Altered Brain Activation During Memory Retrieval Precedes and Predicts Conversion to Psychosis in Individuals at Clinical High Risk

Altered brain activation during memory retrieval mediates the relationship between developmental trauma and psychotic symptom severity

BACKGROUND

Developmental trauma (DT) and poorer episodic memory performance are associated with increased risk of psychotic symptoms, but the mechanisms underlying these associations remain to be established. We sought to investigate whether memory performance and fMRI activity during the retrieval phase of an associative episodic memory task statistically mediated the relationship between trauma multiplicity and psychotic symptom severity in youth at clinical high risk for psychosis.

METHODS

Measures from 795 participants in the North American Prodrome Longitudinal Study (phase two) were analysed. This included the Childhood Trauma and Abuse scale, neurocognitive measures, the Scale of Psychosis-Risk Symptoms and, in a subsample, neural activation from five regions of interest associated with memory processing (n = 219) during a paired-associate memory task (data from this task; n = 198). Linear regressions were conducted to measure whether trauma multiplicity predicted subclinical delusion and hallucination severity and neurocognitive performance, and neurocognitive measures predicted subclinical hallucination or delusion severity. We used mediation analysis when all paths were significant.

RESULTS

Average functional activation in the five memory-associated regions mediated 8.74 % of the association between DT and subclinical hallucination severity, and 7.02 % between DT and delusion severity. Inferior parietal lobe activity mediated 10.08 % of the association between DT and subclinical hallucination severity, and 8.7 % between DT and subclinical delusion severity.

CONCLUSIONS

These findings suggest a role of episodic memory processing and inferior parietal lobe activation in the association between DT and psychosis. Focusing further on these measures could provide insight into the underlying mechanism of this association, and have clinical implications in trauma-exposed individuals with psychosis.

Macro- and Microstructural Alterations in the Midbrain in Early Psychosis Associates with Clinical Symptom Scores

Early psychosis (EP) is a critical period for psychotic disorders during which the brain undergoes rapid and significant functional and structural changes ( Shinn et al., 2017). The Human Connectome Project (HCP) is a global effort to map the human brain's connectivity in health and disease. Here we focus on HCP-EP subjects (i.e., those within 5 years of the initial psychotic episode) to determine macro- and microstructural alterations in EP (HCP-EP sample, n = 179: EP, n = 123, controls, n = 56) and their association with clinical outcomes (i.e., symptoms severity) in HCP-EP. We carried out analyses of deformation-based morphometry (DBM), scalar indices from the diffusion tensor imaging (DTI), and tract-based spatial statistics (TBSS). Lastly, we conducted correlation analyses focused on the midbrain (DBM and DTI) to examine associations between its structure and clinical symptoms. Our results show that the midbrain displays robust alteration in its structure (DBM and DTI) in the voxel-based analysis. Complimentary alterations were also observed for the hippocampus and putamen. A seed-based analysis centered around the midbrain confirms the voxel-based analysis of DBM and DTI. TBSS displays structural differences within the midbrain and complementary alterations in the corticospinal tract and cingulum. Correlations between the midbrain structures and behavior showed that the quantified features correlate with cognition and clinical scores. Our findings contribute to understanding the midbrain-focused circuitry involvement in EP and provide a path for future investigations to inform specific brain-based biomarkers of EP.

Efficacy of Cortical-Hippocampal Target Intermittent Theta Burst Stimulation (iTBS) on Associative Memory of Schizophrenia: A Double-Blind, Randomized Sham-Controlled Trial

Objective

The objective of our study was to evaluate whether intermittent theta burst stimulation(iTBS) applied to the regions with the strongest cortico-hippocampal connectivity within the lateral parietal cortical (LPC) or dorsolateral prefrontal cortical (DLPFC) areas in individuals with schizophrenia could enhance associative memory.

Methods

We randomized 96 participants with schizophrenia to receive either active iTBS applied to the right DLPFC, left LPC or sham iTBS for 20 days. Clinical and cognitive assessments were performed at baseline and at the end of treatment. The primary outcome was change in associative memory. The secondary outcome was change in other cognitive functions and psychiatric symptoms.

Results

In comparison to the sham group, iTBS targeting the right DLPFC or left LPC in schizophrenia did not yield significant improvements in auditory-auditory associative memory (F=1.27, p=0.294), auditory-visual associative memory (F=0.49, p=0.617), or visual-visual associative memory (F=1.094, p=0.347). Furthermore, after adjusting for variables such as education, disease duration, and negative symptoms, no significant changes were observed in any of these three memory domains.

Conclusion

Although our study suggests that iTBS applied to the cortical-hippocampal did not lead to a significant change in associative memory. However, further investigation combining hippocampal-targeted iTBS with functional magnetic resonance imaging (fMRI) is warranted to elucidate the regulatory effects of iTBS on hippocampal function.

Trial Registration

clinicaltrials.gov NCT03608462.

The mesolimbic system and the loss of higher order network features in schizophrenia when learning without reward

Introduction

Schizophrenia is characterized by a loss of network features between cognition and reward sub-circuits (notably involving the mesolimbic system), and this loss may explain deficits in learning and cognition. Learning in schizophrenia has typically been studied with tasks that include reward related contingencies, but recent theoretical models have argued that a loss of network features should be seen even when learning without reward. We tested this model using a learning paradigm that required participants to learn without reward or feedback. We used a novel method for capturing higher order network features, to demonstrate that the mesolimbic system is heavily implicated in the loss of network features in schizophrenia, even when learning without reward.

Methods

fMRI data (Siemens Verio 3T) were acquired in a group of schizophrenia patients and controls (n=78; 46 SCZ, 18 ≤ Age ≤ 50) while participants engaged in associative learning without reward-related contingencies. The task was divided into task-active conditions for encoding (of associations) and cued-retrieval (where the cue was to be used to retrieve the associated memoranda). No feedback was provided during retrieval. From the fMRI time series data, network features were defined as follows: First, for each condition of the task, we estimated 2nd order undirected functional connectivity for each participant (uFC, based on zero lag correlations between all pairs of regions). These conventional 2nd order features represent the task/condition evoked synchronization of activity between pairs of brain regions. Next, in each of the patient and control groups, the statistical relationship between all possible pairs of 2nd order features were computed. These higher order features represent the consistency between all possible pairs of 2nd order features in that group and embed within them the contributions of individual regions to such group structure.

Results

From the identified inter-group differences (SCZ ≠ HC) in higher order features, we quantified the respective contributions of individual brain regions. Two principal effects emerged: 1) SCZ were characterized by a massive loss of higher order features during multiple task conditions (encoding and retrieval of associations). 2) Nodes in the mesolimbic system were over-represented in the loss of higher order features in SCZ, and notably so during retrieval.

Discussion

Our analytical goals were linked to a recent circuit-based integrative model which argued that synergy between learning and reward circuits is lost in schizophrenia. The model's notable prediction was that such a loss would be observed even when patients learned without reward. Our results provide substantial support for these predictions where we observed a loss of network features between the brain's sub-circuits for a) learning (including the hippocampus and prefrontal cortex) and b) reward processing (specifically constituents of the mesolimbic system that included the ventral tegmental area and the nucleus accumbens. Our findings motivate a renewed appraisal of the relationship between reward and cognition in schizophrenia and we discuss their relevance for putative behavioral interventions.

Macro- and Micro-Structural Alterations in the Midbrain in Early Psychosis

Introduction

Early psychosis (EP) is a critical period in the course of psychotic disorders during which the brain is thought to undergo rapid and significant functional and structural changes 1 . Growing evidence suggests that the advent of psychotic disorders is early alterations in the brain's functional connectivity and structure, leading to aberrant neural network organization. The Human Connectome Project (HCP) is a global effort to map the human brain's connectivity in healthy and disease populations; within HCP, there is a specific dataset that focuses on the EP subjects (i.e., those within five years of the initial psychotic episode) (HCP-EP), which is the focus of our study. Given the critically important role of the midbrain function and structure in psychotic disorders (cite), and EP in particular (cite), we specifically focused on the midbrain macro- and micro-structural alterations and their association with clinical outcomes in HCP-EP.

Methods

We examined macro- and micro-structural brain alterations in the HCP-EP sample (n=179: EP, n=123, Controls, n=56) as well as their associations with behavioral measures (i.e., symptoms severity) using a stepwise approach, incorporating a multimodal MRI analysis procedure. First, Deformation Based Morphometry (DBM) was carried out on the whole brain 3 Tesla T1w images to examine gross brain anatomy (i.e., seed-based and voxel-based volumes). Second, we extracted Fractional Anisotropy (FA), Axial Diffusivity (AD), and Mean Diffusivity (MD) indices from the Diffusion Tensor Imaging (DTI) data; a midbrain mask was created based on FreeSurfer v.6.0 atlas. Third, we employed Tract-Based Spatial Statistics (TBSS) to determine microstructural alterations in white matter tracts within the midbrain and broader regions. Finally, we conducted correlation analyses to examine associations between the DBM-, DTI- and TBSS-based outcomes and the Positive and Negative Syndrome Scale (PANSS) scores.

Results

DBM analysis showed alterations in the hippocampus, midbrain, and caudate/putamen. A DTI voxel-based analysis shows midbrain reductions in FA and AD and increases in MD; meanwhile, the hippocampus shows an increase in FA and a decrease in AD and MD. Several key brain regions also show alterations in DTI indices (e.g., insula, caudate, prefrontal cortex). A seed-based analysis centered around a midbrain region of interest obtained from freesurfer segmentation confirms the voxel-based analysis of DTI indices. TBSS successfully captured structural differences within the midbrain and complementary alterations in other main white matter tracts, such as the corticospinal tract and cingulum, suggesting early altered brain connectivity in EP. Correlations between these quantities in the EP group and behavioral scores (i.e., PANSS and CAINS tests) were explored. It was found that midbrain volume noticeably correlates with the Cognitive score of PA and all DTI metrics. FA correlates with the several dimensions of the PANSS, while AD and MD do not show many associations with PANSS or CAINS.

Conclusions

Our findings contribute to understanding the midbrain-focused circuitry involvement in EP and complimentary alteration in EP. Our work provides a path for future investigations to inform specific brain-based biomarkers of EP and their relationships to clinical manifestations of the psychosis course.

Recent advancements in biomarker research in schizophrenia: mapping the road from bench to bedside

Schizophrenia (SZ) is a severe progressive neurodegenerative as well as disruptive behavior disorder affecting innumerable people throughout the world. The discovery of potential biomarkers in the clinical scenario would lead to the development of effective methods of diagnosis and would provide an understanding of the prognosis of the disease. Moreover, breakthrough inventions for the treatment and prevention of this mysterious disease could evolve as a result of a thorough understanding of the clinical biomarkers. In this review, we have discussed about specific biomarkers of SZ an emphasis has been laid to delineate (1) diagnostic biomarkers like neuroimmune biomarkers, metabolic biomarkers, oligodendrocyte biomarkers and biomarkers of negative and cognitive symptoms, (2) therapeutic biomarkers like various neurotransmitter systems and (3) prognostic biomarkers. All the biomarkers were evaluated in drug-naïve (at least for 4 weeks) patients in order to achieve a clear comparison between schizophrenic patients and healthy controls. Also, an attempt has been made to elucidate the potential genes which serve as predictors and tools for the determination of biomarkers and would ultimately help in the prevention and treatment of this deadly illness.

Episodic Memory and Schizophrenia: From Characterization of Relational Memory Impairments to Neuroimaging Biomarkers

Episodic memory research in schizophrenia has a long history already which has clearly established significant impairments and strong associations with brain measures and functional outcome. The purpose of this chapter is not to make an exhaustive review of the recent literature but to highlight some relatively recent developments in the cognitive neuroscience field of episodic memory and schizophrenia. Hence, we present a contemporary view focusing specifically of relational memory which represents a form of episodic memory that refers to associations or binding among items or elements presented together. We describe the major tasks used and illustrate how their combination with brain imaging has: (1) favored the use of experimental memory tasks to isolate specific processes with specific neural correlates, (2) led to a distributed view of the neural correlates of memory impairments in schizophrenia where multiple regions are contributing, and (3) made possible the identification of fMRI biomarkers specific to episodic memory. We then briefly propose what we see as the next steps for memory research in schizophrenia so that the impact of this work can be maximized.

Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra-high risk for psychosis

OBJECTIVE

Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra-high risk for psychosis (UHR).

METHODS

110 UHR individuals underwent 3 Tesla diffusion-weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression.

RESULTS

Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ²  = 17.595, p = 0.040), accounted for 15-33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R²  = 0.055, F = 6.084, p = 0.016) and functional level (R²  = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months.

CONCLUSION

Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition.

BIOMARKERS AND NEUROBEHAVIORAL DIAGNOSIS

Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.

Distinct and temporally associated neural mechanisms underlying concurrent, postsuccess, and posterror cognitive controls: Evidence from a stop-signal task

Cognitive control is built upon the interactions of multiple brain regions. It is currently unclear whether the involved regions are temporally separable in relation to different cognitive processes and how these regions are temporally associated in relation to different task performances. Here, using stop-signal task data acquired from 119 healthy participants, we showed that concurrent and poststop cognitive controls were associated with temporally distinct but interrelated neural mechanisms. Specifically, concurrent cognitive control activated regions in the cingulo-opercular network (including the dorsal anterior cingulate cortex [dACC], insula, and thalamus), together with superior temporal gyrus, secondary motor areas, and visual cortex; while regions in the fronto-parietal network (including the lateral prefrontal cortex [lPFC] and inferior parietal lobule) and cerebellum were only activated during poststop cognitive control. The associations of activities between concurrent and poststop regions were dependent on task performance, with the most notable difference in the cerebellum. Importantly, while concurrent and poststop signals were significantly correlated during successful cognitive control, concurrent activations during erroneous trials were only correlated with posterror activations in the fronto-parietal network but not cerebellum. Instead, the cerebellar activation during posterror cognitive control was likely to be driven secondarily by posterror activation in the lPFC. Further, a dynamic causal modeling analysis demonstrated that postsuccess cognitive control was associated with inhibitory connectivity from the lPFC to cerebellum, while excitatory connectivity from the lPFC to cerebellum was present during posterror cognitive control. Overall, these findings suggest dissociable but temporally related neural mechanisms underlying concurrent, postsuccess, and posterror cognitive control processes in healthy individuals.

Social decline in the psychosis prodrome: Predictor potential and heterogeneity of outcome

BACKGROUND

While an established clinical outcome of high importance, social functioning has been emerging as possibly having a broader significance to the evolution of psychosis and long term disability. In the current study we explored the association between social decline, conversion to psychosis, and functional outcome in individuals at clinical high risk (CHR) for psychosis.

METHODS

585 subjects collected in the North American Prodrome Longitudinal Study (NAPLS2) were divided into 236 Healthy Controls (HCs), and CHR subjects that developed psychosis (CHR + C, N = 79), or those that did not (Non-Converters, CHR-NC, N = 270). CHR + C subjects were further divided into those that experienced an atypical decline in social functioning prior to baseline (beyond typical impairment levels) when in min-to-late adolescence (CHR + C-SD, N = 39) or those that did not undergoing a decline (CHR + C-NSD, N = 40).

RESULTS

Patterns of poor functional outcomes varied across the CHR subgroups: CHR-NC (Poor Social 36.3%, Role 42.2%) through CHR + C-NSD (Poor Social 50%, Poor Role 67.5%) to CHR + C-SD (Poor Social 76.9%, Poor Role 89.7%) functioning. The two Converter subgroups had comparable positive symptoms at baseline. At 12 months, the CHR + C-SD group stabilized, but social functioning levels remained significantly lower than the other two subgroups.

CONCLUSIONS

The current study demonstrates that pre-baseline social decline in mid-to-late adolescence predicts psychosis. In addition, we found that this social decline in converters is strongly associated with especially poor functional outcome and overall poorer prognosis. Role functioning, in contrast, has not shown similar predictor potential, and rather appears to be an illness indicator that worsens over time.

Memory Impairments and Psychosis Prediction: A Scoping Review and Theoretical Overview

Impairments in memory functions are among the most robust correlates of schizophrenia and of poor functional outcomes in individuals with psychotic disorders. Prospective, longitudinal studies are crucial to determining the meaning of these deficits in relation to mechanisms associated with the onset and course of these disorders.The objective of this review is to examine the literature concerning premorbid memory impairments during the prodromal phase of psychosis to address three primary questions 1) are memory impairments present among individuals with a clinical high risk syndrome? 2) are memory deficits in clinical high risk cases predictive of future conversion to psychosis? and 3) what are the underlying neural correlates of memory impairment in clinical high risk individuals and are they also predictive of future conversion?PubMed and Google Scholar databases were systematically searched. The primary inclusion criteria were to select studies that 1) were original research articles published in a peer-reviewed journal in the past 25 years, 2) studied subjects at clinical high risk for psychosis or in the prodromal phase of illness, and 3) included examinations into verbal memory performance in those at clinical high risk for psychosis.64 articles were identified and screened for eligibility. The review included 34 studies investigating verbal memory impairment in clinical high risk individuals compared to controls. The average effect size of verbal learning total recall was .58, indicating a moderate level of impairment in verbal learning among individuals at clinical high risk for psychosis as compared to healthy controls. Of studies that predicted time to conversion, indices of memory, particularly declarative and verbal working memory, were especially predictive of future conversion. Finally, when examining investigations of the neural correlates of memory dysfunction in the clinical high risk state, findings suggest altered activation and functional connectivity among medial temporal lobe regions may underlie differences in memory performance between clinical high risk individuals and healthy controls.Findings to date strongly indicate that memory impairments are present during the premorbid phase of psychosis and that verbal memory impairment in particular is predictive of future conversion to psychosis. Evidence from fMRI studies is fairly consistent in showing greater activation of memory-related regions during retrieval among clinical high risk cases who convert, with less consistent evidence of altered functional connectivity in the encoding phase. These findings support the use of verbal learning and memory measures in the psychosis prediction and prevention field.

Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis

Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR). Using resting-state functional magnetic resonance imaging (fMRI) data from 263 CHR subjects, we extract an α brain atlas and a β brain atlas: the former underlines brain areas associated with prodromal symptoms and the latter highlights brain areas associated with disease onset. In parallel, we identify and separate mediators that potentially positively and negatively mediate symptoms and psychosis, respectively, and quantify the effect of each neural mediator on disease development. Taken together, these results paint a brain-wide picture of neural markers that are potentially mediating behavioral symptoms and the development of psychotic disorders; additionally, they underscore a statistical framework that is useful to uncover large-scale intermediating variables in a regulatory biological system.

Predictors of Transition to Psychosis in Individuals at Clinical High Risk

PURPOSE OF REVIEW

Current research is examining predictors of the transition to psychosis in youth who are at clinical high risk based on attenuated psychotic symptoms (APS). Determining predictors of the development of psychosis is important for an improved understanding of mechanisms as well as the development of preventative strategies. The purpose is to review the most recent literature identifying predictors of the transition to psychosis in those who are already assessed as being at risk.

RECENT FINDINGS

Multidomain models, in particular, integrated models of symptoms, social functioning, and cognition variables, achieve better predictive performance than individual factors. There are many methodological issues; however, several solutions have now been described in the literature. For youth who already have APS, predicting who may go on to later develop psychosis is possible. Several studies are underway in large consortiums that may overcome some of the methodological concerns and develop improved means of prediction.