Genevieve Yang

Altered global brain signal in schizophrenia

Significance This study identified elevated global brain signal variability in schizophrenia, but not bipolar illness. This variability was related to schizophrenia symptoms. A commonly used analytic procedure in neuroimaging, global signal regression, attenuated clinical effects and altered inferences. Furthermore, local voxel-wise variance was increased in schizophrenia, independent of global signal regression. Finally, neurobiologically grounded computational modeling suggests a putative mechanism, whereby altered overall connection strength in schizophrenia may underlie observed empirical results. Neuropsychiatric conditions like schizophrenia display a complex neurobiology, which has long been associated with distributed brain dysfunction. However, no investigation has tested whether schizophrenia shows alterations in global brain signal (GS), a signal derived from functional MRI and often discarded as a meaningless baseline in many studies. To evaluate GS alterations associated with schizophrenia, we studied two large chronic patient samples (n = 90, n = 71), comparing them to healthy subjects (n = 220) and patients diagnosed with bipolar disorder (n = 73). We identified and replicated increased cortical power and variance in schizophrenia, an effect predictive of symptoms yet obscured by GS removal. Voxel-wise signal variance was also increased in schizophrenia, independent of GS effects. Both findings were absent in bipolar patients, confirming diagnostic specificity. Biologically informed computational modeling of shared and nonshared signal propagation through the brain suggests that these findings may be explained by altered net strength of overall brain connectivity in schizophrenia.

Early-Course Unmedicated Schizophrenia Patients Exhibit Elevated Prefrontal Connectivity Associated with Longitudinal Change

Strong evidence implicates prefrontal cortex (PFC) as a major source of functional impairment in severe mental illness such as schizophrenia. Numerous schizophrenia studies report deficits in PFC structure, activation, and functional connectivity in patients with chronic illness, suggesting that deficient PFC functional connectivity occurs in this disorder. However, the PFC functional connectivity patterns during illness onset and its longitudinal progression remain uncharacterized. Emerging evidence suggests that early-course schizophrenia involves increased PFC glutamate, which might elevate PFC functional connectivity. To test this hypothesis, we examined 129 non-medicated, human subjects diagnosed with early-course schizophrenia and 106 matched healthy human subjects using both whole-brain data-driven and hypothesis-driven PFC analyses of resting-state fMRI. We identified increased PFC connectivity in early-course patients, predictive of symptoms and diagnostic classification, but less evidence for “hypoconnectivity.” At the whole-brain level, we observed “hyperconnectivity” around areas centered on the default system, with modest overlap with PFC-specific effects. The PFC hyperconnectivity normalized for a subset of the sample followed longitudinally (n = 25), which also predicted immediate symptom improvement. Biologically informed computational modeling implicates altered overall connection strength in schizophrenia. The initial hyperconnectivity, which may decrease longitudinally, could have prognostic and therapeutic implications.

Connectivity, Pharmacology, and Computation: Toward a Mechanistic Understanding of Neural System Dysfunction in Schizophrenia

Neuropsychiatric diseases such as schizophrenia and bipolar illness alter the structure and function of distributed neural networks. Functional neuroimaging tools have evolved sufficiently to reliably detect system-level disturbances in neural networks. This review focuses on recent findings in schizophrenia and bipolar illness using resting-state neuroimaging, an advantageous approach for biomarker development given its ease of data collection and lack of task-based confounds. These benefits notwithstanding, neuroimaging does not yet allow the evaluation of individual neurons within local circuits, where pharmacological treatments ultimately exert their effects. This limitation constitutes an important obstacle in translating findings from animal research to humans and from healthy humans to patient populations. Integrating new neuroscientific tools may help to bridge some of these gaps. We specifically discuss two complementary approaches. The first is pharmacological manipulations in healthy volunteers, which transiently mimic some cardinal features of psychiatric conditions. We specifically focus on recent neuroimaging studies using the NMDA receptor antagonist, ketamine, to probe glutamate synaptic dysfunction associated with schizophrenia. Second, we discuss the combination of human pharmacological imaging with biophysically informed computational models developed to guide the interpretation of functional imaging studies and to inform the development of pathophysiologic hypotheses. To illustrate this approach, we review clinical investigations in addition to recent findings of how computational modeling has guided inferences drawn from our studies involving ketamine administration to healthy subjects. Thus, this review asserts that linking experimental studies in humans with computational models will advance to effort to bridge cellular, systems, and clinical neuroscience approaches to psychiatric disorders.

Mediodorsal and Visual Thalamic Connectivity Differ in Schizophrenia and Bipolar Disorder With and Without Psychosis History

Empirical and theoretical studies implicate thalamocortical circuits in schizophrenia, supported by emerging resting-state functional connectivity studies (rs-fcMRI). Similar but attenuated alterations were found in bipolar disorder (BD). However, it remains unknown if segregated loops within thalamocortical systems show distinct rs-fcMRI alterations in schizophrenia. For instance, the mediodorsal (MD) nucleus, known to project to prefrontal networks, may be differently altered than the lateral geniculate nucleus (LGN), known to project to the occipital cortex. Also, it remains unknown if these circuits show different patterns of alterations in BD as a function of psychosis history, which may be associated with a more severe clinical course. We addressed these questions in 90 patients with chronic schizophrenia and 73 remitted BD patients (33 with psychosis history) matched to 146 healthy comparison subjects. We hypothesized that the MD vs LGN would show dissociations across diagnostic groups. We found that MD and LGN show more qualitative similarities than differences in their patterns of dysconnectivity in schizophrenia. In BD, patterns qualitatively diverged between thalamic nuclei although these effects were modest statistically. BD with psychosis history was associated with more severe dysconnectivity, particularly for the MD nucleus. Also, the MD nucleus showed connectivity reductions with the cerebellum in schizophrenia but not in BD. Results suggest dissociations for thalamic nuclei across diagnoses, albeit carefully controlling for medication is warranted in future studies. Collectively, these findings have implications for designing more precise neuroimaging-driven biomarkers that can identify common and divergent large-scale network perturbations across psychiatric diagnoses with shared symptoms.

Ventral Anterior Cingulate Connectivity Distinguished Nonpsychotic Bipolar Illness from Psychotic Bipolar Disorder and Schizophrenia

Bipolar illness is a debilitating neuropsychiatric disorder associated with alterations in the ventral anterior cingulate cortex (vACC), a brain region thought to regulate emotional behavior. Although recent data-driven functional connectivity studies provide evidence consistent with this possibility, the role of vACC in bipolar illness and its pattern of whole brain connectivity remain unknown. Furthermore, no study has established whether vACC exhibits differential whole brain connectivity in bipolar patients with and without co-occurring psychosis and whether this pattern resembles that found in schizophrenia. We conducted a human resting-state functional connectivity investigation focused on the vACC seed in 73 remitted bipolar I disorder patients (33 with psychosis history), 56 demographically matched healthy comparison subjects, and 73 demographically matched patients with chronic schizophrenia. Psychosis history within the bipolar disorder group corresponded with significant between-group connectivity alterations along the dorsal medial prefrontal surface when using the vACC seed. Patients with psychosis history showed reduced connectivity (Cohens d = -0.69), whereas those without psychosis history showed increased vACC coupling (Cohens d = 0.8) relative to controls. The vACC connectivity observed in chronic schizophrenia patients was not significantly different from that seen in bipolar patients with psychosis history but was significantly reduced compared with that in bipolar patients without psychosis history. These robust findings reveal complex vACC connectivity alterations in bipolar illness, which suggest differences depending on co-occurrence of lifetime psychosis. The similarities in vACC connectivity patterns in schizophrenia and psychotic bipolar disorder patients may suggest the existence of common mechanisms underlying psychotic symptoms in the two disorders.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia.

Significance Schizophrenia is linked to widespread neuronal-level changes causing cortical excitation-inhibition imbalance. However, functional neuroimaging reveals preferential association network dysconnectivity. Therefore, a tension exists between two competing frameworks: global versus localized neural dysfunction in schizophrenia. To link these levels of analysis, this study initially simulated cellular-level glutamatergic deficits, generating network-level predictions of cortical imbalance. Schizophrenia results revealed widespread hyperconnectivity in line with model predictions, yet effects were most profound within association networks. These clinical effects were computationally captured by considering a pre-existing functional cortical hierarchy between association and sensory regions. This study reveals that widespread cellular deficits in schizophrenia can give rise to network-preferential disruptions observed in neuroimaging as an emergent property of pre-existing functional differences between cortical areas. Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia.

Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders

Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.

Altered Global Signal Topography in Schizophrenia

Abstract Schizophrenia (SCZ) is a disabling neuropsychiatric disease associated with disruptions across distributed neural systems. Resting‐state functional magnetic resonance imaging has identified extensive abnormalities in the blood‐oxygen level‐dependent signal in SCZ patients, including alterations in the average signal over the brain—i.e. the “global” signal (GS). It remains unknown, however, if these “global” alterations occur pervasively or follow a spatially preferential pattern. This study presents the first network‐by‐network quantification of GS topography in healthy subjects and SCZ patients. We observed a nonuniform GS contribution in healthy comparison subjects, whereby sensory areas exhibited the largest GS component. In SCZ patients, we identified preferential GS representation increases across association regions, while sensory regions showed preferential reductions. GS representation in sensory versus association cortices was strongly anti‐correlated in healthy subjects. This anti‐correlated relationship was markedly reduced in SCZ. Such shifts in GS topography may underlie profound alterations in neural information flow in SCZ, informing development of pharmacotherapies.