Authors: Jivesh Ramduny & Clare Kelly
We leverage an emotional evocative movie to study the brain function at multiple spatial and temporal scales in addition to its phenotypic relevance with depressive symptom severity and emotion regulation strategies in a community-based sample of 50 female adolescents enriched for depressive symptoms. The aims of the study are three-fold:
- investigate whole-brain full-length and moment-to-moment brain synchrony during naturalistic emotional viewing, and explore its relationships of each with self-reported depressive symptom severity and emotion regulation strategies;
- examine static and dynamic functional connectivity within an a priori emotion regulation network;
- characterise the underlying stimulus-evoked brain activity using the Hurst Exponent and to explore associations with the phenotypic measures at the network and ROI level.
Participants underwent an fMRI scan during which they watched a movie called The Present (https://www.jacob-frey.com). The Present is an animated film which describes a poignant story featuring a 12-year-old boy who struggles with emotion regulation and self-image in the context of having only one leg. The narrative arc of the film captures changes in the youth’s emotions and emotion regulation around the difficult topic of being differently abled. The film also features a broad range of themes such as frustration, screen-time, disgust, self-image, humour, empathy and attachment. This naturalistic stimulus has recently been used to evoke emotional responses in a psychiatric enriched developmental sample derived from the Healthy Brain Network (Alexander et al., 2017). The movie lasted 4 minutes 18 seconds in total, with the main story taking place during the first 3 minutes 23 seconds, followed by the ending credits (55 seconds). Since the most significant emotional moment of the short movie takes place during the final 87 seconds, we analysed the entire timeseries to account for the haemodynamic delay in the BOLD fMRI signal and enduring emotional processing and regulation.
The structural and functional scans were acquired using a Philips Achieva 3T scanner from the Trinity College Institute of Neuroscience (TCIN) which is located at Trinity College Dublin. A T1-weighted MPRAGE volume with a spatial resolution of 0.9 x 0.9 x 0.9 mm3 (FOV = 230 mm, TR = 8.4 ms, TE = 3.8 ms, flip angle = 8°) was obtained for each participant. The participants underwent resting-state and movie-watching fMRI scans although the resting-state data were not used in the present study. The movie-watching fMRI data were acquired with 132 echo-planar imaging (EPI) volumes (37 slices, TR = 2000 ms, TE = 30 ms, voxel size = 3.2 x 3 x 3 mm3).
The structural and functional scans were preprocessed using the fMRIPrep version stable pipeline (https://fmriprep.org/en/stable/) and in-house scripts using FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL) and AFNI (https://afni.nimh.nih.gov). The structural data underwent bias field correction, skull stripping, tissue segmentation (i.e., grey matter, white matter, cerebrospinal fluid) and spatial normalisation of the anatomical data to the MNI152 standard space using non-linear transformation. Preprocessing of the functional data comprised volume-based motion correction and functional to anatomical co-registration using boundary-based registration. Confound regression was performed with 24 motion parameters (i.e., 3 translational and 3 rotational parameters, their first derivatives and the squares of each of these terms) and 12 nuisance signal regressors (i.e., cerebrospinal fluid, white matter, global signal, their squares and the squares of their first derivatives). Spatial smoothing was applied to the functional data with a Gaussian kernel at 6 mm FWHM followed by temporal filtering (0.01 ≤ f ≤ 0.1 Hz). The fMRI timeseries which were extracted from the Shen parcellation are provided in the movie directory.
movie_watching_analysis: notebook containing full-length ISC analysis, static analysis, hurst exponent analysis among othersemotion_segment: notebook containing the difference in ISC in the high-emotion relative to low-emotion segments of the moviedynamic_isc_analysis: notebook containing dynamic ISC analysis using a tapered cosine sliding windowdynamic_FC_analysis: notebook containing dynamic FC analysis using a tapered cosine sliding windowhurst_exponent_FDR: notebook containing the FDR thresholding of the hurst exponent at the network and ROI level
We kindly thank the volunteers from the community and community-based Child and Adolescent Mental Health Services clinic in Ireland. This work has been supported by the Trinity College Dublin Provost Award (2018-2019) and a NARSAD Young Investigator Award from the Brain and Behaviour Research Foundation (2015-2017) awarded to Dr. Clare Kelly. We also wish to thank the creators of the online book on the naturalistic data analysis as part of the Educational Course for OHBM 2020: https://naturalistic-data.org/content/intro.html.
Ramduny, J., MacSweeney, N., Petkova, E., Kellaghan, E., Lahert, N., Gallagher, L., Vanderwal, T., & Kelly C. Naturalistic emotional processing in adolescent females with depressive symptoms.