About this Research Topic
Functional MRI has had a significant impact on a wide range of fields that study human behavior and its underlying neural mechanisms. It has been argued that fMRI can provide information about the human brain that is not available through other neuroimaging mechanisms and, therefore, holds a place of importance in the field of Neuroscience. However, as an indirect measurement of the aggregate responses in relatively large neural populations, fMRI is biased toward some aspects of neuronal responses and blind to others. This Research Topic solicits contributions arguing both sides of the question. On the one hand, evidence suggests that the bias of fMRI to reflect neural computations that are common across a large population of neurons lends efficiency to experiments that aim to map responses on the meso- or macro-scale (a few millimeters to several centimeters). On the other hand, it has been claimed that the inability of fMRI to resolve signals that are either unique to a subpopulation of neurons, or diverse on the scale of the hypercolumn, creates a dangerous blindness for experiments that aim to uncover the nuances of the local population code.
We are interested in both theoretical and empirical contributions. Examples of theoretical contributions might be: (1) well-founded opinion pieces serving as an orientation to the field for a new user and offering an opinion on what fMRI should not try to do; (2) computational work on neurohemodynamic coupling indicating what aspects of the neuronal population response are not detectable in the hemodynamic response; (3) computational work on the neural code indicating the relative contributions of different sub-populations to the local neuronal response. Examples of empirical contributions might be: (1) datasets and analyses demonstrating the failure of fMRI to reflect a known aspect of the local neuronal response; (2) datasets and analyses demonstrating a surprising fMRI response where there is no known neuronal sensitivity; (3) multimodal studies differentiating sensitivity of fMRI and other modalities (e.g., EEG) to local neuronal responses.
Keywords: neuroimaging, computational neuroscience, encoding, decoding, inference
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