Extended Frontal Networks for Visual and Auditory Working Memory.

Working memory (WM) supports the persistent representation of transient sensory information. Visual and auditory stimuli place different demands on WM and recruit different brain networks. Separate auditory- and visual-biased WM networks extend into the frontal lobes, but several challenges confront attempts to parcellate human frontal cortex, including fine-grained organization and between-subject variability. Here, we use differential intrinsic functional connectivity from 2 visual-biased and 2 auditory-biased frontal structures to identify additional candidate sensory-biased regions in frontal cortex. We then examine direct contrasts of task functional magnetic resonance imaging during visual versus auditory 2-back WM to validate those candidate regions. Three visual-biased and 5 auditory-biased regions are robustly activated bilaterally in the frontal lobes of individual subjects (N = 14, 7 women). These regions exhibit a sensory preference during passive exposure to task stimuli, and that preference is stronger during WM. Hierarchical clustering analysis of intrinsic connectivity among novel and previously identified bilateral sensory-biased regions confirms that they functionally segregate into visual and auditory networks, even though the networks are anatomically interdigitated. We also observe that the frontotemporal auditory WM network is highly selective and exhibits strong functional connectivity to structures serving non-WM functions, while the frontoparietal visual WM network hierarchically merges into the multiple-demand cognitive system.

Gradients of functional organization in posterior parietal cortex revealed by visual attention, visual short-term memory, and intrinsic functional connectivity.

Visual attention and visual working memory tasks recruit a common network of lateral frontal cortical (LFC) and posterior parietal cortical (PPC) regions. Here, we examine finer-scale organization of this frontoparietal network. Three LFC regions recruited by visual cognition tasks, superior precentral sulcus (sPCS), inferior precentral sulcus (iPCS), and mid inferior frontal sulcus (midIFS) exhibit differential patterns of resting-state functional connectivity to PPC. A broad dorsomedial to ventrolateral gradient is observed, with sPCS connectivity dominating in the dorsomedial PPC band, iPCS dominating in the middle band, and midIFS dominating in the ventrolateral band. These connectivity-defined subregions of PPC capture differential task activation between a pair of visual attention and working memory tasks. The relative functional connectivity of sPCS and iPCS also varies along the rostral-caudal axis of the retinotopic regions of PPC. iPCS connectivity is relatively stronger near the IPS0/IPS1 and IPS2/IPS3 borders, especially on the lateral portions of these borders, which each preferentially encode central visual field representations. In contrast, sPCS connectivity is relatively stronger elsewhere in retinotopic IPS regions which preferentially encode peripheral visual field representations. These findings reveal fine-scale gradients in functional connectivity within the frontoparietal visual network that capture a high-degree of specificity in PPC functional organization.

Using Expectancy Theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: An fMRI study.

Researchers have yet to apply a formal operationalized theory of motivation to neurobiology that would more accurately and precisely define neural activity underlying motivation. We overcome this challenge with the novel application of the Expectancy Theory of Motivation to human fMRI to identify brain activity that explicitly reflects motivation. Expectancy Theory quantitatively describes how individual constructs determine motivation by defining motivation force as the product of three variables: expectancy - belief that effort will better performance; instrumentality - belief that successful performance leads to particular outcome, and valence - outcome desirability. Here, we manipulated information conveyed by reward-predicting cues such that relative cue-evoked activity patterns could be statistically mapped to individual Expectancy Theory variables. The variable associated with activity in any voxel is only reported if it replicated between two groups of healthy participants. We found signals in midbrain, ventral striatum, sensorimotor cortex, and visual cortex that specifically map to motivation itself, rather than other factors. This is important because, for the first time, it empirically clarifies approach motivation neural signals during reward anticipation. It also highlights the effectiveness of the application of Expectancy Theory to neurobiology to more precisely and accurately probe motivation neural correlates than has been achievable previously.