Project description:Working memory is a temporary storage system under attentional control. It is believed to play a central role in online processing of complex cognitive information and may also play a role in social cognition and interpersonal interactions. Adolescents with a disorder on the autism spectrum display problems in precisely these domains. Social impairments, communication difficulties, and repetitive interests and activities are core domains of autism spectrum disorders (ASD), and executive function problems are often seen throughout the spectrum. As the main cognitive theories of ASD, including the theory of mind deficit hypotheses, weak central coherence account, and the executive dysfunction theory, still fail to explain the broad spectrum of symptoms, a new perspective on the etiology of ASD is needed. Deficits in working memory are central to many theories of psychopathology, and are generally linked to frontal-lobe dysfunction. This article will review neuropsychological and (functional) brain imaging studies on working memory in adolescents with ASD. Although still disputed, it is concluded that within the working memory system specific problems of spatial working memory are often seen in adolescents with ASD. These problems increase when information is more complex and greater demands on working memory are made. Neuroimaging studies indicate a more global working memory processing or connectivity deficiency, rather than a focused deficit in the prefrontal cortex. More research is needed to relate these working memory difficulties and neuroimaging results in ASD to the behavioral difficulties as seen in individuals with a disorder on the autism spectrum.
Project description:BackgroundAntipsychotic drugs remain the mainstay of schizophrenia treatment; however, their effectiveness has been questioned, and it is not possible to predict the response to a specific antipsychotic drug in an individual patient. Thus, it is important to compare the effectiveness of the various antipsychotics and search for possible response predictors.AimTo investigate the effectiveness of antipsychotic drugs, we examined response trajectories and predictors for belonging to different trajectory groups.MethodsThe Bergen-Stavanger-Innsbruck-Trondheim (BeSt InTro) trial compared the effectiveness of three atypical antipsychotics-amisulpride, aripiprazole, and olanzapine-in a prospective, semirandomized, rater-blind, head-to-head design. Adult participants with a schizophrenia spectrum disorder diagnosis, according to international classification of diseases, Tenth Revision (ICD-10) F20-29, were included. Participants were followed for a period of 12 mo, with assessments at baseline; after one, three and six weeks; and after three, six, nine and 12 mo. A latent class mixed model was fitted to our data. The three-trajectory model based on the Positive and Negative Syndrome Scale (PANSS) total score reduction was found to have adequate fit, and the study drugs, as well as various demographic and clinical parameters, were tested as predictors for belonging to the different trajectory groups.ResultsOverall, 144 participants were included, and 41% completed the 12-mo study period. The largest trajectory group, consisting of 74% of participants, showed a PANSS total score reduction of 59% from baseline to 12 mo (Good response group). A trajectory group comprising 13% of participants had their PANSS total score reduced by 82.5% at 12 mo (Strong response group), while the last response trajectory group comprising 13% of the participants had a PANSS total score reduction of 13.6% (Slight response group). The largest part of the total reduction for the Good and Strong response groups occurred at six weeks of treatment, amounting to 45% and 48% reductions from baseline, respectively. The use of amisulpride predicted belonging to the Strong response group, while unemployment, depression, and negative psychotic symptoms at baseline increased the chance of belonging to the Slight response group, indicating a poor response to antipsychotic drug treatment.ConclusionMost of the participants (87%) had a good outcome after one year. Amisulpride users, more often than aripiprazole and olanzapine users, belonged to the response trajectory group with a strong response.
Project description:The adverse metabolic risks associated with second generation antipsychotics (SGAs) are well known, and likely contribute to the high rate of premature mortality due to cardiovascular disease in schizophrenia. Female schizophrenia patients appear to be diagnosed with metabolic diseases at higher rates than males, which may reflect disparate adverse responses to SGAs. However, the relationship between sex, metabolic risk, and drug use is less developed. We aimed to explore this relationship further by identifying rates of metabolic disease in community dwelling schizophrenia patients by sex and SGA risk. Schizophrenia participants (N = 287, 40.4% female) were included in this analysis. Oneway-ANOVA and Fisher's Exact Test were used to compare groups, as appropriate, and Cohen's d was employed to estimate the effect size of sex. In the group as a whole, the rate of metabolic syndrome was higher than previously reported, but did not differ by sex. For females, greater metabolic disturbances across all medication risk groups were seen in BMI and waist circumference (p < 0.005) but most commonly in those receiving high risk medication (clozapine or olanzapine). Additionally, the number of participants receiving medications for these metabolic disturbances was extremely low (<30%). These results suggest that female schizophrenia patients taking clozapine or olanzapine represent a group at uniquely high risk for metabolic dysfunction and future adverse cardiovascular outcomes, and warrant close monitoring by clinicians to prevent worsening of metabolic risk through proper monitoring and interventions.
Project description:BackgroundSchizophrenia (SCZ) is marked by working memory (WM) deficits, which predict poor functional outcome. While most functional magnetic resonance imaging studies of WM in SCZ have focused on the dorsolateral prefrontal cortex (PFC), some recent work suggests that the medial PFC (mPFC) may play a role. We investigated whether task-evoked mPFC deactivation is associated with WM performance and whether it mediates deficits in SCZ. In addition, we investigated associations between mPFC deactivation and cortical dopamine release.MethodsPatients with SCZ (n = 41) and healthy control participants (HCs) (n = 40) performed a visual object n-back task during functional magnetic resonance imaging. Dopamine release capacity in mPFC was quantified with [11C]FLB457 in a subset of participants (9 SCZ, 14 HCs) using an amphetamine challenge. Correlations between task-evoked deactivation and performance were assessed in mPFC and dorsolateral PFC masks and were further examined for relationships with diagnosis and dopamine release.ResultsmPFC deactivation was associated with WM task performance, but dorsolateral PFC activation was not. Deactivation in the mPFC was reduced in patients with SCZ relative to HCs and mediated the relationship between diagnosis and WM performance. In addition, mPFC deactivation was significantly and inversely associated with dopamine release capacity across groups and in HCs alone, but not in patients.ConclusionsReduced WM task-evoked mPFC deactivation is a mediator of, and potential substrate for, WM impairment in SCZ, although our study design does not rule out the possibility that these findings could relate to cognition in general rather than WM specifically. We further present preliminary evidence of an inverse association between deactivation during WM tasks and dopamine release capacity in the mPFC.
Project description:OBJECTIVE:Working memory impairments serve as prognostic factors for patients with schizophrenia. Working memory deficits are mainly associated with gray matter (GM) thickness and volume. We investigated the association between GM diffusivity and working memory in controls and individuals with schizophrenia. METHODS:T1 and diffusion tensor images of the brain, working memory task (letter number sequencing) scores, and the demographic data of 90 individuals with schizophrenia and 97 controls were collected from the SchizConnect database. T1 images were parcellated into the 68 GM Regions of Interest (ROI). Axial Diffusivity (AD), Fractional Anisotropy (FA), Radial Diffusivity (RD), and Trace (TR) were calculated for each of the ROIs. RESULTS:Compared to the controls, schizophrenia group showed significantly increased AD, RD, and TR in specific regions on the frontal, temporal, and anterior cingulate area. Moreover, working memory was negatively correlated with AD, RD, and TR in the lateral orbitofrontal, superior temporal, inferior temporal, and rostral anterior cingulate area on left hemisphere in the individuals with schizophrenia. CONCLUSION:These results demonstrated GM microstructural abnormalities in the frontal, temporal, and anterior cingulate regions of individuals with schizophrenia. Furthermore, these regional GM microstructural abnormalities suggest a neuropathological basis for the working memory deficits observed clinically in individuals with schizophrenia.
Project description:Substantial evidence implicates working memory (WM) as a core deficit in schizophrenia (SCZ), purportedly due to primary deficits in dorsolateral prefrontal cortex functioning. Recent findings suggest that SCZ is also associated with abnormalities in suppression of certain regions during cognitive engagement--namely the default mode system--that may further contribute to WM pathology. However, no study has systematically examined activation and suppression abnormalities across both encoding and maintenance phases of WM in SCZ. Twenty-eight patients and 24 demographically matched healthy subjects underwent functional magnetic resonance imaging at 3T while performing a delayed match-to-sample WM task. Groups were accuracy matched to rule out performance effects. Encoding load was identical across subjects to facilitate comparisons across WM phases. We examined activation differences using an assumed model approach at the whole-brain level and within meta-analytically defined WM areas. Despite matched performance, we found regions showing less recruitment during encoding and maintenance for SCZ subjects. Furthermore, we identified 2 areas closely matching the default system, which SCZ subjects failed to deactivate across WM phases. Lastly, activation in prefrontal regions predicted the degree of deactivation for healthy but not SCZ subjects. Current results replicate and extend prefrontal recruitment abnormalities across WM phases in SCZ. Results also indicate deactivation abnormalities across WM phases, possibly due to inefficient prefrontal recruitment. Such regional deactivation may be critical for suppressing sources of interference during WM trace formation. Thus, deactivation deficits may constitute an additional source of impairments, which needs to be further characterized for a complete understanding of WM pathology in SCZ.
Project description:By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. There is increasing interest to uncover the neurocognitive mapping of specific clinical measurements on enriched brain imaging data; hence, a supervised, goal-directed model that employs prior information as a reference to guide multimodal data fusion is much needed and becomes a natural option. Here, we proposed a fusion with reference model called "multi-site canonical correlation analysis with reference + joint-independent component analysis" (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to the reference, such as cognitive scores. In a three-way fusion simulation, the proposed method was compared with its alternatives on multiple facets; MCCAR+jICA outperforms others with higher estimation precision and high accuracy on identifying a target component with the right correspondence. In human imaging data, working memory performance was utilized as a reference to investigate the co-varying working memory-associated brain patterns among three modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Similar brain maps were identified between the two cohorts along with substantial overlaps in the central executive network in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports and MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the ability of the proposed method to identify potential neuromarkers for mental disorders.
Project description:BackgroundWorking memory (WM) deficit is a key feature of schizophrenia that relates to a generalized neural inefficiency of extensive brain areas. To date, it remains unknown how these distributed regions are systemically organized at the connectome level and how the disruption of such organization brings about the WM impairment seen in schizophrenia.MethodsWe used graph theory to examine the neural efficiency of the functional connectome in different granularity in 155 patients with schizophrenia and 96 healthy controls during a WM task. These analyses were repeated in another independent dataset (81 patients and 54 controls). Linear regression analysis was used to test associations of altered graph properties, clinical symptoms, and WM accuracy in patients. A machine-learning approach was adopted to study the ability of multivariate connectome features from one dataset to discriminate patients from controls in the second dataset.ResultsSmall-worldness of the whole-brain connectome was significantly increased in schizophrenia during the WM task; this increase is related to better (though subpar) WM accuracy in patients with more severe negative symptom burden. There was a shift in the degree distribution to a more homogeneous form in patients. The machine-learning approach classified a new set of patients from controls with 84.3% true-positivity rate for schizophrenia and 71.6% overall accuracy.ConclusionsWe demonstrate a putative mechanistic link between connectome topology, hub redistribution, and impaired n-back performance in schizophrenia. The task-dependent modulation of the connectome relates to, but remains inefficient in, improving the performance above par in the presence of severe negative symptoms.
Project description:Working memory (WM) deficits have been widely documented in schizophrenia (SZ), and almost all existing studies attributed the deficits to decreased capacity as compared to healthy control (HC) subjects. Recent developments in WM research suggest that other components, such as precision, also mediate behavioral performance. It remains unclear how different WM components jointly contribute to deficits in schizophrenia. We measured the performance of 60 SZ (31 females) and 61 HC (29 females) in a classical delay-estimation visual working memory (VWM) task and evaluated several influential computational models proposed in basic science of VWM to disentangle the effect of various memory components. We show that the model assuming variable precision (VP) across items and trials is the best model to explain the performance of both groups. According to the VP model, SZ exhibited abnormally larger variability of allocating memory resources rather than resources or capacity per se. Finally, individual differences in the resource allocation variability predicted variation of symptom severity in SZ, highlighting its functional relevance to schizophrenic pathology. This finding was further verified using distinct visual features and subject cohorts. These results provide an alternative view instead of the widely accepted decreased-capacity theory and highlight the key role of elevated resource allocation variability in generating atypical VWM behavior in schizophrenia. Our findings also shed new light on the utility of Bayesian observer models to characterize mechanisms of mental deficits in clinical neuroscience.
Project description:Human immunodeficiency virus (HIV) continues to have adverse effects on cognition and the brain in many infected people, despite a reduced incidence of HIV-associated dementia with combined antiretroviral therapy (cART). Working memory is often affected, along with attention, executive control, and cognitive processing speed. Verbal working memory (VWM) requires the interaction of each of the cognitive component processes along with a phonological loop for verbal repetition and rehearsal. HIV-related functional brain response abnormalities during VWM are evident in functional MRI (fMRI), though the neural substrate underlying these neurocognitive deficits is not well understood. The current study addressed this by comparing 24 HIV+ to 27 demographically matched HIV-seronegative (HIV-) adults with respect to fMRI activation on a VWM paradigm (n-back) relative to performance on two standardized tests of executive control, attention and processing speed (Stroop and Trail Making A-B). As expected, the HIV+ group had deficits on these neurocognitive tests compared to HIV- controls, and also differed in neural response on fMRI relative to neuropsychological performance. Reduced activation in VWM task-related brain regions on the 2-back was associated with Stroop interference deficits in HIV+ but not with either Trail Making A or B performance. Activation of the posterior cingulate cortex (PCC) of the default mode network during rest was associated with Hopkins Verbal Learning Test-2 (HVLT-2) learning in HIV+. These effects were not observed in the HIV- controls. Reduced dynamic range of neural response was also evident in HIV+ adults when activation on the 2-back condition was compared to the extent of activation of the default mode network during periods of rest. Neural dynamic range was associated with both Stroop and HVLT-2 performance. These findings provide evidence that HIV-associated alterations in neural activation induced by VWM demands and during rest differentially predict executive-attention and verbal learning deficits. That the Stroop, but not Trail Making was associated with VWM activation suggests that attentional regulation difficulties in suppressing interference and/or conflict regulation are a component of working memory deficits in HIV+ adults. Alterations in neural dynamic range may be a useful index of the impact of HIV on functional brain response and as a fMRI metric in predicting cognitive outcomes.