Resting state functional connectivity of the whole head with near-infrared spectroscopy

Resting state connectivity aims to identify spontaneous cerebral hemodynamic fluctuations that reflect neuronal activity at rest. In this study, we investigated the spatial-temporal correlation of hemoglobin concentration signals over the whole head during the resting state. By choosing a source-detector pair as a seed, we calculated the correlation value between its time course and the time course of all other source-detector combinations, and projected them onto a topographic map. In all subjects, we found robust spatial interactions in agreement with previous fMRI and NIRS findings. Strong correlations between the two opposite hemispheres were seen for both sensorimotor and visual cortices. Correlations in the prefrontal cortex were more heterogeneous and dependent on the hemodynamic contrast. HbT provided robust, well defined maps, suggesting that this contrast may be used to better localize functional connectivity. The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results. These results confirm the feasibility of using functional connectivity with optical methods during the resting state, and validate its use to investigate cortical interactions across the whole head

Resting State Connectivity Patterns With Near-infrared Spectroscopy Data Of The Whole Head

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Resting state cerebral dynamics has been a useful approach to explore the brain's functional organization. In this study, we employed graph theory to deeply investigate resting state functional connectivity (rsFC) as measured by near-infrared spectroscopy (NIRS). Our results suggest that network parameters are very similar across time and subjects. We also identified the most frequent connections between brain regions and the main hubs that participate in the spontaneous activity of brain hemodynamics. Similar to previous findings, we verified that symmetrically located brain areas are highly connected. Overall, our results introduce new insights in NIRS-based functional connectivity at rest. (C) 2016 Optical Society of America725242537Sao Paulo Research Foundation (FAPESP) [2012/02500-8, 2013/07559-3, 2014/23873-2, 2015/00576-5]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

On Temporal Connectivity of PFC Via Gauss-Markov Modeling of fNIRS Signals

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus ( IS), congruent stimulus ( CS), and neutral stimulus (NS), respectively. We introduce a new measure, called information transfermetric (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.Bogazici University Research FundBogazici University [04X102D, 04S101]; Turkish State Planning Organization [03K120250, 03K120240]; Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [106E117]; Turkiye Bilimler Akademisi-Genc Bilim Insanlarini Odullendirme Programi (TUBA-GEBIP)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)Manuscript received September 8, 2008; revised December 16, 2008 and March 3, 2009. First published April 28, 2009; current version published February 17, 2010. This work was supported by the Bogazici University Research Fund under Project 04X102D and Project 04S101, and by the Turkish State Planning Organization under Project 03K120250 and Project 03K120240. The work of M. K. Mihcak was supported in part by Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) Career Award 106E117. The work of S. Aydore was supported in part by the Turkiye Bilimler Akademisi-Genc Bilim Insanlarini Odullendirme Programi (TUBA-GEBIP) Award and in part by the TUBITAK Graduate Scholarship. Asterisk indicates corresponding author