Research Topic

What Can fMRI Teach Us About the Neural Code?

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


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

05 January 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..

Topic Editors

Loading..

Submission Deadlines

05 January 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..

Comments

Loading..

Add a comment

Add comment
Back to top