The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

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BrainNet Viewer: a network visualization tool for human brain connectomics.

https://sites.oxy.edu/clint/physio/article/therewardcircuitlinkingprimateanatomyandhumanimaging.pdf

The reward circuit: linking primate anatomy and human imaging.

We provide an “executive-attention” framework for organizing the cognitive neuroscience research on the constructs of working-memory capacity (WMC), general fluid intelligence, and prefrontal cortex (PFC) function. Rather than provide a novel theory of PFC function, we synthesize a wealth of singlecell, brain-imaging, and neuropsychological research through the lens of our theory of normal individual differences in WMC and attention control (Engle, Kane, & Tuholski, 1999; Engle, Tuholski, Laughlin, & Conway, 1999). Our critical review confirms the prevalent view that dorsolateral PFC circuitry is critical to executive-attention functions. Moreover, although the dorsolateral PFC is but one critical structure in a network of anterior and posterior “attention control” areas, it does have a unique executiveattention role in actively maintaining access to stimulus representations and goals in interference-rich contexts. Our review suggests the utility of an executive-attention framework for guiding future research on both PFC function and cognitive control.

/pdf/the-role-of-prefrontal-cortex-in-working-memory-capacity-jwrotkwivk.pdf

The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective

Hedonic experience is arguably at the heart of what makes us human. In recent neuroimaging studies of the cortical networks that mediate hedonic experience in the human brain, the orbitofrontal cortex has emerged as the strongest candidate for linking food and other types of reward to hedonic experience. The orbitofrontal cortex is among the least understood regions of the human brain, but has been proposed to be involved in sensory integration, in representing the affective value of reinforcers, and in decision making and expectation. Here, the functional neuroanatomy of the human orbitofrontal cortex is described and a new integrated model of its functions proposed, including a possible role in the mediation of hedonic experience.

Jelliffe

Papers

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