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Background Converging lines of evidence point to hippocampal dysfunction in psychosis spectrum disorders, including altered functional connectivity. Evidence also suggests that antipsychotic medications can modulate hippocampal dysfunction. The goal of this project was to identify patterns of hippocampal connectivity predictive of response to antipsychotic treatment in 2 cohorts of patients with a psychosis spectrum disorder, one medication-naïve and the other one unmedicated. Hypothesis We hypothesized that we would identify reliable patterns of hippocampal connectivity in the 2 cohorts that were predictive of treatment response and that medications would modulate abnormal hippocampal connectivity after 6 weeks of treatment. Study Design We used a prospective design to collect resting-state fMRI scans prior to antipsychotic treatment and after 6 weeks of treatment with risperidone, a commonly used antipsychotic medication, in both cohorts. We enrolled 44 medication-naïve first-episode psychosis patients (FEP) and 39 unmedicated patients with schizophrenia (SZ). Study Results In both patient cohorts, we observed a similar pattern where greater hippocampal connectivity to regions of the occipital cortex was predictive of treatment response. Lower hippocampal connectivity of the frontal pole, orbitofrontal cortex, subcallosal area, and medial prefrontal cortex was predictive of treatment response in unmedicated SZ, but not in the medication-naïve cohort. Furthermore, greater reduction in hippocampal connectivity to the visual cortex with treatment was associated with better clinical response. Conclusions Our results suggest that greater connectivity between the hippocampus and occipital cortex is not only predictive of better treatment response, but that antipsychotic medications have a modulatory effect by reducing hyperconnectivity.

Background The deficit syndrome is a clinical subtype of schizophrenia that is characterized by enduring negative symptoms. Several lines of evidence point to frontoparietal involvement, but the frontoparietal control network (FPCN) and its subsystems (FPCNA and FPCNB) proposed by Yeo et al. have not been systematically characterized at rest in patients with the deficit syndrome. Methods We used resting-state fMRI to investigate the FPCN and its subnetworks in 72 healthy controls and 65 antipsychotic medication-naive, first-episode psychosis patients (22 displayed deficit syndrome features, 43 did not). To assess whole-brain FPCN connectivity, we used the right posterior parietal cortex as the seed region. We then performed region of interest analyses in FPCN subsystems. Results We found that patterns of FPCN dysconnectivity to the whole brain differed in patients who displayed deficit syndrome features compared with those who did not. Examining the FPCN on a more granular level revealed reduced within-FPCN(A) connectivity only in patients displaying deficit features. FPCNB connectivity did not differ between patient groups. Discussion Here, we describe a neurobiological signature of aberrant FPCN connectivity in antipsychotic-naive, first-episode patients who display clinical features of the deficit syndrome. Importantly, frontoparietal subnetwork connectivity differentiated subgroups, where the FPCNA is selectively involved in patients with deficit features. Our findings add to the growing body of literature supporting a neurobiological distinction between two clinical subtypes of schizophrenia, which has the potential to be leveraged for patient stratification in clinical trials and the development of novel treatments.

Background Converging lines of evidence point to hippocampal dysfunction in schizophrenia. It is thought that hippocampal dysfunction spreads across hippocampal subfields and to cortical regions by way of long-range efferent projections. Importantly, abnormalities in the excitation/inhibition balance could impair the long-range modulation of neural networks. The goal of this project was twofold. First, we sought to identify replicable patterns of hippocampal dysconnectivity in patients with a psychosis spectrum disorder. Second, we aimed to investigate a putative link between glutamatergic metabolism and hippocampal connectivity alterations. Methods We evaluated resting-state hippocampal functional connectivity alterations in two cohorts of patients with a psychosis spectrum disorder. The first cohort consisted of 55 medication-naive patients with first-episode psychosis and 41 matched healthy control subjects, and the second cohort consisted of 42 unmedicated patients with schizophrenia and 41 matched control subjects. We also acquired measurements of glutamate + glutamine in the left hippocampus using magnetic resonance spectroscopy for 42 patients with first-episode psychosis and 37 healthy control subjects from our first cohort. Results We observed a pattern of hippocampal functional hypoconnectivity to regions of the default mode network and hyperconnectivity to the lateral occipital cortex in both cohorts. We also show that in healthy control subjects, greater hippocampal glutamate + glutamine levels predicted greater hippocampal functional connectivity to the anterior default mode network. Furthermore, this relationship was reversed in medication-naive subjects with first-episode psychosis. Conclusions These results suggest that an alteration in the relationship between glutamate and functional connectivity may disrupt the dynamic of major neural networks.

ObjectiveThe aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.MethodsA systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.ResultsA total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."ConclusionsThere is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Prior studies indicate that chronic schizophrenia (SZ) is associated with a specific profile of reinforcement learning abnormalities. These impairments are characterized by: 1) reductions in learning rate, and 2) impaired Go learning and intact NoGo learning. Furthermore, each of these deficits are associated with greater severity of negative symptoms, consistent with theoretical perspectives positing that avolition and anhedonia are associated with impaired value representation. However, it is unclear whether these deficits extend to earlier phases of psychotic illness and when individuals are unmedicated. Two studies were conducted to examine reinforcement learning deficits in earlier phases of psychosis and in high risk patients. In study 1, participants included 35 participants with first episode psychosis (FEP) with limited antipsychotic medication exposure and 25 healthy controls (HC). Study 2 included 17 antipsychotic naïve individuals who were at clinical high-risk for psychosis (CHR) (i.e., attenuated psychosis syndrome) and 18 matched healthy controls (HC). In both studies, participants completed the Temporal Utility Integration Task, a measure of probabilistic reinforcement learning that contained Go and NoGo learning blocks. FEP displayed impaired Go and NoGo learning. In contrast, CHR did not display impairments in Go or NoGo learning. Impaired Go learning was not significantly associated with clinical outcomes in the CHR or FEP samples. Findings provide new evidence for areas of spared and impaired reinforcement learning in early phases of psychosis.

The deficit syndrome is thought to be a more homogenous clinical subgroup within the syndrome of schizophrenia that is characterized by enduring negative symptoms. It is hypothesized that distinct pathophysiological processes underlie the subtypes, where the deficit syndrome reflects an early onset nonprogressive developmental process, and the nondeficit form of the illness is characterized by attenuated neuroplasticity secondary to elevated glutamate levels. We used single-voxel magnetic resonance spectroscopy (PRESS; TE: 30 ms) to measure left frontal white matter neurometabolite levels in 61 antipsychotic-naïve first-episode psychosis patients (39 who did not display deficit features, 22 who did display deficit features, assessed with the Schedule for the Deficit Syndrome) and 59 healthy controls. Metabolite levels were quantified with the LCModel. We used a MANCOVA to determine neurometabolite differences between healthy controls, deficit syndrome patients, and nondeficit patients. We report a significant group difference when all metabolites were considered jointly (F[10,208] = 2.16; P = .02). Post hoc analyses showed that patients presenting without deficit features had higher glutamate levels than patients with deficit features and controls. Patients presenting without deficit features also had significantly higher myoinositol levels than controls; myoinositol levels were trend-level higher in patients presenting with deficit features compared to controls. Our data support the idea that the pathophysiology of patients presenting without deficit features may differ from those presenting with deficit features.

Objective To further evaluate the relationship between the clinical profiles and limbic and motor brain regions and their connecting pathways in psychogenic nonepileptic seizures (PNES). Neurite Orientation Dispersion and Density Indices (NODDI) multicompartment modeling was used to test the relationships between tissue alterations in patients with traumatic brain injury (TBI) and multiple psychiatric symptoms. Methods The sample included participants with prior TBI (TBI; N = 37) but no PNES, and with TBI and PNES (TBI + PNES; N = 34). Participants completed 3T Siemens Prisma MRI high angular resolution imaging diffusion protocol. Statistical maps, including fractional anisotropy (FA), mean diffusivity (MD), neurite dispersion [orientation dispersion index (ODI)] and density [intracellular volume fraction (ICVF), and free water (i.e., isotropic) volume fraction (V‐ISO)] signal intensity, were generated for each participant. Linear mixed‐effects models identified clusters of between‐group differences in indices of white matter changes. Pearson’s r correlation tests assessed any relationship between signal intensity and psychiatric symptoms. Results Compared to TBI, TBI + PNES revealed decreases in FA, ICVF, and V‐ISO and increases in MD for clusters within cingulum bundle, uncinate fasciculus, fornix/stria terminalis, and corticospinal tract pathways (cluster threshold α = 0.05). Indices of white matter changes for these clusters correlated with depressive, anxiety, PTSD, psychoticism, and somatization symptom severity (FDR threshold α = 0.05). A follow‐up within‐group analysis revealed that these correlations failed to reach the criteria for significance in the TBI + PNES group alone. Interpretation The results expand support for the hypothesis that alterations in pathways comprising the specific PNES network correspond to patient profiles. These findings implicate myelin‐specific changes as possible contributors to PNES, thus introducing novel potential treatment targets.

Psychotic disorders are disabling clinical syndromes characterized by widespread alterations in cortical information processing. Disruption of frontoparietal network (FPN) connectivity has emerged as a common footprint across the psychosis spectrum. Our goal was to characterize the static and dynamic resting‐state functional connectivity (FC) of the FPN in antipsychotic‐naïve first‐episode psychosis (FEP) subjects. We compared the static FC of the FPN in 40 FEP and 40 healthy control (HC) subjects, matched on age, sex, and socioeconomic status. To study the dynamic FC, we measured quasiperiodic patterns (QPPs) that consist of infraslow spatioemporal patterns embedded in the blood oxygen level‐dependent signal that repeats over time, exhibiting alternation of high and low activity. Relative to HC, we found functional hypoconnectivity between the right middle frontal gyrus and the right middle temporal gyrus, as well as the left inferior temporal gyrus and the left inferior parietal gyrus in FEP (p

It is becoming increasingly clear that longer duration of untreated psychosis (DUP) is associated with adverse clinical outcomes in patients with psychosis spectrum disorders. Because this association is often cited when justifying early intervention efforts, it is imperative to better understand underlying biological mechanisms. We enrolled 66 antipsychotic-naïve first episode psychosis (FEP) patients and 45 matched healthy controls in this trial. At baseline, we used a human connectome style diffusion weighted imaging (DWI) sequence to quantify white matter integrity in both groups. Patients then received 16 weeks of treatment with risperidone, 51 FEP completed the trial. We compared whole brain fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD) and radial diffusivity between groups. To test if structural white matter integrity mediates the relationship between longer DUP and poorer treatment response, we fit a mediator model and estimated indirect effects. We found decreased whole brain FA and AD in medication-naive FEP compared to controls. In patients, lower FA was correlated with longer DUP (r= −0.32; p= 0.03) and poorer subsequent response to antipsychotic treatment (r= 0.40; p= 0.01). Importantly, we found a significant mediation effect for FA (indirect effect: −2.70; p= 0.03), indicating that DUP exerts its effects on treatment response through affecting white matter integrity. Our data provide empirical support to the idea the DUP may have fundamental pathogenic effects on the natural history of psychosis, suggest a biological mechanism underlying this phenomenon, and underscore the importance of early intervention efforts in this disabling neuropsychiatric syndrome. Trial registration: ClinicalTrials.gov: NCT02034253

There is no pharmacological treatment to remediate cognitive impairment in schizophrenia (SZ). It is imperative to characterize underlying pathologies of memory processing in order to effectively develop new treatments. In this longitudinal study, we combined functional magnetic resonance imaging during a memory encoding task with proton MR spectroscopy to measure hippocampal glutamate + glutamine (Glx). Seventeen SZ were scanned while unmedicated and after 6 weeks of treatment with risperidone and compared to a group of matched healthy controls (HC) scanned 6 weeks apart. Unmedicated patients showed reduced blood oxygen level dependent (BOLD) response in several regions, including the hippocampus, and greater BOLD response in regions of the default mode network (DMN) during correct memory encoding. Post hoc contrasts from significant group by time interactions indicated reduced hippocampal BOLD response at baseline with subsequent increase following treatment. Hippocampal Glx was not different between groups at baseline, but at week 6, hippocampal Glx was significantly lower in SZ compared to HC. Finally, in unmedicated SZ, higher hippocampal Glx predicted less deactivation of the BOLD response in regions of the DMN. Using 2 brain imaging modalities allowed us to concurrently investigate different mechanisms involved in memory encoding dysfunction in SZ. Hippocampal pathology during memory encoding stems from decreased hippocampal recruitment and faulty deactivation of the DMN, and hippocampal recruitment during encoding can be modulated by antipsychotic treatment. High Glx in unmedicated patients predicted less deactivation of the DMN; these results suggest a mechanism by which faulty DMN deactivation, a hallmark of pathological findings in SZ, is achieved.

Data on COVID-19 supports targeted social distancing could be an effective way to reduce morbidity and mortality, but could inadvertently increase stigma for affected populations. As health care providers we must be aware of the facts of COVID-19, cultural implications, and potential for stigmatization of populations affected by COVID-2019. It is important to consider the real economic impact related to lost workdays due to quarantine and social isolation efforts as well as travel restrictions that may negatively impact access to care and ability to pay for care. Efforts geared towards general education about the disease and the rationale for quarantine and public health information provided to the general public can reduce stigmatization. Countries who are successful at aggressive screening, early identification, patient isolation, contact tracing, quarantine, and infection control methods should also address the risk of stigmatization among populations and the negative effects which could occur. The cases of COVID-19 will continue to rise and the virus will be sustainable for future infections. Timely and appropriate public health interventions addressing cultural impact and risk for stigmatization along with proper screening, treatment, and follow up for affected individuals and close contacts can reduce the number of infections, serious illness, and deaths.

Neurological soft signs (NSS) are common in patients with schizophrenia. However, the neural substrates of NSS remain poorly understood. Using legacy PubMed, we performed a systematic review and included studies that assessed NSS and obtained neuroimaging data in patients with a schizophrenia spectrum disorder published up to June 2020. We systematically reviewed 35 relevant articles. Studies consistently implicate the basal ganglia and cerebellum as structural substrates of NSS and suggest that somatomotor and somatosensory regions as well as areas involved in visual processing and spatial orientation may underlie NSS in psychosis spectrum disorders. Additionally, dysfunction of frontoparietal and cerebellar networks has been implicated in the pathophysiology of NSS. The current literature outlines several structural and functional brain signatures that are relevant for NSS in schizophrenia spectrum disorder. The majority of studies assessed gray matter structure, but only a few studies leveraged other imaging methods such as diffusion weighted imaging, or molecular imaging. Due to this, it remains unclear if white matter integrity deficits or neurometabolic alterations contribute to NSS in the illness. While a substantial portion of the literature has been conducted in patients in the early illness stages, mitigating confounds of illness chronicity, few studies have been conducted in antipsychotic medication-naïve patients, which is a clear limitation. Furthermore, only little is known about the temporal evolution of NSS and associated brain signatures. Future studies addressing these pivotal gaps in our mechanistic understanding of NSS will be important.

The dorsal striatum, comprised of the caudate and putamen, is implicated in the pathophysiology of psychosis spectrum disorders. Given the high concentration of dopamine receptors in the striatum, striatal dopamine imbalance is a likely cause in cortico-striatal dysconnectivity. There is great interest in understanding the relationship between striatal abnormalities in psychosis and antipsychotic treatment response, but few studies have considered differential involvement of the caudate and putamen. This study's goals were twofold. First, identify patterns of dorsal striatal dysconnectivity for the caudate and putamen separately in patients with a psychosis spectrum disorder; second, determine if these dysconnectivity patterns were predictive of treatment response.Using resting state functional connectivity, we evaluated dorsal striatal connectivity using separate bilateral caudate and putamen seed regions in two cohorts of subjects: a cohort of 71 medication-naïve first episode psychosis patients and a cohort of 42 unmedicated patients with schizophrenia (along with matched controls). Patient and control connectivity maps were contrasted for each cohort. After receiving 6 weeks of risperidone treatment, patients' clinical response was calculated. We used regression analyses to determine the relationship between baseline dysconnectivity and treatment response.This dysconnectivity was also predictive of treatment response in both cohorts.These findings suggest that the caudate may be more of a driving factor than the putamen in early cortico-striatal dysconnectivity.

Background: Cortical thickness (CT) and gyrification are complementary indices that assess different aspects of gray matter structural integrity. Both neurodevelopment insults and acute tissue response to antipsychotic medication could underlie the known heterogeneity of treatment response and are well-suited for interrogation into the relationship between gray matter morphometry and clinical outcomes in schizophrenia (SZ). Methods: Using a prospective design, we enrolled 34 unmedicated patients with SZ and 23 healthy controls. Patients were scanned at baseline and after a 6-week trial with risperidone. CT and local gyrification index (LGI) values were quantified from structural MRI scans using FreeSurfer 5.3. Results: We found reduced CT and LGI in patients compared to controls. Vertex-wise analyses demonstrated that hypogyrification was most prominent in the inferior frontal cortex, temporal cortex, insula, pre/postcentral gyri, temporoparietal junction, and the supramarginal gyrus. Baseline CT was predictive of subsequent response to antipsychotic treatment, and increase in CT after 6 weeks was correlated with greater symptom reductions. Conclusions: In summary, we report evidence of reduced CT and LGI in unmedicated patients compared to controls, suggesting involvement of different aspects of gray matter morphometry in the pathophysiology of SZ. Importantly, we found that lower CT at baseline and greater increase of CT following 6 weeks of treatment with risperidone were associated with better clinical response. Our results suggest that cortical thinning may normalize as a result of a good response to antipsychotic medication, possibly by alleviating potential neurotoxic processes underlying gray matter deterioration.

Background In the United States, the average duration of untreated psychosis (DUP) is 21 months, and it remains unknown how longer DUP may affect brain functioning in antipsychotic-naive patients with first-episode psychosis. The objective was to determine the effects of DUP on functional connectivity and brain morphology measured with resting-state functional and structural magnetic resonance imaging. Methods Medication-naive patients with first-episode psychosis were referred from various clinical settings. After accounting for exclusion criteria, attrition, and data quality, final analyses included 55 patients (35 male and 20 female; mean age, 24.18 years). Patients with first-episode psychosis were subjected to a 16-week trial of risperidone, a commonly used antipsychotic drug. Treatment response was calculated as change in the psychosis subscale of the Brief Psychiatric Rating Scale between baseline and 16 weeks. Resting-state functional connectivity magnetic resonance imaging and brain morphology (surface area and cortical thickness) were assessed. Results Longer DUP was associated with worse treatment response and reduced functional connectivity—more specifically in the default, salience, and executive networks. Moreover, longer DUP was associated with reduced surface area in the salience and executive networks and with increased cortical thickness in the default mode and salience networks. When the functional connectivity of the default mode network was added as a mediator, the relationship between DUP and treatment response was no longer significant. Conclusions These data suggest that several neurobiological alterations in the form of reduced functional connectivity and surface area and increased cortical thickness underpin the effect of prolonged DUP.

Antipsychotic medications are the cornerstone of treatment in schizophrenia spectrum disorders. In first-episode psychosis, the recommended time for an antipsychotic medication trial is up to 16 weeks, but the biological correlates of shorter and longer antipsychotic treatment trials in these cohorts remain largely unknown. We enrolled 29 medication-naive first-episode patients (FEP) and 22 matched healthy controls (HC) in this magnetic resonance spectroscopy (MRS) study, examining the levels of combined glutamate and glutamine (commonly referred to as Glx) in the bilateral medial prefrontal cortex (MPFC) with a PRESS sequence (TR/TE = 2000/80 ms) before initiation of antipsychotic treatment, after 6 and 16 weeks of treatment with risperidone. Data were quantified in 18 HC and 20 FEP at baseline, for 19 HC and 15 FEP at week 6, and for 14 HC and 16 FEP at week 16. At baseline, none of the metabolites differed between groups. Metabolite levels did not change after 6 or 16 weeks of treatment in patients. Our data suggest that metabolite levels do not change after 6 or 16 weeks of treatment with risperidone in FEP. It is possible that our choice of sequence parameters and the limited sample size contributed to negative findings reported here. On the other hand, longer follow-up may be needed to detect treatment-related metabolic changes with MRS. In summary, our study adds to the efforts in better understanding glutamatergic neurometabolism in schizophrenia, especially as it relates to antipsychotic exposure.

Several imaging studies have attempted to characterize the contribution of glutamatergic dysfunction to functional dysconnectivity of large-scale brain networks using ketamine models. However, findings from BOLD imaging studies are conflicting, in part because the signal stems from a complex interaction between blood flow, blood volume, and oxygen consumption. We used arterial spin labelling imaging to measure regional cerebral blood flow (rCBF) in a group of healthy volunteers during a saline and during a ketamine infusion. We examined changes in rCBF and interregional connectivity patterns, as well as their associations with clinical symptom severity and Glx (glutamate + glutamine) assessed with magnetic resonance spectroscopy. We report a regionally selective pattern of rCBF changes following ketamine administration and complex changes in interregional connectivity patterns. We also found that the increase in rCBF in the bilateral putamen and left hippocampus was positively correlated with ketamine induced clinical symptom severity while anterior cingulate rCBF during the ketamine challenge was negatively correlated with change in hippocampal Glx. Our study adds to the efforts to empirically confirm putative links between an NMDA receptor blockage and dysconnectivity of large-scale brain networks, specifically the salience, executive control and default mode networks, suggesting that a glutamatergic imbalance may contribute to dysconnectivity. Development of glutamatergic compounds that alleviate disease burden, possibly through normalizing glutamate excess related increased rCBF, is direly needed.

Magnetic Resonance Spectroscopy is a popular approach to probe brain chemistry in schizophrenia (SZ), but no consensus exists as to the extent of alterations. This may be attributable to differential effects of populations studied, brain regions examined, or antipsychotic medication effects. Here, we measured neurometabolites in the anterior cingulate cortex (ACC) and hippocampus, two structurally dissimilar brain regions implicated in the SZ pathophysiology. We enrolled 61 SZ with the goal to scan them before and after six weeks of treatment with risperidone. We also scanned 31 matched healthy controls twice, six weeks apart. Using mixed effect repeated measures linear models to examine the effect of group and time on metabolite levels in each voxel, we report an increase in hippocampal glutamate + glutamine (Glx) in SZ compared to controls (p = 0.043), but no effect of antipsychotic medication (p = 0.330). In the ACC, we did not find metabolite alterations or antipsychotic medication related changes after six weeks of treatment with risperidone. The coefficients for the discriminant function (differentiating SZ from HC) in the ACC were greatest for NAA (−0.83), and in the hippocampus for Glx (0.76), the same metabolites were associated with greater treatment response in patients at trend level. Taken together, our data extends the existing literature by demonstrating regionally distinct metabolite alterations in the same patient group and suggests that antipsychotic medications may have limited effects on metabolite levels in these regions.

Diffusion tensor imaging (DTI) studies show widespread white matter abnormalities in schizophrenia, but it is difficult to directly relate these parameters to biological processes. Neurite orientation dispersion and density imaging (NODDI) is geared toward biophysical characterization of white matter microstructure, but only few studies have leveraged this technique to study white matter alterations. We recruited 42 schizophrenia patients (30 antipsychotic-naïve and 12 currently untreated) and 42 matched controls in this prospective study. We assessed the orientation dispersion index (ODI) and extracellular free water (FW) using single-shell DTI data before and after a 6-week trial of risperidone. Longitudinal data were available for 27 patients. Voxelwise analyses showed significantly increased ODI in the posterior limb of the internal capsule in unmedicated patients (242 voxels; x = −24; y = 6; z = 6; p

Schizophrenia is associated with progressive white matter changes, but it is unclear whether antipsychotic medications contribute to these. Our objective was to characterize effects of short-term treatment with risperidone on white matter diffusion indices.We recruited 42 patients with schizophrenia (30 never treated and 12 currently untreated) and 42 matched healthy control subjects in this prospective case-control neuroimaging study. Patients received a 6-week trial of risperidone. Using diffusion tensor imaging, we assessed microstructural (fractional anisotropy, mean diffusivity, and radial diffusivity) and macrostructural (radial fiber trophy) white matter integrity deficits in unmedicated patients compared with control subjects and change in white matter integrity in patients before and after antipsychotic treatment (mean risperidone dose at end point was 3.73 ± 1.72 mg).At baseline, fractional anisotropy was decreased in the left medial temporal white matter (cluster extent: 123 voxels; Montreal Neurological Institute peak coordinates: x = -51, y = -44, z = -7; α.05), and mean diffusivity was increased in the fusiform/lingual gyrus white matter extending to the hippocampal part of the cingulum (cluster extent: 185 voxels; peak coordinates: x = -27, y = -49, z = 2; α.04) in patients compared with control subjects. Radial diffusivity and macrostructure were not abnormal. None of the diffusion indices showed a significant change after 6 weeks of treatment with both voxelwise and whole-brain white matter analyses.We demonstrate microstructural white matter integrity abnormalities in the absence of macrostructural impairment in unmedicated patients with primarily early-stage schizophrenia. In our data, we found no significant white matter changes after short-term treatment with risperidone.

Background: The major excitatory and inhibitory neurometabolites in the brain, glutamate and γ-aminobutyric acid (GABA), respectively, are related to the functional MRI signal. Disruption of resting-state functional MRI signals has been reported in psychosis spectrum disorders, but few studies have investigated the role of these metabolites in this context. Methods: We included 19 patients with first-episode psychosis and 21 healthy controls in this combined magnetic resonance spectroscopy (MRS) and resting-state functional connectivity study. All imaging was performed on a Siemens Magnetom 7 T MRI scanner. Both the MRS voxel and the seed for functional connectivity analysis were located in the dorsal anterior cingulate cortex (ACC). We used multiple regressions to test for an interaction between ACC brain connectivity, diagnosis and neurometabolites. Results: ACC brain connectivity was altered in first-episode psychosis. The relationship between ACC glutamate and ACC functional connectivity differed between patients with first-episode psychosis and healthy controls in the precuneus, retrosplenial cortex, supramarginal gyrus and angular gyrus. As well, the relationship between ACC GABA and ACC functional connectivity differed between groups in the caudate, putamen and supramarginal gyrus. Limitations: We used a small sample size. As well, although they were not chronically medicated, all participants were medicated during the study. Conclusion: We demonstrated a link between the major excitatory and inhibitory brain metabolites and resting-state functional connectivity in healthy participants, as well as an alteration in this relationship in patients with first-episode psychosis. Combining data from different imaging modalities may help our mechanistic understanding of the relationship between major neurometabolites and brain network dynamics, and shed light on the pathophysiology of first-episode psychosis.

“Mr. A,” a 24-year-old man, presents for evaluation of worsening depression. He describes a history of depression since adolescence, although he notes that he suffered a troubled childhood, includi...

Neurological soft signs (NSS) are common in patients with schizophrenia. However, the neural substrates of NSS remain poorly understood. Using legacy PubMed, we performed a systematic review and included studies that assessed NSS and obtained neuroimaging data in patients with a schizophrenia spectrum disorder published up to June 2020. We systematically reviewed 35 relevant articles. Studies consistently implicate the basal ganglia and cerebellum as structural substrates of NSS and suggest that somatomotor and somatosensory regions as well as areas involved in visual processing and spatial orientation may underlie NSS in psychosis spectrum disorders. Additionally, dysfunction of frontoparietal and cerebellar networks has been implicated in the pathophysiology of NSS. The current literature outlines several structural and functional brain signatures that are relevant for NSS in schizophrenia spectrum disorder. The majority of studies assessed gray matter structure, but only a few studies leveraged other imaging methods such as diffusion weighted imaging, or molecular imaging. Due to this, it remains unclear if white matter integrity deficits or neurometabolic alterations contribute to NSS in the illness. While a substantial portion of the literature has been conducted in patients in the early illness stages, mitigating confounds of illness chronicity, few studies have been conducted in antipsychotic medication-naïve patients, which is a clear limitation. Furthermore, only little is known about the temporal evolution of NSS and associated brain signatures. Future studies addressing these pivotal gaps in our mechanistic understanding of NSS will be important.

Background Diffusion tensor imaging suggests that white matter alterations are already evident in first episode psychosis patients (FEP) and may become more prominent as the duration of untreated psychosis (DUP) increases. But because the tensor model lacks specificity, it remains unclear how to interpret findings on a biological level. Here, we used a biophysical diffusion model, Neurite Orientation Dispersion and Density Imaging (NODDI), to map microarchitecture in FEP, and to investigate associations between DUP and microarchitectural integrity. Methods We scanned 78 antipsychotic medication-naive FEP and 64 healthy controls using a multi-shell diffusion weighted sequence and used the NODDI toolbox to compute neurite density (ND), orientation dispersion index (ODI) and extracellular free water (FW) maps. AFNI’s 3dttest++ was used to compare diffusion maps between groups and to perform regression analyses with DUP. Results We found that ND was decreased in commissural and association fibers but increased in projection fibers in FEP. ODI was largely increased regardless of fiber type, and FW showed a mix of increase in decrease across fiber tracts. We also demonstrated associations between DUP and microarchitecture for all NODDI indices. Conclusions We demonstrated that complex microarchitecture abnormalities are already evident in antipsychotic-naive FEP. ND alterations are differentially expressed depending on fiber type, while decreased fiber complexity appears to be a uniform marker of white matter deficit in the illness. Importantly, we identified an empirical link between longer DUP and greater white matter pathology across NODDI indices, underscoring the critical importance of early intervention in this devastating illness.

Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.

Introduction Only a few studies have comprehensively characterized default mode network (DMN) pathology on a structural and functional level, and definite conclusions cannot be drawn due to antipsychotic medication exposure and illness chronicity. The objective of this study was to characterize DMN pathology in medication-naïve first episode psychosis (FEP) patients, and determine if DMN structural and functional connectivity (FC) have potential utility as a predictor for subsequent antipsychotic treatment response. Methods Diffusion imaging and resting state FC data from 42 controls and 52 FEP were analyzed. Patients then received 16 weeks of antipsychotic treatment. Using region of interest analyses, we quantified FC of the DMN and structural integrity of the white matter tracts supporting DMN function. We then did linear regressions between DMN structural and FC indices and antipsychotic treatment response. Results We detected reduced DMN fractional anisotropy and axial diffusivity in FEP compared to controls. No DMN FC abnormalities nor correlations between DMN structural and FC were found. Finally, DMN fractional anisotropy and radial diffusivity were associated with response to treatment. Conclusion Our study highlights the critical role of the DMN in the pathophysiology suggesting that axonal damage may already be present in FEP patients. We also demonstrated that DMN pathology is clinically relevant, as greater structural DMN alterations were associated with a less favorable clinical response to antipsychotic medications.

Highlights • The pathophysiology of salience network in schizophrenia remains poorly understood. • We found reduced connectivity, but no Glx alterations in psychosis patients. • The relationship between Glx and connectivity was abnormal in psychosis patients. • Findings suggest altered glutamatergic neurometabolism and connectivity in psychosis., Background Salience network (SN) connectivity is altered in schizophrenia, but the pathophysiological origin remains poorly understood. The goal of this multimodal neuroimaging study was to investigate the role of glutamatergic metabolism as putative mechanism underlying SN dysconnectivity in first episode psychosis (FEP) subjects. Methods We measured glutamate + glutamine (Glx) in the dorsal anterior cingulate cortex (dACC) from 70 antipsychotic-naïve FEP subjects and 52 healthy controls (HC). The dACC was then used as seed to define positive and negative resting state functional connectivity (FC) of the SN. We used multiple regression analyses to test main effects and group interactions of Glx and FC associations. Results dACC Glx levels did not differ between groups. Positive FC was significantly reduced in FEP compared to HC, and no group differences were found in negative FC. Group interactions of Glx-FC associations were found within the SN for positive FC, and in parietal cortices for negative FC. In HC, higher Glx levels predicted greater positive FC in the dACC and insula, and greater negative FC of the lateral parietal cortex. These relationships were weaker or absent in FEP. Conclusions Here, we found that positive FC in the SN is already altered in medication-naïve FEP, underscoring the importance of considering both correlations and anticorrelations for characterization of pathology. Our data demonstrate that Glx and functional connectivity work differently in FEP than in HC, pointing to a possible mechanism underlying dysconnectivity in psychosis.

Schizophrenia is a complex neuropsychiatric disorder with a diverse clinical phenotype that has a substantial personal and public health burden. To advance the mechanistic understanding of the illness, neuroimaging can be utilized to capture different aspects of brain pathologyin vivo, including brain structural integrity deficits, functional dysconnectivity, and altered neurotransmitter systems. In this review, we consider a number of key scientific questions relevant in the context of neuroimaging studies aimed at unraveling the pathophysiology of schizophrenia and take the opportunity to reflect on our progress toward advancing the mechanistic understanding of the illness. Our data is congruent with the idea that the brain is fundamentally affected in the illness, where widespread structural gray and white matter involvement, functionally abnormal cortical and subcortical information processing, and neurometabolic dysregulation are present in patients. Importantly, certain brain circuits appear preferentially affected and subtle abnormalities are already evident in first episode psychosis patients. We also demonstrated that brain circuitry alterations are clinically relevant by showing that these pathological signatures can be leveraged for predicting subsequent response to antipsychotic treatment. Interestingly, dopamine D2 receptor blockers alleviate neural abnormalities to some extent. Taken together, it is highly unlikely that the pathogenesis of schizophrenia is uniform, it is more plausible that there may be multiple different etiologies that converge to the behavioral phenotype of schizophrenia. Our data underscore that mechanistically oriented neuroimaging studies must take non-specific factors such as antipsychotic drug exposure or illness chronicity into consideration when interpreting disease signatures, as a clear characterization of primary pathophysiological processes is an imperative prerequisite for rational drug development and for alleviating disease burden in our patients.

We combined magnetoencephalography (MEG), 7 T proton magnetic resonance spectroscopy (MRS), and 7 T fMRI during performance of a task in a group of 23 first episode psychosis (FEP) patients and 26 matched healthy controls (HC). We recorded both the auditory evoked response to 40 Hz tone clicks and the resting state in MEG. Neurometabolite levels were obtained from the anterior cingulate cortex (ACC). The fMRI BOLD response was obtained during the Stroop inhibitory control task. FEP showed a significant increase in resting state low frequency theta activity (p d = 0.69), but no significant difference in the 40 Hz auditory evoked response compared to HC. An across-groups whole brain analysis of the fMRI BOLD response identified eight regions that were significantly activated during task performance (p p = 0.0006; d = 1.19). In the combined FEP and HC group, there was a significant correlation between the BOLD signal during task performance and MEG resting state low frequency activity (p

To better understand cognitive control impairment in schizophrenia, it is vital to determine the extent of dysfunctional connectivity in the associated fronto-striatal brain network, with a focus on the connections with the anterior cingulate cortex (ACC), prior to the potential confounding effect of medication. It is also essential to determine the effects following antipsychotic medication and the relationship of those effects on psychosis improvement. Twenty-two patients with schizophrenia, initially unmedicated and after a 6-week course of risperidone, and 20 matched healthy controls (HC) performed a fMRI task twice, six weeks apart. We investigated group and longitudinal differences in ACC-related functional connectivity during performance of a Stroop color task as well as connectivity patterns associated with improvement in psychosis symptoms. Unmedicated patients with schizophrenia showed greater functional connectivity between ACC and bilateral caudate and midbrain and lower connectivity with left putamen compared to healthy controls. At baseline, greater functional connectivity between ACC and bilateral putamen predicted subsequent better treatment response. Change in functional connectivity between ACC and left putamen positively correlated with better treatment response. These results suggest that patterns of functional connectivity in fronto-striatal networks can be utilized to predict potential response to antipsychotic medication. Prior to treatment, brain function may be structured with a predisposition that favors or not treatment response.

Evidence points toward a relationship between longer duration of untreated psychosis (DUP) and worse long-term outcomes in patients with first episode psychosis (FEP), but the underlying neurobiology remains poorly understood. Proton magnetic resonance spectroscopy studies have reported altered hippocampus glutamatergic neurotransmission, and structural MRI as reported hippocampal atrophy that may be associated with memory impairment in schizophrenia. Here, we quantify left hippocampus glutamate (Glx) and left hippocampus subfield volumes in 54 antipsychotic-naive FEP and 41 healthy controls (HC), matched on age, sex, and parental occupation. While there were no significant group difference in Glx levels, hippocampal Glx levels were significantly higher in those who underwent a long DUP (>12 months) compared to those with a short DUP, and compared to HC. Compared to HC, FEP had significantly reduced whole hippocampus volume, as well as of CA1, CA4, granule cell layer, subiculum, and presubiculum subfields. Smaller whole hippocampal volume, as well as CA1, molecular layer, subiculum, presubiculum, and hippocampal tail volumes were significantly associated with longer DUP. However, we found no significant association between hippocampal Glx levels and hippocampal volume or subfields, suggesting that these alterations are not related, or their relationship does not follow a linear pattern. However, our results strongly suggest that one or several pathophysiological processes underlie the DUP. Importantly, our data highlight the critical need for reducing the DUP and for early pharmacological intervention with the hope to prevent structural deficits and, hopefully, improve clinical outcomes.

Schizophrenia is a chronic, often progressive, disorder. Understanding the underlying neurobiology present in the early stages of the illness is as a pivotal step in designing targeted interventions aimed at arresting disease progression. The aim of our study was to examine neurometabolic changes in the dopamine rich associative striatum in medication-naive first episode psychosis (FEP). We quantified neurometabolites in 14 FEP and 18 healthy controls (HC) matched on key demographic characteristics. Spectra from the voxel in the left associative striatum were acquired using a PRESS sequence (TR/TE = 2000/80 ms; 512 averages). MRS data were quantified in the time domain with AMARES in jMRUI. Choline was significantly elevated in FEP compared to HC. No significant alterations in other metabolites were observed. We did not observe correlations between metabolite levels and clinical characteristics in FEP. Here, we demonstrated elevated choline and a disruption of the relationship between N-acetyl-aspartate and Glx (glutamate + glutamine) in medication-naive FEP patients in the left striatum indicating possible mitochondrial, membrane and glial dysfunction as an underlying pathological phenomenon. In addition, striatal choline shows promise as a biomarker for FEP that may have utility in clinical trials investigating target engagement in experimental regimens.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). Retraction notice to: “Mnemonic Discrimination Deficits in First-Episode Psychosis and a Ketamine Model Suggests Dentate Gyrus Pathology Linked to N-Methyl-D-Aspartate Receptor Hypofunction” by Nina Vanessa Kraguljac, Matthew Carle, Michael A. Frölich, Steve Tran, Michael A. Yassa, David Matthew White, Abhishek Reddy, and Adrienne Carol Lahti (Biol Psychiatry Cogn Neurosci Neuroimaging 2018; 3:231-238); https://doi.org/10.1016/j.bpsc.2017.02.005. This article has been retracted at the request of Cameron S. Carter, M.D., Editor of Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, with agreement from all authors. The authors discovered an error in the calculation of the response bias–corrected pattern recognition score in this article, which has significantly changed the results for experiment 1. Specifically, the authors discovered that the response bias corrected pattern recognition score was erroneously computed as P(‘old’|target) minus P(‘old’|lure) rather than P(‘old’|target) minus P(‘old’|foil). After re-running statistical analyses with the correct values, the authors found a significant difference in the response bias–corrected pattern recognition score in healthy volunteers (HV) compared with first-episode psychosis (FEP) patients (HV: 84.13 ± 10.96; FEP: 63.70 ± 21.83; t = 4.01; p.01) in experiment 1. This finding is not consistent with the original report, where the authors reported no group differences in bias-corrected pattern recognition scores (originally reported values: t = 0.93, p = .36). The authors again found no significant correlations between pattern completion scores and BPRS total, positive, or negative symptom scores or RBANS scores, consistent with the original report. In experiment 2, bias-corrected pattern recognition scores did not differ between the saline and ketamine conditions (saline: 78.29 ± 28.04; ketamine: 73.59 ± 18.94; t = 0.81; p = 0.43), which is consistent with the original report (originally reported values: t = −0.69, p = .50). Contrary to the original report, task performance during the saline and ketamine infusions was no longer correlated at trend level for pattern recognition. Repeat analyses showed no correlations between pattern recognition scores during the ketamine challenge and BPRS total, positive, and negative symptom scores, or ketamine plasma levels at either time point, consistent with the original report. The authors have verified that bias-corrected pattern separation scores were calculated correctly for both experiments in the initial report. This error affects the abstract, the results, Figure 1, and discussion of the manuscript. The authors voluntarily informed the Journal of this honest error upon its discovery. Because of the extent and nature of the changes to the paper, the editors and authors concluded that, to ensure maximum clarity and transparency, the only course of action was to retract this version of the paper. The authors are revising the paper, which the Journal will re-review and consider further for publication.

Background Approximately 30% of patients with schizophrenia do not improve with antipsychotic drug (APD) treatment and 60% show sub-optimal response. Converging lines of evidence point to hippocampal dysfunction in schizophrenia. It is thought that hippocampal dysfunction spreads across hippocampal subfields and to cortical regions by way of long-range efferent projections. Our prior studies have shown altered hippocampal regional cerebral blood flow in unmedicated patients and normalization after APD treatment. Meta-analyses show reduced hippocampal volume in first episode psychosis (FEP) patients. We evaluated resting state hippocampal functional connectivity (hFC) as well as hippocampal and hippocampal subfield volumes as predictors of treatment response (TR) in two cohorts of patients with a psychosis spectrum disorder. All patients were subsequently treated with an APD for 6 weeks. Methods Cohort 1 consisted of 55 medication-naïve first episode psychosis (FEP) subjects (36 male; mean age 24.18 years). Cohort 2 consisted of 42 unmedicated patients with schizophrenia (SZ) (31 male; mean age 27.9 years). FEP were scanned on a Siemens MAGNETOM Prisma MRI scanner using a 20 channel head coil. Anatomical scans were acquired via T1-weighted and T2-weighted images. Two 6-minute resting state scans were acquired in opposing phase encoding directions (A > P and P > A). SZ were scanned on a Siemens MAGNETOM Allegra MRI scanner with a circularly polarized transmit/receive head coil. Anatomical scans were acquired via a T1-weighted sequence. Resting state scans were acquired with a single 5-minute gradient recalled echo-planar imaging sequence. For both datasets, resting state data were preprocessed in the CONN toolbox (version 18a). We used the left hippocampus as a seed region to create whole brain seed-to-voxel correlation maps for each subject. Regression analyses were then performed to assess the relationship between resting state connectivity and TR (% change in BPRS positive score from (A) baseline to (B) after 6 weeks of APD: (((B-A)/A)*-100). Analyses were corrected using voxel (p < 0.05, uncorrected) and cluster level correction (p < 0.05, FDR corrected). Age, sex, and framewise displacement were used as covariates of no interest. T1 and T2 weighted images were preprocessed using FreeSurfer 6.0. Freesurfer’s hippocampus subfield segmentation module was used to calculate left and right subfield volumes. SPSS 25 was used to regress hippocampal subfield volumes on TR. Age and estimated total intracranial volume (eTIV) were included as covariates of no interest. Results In both cohorts greater hFC to the cuneus and precuneus was predictive of better TR, as was greater hFC to the fusiform gyrus, medial prefrontal cortex (PFC) and anterior cingulate cortex in cohort 2. Reduced hFC connectivity to the angular gyrus in supramarginal gyrus and temporal pole in cohort 1 as well as the orbitofrontal cortex and dorsolateral PFC in cohort 2 were also predictive of better TR. Results from the stepwise regression showed that neither right nor left whole hippocampal volume, or subfield volumes, significantly predict TR for either cohort. Discussion In two patient cohorts, we observed a similar pattern where increased hFC to the cuneus and precuneus was predictive of better response to APD. Furthermore, the lack of a significant predictive value of hippocampal volumes in predicting TR was replicated in each cohort. The replicability of these findings, particularly in a cohort of medication-naïve FEP provides potential biological patterns useful in determining initial response to APD medication in patients with a psychosis spectrum disorder.

Epidemiologic, genetic, and neurobiological studies suggest considerable overlap between schizophrenia and mood disorders. Importantly, both disorders are associated with a broad range of cognitive deficits as well as altered glutamatergic and GABAergic neurometabolism. We conducted a systematic review of magnetic resonance spectroscopy (MRS) studies investigating the relationship between glutamatergic and GABAergic neurometabolites and cognition in schizophrenia spectrum disorders and mood disorders. A literature search in Pubmed of studies published before April 15(th) 2019 was conducted and 37 studies were deemed eligible for systematic review. We found that alterations in glutamatergic and GABAergic neurotransmission have been identified relatively consistently in both schizophrenia and mood disorders. However, because of the vast heterogeneity of published studies in terms of illness stage, medication exposure, MRS acquisition parameters and data post-processing strategies, we still do not understand the relationship between those neurotransmitters and cognitive dysfunction in mental illness, which is a critical initial step for rational drug development. Our findings emphasize the need for coordinated multi-center studies that characterize cognitive function and its biological substrates in large and well-defined clinical populations, using harmonized imaging sequences and analytical methods with the goal to elucidate the underlying pathophysiological mechanisms and to inform future clinical trials.

Background In the perioperative context, benzodiazepines are widely used as anxiolytics. They affect cognition in general, but it is unclear whether the effects of a small dose of the short-acting benzodiazepine midazolam can be assessed objectively. To address this scientific question, we conducted a prospective observational study in adults 55-73 years of age. Using both validated psychometric and functional imaging techniques, we determined whether a 2-mg intravenous (IV) dose of midazolam affects cognitive function. Methods We measured the effect of 2 mg IV of midazolam with both the well-established Repeatable Battery for the Assessment of Neuropsychological Status test and resting-state functional magnetic imaging (rs-fMRI) in older adults. Results Midazolam reduces immediate and delayed memory and has a profound and robust effect on rs-fMRI. Baseline resting-state connectivity predicts memory decline after midazolam administration. Conclusions Observed effects of midazolam on brain networks were statistically significant even in a small group of volunteers. If validated by other investigators, resting-state brain connectivity may have utility as a measure to predict sensitivity to midazolam in older adults.

BACKGROUND: Approximately 30% of patients with schizophrenia (SZ) do not improve with antipsychotic drug (APD) treatment and 60% show sub-optimal response. Our prior studies have showed that hippocampal regional cerebral blood flow (rCBF) is elevated in unmedicated patients and that rCBF reduction is correlated with good treatment response (Lahti, 2009). In addition, we found elevated hippocampal glutamate in unmedicated (Kraguljac, 2013) but not in medicated patients (Kraguljac, 2012). To characterize this pattern, we conducted a longitudinal study where hippocampal neurochemistry and function were measured while patients were unmedicated and after a 6-week course of APD. METHODS: Thirty-four unmedicated SZ were enrolled in this multimodal neuroimaging study. They were scanned while unmedicated and after a 6-week treatment with risperidone. We obtained resting state fMRI scans (TR/TE= 2100/30msec, flip angle= 70, 4mm slice thickness, 1mm gap, 150 acquisitions) and MR spectroscopy scans from a left hippocampus voxel (TR/TE= 2000/80ms; 640 averages, 2.7x 1.5x 1cm). Treatment response criteria were based on a >50% improvement on the Brief Psychiatric Rating Scale (BPRS) psychosis subscale. Seventeen patients met this criterion (10 male; mean age 28.53 years), and 17 did not (14 male; mean age 29.94 years). Using a left hippocampus seed region, functional connectivity maps to the whole brain were generated in the CONN toolbox. MRS data were quantified using jMRUI. We compared hippocampal connectivity between good and poor responders at baseline and examined whether hippocampal functional connectivity was predictive of subsequent treatment response. A group x time (baseline vs week 6) interaction was used to assess group differences longitudinally. We examined the correlation between treatment response and change in hippocampal connectivity. Connectivity analyses were corrected for age as appropriate and corrected for multiple comparisons using voxel height threshold (p

BACKGROUND: Several neuroimaging studies have attempted to characterize the contribution of glutamatergic dysfunction to functional dysconnectivity of large-scale brain networks using ketamine models. However, findings from blood oxygen level dependent signal (BOLD) imaging studies have been conflicting, in part because the signal stems from a complex interaction between blood flow, blood volume, and oxygen consumption. METHODS: We obtained multimodal neuroimaging in a group of healthy volunteers (n= 15) during a saline and during a ketamine infusion (0.27mg/kg bolus over 10 minutes, followed by a continuous infusion of 0.25mg/kg/hour for 50 minutes). We acquired 2D pCASL scans (TR/ TE= 5230/ 53ms, excitation flip angle= 90°, in-plane resolution= 3.75× 3.75mm2, matrix= 64× 64, slice thickness= 6mm, label time 1s, delay time 1s, labeling offset 8cm) with 30 pairs of labeled and unlabeled images to measure regional cerebral blood flow (rCBF) and MR spectroscopy scans in the left hippocampus (TR/TE= 2000/80ms; 1200 Hz spectral bandwidth; 1024 points; 640 averages, and 8 averages without water suppression, voxel size: 2.7x 1.5x 1cm) to measure glx (glutamate+glutamine). We examined changes in rCBF and metabolic connectivity, as well as their associations with clinical symptom severity (measured with the Brief Psychiatric Rating Scale [BPRS]) and glx levels. RESULTS: Voxelwise analysis comparing rCBF during a saline infusion and ketamine challenge demonstrated regionally selective increases in the prefrontal, orbitofrontal and cingulate cortices as well as the insula, angular gyrus, caudate, putamen, thalamus and hippocampus. No areas showed a decrease in rCBF. Metabolic connectivity analyses revealed a complex pattern of ketamine related rCBF changes. Positive correlations between the anterior cingulate/ frontal pole and insula decreased. Negative correlations between the hippocampus and the dorsolateral prefrontal cortex as well as the putamen decreased. We also found that the increase in rCBF in the bilateral putamen and left hippocampus was positively correlated with psychosis severity during the ketamine challenge while change in anterior cingulate cortex rCBF was negatively correlated with change in hippocampal Glx. DISCUSSION: Here we find regionally selective patterns of rCBF changes, and metabolic connectivity changes at the level of large-scale brain networks that are thought to be central to the schizophrenia psychopathology. Our study adds to the efforts to confirm putative links between an imbalance in glutamate metabolism and dysconnectivity of large-scale brain networks. Development of glutamatergic compounds that alleviate disease burden, possibly through normalizing glutamate excess related increased rCBF, are direly needed.

BACKGROUND: The National Institute of Mental Health has deemed imperative to 1) fully understand the behavioral and brain mechanisms of individuals who experience first episode psychosis (FEP) and to 2) substantially reduce the duration of untreated psychosis (DUP; the time between the onset of psychosis and initiation of appropriate treatment) as shorter DUP has been associated with a better prognosis in schizophrenia (SZ). Deficits in SZ have been linked to aberrant functional connectivity among three key brain networks: the default mode (DMN), salience (SN), and central executive networks (CEN). To date, only a handful of studies have examined DUP in SZ using in-vivo neuroimaging techniques. The objective of this study is to examine the effect of DUP using resting state functional connectivity MRI (rsfcMRI) in a sample of antipsychotic-naïve patients with FEP. METHODS: rs-fMRI data from 45 patients with SZ (mean age = 23 yo; 32M/13F) were used and processed using a standard preprocessing pipeline. Signal from a priori brain regions of interest from posterior cingulate cortex (DMN), right insula (SN), and bilateral posterior parietal cortex (CEN) were extracted and correlated with the rest of the brain. Additionally, exploratory connectivity analyses were also performed: local correlation (LCOR; the average of correlation coefficients between each individual voxel and a region of neighboring voxels) and global correlation (GCOR; the average of correlation coefficients between each individual voxel and all of the voxels in the brain). To examine DUP and brain connectivity, patients were divided into 3 groups: short DUP (≤ 1month; n = 15), medium DUP (< 1 year; n = 17), and long DUP (≥ 1 year; n = 13) and groups differences were tested. DUP, as a continuous variable, was also correlated with brain connectivity across all patients. All analyses were corrected for age and gender. RESULTS: The results are: 1) for a priori analysis, significant clusters of group differences were found in L/R postcentral (DMN), L/R middle frontal/temporal and L/R superior temporal (SN), left inferior temporal, right frontal pole, left supramarginal and left fusiform gyri (CEN); 2) for exploratory analyses, significant clusters of group differences were found in left superior temporal and precentral, and right frontal pole (LCOR) and in left insula and temporal pole, and left superior temporal and precentral gyrus (GCOR); and 3) correlations between DUP and brain connectivity were found across both analysis in the same regions. Across all results, a very consistent pattern of greater rs-fcMRI for shorter vs. longer DUP was observed. All analyses were corrected using voxel (p < .01, uncorrected) and cluster level correction (p < .05, FDR corrected). DISCUSSION: Our findings of rs-fcMRI suggest that heterogeneity in SZ may relate to alterations in brain mechanisms due to a possible effect of DUP. Furthermore, these differences may be mediated by symptom severity and cognitive deficits within the disorder. Future steps will include examining the impact of DUP on response to treatment using antipsychotic medication on these same patients. Overall, these preliminary findings underscore the need to further examine and shorten DUP in psychiatric populations. Funding: NIH (R01MH102951).

BACKGROUND: Meta-analyses have consistently identified a relationship between longer duration of untreated psychosis (DUP) and worse long-term outcomes in patients with schizophrenia. However, the neurobiology of this phenomenon and its implications for response to antipsychotic medications remain poorly understood. We previously identified two indices of glutamatergic dysfunction: excess of glutamate + glutamine (Glx) (reference) and an abnormal correlation between N-acetyl-aspartate (NAA) and Glx 1. The aim of this longitudinal study was to measure Glx and NAA in antipsychotic-naive first episode psychosis subjects (FEP) before and after antipsychotic treatment and evaluate their relationships to DUP and treatment response. METHODS: 51 FEP (age: 23.55 ± 5.92, 34M/17F) were enrolled in this proton magnetic resonance spectroscopy (1H-MRS) study. Two voxels were assessed: the anterior cingulate cortex (ACC) and the hippocampus (HIP) (PRESS, TR/TE= 2000/80 ms), at baseline and after 6 and 16 weeks of treatment with risperidone. Metabolite concentrations were quantified as absolute value with partial volume corrections 2 using TARQUIN 3. DUP was defined as the duration between discernable psychotic symptoms to the time of initial treatment contact. Treatment response was assessed as percent change of the score on positive subscale of the Brief Psychiatric Rating Scale (BPRS) between baseline and week 16. Differences in metabolite levels between sessions were investigated using MANOVA, and the NAA-Glx correlation was examined using partial correlations (controlled for age and gender). We also used partial correlations to assess relationships between baseline metabolites and DUP (log-transformed). RESULTS: Effect of DUP on NAA and Glx levels: There were trend-level negative correlations between Glx and DUP in both the ACC (r=-0.26, p=0.07) and hippocampus (r=-0.27, p=0.07). No significant correlations were found for NAA (ACC: r=0.07, p=0.63; HIP: r=-0.18, p=0.23). Effect of medication on NAA, Glx and NAA-Glx correlation: At baseline, a correlation between NAA and Glx was found in both ACC (r=0.55, p

BACKGROUND: Considerable research suggests that one of the pathophysiological mechanisms underlying schizophrenia (SZ) is aberrant functional connectivity (fnc) between brain regions. Typically, one explores this issue by determining if the fnc between two specified brain regions is either consistently higher or consistently lower in SZ than in matched healthy controls (HC). However, suppose that in SZ there is a problem in how the brain regulates the connectivity between brain regions: in this case, SZ might show increased deviation from an optimal global pattern of functional connectivity, but not have consistently higher or lower values of fnc between any two specific regions. Here we investigated whether there was evidence for global shifts in the pattern of fnc in HC and SZ in resting state fMRI and also resting state magnetoencephalography (MEG). METHODS: Minimally treated first episode SZ (n=19) and HC (n=24) matched for age, gender, and family socio-economic status were recruited. MEG was performed in a 4D systems 148 channel magnetometer and the resting state was recorded. MEG activity was filtered into EEG bands and the low-frequency envelope extracted. The fMRI BOLD resting state activity was recorded in a 7T scanner. fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state components was computed separately for fMRI and the different MEG frequency bands. We created a mean template of the fnc matrix of correlation coefficients for both SZ and HC combined, and determined the similarity between this mean template and each individual subject’s fnc by using the dot product. RESULTS: We calculated the fnc between 30 regions for fMRI and 33 regions for MEG for each subject. SZ had on average lower similarity to the mean fnc matrix than HC for the fMRI data (HC: 33.2 +/- 1.6 stderr, SZ: 28.3 +/- 1.0, P=0.018 by t-test). This was also true for the MEG alpha band (HC: 90.6 +/- 5.2 stderr, SZ: 76.1 +/- 3.6, P=0.036 by t-test) and the MEG beta band (HC: 107.8 +/- 5.7, SZ: 87.7 +/- 4.9, P=0.014 by t-test). However, there were no significant differences between SZ and HC in the MEG gamma, delta, or theta bands. DISCUSSION: When exploring the pattern of connectivity between every brain region and every other brain region, the number of potential connections goes up as the square of the number of regions. You can maintain statistical power by limiting yourself a priori to a subset of all possible brain regions - for example, just the default network, or just sensorimotor. Or you can look at the entire brain, but the loss of statistical power means that you will only be able to detect the dysconnectivities with the largest differences between HC and SZ. Our results here suggest that to some extent it is the overall pattern of connectivity in SZ that is aberrant compared to HC, and that some SZ may have a functional connection strength between two regions that is aberrantly low, and others, that is aberrantly high. It is proposed that future studies using large number of subjects, and standardized maps of functional connectivity, might further address this possibility.

A growing body of evidence suggests glutamate excess in schizophrenia and that N-methyl-d-aspartate receptor (NMDAR) hypofunction on γ-aminobutyric acid (GABA) interneurons disinhibiting pyramidal cells may be relevant to this hyperglutamatergic state. To better understand how NMDAR hypofunction affects the brain, we used Magnetic Resonance Spectroscopy and resting state functional MRI to study the effects of ketamine on hippocampal neurometabolite levels and functional connectivity in 15 healthy human subjects. We observed a ketamine induced increase of hippocampal Glx (glutamate+glutamine; F= 3.76; p= 0.04), a decrease in fronto-temporal (t=4.92, pFDR< .05, kE= 2198, x= -30, y= 52, z= 14) and temporo-parietal functional connectivity (t=5.07, pFDR< .05, kE= 6094, x= -28, y= -36, z= -2), and a possible link between connectivity changes and elevated Glx. Our data empirically support that hippocampal glutamatergic elevation and resting state network alterations may arise from NMDAR hypofunction and establish a proof of principle whereby experimental modelling of a disorder can help mechanistically integrate distinct neuroimaging abnormalities in schizophrenia.

Background Schizophrenia is thought to be a disorder of brain dysconnectivity. An imbalance between cortical excitation/inhibition is also implicated, but the link between these abnormalities remains unclear. The present study used resting state functional connectivity MRI (rs-fcMRI) and magnetic resonance spectroscopy (MRS) to investigate how measurements of glutamate + glutamine (Glx) in the anterior cingulate cortex (ACC) relate to rs-fcMRI in medication-naïve first episode psychosis (FEP) subjects compared to healthy controls (HC). Based on our previous findings, we hypothesized that in HC would show correlations between Glx and rs-fMRI in the salience and default mode network, but these relationships would be altered in FEP. Methods Data from 53 HC (age = 24.70 ±6.23, 34M/19F) and 60 FEP (age = 24.08 ±6.29, 38M/22F) were analyzed. To obtain MRS data, a voxel was placed in the ACC (PRESS, TR/TE = 2000/80ms). Metabolite concentrations were quantified with respect to internal water using the AMARES algorithm in jMRUI. rs-fMRI data were processed using a standard preprocessing pipeline in the CONN toolbox. BOLD signal from a priori brain regions of interest from posterior cingulate cortex (default mode network, DMN), anterior cingulate cortex (salience network, SN), and right posterior parietal cortex (central executive network, CEN) were extracted and correlated with the rest of the brain to measure functional connectivity (FC). Group analyses were performed on Glx, FC, and Glx-FC interactions while controlling for age, gender, and motion when applicable. FC and Glx-FC analyses were performed using small volume correction [(p < 0.01, threshold-free cluster enhancement corrected (TFCE)]. Results No significant between-group differences were found in Glx concentration in the ACC [F(1, 108) = 0.34, p = 0.56], but reduced FC was found on each network in FEP compared to HC (pTFCE corrected). Group Glx-FC interactions were found in the form of positive correlations between Glx and FC in DMN and SN in the HC group, but not in FEP; and negative correlations in CEN in HC, but not in FEP. Discussion While we did not find significant group differences in ACC Glx measurements, ACC Glx modulated FC differentially in FEP and HC. Positive correlations between Glx and FC were found in the SN and DMN, suggesting long range modulation of the two networks in HC, but not in FEP. Additionally, negative correlations between Glx and FC were found in CEN in HC, but not in FEP. Overall, these results suggest that even in the absence of group differences in Glx concentration, the long-range modulation of these 3 networks by ACC Glx is altered in FEP.

Background It is becoming increasingly clear that longer duration of untreated psychosis (DUP) is associated with adverse clinical outcomes in patients with psychosis spectrum disorders. Especially because this association is often cited when justifying early intervention efforts, it is imperative to better understand underlying biological mechanisms. Methods We recruited 74 antipsychotic-naïve first episode psychosis (FEP) patients and 45 matched healthy controls in this trial. At baseline, we used a human connectome style diffusion weighted imaging (DWI) sequence to quantify white matter integrity in both groups. Patients then received 16 weeks of treatment with risperidone. DWI scans were acquired with opposite phase encoding directions [TR/TE: 3230ms/ 89.20ms; multiband acceleration factor 4, Flip angle: 84°; slice thickness 1.5mm, 92 slices, voxel size 1.5mm3, 92 diffusion weighted images distributed equally over 2 shells with b-values of ̴ 1500s/mm2 and ̴ 3000s/mm2, as well as 7 interspersed b= ̴ 0s/mm2 images]). Preprocessing of DWI images was performed in TORTOISE (version 3.1.2). This included correction for thermal noise, Gibbs-ringing, high b-value based bulk motion and eddy-current distortions using a MAP-MRI model, resampling of images to 1mm3, and rotation of gradient tables independently for each DWI phase encoding direction. Then, DR-BUDDI was used to correct EPI distortions with input from the anatomical image and to combine the two datasets using geometric averaging to generate the final corrected dataset. Tensors were computed with DIFF_CALC using a linear fitting algorithm. To spatially normalize images to the Illinois Institute of Technology atlas (IIT4) space, we implemented an optimized non-linear image registration procedure using a modified version of 3dQwarp in AFNI. We compared whole brain fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD) and radial diffusivity between groups. To test if structural white matter integrity mediates the relationship between longer DUP and poorer treatment response, we fit a mediator model and estimated indirect effects. Results Groups did not differ in age (FEP: 23.83+/-6.21 years; HC: 24.78+/-6.24 years), sex (FEP: 65.2% male; HC: 64.4% male), or parental socioeconomic status (FEP: 5.95+/-4.83; HC: 4.22+/-4.06). We found decreased whole brain FA and AD in medication-naive FEP compared to controls. In patients, lower FA was correlated with longer DUP (r= -0.32; p= 0.03) and poorer subsequent response to antipsychotic treatment (r= 0.40; p= 0.01). Importantly, we found a significant mediation effect for FA (indirect effect: -2.70; p= 0.03), indicating that DUP exerts its effects on treatment response through affecting white matter integrity. Discussion To our knowledge, this is the first study to examine a putative role of white matter integrity in the observed association between DUP and clinical outcomes in first episode psychosis. Our data provide empirical support to the idea the DUP may have fundamental pathogenic effects on the natural history of psychosis, suggest a biological mechanism underlying this phenomenon, and underscore the importance of early intervention efforts in this disabling neuropsychiatric syndrome.

Background Prior studies indicate that chronic schizophrenia (SZ) is associated with a specific profile of reinforcement learning abnormalities. These impairments are characterized by: 1) reductions in learning rate, and 2) impaired Go learning and intact NoGo learning. Furthermore, each of these deficits are associated with greater severity of negative symptoms, consistent with theoretical perspectives positing that avolition and anhedonia are associated with deficits in generating, updating, and maintaining mental representations of reward value hat are needed to guide decision-making. However, it is unclear whether these deficits extend to earlier phases of psychotic illness and when individuals are unmedicated. Methods Two studies were conducted to examine reinforcement learning deficits in earlier phases of psychosis. In study 1, participants included 35 participants with first episode psychosis (FEP) and 25 healthy controls (HC). Study 2 included 17 antipsychotic naïve individuals who met criteria for attenuated psychosis syndrome (APS) (i.e., those with a prodromal syndrome) and 18 matched healthy controls (HC). In both studies, participants completed the Temporal Utility Integration Task, a measure of probabilistic reinforcement learning that contained Go and NoGo learning blocks. Participants in the clinical groups also completed neuropsychological testing and standard clinical interviews designed to determine symptom severity and diagnosis. Results FEP displayed impaired Go learning and intact NoGo learning. In contrast, APS did not display impairments in Go or NoGo learning at the group level. Negative symptoms were not significantly associated with reinforcement learning in APS participants. However, greater impairments in Go learning were associated with increased cross-sectional risk for conversion on the NAPLS risk calculator score in the APS group. Discussion Findings provide new evidence for areas of spared and impaired reinforcement learning in early phases of psychosis. Similar to chronic SZ, FEP was associated with impaired Go learning, and intact NoGo learning. Reinforcement learning is more spared in those at clinical high-risk, except those at greatest risk for conversion, where Go learning deficits are more pronounced. These findings suggest that reinforcement learning deficits may emerge early among those who are at clinical high risk for developing psychosis and that they are already pronounced by illness onset in the first episode. Importantly, these reinforcement learning deficits do not appear to be a byproduct of illness chronicity or antipsychotic medication use, but rather a consequence of the illness itself.