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An alternative method to group analysis of fNIRS signals from ecological experiments: An application to an emotional music induced experiment

Cândida D. Barreto1*, Patricia M. Vanzella1 and Joao R. Sato1
  • 1 Centro de Matemática Computação e Cognição, Universidade Federal do ABC, Neuroscience and Cognition, Brazil

Introduction: Functional Near Infrared Spectroscopy-fNIRS has been shown a powerful tool to measure cortical activity of individuals in everyday life situations. However, the analysis of data from experiments with an ecological environment and naturalistic stimuli are limited. Generally, the analysis are based on the hemodynamics response function – HRF. It requires protocols such block designs or evented related which limit the possibilities of ecological experiments with fNIRS. Therefore, other methods to analyse those data are required. In this work, we propose a methodology to analyse fNIRS signals from ecological settings. We compute a pairwise distance between fNIRS signals of pair of subjects (across subjects) and associate those distances with their behavioral responses. The methodology can be described in three main steps: (i) We apply the Inter Subject Correlation-ISC analysis by measuring the similarity between brain hemodynamic signals for each pair of subjects submitted to the same stimuli (Hasson, Nir, Levy, Fuhrmann, & Malach, 2004). (ii) We compute the distance between behavioral responses for each pair of subjects. (iii) We test for associations between the ISC and behavioral responses similarities. We evaluate the statistical significance of these associations using the Multivariate Distance Matrix Regressor (MDMR) (Anderson, 2000). To provide an application, we performed an emotional music induced experiment and applied our methodology to the data from this experiment. Our hypotheses is that individuals who have similar emotional responses to the music, may have more synchronizations on the fNIRS signals. Materials and Methods: 33 subjects participated on the experiment. All participants were submitted to the following protocol: 30s in resting + 60s listening to a music excerpt + time to answer questionnaires +30s resting. The protocol was repeated for eight music excerpts. The excerpts were segmentations of Wagner’s operas. All stimuli have been previously classified as positive/negative valences, and high/low arousal (Andrade, Vanzella, Andrade, & Schellenberg, 2016). We collected the signals from pre-frontal cortex (figure 1), as our primary interest is the emotional response to the music. We computed the correlation of Oxygenated Hemoglobin (OxyHb) and Deoxygenated Hemoglobin (DeoxyHb) signals between each channel for each pair of individuals. Then, we selected the maximum of these correlations and computed the correlation of these values with the difference on the questionnaires answers. Finally, we tested the statistical significance of these correlations using a Multivariate Distance Matrix Regressor (MDMR) (Anderson, 2000) to avoid data dependency problems. Results: All reported results are related to the OxyHb signals, as we did not find any statistical significant results to DeoxyHb signals. A positive statistical significant correlation (r=0.139, p-value < 0.05) between the ICS measure and behavioral response similarities was found for the most negative excerpt. It suggests that subjects with similar emotional responses to the music stimuli presented more similar brain activation trajectories. Furthermore, more than half of the subjects reported responses in agreement with the characterization previously made by (Andrade, Vanzella, Andrade, & Schellenberg, 2016), considering only musicological features. In addition, the subjects most liked the excerpts with positive valence in comparison with the ones with negative valences. Discussion: The proposed method do not require a HRF to analyse fNIRS data. It means that the experimental protocol does not need to be restricted to a block or event related design. It is a simple and practical methodology as It requires only two conditions i) fNIRS data of multiple subjects submitted to the same stimuli; ii) behavioural data (e.g., questionnaires, etc) related to those stimuli. However, some limitations must be considered. The methodology does not give information about activation of specific regions. It informs how the cortical signals synchronization are related to a set of behavioral responses. In addition, it is important to consider that systemic artifacts may cause spurious signal correlations leading to biased results, which might be more related to the vascular responses than the neural ones. Finally, it is fundamental to work with participants in the same age span, since the vascular system is different between children, adults and elderly, Conclusion: We expect that this methodology will contribute to analyse fNIRS data from experiments with more ecological validity, in which block and event-related designs are not suitable.

Figure 1
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References

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Andrade, P. E., Vanzella, P., Andrade, O. V., & Schellenberg, E. G. (24 de November de 2016). Associating emotions with Wagner’s music: A developmental perspective. Psychology of Music. doi:10.1177/0305735616678056

Balardin, J. B., Zimeo Morais, G. A., Furucho, R. A., Trambaiolli, L., Vanzella, P., & Biazoli, C. J. (2017). Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments. Frontiers in Human Neuroscience. doi:10.3389/fnhum.2017.00258

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Keywords: fNIRS, naturalistic stimuli, Inter Subject Correlation, multivariate analysis, Ecological experiments

Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018.

Presentation Type: Poster Presentation

Topic: Neuroergonomics

Citation: Barreto CD, Vanzella PM and Sato JR (2019). An alternative method to group analysis of fNIRS signals from ecological experiments: An application to an emotional music induced experiment. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00061

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Received: 03 Apr 2018; Published Online: 27 Sep 2019.

* Correspondence: Mrs. Cândida D Barreto, Centro de Matemática Computação e Cognição, Universidade Federal do ABC, Neuroscience and Cognition, Santo André, SP, 09210-580, Brazil, ferreira_candida@yahoo.com.br