Deciphering brain activation during wrist movements: comparative fMRI and fNIRS analysis of active, passive, and imagery states
Understanding the complex activation patterns of brain regions during motor tasks is crucial. Integrated functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) offers advanced insights into how brain activity fluctuates with motor activities. This study explor...
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| description | Understanding the complex activation patterns of brain regions during motor tasks is crucial. Integrated functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) offers advanced insights into how brain activity fluctuates with motor activities. This study explores neuronal activation patterns in the cerebral cortex during active, passive, and imagined wrist movements using these functional imaging techniques. Data were collected from 10 right-handed volunteers performing a motor task using fMRI and fNIRS. fMRI utilized a 3T scanner and a 20-channel head coil, while fNIRS recorded data with a 48-channel device at 765 nm and 855 nm. Analysis focused on key motor and sensory cortices using NIRS-SPM and SPM12, applying a significance threshold of
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| doi_str_mv | 10.1007/s00221-024-06977-7 |
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p
< 0.05 and a minimum cluster size of 10 voxels for group analysis. Super-threshold voxels were identified with FWE thresholding in SPM12. For activation map extraction we focused on the primary motor cortex, primary somatosensory cortex, somatosensory association cortex, premotor cortex, and supplementary motor cortex. Both fMRI and fNIRS detected activation in the primary motor cortex (M1). The primary somatosensory cortex was found to influence movement direction coding, with smaller activation sizes for upward movements. Combining fNIRS with fMRI provided clearer differentiation of brain activation patterns for wrist movements in various directions and conditions (
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p
< 0.05 and a minimum cluster size of 10 voxels for group analysis. Super-threshold voxels were identified with FWE thresholding in SPM12. For activation map extraction we focused on the primary motor cortex, primary somatosensory cortex, somatosensory association cortex, premotor cortex, and supplementary motor cortex. Both fMRI and fNIRS detected activation in the primary motor cortex (M1). The primary somatosensory cortex was found to influence movement direction coding, with smaller activation sizes for upward movements. Combining fNIRS with fMRI provided clearer differentiation of brain activation patterns for wrist movements in various directions and conditions (
p
< 0.05). This study highlights variations in left motor cortex activity across different movement states. fNIRS proved effective in detecting brain function and showed strong correlation with fMRI results, suggesting it as a viable alternative for those unable to undergo fMRI.</description><subject>Adult</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical engineering</subject><subject>Biomedicine</subject><subject>Brain mapping</subject><subject>Brain Mapping - methods</subject><subject>Brain research</subject><subject>Cerebral cortex</subject><subject>Cerebrum</subject><subject>Cortex (motor)</subject><subject>Cortex (premotor)</subject><subject>Female</subject><subject>Functional magnetic resonance imaging</subject><subject>Handedness</subject><subject>Hemoglobin</subject><subject>Humans</subject><subject>Imagination - physiology</subject><subject>Infrared spectroscopy</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Mental task performance</subject><subject>Movement - physiology</subject><subject>Neural coding</subject><subject>Neuroimaging</subject><subject>Neurology</subject><subject>Neurosciences</subject><subject>Preventive medicine</subject><subject>Research Article</subject><subject>Sensory evaluation</subject><subject>Somatosensory cortex</subject><subject>Spectroscopy, Near-Infrared - methods</subject><subject>Spectrum analysis</subject><subject>Wrist</subject><subject>Wrist - physiology</subject><subject>Young Adult</subject><issn>0014-4819</issn><issn>1432-1106</issn><issn>1432-1106</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU1v1DAQhi0EotvCH-CALHHh0FCP7cRrbqh8rdSCVOBsOc64pNp81JMs2hN_vcmmUIkDJ4-tx-94_DD2AsQbEMKckRBSQiakzkRhjcnMI7YCrWQGIIrHbCUE6EyvwR6xY6KbeauMeMqOlDXKgoQV-_0eQ93_xFS317xMvm65D0O980PdtbwaD-e_Uk0Db7odNtgO9JaHrul9mpgd8nh5teG-rXj8srn6NlV-u6eaeBeXJDzlvSc6FDNWN_4a057T4AekZ-xJ9FvC5_frCfvx8cP388_ZxddPm_N3F1mQeTFkygpQWCBa0LHSSmlVliVE1DqGotTS5FqYUGpjQ8wxllCptZWVFQEhaqNO2Oslt0_d7Yg0uKamgNutb7EbySnIRS5B58WEvvoHvenGNI21UFoVazNTcqFC6ogSRtenabS0dyDcrMctetykxx30uPkVL--jx7LB6u-VPz4mQC0A9fPPY3ro_Z_YO5fFm3Q</recordid><startdate>20250101</startdate><enddate>20250101</enddate><creator>Jalalvandi, Maziar</creator><creator>Sharini, Hamid</creator><creator>Shafaghi, Lida</creator><creator>Alam, Nader Riyahi</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20250101</creationdate><title>Deciphering brain activation during wrist movements: comparative fMRI and fNIRS analysis of active, passive, and imagery states</title><author>Jalalvandi, Maziar ; Sharini, Hamid ; Shafaghi, Lida ; Alam, Nader Riyahi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c256t-39013e6ee914fd43343bbb1fe44fc6b4275407cb479cf5efb1d3892d90ce1f473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Adult</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedical engineering</topic><topic>Biomedicine</topic><topic>Brain mapping</topic><topic>Brain Mapping - methods</topic><topic>Brain research</topic><topic>Cerebral cortex</topic><topic>Cerebrum</topic><topic>Cortex (motor)</topic><topic>Cortex (premotor)</topic><topic>Female</topic><topic>Functional magnetic resonance imaging</topic><topic>Handedness</topic><topic>Hemoglobin</topic><topic>Humans</topic><topic>Imagination - physiology</topic><topic>Infrared spectroscopy</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Mental task performance</topic><topic>Movement - physiology</topic><topic>Neural coding</topic><topic>Neuroimaging</topic><topic>Neurology</topic><topic>Neurosciences</topic><topic>Preventive medicine</topic><topic>Research Article</topic><topic>Sensory evaluation</topic><topic>Somatosensory cortex</topic><topic>Spectroscopy, Near-Infrared - methods</topic><topic>Spectrum analysis</topic><topic>Wrist</topic><topic>Wrist - physiology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jalalvandi, Maziar</creatorcontrib><creatorcontrib>Sharini, Hamid</creatorcontrib><creatorcontrib>Shafaghi, Lida</creatorcontrib><creatorcontrib>Alam, Nader Riyahi</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Experimental brain research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jalalvandi, Maziar</au><au>Sharini, Hamid</au><au>Shafaghi, Lida</au><au>Alam, Nader Riyahi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deciphering brain activation during wrist movements: comparative fMRI and fNIRS analysis of active, passive, and imagery states</atitle><jtitle>Experimental brain research</jtitle><stitle>Exp Brain Res</stitle><addtitle>Exp Brain Res</addtitle><date>2025-01-01</date><risdate>2025</risdate><volume>243</volume><issue>1</issue><spage>36</spage><pages>36-</pages><artnum>36</artnum><issn>0014-4819</issn><issn>1432-1106</issn><eissn>1432-1106</eissn><abstract>Understanding the complex activation patterns of brain regions during motor tasks is crucial. Integrated functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) offers advanced insights into how brain activity fluctuates with motor activities. This study explores neuronal activation patterns in the cerebral cortex during active, passive, and imagined wrist movements using these functional imaging techniques. Data were collected from 10 right-handed volunteers performing a motor task using fMRI and fNIRS. fMRI utilized a 3T scanner and a 20-channel head coil, while fNIRS recorded data with a 48-channel device at 765 nm and 855 nm. Analysis focused on key motor and sensory cortices using NIRS-SPM and SPM12, applying a significance threshold of
p
< 0.05 and a minimum cluster size of 10 voxels for group analysis. Super-threshold voxels were identified with FWE thresholding in SPM12. For activation map extraction we focused on the primary motor cortex, primary somatosensory cortex, somatosensory association cortex, premotor cortex, and supplementary motor cortex. Both fMRI and fNIRS detected activation in the primary motor cortex (M1). The primary somatosensory cortex was found to influence movement direction coding, with smaller activation sizes for upward movements. Combining fNIRS with fMRI provided clearer differentiation of brain activation patterns for wrist movements in various directions and conditions (
p
< 0.05). This study highlights variations in left motor cortex activity across different movement states. fNIRS proved effective in detecting brain function and showed strong correlation with fMRI results, suggesting it as a viable alternative for those unable to undergo fMRI.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>39739121</pmid><doi>10.1007/s00221-024-06977-7</doi></addata></record> |
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| subjects | Adult Biomedical and Life Sciences Biomedical engineering Biomedicine Brain mapping Brain Mapping - methods Brain research Cerebral cortex Cerebrum Cortex (motor) Cortex (premotor) Female Functional magnetic resonance imaging Handedness Hemoglobin Humans Imagination - physiology Infrared spectroscopy Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Medical imaging Mental task performance Movement - physiology Neural coding Neuroimaging Neurology Neurosciences Preventive medicine Research Article Sensory evaluation Somatosensory cortex Spectroscopy, Near-Infrared - methods Spectrum analysis Wrist Wrist - physiology Young Adult |
| title | Deciphering brain activation during wrist movements: comparative fMRI and fNIRS analysis of active, passive, and imagery states |
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