Brain Connectivity and, more generally, neural causal networks are currently one of the fastest growing topics in Neuroscience. In contrast to how much we know about the functioning of isolated structures in the brain, there is relatively less understanding about how those areas interconnect with each other, especially in regard to the temporal sequences of network component activation that underlie cognitive processes.
The last decade has seen an exponential growth in the number of methods developed for studying brain connectivity. Unfortunately many of them remain controversial, either because of inadequate understanding of the connectivity aspects each method is supposed to expose, or more commonly because most methods have not been sufficiently tested and fail to adequately integrate different neuro-imaging modalities to produce a more solid and trustworthy picture of the underlying cognitive dynamics.
The aim of this research topic is to bring together the work of different groups in this field that are both developing and using these methods in order to study patterns of connectivity in the brain, to compare the available techniques, to discuss the state of the art, and to stimulate the development of approaches by integrating the knowledge accumulated in different fields.
Many questions are required to tackle this topic systematically:
• Can methods to study functional connectivity, whether based on the EEG, MEG, fMRI or SPECT or other modalities benefit from knowledge of the anatomical connectivity obtained through tractography?
• How far is it possible to push the granularity of estimators of brain connectivity? Are we able to develop reliable methods that can attain voxel level resolution from a limited number of sensors such as used for the EEG/MEG inverse problem?
• Are the current methods for electrophysiological source imaging able to infer the connectivity patterns at a mesoscopic level using scalp information?
• Beyond mere connectivity, can we determine the precise nature of the connections as well as the temporal sequence of activation? In other words, how important is the specific nature of connections for the workings of the brain?
• When can we determine that a connection is more than merely functional but is also effective? In other words, to what extent can one determine causal interactions between neural masses and actually gauge their strength?
• Is the HRF deconvolution necessary for an accurate fMRI-based connectivity analysis?
In posing these questions we wish to stimulate discussions and encourage researchers to reassess their methods, making room for useful refinements. By establishing a common framework for method appraisal with the same metrics on standardized datasets, we hope to allow an evaluation of the performance and the applicability of each method in a variety of situations.
The 2015 edition of the Brain Connectivity Workshop series recently held in La Jolla, California, saw attractive and provocative discussions highlighting the importance of the theme of using electrophysiological recordings for the connectivity analysis. Thus, we also welcome workshop participants to share the aftermath of their conclusions with the larger community.
Brain Connectivity and, more generally, neural causal networks are currently one of the fastest growing topics in Neuroscience. In contrast to how much we know about the functioning of isolated structures in the brain, there is relatively less understanding about how those areas interconnect with each other, especially in regard to the temporal sequences of network component activation that underlie cognitive processes.
The last decade has seen an exponential growth in the number of methods developed for studying brain connectivity. Unfortunately many of them remain controversial, either because of inadequate understanding of the connectivity aspects each method is supposed to expose, or more commonly because most methods have not been sufficiently tested and fail to adequately integrate different neuro-imaging modalities to produce a more solid and trustworthy picture of the underlying cognitive dynamics.
The aim of this research topic is to bring together the work of different groups in this field that are both developing and using these methods in order to study patterns of connectivity in the brain, to compare the available techniques, to discuss the state of the art, and to stimulate the development of approaches by integrating the knowledge accumulated in different fields.
Many questions are required to tackle this topic systematically:
• Can methods to study functional connectivity, whether based on the EEG, MEG, fMRI or SPECT or other modalities benefit from knowledge of the anatomical connectivity obtained through tractography?
• How far is it possible to push the granularity of estimators of brain connectivity? Are we able to develop reliable methods that can attain voxel level resolution from a limited number of sensors such as used for the EEG/MEG inverse problem?
• Are the current methods for electrophysiological source imaging able to infer the connectivity patterns at a mesoscopic level using scalp information?
• Beyond mere connectivity, can we determine the precise nature of the connections as well as the temporal sequence of activation? In other words, how important is the specific nature of connections for the workings of the brain?
• When can we determine that a connection is more than merely functional but is also effective? In other words, to what extent can one determine causal interactions between neural masses and actually gauge their strength?
• Is the HRF deconvolution necessary for an accurate fMRI-based connectivity analysis?
In posing these questions we wish to stimulate discussions and encourage researchers to reassess their methods, making room for useful refinements. By establishing a common framework for method appraisal with the same metrics on standardized datasets, we hope to allow an evaluation of the performance and the applicability of each method in a variety of situations.
The 2015 edition of the Brain Connectivity Workshop series recently held in La Jolla, California, saw attractive and provocative discussions highlighting the importance of the theme of using electrophysiological recordings for the connectivity analysis. Thus, we also welcome workshop participants to share the aftermath of their conclusions with the larger community.
