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Daniel H. Mathalon

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22 papers

1 author row

YNICL Journal 2023 Journal Article

Advanced brain age correlates with greater rumination and less mindfulness in schizophrenia

Samantha V. Abram
Brian J. Roach
Jessica P.Y. Hua
Laura K.M. Han
Daniel H. Mathalon
Judith M. Ford
Susanna L. Fryer

BACKGROUND: Individual variation in brain aging trajectories is linked with several physical and mental health outcomes. Greater stress levels, worry, and rumination correspond with advanced brain age, while other individual characteristics, like mindfulness, may be protective of brain health. Multiple lines of evidence point to advanced brain aging in schizophrenia (i.e., neural age estimate > chronological age). Whether psychological dimensions such as mindfulness, rumination, and perceived stress contribute to brain aging in schizophrenia is unknown. METHODS: We estimated brain age from high-resolution anatomical scans in 54 healthy controls (HC) and 52 individuals with schizophrenia (SZ) and computed the brain predicted age difference (BrainAGE-diff), i.e., the delta between estimated brain age and chronological age. Emotional well-being summary scores were empirically derived to reflect individual differences in trait mindfulness, rumination, and perceived stress. Core analyses evaluated relationships between BrainAGE-diff and emotional well-being, testing for slopes differences across groups. RESULTS: HC showed higher emotional well-being (greater mindfulness and less rumination/stress), relative to SZ. We observed a significant group difference in the relationship between BrainAge-diff and emotional well-being, explained by BrainAGE-diff negatively correlating with emotional well-being scores in SZ, and not in HC. That is, SZ with younger appearing brains (predicted age < chronological age) had emotional summary scores that were more like HC, a relationship that endured after accounting for several demographic and clinical variables. CONCLUSIONS: These data reveal clinically relevant aspects of brain age heterogeneity among SZ and point to case-control differences in the relationship between advanced brain aging and emotional well-being.

YNICL Journal 2023 Journal Article

Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study

Xing Meng
Armin Iraji
Zening Fu
Peter Kochunov
Aysenil Belger
Judy M. Ford
Sara McEwen
Daniel H. Mathalon

Brain functional networks identified from resting functional magnetic resonance imaging (fMRI) data have the potential to reveal biomarkers for brain disorders, but studies of complex mental illnesses such as schizophrenia (SZ) often yield mixed results across replication studies. This is likely due in part to the complexity of the disorder, the short data acquisition time, and the limited ability of the approaches for brain imaging data mining. Therefore, the use of analytic approaches which can both capture individual variability while offering comparability across analyses is highly preferred. Fully blind data-driven approaches such as independent component analysis (ICA) are hard to compare across studies, and approaches that use fixed atlas-based regions can have limited sensitivity to individual sensitivity. By contrast, spatially constrained ICA (scICA) provides a hybrid, fully automated solution that can incorporate spatial network priors while also adapting to new subjects. However, scICA has thus far only been used with a single spatial scale (ICA dimensionality, i.e., ICA model order). In this work, we present an approach using multi-objective optimization scICA with reference algorithm (MOO-ICAR) to extract subject-specific intrinsic connectivity networks (ICNs) from fMRI data at multiple spatial scales, which also enables us to study interactions across spatial scales. We evaluate this approach using a large N (N > 1,600) study of schizophrenia divided into separate validation and replication sets. A multi-scale ICN template was estimated and labeled, then used as input into scICA which was computed on an individual subject level. We then performed a subsequent analysis of multiscale functional network connectivity (msFNC) to evaluate the patient data, including group differences and classification. Results showed highly consistent group differences in msFNC in regions including cerebellum, thalamus, and motor/auditory networks. Importantly, multiple msFNC pairs linking different spatial scales were implicated. The classification model built on the msFNC features obtained up to 85% F1 score, 83% precision, and 88% recall, indicating the strength of the proposed framework in detecting group differences between schizophrenia and the control group. Finally, we evaluated the relationship of the identified patterns to positive symptoms and found consistent results across datasets. The results verified the robustness of our framework in evaluating brain functional connectivity of schizophrenia at multiple spatial scales, implicated consistent and replicable brain networks, and highlighted a promising approach for leveraging resting fMRI data for brain biomarker development.

YNIMG Journal 2021 Journal Article

Aperiodic measures of neural excitability are associated with anticorrelated hemodynamic networks at rest: A combined EEG-fMRI study

Michael S. Jacob
Brian J. Roach
Kaia S. Sargent
Daniel H. Mathalon
Judith M. Ford

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.

YNICL Journal 2021 Journal Article

Discriminatory experiences predict neuroanatomical changes and anxiety among healthy individuals and those at clinical high risk for psychosis

Meghan A. Collins
Yoonho Chung
Jean Addington
Carrie E. Bearden
Kristin S. Cadenhead
Barbara A. Cornblatt
Daniel H. Mathalon
Thomas H. McGlashan

Individuals face discrimination based on characteristics including race/ethnicity, gender, age, and disability. Discriminatory experiences (DE) are associated with poor psychological health in the general population and with worse outcomes among individuals at clinical high risk for psychosis (CHR). Though the brain is sensitive to stress, and brain structural change is a well-documented precursor to psychosis, potential relationships between DE and brain structure among CHR or healthy individuals are not known. This report assessed whether lifetime DE are associated with cortical thinning and clinical outcomes across time, after controlling for discrimination-related demographic factors among CHR individuals who ultimately do (N = 57) and do not convert to psychosis (N = 451), and healthy comparison (N = 208) participants in the North American Prodrome Longitudinal Study 2. Results indicate that DE are associated with thinner cortex across time in several cortical areas. Thickness in several right hemisphere regions partially mediates associations between DE and subsequent anxiety symptoms, but not attenuated positive symptoms of psychosis. This report provides the first evidence to date of an association between DE and brain structure in both CHR and healthy comparison individuals. Results also suggest that thinner cortex across time in areas linked with DE may partially explain associations between DE and cross-diagnostic indicators of psychological distress.

YNICL Journal 2020 Journal Article

Reward processing electrophysiology in schizophrenia: Effects of age and illness phase

Samantha V. Abram
Brian J. Roach
Clay B. Holroyd
Martin P. Paulus
Judith M. Ford
Daniel H. Mathalon
Susanna L. Fryer

BACKGROUND: Reward processing abnormalities may underlie characteristic pleasure and motivational impairments in schizophrenia. Some neural measures of reward processing show age-related modulation, highlighting the importance of considering age effects on reward sensitivity. We compared event-related potentials (ERPs) reflecting reward anticipation (stimulus-preceding negativity, SPN) and evaluation (reward positivity, RewP; late positive potential, LPP) across individuals with schizophrenia (SZ) and healthy controls (HC), with an emphasis on examining the effects of chronological age, brain age (i.e., predicted age based on neurobiological measures), and illness phase. METHODS: Subjects underwent EEG while completing a slot-machine task for which rewards were not dependent on performance accuracy, speed, or response preparation. Slot-machine task EEG responses were compared between 54 SZ and 54 HC individuals, ages 19 to 65. Reward-related ERPs were analyzed with respect to chronological age, categorically-defined illness phase (early; ESZ versus chronic schizophrenia; CSZ), and were used to model brain age relative to chronological age. RESULTS: Illness phase-focused analyses indicated there were no group differences in average SPN or RewP amplitudes. However, a group × reward outcome interaction revealed that ESZ differed from HC in later outcome processing, reflected by greater LPP responses following loss versus reward (a reversal of the HC pattern). While brain age estimates did not differ among groups, depressive symptoms in SZ were associated with older brain age estimates while controlling for negative symptoms. CONCLUSIONS: ESZ and CSZ did not differ from HC in reward anticipation or early outcome processing during a cognitively undemanding reward task, highlighting areas of preserved functioning. However, ESZ showed altered later reward outcome evaluation, pointing to selective reward deficits during the early illness phase of schizophrenia. Further, an association between ERP-derived brain age and depressive symptoms in SZ extends prior findings linking depression with reward-related ERP blunting. Taken together, both illness phase and age may impact reward processing among SZ, and brain aging may offer a promising, novel marker of reward dysfunction that warrants further study.

YNIMG Journal 2019 Journal Article

A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study

Barnaly Rashid
Jiayu Chen
Ishtiaque Rashid
Eswar Damaraju
Jingyu Liu
Robyn Miller
Oktay Agcaoglu
Theo G.M. van Erp

Multimodal, imaging-genomics techniques offer a platform for understanding genetic influences on brain abnormalities in psychiatric disorders. Such approaches utilize the information available from both imaging and genomics data and identify their association. Particularly for complex disorders such as schizophrenia, the relationship between imaging and genomic features may be better understood by incorporating additional information provided by advanced multimodal modeling. In this study, we propose a novel framework to combine features corresponding to functional magnetic resonance imaging (functional) and single nucleotide polymorphism (SNP) data from 61 schizophrenia (SZ) patients and 87 healthy controls (HC). In particular, the features for the functional and genetic modalities include dynamic (i. e. , time-varying) functional network connectivity (dFNC) features and the SNP data, respectively. The dFNC features are estimated from component time-courses, obtained using group independent component analysis (ICA), by computing sliding-window functional network connectivity, and then estimating subject specific states from this dFNC data using a k-means clustering approach. For each subject, both the functional (dFNC states) and SNP data are selected as features for a parallel ICA (pICA) based imaging-genomic framework. This analysis identified a significant association between a SNP component (defined by large clusters of functionally related SNPs statistically correlated with phenotype components) and time-varying or dFNC component (defined by clusters of related connectivity links among distant brain regions distributed across discrete dynamic states, and statistically correlated with genomic components) in schizophrenia. Importantly, the polygenetic risk score (PRS) for SZ (computed as a linearly weighted sum of the genotype profiles with weights derived from the odds ratios of the psychiatric genomics consortium (PGC)) was negatively correlated with the significant dFNC component, which were mostly present within a state that exhibited a lower occupancy rate in individuals with SZ compared with HC, hence identifying a potential dFNC imaging biomarker for schizophrenia. Taken together, the current findings provide preliminary evidence for a link between dFNC measures and genetic risk, suggesting the application of dFNC patterns as biomarkers in imaging genetic association study.

YNICL Journal 2019 Journal Article

Aberrant activity in conceptual networks underlies N400 deficits and unusual thoughts in schizophrenia

Michael S. Jacob
Judith M. Ford
Brian J. Roach
Vince D. Calhoun
Daniel H. Mathalon

BACKGROUND: The N400 event-related potential (ERP) is triggered by meaningful stimuli that are incongruous, or unmatched, with their semantic context. Functional magnetic resonance imaging (fMRI) studies have identified brain regions activated by semantic incongruity, but their precise links to the N400 ERP are unclear. In schizophrenia (SZ), N400 amplitude reduction is thought to reflect overly broad associations in semantic networks, but the abnormalities in brain networks underlying deficient N400 remain unknown. We utilized joint independent component analysis (JICA) to link temporal patterns in ERPs to neuroanatomical patterns from fMRI and investigate relationships between N400 amplitude and neuroanatomical activation in SZ patients and healthy controls (HC). METHODS: SZ patients (n = 24) and HC participants (n = 25) performed a picture-word matching task, in which words were either matched (APPLE→apple) by preceding pictures, or were unmatched by semantically related (in-category; IC, APPLE→lemon) or unrelated (out of category; OC, APPLE→cow) pictures, in separate ERP and fMRI sessions. A JICA "data fusion" analysis was conducted to identify the fMRI brain regions specifically associated with the ERP N400 component. SZ and HC loading weights were compared and correlations with clinical symptoms were assessed. RESULTS: JICA identified an ERP-fMRI "fused" component that captured the N400, with loading weights that were reduced in SZ. The JICA map for the IC condition showed peaks of activation in the cingulate, precuneus, bilateral temporal poles and cerebellum, whereas the JICA map from the OC condition was linked primarily to visual cortical activation and the left temporal pole. Among SZ patients, fMRI activity from the IC condition was inversely correlated with unusual thought content. CONCLUSIONS: The neural networks associated with the N400 ERP response to semantic violations depends on conceptual relatedness. These findings are consistent with a distributed network underlying neural responses to semantic incongruity including unimodal visual areas as well as integrative, transmodal areas. Unusual thoughts in SZ may reflect impaired processing in transmodal hub regions such as the precuneus, leading to overly broad semantic associations.

YNICL Journal 2019 Journal Article

Cortical abnormalities in youth at clinical high-risk for psychosis: Findings from the NAPLS2 cohort

Yoonho Chung
Dana Allswede
Jean Addington
Carrie E. Bearden
Kristin Cadenhead
Barbara Cornblatt
Daniel H. Mathalon
Thomas McGlashan

MRI scans from 378 CHR individuals and 190 healthy controls (HC) from the North American Prodrome Longitudinal Study (NAPLS2) were analyzed. Widespread smaller cortical volume was observed among CHR individuals compared with HC at baseline evaluation, particularly among the younger group (i.e., those who were 12 to 17 years of age). Moreover, the younger CHR individuals who converted or presented worsened clinical symptoms at follow-up (within 2 years) exhibited smaller surface area in rostral anterior cingulate, lateral and medial prefrontal regions, and parahippocampal gyrus relative to the younger CHR individuals who remitted or presented a stable pattern of prodromal symptoms at follow-up. In turn, poorer premorbid functioning in childhood was associated with smaller surface area in medial orbitofrontal, lateral frontal, rostral anterior cingulate, precuneus, and temporal regions. Together with our prior report, these results are consistent with the view that neuroanatomical deviance manifesting in early adolescence marks vulnerability to a form of psychosis presenting with poor premorbid adjustment, an earlier age of onset (generally prior to the age of 18 years), and poor long-term outcome.

YNICL Journal 2019 Journal Article

Group ICA for identifying biomarkers in schizophrenia: ‘Adaptive’ networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression

Mustafa S. Salman
Yuhui Du
Dongdong Lin
Zening Fu
Alex Fedorov
Eswar Damaraju
Jing Sui
Jiayu Chen

Brain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45 ± 8.9%, sensitivity 0.74 ± 0.11, specificity 0.79 ± 0.11) than STR (accuracy 67.45 ± 8.13%, sensitivity 0.65 ± 0.11, specificity 0.71 ± 0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease.

YNICL Journal 2019 Journal Article

Test-retest reliability of time-frequency measures of auditory steady-state responses in patients with schizophrenia and healthy controls

Brian J. Roach
Deepak Cyril D'Souza
Judith M. Ford
Daniel H. Mathalon

BACKGROUND: Auditory steady-state response (ASSR) paradigms have consistently demonstrated gamma band abnormalities in schizophrenia at a 40-Hz driving frequency with both electroencephalography (EEG) and magnetoencephalography (MEG). Various time-frequency measures have been used to assess the 40-Hz ASSR, including evoked power, single trial total power, phase-locking factor (PLF), and phase-locking angle (PLA). While both EEG and MEG studies have shown power and PLF ASSR measures to exhibit excellent test-retest reliability in healthy adults, the reliability of these measures in patients with schizophrenia has not been determined. METHODS: ASSRs were obtained by recording EEG data during presentation of repeated 20-Hz, 30-Hz and 40-Hz auditory click trains from nine schizophrenia patients (SZ) and nine healthy controls (HC) tested on two occasions. Similar ASSR data were collected from a separate group of 30 HC on two to three test occasions. A subset of these HC subjects had EEG recordings during two tasks, passively listening and actively attending to click train stimuli. Evoked power, total power, PLF, and PLA were calculated following Morlet wavelet time-frequency decomposition of EEG data and test-retest generalizability (G) coefficients were calculated for each ASSR condition, time-frequency measure, and subject group. RESULTS: G-coefficients ranged from good to excellent (> 0.6) for most 40-Hz time-frequency measures and participant groups, whereas 20-Hz G-coefficients were much more variable. Importantly, test-retest reliability was excellent for the various 40-Hz ASSR measures in SZ, similar to reliabilities in HC. Active attention to click train stimuli modestly reduced G-coefficients in HC relative to the passive listening condition. DISCUSSION: The excellent test-retest reliability of 40-Hz ASSR measures replicates previous EEG and MEG studies. PLA, a relatively new time-frequency measure, was shown for the first time to have excellent reliability, comparable to power and PLF measures. Excellent reliability of 40 Hz ASSR measures in SZ supports their use in clinical trials and longitudinal observational studies.

YNIMG Journal 2018 Journal Article

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis

Yuhui Du
Susanna L. Fryer
Zening Fu
Dongdong Lin
Jing Sui
Jiayu Chen
Eswar Damaraju
Eva Mennigen

Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.

YNICL Journal 2018 Journal Article

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study

Yuhui Du
Susanna L. Fryer
Dongdong Lin
Jing Sui
Qingbao Yu
Jiayu Chen
Barbara Stuart
Rachel L. Loewy

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression.

YNIMG Journal 2017 Journal Article

Multisite reliability of MR-based functional connectivity

Stephanie Noble
Dustin Scheinost
Emily S. Finn
Xilin Shen
Xenophon Papademetris
Sarah C. McEwen
Carrie E. Bearden
Jean Addington

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60–80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i. e. , subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0. 07–0. 17), but increased with increasing scan duration (ICC=0. 21–0. 36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

YNIMG Journal 2017 Journal Article

Reliability of functional magnetic resonance imaging activation during working memory in a multisite study: Clarification and implications for statistical power

Tyrone D. Cannon
Hengyi Cao
Daniel H. Mathalon
Jennifer Forsyth

In this technical note, we clarify the meaning of the generalizability-theory based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during working memory processing (Forsyth et al. , Neuroimage 2014; 97: 51-52). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i. e. , analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single site study design for statistical power, including a figure that shows sample size requirements to detect activation in two key nodes of the working memory circuitry given observed differences in reliability of measurement between single and multisite designs.

YNIMG Journal 2016 Journal Article

The effect of cognitive challenge on delay discounting

Gabriel J. Aranovich
Samuel M. McClure
Susanna Fryer
Daniel H. Mathalon

Recent findings suggest that the dorsolateral prefrontal cortex (DLPFC), a region consistently associated with impulse control, is vulnerable to transient suppression of its activity and attendant functions by excessive stress and/or cognitive demand. Using functional magnetic resonance imaging, we show that a capacity-exceeding cognitive challenge induced decreased DLPFC activity and correlated increases in the preference for immediately available rewards. Consistent with growing evidence of a link between working memory capacity and delay discounting, the effect was inversely proportional to baseline performance on a working memory task. Subjects who performed well on the working memory task had unchanged, or even decreased, delay discounting rates, suggesting that working memory ability may protect cognitive control from cognitive challenge.

YNIMG Journal 2016 Journal Article

The Function Biomedical Informatics Research Network Data Repository

David B. Keator
Theo G.M. van Erp
Jessica A. Turner
Gary H. Glover
Bryon A. Mueller
Thomas T. Liu
James T. Voyvodic
Jerod Rasmussen

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1. 5 to 4T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

YNICL Journal 2016 Journal Article

Using concurrent EEG and fMRI to probe the state of the brain in schizophrenia

Judith M. Ford
Brian J. Roach
Vanessa A. Palzes
Daniel H. Mathalon

Perceptional abnormalities in schizophrenia are associated with hallucinations and delusions, but also with negative symptoms and poor functional outcome. Perception can be studied using EEG-derived event related potentials (ERPs). Because of their excellent temporal resolution, ERPs have been used to ask when perception is affected by schizophrenia. Because of its excellent spatial resolution, functional magnetic resonance imaging (fMRI) has been used to ask where in the brain these effects are seen. We acquired EEG and fMRI data simultaneously to explore when and where auditory perception is affected by schizophrenia. Thirty schizophrenia (SZ) patients and 23 healthy comparison subjects (HC) listened to 1000 Hz tones occurring about every second. We used joint independent components analysis (jICA) to combine EEG-based event-related potential (ERP) and fMRI responses to tones. Five ERP-fMRI joint independent components (JIC) were extracted. The "N100" JIC had temporal weights during N100 (peaking at 100 ms post-tone onset) and fMRI spatial weights in superior and middle temporal gyri (STG/MTG); however, it did not differ between groups. The "P200" JIC had temporal weights during P200 and positive fMRI spatial weights in STG/MTG and frontal areas, and negative spatial weights in the nodes of the default mode network (DMN) and visual cortex. Groups differed on the "P200" JIC: SZ had smaller "P200" JIC, especially those with more severe avolition/apathy. This is consistent with negative symptoms being related to perceptual deficits, and suggests patients with avolition/apathy may allocate too few resources to processing external auditory events and too many to processing internal events.

YNIMG Journal 2014 Journal Article

Action planning and predictive coding when speaking

Jun Wang
Daniel H. Mathalon
Brian J. Roach
James Reilly
Sarah K. Keedy
John A. Sweeney
Judith M. Ford

Across the animal kingdom, sensations resulting from an animal's own actions are processed differently from sensations resulting from external sources, with self-generated sensations being suppressed. A forward model has been proposed to explain this process across sensorimotor domains. During vocalization, reduced processing of one's own speech is believed to result from a comparison of speech sounds to corollary discharges of intended speech production generated from efference copies of commands to speak. Until now, anatomical and functional evidence validating this model in humans has been indirect. Using EEG with anatomical MRI to facilitate source localization, we demonstrate that inferior frontal gyrus activity during the 300ms before speaking was associated with suppressed processing of speech sounds in auditory cortex around 100ms after speech onset (N1). These findings indicate that an efference copy from speech areas in prefrontal cortex is transmitted to auditory cortex, where it is used to suppress processing of anticipated speech sounds. About 100ms after N1, a subsequent auditory cortical component (P2) was not suppressed during talking. The combined N1 and P2 effects suggest that although sensory processing is suppressed as reflected in N1, perceptual gaps may be filled as reflected in the lack of P2 suppression, explaining the discrepancy between sensory suppression and preserved sensory experiences. These findings, coupled with the coherence between relevant brain regions before and during speech, provide new mechanistic understanding of the complex interactions between action planning and sensory processing that provide for differentiated tagging and monitoring of one's own speech, processes disrupted in neuropsychiatric disorders.

YNIMG Journal 2014 Journal Article

Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: Analysis from the North American Prodrome Longitudinal Study

Jennifer K. Forsyth
Sarah C. McEwen
Dylan G. Gee
Carrie E. Bearden
Jean Addington
Brad Goodyear
Kristin S. Cadenhead
Heline Mirzakhanian

Multi-site neuroimaging studies offer an efficient means to study brain functioning in large samples of individuals with rare conditions; however, they present new challenges given that aggregating data across sites introduces additional variability into measures of interest. Assessing the reliability of brain activation across study sites and comparing statistical methods for pooling functional data are critical to ensuring the validity of aggregating data across sites. The current study used two samples of healthy individuals to assess the feasibility and reliability of aggregating multi-site functional magnetic resonance imaging (fMRI) data from a Sternberg-style verbal working memory task. Participants were recruited as part of the North American Prodrome Longitudinal Study (NAPLS), which comprises eight fMRI scanning sites across the United States and Canada. In the first study sample (n =8), one participant from each home site traveled to each of the sites and was scanned while completing the task on two consecutive days. Reliability was examined using generalizability theory. Results indicated that blood oxygen level-dependent (BOLD) signal was reproducible across sites and was highly reliable, or generalizable, across scanning sites and testing days for core working memory ROIs (generalizability ICCs=0. 81 for left dorsolateral prefrontal cortex, 0. 95 for left superior parietal cortex). In the second study sample (n =154), two statistical methods for aggregating fMRI data across sites for all healthy individuals recruited as control participants in the NAPLS study were compared. Control participants were scanned on one occasion at the site from which they were recruited. Results from the image-based meta-analysis (IBMA) method and mixed effects model with site covariance method both showed robust activation in expected regions (i. e. dorsolateral prefrontal cortex, anterior cingulate cortex, supplementary motor cortex, superior parietal cortex, inferior temporal cortex, cerebellum, thalamus, basal ganglia). Quantification of the similarity of group maps from these methods confirmed a very high (96%) degree of spatial overlap in results. Thus, brain activation during working memory function was reliable across the NAPLS sites and both the IBMA and mixed effects model with site covariance methods appear to be valid approaches for aggregating data across sites. These findings indicate that multi-site functional neuroimaging can offer a reliable means to increase power and generalizability of results when investigating brain function in rare populations and support the multi-site investigation of working memory function in the NAPLS study, in particular.

YNIMG Journal 2011 Journal Article

Multisite reliability of cognitive BOLD data

Gregory G. Brown
Daniel H. Mathalon
Hal Stern
Judith Ford
Bryon Mueller
Douglas N. Greve
Gregory McCarthy
James Voyvodic

Investigators perform multi-site functional magnetic resonance imaging studies to increase statistical power, to enhance generalizability, and to improve the likelihood of sampling relevant subgroups. Yet undesired site variation in imaging methods could off-set these potential advantages. We used variance components analysis to investigate sources of variation in the blood oxygen level-dependent (BOLD) signal across four 3-T magnets in voxelwise and region-of-interest (ROI) analyses. Eighteen participants traveled to four magnet sites to complete eight runs of a working memory task involving emotional or neutral distraction. Person variance was more than 10 times larger than site variance for five of six ROIs studied. Person-by-site interactions, however, contributed sizable unwanted variance to the total. Averaging over runs increased between-site reliability, with many voxels showing good to excellent between-site reliability when eight runs were averaged and regions of interest showing fair to good reliability. Between-site reliability depended on the specific functional contrast analyzed in addition to the number of runs averaged. Although median effect size was correlated with between-site reliability, dissociations were observed for many voxels. Brain regions where the pooled effect size was large but between-site reliability was poor were associated with reduced individual differences. Brain regions where the pooled effect size was small but between-site reliability was excellent were associated with a balance of participants who displayed consistently positive or consistently negative BOLD responses. Although between-site reliability of BOLD data can be good to excellent, acquiring highly reliable data requires robust activation paradigms, ongoing quality assurance, and careful experimental control.

YNIMG Journal 2008 Journal Article

Chronic smoking and the BOLD response to a visual activation task and a breath hold task in patients with schizophrenia and healthy controls

Lee Friedman
Jessica A. Turner
Hal Stern
Daniel H. Mathalon
Liv C. Trondsen
Steven G. Potkin

Many psychiatric patient groups smoke heavily, but little is known regarding the effects of this habit on functional brain imaging results. The present report assesses the effect of chronic smoking on the blood oxygen level-dependent (BOLD) response to a simple visual activation (VA) task and a breath hold (BH) task in patients with schizophrenia. Eight healthy controls and twelve patients with schizophrenia were studied. Half of each group had never smoked and the other half of each group had smoked for more than 10 pack years. Responses to the VA task were assessed in the visual cortex and responses to the BH task were assessed in gray matter generally. There were four fMRI-dependent measures: (1) median percent signal change; (2) activation volume (in voxels); (3) time-to-peak of the impulse response function (IRF); and (4) time-to-trough of the IRF. All measures were tested as dependent variables in an ANCOVA with diagnosis and smoking status as crossed factors and age as a covariate. Heavy smokers had 22% larger percent signal change for the VA task and 50% larger percent signal change for the BH task. Patients had a 40% larger percent signal change for the breath hold task. Other statistically significant effects of smoking history on activation volume and the timing of the brain responses were noted. If replicated, the results may have important implications for fMRI studies comparing groups with markedly different smoking habits, such as studies comparing patients with schizophrenia, 60–90% of whom smoke, and healthy controls, who smoke with a much lower frequency.

YNIMG Journal 2005 Journal Article

Delayed hemodynamic responses in schizophrenia

Judith M. Ford
Matthew B. Johnson
Susan L. Whitfield
William O. Faustman
Daniel H. Mathalon

While there are many reports of reduced amplitude of hemodynamic responses in schizophrenia, there are no reports of delayed hemodynamic responses, in spite of event-related brain potential (ERP) evidence of slowed neural responses. Recently, Henson et al. (2002) [Henson, R. , Price, C. , Rugg, M. , Turner, R. , Friston, K. , 2002. Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations. NeuroImage, 15: 83–97] proposed a new method for testing small latency effects (<2 s) in hemodynamic responses. fMRI data were collected during a visual oddball task with infrequent (12%) targets (K) and frequent (88%) standards (X), presented every 1–3 s pseudorandomly, with 7–24 s between targets. SPM99 yielded parameter estimates for the hemodynamic response and its temporal derivative (TD). Beta images reflecting hemodynamic response magnitude to target stimuli were minimally thresholded (P < 0. 05, uncorrected), and latencies were estimated for surviving voxels using TD and hemodynamic response beta values. DSM-IV schizophrenia patients (n = 12) and sex- and age-matched healthy control subjects (n = 12) were recruited from the community. Although groups differed only minimally in activation height, hemodynamic responses were significantly delayed in basal ganglia, thalamus, and anterior cingulate in patients with schizophrenia. Psychomotor slowing reflected in reaction times to targets recorded outside the magnet was related to hemodynamic slowing in basal ganglia, anterior cingulate, thalamus, as well as left cerebellum in controls. Delays in the hemodynamic response have far-reaching implications for understanding the pathophysiology of schizophrenia from slowed neural responses to slowed substrate delivery, and depending of the degree of delay, may raise methodological issues regarding modeling hemodynamic responses in patients and controls.