![]() ![]() Novel analytic fMRI techniques, such as multivariate pattern analysis (MVPA), employ the distributed patterns of voxels across a brain region to make inferences about information content rather than whether a small number of voxels go up or down relative to baseline in response to a stimulus. Relatedly, I consider four important factors in linking fMRI to neural activity: interpretation of correlations between these signals, regional variability in local vasculature, distributed neural coding schemes and varying fMRI signal quality. While there is some support for this idea in sensory cortices, findings in deeper brain structures like the hippocampus instead suggest both regional and frequency-wise differences. Here, I evaluate the proposal that BOLD signal changes equate to changes in gamma-band activity, which in turn may partially relate to the spiking activity of neurons. A major research goal, therefore, has been to uncover a ‘Rosetta Stone’ providing direct translation between the blood oxygen level-dependent (BOLD) signal, the local field potential and single-neuron activity. Functional magnetic resonance imaging (fMRI) is the dominant tool in cognitive neuroscience although its relation to underlying neural activity, particularly in the human brain, remains largely unknown. ![]()
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