{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T06:30:29Z","timestamp":1773383429728,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,11]],"date-time":"2018-05-11T00:00:00Z","timestamp":1525996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Functional Near InfraRed Spectroscopy (fNIRS) connectivity analysis is often performed using the measured oxy-haemoglobin (HbO2) signal, while the deoxy-haemoglobin (HHb) is largely ignored. The in-common information of the connectivity networks of both HbO2 and HHb is not regularly reported, or worse, assumed to be similar. Here we describe a methodology that allows the estimation of the symmetry between the functional connectivity (FC) networks of HbO2 and HHb and propose a differential symmetry index (DSI) indicative of the in-common physiological information. Our hypothesis is that the symmetry between FC networks associated with HbO2 and HHb is above what should be expected from random networks. FC analysis was done in fNIRS data collected from six freely-moving healthy volunteers over 16 locations on the prefrontal cortex during a real-world task in an out-of-the-lab environment. In addition, systemic data including breathing rate (BR) and heart rate (HR) were also synchronously collected and used within the FC analysis. FC networks for HbO2 and HHb were established independently using a Bayesian networks analysis. The DSI between both haemoglobin (Hb) networks with and without systemic influence was calculated. The relationship between the symmetry of HbO2 and HHb networks, including the segregational and integrational characteristics of the networks (modularity and global efficiency respectively) were further described. Consideration of systemic information increases the path lengths of the connectivity networks by 3%. Sparse networks exhibited higher asymmetry than dense networks. Importantly, our experimental connectivity networks symmetry between HbO2 and HHb departs from random (t-test: t(509) = 26.39, p &lt; 0.0001). The DSI distribution suggests a threshold of 0.2 to decide whether both HbO2 and HHb FC networks ought to be studied. For sparse FC networks, analysis of both haemoglobin species is strongly recommended. Our DSI can provide a quantifiable guideline for deciding whether to proceed with single or both Hb networks in FC analysis.<\/jats:p>","DOI":"10.3390\/a11050070","type":"journal-article","created":{"date-parts":[[2018,5,14]],"date-time":"2018-05-14T02:57:20Z","timestamp":1526266640000},"page":"70","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Estimating Functional Connectivity Symmetry between Oxy- and Deoxy-Haemoglobin: Implications for fNIRS Connectivity Analysis"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4093-8066","authenticated-orcid":false,"given":"Samuel","family":"Montero-Hernandez","sequence":"first","affiliation":[{"name":"Department of Computer Sciences, Instituto Nacional de Astrof\u00edsica \u00d3ptica y Electr\u00f3nica, 72840 Puebla, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8963-7283","authenticated-orcid":false,"given":"Felipe","family":"Orihuela-Espina","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, Instituto Nacional de Astrof\u00edsica \u00d3ptica y Electr\u00f3nica, 72840 Puebla, Mexico"}]},{"given":"Luis","family":"Sucar","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, Instituto Nacional de Astrof\u00edsica \u00d3ptica y Electr\u00f3nica, 72840 Puebla, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6667-3481","authenticated-orcid":false,"given":"Paola","family":"Pinti","sequence":"additional","affiliation":[{"name":"Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"},{"name":"Institute of Cognitive Neuroscience, University College London, London WC1E 6BT, UK"}]},{"given":"Antonia","family":"Hamilton","sequence":"additional","affiliation":[{"name":"Institute of Cognitive Neuroscience, University College London, London WC1E 6BT, UK"}]},{"given":"Paul","family":"Burgess","sequence":"additional","affiliation":[{"name":"Institute of Cognitive Neuroscience, University College London, London WC1E 6BT, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8125-0313","authenticated-orcid":false,"given":"Ilias","family":"Tachtsidis","sequence":"additional","affiliation":[{"name":"Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/S0166-2236(97)01132-6","article-title":"Non-invasive optical spectroscopy and imaging of human brain function","volume":"20","author":"Villringer","year":"1997","journal-title":"Trends Neurosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.cobme.2017.09.011","article-title":"Functional near infrared spectroscopy: Enabling routine functional brain imaging","volume":"4","author":"Selb","year":"2017","journal-title":"Curr. Opin. Biomed. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1002\/hbm.460020107","article-title":"Functional and effective connectivity in neuroimaging: A synthesis","volume":"2","author":"Friston","year":"1994","journal-title":"Hum. Brain Mapp."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1089\/brain.2011.0008","article-title":"Functional and Effective Connectivity: A Review","volume":"1","author":"Friston","year":"2011","journal-title":"Brain Connect."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2922","DOI":"10.1016\/j.neuroimage.2010.10.058","article-title":"Assessment of the Cerebral Cortex during Motor Task Behaviours in Adults: A Systematic Review of Functional Near Infrared Spectroscopy (fNIRS) Studies","volume":"54","author":"Leff","year":"2011","journal-title":"Neuroimage"},{"key":"ref_6","first-page":"240","article-title":"Coupling of brain activity and cerebral blood flow: Basis of functional neuroimaging","volume":"7","author":"Villringer","year":"1995","journal-title":"Cerebrovasc. Brain Metab. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1146\/annurev.neuro.29.051605.112819","article-title":"Brain Work and Brain Imaging","volume":"29","author":"Raichle","year":"2006","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Van Wijk, B.C.M., Stam, C.J., and Daffertshofer, A. (2010). Comparing brain networks of different size and connectivity density using graph theory. PLoS ONE, 5.","DOI":"10.1371\/journal.pone.0013701"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1016\/j.neuroimage.2006.08.048","article-title":"A spatial and temporal comparison of hemodynamic signals measured using optical and functional magnetic resonance imaging during activation in the human primary visual cortex","volume":"34","author":"Toronov","year":"2007","journal-title":"Neuroimage"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1364\/BOE.1.000324","article-title":"Resting state functional connectivity of the whole head with near-infrared spectroscopy","volume":"1","author":"Mesquita","year":"2010","journal-title":"Biomed. Opt. Express"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.neuroimage.2009.03.058","article-title":"Resting-state functional connectivity in the human brain revealed with diffuse optical tomography","volume":"47","author":"White","year":"2009","journal-title":"Neuroimage"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1150","DOI":"10.1016\/j.neuroimage.2010.02.080","article-title":"Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements","volume":"51","author":"Zhang","year":"2010","journal-title":"Neuroimage"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1016\/j.neuroimage.2010.12.007","article-title":"Test\u2013retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy","volume":"55","author":"Zhang","year":"2011","journal-title":"Neuroimage"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.jneumeth.2009.11.010","article-title":"Use of fNIRS to assess resting state functional connectivity","volume":"186","author":"Lu","year":"2010","journal-title":"J. Neurosci. Methods"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2524","DOI":"10.1364\/BOE.7.002524","article-title":"Resting state connectivity patterns with near-infrared spectroscopy data of the whole head","volume":"7","author":"Novi","year":"2016","journal-title":"Biomed. Opt. Express"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"39801","DOI":"10.1117\/1.NPh.3.3.039801","article-title":"Publisher\u2019s note: False positives and false negatives in functional near-infrared spectroscopy: Issues, challenges, and the way forward","volume":"3","author":"Tachtsidis","year":"2016","journal-title":"Neurophotonics"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3701","DOI":"10.1088\/0031-9155\/55\/13\/009","article-title":"Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation","volume":"55","author":"Leff","year":"2010","journal-title":"Phys. Med. Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.neuroimage.2016.08.058","article-title":"Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy","volume":"143","author":"Caldwell","year":"2016","journal-title":"Neuroimage"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neuroimage.2012.02.074","article-title":"The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy","volume":"61","author":"Kirilina","year":"2012","journal-title":"Neuroimage"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"285","DOI":"10.3389\/fnhum.2015.00285","article-title":"deB Can apparent resting state connectivity arise from systemic fluctuations?","volume":"9","author":"Tong","year":"2015","journal-title":"Front. Hum. Neurosci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"813","DOI":"10.3389\/fnhum.2013.00813","article-title":"A new methodical approach in neuroscience: Assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI) hyperscanning","volume":"7","author":"Scholkmann","year":"2013","journal-title":"Front. Hum. Neurosci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Crivelli, D., and Balconi, M. (2017). Near-Infrared Spectroscopy Applied to Complex Systems and Human Hyperscanning Networking. Appl. Sci., 7.","DOI":"10.3390\/app7090922"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.neuroimage.2004.02.023","article-title":"Separability and cross-talk: Optimizing dual wavelength combinations for near-infrared spectroscopy of the adult head","volume":"22","author":"Uludag","year":"2004","journal-title":"Neuroimage"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1006\/nimg.2002.1227","article-title":"A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation","volume":"17","author":"Strangman","year":"2002","journal-title":"Neuroimage"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1006\/nimg.2002.1128","article-title":"Different time evolution of oxyhemoglobin and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: A near-infrared spectroscopy study","volume":"16","author":"Wolf","year":"2002","journal-title":"Neuroimage"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.neuroimage.2010.12.075","article-title":"Frequency-specific functional connectivity in the brain during resting state revealed by NIRS","volume":"56","author":"Sasai","year":"2011","journal-title":"Neuroimage"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"D280","DOI":"10.1364\/AO.48.00D280","article-title":"A HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain","volume":"48","author":"Huppert","year":"2009","journal-title":"Appl. Opt."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.1002\/mrm.22159","article-title":"Disease state prediction from resting state functional connectivity","volume":"62","author":"Craddock","year":"2009","journal-title":"Magn. Reson. Med."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3110","DOI":"10.1016\/j.neuroimage.2009.11.011","article-title":"Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI","volume":"49","author":"Shen","year":"2010","journal-title":"Neuroimage"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pinti, P., Aichelburg, C., Lind, F., Power, S., Swingler, E., Merla, A., Hamilton, A., Gilbert, S., Burgess, P., and Tachtsidis, I. (2015). Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks. J. Vis. Exp., 1\u201313.","DOI":"10.3791\/53336-v"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1016\/S0028-3932(02)00327-5","article-title":"The role of the rostral frontal cortex (area 10) in prospective memory: A lateral versus medial dissociation","volume":"41","author":"Burgess","year":"2003","journal-title":"Neuropsychologia"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"43704","DOI":"10.1063\/1.3115207","article-title":"Development of wearable optical topography system for mapping the prefrontal cortex activation","volume":"80","author":"Atsumori","year":"2009","journal-title":"Rev. Sci. Instrum."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1088\/0967-3334\/33\/2\/259","article-title":"Wavelet-based motion artifact removal for functional near-infrared spectroscopy","volume":"33","author":"Molavi","year":"2012","journal-title":"Physiol. Meas."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Spirtes, P., Glymour, C., Scheines, R., and Burr, T. (2000). Causation, Prediction, and Search, MIT Press. [2nd ed.].","DOI":"10.7551\/mitpress\/1754.001.0001"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"26","DOI":"10.18637\/jss.v047.i11","article-title":"Causal Inference Using Graphical Models with the R Package pcalg","volume":"47","author":"Kalisch","year":"2012","journal-title":"J. Stat. Softw."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"92","DOI":"10.2174\/2213385203666150328002017","article-title":"Group-analysis of Resting-state fMRI Based on Bayesian Network: A Comparison of Three Virtual-typical-subject Methods","volume":"2","author":"Tong","year":"2015","journal-title":"Neurosci. Biomed. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.neuroimage.2008.01.068","article-title":"Dynamic Bayesian network modeling of fMRI: A comparison of group-analysis methods","volume":"41","author":"Li","year":"2008","journal-title":"Neuroimage"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.ijar.2013.03.013","article-title":"Bayesian network models in brain functional connectivity analysis","volume":"55","author":"Ide","year":"2014","journal-title":"Int. J. Approx. Reason."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sucar, L.E. (2015). Probabilistic Graphical Models: Principles and Applications, Springer. Advances in Computer Vision and Pattern Recognition.","DOI":"10.1007\/978-1-4471-6699-3"},{"key":"ref_40","unstructured":"Montero-Hernandez, S.A., Orihuela-Espina, F., Herrera-Vega, J., and Sucar, L.E. (2016). Causal Probabilistic Graphical Models for Decoding Effective Connectivity in Functional Near InfraRed Spectroscopy. Twenty-Ninth International Florida Artificial Intelligence Research Society Conference Causal, AAAI Press."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2695","DOI":"10.1016\/j.neuroimage.2010.10.054","article-title":"Effective connectivity of fMRI data using ancestral graph theory: Dealing with missing regions","volume":"54","author":"Waldorp","year":"2011","journal-title":"Neuroimage"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"118","DOI":"10.3389\/fncom.2014.00118","article-title":"Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state","volume":"8","author":"Wu","year":"2014","journal-title":"Front. Comput. Neurosci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1016\/j.neuroimage.2009.08.065","article-title":"Six problems for causal inference from fMRI","volume":"49","author":"Ramsey","year":"2010","journal-title":"Neuroimage"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1016\/j.neuroimage.2006.01.031","article-title":"Learning functional structure from fMR images","volume":"31","author":"Zheng","year":"2006","journal-title":"Neuroimage"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.neuroimage.2007.06.003","article-title":"Learning effective brain connectivity with dynamic Bayesian networks","volume":"37","author":"Rajapakse","year":"2007","journal-title":"Neuroimage"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"198701","DOI":"10.1103\/PhysRevLett.87.198701","article-title":"Efficient Behavior of Small-World Networks","volume":"87","author":"Latora","year":"2001","journal-title":"Phys. Rev. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"66133","DOI":"10.1103\/PhysRevE.69.066133","article-title":"Fast algorithm for detecting community structure in networks","volume":"69","author":"Newman","year":"2004","journal-title":"Phys. Rev. E\u2014Stat. Nonlinear Soft Matter Phys."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"26113","DOI":"10.1103\/PhysRevE.69.026113","article-title":"Finding and evaluating community structure in networks","volume":"69","author":"Newman","year":"2004","journal-title":"Phys. Rev. E"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.amc.2015.02.042","article-title":"A comparative analysis of the Tanimoto index and graph edit distance for measuring the topological similarity of trees","volume":"259","author":"Dehmer","year":"2015","journal-title":"Appl. Math. Comput."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1007\/s10803-016-2987-y","article-title":"A Meta-Analysis and Critical Review of Prospective Memory in Autism Spectrum Disorder","volume":"47","author":"Landsiedel","year":"2017","journal-title":"J. Autism Dev. Disord."},{"key":"ref_51","unstructured":"Stuss, D.T., and Knight, R.T. (2013). Rostral Prefrontal Cortex (Brodmann Area 10): Metacognition in the Brain. Principles of Frontal Lobe Function, Oxford University Press."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1007\/s00429-015-1001-3","article-title":"Atlasing the frontal lobe connections and their variability due to age and education: A spherical deconvolution tractography study","volume":"221","author":"Rojkova","year":"2016","journal-title":"Brain Struct. Funct."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.cortex.2011.10.001","article-title":"Monkey to human comparative anatomy of the frontal lobe association tracts","volume":"48","author":"Valabregue","year":"2012","journal-title":"Cortex"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1006\/nimg.2002.1136","article-title":"Virtual in Vivo interactive dissection of white matter fasciculi in the human brain","volume":"17","author":"Catani","year":"2002","journal-title":"Neuroimage"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1016\/j.neuroimage.2010.07.032","article-title":"Distinct functional connectivity associated with lateral versus medial rostral prefrontal cortex: A meta-analysis","volume":"53","author":"Gilbert","year":"2010","journal-title":"Neuroimage"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1098\/rstb.1996.0124","article-title":"The Domain of Supervisory Processes and Temporal Organization of Behaviour","volume":"351","author":"Shallice","year":"1996","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1017\/S1355617706060310","article-title":"The case for the development and use of \u201cecologically valid\u201d measures of executive function in experimental and clinical neuropsychology","volume":"12","author":"Burgess","year":"2006","journal-title":"J. Int. Neuropsychol. Soc."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2246","DOI":"10.1016\/j.neuropsychologia.2011.02.014","article-title":"Functional neuroimaging studies of prospective memory: What have we learnt so far?","volume":"49","author":"Burgess","year":"2011","journal-title":"Neuropsychologia"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.neuroimage.2013.10.013","article-title":"Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state","volume":"86","author":"Carbonell","year":"2014","journal-title":"Neuroimage"},{"key":"ref_60","first-page":"20110612","article-title":"The impact of latent confounders in directed network analysis in neuroscience","volume":"371","author":"Ramb","year":"2013","journal-title":"Philos. Trans. A Math. Phys. Eng. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1006\/nimg.2000.0657","article-title":"Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in Human Adults","volume":"12","author":"Obrig","year":"2000","journal-title":"Neuroimage"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"96006","DOI":"10.1117\/1.JBO.19.9.096006","article-title":"Optimizing the regularization for image reconstruction of cerebral diffuse optical tomography","volume":"19","author":"Habermehl","year":"2014","journal-title":"J. Biomed. Opt."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"864","DOI":"10.3389\/fnhum.2013.00864","article-title":"Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex","volume":"7","author":"Kirlilna","year":"2013","journal-title":"Front. Hum. Neurosci."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1118\/1.598943","article-title":"Near-infrared study of fluctuations in cerebral hemodynamics during rest and motor stimulation: Temporal analysis and spatial mapping","volume":"27","author":"Toronov","year":"2000","journal-title":"Med. Phys."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/11\/5\/70\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:03:55Z","timestamp":1760195035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/11\/5\/70"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,11]]},"references-count":64,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2018,5]]}},"alternative-id":["a11050070"],"URL":"https:\/\/doi.org\/10.3390\/a11050070","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,11]]}}}