Interactive memory systems and category learning in schizophrenia

Involvement of the long intergenic non-coding RNA LINC00461 in schizophrenia

OBJECTIVE

LINC00461 is a highly conserved intergenic non-protein coding RNA that was implicated in schizophrenia at the genome-wide level. We aim to explore potential mechanisms underlying the involvement of LINC00461 in schizophrenia.

METHODS

We performed a meta-analysis to investigate the association of LINC00461 rs410216 with schizophrenia, and evaluate the effects of the rs410216 on hippocampal volume and function using the functional magnetic resonance imaging (fMRI) analysis. We utilized the GTEx dataset to profile the expression distribution of LINC00461 across different brain regions, and to investigate the potential impact of the risk SNPs on the expression of LINC00461 and other nearby genes. We compared blood expression levels of LINC00461 between schizophrenia patients and controls.

RESULTS

Here we show that single-nucleotide polymorphisms (SNPs) located in regulatory elements spanning the LINC00461 region are significantly associated with schizophrenia (index SNP rs410216, P_meta = 1.43E-05); subjects carrying the risk allele of rs410216 showed decreased hippocampal volume. However, no significant association of the rs410216 variant with hippocampal activation was observed. Moreover, the expression level of LINC00461 mRNA was significantly lower in first-onset schizophrenia patients, and the risk allele also predicts a lower transcriptional level of LINC00461 in the hippocampus.

CONCLUSION

Together, these convergent lines of evidence implicate inadequate LINC00461 expression in the hippocampus in the development of schizophrenia, providing novel insight into the genetic architecture and biological etiology of schizophrenia.

Early adolescent brain markers of late adolescent academic functioning

Academic performance in adolescence strongly influences adult prospects. Intelligence quotient (IQ) has historically been considered a strong predictor of academic performance. Less objectively explored have been morphometric features. We analyzed brain MRI morphometry metrics in early adolescence (age 12-14 years) as quantitative predictors of academic performance over high school using a naïve Bayesian classifier approach with n = 170 subjects. Based on the mean GPA, subjects were divided into high (GPA ≥3.54; n = 87) and low (GPA <3.54; n = 83) academic performers. Covariance analysis was performed to look at the influence of subject demographics. We examined predictive features from the 343 available regions (surface areas, cortical thickness, and subcortical volumes) and applied 4 algorithms for selection and reduction of attributes using Weka. Cortical thickness measures performed better than surface areas or subcortical volumes as predictors of academic performance. We identified 15 cortical thickness regions most predictive of academic performance, three of which have not been described in the literature predictive of academic performance. These were in the left hemisphere fusiform, bilateral insula, and left hemisphere paracentral regions. Prediction had a sensitivity of 0.65 and specificity of 0.73 with independent validation. Follow-up independent t-test analyses between high and low academic achievers on 10 of 15 regions showed between-group significance at the p < 0.05 level. High achievers demonstrated thicker cortices than low achievers. These newly identified regions may help pinpoint new targets for further study in understanding the developing adolescent brain in the classroom setting.

Cognitive function in schizophrenia: conflicting findings and future directions

INTRODUCTION

Schizophrenia is a severe mental disorder with multiple psychopathological domains being affected. Several lines of evidence indicate that cognitive impairment serves as the key component of schizophrenia psychopathology. Although there have been a multitude of cognitive studies in schizophrenia, there are many conflicting results. We reasoned that this could be due to individual differences among the patients (i.e. variation in the severity of positive vs. negative symptoms), different task designs, and/or the administration of different antipsychotics.

METHODS

We thus review existing data concentrating on these dimensions, specifically in relation to dopamine function. We focus on most commonly used cognitive domains: learning, working memory, and attention.

RESULTS

We found that the type of cognitive domain under investigation, medication state and type, and severity of positive and negative symptoms can explain the conflicting results in the literature.

CONCLUSIONS

This review points to future studies investigating individual differences among schizophrenia patients in order to reveal the exact relationship between cognitive function, clinical features, and antipsychotic treatment.

On the Complexity of Brain Disorders: A Symptom-Based Approach

Mounting evidence shows that brain disorders involve multiple and different neural dysfunctions, including regional brain damage, change to cell structure, chemical imbalance, and/or connectivity loss among different brain regions. Understanding the complexity of brain disorders can help us map these neural dysfunctions to different symptom clusters as well as understand subcategories of different brain disorders. Here, we discuss data on the mapping of symptom clusters to different neural dysfunctions using examples from brain disorders such as major depressive disorder (MDD), Parkinson’s disease (PD), schizophrenia, posttraumatic stress disorder (PTSD) and Alzheimer’s disease (AD). In addition, we discuss data on the similarities of symptoms in different disorders. Importantly, computational modeling work may be able to shed light on plausible links between various symptoms and neural damage in brain disorders.

Cognitive correlates of psychosis in patients with Parkinson's disease

INTRODUCTION

Psychosis and hallucinations occur in 20-30% of patients with Parkinson's disease (PD). In the current study, we investigate cognitive functions in relation to the occurrence of psychosis in PD patients.

METHODS

We tested three groups of subjects - PD with psychosis, PD without psychosis and healthy controls - on working memory, learning and transitive inference tasks, which are known to assess prefrontal, basal ganglia and hippocampal functions.

RESULTS

In the working memory task, results show that patients with and without psychosis were more impaired than the healthy control group. In the transitive inference task, we did not find any difference among the groups in the learning phase performance. Importantly, PD patients with psychosis were more impaired than both PD patients without psychosis and controls at transitive inference. We also found that the severity of psychotic symptoms in PD patients [as measured by the Unified Parkinson Disease Rating Scale Thought Disorder (UPDRS TD) item] is directly associated with the severity of cognitive impairment [as measured by the mini-mental status exam (MMSE)], sleep disturbance [as measured by the Scales for Outcome in Parkinson Disease (SCOPA) sleep scale] and transitive inference (although the latter did not reach significance).

CONCLUSIONS

Although hypothetical, our data may suggest that the hippocampus is a neural substrate underlying the occurrence of psychosis, sleep disturbance and cognitive impairment in PD patients.

Neural and behavioral substrates of subtypes of Parkinson's disease

Parkinson’s disease (PD) is a neurological disorder, associated with rigidity, bradykinesia, and resting tremor, among other motor symptoms. In addition, patients with PD also show cognitive and psychiatric dysfunction, including dementia, mild cognitive impairment (MCI), depression, hallucinations, among others. Interestingly, the occurrence of these symptoms—motor, cognitive, and psychiatric—vary among individuals, such that a subgroup of PD patients might show some of the symptoms, but another subgroup does not. This has prompted neurologists and scientists to subtype PD patients depending on the severity of symptoms they show. Neural studies have also mapped different motor, cognitive, and psychiatric symptoms in PD to different brain networks. In this review, we discuss the neural and behavioral substrates of most common subtypes of PD patients, that are related to the occurrence of: (a) resting tremor (vs. nontremor-dominant); (b) MCI; (c) dementia; (d) impulse control disorders (ICD); (e) depression; and/or (f) hallucinations. We end by discussing the relationship among subtypes of PD subgroups, and the relationship among motor, cognitive, psychiatric factors in PD.

Shared impairment in associative learning in schizophrenia and bipolar disorder

BACKGROUND

Schizophrenia (SCZ) and bipolar disorder (BD) share some cognitive commonalities. However, the role of associative learning, which is a cornerstone of human cognition mainly relying on hippocampus, has been under-investigated. We assessed behavioral performance during associative learning in a group of SCZ, BD and healthy controls (HC).

METHODS

Nineteen patients with SCZ (36 ± 8.1 years; 13 males, 6 females; all Caucasians), 14 patients with BD (41 ± 9.6 years; 5 males, 9 females; all Caucasians) and 45 HC (27.7 ± 6.9 years; 18 males, 27 females; all Caucasians) were studied. Learning was assessed using an established object-location paired-associative learning paradigm. Subjects learned associations between nine equi-familiar common objects and locations in a nine-location grid. Performance data were analyzed in a repeated measures analysis of variance with time (repeated) and group as factors.

RESULTS

Learning curves (performance = (1-e(-k x time)) fitted to average performance data in the three groups revealed lower learning rates in SCZ and BD (k = 0.17 and k = 0.34) than HC (k = 0.78). Significant effects of group (F = 11.05, p < 0.001) and time (F = 122.06, p < 0.001) on learning performance were observed.

CONCLUSIONS

Our study showed that associative learning is impaired in both SCZ and BD, being potentially not affected by medication. Future studies should investigate the neural substrates of learning deficits in SCZ and BD, particularly focusing on hippocampus function and glutamatergic transmission.

Computational cognitive models of prefrontal-striatal-hippocampal interactions in Parkinson's disease and schizophrenia

Disruption to different components of the prefrontal cortex, basal ganglia, and hippocampal circuits leads to various psychiatric and neurological disorders including Parkinson's disease (PD) and schizophrenia. Medications used to treat these disorders (such as levodopa, dopamine agonists, antipsychotics, among others) affect the prefrontal-striatal-hippocampal circuits in a complex fashion. We have built models of prefrontal-striatal and striatal-hippocampal interactions which simulate cognitive dysfunction in PD and schizophrenia. In these models, we argue that the basal ganglia is key for stimulus-response learning, the hippocampus for stimulus-stimulus representational learning, and the prefrontal cortex for stimulus selection during learning about multidimensional stimuli. In our models, PD is associated with reduced dopamine levels in the basal ganglia and prefrontal cortex. In contrast, the cognitive deficits in schizophrenia are associated primarily with hippocampal dysfunction, while the occurrence of negative symptoms is associated with frontostriatal deficits in a subset of patients. In this paper, we review our past models and provide new simulation results for both PD and schizophrenia. We also describe an extended model that includes simulation of the different functional role of D1 and D2 dopamine receptors in the basal ganglia and prefrontal cortex, a dissociation we argue is essential for understanding the non-uniform effects of levodopa, dopamine agonists, and antipsychotics on cognition. Motivated by clinical and physiological data, we discuss model limitations and challenges to be addressed in future models of these brain disorders.

A neural model of hippocampal-striatal interactions in associative learning and transfer generalization in various neurological and psychiatric patients

Building on our previous neurocomputational models of basal ganglia and hippocampal region function (and their modulation by dopamine and acetylcholine, respectively), we show here how an integration of these models can inform our understanding of the interaction between the basal ganglia and hippocampal region in associative learning and transfer generalization across various patient populations. As a common test bed for exploring interactions between these brain regions and neuromodulators, we focus on the acquired equivalence task, an associative learning paradigm in which stimuli that have been associated with the same outcome acquire a functional similarity such that subsequent generalization between these stimuli increases. This task has been used to test cognitive dysfunction in various patient populations with damages to the hippocampal region and basal ganglia, including studies of patients with Parkinson's disease (PD), schizophrenia, basal forebrain amnesia, and hippocampal atrophy. Simulation results show that damage to the hippocampal region-as in patients with hippocampal atrophy (HA), hypoxia, mild Alzheimer's (AD), or schizophrenia-leads to intact associative learning but impaired transfer generalization performance. Moreover, the model demonstrates how PD and anterior communicating artery (ACoA) aneurysm-two very different brain disorders that affect different neural mechanisms-can have similar effects on acquired equivalence performance. In particular, the model shows that simulating a loss of dopamine function in the basal ganglia module (as in PD) leads to slow acquisition learning but intact transfer generalization. Similarly, the model shows that simulating the loss of acetylcholine in the hippocampal region (as in ACoA aneurysm) also results in slower acquisition learning. We argue from this that changes in associative learning of stimulus-action pathways (in the basal ganglia) or changes in the learning of stimulus representations (in the hippocampal region) can have similar functional effects.

Patients with schizophrenia have a reduced neural response to both unpredictable and predictable primary reinforcers

One prevalent theory of learning states that dopamine neurons signal mismatches between expected and actual outcomes, called temporal difference errors (TDEs). Evidence indicates that dopamine system dysfunction is involved in negative symptoms of schizophrenia (SZ), including avolition and anhedonia. As such, we predicted that brain responses to TDEs in dopamine midbrain nuclei and target areas would be abnormal in SZ. A total of 18 clinically stable patients with chronic SZ and 18 controls participated in an fMRI study, which used a passive conditioning task. In the task, the delivery of a small amount of juice followed a light stimulus by exactly 6 s on approximately 75% of 78 total trials, and was further delayed by 4-7 s on the remaining trials. The delayed juice delivery was designed to elicit the two types of TDE signals, associated with the recognition that a reward was omitted at the expected time, and delivered at an unexpected time. Main effects of TDE valence and group differences in the positive-negative TDE contrast (unexpected juice deliveries-juice omissions) were assessed through whole-brain and regions of interest (ROI) analyses. Main effects of TDE valence were observed for the entire sample in the midbrain, left putamen, left cerebellum, and primary gustatory cortex, bilaterally. Whole-brain analyses revealed group differences in the positive-negative TDE contrast in the right putamen and left precentral gyrus, whereas ROI analyses revealed additional group differences in the midbrain, insula, and parietal operculum, on the right, the putamen and cerebellum, on the left, and the frontal operculum, bilaterally. Further, these group differences were generally driven by attenuated responses in patients to positive TDEs (unexpected juice deliveries), whereas responses to negative TDEs (unexpected juice omissions) were largely intact. Patients also showed reductions in responses to juice deliveries on standard trials, and more blunted reinforcer responses in the left putamen corresponded to higher ratings of avolition. These results provide evidence that SZ patients show abnormal brain responses associated with the processing of a primary reinforcer, which may be a source of motivational deficits.

The role of attention and immediate memory in vulnerability to interpersonal criticism during family transactions in schizophrenia

OBJECTIVE

Cognitive dysfunctions may represent vulnerability markers to psychosocial stress in schizophrenia. The purpose of this study was to investigate the possibility that cognitive deficits are associated with the emergence of unusual thoughts during a stressful family transaction.

METHODS

The cognitive performance of 80 patients with schizophrenia was characterized by the five index scores of the repeatable brief assessment of neuropsychological status (RBANS) test battery (immediate and delayed memory, visuospatial/constructional functions, language, and attention). The patients and one of their family members participated in a 20-minute interaction during which the number of relatives' harsh criticisms and the number of patients' unusual thoughts was measured.

RESULTS

Regression analyses revealed that criticism together with attention/immediate memory best predicted the number of unusual thoughts (>25% of variance). In patients with poor attention/immediate memory, there was a significant positive relationship between the number of criticisms and unusual thoughts.

CONCLUSIONS

The results indicate that family criticism is related to thinking disturbances in patients with poor attention/immediate memory. The enhancement of these cognitive functions may increase resistance to psychosocial stress in schizophrenia.