111 research outputs found
A morphospace of functional configuration to assess configural breadth based on brain functional networks
The best approach to quantify human brain functional reconfigurations in
response to varying cognitive demands remains an unresolved topic in network
neuroscience. We propose that such functional reconfigurations may be
categorized into three different types: i) Network Configural Breadth, ii)
Task-to-Task transitional reconfiguration, and iii) Within-Task
reconfiguration. In order to quantify these reconfigurations, we propose a
mesoscopic framework focused on functional networks (FNs) or communities. To do
so, we introduce a 2D network morphospace that relies on two novel mesoscopic
metrics, Trapping Efficiency (TE) and Exit Entropy (EE), which capture topology
and integration of information within and between a reference set of FNs. In
this study, we use this framework to quantify the Network Configural Breadth
across different tasks. We show that the metrics defining this morphospace can
differentiate FNs, cognitive tasks and subjects. We also show that network
configural breadth significantly predicts behavioral measures, such as episodic
memory, verbal episodic memory, fluid intelligence and general intelligence. In
essence, we put forth a framework to explore the cognitive space in a
comprehensive manner, for each individual separately, and at different levels
of granularity. This tool that can also quantify the FN reconfigurations that
result from the brain switching between mental states.Comment: main article: 24 pages, 8 figures, 2 tables. supporting information:
11 pages, 5 figure
Association of structural brain imaging markers with alcoholism incorporating structural connectivity information: a regularized statistical approach
poster abstractAbstract: Brain imaging studies collect multiple imaging data types, but most analyses are done for each modality separately. Statistical methods that simultaneously utilize and combine multiple data types can instead provide a more holistic view of brain function. Here we model associations between alcohol abuse phenotypes and imaging data while incorporating prior scientific knowledge. Specifically, we utilize cortical thickness and integrated rectified mean curvature measures obtained by FreeSurfer software [1] to predict the alcoholism-related phenotypes while incorporating prior information from the structural connectivity between cortical regions. The sample consisted of 148 young (21-35 years) social-to-heavy drinking male subjects from several alcoholism risk studies [2,3,4]. Structural connectivity model [5] was used to estimate the density of connections between 66 cortical regions based on Desikan-Killiany atlas [6]. We employed a functional linear model with a penalty operator to quantify the relative contributions of imaging markers obtained from high resolution structural MRI (cortical thickness and curvature) as predictors of drinking frequency and risk-relevant personality traits, while co-varying for age. Model parameters were estimated by a unified approach directly incorporating structural connectivity information into the estimation by exploiting the joint eigenproperties of the predictors and the penalty operator [7]. We found that the best predictive imaging markers of the Alcohol Use Disorders Identification Test (AUDIT) score were the average thickness of left frontal pole (-), right transverse temporal gyrus (+), left inferior parietal lobule (+), right supramarginal gyrus (-), right rostral middle frontal gyrus (+), right precentral gyrus (+), left superior parietal lobule (-), left lateral orbitofrontal cortex (+), left rostral middle frontal gyrus (+), left postcentral gyrus (+) and left supramarginal gyrus (-), where (+) denotes positive and (-) negative association. In summary, the use of structural connectivity information allowed the incorporation of different modalities in associating cortical measures and alcoholism risk
Keeping the inner voice inside the head, a pilot fMRI study
Introduction: The inner voice is experienced during thinking in words (inner speech) and silent reading and evokes brain activity that is highly similar to that associated with external voices. Yet while the inner voice is experienced in internal space (inside the head), external voices (one's own and those of others) are experienced in external space. In this paper, we investigate the neural basis of this differential spatial localization.
Methods: We used fMRI to examine the difference in brain activity between reading silently and reading aloud. As the task involved reading aloud, data were first denoised by removing independent components related to head movement. They were subsequently processed using finite impulse response basis function to address the variations of the hemodynamic response. Final analyses were carried out using permutation-based statistics, which is appropriate for small samples. These analyses produce spatiotemporal maps of brain activity.
Results: Reading silently relative to reading aloud was associated with activity of the "where" auditory pathway (Inferior parietal lobule and middle temporal gyrus), and delayed activity of the primary auditory cortex.
Conclusions: These pilot data suggest that internal space localization of the inner voice depends on the same neural resources as that for external space localization of external voices-the "where" auditory pathway. We discuss the implications of these findings on the possible mechanisms of abnormal experiences of the inner voice as is the case in verbal hallucinations
Semiparametric Estimation of Task-Based Dynamic Functional Connectivity on the Population Level
Dynamic functional connectivity (dFC) estimates time-dependent associations between pairs of brain region time series as typically acquired during functional MRI. dFC changes are most commonly quantified by pairwise correlation coefficients between the time series within a sliding window. Here, we applied a recently developed bootstrap-based technique (Kudela et al., 2017) to robustly estimate subject-level dFC and its confidence intervals in a task-based fMRI study (24 subjects who tasted their most frequently consumed beer and Gatorade as an appetitive control). We then combined information across subjects and scans utilizing semiparametric mixed models to obtain a group-level dFC estimate for each pair of brain regions, flavor, and the difference between flavors. The proposed approach relies on the estimated group-level dFC accounting for complex correlation structures of the fMRI data, multiple repeated observations per subject, experimental design, and subject-specific variability. It also provides condition-specific dFC and confidence intervals for the whole brain at the group level. As a summary dFC metric, we used the proportion of time when the estimated associations were either significantly positive or negative. For both flavors, our fully-data driven approach yielded regional associations that reflected known, biologically meaningful brain organization as shown in prior work, as well as closely resembled resting state networks (RSNs). Specifically, beer flavor-potentiated associations were detected between several reward-related regions, including the right ventral striatum (VST), lateral orbitofrontal cortex, and ventral anterior insular cortex (vAIC). The enhancement of right VST-vAIC association by a taste of beer independently validated the main activation-based finding (Oberlin et al., 2016). Most notably, our novel dFC methodology uncovered numerous associations undetected by the traditional static FC analysis. The data-driven, novel dFC methodology presented here can be used for a wide range of task-based fMRI designs to estimate the dFC at multiple levels-group-, individual-, and task-specific, utilizing a combination of well-established statistical methods
An fMRI Study of Responses to Sexual Stimuli as a Function of Gender and Sensation Seeking: A Preliminary Analysis
Although sexual cues produce stronger neural activation in men than in women, mechanisms underlying this differential response are unclear. We examined the relationship of sensation seeking and the brainâs response to sexual stimuli across gender in 27 subjects (14 men, M = 25.2 years, SD = 3.6, 85.2% Caucasian) who underwent functional magnetic resonance imaging (fMRI) while viewing sexual and nonsexual images. Whole-brain corrected significant clusters of regional activation were extracted and associated with gender, sensation seeking, and sexual behaviors. Men responded more to sexual than nonsexual images in the anterior cingulate/medial prefrontal cortex (ACC/mPFC), anterior insula/lateral orbitofrontal cortex, bilateral amygdala, and occipital regions. Sensation seeking related positively to ACC/mPFC (r = 0.65, p = 0.01) and left amygdala (r = 0.66, p = 0.01) response in men alone, with both of these correlations being significantly larger in men than in women (ps < 0.03). The relationship between brain responses and self-reported high-risk and low-risk sexual behaviors showed interesting, albeit nonsignificant, gender-specific trends. These findings suggest the relationship between sexual responsivity, sensation seeking, and sexual behavior is gender specific. This study indicates a need to identify the gender-specific mechanisms that underlie sexual responsivity and behaviors. In addition, it demonstrates that the nature of stimuli used to induce positive mood in imaging and other studies should be carefully considered
A preliminary study of the human brain response to oral sucrose and its association with recent drinking
BACKGROUND: A preference for sweet tastes has been repeatedly shown to be associated with alcohol preference in both animals and humans. In this study, we tested the extent to which recent drinking is related to blood oxygen level-dependent (BOLD) activation from an intensely sweet solution in orbitofrontal areas known to respond to primary rewards.
METHODS: Sixteen right-handed, non-treatment-seeking, healthy volunteers (mean age: 26 years; 75% male) were recruited from the community. All underwent a taste test using a range of sucrose concentrations, as well as functional magnetic resonance imaging (fMRI) during pseudorandom, event-driven stimulation with water and a 0.83 M concentration of sucrose in water.
RESULTS: [Sucrose > water] provoked a significant BOLD activation in primary gustatory cortex and amygdala, as well as in the right ventral striatum and in bilateral orbitofrontal cortex. Drinks/drinking day correlated significantly with the activation as extracted from the left orbital area (r = 0.52, p = 0.04 after correcting for a bilateral comparison). Using stepwise multiple regression, the addition of rated sucrose liking accounted for significantly more variance in drinks/drinking day than did left orbital activation alone (multiple R = 0.79, p = 0.002).
CONCLUSIONS: Both the orbitofrontal response to an intensely sweet taste and rated liking of that taste accounted for significant variance in drinking behavior. The brain response to sweet tastes may be an important phenotype of alcoholism risk
Aberrations of anterior insular cortex functional connectivity in nontreatment-seeking alcoholics
An emergent literature suggests that resting state functional magnetic resonance imaging (rsfMRI) functional connectivity (FC) patterns are aberrant in alcohol use disorder (AUD) populations. The salience network (SAL) is an established set of brain regions prominent in salience attribution and valuation, and includes the anterior insular cortex (AIC). The SAL is thought to play a role in AUD through directing increased attention to interoceptive cues of intoxication. There is very little information on the salience network (SAL) in AUD, and, in particular, there are no data on SAL FC in currently drinking, nontreatment seeking individuals with AUD (NTS). rsfMRI data from 16 NTS and 21 social drinkers (SD) were compared using FC correlation maps from ten seed regions of interest in the bilateral AIC. As anticipated, SD subjects demonstrated greater insular FC with frontal and parietal regions. We also found that, compared to SD, NTS had higher insular FC with hippocampal and medial orbitofrontal regions. The apparent overactivity in brain networks involved in salience, learning, and behavioral control in NTS suggests possible mechanisms in the development and maintenance of AUD
A cross-linguistic fMRI study of perception of intonation and emotion in Chinese
Conflicting data from neurobehavioral studies of the perception of intonation (linguistic) and emotion (affective) in spoken language highlight the need to further examine how functional attributes of prosodic stimuli are related to hemispheric differences in processing capacity. Because of similarities in their acoustic profiles, intonation and emotion permit us to assess to what extent hemispheric lateralization of speech prosody depends on functional instead of acoustical properties. To examine how the brain processes linguistic and affective prosody, an fMRI study was conducted using Chinese, a tone language in which both intonation and emotion may be signaled prosodically, in addition to lexical tones. Ten Chinese and 10 English subjects were asked to perform discrimination judgments of intonation (I: statement, question) and emotion (E: happy, angry, sad) presented in semantically neutral Chinese sentences. A baseline task required passive listening to the same speech stimuli (S). In direct betweenâgroup comparisons, the Chinese group showed leftâsided frontoparietal activation for both intonation (I vs. S) and emotion (E vs. S) relative to baseline. When comparing intonation relative to emotion (I vs. E), the Chinese group demonstrated prefrontal activation bilaterally; parietal activation in the left hemisphere only. The reverse comparison (E vs. I), on the other hand, revealed that activation occurred in anterior and posterior prefrontal regions of the right hemisphere only. These findings show that some aspects of perceptual processing of emotion are dissociable from intonation, and, moreover, that they are mediated by the right hemisphere
Brain Connectivity-Informed Regularization Methods for Regression
One of the challenging problems in brain imaging research is a principled incorporation of information from different imaging modalities. Frequently, each modality is analyzed separately using, for instance, dimensionality reduction techniques, which result in a loss of mutual information. We propose a novel regularization method to estimate the association between the brain structure features and a scalar outcome within the linear regression framework. Our regularization technique provides a principled approach to use external information from the structural brain connectivity and inform the estimation of the regression coefficients. Our proposal extends the classical Tikhonov regularization framework by defining a penalty term based on the structural connectivity-derived Laplacian matrix. Here, we address both theoretical and computational issues. The approach is first illustrated using simulated data and compared with other penalized regression methods. We then apply our regularization method to study the associations between the alcoholism phenotypes and brain cortical thickness using a diffusion imaging derived measure of structural connectivity. Using the proposed methodology in 148 young male subjects with a risk for alcoholism, we found a negative associations between cortical thickness and drinks per drinking day in bilateral caudal anterior cingulate cortex, left lateral OFC, and left precentral gyrus
Neural correlates of segmental and tonal information in speech perception
The Chinese language provides an optimal window for investigating both segmental and suprasegmental units. The aim of this crossâlinguistic fMRI study is to elucidate neural mechanisms involved in extraction of Chinese consonants, rhymes, and tones from syllable pairs that are distinguished by only one phonetic feature (minimal) vs. those that are distinguished by two or more phonetic features (nonâminimal). Triplets of Chinese monosyllables were constructed for three tasks comparing consonants, rhymes, and tones. Each triplet consisted of two target syllables with an intervening distracter. Ten Chinese and English subjects were asked to selectively attend to targeted subâsyllabic components and make sameâdifferent judgments. Direct betweenâgroup comparisons in both minimal and nonâminimal pairs reveal increased activation for the Chinese group in predominantly leftâsided frontal, parietal, and temporal regions. Withinâgroup comparisons of nonâminimal and minimal pairs show that frontal and parietal activity varies for each subâsyllabic component. In the frontal lobe, the Chinese group shows bilateral activation of the anterior middle frontal gyrus (MFG) for rhymes and tones only. Withinâgroup comparisons of consonants, rhymes, and tones show that rhymes induce greater activation in the left posterior MFG for the Chinese group when compared to consonants and tones in nonâminimal pairs. These findings collectively support the notion of a widely distributed cortical network underlying different aspects of phonological processing. This neural network is sensitive to the phonological structure of a listener's native language
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