Meta-analysis of functional magnetic resonance imaging studies of timing and cognitive control in schizophrenia and bipolar disorder: Evidence of a primary time deficit

Understanding the mechanisms underlying cognitive control in psychosis

BACKGROUND

Cognitive control (CC) involves a top-down mechanism to flexibly respond to complex stimuli and is impaired in schizophrenia.

METHODS

This study investigated the impact of increasing complexity of CC processing in 140 subjects with psychosis and 39 healthy adults, with assessments of behavioral performance, neural regions of interest and symptom severity.

RESULTS

The lowest level of CC (Stroop task) was impaired in all patients; the intermediate level of CC (Faces task) with explicit emotional information was most impaired in patients with first episode psychosis. Patients showed activation of distinct neural CC and reward networks, but iterative learning based on the higher-order of CC during the trust game, was most impaired in chronic schizophrenia. Subjects with first episode psychosis, and patients with lower symptom load, demonstrate flexibility of the CC network to facilitate learning, which appeared compromised in the more chronic stages of schizophrenia.

CONCLUSION

These data suggest optimal windows for opportunities to introduce therapeutic interventions to improve CC.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Resting-state perfusion in motor and fronto-limbic areas is linked to diminished expression of emotion and speech in schizophrenia

Negative symptoms (NS) are a core component of schizophrenia affecting community functioning and quality of life. We tested neural correlates of NS considering NS factors and consensus subdomains. We assessed NS using the Clinical Assessment Interview for Negative Symptoms and the Scale for Assessment of Negative Symptoms. Arterial spin labeling was applied to measure resting-state cerebral blood flow (rCBF) in 47 schizophrenia patients and 44 healthy controls. Multiple regression analyses calculated the relationship between rCBF and NS severity. We found an association between diminished expression (DE) and brain perfusion within the cerebellar anterior lobe and vermis, and the pre-, and supplementary motor area. Blunted affect was linked to fusiform gyrus and alogia to fronto-striatal rCBF. In contrast, motivation and pleasure was not associated with rCBF. These results highlight the key role of motor areas for DE. Considering NS factors and consensus subdomains may help identifying specific pathophysiological pathways of NS.

Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study

Introduction

Over the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort.

Methods

We designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference.

Results

We defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them.

Discussion

We conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia.

Dysconnection and cognition in schizophrenia: A spectral dynamic causal modeling study

Schizophrenia (SZ) is a severe mental disorder characterized by failure of functional integration (aka dysconnection) across the brain. Recent functional connectivity (FC) studies have adopted functional parcellations to define subnetworks of large-scale networks, and to characterize the (dys)connection between them, in normal and clinical populations. While FC examines statistical dependencies between observations, model-based effective connectivity (EC) can disclose the causal influences that underwrite the observed dependencies. In this study, we investigated resting state EC within seven large-scale networks, in 66 SZ and 74 healthy subjects from a public dataset. The results showed that a remarkable 33% of the effective connections (among subnetworks) of the cognitive control network had been pathologically modulated in SZ. Further dysconnection was identified within the visual, default mode and sensorimotor networks of SZ subjects, with 24%, 20%, and 11% aberrant couplings. Overall, the proportion of discriminative connections was remarkably larger in EC (24%) than FC (1%) analysis. Subsequently, to study the neural correlates of impaired cognition in SZ, we conducted a canonical correlation analysis between the EC parameters and the cognitive scores of the patients. As such, the self-inhibitions of supplementary motor area and paracentral lobule (in the sensorimotor network) and the excitatory connection from parahippocampal gyrus to inferior temporal gyrus (in the cognitive control network) were significantly correlated with the social cognition, reasoning/problem solving and working memory capabilities of the patients. Future research can investigate the potential of whole-brain EC as a biomarker for diagnosis of brain disorders and for neuroimaging-based cognitive assessment.

Neurotransmission-related gene expression in the frontal pole is altered in subjects with bipolar disorder and schizophrenia

The frontal pole (Brodmann area 10, BA10) is the largest cytoarchitectonic region of the human cortex, performing complex integrative functions. BA10 undergoes intensive adolescent grey matter pruning prior to the age of onset for bipolar disorder (BP) and schizophrenia (SCHIZ), and its dysfunction is likely to underly aspects of their shared symptomology. In this study, we investigated the role of BA10 neurotransmission-related gene expression in BP and SCHIZ. We performed qPCR to measure the expression of 115 neurotransmission-related targets in control, BP, and SCHIZ postmortem samples (n = 72). We chose this method for its high sensitivity to detect low-level expression. We then strengthened our findings by performing a meta-analysis of publicly released BA10 microarray data (n = 101) and identified sources of convergence with our qPCR results. To improve interpretation, we leveraged the unusually large database of clinical metadata accompanying our samples to explore the relationship between BA10 gene expression, therapeutics, substances of abuse, and symptom profiles, and validated these findings with publicly available datasets. Using these convergent sources of evidence, we identified 20 neurotransmission-related genes that were differentially expressed in BP and SCHIZ in BA10. These results included a large diagnosis-related decrease in two important therapeutic targets with low levels of expression, HTR2B and DRD4, as well as other findings related to dopaminergic, GABAergic and astrocytic function. We also observed that therapeutics may produce a differential expression that opposes diagnosis effects. In contrast, substances of abuse showed similar effects on BA10 gene expression as BP and SCHIZ, potentially amplifying diagnosis-related dysregulation.

Brain correlates of impaired goal management in bipolar mania

BACKGROUND

Although executive impairment has been reported in mania, its brain functional correlates have been relatively little studied. This study examined goal management, believed to be more closely related to executive impairment in daily life than other executive tasks, using a novel functional magnetic resonance imaging (fMRI) paradigm in patients in this illness phase.

METHODS

Twenty-one currently manic patients with bipolar disorder and 30 matched healthy controls were scanned while performing the Computerized Multiple Elements Test (CMET). This requires participants to sequentially play four simple games, with transition between games being made either voluntarily (executive condition) or automatically (control condition).

RESULTS

CMET performance was impaired in the manic patients compared to the healthy controls. Manic patients failed to increase activation in the lateral frontal, cingulate and inferior parietal cortex when the executive demands of the task increased, while this increase was observed in the healthy controls. Activity in these regions was associated with task performance.

CONCLUSIONS

Manic patients show evidence of impaired goal management, which is associated with a pattern of reduced medial and lateral frontal and parietal activity.

Differences of resting fMRI and cognitive function between drug-naïve bipolar disorder and schizophrenia

BACKGROUND

Bipolar disorder (BD) and schizophrenia (SC) have many similarities in clinical manifestations. The acute phase of BD has psychotic symptoms, while SC also has emotional symptoms during the onset, which suggests that there is some uncertainty in distinguishing BD and SC through clinical symptoms.

AIM

To explore the characteristics of brain functional activities and cognitive impairment between BD and SC.

METHODS

Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test was performed on patients in drug-naïve BD and SC (50 subjects in each group), and resting-state functional magnetic resonance imaging (rs-fMRI) scanning was performed meanwhile. Rs-fMRI data were routinely preprocessed, and the value of the fractional amplitude of low-frequency fluctuation (fALFF) was calculated. Then each part of the scores of the RBANS and the characteristics of brain function activities were compared between the two groups. Finally used Pearson correlation to analyze the correlation between cognition and brain function.

RESULTS

(1) Compared with BD group, all parts of RBANS scores in SC group decreased; (2) The left inferior occipital gyrus (IOG, peak coordinates - 30, -87, -15; t = 4.78, voxel size = 31, Alphasim correction) and the right superior temporal gyrus (STG, peak coordinates 51, -12, 0; t = 5.08, voxel size = 17, AlphaSim correction) were the brain areas with significant difference in fALFF values between BD and SC. Compared with SC group, the fALFF values of the left IOG and the right STG in BD group were increased (p < 0.05); (3) Pearson correlation analysis showed that the visuospatial construction score was positively correlated with the fALFF values of the left IOG and the right STG (r_{left IOG} = 0.304, p = 0.003; r_{right STG} = 0.340, p = 0.001); The delayed memory (figure recall) score was positively correlated with the fALFF value of the left IOG (r_{left IOG} = 0.207, p = 0.044).

DISCUSSION

The cognitive impairment of SC was more serious than BD. The abnormal activities of the left IOG and the right STG may be the core brain region to distinguish BD and SC, and are closely related to cognitive impairment, which provide neuroimaging basis for clinical differential diagnosis and explore the pathological mechanism of cognitive impairment.

Demographics, clinical characteristics and cognitive symptoms of heavy smokers and non-heavy smokers in Chinese male patients with chronic schizophrenia

Many studies have shown a high smoking rate and cognitive impairment in patients with schizophrenia. The effects of smoking and nicotine intake on cognitive function in schizophrenia are still controversial. In this study, we divided patients into heavy smoking and non-heavy smoking groups and compared the clinical characteristics and cognitive symptoms between the two groups in Chinese male patients with schizophrenia. A total of 154 heavy smoking patients and 372 non-heavy smoking patients were recruited. They completed a detailed questionnaire including general and socio-demographic data. Positive and Negative Syndrome Scale (PANSS) was rated for psychopathology. The Fagerstrom Test for Nicotine Dependence (FTND) was used to assess the degree of nicotine dependence. Heavy smokers were younger, started smoking earlier and had a higher FTND total score than non-heavy smoking patients. Moreover, we found that heavy smokers had significantly lower negative symptom scores and cognitive factor scores than non-heavy smokers. Logistic regression analysis showed that cognitive factor score and age of initial smoking were significantly associated with heavy smoking. Linear regression analysis showed that cognitive factor score, age of initial smoking and dose of antipsychotics were significant predictors of the amount of smoking. Our findings suggest that there are significant differences in some demographic and clinical variables between heavy and non-heavy smokers in Chinese male patients with chronic schizophrenia. Moreover, heavy smokers have less cognitive symptoms, suggesting that heavy smoking may be beneficial for cognition of patients with schizophrenia.

A systematic review and meta-analysis of structural and functional brain alterations in individuals with genetic and clinical high-risk for psychosis and bipolar disorder

Neuroimaging findings in people at either genetic risk or at clinical high-risk for psychosis (CHR-P) or bipolar disorder (CHR-B) remain unclear. A meta-analytic review of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies in individuals with genetic risk or CHR-P or CHR-B and controls identified 94 datasets (N = 7942). Notwithstanding no significant findings were observed following adjustment for multiple comparisons, several findings were noted at a more liberal threshold. Subjects at genetic risk for schizophrenia or bipolar disorder or at CHR-P exhibited lower gray matter (GM) volumes in the gyrus rectus (Hedges' g = -0.19). Genetic risk for psychosis was associated with GM reductions in the right cerebellum and left amygdala. CHR-P was associated with decreased GM volumes in the frontal superior gyrus and hypoactivation in the right precuneus, the superior frontal gyrus and the right inferior frontal gyrus. Genetic and CHR-P were associated with small structural and functional alterations involving regions implicated in psychosis. Further neuroimaging studies in individuals with genetic or CHR-B are warranted.

The instrumental role of operant paradigms in translational psychiatric research: Insights from a maternal immune activation model of schizophrenia risk

Rigorous behavioral analysis is essential to the translation of research conducted using animal models of neuropsychiatric disease. Here we discuss the use of operant paradigms within our lab as a powerful approach for exploring the biobehavioral bases of disease in the maternal immune activation rat model of schizophrenia. We have investigated a range of disease features in schizophrenia including abnormal perception of time, cognition, learning, motivation, and internal state (psychosis), providing complex insights into brain and behavior. Beyond simple phenotyping, implementing sophisticated operant procedures has been effective in delineating aspects of pathological behavior, identifying interacting pathologies, and isolating contributing mechanisms of disease. We provide comment on the strengths of operant techniques to support high-quality behavioral investigations in fundamental neuropsychiatric research.

Cerebral glucose metabolism in bipolar disorder: A voxel-based meta-analysis of positron emission tomography studies

BACKGROUND

Previous positron emission tomography studies have reported the changes of cerebral glucose metabolism in bipolar disorder. However, the findings across studies remain controversial, containing differing results.

METHODS

A systematic literature search of the PubMed, Embase, Cochrane Library, and Web of Science databases was conducted. We conducted a voxel-wide meta-analysis of cerebral glucose metabolism studies, using the seed-based mapping approach, in patients with bipolar disorder (BD).

RESULTS

We identified 7 studies suitable for inclusion, which included a total of 126 individuals with BD and 160 healthy controls. The most consistent and robust findings were an increase in cerebral glucose metabolism in the right precentral gyrus and a decrease in the left superior temporal gyrus, left middle temporal gyrus, and cerebellum. Additionally, the sex distribution and illness duration had significant moderating effects on cerebral glucose metabolism alterations.

CONCLUSIONS

Cerebral glucose metabolism alterations in these brain regions are likely to reflect the disease-related functional abnormalities such as emotion and cognition. These findings contribute to a better understanding of the neurobiological underpinnings of bipolar disorder.

LIMITATIONS

This study was done at a study level and cannot be addressed at the patient level. Subgroup analysis of BD I and BD II is not possible due to limited literature data.

Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls

The complexity and heterogeneity of schizophrenia symptoms challenge an objective diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the boundaries of schizophrenia are not precisely demarcated from other nosologic categories, such as bipolar disorder. The early detection of schizophrenia can lead to a more effective treatment, improving patients' quality of life. Over the last decades, hundreds of studies aimed at specifying the neurobiological mechanisms that underpin clinical manifestations of schizophrenia, using techniques such as electroencephalography (EEG). Changes in event-related potentials of the EEG have been associated with sensory and cognitive deficits and proposed as biomarkers of schizophrenia. Besides contributing to a more effective diagnosis, biomarkers can be crucial to schizophrenia onset prediction and prognosis. However, any proposed biomarker requires substantial clinical research to prove its validity and cost-effectiveness. Fueled by developments in computational neuroscience, automatic classification of schizophrenia at different stages (prodromal, first episode, chronic) has been attempted, using brain imaging pattern recognition methods to capture differences in functional brain activity. Advanced learning techniques have been studied for this purpose, with promising results. This review provides an overview of recent machine learning-based methods for schizophrenia classification using EEG data, discussing their potentialities and limitations. This review is intended to serve as a starting point for future developments of effective EEG-based models that might predict the onset of schizophrenia, identify subjects at high-risk of psychosis conversion or differentiate schizophrenia from other disorders, promoting more effective early interventions.

Flexible and specific contributions of thalamic subdivisions to human cognition

The thalamus participates in multiple functional brain networks supporting different cognitive abilities. How thalamo-cortical connections map onto the architecture of human cognition remains an outstanding question. The aim of this meta-analysis is to map co-activation between thalamic and extra-thalamic brain regions onto separate cognitive domains and to assess thalamic subdivision specificity within each of the cognitive domains considered. We parsed 93 fMRI studies into twelve cognitive domains. Signed Differential Mapping served to obtain co-activation maps. We then projected the contribution of thalamic subdivisions onto a thalamic atlas to assess cognitive domain specificity. A set of brain regions was flexibly involved with thalamus in several cognitive domains. Thalamic subdivisions showed ample cognitive heterogeneity. Our proposed model represents thalamic involvement in cognition as an "ensemble" of functional subdivisions with common cell properties embedded in separate cortical circuits rather than a homogeneous functional unit.

Cortical activation abnormalities in bipolar and schizophrenia patients in a combined oddball-incongruence paradigm

Patients with bipolar disorder and schizophrenia often suffer from severe cognitive impairment even during times of remission. This study investigated the pathomechanisms underlying their deficits in cognitive control. A combined oddball-incongruence fMRI task was applied to examine similarities and differences of neural activation patterns between patients and healthy controls. Bipolar and schizophrenia patients demonstrated hyperactivations in the intraparietal cortex during the oddball condition. Furthermore, bipolar patients revealed diagnosis-specific hyperactivation in the left middle frontal gyrus, precentral gyrus, anteroventral prefrontal cortex and orbitofrontal cortex regions compared to schizophrenia patients and healthy individuals. In comparison to healthy controls the patients showed hypoactivations in the inferior frontal junction and ventral pathway during the cognitively more demanding incongruence. Taken together, bipolar patients seem to recruit frontal and parietal areas during the oddball condition to compensate for potential deficits in their attentional network. During more challenging tasks, i.e., the incongruence condition, their compensatory mechanisms seem to collapse leading to hypoactivations in the same frontal areas as well as the ventral pathway.

An fMRI Study Using a Combined Task of Interval Discrimination and Oddball Could Reveal Common Brain Circuits of Cognitive Change

Recent functional neuroimaging studies suggest that the brain networks responsible for time processing are involved during other cognitive processes, leading to a hypothesis that time-related processing is needed to perform a range of tasks across various cognitive functions. To examine this hypothesis, we analyze whether, in healthy subjects, the brain structures activated or deactivated during performance of timing and oddball-detection type tasks coincide. To this end, we conducted two independent signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging (fMRI) studies assessing the cerebral generators of the responses elicited by tasks based on timing and oddball-detection paradigms. Finally, we undertook a multimodal meta-analysis to detect brain regions common to the findings of the two previous meta-analyses. We found that healthy subjects showed significant activation in cortical areas related to timing and salience networks. The patterns of activation and deactivation corresponding to each task type partially coincided. We hypothesize that there exists a time and change-detection network that serves as a common underlying resource used in a broad range of cognitive processes.

Association of cigarette smoking with cognitive impairment in male patients with chronic schizophrenia

BACKGROUND

Previous studies have shown that patients with schizophrenia have higher smoking rates and worse cognitive function than healthy controls. However, there is no consistent conclusion about the relationship between smoking and cognitive impairment.

OBJECTIVES

The main purpose of this study was to explore the effects of smoking on cognitive function by using MATRICS Cognitive Consensus Battery (MCCB) in Chinese male patients with schizophrenia.

METHODS

There were 164 patients with chronic schizophrenia and 82 healthy controls. All subjects were interviewed about smoking status. The cognitive function was assessed by MCCB and Stroop tests. The Positive and Negative Syndrome Scale (PANSS) was used to assess the clinical symptoms of the patients.

RESULTS

Compared with healthy controls, patients had lower MCCB scores in all of its domain scores (all p < 0.05). In the patients, the scores of spatial span test (42.3 ± 11.6), digital sequence test (42.9 ± 10.6), and Hopkins Verbal Learning Test (42.2 ± 10.1) were lower in smokers than those in nonsmokers (all p < 0.05, effect size: 0.28-0.45). Logistic regression analysis showed that the smoking status of the patients was correlated with digital sequence score (p < 0.05, OR = 1.072, 95%CI: 1.013-1.134). Multivariate regression analysis showed that the spatial span total score (β = - 0.26, t = - 2.74, p < 0.001) was associated with the duration of smoking in patients with schizophrenia.

CONCLUSIONS

Our findings show that smoking patients with chronic schizophrenia exhibit more severe cognitive impairment than nonsmoking patients, especially in working memory and executive function.

Fractional amplitude of low-frequency fluctuations and gray matter volume alterations in patients with bipolar depression

PURPOSE

We used fractional amplitude of low-frequency fluctuations (fALFF) and gray matter volume (GMV) jointly to explore the mechanism of brain function and structure in unmedicated patients with bipolar disorder (BD).

METHODS

Thirty first episode drug-naive patients with and thirty healthy controls (HCs) were recruited in this study; All the subjects underwent Magnetic Resonance Imaging (MRI) scanning and performed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), all the patients with MDD finished the 17-item Hamilton Depression Rating Scale (HAMD17). Data Processing and Analysis for Brain Imaging (DPABI) and SPM8 were used to find potential differences in fALFF and GMV between the two groups. A Pearson correlation model was used to analyze associations of functional and morphometric changes with clinical symptoms and cognitive tests.

RESULTS

Compared to healthy controls, the BD group had significantly reduced fALFF values in the lingual gyrus and increased fALFF values in the bilateral superior frontal gyrus and superior frontal gyrus. With regards to VBM, patients with BD showed significant GMV decreases in the bilateral superior temporal gyrus, bilateral superior frontal gyrus, right superior frontal gyrus, right parahippocampal gyrus and precuneus. Additionally, we found an overlap of brain regions focused on the left SFG. Significant negative correlations were observed between abnormal GMV values in the left SFG and vocabulary memory.

CONCLUSION

The superior frontal gyrus was the site of the most robust and reliable abnormality, with an overlap of abnormal structural and functional MRI features that play an important role in pathology in BD.

A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder

BACKGROUND

Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy individuals from Bipolar disorder. In this study, we examined the utility of support vector machine (SVM) technique to differentiate bipolar disorder patients and healthy using structural, functional and diffusion tensor images of brain and neurocognitive measures.

METHODS

30 patients with Bipolar disorder-I and 30 age, sex matched individuals participated in the study. Structural MRI, resting state functional MRI and diffusion tensor images were obtained using a 1.5 T scanner. All participants were administered neuropsychological tests to measure executive functions. SVM, a supervised machine learning technique was applied to differentiate patients and healthy individuals with k-fold cross validation over 10 trials.

RESULTS

The composite marker consisting of both neuroimaging and neuropsychological measures, had an accuracy of 87.60 %, sensitivity of 82.3 % and specificity of 92.7 %. The performance of composite marker was better compared to that of individual markers on classificatory.

CONCLUSIONS

We were able to achieve a high accuracy for machine learning technique in distinguishing BD from HV using a combination of multimodal neuroimaging and neurocognitive measures. Findings of this proof of concept study, if replicated in larger samples, could have potential clinical applications.

Deep Temporal Organization of fMRI Phase Synchrony Modes Promotes Large-Scale Disconnection in Schizophrenia

Itinerant dynamics of the brain generates transient and recurrent spatiotemporal patterns in neuroimaging data. Characterizing metastable functional connectivity (FC) - particularly at rest and using functional magnetic resonance imaging (fMRI) - has shaped the field of dynamic functional connectivity (DFC). Mainstream DFC research relies on (sliding window) correlations to identify recurrent FC patterns. Recently, functional relevance of the instantaneous phase synchrony (IPS) of fMRI signals has been revealed using imaging studies and computational models. In the present paper, we identify the repertoire of whole-brain inter-network IPS states at rest. Moreover, we uncover a hierarchy in the temporal organization of IPS modes. We hypothesize that connectivity disorder in schizophrenia (SZ) is related to the (deep) temporal arrangement of large-scale IPS modes. Hence, we analyze resting-state fMRI data from 68 healthy controls (HC) and 51 SZ patients. Seven resting-state networks (and their sub-components) are identified using spatial independent component analysis. IPS is computed between subject-specific network time courses, using analytic signals. The resultant phase coupling patterns, across time and subjects, are clustered into eight IPS states. Statistical tests show that the relative expression and mean lifetime of certain IPS states have been altered in SZ. Namely, patients spend (45%) less time in a globally coherent state and a subcortical-centered state, and (40%) more time in states reflecting anticoupling within the cognitive control network, compared to the HC. Moreover, the transition profile (between states) reveals a deep temporal structure, shaping two metastates with distinct phase synchrony profiles. A metastate is a collection of states such that within-metastate transitions are more probable than across. Remarkably, metastate occupation balance is altered in SZ, in favor of the less synchronous metastate that promotes disconnection across networks. Furthermore, the trajectory of IPS patterns is less efficient, less smooth, and more restricted in SZ subjects, compared to the HC. Finally, a regression analysis confirms the diagnostic value of the defined IPS measures for SZ identification, highlighting the distinctive role of metastate proportion. Our results suggest that the proposed IPS features may be used for classification studies and for characterizing phase synchrony modes in other (clinical) populations.

Failure of activation of striatum during the performance of executive function tasks in adult patients with bipolar disorder

BACKGROUND

Although numerous studies have used functional neuroimaging to identify executive dysfunction in patients with bipolar disorder (BD), the findings are not consistent. The aim of this meta-analysis is to identify the most reliable functional anomalies in BD patients during performance of Executive Function (EF) tasks.

METHODS

A web-based search was performed on publication databases to identify functional magnetic resonance imaging studies of BD patients performing EF tasks and a voxel-based meta-analytic method known as anisotropic Effect Size Signed Differential Mapping (ES-SDM) was used to identify brain regions which showed anomalous activity in BD patients compared with healthy controls (HC).

RESULTS

Twenty datasets consisting of 463 BD patients and 484 HC were included. Compared with HC, BD patients showed significant hypo-activation or failure of activation in the left striatum (p = 0.00007), supplementary motor area (BA 6, p = 0.00037), precentral gyrus (BA 6, p = 0.0014) and cerebellum (BA 37, p = 0.0019), and hyper-activation in the left gyrus rectus (BA 11, p ≈ 0) and right middle temporal gyrus (BA 22, p = 0.00031) during performance of EF tasks. Sensitivity and subgroup analyses showed that the anomaly of left striatum is consistent across studies and present in both euthymic and BD I patients.

CONCLUSIONS

Patients with BD consistently showed abnormal activation in the cortico-striatal system during performance of EF tasks compared with HC. Failure of activation of the striatum may be a reliable marker for impairment in performance of especially inhibition tasks by patients with BD.

Association of circadian properties of temporal processing with rapid antidepressant response to wake and light therapy in bipolar disorder

BACKGROUND

Temporal processing, crucial to guide behavior toward a goal, may have a role in forming a depressive episode, yet it remains unclear which properties of temporal processing are central to antidepressant response. Production of a short duration oscillates in a circadian manner. Altered circadian organization of physiology and behavior are a hallmark of bipolar disorder. We thus tested whether circadian dynamics of time production associate with treatment response in bipolar disorder.

METHODS

Over the three cycles of total sleep deprivation combined with light therapy (chronotherapeutics) in one week, 20 inpatients with a major depressive episode in the course of bipolar disorder produced 10 s and rated their subjective mood and vigilance levels repeatedly.

RESULTS

Eleven patients (58%) among 19 completers achieved remission. Produced time intervals (PTIs) fluctuated more synchronously with mood levels (r = -0.77) than vigilance levels (r = -0.59) during treatment. A higher degree of shortening of PTIs, but not changes in mood or vigilance levels, during the initial 24-h period of treatment predicted better response (LR χ² = 4.58, P = 0.032). Strong opposite daily changes for PTIs and mood levels observed at baseline were both attenuated after treatment only in remitters (F = 7.25, P = 0.015).

LIMITATIONS

Potential external confounders that affect time perception were not controlled.

CONCLUSIONS

The results are the first to demonstrate an association of the circadian properties of time perception with antidepressant effects of chronotherapeutics and suggest the potential utility of time production in predicting clinical outcome of bipolar depression.

Aberrant timing and oddball detection in Schizophrenia: findings from a signed differential mapping meta-analysis

Schizophrenia (SZ) is associated with deficits in both temporal and salience processing. The underlying neurological dysfunctions in both processes, which are interrelated and share neuroanatomical bases, remain poorly understood. The principal objective of this study was to elucidate whether there are any brain regions that show abnormal response during timing and oddball tasks in patients with SZ. To this end, we conducted a signed differential mapping (SDM) meta-analysis of functional magnetic resonance imaging (fMRI) studies assessing abnormal responses elicited by tasks based on the oddball paradigm in patients with SZ. We conducted a similar SDM meta-analysis of neuroimaging studies of timing tasks in SZ. Finally, we undertook a multimodal meta-analysis to detect the common findings of the two previous meta-analyses. We found that SZ patients showed hypoactivation in cortical and subcortical areas related to timing. The dysfunction observed during timing tasks partially coincided with deficiencies in change-detection functions (particularly in the case of preattentional processing in the mismatch negativity response). We hypothesize that a dysfunctional timing/change detection network underlies the cognitive impairment observed in SZ.

Knowing when to stop: Aberrant precision and evidence accumulation in schizophrenia

Predictive coding and active inference formulations of the dysconnection hypothesis suggest that subjects with schizophrenia (SZ) hold unduly precise prior beliefs to compensate for a failure of sensory attenuation. This implies that SZ subjects should both initiate responses prematurely during evidence-accumulation tasks and fail to inhibit their responses at long stop-signal delays. SZ and healthy control subjects were asked to report the timing of billiards-ball collisions and were occasionally required to withhold their responses. SZ subjects showed larger temporal estimation errors, which were associated with premature responses and decreased response inhibition. To account for these effects, we used hierarchical (Bayesian) drift-diffusion models (HDDM) and model selection procedures to adjudicate among four hypotheses. HDDM revealed that the precision of prior beliefs (i.e., starting point) rather than increased sensory precision (i.e., drift rate) drove premature responses and impaired response inhibition in patients with SZ. From the perspective of active inference, we suggest that premature predictions in SZ are responses that, heuristically, are traded off against accuracy to ensure action execution. On the basis of previous work, we suggest that the right insular cortex might mediate this trade-off.

Electroencephalographic delta/alpha frequency activity differentiates psychotic disorders: a study of schizophrenia, bipolar disorder and methamphetamine-induced psychotic disorder

Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. It is known that increased delta and decreased alpha, which are apparent in psychosis, are indicative of inappropriate arousal state, which leads to reduced ability to attend to relevant information. On this premise, we investigated delta/alpha frequency activity, as this ratio of frequency activity may serve as an effective neurophysiological biomarker. The current study investigated differences in delta/alpha frequency activity, in schizophrenia (SCZ), bipolar I disorder with psychotic features and methamphetamine-induced psychosis. One hundred and nine participants, including individuals with SCZ (n = 28), bipolar I disorder with psychotic features (n = 28), methamphetamine-induced psychotic disorder (MPD) (n = 24) and healthy controls (CON, n = 29). Diagnosis was ascertained with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition disorders and current medication was recorded. EEG was undertaken in three testing conditions: resting eyes open, resting eyes closed and during completion of a simple cognitive task (visual continuous performance task). EEG delta/alpha frequency activity was investigated across these conditions. First, delta/alpha frequency activity during resting eyes closed was higher in SCZ and MPD globally, when compared to CON, then lower for bipolar disorder (BPD) than MPD for right hemisphere. Second, delta/alpha frequency activity during resting eyes open was higher in SCZ, BPD and MPD for all electrodes, except left frontal, when compared to CON. Third, delta/alpha frequency activity during the cognitive task was higher in BPD and MPD for all electrodes, except left frontal, when compared to CON. Assessment of EEG delta/alpha frequency activity supports the delineation of underlying neurophysiological mechanisms present in psychotic disorders, which are likely related to dysfunctional thalamo-cortical connectivity. Delta/alpha frequency activity may provide a useful neurophysiological biomarker to delineate psychotic disorders.

Effort-cost decision-making in psychosis and depression: could a similar behavioral deficit arise from disparate psychological and neural mechanisms?

Motivational impairment is a common feature of both depression and psychosis; however, the psychological and neural mechanisms that give rise to motivational impairment in these disorders are poorly understood. Recent research has suggested that aberrant effort-cost decision-making (ECDM) may be a potential contributor to motivational impairment in both psychosis and depression. ECDM refers to choices that individuals make regarding the amount of 'work' they are willing to expend to obtain a certain outcome or reward. Recent experimental work has suggested that those with psychosis and depression may be less willing to expend effort to obtain rewards compared with controls, and that this effort deficit is related to motivational impairment in both disorders. In the current review, we aim to summarize the current literature on ECDM in psychosis and depression, providing evidence for transdiagnostic impairment. Next, we discuss evidence for the hypothesis that a seemingly similar behavioral ECDM deficit might arise from disparate psychological and neural mechanisms. Specifically, we argue that effort deficits in psychosis might be largely driven by deficits in cognitive control and the neural correlates of cognitive control processes, while effort deficits in depression might be largely driven by reduced reward responsivity and the associated neural correlates of reward responsivity. Finally, we will provide some discussion regarding future directions, as well as interpretative challenges to consider when examining ECDM transdiagnostically.

Imaging and Genetic Biomarkers Predicting Transition to Psychosis

The search for diagnostic and prognostic biomarkers in schizophrenia care and treatment is the focus of many within the research community. Longitudinal cohorts of patients presenting at elevated genetic and clinical risk have provided a wealth of data that has informed our understanding of the development of schizophrenia and related psychotic disorders.Imaging follow-up of high-risk cohorts has demonstrated changes in cerebral grey matter of those that eventually transition to schizophrenia that predate the onset of symptoms and evolve over the course of illness. Longitudinal follow-up studies demonstrate that observed grey matter changes can be employed to differentiate those who will transition to schizophrenia from those who will not prior to the onset of the disorder.In recent years our understanding of the genetic makeup of schizophrenia has advanced significantly. The development of modern analysis techniques offers researchers the ability to objectively quantify genetic risk; these have been successfully applied within a high-risk paradigm to assist in differentiating between high-risk individuals who will subsequently become unwell and those who will not.This chapter will discuss the application of imaging and genetic biomarkers within high-risk groups to predict future transition to schizophrenia and related psychotic disorders. We aim to provide an overview of current approaches focussing on grey matter changes that are predictive of future transition to illness, the developing field of genetic risk scores and other methods being developed to aid clinicians in diagnosis and prognosis.