; nonsocial, β = 0.13) and to self-reported approach motivation (social, β = 0.14; nonsocial, β = 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 to better characterize normative and pathological variation and develop personalized interventions targeting specific contributors to social impairment.

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 598 individuals (347 amyloid positive [58% female], 251 amyloid negative [62% female] subset in tau positron emission tomography and functional magnetic resonance imaging cohorts) from the A4 (Anti-Amyloid Treatment in Asymptomatic AD) Study. In the tau positron emission tomography cohort, we used amygdalar segmentations to examine representative nuclei from 3 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 functional magnetic resonance imaging 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 the 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 the amygdala to other temporal regions, the insula, and the orbitofrontal cortex, but medial amygdala to retrosplenial cortex connectivity 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 be related to early mood symptoms in AD.

Background: Abnormalities in dorsolateral prefrontal cortex (DLPFC) oscillations are neurophysiological signatures of schizophrenia thought to underlie its cognitive deficits. Transcranial magnetic stimulation with electroencephalography (TMS-EEG) provides a measure of cortical oscillations unaffected by sensory relay functionality and/or patients' level of engagement, which are important confounding factors in schizophrenia. Previous TMS-EEG work showed reduced fast, gamma-range oscillations and a slowing of the main DLPFC oscillatory frequency, or natural frequency, in chronic schizophrenia. However, it is unclear whether this DLPFC natural frequency slowing is present in early-course schizophrenia (EC-SCZ) and is associated with symptom severity and cognitive dysfunction.

Methods: We applied TMS-EEG to the left DLPFC in 30 individuals with EC-SCZ and 28 healthy control participants. Goal-directed working memory performance was assessed using the AX-Continuous Performance Task. The EEG frequency with the highest cumulative power at the stimulation site, or natural frequency, was extracted. We also calculated the local relative spectral power as the average power in each frequency band divided by the broadband power.

Results: Compared with the healthy control group, the EC-SCZ group had reduced DLPFC natural frequency (p = .0000002, Cohen's d = -2.32) and higher DLPFC beta-range relative spectral power (p = .0003, Cohen's d = 0.77). In the EC-SCZ group, the DLPFC natural frequency was inversely associated with negative symptoms. Across all participants, the beta band relative spectral power negatively correlated with AX-Continuous Performance Task performance.

Conclusions: DLPFC oscillatory slowing is an early pathophysiological biomarker of schizophrenia that is associated with its symptom severity and cognitive impairments. Future work should assess whether noninvasive neurostimulation, including repetitive TMS, can ameliorate prefrontal oscillatory deficits and related clinical functions in patients with EC-SCZ.

Background: The anterior limb of the internal capsule (ALIC) is a white matter structure that connects the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation for obsessive-compulsive disorder. There is strong interest in improving deep brain stimulation targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions.

Methods: Following algorithm development and refinement, we analyzed 43 control participants, each with 2 sets of 3T magnetic resonance imaging data and a subset of 5 control participants with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on PFC regions of interest, and we analyzed the relationships among bundles.

Results: We successfully reproduced the topographies established by previous anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intraparticipant variability than interparticipant variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline.

Conclusions: Our diffusion magnetic resonance imaging algorithm reliably generates biologically validated ALIC white matter reconstructions, thereby allowing for more precise modeling of fibers for neuromodulation therapies.

Background: Posttraumatic stress disorder (PTSD) is characterized not only by its direct association with traumatic events but also by a potential deficit in inhibitory control across emotional, cognitive, and sensorimotor domains. Recent research has shown that a continuous sensorimotor feedback control task, the rapid assessment of motor processing paradigm, can yield reliable measures of individual sensorimotor control performance. This study used this paradigm to investigate control deficits in PTSD compared with both a healthy volunteer group and a non-PTSD psychiatric comparison group.

Methods: We examined control processing using the rapid assessment of motor processing paradigm in a sample of 40 individuals with PTSD, matched groups of 40 individuals with mood and anxiety complaints, and 40 healthy control participants. We estimated K_p (drive) and K_d (damping) parameters using a proportional-derivative control modeling approach.

Results: The K_p parameter was lower in the PTSD group than in the healthy control (Cohen's d = 0.86) and mood and anxiety (Cohen's d = 0.63) groups. After controlling for color-word inhibition, K_p remained lower in the PTSD group than in the healthy control (Cohen's d = 0.79) and mood and anxiety (Cohen's d = 0.62) groups. Mediation analysis showed that K_d significantly mediated the relationship between PTSD and control deficits in the K_p parameter, with 96% of the effect being mediated by K_d.

Conclusions: These findings underscore the potential of using dynamic control paradigms to elucidate the control dysfunctions in PTSD and suggest that different psychiatric conditions may distinctly influence subcomponents of sensorimotor control.

There is growing interest in the ketogenic diet as a treatment for bipolar disorder (BD), and there are promising anecdotal and small case study reports of efficacy. However, the neurobiological mechanisms by which diet-induced ketosis might ameliorate BD symptoms remain to be determined, particularly in manic and hypomanic states-defining features of BD. Identifying these mechanisms will provide new markers to guide personalized interventions and provide targets for novel treatment developments for individuals with BD. In this critical review, we describe recent findings highlighting 2 types of neurobiological abnormalities in BD: 1) mitochondrial dysfunction and 2) neurotransmitter and neural network functional abnormalities. We link these abnormalities to mania/hypomania and depression in BD and then describe the biological underpinnings by which the ketogenic diet may have a beneficial effect in individuals with BD. We end the review by describing approaches that can be employed in future studies to elucidate the neurobiology that underlies the therapeutic effect of the ketogenic diet in BD. Doing this may provide marker predictors to identify individuals who will respond well to the ketogenic diet, as well as offer neural targets for novel treatment developments for BD.

To mitigate limitations of self-reported mood assessments, we introduce a novel affective bias task. The task quantifies instantaneous emotional state by leveraging the phenomenon of affective bias, in which people interpret external emotional stimuli in a manner consistent with their current emotional state. This study establishes task stability in measuring and tracking depressive symptoms in clinical and nonclinical populations. Initial assessment in a large nonclinical sample established normative ratings. Depressive symptoms were measured and compared with task performance in a nonclinical sample, as well as in a clinical cohort of individuals who were undergoing surgical evaluation for severe epilepsy. In both cohorts, a stronger negative affective bias was associated with a higher Beck Depression Inventory-II score. The affective bias task exhibited high stability and interrater reliability as well as construct validity in predicting depression levels in both cohorts, suggesting that the task is a reliable proxy for mood and a diagnostic tool for detecting depressive symptoms.

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.

Background: The mechanisms that link neural and behavioral indices of reduced reward sensitivity in depression, particularly in children, remain unclear. Reward positivity (RewP), a neural index of reward processing, has been consistently associated with depression. Separately, recent studies using the drift-diffusion model on behavioral data have delineated computational indices of reward sensitivity. Therefore, in the current study, we examined whether RewP is a neural mediator of drift-diffusion model-based indices of reward processing in predicting pediatric depression across varying levels of symptom severity.

Methods: A community sample of 166 girls, ages 8 to 14 years, completed 2 tasks. The first was a reward guessing task from which RewP was computed using electroencephalography; the second was a probabilistic reward-based decision-making task. On this second task, drift-diffusion model analysis was applied to behavioral data to quantify the efficiency of accumulating reward-related evidence (drift rate) and potential baseline bias (starting point) toward the differently rewarded choices. Depression severity was measured using the self-report Children's Depression Inventory.

Results: RewP was correlated with drift rate, but not starting point bias, toward the more rewarded choice. Furthermore, RewP completely mediated the association between a slower drift rate toward the more rewarded option and higher depression symptom severity.

Conclusions: Our findings suggest that reduced neural sensitivity to reward feedback may be a neural mechanism that underlies behavioral insensitivity to reward in children and adolescents with higher depression symptom severity, offering novel insights into the relationship between neural and computational indices of reward processing in this context.