Dataset Information

Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis.

ABSTRACT: Numerous studies have identified reinforcement learning (RL) deficits in schizophrenia. Most have focused on chronic patients with longstanding antipsychotic treatment, however, and studies of RL in early-illness patients have produced mixed results, particularly regarding gradual/procedural learning. No study has directly contrasted both rapid and gradual RL in first-episode psychosis (FEP) samples. We examined probabilistic RL in 34 FEP patients and 36 controls, using Go/NoGo (GNG) and Gain vs Loss-Avoidance (GLA) paradigms. Our results were mixed, with FEP patients exhibiting greater impairment in the ability to use positive, as opposed to negative, feedback to drive rapid RL on the GLA, but not the GNG. By contrast, patients and controls showed similar improvement across the acquisition. Finally, we found no significant between-group differences in the postacquisition expression of value-based preference in both tasks. Negative symptoms were modestly associated with RL measures, while the overall bias to engage in Go-responding correlated significantly with psychosis severity in FEP patients, consistent with striatal hyperdopaminergia. Taken together, FEP patients demonstrated more circumscribed RL impairments than previous studies have documented in chronic samples, possibly reflecting differential symptom profiles between first-episode and chronic samples. Our finding of relatively preserved gradual/procedural RL, in briefly medicated FEP patients, might suggest spared or restored basal ganglia function. Our findings of preserved abilities to use representations of expected value to guide decision making, and our mixed results regarding rapid RL, may reflect a lesser degree of prefrontal cortical functional impairment in FEP than in chronic samples. Further longitudinal research, in larger samples, is required.

SUBMITTER: Chang WC

PROVIDER: S-EPMC5049533 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis.

Chang Wing Chung WC Waltz James A JA Gold James M JM Chan Tracey Chi Wan TCW Chen Eric Yu Hai EYH

Schizophrenia bulletin 20160513 6

Numerous studies have identified reinforcement learning (RL) deficits in schizophrenia. Most have focused on chronic patients with longstanding antipsychotic treatment, however, and studies of RL in early-illness patients have produced mixed results, particularly regarding gradual/procedural learning. No study has directly contrasted both rapid and gradual RL in first-episode psychosis (FEP) samples. We examined probabilistic RL in 34 FEP patients and 36 controls, using Go/NoGo (GNG) and Gain vs ...[more]

PMID: 27179125

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Project description:BACKGROUND:Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic and functional outcomes. Our study objective is to use routinely collected baseline demographic and clinical characteristics to predict employment, education or training (EET) status, and symptom remission in patients with first episode psychosis (FEP) at one-year. METHODS AND FINDINGS:83 FEP patients were recruited from National Health Service (NHS) Glasgow between 2011 and 2014 to a 24-month prospective cohort study with regular assessment of demographic and psychometric measures. An external independent cohort of 79 FEP patients were recruited from NHS Glasgow and Edinburgh during a 12-month study between 2006 and 2009. Elastic net regularised logistic regression models were built to predict binary EET status, period and point remission outcomes at one-year on 83 Glasgow patients (training dataset). Models were externally validated on an independent dataset of 79 patients from Glasgow and Edinburgh (validation dataset). Only baseline predictors shared across both cohorts were made available for model training and validation. After excluding participants with missing outcomes, models were built on the training dataset for EET status, period and point remission outcomes and externally validated on the validation dataset. Models predicted EET status, period and point remission with receiver operating curve (ROC) area under the curve (AUC) performances of 0.876 (95%CI: 0.864, 0.887), 0.630 (95%CI: 0.612, 0.647) and 0.652 (95%CI: 0.635, 0.670) respectively. Positive predictors of EET included baseline EET and living with spouse/children. Negative predictors included higher PANSS suspiciousness, hostility and delusions scores. Positive predictors for symptom remission included living with spouse/children, and affective symptoms on the Positive and Negative Syndrome Scale (PANSS). Negative predictors of remission included passive social withdrawal symptoms on PANSS. A key limitation of this study is the small sample size (n) relative to the number of predictors (p), whereby p approaches n. The use of elastic net regularised regression rather than ordinary least squares regression helped circumvent this difficulty. Further, we did not have information for biological and additional social variables, such as nicotine dependence, which observational studies have linked to outcomes in psychosis. CONCLUSIONS AND RELEVANCE:Using advanced statistical machine learning techniques, we provide the first externally validated evidence, in a temporally and geographically independent cohort, for the ability to predict one-year EET status and symptom remission in individual FEP patients.

Project description:BackgroundThough olfactory deficits are well-documented in schizophrenia, fewer studies have examined olfactory performance profiles across the psychosis spectrum. The current study examined odor identification, discrimination, and detection threshold performance in first-episode psychosis (FEP) patients diagnosed with schizophrenia, schizoaffective disorder, bipolar disorder with psychotic features, major depression with psychotic features, and other psychotic conditions.MethodFEP patients (n = 97) and healthy adults (n = 98) completed birhinal assessments of odor identification, discrimination, and detection threshold sensitivity for lyral and citralva. Participants also completed measures of anticipatory pleasure, anhedonia, and empathy. Differences in olfactory performances were assessed between FEP patients and controls and within FEP subgroups. Sex-stratified post hoc analyses were employed for a complete analysis of sex differences. Relationships between self-report measures and olfactory scores were also examined.ResultsIndividuals with psychosis had poorer scores across all olfactory measures when compared to the control group. Within the psychosis cohort, patients with schizophrenia-associated psychosis had poorer odor identification, discrimination, and citralva detection threshold scores relative to controls. In schizophrenia patients, greater olfactory disturbance was associated with increased negative symptomatology, greater self-reported anhedonia, and lower self-reported anticipatory pleasure. Patients with mood-associated psychosis performed comparable to controls though men and women in this cohort showed differential olfactory profiles.ConclusionsThese findings indicate that olfactory deficits extend beyond measures of odor identification in FEP with greater deficits observed in schizophrenia-related subgroups of psychosis. Studies examining whether greater olfactory dysfunction confers greater risk for developing schizophrenia relative to other forms of psychosis are warranted.

Dataset Information

Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis.

Publications

Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis.

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