Rachael D. Seidler

Aging, Training, and the Brain: A Review and Future Directions

As the population ages, the need for effective methods to maintain or even improve older adults’ cognitive performance becomes increasingly pressing. Here we provide a brief review of the major intervention approaches that have been the focus of past research with healthy older adults (strategy training, multi-modal interventions, cardiovascular exercise, and process-based training), and new approaches that incorporate neuroimaging. As outcome measures, neuroimaging data on intervention-related changes in volume, structural integrity; and functional activation can provide important insights into the nature and duration of an intervention’s effects. Perhaps even more intriguingly, several recent studies have used neuroimaging data as a guide to identify core cognitive processes that can be trained in one task with effective transfer to other tasks that share the same underlying processes. Although many open questions remain, this research has greatly increased our understanding of how to promote successful aging of cognition and the brain.

Feedforward and feedback processes in motor control

In this study, we utilized functional magnetic resonance imaging (fMRI) to examine which brain regions contribute to feedback and feedforward motor control processes. Several studies have investigated the contributions of cortical and subcortical brain regions to motor performance by independently varying factors such as movement rate, force, and speed, and observing the neural responses. Such studies have contributed greatly to our understanding of neural coding of movement variables. Under natural movement conditions, however, these factors interact in a complex manner to produce differing performance levels. In the current investigation, we induced performance changes in a less constrained way, by having subjects move a joystick to hit targets of differing sizes on an LCD screen. These parametric changes in target size resulted in the well-known speed-accuracy tradeoff effect, allowing us to examine the brain regions responsive to global shifts in motor performance levels. That is, movements made to larger targets relied more on feedforward control whereas movements made to smaller targets relied more on feedback control. Using functional MRI, we identified two sets of brain regions in which activation was modulated with task difficulty. Areas exhibiting activation that was positively correlated with increasing target size included primary motor cortex, premotor cortex, and the basal ganglia, regions that are typically classified as playing a role in force control and movement planning. Brain regions whose activation was negatively correlated with increasing target size included the ipsilateral sensorimotor cortex, multiple cerebellar regions, and the thalamus. These areas contributed to motor performance under higher levels of task difficulty. The results elucidate cortical and subcortical brain regions that are responsive to global shifts in motor performance, reflecting changes along the continuum of feedforward and feedback motor control.

Altered Resting State Cortico-Striatal Connectivity in Mild to Moderate Stage Parkinson's Disease

Parkinsons disease (PD) is a progressive neurodegenerative disorder that is characterized by dopamine depletion in the striatum. One consistent pathophysiological hallmark of PD is an increase in spontaneous oscillatory activity in the basal ganglia thalamocortical networks. We evaluated these effects using resting state functional connectivity MRI in mild to moderate stage Parkinsons patients on and off l-DOPA and age-matched controls using six different striatal seed regions. We observed an overall increase in the strength of cortico-striatal functional connectivity in PD patients off l-DOPA compared to controls. This enhanced connectivity was down-regulated by l-DOPA as shown by an overall decrease in connectivity strength, particularly within motor cortical regions. We also performed a frequency content analysis of the BOLD signal time course extracted from the six striatal seed regions. PD off l-DOPA exhibited increased power in the frequency band 0.02–0.05 Hz compared to controls and to PD on l-DOPA. The l-DOPA associated decrease in the power of this frequency range modulated the l-DOPA associated decrease in connectivity strength between striatal seeds and the thalamus. In addition, the l-DOPA associated decrease in power in this frequency band correlated with the l-DOPA associated improvement in cognitive performance. Our results demonstrate that PD and l-DOPA modulate striatal resting state BOLD signal oscillations and cortico-striatal network coherence.

Contributions of spatial working memory to visuomotor learning

Previous studies of motor learning have described the importance of cognitive processes during the early stages of learning; however, the precise nature of these processes and their neural correlates remains unclear. The present study investigated whether spatial working memory (SWM) contributes to visuomotor adaptation depending on the stage of learning. We tested the hypothesis that SWM would contribute early in the adaptation process by measuring (i) the correlation between SWM tasks and the rate of adaptation, and (ii) the overlap between the neural substrates of a SWM mental rotation task and visuomotor adaptation. Participants completed a battery of neuropsychological tests, a visuomotor adaptation task, and an SWM task involving mental rotation, with the latter two tasks performed in a 3.0-T MRI scanner. Performance on a neuropsychological test of SWM (two-dimensional mental rotation) correlated with the rate of early, but not late, visuomotor adaptation. During the early, but not late, adaptation period, participants showed overlapping brain activation with the SWM mental rotation task, in right dorsolateral prefrontal cortex and the bilateral inferior parietal lobules. These findings suggest that the early, but not late, phase of visuomotor adaptation engages SWM processes.

Neural correlates of encoding and expression in implicit sequence learning

In the domain of motor learning it has been difficult to separate the neural substrate of encoding from that of change in performance. Consequently, it has not been clear whether motor effector areas participate in learning or merely modulate changes in performance. Here, using a variant of the serial reaction time task that dissociated these two factors, we report that encoding during procedural motor learning does engage cortical motor areas and can be characterized by distinct early and late encoding phases. The highest correlation between activation and subsequent changes in motor performance was seen in the motor cortex during early encoding, and in the basal ganglia during the late encoding phase. Our results show that rapid encoding during procedural motor learning involves several distinct processes, and is represented primarily within motor system structures.

Functional implications of age differences in motor system connectivity

Older adults show less lateralized task-related brain activity than young adults. One potential mechanism of this increased activation is that age-related degeneration of the corpus callosum (CC) may alter the balance of inhibition between the two hemispheres. To determine whether age differences in interhemispheric connectivity affect functional brain activity in older adults, we used magnetic resonance imaging (MRI) to assess resting functional connectivity and functional activation during a simple motor task. We found that older adults had smaller CC area compared to young adults. Older adults exhibited greater recruitment of ipsilateral primary motor cortex (M1), which was associated with longer reaction times. Additionally, recruitment of ipsilateral M1 in older adults was correlated with reduced resting interhemispheric connectivity and a larger CC. We suggest that reduced interhemispheric connectivity reflects a loss of the ability to inhibit the non-dominant hemisphere during motor task performance for older adults, which has a negative impact on performance.

Multiple Motor Learning Experiences Enhance Motor Adaptability

Traditional motor learning theory emphasizes that skill learning is specific to the context and task performed. Recent data suggest, however, that subjects exposed to a variety of motor learning paradigms may be able to acquire general, transferable knowledge about skill learning processes. I tested this idea by having subjects learn five different motor tasks, three that were similar to each other and two that were not related. A group of experimental subjects first performed a joystick-aiming task requiring adaptation to three different visuomotor rotations, with a return to the null conditions between each exposure. They then performed the same joystick-aiming task but had to adapt to a change in display gain instead of rotation. Lastly, the subjects used the joystickaiming task to learn a repeating sequence of movements. Two groups of control subjects performed the same number of trials, but learned only the gain change or the movement sequence. Experimental subjects showed generalization of learning across the three visuomotor rotations. Experimental subjects also exhibited transfer of learning ability to the gain change and the movement sequence, resulting in faster learning than that seen in the control subjects. However, transient perturbations affected the movements of the experimental subjects to a greater extent than those of the control subjects. These data demonstrate that humans can acquire a general enhancement in motor skill learning capacity through experience, but it comes with a cost. Although movement becomes more adaptable following multiple learning experiences, it also becomes less stable to external perturbation.

Neural correlates of motor learning, transfer of learning, and learning to learn.

Recent studies on the neural bases of sensorimotor adaptation demonstrate that the cerebellar and striatal thalamocortical pathways contribute to early learning. Transfer of learning involves a reduction in the contribution of early learning networks and increased reliance on the cerebellum. The neural correlates of learning to learn remain to be determined but likely involve enhanced functioning of the general aspects of early learning.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called “model-based” functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

Visuospatial Working Memory Capacity Predicts the Organization of Acquired Explicit Motor Sequences

Studies have suggested that cognitive processes such as working memory and temporal control contribute to motor sequence learning. These processes engage overlapping brain regions with sequence learning, but concrete evidence has been lacking. In this study, we determined whether limits in visuospatial working memory capacity and temporal control abilities affect the temporal organization of explicitly acquired motor sequences. Participants performed an explicit sequence learning task, a visuospatial working memory task, and a continuous tapping timing task. We found that visuospatial working memory capacity, but not the CV from the timing task, correlated with the rate of motor sequence learning and the chunking pattern observed in the learned sequence. These results show that individual differences in short-term visuospatial working memory capacity, but not temporal control, predict the temporal structure of explicitly acquired motor sequences.