Youngsun T. Cho

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.

Cortico-amygdala-striatal circuits are organized as hierarchical subsystems through the primate amygdala.

The prefrontal and insula cortex, amygdala, and striatum are key regions for emotional processing, yet the amygdalas role as an interface between the cortex and striatum is not well understood. In the nonhuman primate (Macaque fascicularis), we analyzed a collection of bidirectional tracer injections in the amygdala to understand how cortical inputs and striatal outputs are organized to form integrated cortico–amygdala–striatal circuits. Overall, diverse prefrontal and insular cortical regions projected to the basal and accessory basal nuclei of the amygdala. In turn, these amygdala regions projected to widespread striatal domains extending well beyond the classic ventral striatum. Analysis of the cases in aggregate revealed a topographic colocalization of cortical inputs and striatal outputs in the amygdala that was additionally distinguished by cortical cytoarchitecture. Specifically, the degree of cortical laminar differentiation of the cortical inputs predicted amygdalostriatal targets, and distinguished three main cortico–amygdala–striatal circuits. These three circuits were categorized as “primitive,” “intermediate,” and “developed,” respectively, to emphasize the relative phylogenetic and ontogenetic features of the cortical inputs. Within the amygdala, these circuits appeared arranged in a pyramidal-like fashion, with the primitive circuit found in all examined subregions, and subsequent circuits hierarchically layered in discrete amygdala subregions. This arrangement suggests a stepwise integration of the functions of these circuits across amygdala subregions, providing a potential mechanism through which internal emotional states are managed with external social and sensory information toward emotionally informed complex behaviors.

Amygdala Connectivity Differs Among Chronic, Early Course, and Individuals at Risk for Developing Schizophrenia

Alterations in circuits involving the amygdala have been repeatedly implicated in schizophrenia neuropathology, given their role in stress, affective salience processing, and psychosis onset. Disturbances in amygdala whole-brain functional connectivity associated with schizophrenia have yet to be fully characterized despite their importance in psychosis. Moreover, it remains unknown if there are functional alterations in amygdala circuits across illness phases. To evaluate this possibility, we compared whole-brain amygdala connectivity in healthy comparison subjects (HCS), individuals at high risk (HR) for schizophrenia, individuals in the early course of schizophrenia (EC-SCZ), and patients with chronic schizophrenia (C-SCZ). We computed whole-brain resting-state connectivity using functional magnetic resonance imaging at 3T via anatomically defined individual-specific amygdala seeds. We identified significant alterations in amygdala connectivity with orbitofrontal cortex (OFC), driven by reductions in EC-SCZ and C-SCZ (effect sizes of 1.0 and 0.97, respectively), but not in HR for schizophrenia, relative to HCS. Reduced amygdala-OFC coupling was associated with schizophrenia symptom severity (r = .32, P < .015). Conversely, we identified a robust increase in amygdala connectivity with a brainstem region around noradrenergic arousal nuclei, particularly for HR individuals relative to HCS (effect size = 1.54), but not as prominently for other clinical groups. These results suggest that deficits in amygdala-OFC coupling could emerge during the initial episode of schizophrenia (EC-SCZ) and may present as an enduring feature of the illness (C-SCZ) in association with symptom severity but are not present in individuals with elevated risk for developing schizophrenia. Instead, in HR individuals, there appears to be increased connectivity in a circuit implicated in stress response.

Schizophrenia is associated with a pattern of spatial working memory deficits consistent with cortical disinhibition.

Schizophrenia is associated with severe cognitive deficits, including impaired working memory (WM). A neural mechanism that may contribute to WM impairment is the disruption in excitation-inhibition (E/I) balance in cortical microcircuits. It remains unknown, however, how these alterations map onto quantifiable behavioral deficits in patients. Based on predictions from a validated microcircuit model of spatial WM, we hypothesized two key behavioral consequences: i) increased variability of WM traces over time, reducing performance precision; and ii) decreased ability to filter out distractors that overlap with WM representations. To test model predictions, we studied N=27 schizophrenia patients and N=28 matched healthy comparison subjects (HCS) who performed a spatial WM task designed to test the computational model. Specifically, we manipulated delay duration and distractor distance presented during the delay. Subjects used a high-sensitivity joystick to indicate the remembered location, yielding a continuous response measure. Results largely followed model predictions, whereby patients exhibited increased variance and less WM precision as the delay period increased relative to HCS. Schizophrenia patients also exhibited increased WM distractibility, with reports biased toward distractors at specific spatial locations, as predicted by the model. Finally, the magnitude of the WM drift and distractibility were significantly correlated, indicating a possibly shared underlying mechanism. Effects are consistent with elevated E/I ratio in schizophrenia, establishing a framework for translating neural circuit computational model of cognition to human experiments, explicitly testing mechanistic behavioral hypotheses of cellular-level neural deficits in patients.

Amygdala volume is reduced in early course schizophrenia

Subcortical structural alterations have been implicated in the neuropathology of schizophrenia. Yet, the extent of anatomical alterations for subcortical structures across illness phases remains unknown. To assess this, magnetic resonance imaging (MRI) was used to examine volume differences of major subcortical structures: thalamus, nucleus accumbens, caudate, putamen, globus pallidus, amygdala and hippocampus. These differences were examined across four groups: (i) healthy comparison subjects (HCS, n=96); (ii) individuals at high risk (HR, n=21) for schizophrenia; (iii) early-course schizophrenia patients (EC-SCZ, n=28); and (iv) chronic schizophrenia patients (C-SCZ, n=20). Raw gray matter volumes and volumetric ratios (volume of specific structure/total gray matter volume) were extracted using automated segmentation tools. EC-SCZ group exhibited smaller bilateral amygdala volumetric ratios, compared to HCS and HR subjects. Findings did not change when corrected for age, level of education and medication use. Amygdala raw volumes did not differ among groups once adjusted for multiple comparisons, but the smaller amygdala volumetric ratio in EC-SCZ survived Bonferroni correction. Other structures were not different across the groups following Bonferroni correction. Smaller amygdala volumes during early illness course may reflect pathophysiologic changes specific to illness development, including disrupted salience processing and acute stress responses.

Effects of reward on spatial working memory in schizophrenia.

Reward processing and cognition are disrupted in schizophrenia (SCZ), yet how these processes interface is unknown. In SCZ, deficits in reward representation may affect motivated, goal-directed behaviors. To test this, we examined the effects of monetary reward on spatial working memory (WM) performance in patients with SCZ. To capture complimentary effects, we tested biophysically grounded computational models of neuropharmacologic manipulations onto a canonical fronto-parietal association cortical microcircuit capable of WM computations. Patients with SCZ (n = 33) and healthy control subjects (HCS; n = 32) performed a spatial WM task with 2 reward manipulations: reward cues presented prior to each trial, or contextually prior to a block of trials. WM performance was compared with cortical circuit models of WM subjected to feed-forward glutamatergic excitation, feed-forward GABAergic inhibition, or recurrent modulation strengthening local connections. Results demonstrated that both groups improved WM performance to reward cues presented prior to each trial (HCS d = −0.62; SCZ d = −1.0), with percent improvement correlating with baseline WM performance (r = .472, p < .001). However, rewards presented contextually before a block of trials did not improve WM performance in patients with SCZ (d = 0.01). Modeling simulations achieved improved WM precision through strengthened local connections via neuromodulation, or feed-forward inhibition. Taken together, this work demonstrates that patients with SCZ can improve WM performance to short-term, but not longer-term rewards—thus, motivated behaviors may be limited by strength of reward representation. A potential mechanism for transiently improved WM performance may be strengthening of local fronto-parietal microcircuit connections via neuromodulation or feed-forward inhibitory drive.