Lost in Time: Temporal Monitoring Elicits Clinical Decrements in Sustained Attention Post-Stroke.

OBJECTIVES: Mental fatigue, 'brain fog', and difficulties maintaining engagement are commonly reported issues in a range of neurological and psychiatric conditions. Traditional sustained attention tasks commonly measure this capacity as the ability to detect target stimuli based on sensory features in the auditory or visual domains. However, with this approach, discrete target stimuli may exogenously capture attention to aid detection, thereby masking deficits in the ability to endogenously sustain attention over time. METHODS: To address this, we developed the Continuous Temporal Expectancy Task (CTET) where individuals continuously monitor a stream of patterned stimuli alternating at a fixed temporal interval (690 ms) and detect an infrequently occurring target stimulus defined by a prolonged temporal duration (1020 ms or longer). As such, sensory properties of target and non-target stimuli are perceptually identical and differ only in temporal duration. Using the CTET, we assessed stroke survivors with unilateral right hemisphere damage (N = 14), a cohort in which sustained attention deficits have been extensively reported. RESULTS: Stroke survivors had overall lower target detection accuracy compared with neurologically healthy age-matched older controls (N = 18). Critically, stroke survivors performance was characterised by significantly steeper within-block performance decrements, which occurred within short temporal windows (˜3 ½ min), and were restored by the break periods between blocks. CONCLUSIONS: These findings suggest that continuous temporal monitoring taxes sustained attention processes to capture clinical deficits in this capacity over time, and outline a precise measure of the endogenous processes hypothesised to underpin sustained attention deficits following right hemisphere stroke.

An MRI method for parcellating the human striatum into matrix and striosome compartments in vivo.

The mammalian striatum is comprised of intermingled tissue compartments, matrix and striosome. Though indistinguishable by routine histological techniques, matrix and striosome have distinct embryologic origins, afferent/efferent connections, surface protein expression, intra-striatal location, susceptibilities to injury, and functional roles in a range of animal behaviors. Distinguishing the compartments previously required post-mortem tissue and/or genetic manipulation; we aimed to identify matrix/striosome non-invasively in living humans. We used diffusion MRI (probabilistic tractography) to identify human striatal voxels with connectivity biased towards matrix-favoring or striosome-favoring regions (determined by prior animal tract-tracing studies). Segmented striatal compartments replicated the topological segregation and somatotopic organization identified in animal matrix/striosome studies. Of brain regions mapped in prior studies, our human brain data confirmed 93% of the compartment-selective structural connectivity demonstrated in animals. Test-retest assessment on repeat scans found a voxel classification error rate of 0.14%. Fractional anisotropy was significantly higher in matrix-like voxels, while mean diffusivity did not differ between the compartments. As mapped by the Talairach human brain atlas, 460 regions were significantly biased towards either matrix or striosome. Our method allows the study of striatal compartments in human health and disease, in vivo, for the first time.

A registration method for improving quantitative assessment in probabilistic diffusion tractography.

Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible - determining where tracts "should" lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity. We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (-35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts "peak-to-peak" is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2 mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts. We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.