The basolateral complex of the amygdala (BLA) is a critical component of the neural circuit regulating fear learning. During fear learning and recall, the amygdala and other brain regions, including the hippocampus and prefrontal cortex, exhibit phase-locked oscillations in the high delta/low theta frequency band (∼2–6 Hz) that have been shown to contribute to the learning process. Network oscillations are commonly generated by inhibitory synaptic input that coordinates action potentials in groups of neurons. In the rat BLA, principal neurons spontaneously receive synchronized, inhibitory input in the form of compound, rhythmic, inhibitory postsynaptic potentials (IPSPs), likely originating from burst-firing parvalbumin interneurons. Here we investigated the role of compound IPSPs in the rat and rhesus macaque BLA in regulating action potential synchrony and spike-timing precision. Furthermore, because principal neurons exhibit intrinsic oscillatory properties and resonance between 4 and 5 Hz, in the same frequency band observed during fear, we investigated whether compound IPSPs and intrinsic oscillations interact to promote rhythmic activity in the BLA at this frequency. Using whole-cell patch clamp in brain slices, we demonstrate that compound IPSPs, which occur spontaneously and are synchronized across principal neurons in both the rat and primate BLA, significantly improve spike-timing precision in BLA principal neurons for a window of ∼300 ms following each IPSP. We also show that compound IPSPs coordinate the firing of pairs of BLA principal neurons, and significantly improve spike synchrony for a window of ∼130 ms. Compound IPSPs enhance a 5 Hz calcium-dependent membrane potential oscillation (MPO) in these neurons, likely contributing to the improvement in spike-timing precision and synchronization of spiking. Activation of the cAMP-PKA signaling cascade enhanced the MPO, and inhibition of this cascade blocked the MPO. We discuss these results in the context of spike-timing dependent plasticity and modulation by neurotransmitters important for fear learning, such as dopamine.
Background: Definition of response is critical when seeking to establish valid predictors of treatment success. However, response at the end of study or endpoint only provides one view of the overall clinical picture that is relevant in testing for predictors. The current study employed a classification technique designed to group subjects based on their rate of change over time, while simultaneously addressing the issue of controlling for baseline severity.
Methods: A set of latent class trajectory analyses, incorporating baseline level of symptoms, were performed on a sample of 344 depressed patients from a clinical trial evaluating the efficacy of cognitive behavior therapy and two antidepressant medications (escitalopram and duloxetine) in patients with major depressive disorder.
Results: Although very few demographic and illness-related features were associated with response rate profiles, the aggregated effect of candidate genetic variants previously identified in large pharmacogenetic studies and meta-analyses showed a significant association with early remission as well as nonresponse. These same genetic scores showed a less compelling relationship with endpoint response categories. In addition, consistent nonresponse throughout the study treatment period was shown to occur in different subjects than endpoint nonresponse, which was verified by follow-up augmentation treatment outcomes.
Conclusions: When defining groups based on the rate of change, controlling for baseline depression severity may help to identify the clinically relevant distinctions of early response on one end and consistent nonresponse on the other.
by
Jamie L. Hanson;
Alysha D. Gillmore;
Tianyi Yu;
Christopher J. Holmes;
Emily S. Hallowell;
Allen W. Barton;
Steven R.H. Beach;
Adrianna Galvan;
James MacKillop;
Michael Windle;
Edith Chen;
Gregory E. Miller;
Lawrence H. Sweet;
Gene Brody
Child Development published by Wiley Periodicals, Inc. on behalf of Society for Research in Child Development. The stressors associated with poverty increase the risks for externalizing psychopathology; however, specific patterns of neurobiology and higher self-regulation may buffer against these effects. This study leveraged a randomized control trial, aimed at increasing self-regulation at ~11 years of age. As adults, these same individuals completed functional MRI scanning (Mage = 24.88 years; intervention n = 44; control n = 49). Functional connectivity between the hippocampus and ventromedial prefrontal cortex was examined in relation to the intervention, gains in self-regulation, and present-day externalizing symptoms. Increased connectivity between these brain areas was noted in the intervention group compared to controls. Furthermore, individual gains in self-regulation, instilled by the intervention, statistically explained this brain difference. These results begin to connect neurobiological and psychosocial markers of risk and resiliency.
Background:
High levels of positive mental health protect individuals from mental illness. This study investigates longitudinal change in positive mental health as a predictor of mental illness recovery in a cohort group.
Methods:
Using data from the 1995 and 2005 Midlife in the United States cross-sectional surveys (n = 1,723), logistic regression was used to estimate the odds ratio that individuals diagnosed with a mental illness in 1995 would have recovered in 2005 based on whether their level of positive mental health changed over the 10-year period.
Results:
Individuals who maintained or gained the highest levels of positive mental health were more than 27.6 and 7.4 times, respectively, more likely to recover when compared to those who maintained the lowest level of positive mental health. Those who maintained or gained moderate levels of positive mental health had more moderate likelihood of recovery, and those whose positive mental health declined to the lowest levels had no significantly different likelihood of recovery compared to participants whose positive mental health remained low. Limitations: This study was limited by the age of the data, and the inability to control for some predictors of recovery.
Conclusions:
This study suggests that positive mental health may be an important resource for individuals to recover from mental illness and stay mentally healthy. Results point to the need to include positive mental health assessment and interventions into mental health care systems.
by
Luc Lecavalier;
Courtney E. McCracken;
Michael G. Aman;
Christopher J. McDougle;
James T. McCracken;
Elaine Tierney;
Tristram Smith;
Cynthia Johnson;
Bryan King;
Benjamin Handen;
Naomi B. Swiezy;
L. Eugene Arnold;
Karen Bearss;
Benedetto Vitiello;
Lawrence Scahill
Objective: We explored patterns of concomitant psychiatric disorders in a large sample of treatment-seeking children and adolescents with autism spectrum disorder (ASD). Methods: Participants were 658 children with ASD (age 3–17 years; mean = 7.2 years) in one of six federally-funded multisite randomized clinical trials (RCT) between 1999 and 2014. All children were referred for hyperactivity or irritability. Study designs varied, but all used the Child and Adolescent Symptom Inventory or Early Childhood Inventory to assess Attention Deficit Hyperactivity Disorder (ADHD), Oppositional-Defiant Disorder (ODD), Conduct Disorder (CD), Anxiety Disorders, and Mood Disorders. In addition, several measures in common were used to assess demographic and clinical characteristics. Results: Of the 658 children, 73% were Caucasian and 59% had an IQ >70. The rates of concomitant disorders across studies were: ADHD 81%, ODD 46%, CD 12%, any anxiety disorder 42%, and any mood disorder 8%. Two or more psychiatric disorders were identified in 66% of the sample. Of those who met criteria for ADHD, 50% also met criteria for ODD and 46% for any anxiety disorder. Associations between types of concomitant disorders and a number of demographic and clinical characteristics are presented. Conclusion: In this well-characterized sample of treatment-seeking children with ASD, rates of concomitant psychiatric disorders were high and the presence of two or more co-occurring disorders was common. Findings highlight the importance of improving diagnostic practice in ASD and understanding possible mechanisms of comorbidity.
Social subordination in female macaques is imposed by harassment and the threat of aggression and produces reduced control over one's social and physical environment and a dysregulation of the limbic-hypothalamic-pituitary-adrenal axis resembling that observed in people suffering from psychopathologies. These effects support the contention that this particular animal model is an ethologically relevant paradigm in which to investigate the etiology of stress-induced psychological illness related to women. Here, we sought to expand this model by performing a discriminate analysis (DA) on 33 variables within three domains; behavioral, metabolic/anthropomorphic, and neuroendocrine, collected from socially housed female rhesus monkeys in order to assess whether exposure to social subordination produces a distinct phenotype. A receiver operating characteristic (ROC) curve was also calculated to determine each domain's classification accuracy. DA found significant markers within each domain that differentiated dominant and subordinate females. Subordinate females received more aggression, showed more submissive behavior, and received less of affiliation from others than did dominant females. Metabolic differences included increased leptin, and reduced adiponectin in dominant compared to subordinate females. Dominant females exhibited increased sensitivity to hormonal stimulation with higher serum LH in response to estradiol, cortisol in response to ACTH, and increased glucocorticoid negative feedback. Serum oxytocin, CSF DOPAC and serum PACAP were all significantly higher in dominant females. ROC curve analysis accurately predicted social status in all three domains. Results suggest that socially house rhesus monkeys represent a cogent animal model in which to study the physiology and behavioral consequences of chronic psychosocial stress in humans.
Background:
Polymorphisms in cannabinoid receptor type 1 (encoded by CNR1) and fatty acid amide hydrolase (encoded by FAAH) have been associated with cannabis dependence, but it remains unknown whether variation within these genes influences cannabis’ acute effects on affect.
Objective:
Conduct a secondary data analysis study to determine whether previously observed acute effects of tetrahydrocannabinol (THC) on mood was dependent upon variation in CNR1 and FAAH.
Methods:
A balanced placebo design was used crossing marijuana administration (i.e., 0% THC vs. 2.8% THC) with stimulus expectancy. Participants (N = 118; 64% male) provided DNA and completed the Profile of Mood States questionnaire prior to and after smoking. Haplotypes were constructed from genotyped single nucleotide polymorphisms for CNR1 (rs1049353 and rs806368) and FAAH (rs4141964, rs324420, and rs11576941); rs2023239 (CNR1) and rs6703669 (FAAH) were not part of a phased haplotype block. Analyses tested both main and interaction effects for genotype across CNR1 and FAAH, and drug, and expectancy effects.
Results:
THC increased levels of POMS Tension-Anxiety and Confusion-Bewilderment over and above the effects of variation in CNR1 and FAAH. Significant drug X genotype/haplotype and expectancy X genotype/haplotype interaction effects were observed for some but not all mood states [e.g., ‘C’ allele carriers of rs2023239 who received THC had higher levels of Anger-Hostility (β= 0.29 (0.12), p=.02) compared to those who received placebo].
Conclusion:
These preliminary findings suggest individual differences in mood states after using marijuana depend on genetic variation. Such information might be useful in understanding either motivation for use of marijuana and/or risk for associated behaviors.
Some nonhuman species demonstrate metamemory, the ability to monitor and control memory. Here, we identify memory signals that control metamemory judgments in rhesus monkeys by directly comparing performance in two metamemory paradigms while holding the availability of one memory signal constant and manipulating another. Monkeys performed a four-choice match-to-sample memory task. In Experiment 1, monkeys could decline memory tests on some trials for a small, guaranteed reward. In Experiment 2, monkeys could review the sample on some trials. In both experiments, monkeys improved accuracy by selectively declining tests or reviewing samples when memory was poor. To assess the degree to which different memory signals made independent contributions to the metamemory judgement, we made the decline-test or review-sample response available either prospectively, before the test, or concurrently with test stimuli.
Prospective metamemory judgements are likely controlled by the current contents of working memory, whereas concurrent metamemory judgements may also be controlled by additional relative familiarity signals evoked by the sight of the test stimuli. In both paradigms, metacognitive responding enhanced accuracy more on concurrent than on prospective tests, suggesting additive contributions of working memory and stimulus-evoked familiarity. Consistent with the hypothesis that working memory and stimulus-evoked familiarity both control metamemory judgments when available, metacognitive choice latencies were longer in the concurrent condition, when both were available. Together, these data demonstrate that multiple memory signals can additively control metacognitive judgements in monkeys and provide a framework for mapping the interaction of explicit memory signals in primate memory.
Neuroimaging‐based approaches have been extensively applied to study mental illness in recent years and have deepened our understanding of both cognitively healthy and disordered brain structure and function. Recent advancements in machine learning techniques have shown promising outcomes for individualized prediction and characterization of patients with psychiatric disorders. Studies have utilized features from a variety of neuroimaging modalities, including structural, functional, and diffusion magnetic resonance imaging data, as well as jointly estimated features from multiple modalities, to assess patients with heterogeneous mental disorders, such as schizophrenia and autism. We use the term “predictome” to describe the use of multivariate brain network features from one or more neuroimaging modalities to predict mental illness.
In the predictome, multiple brain network‐based features (either from the same modality or multiple modalities) are incorporated into a predictive model to jointly estimate features that are unique to a disorder and predict subjects accordingly. To date, more than 650 studies have been published on subject‐level prediction focusing on psychiatric disorders. We have surveyed about 250 studies including schizophrenia, major depression, bipolar disorder, autism spectrum disorder, attention‐deficit hyperactivity disorder, obsessive–compulsive disorder, social anxiety disorder, posttraumatic stress disorder, and substance dependence. In this review, we present a comprehensive review of recent neuroimaging‐based predictomic approaches, current trends, and common shortcomings and share our vision for future directions.
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Christopher J. Hyatt;
Vince D. Calhoun;
Brian Pittman;
Silvia Corbera;
Morris D. Bell;
Liron Rabany;
Kevin Pelphrey;
Godfrey D. Pearlson;
Michal Assaf
Schizophrenia and autism spectrum disorder (ASD) are nosologically distinct neurodevelopmental disorders with similar deficits in social cognition, including the ability to form mental representations of others (i.e., mentalizing). However, the extent of patient deficit overlap in underlying neural mechanisms is unclear. Our goal was to examine deficits in mentalizing task-related (MTR) activity modulation in schizophrenia and ASD and the relationship of such deficits with social functioning and psychotic symptoms in patients. Adults, ages 18–34, diagnosed with either ASD or schizophrenia, and typically developed controls (n = 30/group), performed an interactive functional MRI Domino task.
Using independent component analysis, we analyzed game intervals known to stimulate mentalizing in the default mode network (DMN), i.e., medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), precuneus, and temporoparietal junction (TPJ), for group differences in MTR activity and associations between MTR activity and social and psychosis measures. Compared to controls, both schizophrenia and ASD groups showed MTR activity deficits in PCC and TPJ. In TPJ and MPFC, MTR activity modulation was associated with social communication impairments only in ASD. In precuneus, MTR activity was associated with increased self-reported fantasizing only in schizophrenia.
In schizophrenia, we found no indication of over-mentalizing activity or an association between MTR activity and psychotic symptoms. Results suggest shared neural deficits between ASD and schizophrenia in mentalizing-associated DMN regions; however, neural organization might correspond to different dimensional social deficits. Our results therefore indicate the importance of examining both categorical-clinical diagnosis and social functioning dimensional constructs when examining neural deficits in schizophrenia and ASD.