Differences in fMRI intersubject correlation while viewing unedited and edited videos of dance performance

Intersubject Correlation (ISC) analysis of fMRI data provides insight into how continuous streams of sensory stimulation are processed by groups of observers. Although edited movies are frequently used as stimuli in ISC studies, there has been little direct examination of the effect of edits on the resulting ISC maps. In this study we showed 16 observers two audiovisual movie versions of the same dance. In one experimental condition there was a continuous view from a single camera (Unedited condition) and in the other condition there were views from different cameras (Edited condition) that provided close up views of the feet or face and upper body. We computed ISC maps for each condition, as well as created a map that showed the difference between the conditions. The results from the Unedited and Edited maps largely overlapped in the occipital and temporal cortices, although more voxels were found for the Edited map. The difference map revealed greater ISC for the Edited condition in the Postcentral Gyrus, Lingual Gyrus, Precentral Gyrus and Medial Frontal Gyrus, while the Unedited condition showed greater ISC in only the Superior Temporal Gyrus. These findings suggest that the visual changes associated with editing provide a source of correlation in maps obtained from edited film, and highlight the utility of using maps to evaluate the difference in ISC between conditions

A versatile software package for inter-subject correlation based analyses of fMRI

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with resampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time.Peer reviewe

Inter-Subject Correlation in fMRI: Method Validation against Stimulus-Model Based Analysis

Peer reviewe

Utilizing the International Classification of Functioning, Disability and Health (ICF) in forming a personal health index

We propose a new model for comprehensively monitoring the health status of individuals by calculating a personal health index. The central framework of the model is the International Classification of Functioning, Disability and Health (ICF) developed by the World Health Organization. The model is capable of handling incomplete and heterogeneous data sets collected using different techniques. The health index was validated by comparing it to two self-assessed health measures provided by individuals undergoing rehabilitation. Results indicate that the model yields valid health index outcomes, suggesting that the proposed model is applicable in practice.Comment: 29 pages, 15 figure

Time-resolved classification of dog brain signals reveals early processing of faces, species and emotion

Dogs process faces and emotional expressions much like humans, but the time windows important for face processing in dogs are largely unknown. By combining our non-invasive electroencephalography (EEG) protocol on dogs with machine-learning algorithms, we show category-specific dog brain responses to pictures of human and dog facial expressions, objects, and phase-scrambled faces. We trained a support vector machine classifier with spatiotemporal EEG data to discriminate between responses to pairs of images. The classification accuracy was highest for humans or dogs vs. scrambled images, with most informative time intervals of 100-140 ms and 240-280 ms. We also detected a response sensitive to threatening dog faces at 30-40 ms; generally, responses differentiating emotional expressions were found at 130-170 ms, and differentiation of faces from objects occurred at 120-130 ms. The cortical sources underlying the highest-amplitude EEG signals were localized to the dog visual cortex.Peer reviewe

Three-Way Analysis of Spectrospatial Electromyography Data : Classification and Interpretation

Classifying multivariate electromyography (EMG) data is an important problem in prosthesis control as well as in neurophysiological studies and diagnosis. With modern high-density EMG sensor technology, it is possible to capture the rich spectrospatial structure of the myoelectric activity. We hypothesize that multi-way machine learning methods can efficiently utilize this structure in classification as well as reveal interesting patterns in it. To this end, we investigate the suitability of existing three-way classification methods to EMG-based hand movement classification in spectrospatial domain, as well as extend these methods by sparsification and regularization. We propose to use Fourier-domain independent component analysis as preprocessing to improve classification and interpretability of the results. In high-density EMG experiments on hand movements across 10 subjects, three-way classification yielded higher average performance compared with state-of-the art classification based on temporal features, suggesting that the three-way analysis approach can efficiently utilize detailed spectrospatial information of high-density EMG. Phase and amplitude patterns of features selected by the classifier in finger-movement data were found to be consistent with known physiology. Thus, our approach can accurately resolve hand and finger movements on the basis of detailed spectrospatial information, and at the same time allows for physiological interpretation of the results.Peer reviewe

Spectators’ aesthetic experience of sound and movement in dance performance:a transdisciplinary investigation

We utilize qualitative audience research and functional brain imaging (fMRI) to examine the aesthetic experience of watching dance both with and without music. This transdisciplinary approach was motivated by the recognition that the aesthetic experience of dance revealed through conscious interpretation could have neural correlates in brain activity. When audiences were engaged in watching dance accompanied by music, the fMRI data revealed evidence of greater intersubject correlation in a left anterior region of the superior temporal gyrus known to be involved in complex audio processing. Moreover, the qualitative data revealed how spectators derived pleasure from finding convergences between 2 complex stimuli (dance and music). Without music, greater intersubject correlation was found bilaterally in a posterior region of the superior temporal gyrus, showing that bodily sounds such as breath provide a more salient auditory signal than music in primary auditory regions. Watching dance without music also resulted in increased intersubject correlation among spectators in the parietal and occipitotemporal cortices, suggesting a greater influence of the body than when interpreting the dance stimuli with music. Similarly, the audience research found evidence of corporeally focused experience, but suggests that while embodied responses were common across spectators, they were accompanied by different evaluative judgments

Decoding Emotional Valence from Electroencephalographic Rhythmic Activity

We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.Peer reviewe

Adalimumab and sulfasalazine in alleviating sacroiliac and aortic inflammation detected in PET/CT in patients with axial spondyloarthritis : PETSPA

Publisher Copyright: © 2021 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.Aim: Inflammatory signals in the sacroiliac (SI) joints and the aorta of patients with axial spondyloarthritis (axSpA) were graded by positron emission tomography/computed tomography (PET/CT) imaging before and after treatment with sulfasalazine (SSZ) or adalimumab (ADA). Methods: Patients with axSpA, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ≥ 4, were recruited. Disease-modifying antirheumatic drug-naïve patients started SSZ for 12 weeks, whereas those with prestudy treatment with or contraindication to SSZ commenced ADA for 16 weeks. In addition, those patients in the SSZ group with insufficient response commenced ADA for 16 weeks. 18F-fluorodeoxyglucose PET/CT was performed after inclusion and after treatment with SSZ and ADA. Maximum standardized uptake value (SUVmax) was assessed for the aorta and the SI joints, and maximal target-to-blood-pool ratio (TBRmax) only for the aorta. Results: Among five SSZ patients, mean ± SD BASDAI was 4.7 ± 1.6 before and 3.5 ± 1.4 after treatment (p =.101). In 13 ADA patients, the BASDAI decreased from 5.4 ± 1.6 to 2.8 ± 2.2 (p <.001). Among the SSZ patients, SUVmax in SI joints decreased from 2.35 ± 0.55 to 1.51 ± 0.22 (−35.8%, p =.029). Aortic TBRmax decreased from 1.59 ± 0.43 to 1.26 ± 0.26 (−33.2%, p =.087). In the ADA patients, SUVmax in the SI joints was 1.92 ± 0.65 before and 1.88 ± 0.54 after treatment (−1.8%, p =.808) and TBRmax in the aorta 1.50 ± 0.60 before and 1.40 ± 0.26 after treatment (−6.7%, p =.485). Conclusions: Our small open-label study showed that SSZ may reduce PET-CT-detectable inflammation in the SI joints, with a trend towards a reduction in the aorta.Peer reviewe

Collaborative roles of Temporoparietal Junction and Dorsolateral Prefrontal Cortex in Different Types of Behavioural Flexibility

Behavioural flexibility is essential for everyday life. This involves shifting attention between different perspectives. Previous studies suggest that flexibility is mainly subserved by the dorsolateral prefrontal cortex (DLPFC). However, although rarely emphasized, the temporoparietal junction (TPJ) is frequently recruited during flexible behaviour. A crucial question is whether TPJ plays a role in different types of flexibility, compared to its limited role in perceptual flexibility. We hypothesized that TPJ activity during diverse flexibility tasks plays a common role in stimulus-driven attention-shifting, thereby contributing to different types of flexibility, and thus the collaboration between DLPFC and TPJ might serve as a more appropriate mechanism than DLPFC alone. We used fMRI to measure DLPFC/TPJ activity recruited during moral flexibility, and examined its effect on other domains of flexibility (economic/perceptual). Here, we show the additional, yet crucial role of TPJ: a combined DLPFC/TPJ activity predicted flexibility, regardless of domain. Different types of flexibility might rely on more basic attention-shifting, which highlights the behavioural significance of alternatives.Peer reviewe