The Role of Neural Context in Large-Scale Neurocognitive Network Operations

Abstract

Brain connectivity has been a central factor in the development of theories about the mind-brain link. In its simplest form, brain connectivity analysis has revealed serial processing systems, wherein specific neural elements (neurons, neuronal assemblies, neuronal populations) cooperate to express a circumscribed function that is realized as information passes through the system in a feedforward manner. Consideration of parallel architectures provides a more complex view of system processing by revealing that each brain region may impact many other regions through direct and indirect routes, including areas from which it receives its input. Regardless of the specific architecture, the notion that cognition results from the operations of large-scale neural networks has been present in various forms throughout the history of neuroscience (Finger, 1994; Bressler 1995Bressler , 2002. For a large part of that history, it was difficult to verify this notion because most available methods only allowed investigation of small parts of the nervous system in isolation. Ideally, simultaneous measures from many parts of the brain must be analyzed to understand the operations of large-scale networks that underlie cognition. In the past few decades, advances in functional neuroimaging, including Positron Emission Tomography (PET) functional Magnetic Resonance Imaging (fMRI), and EEG/MEG-based source localization, have allowed simultaneous distributed measures of brain function to be related to cognition.This chapter examines the role of a critical aspect of brain function, which we call neural context, in the selective functioning of interacting neural systems in cognition. We define neural context as the local processing environment of a given neural element that is created by modulatory influences from other neural elements. Neural context allows the response properties of one element in a network to be profoundly affected by the status of other neural elements in that network. As a result of neural context, the relevance of a given neural element for cognitive function typically depends on the status of other interacting elements (McIntosh 1999;Bressler 2003a). By this definition, the processing performed by a given brain area may be modulated by a potentially

Natural world physical, brain operational, and mind phenomenal space–time

“…These findings lead to the conclusion that such optimal resting state in the brain depends upon a delicate metastable balance between local specialized processes and global integration. Excess or lack of either component would be a deviation of the optimal situation (see also [2,123,550]). At the same time, our data pointed to the fact that not all characteristics of neuronal assemblies' dynamics and their functional interrelations during a particular pathological condition are incompatible with dynamics of normal brain functioning.…”

Interpretation of Neuroimaging Data Based on Network Concepts

“…What distinguishes the operation is not the involvement of the area per se, but rather the status of other areas during that function. This dependence of the contribution of a region on other connected regions has been referred to as "neural context" (Bressler and Mcintosh 2007). Neural context allows the response properties of one element in a network to be profoundly affected by the status of other neural elements in that network.…”

“…Contextual effects can be demonstrated in simple nervous systems, basic sensory functions, and higher cognitive functions (Bressler and Mcintosh 2007). An appreciation of neural context formed the basis for considering working memory at the confluence of sustained attention and memory.…”

Neural field dynamics with local and global connectivity and time delay

“…Large-scale neural network models are thought to be involved in the implementation of cognitive function of the brain (Bressler 1995(Bressler , 2002(Bressler , 2003Bullmore et al 1996;Mesulam 1998;Mountcastle 1998;McIntosh 2000;Bressler & Kelso 2001;Jirsa 2004;Bressler & Tognoli 2006;Bressler & McIntosh 2007). In particular, peripheral areas are more functionally differentiated, whereas the ensuing cognitive integration appears to require more global network activations.…”