Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.

Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.

Electrophysiological investigation of reward anticipation and outcome evaluation during slot machine play.

Slot machines are a popular form of gambling, offering a tractable way to experimentally model reward processes. This study used a 3-reel slot paradigm to assess psychologically distinct phases of reward processing, reflecting anticipation, and early- and late-stage outcome processing. EEG measures of winning, nearly missing (a losing outcome revealed at the final, third reel), and "totally" missing (a losing outcome revealed earlier, at the second reel) were collected from healthy adults (n=54). Condition effects were evaluated in: i) event-related potential (ERP) components reflecting anticipatory attention (stimulus preceding negativity, SPN) and outcome processing (reward positivity, RewP and late-positive potential, LPP) and ii) total power and phase synchrony of theta and delta band oscillations. Behaviorally, trial initiation was fastest after a near miss outcome and slowest after a winning outcome. As expected, a significant SPN was observed for possible wins (AA) vs. total misses (AB), consistent with reward anticipation. Larger win (AAA) vs. near miss (AAB) amplitudes were observed for the RewP; LPP amplitudes were largest for wins (AAA), intermediate for near misses (AAB), and smallest for total misses (ABC), reflecting significant early (RewP) and late-stage (LPP) outcome processing effects. There was an effect of reel position on the RewP, with larger amplitude in the final reel (AAA-AAB) relative to the 2nd-reel locked difference waves (AA-AB). Across all outcomes, near misses elicited the largest and most phase-synchronized theta responses, while wins elicited larger and more phase-synchronized delta responses than total misses, with delta band measures not distinguishing between near misses and wins. . Phase locking measures contrasting win vs. near miss delta and theta synchronization, within time windows corresponding to ERP measurements, covaried with RewP, but not SPN or LPP, amplitude. Lastly, EEG measures showed differential relationships with age and self-reported consummatory pleasure. In the context of slot machine play, where reward anticipation and attainment place minimal demands on effort and skill, ERP and time-frequency methods capture distinct neurophysiological signatures of reward anticipation and outcome processing.

Childhood trauma and cognitive functioning in individuals at clinical high risk (CHR) for psychosis.

Evidence suggests that early trauma may have a negative effect on cognitive functioning in individuals with psychosis, yet the relationship between childhood trauma and cognition among those at clinical high risk (CHR) for psychosis remains unexplored. Our sample consisted of 626 CHR children and 279 healthy controls who were recruited as part of the North American Prodrome Longitudinal Study 2. Childhood trauma up to the age of 16 (psychological, physical, and sexual abuse, emotional neglect, and bullying) was assessed by using the Childhood Trauma and Abuse Scale. Multiple domains of cognition were measured at baseline and at the time of psychosis conversion, using standardized assessments. In the CHR group, there was a trend for better performance in individuals who reported a history of multiple types of childhood trauma compared with those with no/one type of trauma (Cohen d = 0.16). A history of multiple trauma types was not associated with greater cognitive change in CHR converters over time. Our findings tentatively suggest there may be different mechanisms that lead to CHR states. Individuals who are at clinical high risk who have experienced multiple types of childhood trauma may have more typically developing premorbid cognitive functioning than those who reported minimal trauma do. Further research is needed to unravel the complexity of factors underlying the development of at-risk states.

Resting-state thalamic dysconnectivity in schizophrenia and relationships with symptoms.

BACKGROUND: Schizophrenia (SZ) is a severe neuropsychiatric disorder associated with disrupted connectivity within the thalamic-cortico-cerebellar network. Resting-state functional connectivity studies have reported thalamic hypoconnectivity with the cerebellum and prefrontal cortex as well as thalamic hyperconnectivity with sensory cortical regions in SZ patients compared with healthy comparison participants (HCs). However, fundamental questions remain regarding the clinical significance of these connectivity abnormalities. METHOD: Resting state seed-based functional connectivity was used to investigate thalamus to whole brain connectivity using multi-site data including 183 SZ patients and 178 matched HCs. Statistical significance was based on a voxel-level FWE-corrected height threshold of p < 0.001. The relationships between positive and negative symptoms of SZ and regions of the brain demonstrating group differences in thalamic connectivity were examined. RESULTS: HC and SZ participants both demonstrated widespread positive connectivity between the thalamus and cortical regions. Compared with HCs, SZ patients had reduced thalamic connectivity with bilateral cerebellum and anterior cingulate cortex. In contrast, SZ patients had greater thalamic connectivity with multiple sensory-motor regions, including bilateral pre- and post-central gyrus, middle/inferior occipital gyrus, and middle/superior temporal gyrus. Thalamus to middle temporal gyrus connectivity was positively correlated with hallucinations and delusions, while thalamus to cerebellar connectivity was negatively correlated with delusions and bizarre behavior. CONCLUSIONS: Thalamic hyperconnectivity with sensory regions and hypoconnectivity with cerebellar regions in combination with their relationship to clinical features of SZ suggest that thalamic dysconnectivity may be a core neurobiological feature of SZ that underpins positive symptoms.

Intranasal oxytocin increases facial expressivity, but not ratings of trustworthiness, in patients with schizophrenia and healthy controls.

BACKGROUND: Blunted facial affect is a common negative symptom of schizophrenia. Additionally, assessing the trustworthiness of faces is a social cognitive ability that is impaired in schizophrenia. Currently available pharmacological agents are ineffective at improving either of these symptoms, despite their clinical significance. The hypothalamic neuropeptide oxytocin has multiple prosocial effects when administered intranasally to healthy individuals and shows promise in decreasing negative symptoms and enhancing social cognition in schizophrenia. Although two small studies have investigated oxytocin's effects on ratings of facial trustworthiness in schizophrenia, its effects on facial expressivity have not been investigated in any population. METHOD: We investigated the effects of oxytocin on facial emotional expressivity while participants performed a facial trustworthiness rating task in 33 individuals with schizophrenia and 35 age-matched healthy controls using a double-blind, placebo-controlled, cross-over design. Participants rated the trustworthiness of presented faces interspersed with emotionally evocative photographs while being video-recorded. Participants' facial expressivity in these videos was quantified by blind raters using a well-validated manualized approach (i.e. the Facial Expression Coding System; FACES). RESULTS: While oxytocin administration did not affect ratings of facial trustworthiness, it significantly increased facial expressivity in individuals with schizophrenia (Z = -2.33, p = 0.02) and at trend level in healthy controls (Z = -1.87, p = 0.06). CONCLUSIONS: These results demonstrate that oxytocin administration can increase facial expressivity in response to emotional stimuli and suggest that oxytocin may have the potential to serve as a treatment for blunted facial affect in schizophrenia.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Error-related brain activity dissociates hoarding disorder from obsessive-compulsive disorder.

BACKGROUND: Obsessive-compulsive disorder (OCD) is associated with an abnormally large error-related negativity (ERN), an electrophysiological measure of error monitoring in response to performance errors, but it is unclear if hoarding disorder (HD) also shows this abnormality. This study aimed to determine whether the neurophysiological mechanisms underlying error monitoring are similarly compromised in HD and OCD. METHOD: We used a visual flanker task to assess ERN in response to performance errors in 14 individuals with HD, 27 with OCD, 10 with HD+OCD, and 45 healthy controls (HC). Age-corrected performance and ERN amplitudes were examined using analyses of variance and planned pairwise group comparisons. RESULTS: A main effect of hoarding on ERN (p = 0.031) was observed, indicating ERN amplitudes were attenuated in HD relative to non-HD subjects. A group × age interaction effect on ERN was also evident. In HD-positive subjects, ERN amplitude deficits were significantly greater in younger individuals (r = -0.479, p = 0.018), whereas there were no significant ERN changes with increasing age in OCD and HC participants. CONCLUSIONS: The reduced ERN in HD relative to OCD and HC provides evidence that HD is neurobiologically distinct from OCD, and suggests that deficient error monitoring may be a core pathophysiological feature of HD. This effect was particularly prominent in younger HD participants, further suggesting that deficient error monitoring manifests most strongly early in the illness course and/or in individuals with a relatively early illness onset.

Substance use in individuals at clinical high risk of psychosis.

BACKGROUND: A series of research reports has indicated that the use of substances such as cannabis, alcohol and tobacco are higher in youth at clinical high risk (CHR) of developing psychosis than in controls. Little is known about the longitudinal trajectory of substance use, and findings on the relationship between substance use and later transition to psychosis in CHR individuals are mixed. METHOD: At baseline and 6- and 12-month follow-ups, 735 CHR and 278 control participants completed the Alcohol and Drug Use Scale and a cannabis use questionnaire. The longitudinal trajectory of substance use was evaluated with linear mixed models. RESULTS: CHR participants endorsed significantly higher cannabis and tobacco use severity, and lower alcohol use severity, at baseline and over a 1-year period compared with controls. CHR youth had higher lifetime prevalence and frequency of cannabis, and were significantly younger upon first use, and were more likely to use alone and during the day. Baseline substance use did not differentiate participants who later transitioned to psychosis (n = 90) from those who did not transition (n = 272). Controls had lower tobacco use than CHR participants with a prodromal progression clinical outcome and lower cannabis use than those with a psychotic clinical outcome at the 2-year assessment. CONCLUSIONS: In CHR individuals cannabis and tobacco use is higher than in controls and this pattern persists across 1 year. Evaluation of clinical outcome may provide additional information on the longitudinal impact of substance use that cannot be detected through evaluation of transition/non-transition to psychosis alone.

Occasional cannabis use is associated with higher premorbid functioning and IQ in youth at clinical high-risk (CHR) for psychosis: Parallel findings to psychosis cohorts.

BACKGROUND: Neurocognitive deficits have been widely reported in clinical high-risk for psychosis (CHR) populations. Additionally, rates of cannabis use are high among CHR youth and are associated with greater symptom severity. Cannabis use has been sometimes shown to be associated with better neurocognition in more progressed psychosis cohorts, therefore in this study we aimed to determine whether a similar pattern was present in CHR. METHODS: CHR participants ages 12-30 from the North American Prodromal Longitudinal Study (NAPLS-3) (N = 698) were grouped according to: "minimal to no cannabis use" (n = 406), "occasional use" (n = 127), or "frequent use" (n = 165). At baseline, cannabis use groups were compared on neurocognitive tests, clinical, and functional measures. Follow-up analyses were used to model relationships between cannabis use frequency, neurocognition, premorbid, and social functioning. RESULTS: Occasional cannabis users performed significantly better than other use-groups on measures of IQ, with similar trend-level patterns observed across neurocognitive domains. Occasional cannabis users demonstrated better social, global, and premorbid functioning compared to the other use-groups and less severe symptoms compared to the frequent use group. Follow-up structural equation modeling/path analyses found significant positive associations between premorbid functioning, social functioning, and IQ, which in turn was associated with occasional cannabis use frequency. DISCUSSION: Better premorbid functioning positively predicts both better social functioning and higher IQ which in turn is associated with a moderate cannabis use pattern in CHR, similar to reports in first-episode and chronic psychosis samples. Better premorbid functioning likely represents a protective factor in the CHR population and predicts a better functional outcome.

Converging evidence for gamma synchrony deficits in schizophrenia.

BACKGROUND: In electroencephalogram (EEG) studies of auditory steady-state responses (ASSRs), patients with schizophrenia show a deficit in power and/or phase-locking, particularly at the 40 Hz frequency where these responses resonate. In addition, studies of the transient gamma-band response (GBR) elicited by single tones have revealed deficits in gamma power and phase-locking in schizophrenia. We examined the degree to which the 40 Hz ASSR and the transient GBR to single tones are correlated and whether they assess overlapping or distinct gamma-band abnormalities in schizophrenia. METHODS: EEG was recorded during 40 Hz ASSR and auditory oddball paradigms from 28 patients with schizophrenia or schizoaffective disorder (SZ) and 25 age- and gender-matched healthy controls (HC). The ASSR was elicited by 500 ms click trains, and the transient GBR was elicited by the standard tones from the oddball paradigm. Gamma phase and magnitude values, calculated using Morlet wavelet transformations, were used to derive total power and phase-locking measures. RESULTS: Relative to HC, SZ patients had significant deficits in total gamma power and phase-locking for both ASSR- and GBR-based measures. Within both groups, the 40 Hz ASSR and GBR phase-locking measures were significantly correlated, with a similar trend evident for the total power measures. Moreover, co-varying for GBR substantially reduced 40 Hz ASSR power and phase-locking differences between the groups. CONCLUSIONS: 40 Hz ASSR and transient GBR measures provide very similar information about auditory gamma abnormalities in schizophrenia, despite the overall enhancement of 40 Hz ASSR total power and phase-locking values relative to the corresponding GBR values.

A method for estimating and characterizing explicitly nonlinear dynamic functional network connectivity in resting-state fMRI data.

The past 10 years have seen an explosion of approaches that focus on the study of time-resolved change in functional connectivity (FC). FC characterization among networks at a whole-brain level is frequently termed functional network connectivity (FNC). Time-resolved or dynamic functional network connectivity (dFNC) focuses on the estimation of transient, recurring, whole-brain patterns of FNC. While most approaches in this area have attempted to capture dynamic linear correlation, we are particularly interested in whether explicitly nonlinear relationships, above and beyond linear, are present and contain unique information. This study thus proposes an approach to assess explicitly nonlinear dynamic functional network connectivity (EN dFNC) derived from the relationship among independent component analysis time courses. Linear relationships were removed at each time point to evaluate, typically ignored, explicitly nonlinear dFNC using normalized mutual information (NMI). Simulations showed the proposed method estimated explicitly nonlinearity over time, even within relatively short windows of data. We then, applied our approach on 151 schizophrenia patients, and 163 healthy controls fMRI data and found three unique, highly structured, mostly long-range, functional states that also showed significant group differences. In particular, explicitly nonlinear relationships tend to be more widespread than linear ones. Results also highlighted a state with long range connections to the visual domain, which were significantly reduced in schizophrenia. Overall, this work suggests that quantifying EN dFNC may provide a complementary and potentially valuable tool for studying brain function by exposing relevant variation that is typically ignored.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk.

Background: Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods: We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions: Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

Validation of a suite of ERP and QEEG biomarkers in a pre-competitive, industry-led study in subjects with schizophrenia and healthy volunteers.

OBJECTIVE: Complexity and lack of standardization have mostly limited the use of event-related potentials (ERPs) and quantitative EEG (QEEG) biomarkers in drug development to small early phase trials. We present results from a clinical study on healthy volunteers (HV) and patients with schizophrenia (SZ) that assessed test-retest, group differences, variance, and correlation with functional assessments for ERP and QEEG measures collected at clinical and commercial trial sites with standardized instrumentation and methods, and analyzed through an automated data analysis pipeline. METHODS: 81 HV and 80 SZ were tested at one of four study sites. Subjects were administered two ERP/EEG testing sessions on separate visits. Sessions included a mismatch negativity paradigm, a 40 Hz auditory steady-state response paradigm, an eyes-closed resting state EEG, and an active auditory oddball paradigm. SZ subjects were also tested on the Brief Assessment of Cognition (BAC), Positive and Negative Syndrome Scale (PANSS), and Virtual Reality Functional Capacity Assessment Tool (VRFCAT). RESULTS: Standardized ERP/EEG instrumentation and methods ensured few test failures. The automated data analysis pipeline allowed for near real-time analysis with no human intervention. Test-retest reliability was fair-to-excellent for most of the outcome measures. SZ subjects showed significant deficits in ERP and QEEG measures consistent with published academic literature. A subset of ERP and QEEG measures correlated with functional assessments administered to the SZ subjects. CONCLUSIONS: With standardized instrumentation and methods, complex ERP/EEG testing sessions can be reliably performed at clinical and commercial trial sites to produce high-quality data in near real-time.

Anatomical and fMRI-network comparison of multiple DLPFC targeting strategies for repetitive transcranial magnetic stimulation treatment of depression.

BACKGROUND: The efficacy of repetitive transcranial magnetic stimulation (rTMS) for depression may vary depending on the subregion stimulated within the dorsolateral prefrontal cortex (DLPFC). Clinical TMS typically uses scalp-based landmarks for DLPFC targeting, rather than individualized MRI guidance. OBJECTIVE: In rTMS patients, determine the brain systems targeted by multiple DLPFC stimulation rules by computing several surrogate measures: underlying brain targets labeled with connectivity-based atlases, subgenual cingulate anticorrelation strength, and functionally connected networks. METHODS: Forty-nine patients in a randomized controlled trial of rTMS therapy for treatment resistant major depression underwent structural and functional MRI. DLPFC rules were applied virtually using MR-image guidance. Underlying cortical regions were labeled, and connectivity with the subgenual cingulate and whole-brain computed. RESULTS: Scalp-targeting rules applied post hoc to these MRIs that adjusted for head size, including Beam F3, were comparably precise, successful in directly targeting classical DLPFC and frontal networks, and anticorrelated with the subgenual cingulate. In contrast, all rules involving fixed distances introduced variability in regions and networks targeted. The 5 cm rule targeted a transitional DLPFC region with a different connectivity profile from the adjusted rules. Seed-based connectivity analyses identified multiple regions, such as posterior cingulate and inferior parietal lobe, that warrant further study in order to understand their potential contribution to clinical response. CONCLUSION: EEG-based rules consistently targeted DLPFC brain regions with resting-state fMRI features known to be associated with depression response. These results provide a bridge from lab to clinic by enabling clinicians to relate scalp-targeting rules to functionally connected brain systems.

Electrophysiological and diffusion tensor imaging evidence of delayed corollary discharges in patients with schizophrenia.

BACKGROUND: Patients with schizophrenia (SZ) characteristically exhibit supranormal levels of cortical activity to self-induced sensory stimuli, ostensibly because of abnormalities in the neural signals (corollary discharges, CDs) normatively involved in suppressing the sensory consequences of self-generated actions. The nature of these abnormalities is unknown. This study investigated whether SZ patients experience CDs that are abnormally delayed in their arrival at the sensory cortex. METHOD: Twenty-one patients with SZ and 25 matched control participants underwent electroencephalography (EEG). Participants' level of cortical suppression was calculated as the amplitude of the N1 component evoked by a button press-elicited auditory stimulus, subtracted from the N1 amplitude evoked by the same stimulus presented passively. In the three experimental conditions, the auditory stimulus was delivered 0, 50 or 100 ms subsequent to the button-press. Fifteen SZ patients and 17 healthy controls (HCs) also underwent diffusion tensor imaging (DTI), and the fractional anisotropy (FA) of participants' arcuate fasciculus was used to predict their level of cortical suppression in the three conditions. RESULTS: While the SZ patients exhibited subnormal N1 suppression to undelayed, self-generated auditory stimuli, these deficits were eliminated by imposing a 50-ms, but not a 100-ms, delay between the button-press and the evoked stimulus. Furthermore, the extent to which the 50-ms delay normalized a patient's level of N1 suppression was linearly related to the FA of their arcuate fasciculus. CONCLUSIONS: These data suggest that SZ patients experience temporally delayed CDs to self-generated auditory stimuli, putatively because of structural damage to the white-matter (WM) fasciculus connecting the sites of discharge initiation and destination.

Persistent negative symptoms in youth at clinical high risk for psychosis: A longitudinal study.

BACKGROUND: Severity of negative symptoms has been associated with poor functioning, cognitive deficits, and defeatist beliefs in schizophrenia patients. However, one area that remains understudied is persistent negative symptoms (PNS). Negative symptoms, including PNS, have been observed in those at clinical high-risk (CHR) for psychosis. The aim of this study was to determine if PNS were associated with functioning, neurocognition, and defeatist beliefs in a CHR sample. METHOD: CHR participants (n = 764) were recruited for the North American Prodrome Longitudinal Study. Negative symptoms were rated on the Scale of Psychosis-risk Symptoms. Generalized linear mixed models for repeated measures were used to examine changes over time between and within groups (PNS vs non-PNS). RESULTS: The PNS group (n = 67) had significant deficits in functioning at baseline, 6, 12, 18, and 24-months compared to the non-PNS group (n = 673). Functioning improved over time in the non-PNS group, while functioning in the PNS group remained relatively stable and poor over a two-year period. A consistent trend emerged demonstrating higher defeatist beliefs in the PNS group; however, this result was lost when controlling for persistent depressive symptoms. There were no significant differences between the groups on neurocognition, social cognition, and transition to psychosis. CONCLUSIONS: PNS exist in youth at CHR for psychosis, resulting in significant and persistent functional impairment, which remains when controlling for persistent depressive symptoms. PNS remain even in CHR youth who do not transition to psychosis. Thus, PNS may represent an unmet therapeutic need in CHR populations for which there are currently no effective treatments.

Targeting location relates to treatment response in active but not sham rTMS stimulation.

BACKGROUND: Precise targeting of brain functional networks is believed critical for treatment efficacy of rTMS (repetitive pulse transcranial magnetic stimulation) in treatment resistant major depression. OBJECTIVE: To use imaging data from a "failed" clinical trial of rTMS in Veterans to test whether treatment response was associated with rTMS coil location in active but not sham stimulation, and compare fMRI functional connectivity between those stimulation locations. METHODS: An imaging substudy of 49 Veterans (mean age, 56 years; range, 27-78 years; 39 male) from a randomized, sham-controlled, double-blinded clinical trial of rTMS treatment, grouping participants by clinical response, followed by group comparisons of treatment locations identified by individualized fiducial markers on structural MRI and resting state fMRI derived networks. RESULTS: The average stimulation location for responders versus nonresponders differed in the active but not in the sham condition (P = .02). The average responder location derived from the active condition showed significant negative functional connectivity with the subgenual cingulate (P < .001) while the nonresponder location did not (P = .17), a finding replicated in independent cohorts of 84 depressed and 35 neurotypical participants. The responder and nonresponder stimulation locations evoked different seed based networks (FDR corrected clusters, all P < .03), revealing additional brain regions related to rTMS treatment outcome. CONCLUSION: These results provide evidence from a randomized controlled trial that clinical response to rTMS is related to accuracy in targeting the region within DLPFC that is negatively correlated with subgenual cingulate. These results support the validity of a neuro-functionally informed rTMS therapy target in Veterans.

Auditory oddball deficits in schizophrenia: an independent component analysis of the fMRI multisite function BIRN study.

Deficits in the connectivity between brain regions have been suggested to play a major role in the pathophysiology of schizophrenia. A functional magnetic resonance imaging (fMRI) analysis of schizophrenia was implemented using independent component analysis (ICA) to identify multiple temporally cohesive, spatially distributed regions of brain activity that represent functionally connected networks. We hypothesized that functional connectivity differences would be seen in auditory networks comprised of regions such as superior temporal gyrus as well as executive networks that consisted of frontal-parietal areas. Eight networks were found to be implicated in schizophrenia during the auditory oddball paradigm. These included a bilateral temporal network containing the superior and middle temporal gyrus; a default-mode network comprised of the posterior cingulate, precuneus, and middle frontal gyrus; and multiple dorsal lateral prefrontal cortex networks that constituted various levels of between-group differences. Highly task-related sensory networks were also found. These results indicate that patients with schizophrenia show functional connectivity differences in networks related to auditory processing, executive control, and baseline functional activity. Overall, these findings support the idea that the cognitive deficits associated with schizophrenia are widespread and that a functional connectivity approach can help elucidate the neural correlates of this disorder.