White matter hyperintensities negatively impact white matter structure and relate to cognitive decline in aging. Diffusion tensor imaging detects changes to white matter microstructure, both within the white matter hyperintensity and extending into surrounding (perilesional) normal appearing white matter. However, diffusion tensor imaging markers are not specific to tissue components, complicating interpretation of previous microstructural findings. Myelin water imaging is a novel imaging technique that provides specific markers of myelin content (myelin water fraction) and interstitial fluid (geometric mean T2). Here we combined diffusion tensor imaging and myelin water imaging to examine tissue characteristics in white matter hyperintensities and perilesional white matter in 80 individuals (47 older adults and 33 individuals with chronic stroke). To measure perilesional normal appearing white matter, white matter hyperintensity masks were dilated in 2 mm segments up to 10 mm in distance from the white matter hyperintensity. Fractional anisotropy, mean diffusivity, myelin water fraction, and geometric mean T2 were extracted from white matter hyperintensities and perilesional white matter. We observed a spatial gradient of higher mean diffusivity and geometric mean T2, and lower fractional anisotropy, in the white matter hyperintensity and perilesional white matter. In the chronic stroke group, myelin water fraction was reduced in the white matter hyperintensity but did not show a spatial gradient in perilesional white matter. Across the entire sample, white matter metrics within the white matter hyperintensity related to whole-brain white matter hyperintensity volume; with increasing white matter hyperintensity volume there was increased mean diffusivity and geometric mean T2, and decreased myelin water fraction in the white matter hyperintensity. Normal appearing white matter adjacent to white matter hyperintensities exhibits characteristics of a transitional stage between healthy white matter and white matter hyperintensities. This effect was observed in markers sensitive to interstitial fluid, but not in myelin water fraction, the specific marker of myelin concentration. Within the white matter hyperintensity, interstitial fluid was higher and myelin concentration was lower in individuals with more severe cerebrovascular disease. Our data suggests white matter hyperintensities have penumbra-like characteristics in perilesional white matter that specifically reflect increased interstitial fluid, with no changes to myelin concentration. In contrast, within the white matter hyperintensity there are varying levels of demyelination, which vary based on the severity of cerebrovascular disease. Diffusion tensor imaging and myelin imaging may be useful clinical markers to predict white matter hyperintensity formation, and to stage neuronal damage within white matter hyperintensities.

Exercise has emerged as an intervention that may mitigate age-related resting state functional connectivity and sensorimotor decline. Here, 42 healthy older adults rested or completed 3 sets of high-intensity interval exercise for a total of 23 min, then immediately practiced an implicit motor task with their non-dominant hand across five separate sessions. Participants completed resting state functional MRI before the first and after the fifth day of practice; they also returned 24-h and 35-days later to assess short- and long-term retention. Independent component analysis of resting state functional MRI revealed increased connectivity in the frontoparietal, the dorsal attentional, and cerebellar networks in the exercise group relative to the rest group. Seed-based analysis showed strengthened connectivity between the limbic system and right cerebellum, and between the right cerebellum and bilateral middle temporal gyri in the exercise group. There was no motor learning advantage for the exercise group. Our data suggest that exercise paired with an implicit motor learning task in older adults can augment resting state functional connectivity without enhancing behaviour beyond that stimulated by skilled motor practice.

Transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) can facilitate motor learning, but it has not been established how stimulation to other brain regions impacts online and offline motor sequence learning, as well as long-term retention. Here, we completed three experiments comparing the effects of tDCS and sham stimulation to the prefrontal cortex (PFC), M1, and the supplementary motor area complex to understand the contributions of these brain regions to motor sequence learning. In Experiment 1, we found that both left and right PFC tDCS groups displayed a slowing in learning in both reaction time and number of chunks, whereas stimulation over M1 improved both metrics over the course of three sessions. To better understand the sequence learning impairment of left PFC anodal stimulation, we tested a left PFC cathodal tDCS group in Experiment 2. The cathodal group demonstrated learning impairments similar to the left PFC anodal stimulation group. In Experiment 3, a subset of participants from the left PFC, M1, and sham tDCS groups of Experiment 1 returned to complete a single session without tDCS on the same sequences assigned to them 1 year previously. We found that the M1 tDCS group reduced reaction time at a faster rate relative to the sham and left PFC groups, demonstrating faster relearning after a one-year delay. Thus, our findings suggest that, regardless of the polarity of stimulation, tDCS to PFC impairs sequence learning, whereas stimulation to M1 facilitates learning and relearning, especially in terms of chunk formation.

Left and right prefrontal cortex and the primary motor cortex (M1) are activated during learning of motor sequences. Previous literature is mixed on whether prefrontal cortex aids or interferes with sequence learning. The present study investigated the roles of prefrontal cortices and M1 in sequence learning. Participants received anodal transcranial direct current stimulation (tDCS) to right or left prefrontal cortex or left M1 during a probabilistic sequence learning task. Relative to sham, the left prefrontal cortex and M1 tDCS groups exhibited enhanced learning evidenced by shorter response times for pattern trials, but only for individuals who did not gain explicit awareness of the sequence (implicit). Right prefrontal cortex stimulation in participants who did not gain explicit sequence awareness resulted in learning disadvantages evidenced by slower overall response times for pattern trials. These findings indicate that stimulation to left prefrontal cortex or M1 can lead to sequence learning benefits under implicit conditions. In contrast, right prefrontal cortex tDCS had negative effects on sequence learning, with overall impaired reaction time for implicit learners. There was no effect of tDCS on accuracy, and thus our reaction time findings cannot be explained by a speed-accuracy tradeoff. Overall, our findings suggest complex and hemisphere-specific roles of left and right prefrontal cortices in sequence learning. NEW & NOTEWORTHY Prefrontal cortices are engaged in motor sequence learning, but the literature is mixed on whether the prefrontal cortices aid or interfere with learning. In the current study, we used anodal transcranial direct current stimulation to target left or right prefrontal cortex or left primary motor cortex while participants performed a probabilistic sequence learning task. We found that left prefrontal and motor cortex stimulation enhanced implicit learning whereas right prefrontal stimulation negatively impacted performance.

We have previously reported that visuospatial working memory performance and magnitude of activation in the right dorsolateral prefrontal cortex predict the rate of manual visuomotor adaptation. Sensorimotor savings, or faster adaptation to a previously experienced perturbation, has been recently linked to cognitive processes. We show that facilitating the right prefrontal cortex with anodal transcranial direct current stimulation enhances sensorimotor savings compared with sham stimulation.

Introduction: Acute exercise can modulate the excitability of the nonexercised upper limb representation in the primary motor cortex (M1). Measures of M1 excitability using transcranial magnetic stimulation (TMS) are modulated after various forms of acute exercise in young adults, including high-intensity interval training (HIIT). However, the impact of HIIT on M1 excitability in older adults is currently unknown. Therefore, the purpose of the current study was to investigate the effects of lower limb cycling HIIT on bilateral upper limb M1 excitability in older adults. Methods: We assessed the impact of acute lower limb HIIT or rest on bilateral corticospinal excitability, intracortical inhibition and facilitation, and interhemispheric inhibition of the nonexercised upper limb muscle in healthy older adults (mean age 66 ± 8 yr). We used single and pairedpulse TMS to assess motor evoked potentials, short-interval intracortical inhibition, intracortical facilitation, and the ipsilateral silent period. Two groups of healthy older adults completed either HIIT exercise or seated rest for 23 min, with TMS measures performed before (T0), immediately after (T1), and 30 min after (T2) HIIT/rest. Results: Motor evoked potentials were significantly increased after HIIT exercise at T2 compared with T0 in the dominant upper limb. Contrary to our hypothesis, we did not find any significant change in short-interval intracortical inhibition, intracortical facilitation, or ipsilateral silent period after HIIT. Conclusions: Our findings demonstrate that corticospinal excitability of the nonexercised upper limb is increased after HIIT in healthy older adults. Our results indicate that acute HIIT exercise impacts corticospinal excitability in older adults, without affecting intracortical or interhemispheric circuitry. These findings have implications for the development of exercise strategies to potentiate neuroplasticity in healthy older and clinical populations.

Older adults show both age-related decreases in resting state functional connectivity and diminished sensorimotor function. Exercise has emerged as an intervention that may mitigate or even reverse these age-related declines. Here we sought to understand whether exercise impacts resting state functional connectivity, and motor acquisition and learning in older adults. Forty-two healthy older adults rested or completed 3 sets of high-intensity interval exercise (3 minutes at 75% maximal power output and 3 minutes light intensity) for a total of 23 minutes, then immediately practiced a complex, implicit motor task with their non-dominant hand across five separate sessions. Participants completed resting stage functional MRI before the first and after the fifth day of practice; they also returned 24-hours and 35-days following their fifth day of practice to complete short- and long-term retention tests to assess motor learning. Independent component analysis of resting state functional MRI revealed increased connectivity in the frontoparietal, the dorsal attentional, and cerebellar networks in the exercise group relative to the rest group. Seed-based analysis showed strengthened connectivity between the limbic system and right cerebellum, and between the right cerebellum and bilateral middle temporal gyri. There was no motor learning advantage for the exercise group; both rest and exercise groups demonstrated motor learning as measured at the short- and long-term retention tests. Our data suggest that exercise paired with a challenging implicit motor learning task in older adults can augment resting state functional connectivity without enhancing behaviour beyond that stimulated by skilled motor practice.

Reading is a critical neurodevelopmental skill for school‐aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting‐state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed‐based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.