Personalized estimates of morphometric similarity in bipolar disorder and schizophrenia.

Bipolar disorder and schizophrenia are associated with brain morphometry alterations. This study investigates inter-individual variability in brain structural profiles, both within diagnostic groups and between patients and healthy individuals. Brain morphometric measures from three independent samples of patients with schizophrenia (n = 168), bipolar disorder (n = 122), and healthy individuals (n = 180) were modeled as single vectors to generated individualized profiles of subcortical volumes and regional cortical thickness. These profiles were then used to compute a person-based similarity index (PBSI) for subcortical volumes and for regional cortical thickness, to quantify the within-group similarity of the morphometric profile of each individual to that of the other participants in the same diagnostic group. There was no effect of diagnosis on the PBSI for subcortical volumes. In contrast, compared to healthy individuals, the PBSI for cortical thickness was lower in patients with schizophrenia (effect size = 0.4, p ≤ 0.0002), but not in patients with bipolar disorder. The results were robust and reproducible across samples. We conclude that disease mechanisms for these disorders produce modest inter-individual variations in brain morphometry that should be considered in future studies attempting to cluster patients in subgroups.

Diminished neural network dynamics after moderate and severe traumatic brain injury.

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain's subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network "states" that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics.

Frequency-Specific Neural Signatures of Spontaneous Low-Frequency Resting State Fluctuations in Psychosis: Evidence From Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Consortium.

BACKGROUND: We quantified frequency-specific, absolute, and fractional amplitude of low-frequency fluctuations (ALFF/fALFF) across the schizophrenia (SZ)-psychotic bipolar disorder (PBP) psychosis spectrum using resting functional magnetic resonance imaging data from the large BSNIP family study. METHODS: We assessed 242 healthy controls (HC), 547 probands (180 PBP, 220 SZ, and 147 schizoaffective disorder-SAD), and 410 of their first-degree relatives (134 PBPR, 150SZR, and 126 SADR). Following standard preprocessing in statistical parametric mapping (SPM8), we computed absolute and fractional power (ALFF/fALFF) in 2 low-frequency bands: slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz). We evaluated voxelwise post hoc differences across traditional Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic categories. RESULTS: Across ALFF/fALFF, in contrast to HC, BP/SAD showed hypoactivation in frontal/anterior brain regions in the slow-5 band and hypoactivation in posterior brain regions in the slow-4 band. SZ showed consistent hypoactivation in precuneus/cuneus and posterior cingulate across both bands and indices. Increased ALFF/fALFF was noted predominantly in deep subcortical and temporal structures across probands in both bands and indices. Across probands, spatial ALFF/fALFF differences in SAD resembled PBP more than SZ. None of these ALFF/fALFF differences were detected in relatives. CONCLUSIONS: Results suggest ALFF/fALFF is a putative biomarker rather than a familial endophenotype. Overall sensitivity to discriminate proband brain alteration was stronger for fALFF than ALFF. Patterns of differences noted in SAD were more similar to those observed in PBP. Differential effects were noted across the 2 frequency bands, more prominently for BP/SAD compared with SZ, suggesting frequency-sensitive physiologic mechanisms for the former.

Visual hallucinations are associated with hyperconnectivity between the amygdala and visual cortex in people with a diagnosis of schizophrenia.

INTRODUCTION: While auditory verbal hallucinations (AH) are a cardinal symptom of schizophrenia, people with a diagnosis of schizophrenia (SZ) may also experience visual hallucinations (VH). In a retrospective analysis of a large sample of SZ and healthy controls (HC) studied as part of the functional magnetic resonance imaging (fMRI) Biomedical Informatics Research Network (FBIRN), we asked if SZ who endorsed experiencing VH during clinical interviews had greater connectivity between visual cortex and limbic structures than SZ who did not endorse experiencing VH. METHODS: We analyzed resting state fMRI data from 162 SZ and 178 age- and gender-matched HC. SZ were sorted into groups according to clinical ratings on AH and VH: SZ with VH (VH-SZ; n = 45), SZ with AH but no VH (AH-SZ; n = 50), and SZ with neither AH nor VH (NoH-SZ; n = 67). Our primary analysis was seed based, extracting connectivity between visual cortex and the amygdala (because of its role in fear and negative emotion) and visual cortex and the hippocampus (because of its role in memory). RESULTS: Compared with the other groups, VH-SZ showed hyperconnectivity between the amygdala and visual cortex, specifically BA18, with no differences in connectivity among the other groups. In a voxel-wise, whole brain analysis comparing VH-SZ with AH-SZ, the amygdala was hyperconnected to left temporal pole and inferior frontal gyrus in VH-SZ, likely due to their more severe thought broadcasting. CONCLUSIONS: VH-SZ have hyperconnectivity between subcortical areas subserving emotion and cortical areas subserving higher order visual processing, providing biological support for distressing VH in schizophrenia.

The rich get richer: brain injury elicits hyperconnectivity in core subnetworks.

There remains much unknown about how large-scale neural networks accommodate neurological disruption, such as moderate and severe traumatic brain injury (TBI). A primary goal in this study was to examine the alterations in network topology occurring during the first year of recovery following TBI. To do so we examined 21 individuals with moderate and severe TBI at 3 and 6 months after resolution of posttraumatic amnesia and 15 age- and education-matched healthy adults using functional MRI and graph theoretical analyses. There were two central hypotheses in this study: 1) physical disruption results in increased functional connectivity, or hyperconnectivity, and 2) hyperconnectivity occurs in regions typically observed to be the most highly connected cortical hubs, or the "rich club". The current findings generally support the hyperconnectivity hypothesis showing that during the first year of recovery after TBI, neural networks show increased connectivity, and this change is disproportionately represented in brain regions belonging to the brain's core subnetworks. The selective increases in connectivity observed here are consistent with the preferential attachment model underlying scale-free network development. This study is the largest of its kind and provides the unique opportunity to examine how neural systems adapt to significant neurological disruption during the first year after injury.

The impact of NMDA receptor blockade on human working memory-related prefrontal function and connectivity.

Preclinical research suggests that N-methyl-D-aspartate glutamate receptors (NMDA-Rs) have a crucial role in working memory (WM). In this study, we investigated the role of NMDA-Rs in the brain activation and connectivity that subserve WM. Because of its importance in WM, the lateral prefrontal cortex, particularly the dorsolateral prefrontal cortex and its connections, were the focus of analyses. Healthy participants (n=22) participated in a single functional magnetic resonance imaging session. They received saline and then the NMDA-R antagonist ketamine while performing a spatial WM task. Time-course analysis was used to compare lateral prefrontal activation during saline and ketamine administration. Seed-based functional connectivity analysis was used to compare dorsolateral prefrontal connectivity during the two conditions and global-based connectivity was used to test for laterality in these effects. Ketamine reduced accuracy on the spatial WM task and brain activation during the encoding and early maintenance (EEM) period of task trials. Decrements in task-related activation during EEM were related to performance deficits. Ketamine reduced connectivity in the DPFC network bilaterally, and region-specific reductions in connectivity were related to performance. These results support the hypothesis that NMDA-Rs are critical for WM. The knowledge gained may be helpful in understanding disorders that might involve glutamatergic deficits such as schizophrenia and developing better treatments.

Impairment of working memory maintenance and response in schizophrenia: functional magnetic resonance imaging evidence.

BACKGROUND: Comparing prefrontal cortical activity during particular phases of working memory in healthy subjects and individuals diagnosed with schizophrenia might help to define the phase-specific deficits in cortical function that contribute to cognitive impairments associated with schizophrenia. This study featured a spatial working memory task, similar to that used in nonhuman primates, that was designed to facilitate separating brain activation into encoding, maintenance, and response phases. METHODS: Fourteen patients with schizophrenia (4 medication-free) and 12 healthy comparison participants completed functional magnetic resonance imaging while performing a spatial working memory task with two levels of memory load. RESULTS: Task accuracy was similar in patients and healthy participants. However, patients showed reductions in brain activation during maintenance and response phases but not during the encoding phase. The reduced prefrontal activity during the maintenance phase of working memory was attributed to a greater rate of decay of prefrontal activity over time in patients. Cortical deficits in patients did not appear to be related to antipsychotic treatment. In patients and in healthy subjects, the time-dependent reduction in prefrontal activity during working memory maintenance correlated with poorer performance on the memory task. CONCLUSIONS: Overall, these data highlight that basic research insights into the distinct neurobiologies of the maintenance and response phases of working memory are of potential importance for understanding the neurobiology of cognitive impairment in schizophrenia and advancing its treatment.