@inproceedings{41428a2558714335be6e2e34a3bcded5,
title = "Decoding Olfactory Cognition: EEG Functional Modularity Analysis Reveals Differences in Perception of Positively-Valenced Stimuli",
abstract = "Investigating the functional modular organisation of the brain provides a deeper insight into the complex network phenomena that govern cognitive processes like olfactory perception. In recent years, understanding the neural mechanisms associated with this unique sensory modality has been gaining traction, due to increasing applications in various clinical and non-clinical research areas. Anatomically distinct, but functionally interconnected brain regions, organized as communities (or functional modules) enable high-order cognitive processes by providing support for the integration of several localized, highly specialized processing functions. In this work, to understand the elicited neuronal communication pathways in response to fragrance stimuli of varying positive valence, graph theoretical network metrics were calculated to quantify differences in brain{\textquoteright}s functional networks modular organization estimated from source localised EEG signals. We found that inter-modular connectivity differences in neural responses to olfactory stimuli of different pleasantness levels may be linked to inhibitory processes in the frontal and central-occipital regions. Moreover, our results indicate that significant intra-modular connectivity changes may be linked to emotional processing of fragrance stimuli of varying pleasantness.",
keywords = "Brain networks, Functional modularity, Graph theory, Olfaction",
author = "Abbasi, {Nida Itrat} and Sony Saint-Auret and Junji Hamano and Anumita Chaudhury and anastasios Bezerianos and Thakor, {Nitish V.} and Andrei Dragomir",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 27th International Conference on Neural Information Processing, ICONIP 2020 ; Conference date: 18-11-2020 Through 22-11-2020",
year = "2020",
doi = "10.1007/978-3-030-63836-8_7",
language = "English (US)",
isbn = "9783030638351",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "79--89",
editor = "Haiqin Yang and Kitsuchart Pasupa and Leung, {Andrew Chi-Sing} and Kwok, {James T.} and Chan, {Jonathan H.} and Irwin King",
booktitle = "Neural Information Processing - 27th International Conference, ICONIP 2020, Proceedings",
address = "Germany",
}