eprintid: 3997 rev_number: 9 eprint_status: archive userid: 69 dir: disk0/00/00/39/97 datestamp: 2018-03-09 13:13:21 lastmod: 2018-03-09 13:13:21 status_changed: 2018-03-09 13:13:21 type: monograph metadata_visibility: show creators_name: Almog, Assaf creators_name: Roethler, Ori creators_name: Buijink, Renate creators_name: Michel, Stephan creators_name: Meijer, Johanna H creators_name: Rohling, Jos H T creators_name: Garlaschelli, Diego creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: diego.garlaschelli@imtlucca.it title: Uncovering functional brain signature via random matrix theory ispublished: submitted subjects: QC subjects: RC0321 divisions: EIC full_text_status: public monograph_type: working_paper keywords: Biocomplexity abstract: The brain is organized in a modular way, serving multiple functionalities. This multiplicity requires that both positive (e.g. excitatory, phase-coherent) and negative (e.g. inhibitory, phase-opposing) interactions take place across brain modules. Unfortunately, most methods to detect modules from time series either neglect or convert to positive any measured negative correlation. This may leave a significant part of the sign-dependent functional structure undetected. Here we present a novel method, based on random matrix theory, for the identification of sign-dependent modules in the brain. Our method filters out the joint effects of local (unit-specific) noise and global (system-wide) dependencies that empirically obfuscate such structure. The method is guaranteed to identify an optimally contrasted functional `signature', i.e. a partition into modules that are positively correlated internally and negatively correlated across. The method is purely data-driven, does not use any arbitrary threshold or network projection, and outputs only statistically significant structure. In measurements of neuronal gene expression in the biological clock of mice, the method systematically uncovers two otherwise undetectable, negatively correlated modules whose relative size and mutual interaction strength are found to depend on photoperiod. The neurons alternating between the two modules define a candidate region of functional plasticity for circadian modulation. date: 2017 date_type: published publication: https://arxiv.org/abs/1708.07046 publisher: arXiv pages: 11 id_number: arXiv:1708.07046 institution: IMT Institute for Advanced Studies Lucca official_url: https://arxiv.org/pdf/1708.07046 citation: Almog, Assaf and Roethler, Ori and Buijink, Renate and Michel, Stephan and Meijer, Johanna H and Rohling, Jos H T and Garlaschelli, Diego Uncovering functional brain signature via random matrix theory. Working Paper arXiv (Submitted) document_url: http://eprints.imtlucca.it/3997/1/1708.07046.pdf