Listening to real-world sounds: fMRI data for analyzing connectivity networks.

There is a growing interest in functional magnetic resonance imaging (fMRI) studies on connectivity networks in the brain when subjects are under exposure to natural sensory stimulation. Because of a complicated coupling between spontaneous and evoked brain activity under real-world stimulation, there is no critical mapping between the experimental inputs and corresponding brain responses. The dataset contains auditory fMRI scans and T1-weighted anatomical scans acquired under eyes-closed and eyes-open conditions. Within each scanning condition, the subject was presented 12 different sound clips, including human voices followed by animal vocalizations. The dataset is meant to be used to assess brain dynamics and connectivity networks under natural sound stimulation; it also allows for empirical investigation of changes in fMRI responses between eyes-closed and eyes-open conditions, between animal vocalizations and human voices, as well as between the 12 different sound clips during auditory stimulation. The dataset is a supplement to the research findings in the paper "Brain dynamics and connectivity networks under natural auditory stimulation" published in NeuroImage.

Brain dynamics and connectivity networks under natural auditory stimulation.

The analysis of functional magnetic resonance imaging (fMRI) data is challenging when subjects are under exposure to natural sensory stimulation. In this study, a two-stage approach was developed to enable the identification of connectivity networks involved in the processing of information in the brain under natural sensory stimulation. In the first stage, the degree of concordance between the results of inter-subject and intra-subject correlation analyses is assessed statistically. The microstructurally (i.e., cytoarchitectonically) defined brain areas are designated either as concordant in which the results of both correlation analyses are in agreement, or as discordant in which one analysis method shows a higher proportion of supra-threshold voxels than does the other. In the second stage, connectivity networks are identified using the time courses of supra-threshold voxels in brain areas contingent upon the classifications derived in the first stage. In an empirical study, fMRI data were collected from 40 young adults (19 males, average age 22.76 ±â€¯3.25), who underwent auditory stimulation involving sound clips of human voices and animal vocalizations under two operational conditions (i.e., eyes-closed and eyes-open). The operational conditions were designed to assess confounding effects due to auditory instructions or visual perception. The proposed two-stage analysis demonstrated that stress modulation (affective) and language networks in the limbic and cortical structures were respectively engaged during sound stimulation, and presented considerable variability among subjects. The network involved in regulating visuomotor control was sensitive to the eyes-open instruction, and presented only small variations among subjects. A high degree of concordance was observed between the two analyses in the primary auditory cortex which was highly sensitive to the pitch of sound clips. Our results have indicated that brain areas can be identified as concordant or discordant based on the two correlation analyses. This may further facilitate the search for connectivity networks involved in the processing of information under natural sensory stimulation.

Resting heart rate variability in young women is a predictor of EEG reactions to linguistic ambiguity in sentences.

Recent research has found a relationship between heart rate variability (HRV) and cognitive control mechanisms underlying various experimental tasks. This study explored the interaction between gender and resting-state HRV in brain oscillatory activity during visual recognition of linguistic ambiguity while taking state and trait anxiety scores into account. It is well known that stress or anxiety increases arousal levels, particularly under uncertainty situations. We tasked 50 young Mandarin speakers (26 women; average age 26.00 ±â€¯4.449) with the recognition of linguistic ambiguity in English (foreign) sentences with the purpose of imposing a sense of uncertainty in decision-making. Our results revealed a dependency between resting-state HRV and theta/alpha power in individual women. Low HRV women showed stronger theta/alpha desynchronization compared with their high HRV counterparts, independent of topographic localization. However, low and high HRV men exhibited comparable theta/alpha activity. Trait anxiety scores affected alpha power in the parieto-occipital regions, whereas men with higher scores and women with lower scores showed stronger alpha desynchronization. We posit that stress-provoking situations may impose additional effects on theta/alpha desynchronization in the frontal and temporal regions, a condition in which the interdependency between brain oscillatory activity and resting-state HRV could interact with cognitive control differently in men and women.

Beyond p-values: averaged and reproducible evidence in fMRI experiments.

In functional magnetic resonance imaging studies, there might exist activation regions routinely involved in experimental sessions, but modest in response magnitude. These regions may not be easily detectable by the conventional p-value approach using a rigid threshold. With particular reference to the reproducibility analysis method proposed in Liou and colleagues, this study presents some within- and between-subject brain-activation patterns that are replicable between experimental modalities, and robust to the method used for generating the patterns. There is a neurophysiological basis behind these reproducible patterns, and the conventional p-value approach using averaged data across subjects might not suggest the complete patterns. For example, recent studies based on the group-averaged data showed a task-induced deactivation in the precuneus and posterior cingulate, but our reproducibility analysis suggests both increased and decreased responses in the two regions. The increased responses localize in these regions with differentially distributed patterns for individual subjects and for different experimental tasks. In this study, we discuss the neurophysiological basis of the reproducible patterns and propose some applications of our research findings to scientific and clinical studies.

MR image segmentation using a power transformation approach.

This study proposes a segmentation method for brain MR images using a distribution transformation approach. The method extends traditional Gaussian mixtures expectation-maximization segmentation to a power transformed version of mixed intensity distributions, which includes Gaussian mixtures as a special case. As MR intensities tend to exhibit non-Gaussianity due to partial volume effects, the proposed method is designed to fit non-Gaussian tissue intensity distributions. One advantage of the method is that it is intuitively appealing and computationally simple. To avoid performance degradation caused by intensity inhomogeneity, different methods for correcting bias fields were applied prior to image segmentation, and their correction effects on the segmentation results were examined in the empirical study. The partitions of brain tissues (i.e., gray and white matter) resulting from the method were validated and evaluated against manual segmentation results based on 38 real T1-weighted image volumes from the internet brain segmentation repository, and 18 simulated image volumes from BrainWeb. The Jaccard and Dice similarity indexes were computed to evaluate the performance of the proposed approach relative to the expert segmentations. Empirical results suggested that the proposed segmentation method yielded higher similarity measures for both gray matter and white matter as compared with those based on the traditional segmentation using the Gaussian mixtures approach.

EEG-correlates of trait anxiety in the stop-signal paradigm.

The relationship between trait anxiety and event-related EEG oscillatory reactions in the stop-signal paradigm was studied in 15 non-clinical subjects with average age of 26 years (13 men). In the paradigm, subjects responded to target stimuli by pressing one of the two choice buttons. In 30 out of 130 trials, target presentation was followed by a stop-signal, indicating that subjects had to refrain from a prepared motor response. The subject's level of anxiety was assessed using the State Trait Anxiety Inventory. Wide-band desynchronization (8-25 Hz) was found before button-press. It was sustained after the subjects pressed the button at 7-14 Hz frequency range. Also, synchronization at 15-25 Hz band occurred in 400-1400 ms after the button-press. Synchronization at lower frequencies (1-7 Hz) was also found during 0-700 ms after the stop-signal onset. Also, desynchronization at 8-20 Hz was found in 300-800 ms after stop-signal onset. The group with higher anxiety showed desynchronization at 10-13 Hz in 0-800 ms after the button-press, whereas the group with lower anxiety showed synchronization at the same frequency range. In 0-600 ms after stop-signal onset, desynchronization at 8-13 Hz was observed in the group with higher anxiety, whereas the group with lower anxiety demonstrated synchronization or weak desynchronization. Our findings support the Eysenck et al. [M.W. Eysenck, N. Derakshan, R. Santos, M.G. Calvo, Anxiety and cognitive performance: attentional control theory, Emotion 7(2) (2007) 336-356] theory that subjects with higher anxiety have more attentional control over reaction and increased use of processing resources as compared with lower anxiety subjects.

A method for generating reproducible evidence in fMRI studies.

Insights into cognitive neuroscience from neuroimaging techniques are now required to go beyond the localisation of well-known cognitive functions. Fundamental to this is the notion of reproducibility of experimental outcomes. This paper addresses the central issue that functional magnetic resonance imaging (fMRI) experiments will produce more desirable information if researchers begin to search for reproducible evidence rather than only p value significance. The study proposes a methodology for investigating reproducible evidence without conducting separate fMRI experiments. The reproducible evidence is gathered from the separate runs within the study. The associated empirical Bayes and ROC extensions of the linear model provide parameter estimates to determine reproducibility. Empirical applications of the methodology suggest that reproducible evidence is robust to small sample sizes and sensitive to both the magnitude and persistency of brain activation. It is demonstrated that research findings in fMRI studies would be more compelling with supporting reproducible evidence in addition to standard hypothesis testing evidence.

Functional MR images and scientific inference: reproducibility maps.

Historically, reproducibility has been the sine qua non of experimental findings that are considered to be scientifically useful. Typically, findings from functional magnetic resonance imaging (fMRI) studies are assessed with statistical parametric maps (SPMs) using a p value threshold. However, a smaller p value does not imply that the observed result will be reproducible. In this study, we suggest interpreting SPMs in conjunction with reproducibility evidence. Reproducibility is defined as the extent to which the active status of a voxel remains the same across replicates conducted under the same conditions. We propose a methodology for assessing reproducibility in functional MR images without conducting separate experiments. Our procedures include the empirical Bayes method for estimating effects due to experimental stimuli, the threshold optimization procedure for assigning voxels to the active status, and the construction of reproducibility maps. In an empirical example, we implemented the proposed methodology to construct reproducibility maps based on data from the study by Ishai et al. (2000). The original experiments involved 12 human subjects and investigated brain regions most responsive to visual presentation of 3 categories of objects: faces, houses, and chairs. The brain regions identified included occipital, temporal, and fusiform gyri. Using our reproducibility analysis, we found that subjects in one of the experiments exercised at least 2 mechanisms in responding to visual objects when performing alternately matching and passive tasks. One gave activation maps closer to those reported in Ishai et al., and the other had related regions in the precuneus and posterior cingulate. The patterns of activated regions are reproducible for at least 4 out of 6 subjects involved in the experiment. Empirical application of the proposed methodology suggests that human brains exhibit different strategies to accomplish experimental tasks when responding to stimuli. It is important to correlate activations to subjects' behavior such as reaction time and response accuracy. Also, the latency between the stimulus presentation and the peak of the hemodynamic response function varies considerably among individual subjects according to types of stimuli and experimental tasks. These variations per se also deserve scientific inquiries. We conclude by discussing research directions relevant to reproducibility evidence in fMRI.