An approach for identifying brainstem dopaminergic pathways using resting state functional MRI.

Here, we present an approach for identifying brainstem dopaminergic pathways using resting state functional MRI. In a group of healthy individuals, we searched for significant functional connectivity between dopamine-rich midbrain areas (substantia nigra; ventral tegmental area) and a striatal region (caudate) that was modulated by both a pharmacological challenge (the administration of the dopaminergic agonist bromocriptine) and a dopamine-sensitive cognitive trait (an individual's working memory capacity). A significant inverted-U shaped connectivity pattern was found in a subset of midbrain-striatal connections, demonstrating that resting state fMRI data is sufficiently powerful to identify brainstem neuromodulatory brain networks

The Dopamine Agonist Bromocriptine Differentially Affects Fronto-Striatal Functional Connectivity During Working Memory

We investigated the effect of bromocriptine, a dopamine agonist, on individual differences in behavior as well as frontal-striatal connectivity during a working memory task. After dopaminergic augmentation, frontal-striatal connectivity in low working memory capacity individuals increases, corresponding with behavioral improvement whereas decreases in connectivity in high working memory capacity individuals are associated with poorer behavioral performance. These findings corroborate an inverted U-shape response of dopamine function in behavioral performance and provide insight on the corresponding neural mechanisms

Distributed and Dynamic Storage of Working Memory Stimulus Information in Extrastriate Cortex

The predominant neurobiological model of working memory (WM) posits that stimulus information is stored via stable, elevated activity within highly selective neurons. On the basis of this model, which we refer to as the canonical model, the storage of stimulus information is largely associated with lateral PFC (lPFC). A growing number of studies describe results that cannot be fully explained by the canonical model, suggesting that it is in need of revision. In this study, we directly tested key elements of the canonical model. We analyzed fMRI data collected as participants performed a task requiring WM for faces and scenes. Multivariate decoding procedures identified patterns of activity containing information about the items maintained in WM (faces, scenes, or both). Although information about WM items was identified in extrastriate visual cortex (EC) and lPFC, only EC exhibited a pattern of results consistent with a sensory representation. Information in both regions persisted even in the absence of elevated activity, suggesting that elevated population activity may not represent the storage of information in WM. Additionally, we observed that WM information was distributed across EC neural populations that exhibited a broad range of selectivity for the WM items rather than restricted to highly selective EC populations. Finally, we determined that activity patterns coding for WM information were not stable, but instead varied over the course of a trial, indicating that the neural code for WM information is dynamic rather than static. Together, these findings challenge the canonical model of WM

Evidence for working memory storage operations in perceptual cortex

Isolating the short-term storage component of working memory (WM) from the myriad of associated executive processes has been an enduring challenge. Recent efforts have identified patterns of activity in visual regions that contain information about items being held in WM. However, it remains unclear (1) whether these representations withstand intervening sensory input and (2) how communication between multimodal association cortex and the unimodal perceptual regions supporting WM representations is involved in WM storage. We present evidence that the features of a face held in WM are stored within face-processing regions, that these representations persist across subsequent sensory input, and that information about the match between sensory input and a memory representation is relayed forward from perceptual to prefrontal regions. Participants were presented with a series of probe faces and indicated whether each probe matched a target face held in WM. We parametrically varied the feature similarity between the probe and target faces. Activity within face-processing regions scaled linearly with the degree of feature similarity between the probe face and the features of the target face, suggesting that the features of the target face were stored in these regions. Furthermore, directed connectivity measures revealed that the direction of information flow that was optimal for performance was from sensory regions that stored the features of the target face to dorsal prefrontal regions, supporting the notion that sensory input is compared to representations stored within perceptual regions and is subsequently relayed forward. Together, these findings indicate that WM storage operations are carried out within perceptual cortex

Division of the caudate into a head/body and tail regions is displayed at the top of the figure.

<p>Venn diagrams illustrate the degree of overlap between caudate voxels (middle figure – head/body; bottom figure – tail) identified as correlated with the midbrain (p < .05, FDR and small-volume corrected) collapsed across span and drug condition (left circle) and caudate voxels identified as having an inverted-U shaped relationship with the midbrain (p < 0.05, uncorrected; right circle). A significantly greater percentage of overlapping voxels are present in the tail than the head/body of the caudate.</p

Whole-brain correlation maps with midbrain seeds across all subjects and across both placebo and bromocriptine sessions.

<p>Maps are thresholded at p < .05 FDR corrected with a minimum cluster size of 20 voxels. The color bar indicates t values.</p

Representative bilateral midbrain ROI (red) on a co-registered T1 image in one participant.

<p>Representative bilateral midbrain ROI (red) on a co-registered T1 image in one participant.</p

Venn diagrams illustrating degree of overlap.

<p><b>Left.</b> Venn diagram illustrates the degree of overlap between caudate voxels identified as correlated with the midbrain (p < 0.05, FDR and small-volume corrected) collapsed across span and drug condition (left circle) and caudate voxels identified as having an inverted-U shaped relationship with the midbrain (p < 0.05, uncorrected; right circle). Only 122/(122+833) voxels (13%) exhibiting significant midbrain-caudate connectivity also exhibit an inverted –U shaped response dependent on span and drug. <b>Right.</b> Venn diagram illustrates the degree of overlap between caudate voxels identified as having greater connectivity with the midbrain in higher span subjects in the placebo sessions (left circle) and caudate voxels identified as having an inverted-U shaped relationship with the midbrain (p < 0.05, uncorrected). Only 61/(61+61) voxels (50%) exhibiting a significant increase in midbrain-caudate connectivity based on span also exhibit an inverted-U shaped response dependent on span and drug. The number of voxels is presented within the circles.</p