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.
We examined performance and fMRI activity in participants (n=235) aged 17-81yrs on a non-verbal recognition memory task, figural memory. Reaction time, error rate and response bias measures indicated that the youngest and oldest participants were faster, made fewer errors and showed a more conservative response bias than participants in the median age ranges. Encoding and Recognition phases activated a distributed bilateral network encompassing prefrontal, subcortical, lateral and medial temporal and occipital regions. Activation during Encoding phase did not correlate with age. During Recognition, task-related activation for correctly identified targets (Hit-Targets) correlated linearly positively with age; non-task related activity correlated negative quadratically with age. During correctly identified distractors (Hit-Distractors) activity in task-related regions correlated positive linearly with age, non-task activity showed positive and negative quadratic relationships with age. Missed-Targets activity did not correlate with age. We concluded that figural memory performance and fMRI activity during Recognition but not Encoding was affected both by continued maturation of the brain in the early 20s and compensatory recruitment of additional brain regions during recognition memory in oldage.
healthy aging; fMRI; non-verbal memory; figural memory
Psychopathy is believed to be associated with brain abnormalities in both paralimbic (i.e., orbitofrontal cortex, insula, temporal pole, parahippocampal gyrus, posterior cingulate) and limbic (i.e., amygdala, hippocampus, anterior cingulate) regions. Recent structural imaging studies in both community and prison samples are beginning to support this view. Sixty six participants, recruited from community corrections centers, were administered the Hare Psychopathy Checklist Revised (PCL R), and underwent magnetic resonance imaging (MRI). Voxel based morphometry was used to test the hypothesis that psychopathic traits would be associated with gray matter reductions in limbic and paralimbic regions. Effects of lifetime drug and alcohol use on gray matter volume were covaried. Psychopathic traits were negatively associated with gray matter volumes in right insula and right hippocampus. Additionally, psychopathic traits were positively associated with gray matter volumes in bilateral orbital frontal cortex and right anterior cingulate. Exploratory regression analyses indicated that gray matter volumes within right hippocampus and left orbital frontal cortex combined to explain 21.8% of the variance in psychopathy scores. These results support the notion that psychopathic traits are associated with abnormal limbic and paralimbic gray matter volume. Furthermore, gray matter increases in areas shown to be functionally impaired suggests that the structure function relationship may be more nuanced than previously thought.
structural MRI; voxel based morphometry (VBM); paralimbic cortex; limbic structures; substance use
Autism Spectrum Disorders (ASDs) are characterized by core deficits in social functions. Two theories have been suggested to explain these deficits: mind-blindness theory posits impaired mentalizing processes (i.e. decreased ability for establishing a representation of others' state of mind), while social motivation theory proposes that diminished reward value for social information leads to reduced social attention, social interactions, and social learning. Mentalizing and motivation are integral to typical social interactions, and neuroimaging evidence points to independent brain networks that support these processes in healthy individuals. However, the simultaneous function of these networks has not been explored in individuals with ASDs. We used a social, interactive fMRI task, the Domino game, to explore mentalizing- and motivation-related brain activation during a well-defined interval where participants respond to rewards or punishments (i.e. motivation) and concurrently process information about their opponent's potential next actions (i.e. mentalizing). Thirteen individuals with high-functioning ASDs, ages 12–24, and 14 healthy controls played fMRI Domino games against a computer-opponent and separately, what they were led to believe was a human-opponent. Results showed that while individuals with ASDs understood the game rules and played similarly to controls, they showed diminished neural activity during the human-opponent runs only (i.e. in a social context) in bilateral middle temporal gyrus (MTG) during mentalizing and right Nucleus Accumbens (NAcc) during reward-related motivation (Pcluster < 0.05 FWE). Importantly, deficits were not observed in these areas when playing against a computer-opponent or in areas related to motor and visual processes. These results demonstrate that while MTG and NAcc, which are critical structures in the mentalizing and motivation networks, respectively, activate normally in a non-social context, they fail to respond in an otherwise identical social context in ASD compared to controls. We discuss implications to both the mind-blindness and social motivation theories of ASD and the importance of social context in research and treatment protocols.
•We used an fMRI Domino game to map social networks in high-functioning ASDs.•ASDs did not show MTG increased activation during mentalizing in social context.•ASDs did not show NAcc increased activation for processing reward in social context.•Activation deficits were specific to brain areas involved in social processes.•Results support both the mind-blindness and the social motivation theories of ASDs.
Theory of mind; Reward; Nucleus accumbens; Middle temporal gyrus
Background: The default mode network (DMN) is a set of brain regions typically activated at rest and suppressed during extrinsic cognition. Schizophrenia has been associated with deficient DMN suppression, though the extent to which DMN dysfunction predates psychosis onset is unclear. This study examined DMN suppression during working memory (WM) performance in youth at clinical high-risk (CHR) for psychosis, early schizophrenia (ESZ) patients, and healthy controls (HC). We hypothesized that the DMN would show load-dependent suppression during WM retrieval in HC but not in ESZ, with CHR participants showing an intermediate pattern.
Methods: fMRI data were collected from CHR (n = 32), ESZ (n = 22), and HC (n = 54) participants, ages 12–30. DMN regions were defined via seed-based connectivity analysis of resting-state fMRI data from an independent HC sample. Load-dependent deactivations of these DMN regions in response to WM probes were interrogated.
Results: Healthy controls showed linear load-dependent increases in DMN deactivation. Significant Group-by-Load interactions were observed in DMN regions including medial prefrontal and lateral posterior parietal cortices. Group-by-Load effects in posterior DMN nodes resulted from less suppression at higher WM loads in ESZ relative to HC, with CHR differing from neither group. In medial prefrontal cortex, suppression of activity at higher WM loads was significantly diminished in both CHR and ESZ groups, relative to HC. In addition, investigation of dorsolateral prefrontal cortex (DLPFC) activations revealed that ESZ activated right DLPFC significantly more than HC, with CHR differing from neither group.
Conclusion: While HC showed WM load-dependent modulation of DMN suppression, CHR individuals had deficient higher-load DMN suppression that was similar to, but less pronounced than, the distributed suppression deficits evident in ESZ patients. These results suggest that DMN dysregulation associated with schizophrenia predates psychosis onset.
schizophrenia prodrome; ultra-high-risk youth; dorsolateral prefrontal cortex; fMRI task-induced deactivation; adolescent mental health
Recently, deriving candidate endophenotypes from brain imaging data has become a valuable approach to study genetic influences on schizophrenia (SZ), whose pathophysiology remains unclear. In this work we utilized a multivariate approach, parallel independent component analysis, to identify genomic risk components associated with brain function abnormalities in SZ. 5157 candidate single nucleotide polymorphisms (SNPs) were derived from genome-wide array based on their possible connections with SZ and further investigated for their associations with brain activations captured with functional magnetic resonance imaging (fMRI) during a sensorimotor task. Using data from 92 SZ patients and 116 healthy controls, we detected a significant correlation (r= 0.29; p= 2.41×10−5) between one fMRI component and one SNP component, both of which significantly differentiated patients from controls. The fMRI component mainly consisted of precentral and postcentral gyri, the major activated regions in the motor task. On average, higher activation in these regions was observed in participants with higher loadings of the linked SNP component, predominantly contributed to by 253 SNPs. 138 identified SNPs were from known coding regions of 100 unique genes. 31 identified SNPs did not differ between groups, but moderately correlated with some other group-discriminating SNPs, indicating interactions among alleles contributing towards elevated SZ susceptibility. The genes associated with the identified SNPs participated in four neurotransmitter pathways: GABA receptor signaling, dopamine receptor signaling, neuregulin signaling and glutamate receptor signaling. In summary, our work provides further evidence for the complexity of genomic risk to the functional brain abnormality in SZ and suggests a pathological role of interactions between SNPs, genes and multiple neurotransmitter pathways.
schizophrenia; fMRI; SNP; parallel-ICA; multivariate
Substance abusing individuals tend to display abnormal reward processing and a vulnerability to being impulsive. Detoxified alcoholics show differences in regional brain activation during a monetary incentive delay (MID) task. However there is limited information on whether this uncharacteristic behavior represents a biological predisposition towards alcohol abuse, a consequence of chronic alcohol use, or both.
We investigated proposed neural correlates of substance disorder risk by examining reward system activity during a MID task with separate reward prospect, reward anticipation, and reward outcome phases in 30 individuals with and 19 without family histories of alcoholism. All subjects were healthy, lacked DSM-IV past or current alcohol or substance abuse histories, and were free of illegal substances as verified by a urine toxicology screening at the time of scanning. Additionally, we explored specific correlations between task-related nucleus accumbens (NAcc) activation and distinct factor analysis-derived domains of behavioral impulsivity.
During reward anticipation, fMRI data confirmed blunted NAcc activation in family history positive subjects. In addition, we found atypical activation in additional reward-associated brain regions during additional task phases. We further found a significant negative correlation between NAcc activation during reward anticipation and an impulsivity construct.
Overall, results demonstrate that sensitivity of the reward circuit, including NAcc, is functionally different in alcoholism FHP individuals in multiple regards.
Reward; Incentive; Anticipation; Alcoholism; fMRI; Impulsivity; Nucleus Accumbens; Ventral Striatum; Family History
Mesocorticolimbic neurocircuitry and impulsivity have both been implicated in pathological gambling (PG) and in reward processing. However, the neural underpinnings of specific phases of reward and loss processing in PG and their relationships to impulsivity remain only partially understood. The present functional magnetic resonance imaging study examined brain activity associated with different phases of reward and loss processing in PG. Given an inverse relationship between ventral striatal recruitment during anticipation of monetary rewards and impulsivity in alcohol dependence, the current study explored whether a similar association might also be present in PG.
Fourteen adults with PG and 14 control comparison (CC) participants performed the Monetary Incentive Delay Task (MIDT) to identify brain activation changes associated with reward/loss prospect, reward/loss anticipation and reward/loss notification. Impulsivity was assessed separately using the Barratt Impulsiveness Scale.
Relative to the CC group, the PG group exhibited significantly reduced activity in the ventromedial prefrontal cortex, insula and ventral striatum during several phases, including the prospect and anticipation phases of both gain and losses. Activity in the ventral striatum correlated inversely with levels of impulsivity in PG participants, consistent with prior findings in alcohol dependence.
Relatively decreased activity in cortico-striatal neurocircuitry during multiple phases of reward processing suggests consistent alterations in neurocircuitry underlying incentive valuation and loss prediction. Together with findings in alcohol dependence, these results suggest that impulsive tendencies in addictions may be reflected in diminished ventral striatal activations to reward anticipation and may represent targets for treatment development in addictions.
fMRI; vmPFC; ventral striatum; insula; incentive; gambling
In a previous cross-sectional study on baseline data, we demonstrated that the volume of brain white matter hyperintensities (WMH) in the splenium of corpus callosum (SCC) predicted the current mobility function of older persons. The primary aim of this follow-up study was to determine the relation of WMH volume change in SCC (SCC-∆WMH) with change in mobility measures. A secondary aim was to characterize the global and regional progression of WMH. Mobility function and WMH burden were evaluated at baseline and at 2 years in 77 community-dwelling individuals (baseline age, 82 ± 4). Regional WMH in SCC, as well as genu and body of corpus callosum, subregions of corona radiata, and superior longitudinal fasciculus were determined using a white matter parcellation atlas. The total WMH volume increased 3.3 ± 3.5 ml/year, mainly through enlargement. Significant WMH increases were observed in all selected regions, particularly within the corona radiata. While at baseline and follow-up we observed correlations between WMH burden and several measures of mobility, longitudinal change correlated only with change in chair rise (CR). SCC-∆WMH showed the highest correlation (r = −0.413, p = 0.0002) and was the best regional predictor of CR decline (OR = 1.5, r2 = 0.3). The SCC-∆WMH was more than five times larger in the CR-decline group compared to the no-decline group (p = 0.0003). The SCC-∆WMH (top quartile) showed a higher sensitivity/specificity for CR decline compared to change in total WMH, 63/88% versus 52/84%, respectively. The findings suggest that accrual of WMHs in posterior areas of the brain supporting inter-hemispheric integration and processing of visual–spatial information is a mechanism contributing to age-related mobility deterioration.
Electronic supplementary material
The online version of this article (doi:10.1007/s11357-011-9242-4) contains supplementary material, which is available to authorized users.
Aging; Mobility; Brain; White matter hyperintensities; Splenium of corpus callosum; Magnetic resonance imaging
While the cerebellum plays a critical role in motor coordination and control no studies have investigated its involvement in idiopathic mobility impairment in community-dwelling elderly. In this study we tested the hypothesis that structural changes in the cerebellar peduncles not detected by conventional magnetic resonance imaging are associated with reduced mobility performance. The analysis involved eighty-five subjects (age range: 75–90 years) who had no clinical signs of cerebellar dysfunction. Based on the short physical performance battery (SPPB) score, we defined mobility status of the subjects in the study as normal (score 11–12, n = 26), intermediate (score 9–10, n = 27) or impaired (score < 9, n = 32). We acquired diffusion tensor imaging data to obtain indices of white matter integrity: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). Using a parcellation atlas, regional indices within the superior, middle, and inferior cerebellar peduncles (ICP, MCP, SCP) were calculated and their associations with mobility performance were analyzed. Subjects with impaired mobility showed reduced FA and AD values in the ICP and SCP but not in the MCP. The ICP-FA, ICP-AD and SCP-FA indices showed a significant association with the SPPB score. We also observed significant correlation between ICP-FA and walk time (r = − 0.311, p = 0.004), as well as between SCP-AD and self-paced maximum walking velocity (r = 0.385, p = 0.003) and usual walking velocity (r = 0.400, p = 0.002). In logistic regression analysis ICP-FA and ICP-AD together explained 51% of the variability in the mobility status of a sample comprising the normal and impaired subgroups, and correctly classified more than three-quarters of those subjects. Our findings suggest that presence of microstructural damage, likely axonal, in afferent and efferent connections of the cerebellum contributes to the deterioration of motor performance in older people.
•DTI study of the cerebellar peduncles and mobility in elderly.•Fractional anisotropy and axial diffusivity of inferior peduncle predict mobility.•Decreased anisotropy in the peduncles in the absence of T2 lesions.•Findings likely reflect axonal degeneration of proprioceptive afferent fibers.•Abnormalities in infratentorial white matter are novel findings in the field.
Aging; Mobility; Cerebellar peduncles; Diffusion tensor imaging
Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called “mCCA + jICA” as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.
multimodal fusion; mCCA + jICA; resting state fMRI; DTI; sMRI; schizophrenia; ALFF; GM
There is a growing interest in automatic classification of mental disorders based on neuroimaging data. Small training data sets (subjects) and very large amount of high dimensional data make it a challenging task to design robust and accurate classifiers for heterogeneous disorders such as schizophrenia. Most previous studies considered structural MRI, diffusion tensor imaging and task-based fMRI for this purpose. However, resting-state data has been rarely used in discrimination of schizophrenia patients from healthy controls. Resting data are of great interest, since they are relatively easy to collect, and not confounded by behavioral performance on a task. Several linear and non-linear classification methods were trained using a training dataset and evaluate with a separate testing dataset. Results show that classification with high accuracy is achievable using simple non-linear discriminative methods such as k-nearest neighbors (KNNs) which is very promising. We compare and report detailed results of each classifier as well as statistical analysis and evaluation of each single feature. To our knowledge our effects represent the first use of resting-state functional network connectivity (FNC) features to classify schizophrenia.
functional network connectivity; independent component analysis (ICA); classification; schizophrenia; resting-state fMRI
Hoarding disorder (HD), previously considered a subtype of obsessive-compulsive disorder (OCD), has been proposed as a unique diagnostic entity in DSM-5. Current models of HD emphasize problems of decision-making, attachment to possessions, and poor insight, whereas previous neuroimaging studies have suggested abnormalities in frontal brain regions.
To examine the neural mechanisms of impaired decision making in HD in patients with well-defined primary HD compared with patients with OCD and healthy control subjects (HCs).
We compared neural activity among patients with HD, patients with OCD, and HCs during decisions to keep or discard personal possessions and control possessions from November 9, 2006, to August 13, 2010.
Private, not-for-profit hospital.
A total of 107 adults (43 with HD, 31 with OCD, and 33 HCs).
Main Outcome Measures
Neural activity as measured by functional magnetic resonance imaging in which actual real-time and binding decisions had to be made about whether to keep or discard possessions.
Compared with participants with OCD and HC, participants with HD exhibited abnormal activity in the anterior cingulate cortex and insula that was stimulus dependent. Specifically, when deciding about items that did not belong to them, patients with HD showed relatively lower activity in these brain regions. However, when deciding about items that belonged to them, these regions showed excessive functional magnetic resonance imaging signals compared with the other 2 groups. These differences in neural function correlated significantly with hoarding severity and self-ratings of indecisiveness and “not just right” feelings among patients with HD and were unattributable to OCD or depressive symptoms.
Findings suggest a biphasic abnormality in anterior cingulate cortex and insula function in patients with HD related to problems in identifying the emotional significance of a stimulus, generating appropriate emotional response, or regulating affective state during decision making.
Although cocaine dependence involves abnormalities in drug-related reward-based decision-making, it is not well understood whether these abnormalities generalize to non-drug-related cues and rewards, and how neural functions underlying reward processing in cocaine abusers relate to treatment outcome.
Twenty cocaine dependent (CD) patients before treatment and 20 matched healthy control (HC) subjects participated in fMRI while performing a Monetary Incentive Delay Task (MIDT). Outcomes through eight weeks were assessed via percent cocaine-negative urine toxicology, self-reported cocaine abstinence, and treatment retention.
Amongst the whole sample, anticipation of working for monetary reward (i.e., reward anticipation) was associated with activation in the ventral striatum (VS), medial frontal gyrus, thalamus, right subcallosal gyrus, right insula, and left amygdala. CD as compared with HC participants exhibited greater activation during notification of rewarding outcome (i.e., reward receipt) in left and right VS, right caudate, and right insula. In CD participants during reward anticipation, activation in left and right thalamus and right caudate correlated negatively with percent cocaine-negative urine toxicology, activation in thalamus bilaterally correlated negatively with self-reported abstinence measures, and activation in left amygdala and parahippocampal gyrus correlated negatively with treatment retention. During reward notification, activation in right thalamus, right VS and left culmen correlated negatively with abstinence and with urine toxicology.
These findings suggest that in treatment-seeking CD participants, cortico-limbic reward circuitry is relatively over-activated during MIDT performance and specific regional activations related to reward processing may predict aspects of treatment outcome and represent important targets for treatment development in CD.
Cocaine Dependence; Reward Circuitry; Monetary Incentive Delay Task; Anticipation; fMRI; Treatment Outcome
Individual differences in behavioral inhibition and behavioral activation may place certain people at greater risk for neuropsychiatric disorders and engagement in risky behaviors. Therefore, studying the neural correlates of behavioral inhibition and activation may help us understand neural mechanisms underlying risk behaviors in both clinical and non-clinical populations. To investigate, we assessed the relationships between white matter integrity and measures of behavioral inhibition and behavioral activation in 51 healthy participants using diffusion tensor imaging (DTI) and the Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) scale. Scores on the Fun-Seeking subscale of the BAS positively correlated with DTI fractional anisotropy (FA) in the left corona radiata and adjacent superior longitudinal fasciculus, and with mean diffusivity (MD) in the left inferior longitudinal fasciculus and inferior fronto-occipital fasciculus after controlling for age, gender, and education. These findings suggest that the integrity of white matter connecting extensive brain regions implicated in self-control and the processing of rewards and emotions are associated with individual differences in the motivation for seeking and participating in fun and novel experiences.
Behavioral Activation; Behavioral Inhibition; Neuroimaging; DTI; Self-Control; Cognitive Control
Impulsivity, often defined as a human behavior characterized by the inclination of an individual to act on urge rather than thought, with diminished regard to consequences, encompasses a range of maladaptive behaviors which are in turn affected by distinct neural systems. Congruent with the above definition, behavioral studies have consistently shown that the underlying construct of impulsivity is multidimensional in nature. However, research to date has been inconclusive regarding the different domains or constructs that constitute this behavior. In addition there is also no clear consensus as to whether self-report and laboratory based measures of impulsivity measure the same or different domains. The current study aimed to: 1) characterize the underlying multidimensional construct of impulsivity using a sample with varying degrees of putative impulsivity related to substance misuse, including subjects who were at-risk of substance use or addicted (ARA), and 2) assess relationships between self-report and laboratory measures of impulsivity, using a principal component-based factor analysis. In addition, our supplementary goal was to evaluate the structural constructs of impulsivity within each group separately (healthy and ARA). We used five self-report measures (Behavioral Inhibition System/Behavioral Activation System (BIS/BAS), Barratt Impulsivity Scale-11, Padua Inventory, Zuckerman Sensation Seeking Scale (SSS), and Sensitivity to Punishment and Sensitivity to Reward Questionnaire) and two computer based laboratory tasks (Balloon Analog Risk Task and the Experiential Delay Task) to measure aspects of impulsivity in a total of 176 adult subjects. Subjects included healthy controls (N=89), non-alcoholic subjects with family histories of alcoholism (FHP; N=36) and both former (N=20) and current (N=31) cocaine users. Subjects with a family history of alcoholism and cocaine abusers were grouped together as “at-risk/addicted” (ARA) to evaluate our supplementary goal. Our overall results revealed the multidimensional nature of the impulsivity construct as captured optimally through a five factor solution that accounted for nearly 70% of the total variance. The five factors/components were imputed as follows “Self-Reported Behavioral Activation”, “Self-Reported Compulsivity and Reward/Punishment”, “Self-Reported Impulsivity”, “Behavioral Temporal Discounting” and “Behavioral Risk-Taking.” We also found that contrary to previously published reports, there was significant overlap between certain laboratory and self-report measures, indicating that they might be measuring the same impulsivity domain. In addition, our supplemental analysis also suggested that the impulsivity constructs were largely, but not entirely the same within the healthy and ARA groups.
impulsivity; behavior; substance abuse; cocaine; alcohol; factor analysis; PCA; BIS-BAS; BIS-11; EDT; BART; Zuckerman; SPSRQ; human
The anterior cingulate and a collection of other prefrontal and parietal brain regions are implicated in error processing and cognitive control. The effects of different doses of alcohol on activity within these brain regions during an fMRI task where errors are frequently committed have not been fully explored. This study examined the impact of a placebo [Breath Alcohol Concentration (BrAC) = 0.00%], moderate (BrAC = 0.05%) and high (BrAC = 0.10%) doses of alcohol on brain hemodynamic activity during a functional MRI (fMRI) Go/No-Go task in thirty-eight healthy volunteers. Alcohol increased reaction time and false alarm errors in a dose-dependent manner. FMRI analyses showed alcohol decreased activity in anterior cingulate, lateral prefrontal cortex, insula and parietal lobe regions during false alarm responses to No-Go stimuli. These findings indicate that brain regions implicated in error processing are affected by alcohol and might provide a neural basis for alcohol's effects on behavioral performance.
functional imaging; alcohol; Go/No-Go; error monitoring; anterior cingulate
Schizophrenia (SZ) is one of the most cryptic and costly mental disorders in terms of human suffering and societal expenditure (van Os and Kapur, 2009). Though strong evidence for functional, structural, and genetic abnormalities associated with this disease exists, there is yet no replicable finding which has proven accurate enough to be useful in clinical decision making (Fornito et al., 2009), and its diagnosis relies primarily upon symptom assessment (Williams et al., 2010a). It is likely in part that the lack of consistent neuroimaging findings is because most models favor only one data type or do not combine data from different imaging modalities effectively, thus missing potentially important differences which are only partially detected by each modality (Calhoun et al., 2006a). It is becoming increasingly clear that multimodal fusion, a technique which takes advantage of the fact that each modality provides a limited view of the brain/gene and may uncover hidden relationships, is an important tool to help unravel the black box of schizophrenia. In this review paper, we survey a number of multimodal fusion applications which enable us to study the schizophrenia macro-connectome, including brain functional, structural, and genetic aspects and may help us understand the disorder in a more comprehensive and integrated manner. We also provide a table that characterizes these applications by the methods used and compare these methods in detail, especially for multivariate models, which may serve as a valuable reference that helps readers select an appropriate method based on a given research question.
multimodal fusion; schizophrenia; MRI; DTI; EEG; SNP; ICA; CCA
We present a novel method to extract classification features from functional magnetic resonance imaging (fMRI) data collected at rest or during the performance of a task. By combining a two-level feature identification scheme with kernel principal component analysis (KPCA) and Fisher’s linear discriminant analysis (FLD), we achieve high classification rates in discriminating healthy controls from patients with schizophrenia. Experimental results using leave-one-out cross-validation show that features extracted from the default mode network (DMN) lead to a classification accuracy of over 90% in both data sets. Moreover, using a majority vote method that uses multiple features, we achieve a classification accuracy of 98% in auditory oddball (AOD) task and 93% in rest data. Several components, including DMN, temporal, and medial visual regions, are consistently present in the set of features that yield high classification accuracy. The features we have extracted thus show promise to be used as biomarkers for schizophrenia. Results also suggest that there may be different advantages to using resting fMRI data or task fMRI data.
classification; fMRI; independent component analysis; KPCA; FLD
Openness is a personality trait that has been linked to intelligence and divergent thinking. DeYoung, Peterson, and Higgins (2005) theorized that trait Openness depends on dopamine function, especially in the prefrontal cortex. We tested their theory in 335 healthy adults by hypothesizing that individual differences in Openness would correlate more strongly with performance on tests of executive function than on tests of intelligence and fluency. However, Openness correlated more strongly with verbal/crystallized intelligence (Gc; r=0.44) than with executive functioning (r=0.16) and fluency (r=0.24). Further, the partial correlation between Openness and Gc increased from r=0.26 among young adults to r=0.53 among elderly adults. These findings suggest that Openness is more closely associated with the acquisition of broad verbal intellectual skills and knowledge than with executive abilities localized to a specific brain region or neurotransmitter system.
Openness; crystallized intelligence; fluid intelligence; personality; neuropsychology; prefrontal cortex; executive function
Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.
Despite the knowledge that many drugs affect men and women differently, few studies exploring the effects of marijuana use on cognition have included women. Findings from both animal and human studies suggest marijuana may have more marked effects in women. This study examined sex differences in the acute effects of marijuana on cognition in 70 (n= 35 male, 35 female) occasional users of marijuana. Tasks were chosen to tap a wide variety of cognitive domains affected by sex and/or marijuana including attention, cognitive flexibility, time estimation, and visuospatial processing. As expected, acute marijuana use impaired performance on selective and divided attention, time estimation, and cognitive flexibility. While there did not appear to be sex differences in marijuana's effects on cognition, women requested to discontinue the smoking session more often than men likely leading to an underestimation of differences. Further study of psychological differences in marijuana's effects on men and women following both acute and residual effects of marijuana is warranted.
acute effects; marijuana; cannabis; cognition; sex; gender
Autism spectrum disorders (ASDs) are characterized by deficits in social and communication processes. Recent data suggest that altered functional connectivity (FC), i.e. synchronous brain activity, might contribute to these deficits. Of specific interest is the FC integrity of the default mode network (DMN), a network active during passive resting states and cognitive processes related to social deficits seen in ASD, e.g. Theory of Mind. We investigated the role of altered FC of default mode sub-networks (DM-SNs) in 16 patients with high-functioning ASD compared to 16 matched healthy controls of short resting fMRI scans using independent component analysis (ICA). ICA is a multivariate data-driven approach that identifies temporally coherent networks, providing a natural measure of FC. Results show that compared to controls, patients showed decreased FC between the precuneus and medial prefrontal cortex/anterior cingulate cortex, DMN core areas, and other DM-SNs areas. FC magnitude in these regions inversely correlated with the severity of patients' social and communication deficits as measured by the Autism Diagnostic Observational Schedule and the Social Responsiveness Scale. Importantly, supplemental analyses suggest that these results were independent of treatment status. These results support the hypothesis that DM-SNs under-connectivity contributes to the core deficits seen in ASD. Moreover, these data provide further support for the use of data-driven analysis with resting-state data for illuminating neural systems that differ between groups. This approach seems especially well suited for populations where compliance with and performance of active tasks might be a challenge, as it requires minimal cooperation.
Independent component analysis; Functional MRI; Resting state; Default mode network; High-functioning autism
Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published fMRI study (Meda et al, 2009), our group identified five, independent critical driving-associated brain circuits whose inter-regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol-intoxicated states.
In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following two alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%.
At the active dose, we found specific disruptions of functional network connectivity between the frontal-temporal-basal ganglia and the cerebellar circuits. The temporal connectivity between these two circuits was found to be less correlated (p <0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering).
Connections between frontal-temporal-basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior.
Motor; Fronto-Striatal; Virtual Reality; Driving while intoxicated; Cerebellum