2013
DOI: 10.1038/nmeth.2730
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Deciphering laminar-specific neural inputs with line-scanning fMRI

Abstract: Using a line-scanning method during functional magnetic resonance imaging (fMRI) we obtain high temporal (50 ms) and spatial (50 μm) resolution information along the cortical thickness, and show that the laminar position of fMRI onset coincides with distinct neural inputs t in therat somatosensory and motor cortices. This laminar specific fMRI onset allowed the identification of the neural inputs underlying ipsilateral fMRI activation in the barrel cortex due to peripheral denervation-induced plasticity.

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Cited by 165 publications
(247 citation statements)
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“…For 24 example, Trampel et al, (2012) investigated the increased activity in primary motor cortex 25 (M1) associated with motor imagery as compared with an actual motion task, demonstrating 26 that the layer dependence of the ensuing activation differs strikingly for the two conditions. In 27 another example, layer-dependent fMRI was used to study the input characteristics of sensory 28 cortex, and thus to investigate the restructuring of brain connectivity consequent upon 29 denervation-induced plasticity (Yu et al, 2014). In the visual system, layer-dependent fMRI 30 can help to address questions regarding the feedforward-feedback pathways during excitatory 31 and inhibitory stimuli (Goense et al, 2012).…”
mentioning
confidence: 99%
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“…For 24 example, Trampel et al, (2012) investigated the increased activity in primary motor cortex 25 (M1) associated with motor imagery as compared with an actual motion task, demonstrating 26 that the layer dependence of the ensuing activation differs strikingly for the two conditions. In 27 another example, layer-dependent fMRI was used to study the input characteristics of sensory 28 cortex, and thus to investigate the restructuring of brain connectivity consequent upon 29 denervation-induced plasticity (Yu et al, 2014). In the visual system, layer-dependent fMRI 30 can help to address questions regarding the feedforward-feedback pathways during excitatory 31 and inhibitory stimuli (Goense et al, 2012).…”
mentioning
confidence: 99%
“…Channels with unstable signal or severe aliasing artifacts 42 (between 0 and 8) were excluded from the subsequent sum-of-squares combination (see 43 supplementary Fig. S1 for more details).…”
mentioning
confidence: 99%
“…In the present study, T 1 values between segments after the TGN stimulation stage were also well correlated in the range 0.2-1 s with slopes close to 1.0 for all the layers (not shown). Understanding how neural activity is distributed among cortical layers in the barrel cortex is complex (Herman et al 2013;Yu et al 2014). Recently, Yu et al (2014) concluded that the location of BOLD fMRI onset matches well with the input layers across the cortical depth as detected by MEMRI.…”
Section: Discussionmentioning
confidence: 99%
“…Understanding how neural activity is distributed among cortical layers in the barrel cortex is complex (Herman et al 2013;Yu et al 2014). Recently, Yu et al (2014) concluded that the location of BOLD fMRI onset matches well with the input layers across the cortical depth as detected by MEMRI. However, they also mentioned that differences in timing between fMRI and neural events make their results difficult to interpret.…”
Section: Discussionmentioning
confidence: 99%
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