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Human cognitive functions arise through the concerted activity of multiple brain regions. Gaining deeper insights into these network-level functions requires not only studying the modular properties of different brain regions in isolation, but also understanding the functional interactions and anatomical connectivity between them. Methods for mapping structural and functional brain connectivity have made dramatic advances in the last decade that follow in tandem with the development of methods that enable in vivo measurement of activity in many different parts of the brain simultaneously. The expansion of this field of research has relied primarily on the use of functional magnetic resonance imaging (fMRI), where the correlation between the hemodynamics signals in different brain regions is thought to indicate associated neural activity between these areas and is used as an index of effective functional connectivity. In parallel, methods to measure the anatomical substrate of the functional interactions between different regions have advanced over the last decade. Diffusion-weighted MRI (DWI) and related methodologies provide information about the micro-structure of the white matter by probing the spatial geometry of water diffusion. This measurement is often used to infer the orientation of populations of fibers in white matter tracts that can be used to estimate the trajectory of fascicles of nerve fibers connecting different parts of the brain. These functional and anatomical methods have classically been used to identify the existence, and sometimes degree, of a connection between two or more regions. However, novel analytical approaches are starting to characterize connectivity patterns that go well beyond identifying edges of connections. For example, many parts of the brain contain topographically organized maps (e.g. retinotopic cortex) and the connections between them may also be topographically organized (e.g. optic radiations, see Ebeling and Reulen, 1988). Enhanced resolution of these methods, along with novel analytical approaches, allows for more refined inferences about the topography of macroscopic connectivity between brain regions (in optic radiation see Sherbondy et al. 2008 and in corticostriatal pathways see Verstynen et al. 2012). Extending methods of stimulus-referred analysis to the analysis of inter-regional connectivity opens the door for novel inferences about the details of these connectivity patterns (Heinzle et al., Haak et al. 2011) as well as understanding the functional and computational consequences of specific projection patterns (e.g. Saygin et al. 2012). Other analytical advances can be used to infer the main direction of influence that exists between regions. This relies on statistical methods such as Granger ‘causality’ (Bressler et al. 2008) and coherency (Sun et al. 2004, 2005) and
utilizes tightly-controlled experimental designs to probe the way in which functional connectivity is modulated by changes in cognitive state (e.g. Lauritzen et al. 2009). The proposed Research Topic will focus on these novel methods and recent findings about structured and directional brain connectivity. In addition, theoretical perspectives will be sought to shed light on the utility and logic of particular instances of structured and directional connectivity.
Human cognitive functions arise through the concerted activity of multiple brain regions. Gaining deeper insights into these network-level functions requires not only studying the modular properties of different brain regions in isolation, but also understanding the functional interactions and anatomical connectivity between them. Methods for mapping structural and functional brain connectivity have made dramatic advances in the last decade that follow in tandem with the development of methods that enable in vivo measurement of activity in many different parts of the brain simultaneously. The expansion of this field of research has relied primarily on the use of functional magnetic resonance imaging (fMRI), where the correlation between the hemodynamics signals in different brain regions is thought to indicate associated neural activity between these areas and is used as an index of effective functional connectivity. In parallel, methods to measure the anatomical substrate of the functional interactions between different regions have advanced over the last decade. Diffusion-weighted MRI (DWI) and related methodologies provide information about the micro-structure of the white matter by probing the spatial geometry of water diffusion. This measurement is often used to infer the orientation of populations of fibers in white matter tracts that can be used to estimate the trajectory of fascicles of nerve fibers connecting different parts of the brain. These functional and anatomical methods have classically been used to identify the existence, and sometimes degree, of a connection between two or more regions. However, novel analytical approaches are starting to characterize connectivity patterns that go well beyond identifying edges of connections. For example, many parts of the brain contain topographically organized maps (e.g. retinotopic cortex) and the connections between them may also be topographically organized (e.g. optic radiations, see Ebeling and Reulen, 1988). Enhanced resolution of these methods, along with novel analytical approaches, allows for more refined inferences about the topography of macroscopic connectivity between brain regions (in optic radiation see Sherbondy et al. 2008 and in corticostriatal pathways see Verstynen et al. 2012). Extending methods of stimulus-referred analysis to the analysis of inter-regional connectivity opens the door for novel inferences about the details of these connectivity patterns (Heinzle et al., Haak et al. 2011) as well as understanding the functional and computational consequences of specific projection patterns (e.g. Saygin et al. 2012). Other analytical advances can be used to infer the main direction of influence that exists between regions. This relies on statistical methods such as Granger ‘causality’ (Bressler et al. 2008) and coherency (Sun et al. 2004, 2005) and
utilizes tightly-controlled experimental designs to probe the way in which functional connectivity is modulated by changes in cognitive state (e.g. Lauritzen et al. 2009). The proposed Research Topic will focus on these novel methods and recent findings about structured and directional brain connectivity. In addition, theoretical perspectives will be sought to shed light on the utility and logic of particular instances of structured and directional connectivity.
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