Tracking the will to attend: Cortical activity indexes self-generated, voluntary shifts of attention.

The neural substrates of volition have long tantalized philosophers and scientists. Over the past few decades, researchers have employed increasingly sophisticated technology to investigate this issue, but many studies have been limited considerably by their reliance on intrusive experimental procedures (e.g., abrupt instructional cues), measures of brain activity contaminated by overt behavior, or introspective self-report techniques of questionable validity. Here, we used multivoxel pattern time-course analysis of functional magnetic resonance imaging data to index voluntary, covert perceptual acts-shifts of visuospatial attention-in the absence of instructional cues, overt behavioral indices, and self-report. We found that these self-generated, voluntary attention shifts were time-locked to activity in the medial superior parietal lobule, supporting the hypothesis that this brain region is engaged in voluntary attentional reconfiguration. Self-generated attention shifts were also time-locked to activity in the basal ganglia, a novel finding that motivates further research into the role of the basal ganglia in acts of volition. Remarkably, prior to self-generated shifts of attention, we observed early and selective increases in the activation of medial frontal (dorsal anterior cingulate) and lateral prefrontal (right middle frontal gyrus) cortex-activity that likely reflects processing related to the intention or preparation to reorient attention. These findings, which extend recent evidence on freely chosen motor movements, suggest that dorsal anterior cingulate and lateral prefrontal cortices play key roles in both overt and covert acts of volition, and may constitute core components of a brain network underlying the will to attend.

Mild Cognitive Impairment is Associated With White Matter Integrity Changes in Late-Myelinating Regions Within the Corpus Callosum.

Degenerative brain changes in Alzheimer's disease may occur in reverse order of normal brain development based on the retrogenesis model. This study tested whether evidence of reverse myelination was observed in mild cognitive impairment (MCI) using a data-driven analytic approach based on life span developmental data. Whole-brain high-resolution diffusion tensor imaging scans were obtained for 31 patients with MCI and 79 demographically matched healthy older adults. Comparisons across corpus callosum (CC) regions of interest (ROIs) showed decreased fractional anisotropy (FA) in the body but not in the genu or splenium; early-, middle-, and late-myelinating ROIs restricted to the CC revealed decreased FA in late- but not early- or middle-myelinating ROIs. Voxelwise group differences revealed areas of lower FA in MCI, but whole-brain differences were equally distributed across early-, middle-, and late-myelinating regions. Overall, results within the CC support the retrogenesis model, although caution is needed when generalizing these results beyond the CC.

Tracking cognitive fluctuations with multivoxel pattern time course (MVPTC) analysis.

The posterior parietal cortex, including the medial superior parietal lobule (mSPL), becomes transiently more active during acts of cognitive control in a wide range of domains, including shifts of spatial and nonspatial visual attention, shifts between working memory representations, and shifts between categorization rules. Furthermore, spatial patterns of activity within mSPL, identified using multivoxel pattern analysis (MVPA), reliably distinguish between different acts of control. Here we describe a novel multivoxel pattern-based analysis that uses fluctuations in cognitive state over time to reveal inter-regional functional connectivity. First, we used MVPA to model patterns of activity in mSPL associated with shifting or maintaining spatial attention. We then computed a multivoxel pattern time course (MVPTC) that reflects, moment-by-moment, the degree to which the pattern of activity in mSPL more closely matches an attention-shift pattern or a sustained-attention pattern. We then entered the MVPTC as a regressor in a univariate (i.e., voxelwise) general linear model (GLM) to identify voxels whose BOLD activity covaried with the MVPTC. This analysis revealed several regions, including the striatum of the basal ganglia and bilateral middle frontal gyrus, whose activity was significantly correlated with the MVPTC in mSPL. For comparison, we also conducted a conventional functional connectivity analysis, entering the mean BOLD time course in mSPL as a regressor in a univariate GLM. The latter analysis revealed correlations in extensive regions of the frontal lobes but not in any subcortical area. The MVPTC analysis provides greater sensitivity (e.g., revealing the striatal-mSPL connectivity) and greater specificity (i.e., revealing more-focal clusters) than a conventional functional connectivity analysis. We discuss the broad applicability of MVPTC analysis to a variety of neuroimaging contexts.