Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Individuals with substance use disorder show impaired self-awareness of ongoing behavior. This deficit suggests problems with metacognition, operationalized in the cognitive neuroscience literature as the ability to monitor and evaluate the success of one's own cognition and behavior. However, the neural mechanisms of metacognition have not been characterized in a drug-addicted population.

Methods: Community samples of participants with opioid use disorder (OUD) (N=27) and healthy controls (N=29) performed a previously-validated fMRI metacognition task (perceptual decision-making task along with confidence ratings of performance). Measures of recent drug use and addiction severity were also acquired.

Results: Individuals with OUD had lower metacognitive sensitivity than controls (i.e., disconnection between task performance and task-related confidence). Trial-by-trial analyses showed that this overall group difference was driven by (suboptimally) low confidence in OUD during correct trials. In fMRI analyses, the task engaged an expected network of brain regions (e.g., rostrolateral prefrontal cortex and dorsal anterior cingulate/supplementary motor area, both previously linked to metacognition); group differences emerged in a large ventral anterior cluster that included the medial and lateral orbitofrontal cortex and striatum (higher activation in OUD). Trial-by-trial fMRI analyses showed group differences in rostrolateral prefrontal cortex activation, which further correlated with metacognitive behavior across all participants. Exploratory analyses suggested that the behavioral and neural group differences were exacerbated by recent illicit opioid use and unexplained by general cognition.

Conclusions: With confirmation and extension of these findings, metacognition and its associated neural circuits could become new, promising therapeutic targets in addiction.

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 EC-SCZ and 28 healthy control (HC) subjects. Goal-directed working memory performance was assessed using the "AX" Continuous Performance Task (AX-CPT). 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 (RSP) as the average power in each frequency band divided by the broadband power.

Results: Compared to HC, EC-SCZ had reduced DLPFC natural frequency (p=0.0000002, Cohen's d=-2.32) and higher DLPFC beta-range RSP (p=0.0003, Cohen's d=0.77). In EC-SCZ, the DLPFC natural frequency was inversely associated with negative symptoms. Across all participants, the beta-band RSP negatively correlated with the AX-CPT performance.

Conclusions: A 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 non-invasive neurostimulation can ameliorate prefrontal oscillatory deficits and related clinical functions in EC-SCZ.

Background: The anterior limb of the internal capsule (ALIC) is a white matter structure connecting the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation (DBS) for obsessive-compulsive disorder. There is strong interest in improving DBS 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 subjects each with 2 sets of 3T MRI data and a subset of 5 controls with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on prefrontal PFC regions of interest, and we analyzed the relationships among bundles.

Results: We successfully reproduced the topographies established by prior anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intra-subject variability relative to inter-subject 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.

Discussion: Our dMRI algorithm reliably generates biologically validated ALIC white matter reconstructions, allowing for more precise modelling of fibers for neuromodulation therapies.

Background: Late-life depression (LLD) is associated with cognitive impairment, yet substantial heterogeneity exists among patients. Data on the extent of cognitive impairments is inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant vs. nonresistant LLD and aimed to identify distinct cognitive subgroups. Additionally, we examined whether cognitive subgroups differentially responded to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS).

Methods: 165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared to healthy controls (HC) on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups.

Results: Patients with LLD, particularly TRD, exhibited significantly worse cognitive performance than HC. A three-cluster solution was found, including "Cognitively Intact" (n = 89), "Cognitively Diminished" (n = 29), and "Impaired Memory" (n = 47) subgroups. Both the "Cognitively Diminished" and "Impaired Memory" subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the "Cognitively Intact" group, though the latter did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment.

Conclusions: Patients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three identified cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationship among cognitive subgroups, cognitive decline, and neurodegeneration.

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 (RAMP) paradigm, can yield reliable measures of individual sensorimotor control performance. This study used this paradigm to investigate control deficits in PTSD relative to both healthy volunteer and a non-PTSD psychiatric comparison group.

Methods: We examined control processing using the RAMP paradigm in a sample of 40 individuals with PTSD, along with matched groups of 40 individuals with mood and anxiety (MA) complaints and 40 healthy controls (HC). We estimated K_p (drive) and K_d (damping) parameters using a proportion-derivative (PD) control modeling approach.

Results: The K_p parameter was lower in the PTSD group compared to the HC (Cohen's d = .86) and MA groups (Cohen's d = 0.63). After controlling for color-word inhibition, K_p remained lower in the PTSD group versus HC (Cohen's d = 0.79) and versus MA (Cohen's d = 0.62). 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 mediated by K_d.

Conclusions: These findings underscore the potential of using dynamic control paradigms to elucidate the control dysfunctions in PTSD and suggests 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), with promising anecdotal and small case study reports of efficacy. Yet, 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 therefore 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 two types of neurobiological abnormalities in BD: 1) mitochondrial dysfunction; and 2) neurotransmitter and neural network functional abnormalities. We will consequently link these abnormalities lead to mania/hypomania and depression in BD and then describe the biological underpinnings by which the ketogenic diet might have a beneficial effect in individuals with BD. We end the review by describing future approaches that can be employed to elucidate the neurobiology underlying the therapeutic effect of the ketogenic diet in BD. In so 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.

Background: Major depressive disorder (MDD) is characterized by strong emotional dysregulation. Mechanisms driving the negative affect in depression may be fast processes existing on an unconscious level.

Methods: A priming task was conducted using simultaneous EEG-fMRI measurement involving presentation of facial expressions (happy, sad, neutral) to examine the neurophysiological pathway of biased unconscious emotion processing in MDD. Priming prior to a target emotion created unconscious (16.7 ms primer) and conscious (150 ms primer) trials. A large sample of N = 126 was recruited, containing healthy controls (HC; n = 66; 37 women) and MDD (n = 60; 31 women).

Results: HC showed a shorter reaction time in happy, but not in sad or neutral trials compared to MDD. N170 amplitudes were lower in trials with unconscious compared to conscious primer presentation. N170 amplitudes correlated with cortical (right fusiform gyrus (FFG), right middle temporal gyrus, right inferior temporal gyrus, left supplementary motor area, right middle frontal gyrus) and subcortical brain regions (right amygdala). The strength of N170 and brain activity correlation increased when the stimulus was consciously presented. Presented emotions did not affect the correlation of N170 values and brain activity.

Conclusions: Our findings show that MDD may exhibit biased emotion regulation abilities at a behavioral and neurophysiological level. Face-sensitive event-related potentials demonstrate a correlation with heightened brain activity in regions associated with both face recognition (FFG) and emotion processing (amygdala). These findings are evident in both MDD and HC, with lower effect sizes in MDD indicating reduced emotion recognition and processing abilities.

Background: Borderline Personality Disorder (BPD) is associated with heightened impulsivity, evidenced by increased substance abuse, self-harm and suicide attempts. Addressing impulsivity in individuals with BPD is a therapeutic objective; but its underlying neural basis in this clinical population remains unclear, partly due to its frequent co-morbidity with attention-deficit/hyperactivity disorder (ADHD).

Methods: We employed a response inhibition paradigm - the interleaved pro-/anti-saccade task (IPAST) - among adolescents diagnosed with BPD with and without comorbid ADHD (N=25 and N=24, respectively) during concomitant video-based eye-tracking. We quantified various eye movement response parameters reflective of impulsive action during the task, including delay to fixation acquisition, fixation breaks, anticipatory saccades, and direction errors with express saccade (Saccade Reaction Time [SRT]: 90-140 ms) and regular saccade latencies (SRT > 140 ms).

Results: Individuals with BPD exhibited deficient response preparation, exampled by reduced visual fixation on task cues and greater variability of saccade responses (i.e., SRT and peak velocity). The ADHD/BPD group shared these traits, as well as produced an increased frequency of anticipatory responses and direction errors with express saccade latencies and reduced error correction.

Conclusions: Saccadic deficits in BPD and ADHD/BPD stem not from an inability to execute anti-saccades, but rather from an inadequate preparation for the upcoming task set. These distinctions may arise due to abnormal signaling in cortical areas like the frontal eye fields, posterior parietal cortex, and anterior cingulate cortex. Understanding these mechanisms could provide insights into targeted interventions focusing on task set preparation to manage response inhibition deficits in BPD and ADHD/BPD.

To mitigate limitations in self-reported mood assessments, we introduce a novel affective bias task (ABT). 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 non-clinical populations. Initial assessment in a large non-clinical sample established normative ratings. Depressive symptoms were tracked relative to task performance in a non-clinical sample, as well as in a clinical cohort undergoing surgical evaluation for severe epilepsy. In both cohorts, a stronger negative affective bias was associated with higher Beck Depression Inventory (BDI-II) scores. The ABT exhibits high stability and interrater reliability, as well as construct validity in predicting depression levels in both cohorts, suggesting the task as a reliable proxy for mood and a diagnostic tool for detecting depressive symptoms.

Background: According to person-by-environment models, individual differences in traits may moderate the association between stressors and the development of psychopathology; however, findings in the literature have been inconsistent and little literature has examined adolescent brain structure as a moderator of the effects of stress on adolescent internalizing symptoms. The COVID-19 pandemic presented a unique opportunity to examine the associations between stress, brain structure, and psychopathology. Given links of cortical morphology with adolescent depression and anxiety, the present study investigated whether cortical morphology moderates the relationship between stress from the COVID-19 pandemic on the development of internalizing symptoms in familial high-risk adolescents.

Methods: Prior to the COVID-19 pandemic, 72 adolescents (27M) completed a measure of depressive and anxiety symptoms and underwent magnetic resonance imaging. T1-weighted images were acquired to assess cortical thickness and surface area. Approximately 6-8 months after COVID-19 was declared a global pandemic, adolescents reported their depressive and anxiety symptoms and pandemic-related stress.

Results: Adjusting for pre-pandemic depressive and anxiety symptoms and stress, increased pandemic-related stress was associated with increased depressive but not anxiety symptoms. This relationship was moderated by cortical thickness and surface area in the anterior cingulate and cortical thickness in the medial orbitofrontal cortex such that increased stress was only associated with increased depressive and anxiety symptoms among adolescents with lower cortical surface area and higher cortical thickness in these regions.

Conclusions: Results further our understanding of neural vulnerabilities to the associations between stress and internalizing symptoms in general, and during the COVID-19 pandemic in particular.