John D. Murray

The role of default network deactivation in cognition and disease

A considerable body of evidence has accumulated over recent years on the functions of the default-mode network (DMN)--a set of brain regions whose activity is high when the mind is not engaged in specific behavioral tasks and low during focused attention on the external environment. In this review, we focus on DMN suppression and its functional role in health and disease, summarizing evidence that spans several disciplines, including cognitive neuroscience, pharmacological neuroimaging, clinical neuroscience, and theoretical neuroscience. Collectively, this research highlights the functional relevance of DMN suppression for goal-directed cognition, possibly by reducing goal-irrelevant functions supported by the DMN (e.g., mind-wandering), and illustrates the functional significance of DMN suppression deficits in severe mental illness.

Characterizing Thalamo-Cortical Disturbances in Schizophrenia and Bipolar Illness

Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness.

A hierarchy of intrinsic timescales across primate cortex

Specialization and hierarchy are organizing principles for primate cortex, yet there is little direct evidence for how cortical areas are specialized in the temporal domain. We measured timescales of intrinsic fluctuations in spiking activity across areas and found a hierarchical ordering, with sensory and prefrontal areas exhibiting shorter and longer timescales, respectively. On the basis of our findings, we suggest that intrinsic timescales reflect areal specialization for task-relevant computations over multiple temporal ranges.

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.

NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia

Glutamatergic neurotransmission mediated by N-methyl-d-aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain’s global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate’s role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

Linking Microcircuit Dysfunction to Cognitive Impairment: Effects of Disinhibition Associated with Schizophrenia in a Cortical Working Memory Model

Excitation-inhibition balance (E/I balance) is a fundamental property of cortical microcircuitry. Disruption of E/I balance in prefrontal cortex is hypothesized to underlie cognitive deficits observed in neuropsychiatric illnesses such as schizophrenia. To elucidate the link between these phenomena, we incorporated synaptic disinhibition, via N-methyl-D-aspartate receptor perturbation on interneurons, into a network model of spatial working memory (WM). At the neural level, disinhibition broadens the tuning of WM-related, stimulus-selective persistent activity patterns. The model predicts that this change at the neural level leads to 2 primary behavioral deficits: 1) increased behavioral variability that degrades the precision of stored information and 2) decreased ability to filter out distractors during WM maintenance. We specifically tested the main model prediction, broadened WM representation under disinhibition, using behavioral data from human subjects performing a spatial WM task combined with ketamine infusion, a pharmacological model of schizophrenia hypothesized to induce disinhibition. Ketamine increased errors in a pattern predicted by the model. Finally, as proof-of-principle, we demonstrate that WM deteriorations in the model can be ameliorated by compensations that restore E/I balance. Our findings identify specific ways by which cortical disinhibition affects WM, suggesting new experimental designs for probing the brain mechanisms of WM deficits in schizophrenia.

N-Methyl-D-Aspartate Receptor Antagonist Effects on Prefrontal Cortical Connectivity Better Model Early Than Chronic Schizophrenia

BACKGROUND Prefrontal cortex (PFC) function contributes to schizophrenia onset and progression. However, little is known about neural mechanisms behind PFC functional alterations along illness stages. Recent pharmacologic studies indicate that glutamate dysfunction may produce increased functional connectivity. However, pharmacologic models of schizophrenia overlook effects of illness progression on PFC function. This study compared N-methyl-D-aspartate glutamate receptor (NMDAR) antagonist effects in healthy volunteers with stages of schizophrenia with respect to PFC functional connectivity. METHODS First, we tested ketamine effects on PFC functional connectivity in healthy volunteers in a data-driven way (n = 19). Next, we compared healthy subjects (n = 96) with three clinical groups: individuals at high risk for schizophrenia (n = 21), people early in their course of schizophrenia (EC-SCZ) (n = 28), and patients with chronic illness (n = 20). Across independent analyses, we used data-driven global brain connectivity techniques restricted to PFC to identify functional dysconnectivity. RESULTS Results revealed robust PFC hyperconnectivity in healthy volunteers administered ketamine (Cohens d = 1.46), resembling individuals at high risk for schizophrenia and EC-SCZ. Hyperconnectivity was not found in patients with chronic illness relative to EC-SCZ patients. Results provide the first evidence that ketamine effects on PFC functional connectivity resemble early course but not chronic schizophrenia. CONCLUSIONS Results suggest an illness phase-specific relevance of NMDAR antagonist administration for prefrontal dysconnectivity associated with schizophrenia. This finding has implications for the neurobiology of illness progression and for the widespread use of NMDAR antagonists in the development of therapeutics for 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.

NUTRIENT PATTERNS AND BRAIN BIOMARKERS OF ALZHEIMER’S DISEASE IN COGNITIVELY NORMAL INDIVIDUALS

ObjectivesEpidemiological evidence linking diet, one of the most important modifiable lifestyle factors, and risk of Alzheimer’s disease (AD) is rapidly increasing. However, there is little or no evidence for a direct association between dietary nutrients and brain biomarkers of AD. This study identifies nutrient patterns associated with major brain AD biomarkers in a cohort of clinically and cognitively normal (NL) individuals at risk for AD.DesignCross-sectional study.SettingManhattan (broader area).ParticipantsFifty-two NL individuals (age 54+12 y, 70% women, Clinical Dementia Rating=0, MMSE>27, neuropsychological test performance within norms by age and education) with complete dietary information and cross-sectional, 3D T1-weighted Magnetic Resonance Imaging (MRI; gray matter volumes, GMV, a marker of brain atrophy), 11CPittsburgh compound-B (PiB; a marker of fibrillar amyloid-β, Aβ) and 18F-fluorodeoxyglucose (FDG; a marker of glucose metabolism, METglc) Positron Emission Tomography (PET) scans were examined.MeasurementsDietary intake of 35 nutrients associated with cognitive function and AD was assessed using the Harvard/Willet Food Frequency Questionnaire. Principal component analysis was used to generate nutrient patterns (NP) from the full nutrient panel. Statistical parametric mapping and voxel based morphometry were used to assess the associations of the identified NPs with AD biomarkers.ResultsNone of the participants were diabetics, smokers, or met criteria for obesity. Five NPs were identified: NP1 was characterized by most B-vitamins and several minerals [VitB&Minerals]; NP2 by monounsaturated and polyunsaturated fats, including ω-3 and ω-6 PUFA, and vitamin E [VitE&PUFA]; NP3 by vitamin A, vitamin C, carotenoids and dietary fibers [Antioxidants&Fibers]; NP4 by vitamin B12, vitamin D and zinc [VitB12&D]; NP5 by saturated, trans-saturated fats, cholesterol and sodium [Fats]. Voxel-based analysis showed that NP4 scores [VitB12&D] were positively associated with METglc and GMV, and negatively associated with PiB retention in AD-vulnerable regions (p<0.001). In addition, both METglc and GMV were positively associated with NP2 scores [VitE&PUFA], and negatively associated with NP5 scores [Fats] (p<0.001), and METglc was positively associated with higher NP3 scores [Anti-oxidants&Fibers] (p<0.001). Adjusting for age, gender, ethnicity, education, caloric intake, BMI, alcohol consumption, family history and Apolipoprotein E (APOE) status did not attenuate these relationships. The identified ‘AD-protective’ nutrient combination was associated with higher intake of fresh fruit and vegetables, whole grains, fish and low-fat dairies, and lower intake of sweets, fried potatoes, high-fat dairies, processed meat and butter.ConclusionSpecific dietary NPs are associated with brain biomarkers of AD in NL individuals, suggesting that dietary interventions may play a role in the prevention of AD by modulating AD-risk through its effects on Aβ and associated neuronal impairment.

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.