Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.
We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (N= 70 and 52) and 118 healthy subjects, all group age-, sex- and ethnicity-matched. We used functional network connectivity (FNC) analysis to measure differential connectivity among 16 fMRI RSNs. First, we examined connectivity differences between probands and controls. Next, we probed these dysfunctional connections in relatives for potential endophenotypes. Network connectivity was then correlated with PANSS scores to reveal clinical relationships.
Three different network pairs were differentially connected in probands (FDR-corrected q<0.05) involving 5 individual resting-state networks: (A) Fronto/Occipital, (B) anterior Default Mode/Prefrontal, (C) Meso/Paralimbic, (D) Fronto-Temporal/Paralimbic & (E) Sensory-motor. One abnormal pair was unique to schizophrenia, (C-E), one unique to bipolar, (C-D) and one (A-B) shared. Two of these 3 combinations (A-B, C-E) were also abnormal in bipolar relatives, but none in schizophrenia relatives (non-significant trend for C-E). The Paralimbic circuit (C-D), that uniquely distinguished bipolar probands, contained multiple mood-relevant regions. Network relationship C-D correlated significantly with PANSS negative scores in bipolar probands and A-B was correlated to PANSS positive and general scores in schizophrenia.
Schizophrenia and psychotic bipolar probands share several abnormal RSN connections, but there are also unique neural network underpinnings between disorders. We identified specific connections and clinical relationships that may also be candidate psychosis endophenotypes, although these do not segregate straightforwardly with conventional diagnoses.
resting state; default mode; schizophrenia; bipolar; functional connectivity; gene; relatives
Abnormalities in the response of the orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC) to negative emotional stimuli have been reported in acutely depressed patients. However, there is a paucity of studies conducted in unmedicated individuals with major depressive disorder in remission (rMDD) to assess whether these are trait abnormalities. To address this issue, 19 medication-free rMDD individuals and 20 healthy comparison (HC) participants were scanned using functional magnetic resonance imaging while performing an implicit emotion processing task in which they labeled the gender of faces depicting negative (fearful), positive (happy) and neutral facial expressions. The rMDD and HC groups were compared using a region-of-interest approach for two contrasts: fear vs. neutral and happy vs. neutral. Relative to HC, rMDD showed reduced activation in left OFC and DLPFC to fearful (vs. neutral) faces. Right DLPFC activation to fearful (vs. neutral) faces in the rMDD group showed a significant positive correlation with duration of euthymia. The findings support deficits in left OFC and DLPFC responses to negative emotional stimuli during euthymic periods of MDD, which may reflect trait markers of the illness or a ‘scar’ due to previous depression. Recovery may also be associated with compensatory increases in right DLPFC functioning.
depression; functional magnetic resonance imaging; emotion processing
In complex genetic disorders such as schizophrenia, endophenotypes have potential utility both in identifying risk genes and in illuminating pathophysiology. This is due to their presumed status as closer in the etiopathological pathway to the causative genes than is the currently defining clinical phenomenology of the illness and thus their simpler genetic architecture than that of the full syndrome. There, many genes conferring slight individual risk are additive or epistatic (interactive) with regard to cumulative schizophrenia risk. In addition the use of endophenotypes has encouraged a conceptual shift away from the exclusive study of categorical diagnoses in manifestly ill patients, towards the study of quantitative traits in patients, unaffected relatives and healthy controls. A more recently employed strategy is thus to study unaffected first-degree relatives of schizophrenia patients, who share some of the genetic diathesis without illness-related confounds that may themselves impact fMRI task performance. Consistent with the multiple biological abnormalities associated with the disorder, many candidate endophenotypes have been advanced for schizophrenia, including measures derived from structural brain imaging, EEG, sensorimotor integration, eye movements and cognitive performance (Allen et al., 2009), but recent data derived from quantitative functional brain imaging measures present additional attractive putative endophenotypes. We will review two major, conceptually different approaches that use fMRI in this context. One, the dominant paradigm, employs defined cognitive tasks on which schizophrenia patients perform poorly as “cognitive stress tests”. The second uses very simple probes or “task-free” approaches where performance in patients and controls is equal. We explore the potential advantages and disadvantages of each method, the associated data analytic approaches and recent studies exploring their interface with the genetic risk architecture of schizophrenia.
fMRI; schizophrenia; endophenotype; intermediate phenotype; working memory; independent component analysis; default mode; resting state
Expectancy theory posits that decisions to engage in a given behavior are closely tied to expectations of the outcome of that behavior. Gambling outcome expectancies have predicted adolescent gambling and gambling problems. When high school students’ outcome expectancies were measured by Wickwire, Whelan and Meyers (2010), the Adolescent Gambling Expectancy Survey (AGES) revealed five categories of expectancies that were each predictive of gambling frequency and pathology. The present study aimed to explore if the AGES could be successfully replicated with college students. When administered to a diverse college student population, factor analyses identified five factors similar to those found in the high school sample. Several factors of the AGES were also found to predict gambling frequency and gambling problems for college students. Gambling frequency and gambling activity preference were also addressed.
college student gambling; outcome expectancies
18-25-year-olds show the highest rates of alcohol use disorders (AUD) and heavy drinking, which may have critical neurocognitive implications. Regions subserving memory may be particularly susceptible to alcohol-related impairments.
We used blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to examine the neural correlates of visual encoding and recognition among heavy drinking college students. We predicted that heavy drinkers would show worse memory performance and increased frontal/parietal activation and decreased hippocampal response during encoding.
Participants were 23 heavy drinkers and 33 demographically matched light drinkers, ages 18-20, characterized using quantity/frequency of drinking and AUD diagnosis. Participants performed a figural encoding and recognition task during fMRI. BOLD response during encoding was modeled based on whether each stimulus was subsequently recognized or forgotten (i.e., correct vs. incorrect encoding).
There were no group differences in behavioral performance. Compared to light drinkers, heavy drinkers showed: 1) greater BOLD response during correct encoding in right hippocampus/medial temporal, right dorsolateral prefrontal, left inferior frontal, and bilateral posterior parietal cortices; 2) less left inferior frontal activation and greater bilateral precuneus deactivation during incorrect encoding; and 3) less bilateral insula response during correct recognition (clusters >10,233ul, p<.05 whole-brain).
This is the first investigation of the neural substrates of figural memory among heavy drinking older adolescents. Heavy drinkers demonstrated compensatory hyperactivation of memory-related areas during correct encoding, greater deactivation of default mode regions during incorrect encoding, and reduced recognition-related response. Results could suggest use of different encoding and recognition strategies among heavy drinkers.
Alcohol; Adolescent; Young Adult; fMRI; Learning; Memory; Cognition
One application of imaging genomics is to explore genetic variants associated with brain structure and function, presenting a new means of mapping genetic influences on mental disorders. While there is growing interest in performing genome-wide searches for determinants, it remains challenging to identify genetic factors of small effect size, especially in limited sample sizes. In an attempt to address this issue, we propose to take advantage of a priori knowledge, specifically to extend parallel independent component analysis (pICA) to incorporate a reference (pICA-R), aiming to better reveal relationships between hidden factors of a particular attribute. The new approach was first evaluated on simulated data for its performance under different configurations of effect size and dimensionality. Then pICA-R was applied to a 300-participant (140 schizophrenia (SZ) patients versus 160 healthy controls) dataset consisting of structural magnetic resonance imaging (sMRI) and single nucleotide polymorphism (SNP) data. Guided by a reference SNP set derived from ANK3, a gene implicated by the Psychiatric Genomic Consortium SZ study, pICA-R identified one pair of SNP and sMRI components with a significant loading correlation of 0.27 (p = 1.64×10−6). The sMRI component showed a significant group difference in loading parameters between patients and controls (p = 1.33×10−15), indicating SZ-related reduction in gray matter concentration in prefrontal and temporal regions. The linked SNP component also showed a group difference (p = 0.04) and was predominantly contributed to by 1,030 SNPs. The effect of these top contributing SNPs was verified using association test results of the Psychiatric Genomic Consortium SZ study, where the 1,030 SNPs exhibited significant SZ enrichment compared to the whole genome. In addition, pathway analyses indicated the genetic component majorly relating to neurotransmitter and nervous system signaling pathways. Given the simulation and experiment results, pICA-R may prove a promising multivariate approach for use in imaging genomics to discover reliable genetic risk factors under a scenario of relatively high dimensionality and small effect size.
parallel ICA with reference; sMRI; SNP; schizophrenia; multivariate; semi-blind
Functional connectivity examines temporal statistical dependencies among distant brain regions by means of seed-based analysis or independent component analysis (ICA). Spatial ICA also makes it possible to investigate functional connectivity at the network level, termed functional network connectivity (FNC). The dynamics of each network (ICA component) which may consist of several remote regions is described by the ICA time-course of that network; hence FNC studies statistical dependencies among ICA time-courses. In this paper, we compare comprehensively FNC in the resting state and during performance of an auditory oddball (AOD) task in 28 healthy subjects on relevant (non-artifactual) brain networks. The results show global FNC decrease during the performance of the task. Also, we show that specific networks enlarge and/or demonstrate higher activity during the performance of the task. The results suggest that performing an active task like AOD may be facilitated by recruiting more neurons and higher activation of related networks rather than collaboration among different brain networks. We also evaluated the impact of temporal filtering on FNC analyses. Results showed that the final results are not significantly affected by filtering.
fMRI; Functional network connectivity; Independent component analysis
Abnormal function in reward circuitry in cocaine addiction could predate drug use as a risk factor, follow drug use as a consequence of substance-induced alterations, or both.
We used a functional MRI Monetary Incentive Delay Task (MIDT) to investigate reward-loss neural response differences among current cocaine users (N=42), former cocaine users (N=35) and healthy control subjects (N=47). Subjects also completed psychological measures and tasks related to impulsivity and reward.
We found various reward processing-related group differences in several MIDT phases. Across task phases we found a “control>current user>former user” fMRI BOLD activation pattern, except for loss outcome, where former compared to current cocaine users activated ventral tegmental area (VTA) more robustly. We also found regional prefrontal activation differences during loss anticipation between cocaine-using groups. Both groups of cocaine users scored higher than controls on impulsivity, compulsivity and reward-punishment sensitivity factors. In addition, impulsivity-related factors correlated positively with BOLD activation in amygdala and negatively with anterior cingulate activation during loss anticipation.
Compared to healthy subjects, both former and current cocaine users displayed abnormal brain activation patterns during MIDT performance. Both cocaine groups differed similarly from healthy controls, but differences between former and current cocaine users were localized to the VTA during loss outcome and to prefrontal regions during loss anticipation, suggesting that long-term cocaine abstinence does not normalize most reward circuit abnormalities. Elevated impulsivity-related factors that relate to loss processing in current and former cocaine users suggest that these tendencies and relationships may pre-exist cocaine addiction.
Monetary incentive delay task; Cocaine; Monetary reward; Monetary loss; Impulsivity; Addiction
Suicide represents a major health problem world-wide. Nevertheless, the understanding of the neurobiological underpinnings of suicidal behavior remains far from complete. We compared suicide attempters to non-attempters, and high vs. low lethality attempters, to identify brain regions associated with suicidal behavior in patients with psychotic disorders. 489 individuals with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder I and 262 healthy controls enrolled in the B-SNIP study were studied. Groups were compared by attempt history and the highest medical lethality of previous suicide attempts. 97 patients had a history of a high lethality attempt, 51 of a low lethality attempt and 341 had no attempt history. Gray matter volumes were obtained from 3T structural MRI scans using FreeSurfer. ANCOVAs were used to examine differences between groups, followed by Hochberg multiple comparison correction. Compared to non-attempters, attempters had significantly less gray matter volume in bilateral inferior temporal and superior temporal cortices, left superior parietal, thalamus and supramarginal regions, right insula, superior frontal and rostral middle frontal regions. Among attempters, a history of high lethality attempts was associated with significantly smaller volumes in the left lingual gyrus and right cuneus. Compared to non-attempters, low lethality attempters had significant decreases in the left supramarginal gyrus, thalamus and the right insula. Structural brain abnormalities may distinguish suicide attempters from non-attempters and high from low lethality attempters among individuals with psychotic disorders. Regions in which differences were observed are part of neural circuitries that mediate inhibition, impulsivity and emotion, visceral, visual and auditory perception.
imaging; suicide; schizophrenia
Animal studies indicate that different functional networks (FNs), each with a unique timecourse, may overlap at common brain regions. For understanding how different FNs overlap in the human brain and how the timecourses of overlapping FNs are modulated by cognitive tasks, we applied spatial independent component analysis (sICA) to functional magnetic resonance imaging (fMRI) data. These data were acquired from healthy participants while they performed a visual task with parametric loads of attention and working memory. SICA identified a total of 14 FNs, and they showed different extents of overlap at a majority of brain regions exhibiting any functional activity. More FNs overlapped at the higher-order association cortex including the anterior and posterior cingulate, precuneus, insula, and lateral and medial frontoparietal cortex (FPC) than at the primary sensorimotor cortex. Furthermore, overlapping FNs exhibited concurrent but different task-related modulations of timecourses. FNs showing task-related up- vs. down-modulation of timecourses overlapped at both the lateral and medial FPC and subcortical structures including the thalamus, striatum, and midbrain ventral tegmental area (VTA). Such task-related, concurrent, but opposite changes in timecourses in the same brain regions may not be detected by current analyses based on General-Linear-Model (GLM). The present findings indicate that multiple cognitive processes may associate with common brain regions and exhibit simultaneous but different modulations in timecourses during cognitive tasks.
fMRI; neuroimaging; attention; working memory; cognitive function; Independent Component Analysis
Impaired inhibition of prepotent motor response may represent an important risk factor for alcoholism. Alcohol use may also increase impulsive behavior, including impaired response inhibition. Little is known about the brain function underlying response inhibition among college-age drinkers based on their drinking patterns, despite college-age drinkers demonstrating high rates of alcohol-use disorders. Our major objective was to compare behavior and associated brain activity measured with fMRI during a response-inhibition task in matched heavy- and light-alcohol-drinking college students. Participants were light (N=36) and heavy (N=56) drinkers, aged 18–20 years. We characterized blood oxygen level-dependent (BOLD) responses, while participants performed an fMRI Go/No-Go task to quantify inhibitory behavior and brain activity. Behaviorally, group performance differences were observed for Go correct-hit and No-Go false-alarm reaction times with increased reaction times in heavy compared with light drinkers. During fMRI No-Go correct rejections, light drinkers exhibited greater BOLD response than did heavy drinkers in left supplementary motor area (SMA), bilateral parietal lobule, right hippocampus, bilateral middle frontal gyrus, left superior temporal gyrus, and cingulate gyrus/anterior cingulate cortex (Brodmann area 24). Group differences in Go/No-Go-related regional activations correlated with alcohol- and impulsivity-related measures. These findings suggest that heavy alcohol drinkers may have dysfunction in brain regions underlying attention and response inhibition, leading to diminished abilities to suppress prepotent responding. The extent to which these tendencies relate to impulsive decision-making and behaviors in real-life settings and may guide intervention development warrants additional investigation.
addiction & substance abuse; alcohol & alcoholism; alcoholism; psychiatry & behavioral sciences; psychopharmacology; fMRI; alcohol; adolescence; Go/No-Go task; college students
We present a modular, high performance, open-source database system that incorporates popular neuroimaging database features with novel peer-to-peer sharing, and a simple installation. An increasing number of imaging centers have created a massive amount of neuroimaging data since fMRI became popular more than 20 years ago, with much of that data unshared. The Neuroinformatics Database (NiDB) provides a stable platform to store and manipulate neuroimaging data and addresses several of the impediments to data sharing presented by the INCF Task Force on Neuroimaging Datasharing, including 1) motivation to share data, 2) technical issues, and 3) standards development. NiDB solves these problems by 1) minimizing PHI use, providing a cost effective simple locally stored platform, 2) storing and associating all data (including genome) with a subject and creating a peer-to-peer sharing model, and 3) defining a sample, normalized definition of a data storage structure that is used in NiDB. NiDB not only simplifies the local storage and analysis of neuroimaging data, but also enables simple sharing of raw data and analysis methods, which may encourage further sharing.
Database; Neuroinformatics; Neuroimaging; Pipeline
Schizophrenia and bipolar disorder share overlapping symptoms and risk genes. Shared aberrant functional connectivity is hypothesized in both disorders and in relatives.
We investigated resting state functional MRI (fMRI) in 70 schizophrenia and 64 psychotic bipolar probands, their respective first-degree relatives (N = 70 and 52) and 118 healthy subjects. We used independent component analysis (ICA) to identify components representing various resting state networks and assessed spatial aspects of functional connectivity within all networks. We first investigated group differences using five-level, one-way analysis of covariance (ANCOVA), followed by post-hoc t-tests within regions displaying ANCOVA group differences and correlation of such functional connectivity measures with symptom ratings to examine clinical relationships.
Seven different networks revealed abnormalities (five-level one-way ANCOVA, family-wise error correction p < 0.05): (A) fronto-occipital, (B) midbrain/cerebellum, (C) frontal/thalamic/basal ganglia, (D) meso/paralimbic, (E) posterior default mode network, (F) fronto-temporal/paralimbic and (G) sensorimotor networks. Abnormalities in networks B and F were unique to schizophrenia probands only. Furthermore, abnormalities in networks D and E were common to both patient groups. Finally, networks A, C and G showed abnormalities shared by probands and their relative groups. Negative correlation with Positive and Negative Syndrome Scale (PANSS) negative and positive scores were found in regions within network C and F respectively, and positive correlation with PANSS negative scores was found in regions in network D among schizophrenia probands only.
Schizophrenia, psychotic bipolar probands and their relatives share both unique and overlapping within-network brain connectivity abnormalities, revealing potential psychosis endophenotypes.
Bipolar; endophenotype; relatives; resting state; schizophrenia; within-network connectivity
Individuals family-history positive (FHP) for alcoholism have increased risk for the disorder, which may be mediated by intermediate behavioral traits such as impulsivity. Given the sex differences in the risk for and clinical presentation of addictive disorders, risk for addiction may be differentially mediated by impulsivity within FHP males and females. FHP (N=28) and family-history negative (FHN, N=31) healthy, non-substance-abusing adults completed an fMRI Go/No-Go task and were assessed on impulsivity and alcohol use. Effects of family history and sex were investigated as were associations between neural correlates of impulse control and out-of-scanner measures of impulsivity and alcohol use. FHP individuals showed greater activation in the left anterior insula and inferior frontal gyrus during successful inhibitions, an effect that was driven primarily by FHP males. Higher self-reported impulsivity and behavioral discounting impulsivity, but not alcohol use measures, were associated with greater BOLD signal in the region that differentiated the FHP and FHN groups. Impulsivity factors were associated with alcohol use measures across the FHP and FHN groups. These findings are consistent with increased risk for addiction among FHP individuals being conferred through disrupted function within neural systems important for impulse control.
addiction; addiction & substance abuse; alcohol & alcoholism; biological psychiatry; family history of alcoholism; imaging; clinical or preclinical; impulsivity; insula; sex differences; impulsivity; family history of alcoholism; insula; inferior frontal gyrus (IFG); addiction; sex differences.
We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups.
We assessed 576 adults (340 community controls, 126 with bipolar disorder, and 110 with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning.
The six-factor model provided an excellent fit for all three groups [community controls root mean square error of approximation (RMSEA) < 0.048 and comparative fit index (CFI) = 0.99; adults with bipolar disorder RMSEA = 0.071 and CFI = 0.99; and adults with schizophrenia RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness-of-fit. Multi-group CFA results supported factor invariance across the three groups.
Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders.
bipolar disorder; cognition; confirmatory factor analysis; invariance; latent variable analysis; neuropsychology; schizophrenia
Several lines of evidence indicate that white matter integrity is compromised in bipolar disorder, but the nature, extent, and biological causes remain elusive. To determine the extent to which white matter deficits in bipolar disorder are familial, the authors investigated white matter integrity in a large sample of bipolar patients, unaffected siblings, and healthy comparison subjects.
The authors collected diffusion imaging data for 64 adult bipolar patients, 60 unaffected siblings (including 54 discordant sibling pairs), and 46 demographically matched comparison subjects. Fractional anisotropy was compared between the groups using voxel-wise tract-based spatial statistics and by extracting mean fractional anisotropy from 10 regions of interest. Additionally, intra-class correlation coefficients were calculated between the sibling pairs as an index of familiality.
Widespread fractional anisotropy reductions in bipolar patients (>40,000 voxels) and more subtle reductions in their siblings, mainly restricted to the corpus callosum, posterior thalamic radiations, and left superior longitudinal fasciculus (>2,000 voxels) were observed. Similarly, region-of-interest analysis revealed significant reductions in most white matter regions in patients. In siblings, fractional anisotropy in the posterior thalamic radiation and the forceps was nominally reduced. Significant between-sibling correlations were found for mean fractional anisotropy across the tract-based spatial statistic skeleton, within significant clusters, and within nearly all regions of interest.
These findings emphasize the relevance of white matter to neuropathology and familiality of bipolar disorder and encourage further use of white matter integrity markers as endophenotypes in genetic studies.
Individuals with cocaine dependence often evidence poor cognitive control. The purpose of this exploratory study was to investigate networks of functional connectivity underlying cognitive control in cocaine dependence and examine the relationship of the networks to the disorder and its treatment. Independent component analysis (ICA) was applied to fMRI data to investigate if regional activations underlying cognitive control processes operate in functional networks, and whether these networks relate to performance and treatment outcome measures in cocaine dependence. Twenty patients completed a Stroop task during fMRI prior to entering outpatient treatment and were compared to 20 control participants. ICA identified five distinct functional networks related to cognitive control interference events. Cocaine-dependent patients displayed differences in performance-related recruitment of three networks. Reduced involvement of a “top-down” fronto-cingular network contributing to conflict monitoring correlated with better treatment retention. Greater engagement of two “bottom-up” subcortical and ventral prefrontal networks related to cue-elicited motivational processing correlated with abstinence during treatment. The identification of subcortical networks linked to cocaine abstinence and cortical networks to treatment retention suggests that specific circuits may represent important, complementary targets in treatment development for cocaine dependence.
fMRI; substance use disorders; cocaine dependence; cognitive control; cognitive behavioral therapy
Patients meeting criteria for the risk syndrome for psychosis have treatment needs including positive and negative symptoms and cognitive impairment. These features could potentially respond to NMDA glycine-site agonists. The present objective was to determine which symptoms or domains of cognition promise to show the greatest response to glycine in risk syndrome patients. We conducted two short-term pilot studies of glycine used without adjunctive antipsychotic medication. In the first trial, 10 risk syndrome subjects received open-label glycine at doses titrated to 0.8 g/kg/d for 8 weeks, followed by discontinuation and 16 weeks of evaluation for durability of effects. In the second, 8 subjects were randomized to double-blind glycine vs. placebo for 12 weeks, followed by open-label glycine for another 12 weeks. Patients were evaluated every 1–2 weeks with the Scale Of Psychosis-risk Symptoms (SOPS) and before and after treatment with a neurocognitive battery. Within-group and between-group effect sizes were calculated. Effect sizes were large for positive (open-label within-group 1.10, double-blind between-group –1.11) and total (–1.39 and –1.15) symptoms and medium-to-large (–0.74 and –0.79) for negative symptoms. Medium or large effect sizes were also observed for several neurocognitive measures in the open-label study, although data were sparse. No safety concerns were identified. We conclude that glycine was associated with reduced symptoms with promising effect sizes in two pilot studies and a possibility of improvement in cognitive function. Further studies of agents that facilitate NMDA receptor function in risk syndrome patients are supported by these preliminary findings.
Glycine; NMDA receptor; Risk syndrome; Prodrome; Psychosis; Schizophrenia
An important step in obesity research involves identifying neurobiological underpinnings of nonfood reward processing unique to specific subgroups of obese individuals.
Nineteen obese individuals seeking treatment for binge eating disorder (BED) were compared with 19 non-BED obese individuals (OB) and 19 lean control subjects (LC) while performing a monetary reward/loss task that parses anticipatory and outcome components during functional magnetic resonance imaging. Differences in regional activation were investigated in BED, OB, and LC groups during reward/loss prospect, anticipation, and notification.
Relative to the LC group, the OB group demonstrated increased ventral striatal and ventromedial prefrontal cortex activity during anticipatory phases. In contrast, the BED group relative to the OB group demonstrated diminished bilateral ventral striatal activity during anticipatory reward/loss processing. No differences were observed between the BED and LC groups in the ventral striatum.
Heterogeneity exists among obese individuals with respect to the neural correlates of reward/loss processing. Neural differences in separable groups with obesity suggest that multiple, varying interventions might be important in optimizing prevention and treatment strategies for obesity.
Binge eating disorder; fMRI; inferior frontal gyrus; insula; obesity; reward; ventral striatum
Multi-modal fusion is an effective approach to better understand brain diseases. However, most such instances have been limited to pair-wise fusion; because there are often more than two imaging modalities available per subject, there is a need for approaches that can combine multiple datasets optimally. In this paper, we extended our previous two-way fusion model called “multimodal CCA +joint ICA”, to three or N way fusion, that enables robust identification of correspondence among N data types and allows one to investigate the important question of whether certain disease risk factors are shared or distinct across multiple modalities. We compared “mCCA+jICA” with its alternatives in a 3-way fusion simulation and verified its advantages in both decomposition accuracy and modal linkage detection. We also applied it to real functional Magnetic Resonance Imaging (fMRI)-Diffusion Tensor Imaging (DTI) and structural MRI fusion to elucidate the abnormal architecture underlying schizophrenia (n=97) relative to healthy controls (n=116). Both modality-common and modality-unique abnormal regions were identified in schizophrenia. Specifically, the visual cortex in fMRI, the anterior thalamic radiation (ATR) and forceps minor in DTI, and the parietal lobule, cuneus and thalamus in sMRI were linked and discriminated between patients and controls. One fMRI component with regions of activity in motor cortex and superior temporal gyrus individually discriminated schizophrenia from controls. Finally, three components showed significant correlation with duration of illness (DOI), suggesting that lower gray matter volumes in parietal, frontal, temporal lobe and cerebellum are associated with increased DOI, along with white matter disruption in ATR and cortico-spinal tracts. Findings suggest that the identified fractional anisotropy changes may relate to the corresponding functional/structural changes in brain that are thought to play a role in the clinical expression of schizophrenia. The proposed “mCCA +jICA” method showed promise for elucidating the joint or coupled neuronal abnormalities underlying mental illnesses and improves our understanding of the disease process.
Multimodal Fusion; mCCA+jICA; fMRI; DTI; sMRI; schizophrenia; N-way fusion
Semantic association retrieval task (SORT) requires participants to indicate whether word pairs recall a third object, e.g. ‘honey’ and ‘stings’ activates ‘bees’. We have previously shown that individuals with schizophrenia with more severe positive symptoms tend to report associations between unrelated word pairs than healthy controls; schizophrenia individuals with more severe negative symptoms tend to fail to report associations between related word pairs. This over-retrieval and under-retrieval on SORT correlates with functional magnetic resonance imaging (fMRI) activity in inferior parietal lobule (IPL). To examine the suitability of SORT as an endophenotype for schizophrenia, we examined SORT performance and activity across multiple stages of the illness: chronic, relapse, first episode. We also examine SORT performance and activity in unaffected relatives. SORT performance and fMRI activity in schizophrenia-first episode, schizophrenia-chronic and schizophrenia-relapse were significantly impaired relative to healthy controls and unaffected relatives. Schizophrenia-chronic and schizophrenia-relapse participants showing more severe PANSS-positive and -general symptoms showed larger SORT impairments. For schizophrenia-first episode more severe negative symptoms were related to lower IPL activation, consistent with previous results showing that negative symptoms are among the first to emerge in the schizophrenia prodrome and that more severe symptoms in the first episode predict worse future outcomes. Unaffected relatives showed no impairments on SORT performance or fMRI activity relative to healthy controls, which is incompatible with the concept of SORT as an endophenotype for schizophrenia, but is consistent with the concept of SORT as a potential schizophrenia biomarker.
semantic association; biomarker; fMRI; formal thought disorder; positive and negative symptoms
Understanding genetic influences on both healthy and disordered brain function is a major focus in psychiatric neuroimaging. We utilized task-related imaging findings from an fMRI auditory oddball task known to be robustly associated with abnormal activation in schizophrenia, to investigate genomic factors derived from multiple single nucleotide polymorphisms (SNP’s) from genes previously shown to be associated with schizophrenia. Our major aim was to investigate the relationship of these genomic factors to normal/abnormal brain functionality between controls and schizophrenia patients. We studied a Caucasian-only sample of 35 healthy controls and 31 schizophrenia patients. All subjects performed an auditory oddball task, which consists of detecting an infrequent sound within a series of frequent sounds. Each subject was characterized on 24 different SNP markers spanning multiple risk genes previously associated with schizophrenia. We used a recently developed technique named parallel independent component analysis (para-ICA) to analyze this multimodal dataset (Liu et al., 2008). The method aims to identify simultaneously independent components of each modality (functional imaging, genetics) and the relationships between them. We detected 3 fMRI components significantly correlated with two distinct gene components. The fMRI components, along with their significant genetic profile (dominant SNP) correlations were as follows: 1) Inferior frontal- anterior/posterior cingulate-thalamus-caudate with SNPs from Brain derived neurotropic factor (BDNF) & Dopamine Transporter, (DAT) [r=−0.51; p<0.0001], 2) Superior/middle temporal gyrus-Cingulate-premotor with SLC6A4_PR and SLC6A4_PR_AG (Serotonin transporter promoter; 5HTTLPR) [r=0.27; p=0.03], 3) Default Mode-fronto-temporal gyrus with Brain derived neurotropic factor & Dopamine Transporter (BDNF, DAT) [r=−0.25; p=0.04]. Functional components comprised taskrelevant regions (including PFC, ACC, STG and MTG) frequently identified as abnormal in schizophrenia. Further, gene-fMRI combinations 1 (Z=1.75; p=0.03), 2 (Z=1.84;p=0.03) and 3 (Z=1.67; p=0.04) listed above showed significant differences between controls and patients, based on their correlated loading coefficients. We demonstrate a framework to identify interactions between “clusters” of brain function and of genetic information. Our results reveal the effect/influence of specific interactions, (perhaps epistastatic in nature), between schizophrenia risk genes on imaging endophenotypes representing attention/working memory and goal directed related brain function, thus establishing a useful methodology to probe multivariate genotype-phenotype relationships.
auditory oddball; DAT; BDNF; fMRI; gene; parallel ICA; multivariate; 5HTTLPR
Pathophysiological models of bipolar disorder postulate that mood dysregulation arises from fronto-limbic dysfunction, marked by reduced prefrontal cortex (PFC) inhibitory control. This may occur both due to disruptions within PFC networks and abnormal inhibition over subcortical structures involved in emotional processing. However, no study has examined global PFC dysconnectivity in bipolar disorder and tested if regions with within-PFC dysconnectivity also exhibit fronto-limbic connectivity deficits. Further, no study has investigated whether such connectivity disruptions differ for bipolar patients with psychosis history, who may exhibit a more severe clinical course.
We collected resting-state fMRI at 3T in 68 remitted bipolar I patients (34 with psychosis history) and 51 demographically-matched healthy participants. We employed a recently developed Global Brain Connectivity method, restricted to PFC (rGBC). We also independently tested connectivity between anatomically-defined amygdala and PFC.
Bipolar patients exhibited reduced medial PFC (mPFC) rGBC, increased amygdala-MPFC connectivity, and reduced connectivity between amygdala and dorso-lateral PFC. All effects were driven by psychosis history. Moreover, the magnitude of observed effects was significantly associated with lifetime psychotic symptom severity.
This convergence between rGBC, seed-based amygdala findings and symptom severity analyses highlights that mPFC, a core emotion regulation region, exhibits both within-PFC dysconnectivity and connectivity abnormalities with limbic structures in bipolar illness. Furthermore, lateral PFC dysconnectivity in patients with psychosis history converges with published work in schizophrenia, indicating possible shared risk factors. Observed dysconnectivity in remitted patients suggests a bipolar trait characteristic and may constitute a risk factor for phasic features of the disorder.
bipolar disorder; prefrontal cortex; amygdala; connectivity; resting-state; psychosis
The Semantic Object Retrieval Task (SORT) requires participants to indicate whether word pairs recall a third object. Schizophrenia individuals (SZ) tend to report associations between non-associated word pairs; this over-retrieval is related to formal thought disorder (FTD). Since semantic memory impairments and psychosis are not specific to SZ but are also found in bipolar disorder (BP), we examined whether SORT impairments and their relationship to symptoms is also present in BP.
Participants (n=239; healthy controls (HC)=133; BP=32; SZ=74) completed SORT while undergoing fMRI scanning.
Retrieval accuracy negatively correlated with negative symptoms and No-Retrieval accuracy negatively correlated with FTD severity in SZ but not BP. Retrieval vs. No-Retrieval trials activated a distributed fronto-parieto-temporal network; bilateral inferior parietal lobule (IPL) activity was larger in HC vs. SZ and HC vs. BP, with no difference in SZ vs. BP. Right IPL activity positively correlated with positive and general psychosis symptoms in SZ but not BP.
SZ reported more associations between unrelated word pairs than HC; this over- retrieval increased with FTD severity. SZ were also more likely to fail to find associations between related word pairs; this under-retrieval increased with negative symptom severity. fMRI-symptom correlations in IPL in SZ are consistent with arguments that IPL abnormality relates to loosening of associations in SZ. By comparison, BP showed intermediate impairments on SORT, uncorrelated with symptoms, suggesting that the relationship between SORT performance, fMRI activity and psychotic symptoms is schizophrenia-specific.
semantic association retrieval task; schizophrenia; bipolar disorder; formal thought disorder; positive symptoms; fMRI
Functional magnetic resonance imaging (fMRI) studies indicate that the brain organizes its activity into multiple functional networks (FNs) during either resting condition or task-performance. However, the functions of these FNs are not fully understood yet.
To investigate the operation of these FNs, spatial independent component analysis (sICA) was used to extract FNs from fMRI data acquired from healthy participants performing a visual task with two levels of attention and working memory load. The task-related modulations of extracted FNs were assessed. A group of FNs showed increased activity at low-load conditions and reduced activity at high-load conditions. These FNs together involve the left lateral frontoparietal cortex, insula, and ventromedial prefrontal cortex. A second group of FNs showed increased activity at high-load conditions and reduced activity at low-load conditions. These FNs together involve the intraparietal sulcus, frontal eye field, lateral frontoparietal cortex, insula, and dorsal anterior cingulate, bilaterally. Though the two groups of FNs showed opposite task-related modulations, they overlapped extensively at both the lateral and medial frontoparietal cortex and insula. Such an overlap of FNs would not likely be revealed using standard general-linear-model-based analyses.
By assessing task-related modulations, this study differentiated the functional roles of overlapping FNs. Several FNs including the left frontoparietal network are implicated in task conditions of low attentional load, while another set of FNs including the dorsal attentional network is implicated in task conditions involving high attentional demands.