{"id":8858,"date":"2026-03-26T10:00:13","date_gmt":"2026-03-26T14:00:13","guid":{"rendered":"https:\/\/www.bu.edu\/neurophotonics\/?p=8858"},"modified":"2026-05-11T08:52:34","modified_gmt":"2026-05-11T12:52:34","slug":"decoding-the-dynamic-functional-connectivity-in-the-brain","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/neurophotonics\/2026\/03\/26\/decoding-the-dynamic-functional-connectivity-in-the-brain\/","title":{"rendered":"Decoding the Dynamic Functional Connectivity in the Brain"},"content":{"rendered":"

Did you know that brain activity evolves over time? Sometimes it can synchronize sections of the brain, other times it can disconnect\u2013\u2013and during periods of disease, the patterns can be altogether altered. This evolution is known as dynamic functional connectivity (dFC), and can be measured using Blood Oxygenation Level Dependent (BOLD) fMRI studies. Because dFC patterns are altered in brain diseases, there arises the prospect of clinical utility for early diagnosis of mental and neurodegenerative disorders, evaluation of treatments, or tracking of mental health. However, adoption of dFC in standard clinical practice is hampered by limited knowledge of the underlying biological mechanisms.<\/span><\/p>\n

\"\"A new study published in Nature<\/em><\/a><\/strong>, led by <\/span>Professor Anna Devor (BME)<\/span><\/a>, demonstrates that states of arousal affect dFC, a finding that has far-reaching implications for neuroimaging. While BOLD fMRI is widely used for imaging of brain activity, the BOLD signal is sensitive to hemodynamics\u2013\u2013blood flow, volume and oxygenation\u2013\u2013rather than activity of the brain\u2019s neurons. Active neurons release neurochemicals that dilate blood vessels, which then bring glucose and oxygen to active regions.\u00a0<\/span><\/p>\n

\u201cIn this way, fMRI and functional Near Infrared Spectroscopy (fNIRS) measure neuronal activity indirectly, by looking at its effect on hemodynamics,\u201d says Dr. Devor. \u201cThis relationship can be characterized as a neurovascular transfer function linking neuronal activity to hemodynamic signals measured with neuroimaging.\u201d<\/span><\/p>\n

\"\"To perform these measurements, Devor\u2019s team took advantage of neurophotonic tools only available in model organisms such as mice. \u201cOur measurements are based on genetically encoded fluorescent sensors that we express in the brains of living mice,\u201d says the first co-author <\/span>Natalie Fomin-Thunemann<\/span><\/a>, a postdoctoral fellow working with Dr. Devor. \u201cWe can see the process of neurovascular coupling in real time. This is very exciting! These tools provide the microscopic \u2018ground truth\u2019 we need to learn the lessons and develop models that can be translated from mice to humans.\u201d<\/span><\/p>\n

The main neurochemical that modulates arousal and alertness is norepinephrine. It is a cousin of adrenaline, a key hormone in stress responses. Paradoxically, norepinephrine is both a neuro-stimulant and vasoconstrictor.\u00a0<\/span><\/p>\n

\"\"\u201cNorepinephrine influences the neurovascular transfer function in frontal cortical regions much stronger than others,\u201d explains first co-author <\/span>Brad Rauscher<\/span><\/a>, a BME graduate student. \u201cBecause norepinephrine is a vasoconstrictor, hemodynamics in the anterior cortex de-correlates with sensory, motor, and visual areas. And this is despite perfect correlation of the underlying neuronal activity! These mouse data suggest that if we see a decrease in dFC between the frontal cortex and other regions in human BOLD fMRI during high arousal, this may be a false flag.\u201d<\/span><\/p>\n

The finding that norepinephrine and the state of arousal influence hemodynamic correlations across cerebral cortex and cause departures from the underlying neuronal correlations provides a bridge from correlation structure of dFC to biological mechanisms that may be targeted by treatments. Because norepinephrine belongs to a group of neuromodulatory transmitters that make internal cognitive and emotional brain states, the team has also started thinking of possibilities to decode the neuromodulatory brain state from the dynamic relationship between neuronal and vascular signals in the brain.<\/span><\/p>\n

\u201cThis study was a truly multidisciplinary effort of a kind that requires a large and coherent effort,\u201d says Dr. Devor. \u201cWe are blessed with outstanding trainees and an amazing team of senior investigators at BU and beyond who are putting their heads together to crack the neurovascular code that translates large-scale, synchronous patterns of neural activity into hemodynamics that would be detected by fMRI. The Nature Neuroscience publication is a milestone, and I\u2019m happy to see it out. In the meantime, we have already moved to the next step: translation of these results to fMRI studies in humans, with <\/span>Dr. Laura Lewis<\/span><\/a> at MIT, and fNIRS with <\/span>Dr. David Boas<\/span><\/a> here at BU.\u201d<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Did you know that brain activity evolves over time? Sometimes it can synchronize sections of the brain, other times it can disconnect\u2013\u2013and during periods of disease, the patterns can be altogether altered. This evolution is known as dynamic functional connectivity (dFC), and can be measured using Blood Oxygenation Level Dependent (BOLD) fMRI studies. Because dFC […]<\/p>\n","protected":false},"author":22337,"featured_media":8869,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[30,27],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/posts\/8858"}],"collection":[{"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/users\/22337"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/comments?post=8858"}],"version-history":[{"count":4,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/posts\/8858\/revisions"}],"predecessor-version":[{"id":8865,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/posts\/8858\/revisions\/8865"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/media\/8869"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/media?parent=8858"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/categories?post=8858"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/neurophotonics\/wp-json\/wp\/v2\/tags?post=8858"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}