0. Sections ------------ 1. Project 2. Dataset 3. Terms of Use 4. Contents 5. Method and Processing 1. PROJECT ------------ Title: Brain-Computer Music Interface for Monitoring and Inducing Affective States (BCMI-MIdAS) Dates: 2012-2017 Funding organisation: Engineering and Physical Sciences Research Council (EPSRC) Grant no.: EP/J003077/1 and EP/J002135/1. 2. DATASET ------------ Title: EEG data investigating neural correlates of music-induced emotion. Description: This dataset accompanies the publication by Daly et al. (2018) and has been analysed in Daly et al. (2014; 2015a; 2015b) (please see Section 5 for full references). The purpose of the research activity in which the data were collected was to investigate the EEG neural correlates of music-induced emotion. For this purpose 31 healthy adult participants listened to 40 music clips of 12 s duration each, targeting a range of emotional states. The music clips comprised excerpts from film scores spanning a range of styles and rated on induced emotion. The dataset contains unprocessed EEG data from all 31 participants (age range 18-66, 18 female) while listening to the music clips, together with the reported induced emotional responses . The paradigm involved 6 runs of EEG recordings. The first and last runs were resting state runs, during which participants were instructed to sit still and rest for 300 s. The other 4 runs each contained 10 music listening trials. Publication Year: 2018 Creator: Nicoletta Nicolaou, Ian Daly. Contributors: Isil Poyraz Bilgin, James Weaver, Asad Malik. Principal Investigator: Slawomir Nasuto (EP/J003077/1). Co-Investigator: Eduardo Miranda (EP/J002135/1). Organisation: University of Reading Rights-holders: University of Reading Source: The musical stimuli were taken from Eerola & Vuoskoski, “A comparison of the discrete and dimensional models of emotion in music”, Psychol. Music, 39:18-49, 2010 (doi: 10.1177/0305735610362821). 3. TERMS OF USE ----------------- Copyright University of Reading, 2018. This dataset is licensed by the rights-holder(s) under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/. 4. CONTENTS ------------ BIDS File listing: The dataset comprises data from 31 participants, named using the convention: sub_s_number where: s_number is a random participant number from 1 to 31. For example: ‘sub-08’ contains data obtained from participant 8. The data is BIDS format and contains EEG and associated meta data. The sampling rate is 1 kHz and the EEG corresponding to a music clip is 20 s long (the duration of the clips). Each data folder contains the following data (please note that the number of runs varies between participants): EEG data in .tsv format. Event codes (JSON) and timings (tsv). EEG channel information. 5. METHOD and PROCESSING -------------------------- This information is available in the following publications: [1] Daly, I., Nicolaou, N., Williams, D., Hwang, F., Kirke, A., Miranda, E., Nasuto, S.J., Neural and physiological data from participants listening to affective music, Scientific Data, 2018. [2] Daly, I., Malik, A., Hwang, F., Roesch, E., Weaver, J., Kirke, A., Williams, D., Miranda, E. R., Nasuto, S. J., Neural correlates of emotional responses to music: an EEG study, Neuroscience Letters, 573: 52-7, 2014; doi: 10.1016/j.neulet.2014.05.003. [3] Daly, I., Hallowell, J., Hwang, F., Kirke, A., Malik, A., Roesch, E., Weaver, J., Williams, D., Miranda, E., Nasuto, S.J., Changes in music tempo entrain movement related brain activity, Proc. IEEE EMBC 2014, pp.4595-8; doi: 10.1109/EMBC.2014.6944647 [4] Daly, I., Williams, D., Hallowell, J., Hwang, F., Kirke, A., Malik, A., Weaver, J., Miranda, E., Nasuto, S.J., Music-induced emotions can be predicted from a combination of brain activity and acoustic features, Brain and Cognition, 101:1-11, 2015b; doi: 10.1016/j.bandc.2015.08.003 Please cite these references if you use this dataset in your study. Thank you for your interest in our work.