Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Individual differences in reward learning and motivational processes are reflected in sign-tracking behavior. This phenotype, characterized by heightened attraction to reward-associated cues, is linked to increased impulsivity, addiction vulnerability, and externalizing psychiatric disorders.

Methods: To identify underlying neural differences, we tested whether high sign-tracking individuals exhibited an elevated mid-frontal theta/beta ratio, a resting electroencephalography (EEG) biomarker indicating reduced cortical control over subcortical motivational circuits. Sixty volunteers completed a 5-minute resting-state EEG session followed by a Pavlovian learning task. Participants were classified into high or low sign-tracking groups based on objective eye-gaze metrics.

Results: High sign-tracking participants demonstrated a significantly higher mid-frontal theta/beta ratio compared with the low sign-tracking group.

Conclusions: These findings identify the mid-frontal theta/beta ratio as a neural marker capable of distinguishing individual differences in reward cue reactivity. This suggests a pathway for targeted interventions aimed at the underlying cortical-subcortical dysregulation associated with sign-tracking and related vulnerabilities.

With a rapidly growing population of older adults worldwide, understanding how aging shapes mental and cognitive health is an urgent public health priority. Although older age has been considered protective against the development of posttraumatic stress disorder (PTSD), this pattern is far from universal. Emerging evidence indicates that older adults with a history of trauma may experience delayed-onset PTSD or a reemergence of symptoms after years of dormancy. In this review, we examine how age-related changes in the brain intersect with known PTSD mechanisms to influence trajectories of risk and resilience in later life. We focus on the canonical fear network-comprising the amygdala, hippocampus, and ventromedial prefrontal cortex-which is central to fear learning, memory, and emotion regulation. These regions are also highly vulnerable to aging and neurodegenerative processes; however, older adults remain underrepresented in both neurobiological and treatment studies of PTSD. We argue that the structural and functional aging of these systems may exacerbate difficulties with associative learning and emotion regulation while also interacting with psychosocial stressors unique to aging. At the same time, age-related strengths (such as positivity bias) may promote resilience. These insights carry important implications for clinical care; existing empirically supported psychotherapies may benefit from adaptations to account for age-related neural and cognitive shifts. A lifespan neuroscience framework is essential for identifying the shared mechanisms between PTSD and aging, with the goal of informing tailored, mechanism-driven interventions that promote the mental and cognitive health of trauma-exposed older adults.

Background: Accumulating evidence points to the cerebellum's role in executive functioning (EF) and transdiagnostic psychopathology. A general psychopathology p-factor, capturing shared variation across mental disorders, has been associated with EF deficits and structural alterations within the posterior cerebellum. One hypothesis is that the cerebellum contributes to general psychopathology because of its role in executive dysfunctions.

Methods: To test this hypothesis, we used functional magnetic resonance imaging (fMRI) data from the University of California, Los Angeles Consortium for Neuropsychiatric Phenomics study including 257 adults (ages 21-50 years) who met diagnostic criteria for schizophrenia, bipolar disorder, or attention-deficit/hyperactivity disorder or were healthy control participants. We examined relationships between p-factor scores and cerebellar activation across participants during 3 fMRI tasks of working memory (spatial capacity), cognitive flexibility (task switching), and response inhibition (stop signal). Specificity analyses of cerebellar activation associated with internalizing, externalizing, and thought disorder factor scores were also conducted.

Results: Robust posterior cerebellar activation was identified during all 3 fMRI tasks. Higher p-factor scores were associated with poorer EF performance, greater activation of cerebellar crus I/II and lobule VIIIA/B with increasing working memory difficulty, and greater activation of lobules VI and VIIIA/B during successful inhibition (R² range = 0.078-0.108). Associations between cerebellar activation and internalizing, externalizing, and thought disorder factor scores were largely overlapping with associations with the p-factor.

Conclusions: These novel results identify functional alterations within the posterior cerebellum during EF in individuals high in general psychopathology. Greater activation of the posterior cerebellum may be a transdiagnostic dysfunction reflecting inefficient information processing during EF present across disorder categories.

Background: Fear processing is multifaceted, involving dissociable neural and computational pathways that vary depending on its source and context. However, modality-specific fear processing, such as empathic versus subjective fear, remains poorly understood. Moreover, the role of these distinctions in clarifying the high comorbidity between generalized anxiety disorder (GAD) and major depressive disorder (MDD) has been understudied.

Methods: In the current study, we combined functional magnetic resonance imaging with multivariate pattern analysis to develop two neurofunctional models: one for empathic fear (face-induced empathic fear signature [FEFS], n = 81) and another for subjective fear (scene-induced subjective fear signature [SSFS], n = 81) evoked by visual stimuli. After validating these models in the independent cohorts (dynamic stimuli: n = 28), we generalized them to distinguish GAD and MDD during facial emotional-processing (n = 80) and pain empathy (n = 87) tasks.

Results: Our findings revealed that both models engaged distributed brain systems, including cortical regions (e.g., prefrontal, cingulate, insula, and parietal cortices) and subcortical areas (e.g., thalamus and amygdala). Crucially, we identified distinct functional profiles: FEFS-predominant regions were linked to execution, whereas SSFS-predominant regions mapped onto emotion processing. Notably, compared with SSFS, FEFS consistently discriminated between GAD and MDD during both fearful expression and affective pain empathy processing.

Conclusions: These findings demonstrate modality-specific processing of subjective and empathic fear, revealing distinct empathy-related neural signatures that may serve as potential biomarkers for differentiating GAD and MDD, offering new insights into their neurobiological distinctions.

Background: Studies investigating social anxiety disorder (SAD) have reported inconsistent alterations in white matter (WM) microstructure. The ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)-Anxiety Working Group investigated differences in the microstructure of 25 WM tracts between individuals with SAD and healthy control (HC) participants in a mega-analysis.

Methods: We analyzed data from 487 individuals with SAD and 1604 HC participants (ages 8-65 years) from 12 cohorts worldwide. Analyses and quality control were performed using standardized ENIGMA diffusion tensor imaging protocols. We primarily examined fractional anisotropy (FA) as the main parameter of WM microstructure. Linear mixed-effects analyses were conducted to compare individuals with SAD with HC participants in the total sample. Next, adult (age >21) and adolescent (age ≤21) samples were analyzed separately. In sensitivity analyses, additional effects of sex, medication, symptom severity, and comorbid psychiatric disorders were investigated.

Results: In the total sample, individuals with SAD showed lower FA in several tracts, including the corpus callosum and fornix, compared with HC participants. Widespread sex × diagnosis interactions were observed, mostly driven by lower FA in females with SAD. Adults with SAD showed lower FA in multiple tracts, while age × diagnosis interactions were observed in adolescents.

Conclusions: Using a mega-analytic approach, several differences in WM microstructure were found between individuals with SAD and HC participants, both in the full sample and in age group-specific sensitivity analyses. Some neurobiological changes in WM tracts in individuals with SAD may vary with age and sex, whereas others may relate to broader transdiagnostic neurobiological features underlying psychopathology. Further research should investigate these issues in more detail.

Background: The structure and tissue composition of the cortex may be sensitive to loss of synapses. However, the relation between measurements of synaptic density, cortical thickness and microstructure remains unknown. These measures are reduced in schizophrenia spectrum disorders (SSD) and to a lesser degree in unaffected relatives. Here, we investigated if synaptic density and cortical (micro)structure are related in healthy subjects, and if these associations are altered in patients with SSD and unaffected siblings.

Methods: Brain uptake of the tracer [¹¹C]UCB-J, measured in-vivo with positron emission tomography (PET) was used as a proxy measure for synaptic density. Healthy subjects (n=25), patients with SSD (n=24) and unaffected siblings (n=25) underwent [¹¹C]UCB-J PET, T1-weighted MRI and diffusion weighted imaging scans.

Results: We found a positive relation between [¹¹C]UCB-J BP_ND and cortical thickness (β=0.61, p=.02) and showed a similar (yet non-significant) positive relation in unaffected siblings (β=0.41, p=.09). This relation was not present in patients with SSD (β=0.03, p=.90). Additionally, [¹¹C]UCB-J BP_ND had a negative relation with mean diffusivity (MD) in controls (β=-0.54, p=.01) and unaffected siblings (β=-0.47, p=.01). In patients with SSD, again, this relation was disrupted (β=0.07, p=.78).

Conclusion: We found a robust association between synaptic density and cortical (micro)structure in healthy individuals. The lost relation in patients suggest that SSD-related synapse loss is not proportional to the number and organization of grey matter constituents. Despite the shared genetic risk, unaffected siblings preserve this relation, suggesting absence of a second hit inducing excessive synaptic pruning.

Background: Between-subjects studies suggest that psychostimulants can shift whole-brain functional connectivity (FC) toward patterns linked to heightened sustained attention. In this study, we examined how a single dose of methamphetamine (MA) (20 mg) changes sustained attention and associated network-level functional organization in healthy adults.

Methods: We conducted a within-subject study in which 76 healthy participants completed 2 functional magnetic resonance imaging (fMRI) scanning sessions after taking MA or placebo. We tested whether MA selectively affects behavioral and fMRI connectivity signatures of sustained attention and arousal.

Results: Under MA, participants showed improved sustained attention task performance as well as FC signatures of higher sustained attention and arousal. These network changes emerged consistently across resting-state and task-based fMRI, indicating that MA influences attention- and arousal-related networks regardless of cognitive context. Furthermore, a support vector classifier distinguished FC patterns observed during the MA and placebo conditions, identifying connections overlapping with networks related to arousal.

Conclusions: Together, these findings are consistent with previous work on other psychostimulants such as methylphenidate, showing that MA modulates sustained attention and related large-scale brain networks. By revealing how MA modulates attention-relevant brain connectivity patterns, our results highlight the utility of psychostimulants as causal tools for probing the robustness, generalizability, and interpretability of brain-based biomarkers of behavior.

Background: Major depressive disorder (MDD) involves subtle, distributed alterations across multiple large-scale resting-state brain networks (RSNs), highlighting the need for integrative approaches to uncover synergistic network patterns driving clinical symptoms.

Methods: In this study, we used a dynamic systems approach to investigate patterns of simultaneous RSN activation-i.e., coactivation-in 867 participants, including 487 healthy control participants (HCs), 175 patients with current MDD (cMDD), and 205 patients with remitted MDD (rMDD) from the Marburg-Münster Affective Disorders Cohort Study. Using a pairwise maximum entropy model, we estimated RSN coactivation probabilities based on resting-state fMRI data of 7 RSNs-default mode network (DMN), frontoparietal network (FPN), sensorimotor network (SMN), visual network (VIS), salience network, dorsal attention network (DAN), and language network (LAN)-capturing 128 possible states of coactivation.

Results: General linear models revealed elevated coactivation probabilities in cMDD, particularly for states involving the DMN, FPN, and VIS, with the coactivation state involving the DMN, VIS, DAN, FPN, and LAN showing the strongest association with MDD diagnosis, clinical status, and symptom severity. Furthermore, canonical correlation analysis (CCA) on the total sample identified 2 distinct network-symptom profiles: canonical variate (CV) 1 linked high DMN and DAN coactivation probabilities to cognitive, insomnia, and mood/anhedonia symptoms, while CV2 tied the SMN and VIS to cognitive and somatic symptom domains.

Conclusions: These results demonstrate that MDD, especially during acute episodes, is marked by a dominance of DMN, FPN, and VIS coactivation, pointing to altered dynamic network organization. Further, the results highlight how changes in brain state dynamics are linked to MDD symptoms.

Background: Effort-cost decision making (ECDM) is a core component of motivational deficits across diagnostic boundaries, but the mechanisms underlying ECDM deficits are not yet fully understood. Importantly, similar behavioral phenotypes during ECDM paradigms may be associated with distinct underlying cognitive and affective processes across individuals.

Methods: We used a person-centered modeling approach to examine individual decision-making phenotypes (systematic or nonsystematic decision making) during both physical and cognitive ECDM in 5 diagnostic groups: healthy control (n = 90), schizophrenia spectrum disorder (SSD) (n = 67), current major depression (n = 70), remitted major depression (n = 52), and bipolar I disorder (n = 64). We examined the associations between ECDM phenotype, cognitive functioning, motivation, and diagnostic group.

Results: We found significant diagnostic group differences in the ECDM phenotype, such that individuals with an SSD, but not current or remitted major depression or bipolar disorder, were less likely to incorporate changing trialwise reward value information in cognitive effort exertion, with the same trend for physical effort. In all diagnostic groups, nonsystematic decision making was associated with lower cognitive functioning but not lower motivation. In addition, individuals with an SSD showed steeper effort discounting during both physical and cognitive ECDM paradigms.

Conclusions: These findings point toward substantial individual differences in ECDM phenotypes both within and across diagnostic boundaries, suggesting that deficits in subjective value representation may be more prevalent in psychosis compared with in mood disorders.

Background: Neuroimaging methods rely on models of neurovascular coupling that assume hemodynamic responses are canonical, evolving seconds after changes in neural activity. However, emerging evidence reveals noncanonical blood oxygen level-dependent (BOLD) responses that are delayed under stress and aberrant in neuropsychiatric conditions.

Methods: We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging data in people with schizophrenia (n = 57) and psychiatrically unaffected participants (n = 46) during a resting-state paradigm. We focused on alpha band power to examine correlations with voxelwise, time-lagged BOLD signals as a dynamic measure of EEG-BOLD coupling.

Results: We found pronounced diversity in the temporal profile of alpha-BOLD coupling across the brain. This included early coupling (0-2 seconds BOLD lag) for more posterior regions of the default mode network (DMN), thalamus, and brainstem. Anterior regions of the DMN showed coupling at more canonical lags (4-6 seconds), although some participants showed greater than expected lags associated with self-reported measures of stress and there were greater lag scores in participants with schizophrenia. Overall, noncanonical alpha-BOLD coupling is widespread across the DMN and other noncortical regions and is delayed in people with schizophrenia.

Conclusions: These findings suggest that hemodynamic signals are dynamically coupled to ongoing neural activity across distributed networks and that the hemoneural lag may be associated with subjective arousal or stress. Our work highlights the need for more studies of neurovascular coupling in psychiatric conditions.