Effective Connectivity In Brain Networks: Discovering Latent Structure, Network Complexity And Recurrence.

Description

Since the earliest days of neuroscience research, core methods have focused on matching specific functionsto local brain structure and neural activity. The relationship between brain structure and function has been akey motivation for the development and application of novel methods and discovery. Despite the apparentsuccess of this program in identifying brain areas associated with memory, attention, executive control, action-perception, language, etc.. it is typical for many other areas to be engaged during basic cognitive/perceptualtasks, areas that are often considered “background,” “secondary” or often just irrelevant and are consequentlyignored. Given the fundamental nature of the connectivity in brain, theories of cognitive neuroscience will verylikely involve hypotheses about the influence—sometimes called “effective connectivity” (Friston et al, 1994,Sporns, 2011)--- that one brain area may have upon another in the course of basic mental processes. Whetherwe consider language processing, working memory or simple detection tasks, cognitive and perceptualprocesses are likely to include networks of regions that operate interactively to define, both, a distributed aswell as a kind of local computation. It has become increasingly common to posit that networks, circuits, orclusters of brain areas communicate with one another in the implementation of various potential social orsocial-perceptual functions. Many of these hypothesized networks are thought to be organized around 'hubs'that synchronize other areas but are neither exclusive, nor necessary and sufficient, for a given function. Partof this apparent flexibility of brain networks can be attributed to continued ambiguity about the components orparticular function of a given network. For example, many of the brain networks associated with socialfunctioning, include similar function, similar areas, and overlapping networks. As social/affective andcognitive neuroscience continues to evolve it will be more and more critical to disentangle these networks inorder to identify the role that individual networks play in various social, perceptual and cognitive function.Unfortunately, the muddle of networks and their functions has increased rather than decreased in recent years.The field of social and cognitive neuroscience has evolved to a point where principled methods for identifyingnetwork connectivity, and the tools to do so, could well be trans-formative but certainly are urgent. In thisproposal we aim to advance the development of a novel framework based on a model of effective connectivityand Bayesian search called IMaGES (Ramsey et al 2010) using simulation and experimental tests. We alsoaim to develop novel Cognitive Neuroscience tactics and strategies to specifically test graphical models in thebrain and finally we will also develop two new directions including estimation of Recurrent (feedback) networkinformation flow and the Latent structure supporting the complexity and communication within brain networks.
StatusFinished
Effective start/end date9/27/166/30/19

Funding

  • National Institutes of Health (NIH)

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Recurrence
Brain
Neurosciences
Language
Mental Processes
Executive Function
Short-Term Memory
Cognition
Motivation
Communication
Research
Cognitive Neuroscience