Trait contributions of complex dysregulated behavioral organization in schizophrenic patients

Accuracy of diagnostic classification algorithms using cognitive-, electrophysiological-, and neuroanatomical data in antipsychotic-naïve schizophrenia patients

BACKGROUND

A wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.

METHODS

Forty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.

RESULTS

Cognitive data significantly classified patients from controls (accuracies = 60-69%; p values = 0.0001-0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.

CONCLUSIONS

In this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.

Selective functional connectivity abnormality of the transition zone of the inferior parietal lobule in schizophrenia

Structural and functional alterations in the inferior parietal lobule (IPL) in schizophrenia have been frequently reported; however, the IPL connectivity changes in schizophrenia remain largely unknown. Based on heterogeneity of the IPL in structure, connection and function, we hypothesize that the resting-state functional connectivities (rsFCs) of the IPL subregions are differentially affected in schizophrenia. This study included 95 schizophrenia patients and 104 healthy controls. The IPL subregions were defined according to a previous in vivo connection-based parcellation study. We calculated the rsFC of each IPL subregion and compared them between the two groups while controlling for the effects of age, gender, and grey matter volume. Among the six subregions of the left IPL and the five subregions of the right IPL, only the bilateral PFm (a transition zone of the IPL) subregions exhibited abnormal rsFC in schizophrenia. Specifically, the left PFm showed increased rsFC with the bilateral lingual gyri in schizophrenia patients than in healthy controls. The right PFm exhibited increased rsFC with the right lingual gyrus and inferior occipital gyrus, and bilateral mid-cingulate and sensorimotor cortices in schizophrenia patients. These findings suggest a selective rsFC abnormality in the IPL subregions in schizophrenia, characterized by the increased rsFC between the PFm subregion of the IPL and the visual and sensorimotor areas.

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Investigation of the subregional-level rsFC changes of the IPL in schizophrenia

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The PFm is only IPL subregion with significant rsFC changes in schizophrenia.

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Suggesting a selective rsFC abnormality in the IPL subregions in schizophrenia

Is disorganization a feature of schizophrenia or a modifying influence: evidence of covariation of perceptual and cognitive organization in a non-patient sample

A subgroup of people with schizophrenia is characterized by reduced organization in perception, thought, language, and motor functioning, and these impairments covary significantly. While this may reflect multiple expressions of an illness-related core processing impairment, it may also represent the extreme end of an organization-disorganization dimension that is found throughout the general population. In this view, disorganization is a modifying influence on illness expression. To obtain preliminary information on this hypothesis, we examined covariation of perceptual and cognitive organization in a non-patient sample. Subjects completed a battery of perceptual tasks with demonstrated sensitivity to schizophrenia and disorganization, and a battery of questionnaires examining cognitive organization. Our results indicated that level of perceptual organization ability, across multiple tasks, was associated with self-reported levels of cognitive organization on multiple measures. This is thus preliminary evidence for a common process affecting perceptual and cognitive organization in the general population, suggesting that disorganization may reflect a modifying influence mechanism, instead of an illness-related process, in schizophrenia.

Effect of methamphetamine dependence on heart rate variability

Methamphetamine (METH) is an increasing popular and highly addictive stimulant associated with autonomic nervous system (ANS) dysfunction, cardiovascular pathology and neurotoxicity. Heart rate variability (HRV) has been used to assess autonomic function and predict mortality in cardiac disorders and drug intoxication, but has not been characterized in METH use. We recorded HRV in a sample of currently abstinent individuals with a history of METH dependence compared to age- and gender-matched drug-free comparison subjects. HRV was assessed using time domain, frequency domain, and non-linear entropic analyses in 17 previously METH-dependent and 21 drug-free comparison individuals during a 5 minute rest period. The METH-dependent group demonstrated significant reduction in HRV, reduced parasympathetic activity, and diminished heartbeat complexity relative to comparison participants. More recent METH use was associated with increased sympathetic tone. Chronic METH exposure may be associated with decreased HRV, impaired vagal function, and reduction in heart rate complexity as assessed by multiple methods of analysis. We discuss and review evidence that impaired HRV may be related to the cardiotoxic or neurotoxic effects of prolonged METH use.

Optimizing vs. matching: response strategy in a probabilistic learning task is associated with negative symptoms of schizophrenia

Previous research indicates that behavioral performance in simple probability learning tasks can be organized into response strategy classifications that are thought to predict important personal characteristics and individual differences. Typically, relatively small proportion of subjects can be identified as optimizers for effectively exploiting the environment and choosing the more rewarding stimulus nearly all of the time. In contrast, the vast majority of subjects behaves sub-optimally and adopts the matching or super-matching strategy, apportioning their responses in a way that matches or slightly exceeds the probabilities of reinforcement. In the present study, we administered a two-choice probability learning paradigm to 51 individuals with schizophrenia (SZ) and 29 healthy controls (NC) to examine whether there are differences in the proportion of subjects falling into these response strategy classifications, and to determine whether task performance is differentially associated with symptom severity and neuropsychological functioning. Although the sample of SZ patients did not differ from NC in overall rate of learning or end performance, significant clinical differences emerged when patients were divided into optimizing, super-matching and matching subgroups based upon task performance. Patients classified as optimizers, who adopted the most advantageous learning strategy, exhibited higher levels of positive and negative symptoms than their matching and super-matching counterparts. Importantly, when both positive and negative symptoms were considered together, only negative symptom severity was a significant predictor of whether a subject would behave optimally, with each one standard deviation increase in negative symptoms increasing the odds of a patient being an optimizer by as much as 80%. These data provide a rare example of a greater clinical impairment being associated with better behavioral performance.

Decision-making dysregulation in first-episode schizophrenia

Studies with chronic schizophrenia patients have demonstrated that patients fluctuate between rigid and unpredictable responses in decision-making situations, a phenomenon which has been called dysregulation. The aim of this study was to investigate whether schizophrenia patients already display dysregulated behavior at the beginning of their illness. Thirty-two first-episode schizophrenia or schizophreniform patients and 30 healthy controls performed the two-choice prediction task. The decision-making behavior of first-episode patients was shown to be characterized by a high degree of dysregulation accompanied by low metric entropy and a tendency towards increased mutual information. These results indicate that behavioral abnormalities during the two-choice prediction task are already present during the early stages of the illness.

Schizophrenia subjects show intact success-related neural activation but impaired uncertainty processing during decision-making

Decision-making is a complex process that is important for everyday life. This study examined the effect of the degree of success, and outcome uncertainty, on decision-making and associated neural substrate activation in schizophrenia subjects (SZS) and normal comparison subjects (NCS). A total of 15 subjects with a diagnosis of schizophrenia and 15 age- and education-matched NCS participated in this study. These subjects completed the two-choice prediction task during functional magnetic resonance imaging. Decision-making characteristics and activation of neural substrates were obtained at 20, 50, or 80% error rate. Success and uncertainty influenced the behavioral characteristics on the two-choice prediction task, and the task-related activation in SZS and NCS. Neither success nor uncertainty differentially affected the behavioral characteristics of SZS relative to NCS during the two-choice prediction task. Nonetheless, there was a significant interaction between group and error rate in bilateral parietal cortex. The activation in NCS was the highest when the outcome was most uncertain. In contrast, task-related activation in SZS was not modulated by the degree of uncertainty. Thus, SZS failed to utilize the parietal cortex to process decision-making situations with highly uncertain outcomes.

Chaos and schizophrenia: does the method fit the madness?

Over the past 30 years, investigators have used nonlinear and so-called chaos theory-based techniques to examine a wide range of phenomena ranging from electroencephalogram and cardiac rate and rhythm analyses to stock market and weather predictions. Psychiatric neuroscientists are now beginning to apply nonlinear methods to mental disorders such as schizophrenia. These applications are relevant from the level of complex genetic architecture and calcium channel dynamics to the symptomatic, behavioral, and functional outcome of schizophrenia. The key point of this surge of interest is distinguishing complex, nonlinear but lawfully mediated systems from truly random systems. The application of these methods to studies in schizophrenia has yielded findings that are consistent with the general hypothesis that an altered sequential or temporal architecture is a key feature of this disorder. Specifically, we propose that the temporal architecture of schizophrenia is characterized by bursts of complex, nonlinear phenomena alternating with truly random events. Analyzing these patterns of molecular (e.g., calcium channel activity) to molar (e.g., symptom level) phenomena via nonlinear systems methods can provide new approaches to understanding complex temporal and sequential shifts in neural substrate activity, pathophysiology, and the course and treatment and outcome of schizophrenia.

Parietal dysfunction is associated with increased outcome-related decision-making in schizophrenia patients

BACKGROUND

Decision-making is a complex process and depends on a network of fronto-parietal and cingulate areas. Decision-making dysfunctions in schizophrenia patients are characterized by an alternation between stereotypic and unpredictable responses. This study tested the hypothesis that schizophrenia patients show less decision-making-related activation in the prefrontal and parietal cortex.

METHODS

Fifteen schizophrenia patients were matched with fifteen normal comparison subjects. During functional magnetic resonance imaging (fMRI) scanning, subjects were tested on the two-choice prediction task (predicting the location of a randomly presented stimulus) and the two-choice response task (responding according to the location of the stimulus).

RESULTS

Schizophrenia patients relative to comparison subjects generated more outcome-dependent responses. Schizophrenia patients and normal comparison subjects showed decision-making-related activation in right prefrontal cortex, insula, anterior cingulate, and bilateral precuneus. Schizophrenia patients showed less activation in inferior, medial prefrontal, and right superior temporal cortex and more activation in the postcentral and inferior parietal cortex. Decision-making-related activation in both right prefrontal and bilateral parietal cortex was higher in medicated compared to unmedicated schizophrenia patients.

CONCLUSIONS

These results support the hypothesis that the interaction between prefrontal and parietal cortex during decision-making by schizophrenia patients is dysregulated, which results in an increased outcome-dependent response selection.

The borderline diagnosis III: identifying endophenotypes for genetic studies

Although it is generally acknowledged that borderline personality disorder (BPD) has a complex, multifactorial etiology with interacting genetic and environmental substrates, the specific genetic underpinnings of this disorder have not been extensively investigated. Family aggregation studies suggest the heritability for BPD as a diagnosis, but the genetic basis for this disorder may be stronger for dimensions such as impulsivity/aggression and affective instability than for the diagnostic criteria itself. Family, adoptive, and twin studies also converge to support an underlying genetic component to the disorder. An endophenotypic approach to defining the genetics of this complex disorder may be called for. Twin studies in an epidemiologic, non-clinically ascertained sample using both diagnostic measures and laboratory measures that can be operationalized, including neuropsychologic, psychophysiologic, and operationalized behavioral tests, may be useful. Large-scale family studies of clinically ascertained samples with careful diagnostic demarcation and measurement of endophenotypes in probands and relatives may also prove to be a promising approach. The use of laboratory paradigms for measures of aggression and affective instability are discussed in the context of such endophenotypic approaches.