The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin
Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain n...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Xiao [verfasserIn] Zhu, Xiao-Hong [verfasserIn] Zhang, Yi [verfasserIn] Chen, Wei [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Brain topography - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988, 26(2012), 3 vom: 04. Dez., Seite 363-377 |
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| Übergeordnetes Werk: |
volume:26 ; year:2012 ; number:3 ; day:04 ; month:12 ; pages:363-377 |
| Links: |
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| DOI / URN: |
10.1007/s10548-012-0267-5 |
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| Katalog-ID: |
SPR011051280 |
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| 245 | 1 | 4 | |a The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin |
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| 520 | |a Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. | ||
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| 650 | 4 | |a Resting-state fMRI (rs-fMRI) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Functional connectivity |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Anesthesia |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Animal models |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Neural origin |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhu, Xiao-Hong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yi |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Wei |e verfasserin |4 aut | |
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10.1007/s10548-012-0267-5 doi (DE-627)SPR011051280 (SPR)s10548-012-0267-5-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Liu, Xiao verfasserin aut The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 Zhu, Xiao-Hong verfasserin aut Zhang, Yi verfasserin aut Chen, Wei verfasserin aut Enthalten in Brain topography Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988 26(2012), 3 vom: 04. Dez., Seite 363-377 (DE-627)320524574 (DE-600)2015003-9 1573-6792 nnns volume:26 year:2012 number:3 day:04 month:12 pages:363-377 https://dx.doi.org/10.1007/s10548-012-0267-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 26 2012 3 04 12 363-377 |
| spelling |
10.1007/s10548-012-0267-5 doi (DE-627)SPR011051280 (SPR)s10548-012-0267-5-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Liu, Xiao verfasserin aut The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 Zhu, Xiao-Hong verfasserin aut Zhang, Yi verfasserin aut Chen, Wei verfasserin aut Enthalten in Brain topography Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988 26(2012), 3 vom: 04. Dez., Seite 363-377 (DE-627)320524574 (DE-600)2015003-9 1573-6792 nnns volume:26 year:2012 number:3 day:04 month:12 pages:363-377 https://dx.doi.org/10.1007/s10548-012-0267-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 26 2012 3 04 12 363-377 |
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10.1007/s10548-012-0267-5 doi (DE-627)SPR011051280 (SPR)s10548-012-0267-5-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Liu, Xiao verfasserin aut The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 Zhu, Xiao-Hong verfasserin aut Zhang, Yi verfasserin aut Chen, Wei verfasserin aut Enthalten in Brain topography Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988 26(2012), 3 vom: 04. Dez., Seite 363-377 (DE-627)320524574 (DE-600)2015003-9 1573-6792 nnns volume:26 year:2012 number:3 day:04 month:12 pages:363-377 https://dx.doi.org/10.1007/s10548-012-0267-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 26 2012 3 04 12 363-377 |
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10.1007/s10548-012-0267-5 doi (DE-627)SPR011051280 (SPR)s10548-012-0267-5-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Liu, Xiao verfasserin aut The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 Zhu, Xiao-Hong verfasserin aut Zhang, Yi verfasserin aut Chen, Wei verfasserin aut Enthalten in Brain topography Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988 26(2012), 3 vom: 04. Dez., Seite 363-377 (DE-627)320524574 (DE-600)2015003-9 1573-6792 nnns volume:26 year:2012 number:3 day:04 month:12 pages:363-377 https://dx.doi.org/10.1007/s10548-012-0267-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 26 2012 3 04 12 363-377 |
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10.1007/s10548-012-0267-5 doi (DE-627)SPR011051280 (SPR)s10548-012-0267-5-e DE-627 ger DE-627 rakwb eng 610 ASE 44.90 bkl Liu, Xiao verfasserin aut The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 Zhu, Xiao-Hong verfasserin aut Zhang, Yi verfasserin aut Chen, Wei verfasserin aut Enthalten in Brain topography Dordrecht [u.a.] : Springer Science + Business Media B.V, 1988 26(2012), 3 vom: 04. Dez., Seite 363-377 (DE-627)320524574 (DE-600)2015003-9 1573-6792 nnns volume:26 year:2012 number:3 day:04 month:12 pages:363-377 https://dx.doi.org/10.1007/s10548-012-0267-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 26 2012 3 04 12 363-377 |
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Functional MRI (fMRI) BOLD Resting-state fMRI (rs-fMRI) Functional connectivity Anesthesia Animal models Neural origin |
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Liu, Xiao @@aut@@ Zhu, Xiao-Hong @@aut@@ Zhang, Yi @@aut@@ Chen, Wei @@aut@@ |
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To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. 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Liu, Xiao |
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Liu, Xiao ddc 610 bkl 44.90 misc Functional MRI (fMRI) misc BOLD misc Resting-state fMRI (rs-fMRI) misc Functional connectivity misc Anesthesia misc Animal models misc Neural origin The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin |
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610 ASE 44.90 bkl The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin Functional MRI (fMRI) (dpeaa)DE-He213 BOLD (dpeaa)DE-He213 Resting-state fMRI (rs-fMRI) (dpeaa)DE-He213 Functional connectivity (dpeaa)DE-He213 Anesthesia (dpeaa)DE-He213 Animal models (dpeaa)DE-He213 Neural origin (dpeaa)DE-He213 |
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ddc 610 bkl 44.90 misc Functional MRI (fMRI) misc BOLD misc Resting-state fMRI (rs-fMRI) misc Functional connectivity misc Anesthesia misc Animal models misc Neural origin |
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change of functional connectivity specificity in rats under various anesthesia levels and its neural origin |
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The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin |
| abstract |
Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. |
| abstractGer |
Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. |
| abstract_unstemmed |
Abstract Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0 % isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8 % isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states. |
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| container_issue |
3 |
| title_short |
The Change of Functional Connectivity Specificity in Rats Under Various Anesthesia Levels and its Neural Origin |
| url |
https://dx.doi.org/10.1007/s10548-012-0267-5 |
| remote_bool |
true |
| author2 |
Zhu, Xiao-Hong Zhang, Yi Chen, Wei |
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Zhu, Xiao-Hong Zhang, Yi Chen, Wei |
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| doi_str |
10.1007/s10548-012-0267-5 |
| up_date |
2024-07-03T20:04:20.807Z |
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| score |
7.402135 |