Eva-Maria Reuter

A parietal-to-frontal shift in the P300 is associated with compensation of tactile discrimination deficits in late middle-aged adults

Tactile perception declines with age on both behavioral and neurophysiological levels. Less well understood is how neurophysiological changes relate to tactile discrimination performance in middle adulthood. A tactile discrimination task was conducted while ERPs were measured in three groups of healthy adults aged 20 to 66 years. Accuracy was lowest in late middle adulthood (56-66 years) while somatosensory ERP components (P50, N70, P100, N140) were comparable across age groups. The cognitive P300 revealed age-related differences in scalp distribution typical for older adults to already be present in late middle adulthood. Increased recruitment of frontal cognitive processes was positively related to performance in later middle adulthood. Our results further the understanding of age-related differences in tactile perception during middle adulthood and the importance of cognitive processes to compensate for age-related decline.

Tactile stimulation interventions: influence of stimulation parameters on sensorimotor behavior and neurophysiological correlates in healthy and clinical samples.

The pure exposure to extensive tactile stimulation, without the requirement of attention or active training, has been revealed to enhance sensorimotor functioning presumably due to an induction of plasticity in the somatosensory cortex. The induced effects, including increased tactile acuity and manual dexterity have repeatedly been observed in basic as well as clinical research. However, results vary greatly in respect to the strength and direction of the effects on the behavioral and on the brain level. Multiple evidences show that differences in the stimulation protocols (e.g., two vs. multiple stimulation sites) and parameters (e.g., duration, frequency, and amplitude) might contribute to this variability of effects. Nevertheless, stimulation protocols have not been comprehensively compared yet. Identifying favorable parameters for tactile stimulation interventions is especially important because of its possible application as a treatment option for patients suffering from sensory loss, maladaptive plasticity, or certain forms of motor impairment. This review aims to compare the effects of different tactile stimulation protocols and to assess possible implications for tactile interventions. Our goal is to identify ways of optimizing stimulation protocols to improve sensorimotor performance. To this end, we reviewed research on tactile stimulation in the healthy population, with a focus on the effectiveness of the applied parameters regarding psychophysiological measures. We discuss the association of stimulation-induced changes on the behavioral level with alterations in neural representations and response characteristics.

Age-related differences in corticomotor facilitation indicate dedifferentiation in motor planning

Efficient motor control requires motor planning. Age-related changes in motor control are well described, e.g. increased movement variability and greater antagonistic muscle co-activation, as well as less functional and less regional specific brain activation. However, less is known about age-related changes in motor planning. By use of transcranial magnetic stimulation we investigated differences in corticomotor facilitation during motor planning in 17 young (25±3years) and 17 older healthy adults (70±13years) in a delayed movement paradigm for wrist movements. Motor evoked potentials (MEPs) were recorded for the flexor and extensor carpi radialis during movement preparation of wrist flexion and extension as well as during rest. We found that MEPs were less specifically facilitated during planning in older as compared to younger adults, as indicated by an Age×Condition×Muscle interaction. Young participants showed significantly facilitated MEPs in the respective muscle needed for wrist flexion or extension. By contrast MEPs in older participants were less specifically modulated. We conclude that age relates to dedifferentiated activation of the primary motor cortex already during preparation of distinct movements which might contribute to less efficient motor control in older adults.

Practice effects in bimanual force control: does age matter?

ABSTRACT The authors examined age-related differences in fine motor control during a bimanual coordination task. The task required the modulation of fingertip forces in the precision grip according to a visually presented sinusoidal antiphase pattern (force range 2–12 N; frequency 0.2 Hz). Thirty-four right-handed participants of three age groups (young, early middle-aged, and late middle-aged) practiced 30 trials of the task. Accuracy and variability of relative timing and relative forces at minima and maxima of the sine wave were analyzed for hand–hand and hand–stimulus couplings and compared between age groups. Analysis showed for relative timing and force weaker hand–hand than hand–stimulus coupling as well as lower accuracy and higher variability for minima as compared to maxima. Further, we analyzed practice effects by comparing the first and last trials and characterized the course of practice by detecting the transition of a steeper to a shallower acquisition slope for the different age groups. Late middle-aged participants demonstrated poorer performance than both other groups for all parameters. All groups improved performance to a similar amount. However, an age-related difference in acquisition strategy is visible. Late middle-aged participants seemed to have focused on improvement of force amplitude, whereas young and early middle-aged focused on timing.

Extensive occupational finger use delays age effects in tactileperception—an ERP study

Tactile expertise, resulting from extensive use of hands, has previously been shown to improve tactile perception in blind people and musicians and to be associated with changes in the central processing of tactile information. This study investigated whether expertise, due to precise and deliberate use of the fingers at work, relates to improved tactile perception and whether this expertise interacts with age. A tactile pattern and a frequency discrimination task were conducted while ERPs were measured in experts and nonexperts of two age groups within middle adulthood. Independently of age, accuracy was better in experts than in nonexperts in both tasks. Somatosensory N70 amplitudes were larger with increasing age and for experts than for nonexperts. P100 amplitudes were smaller in experts than in nonexperts in the frequency discrimination task. In the pattern discrimination task, P300 difference wave amplitude was reduced in experts and late middle-aged adults. In the frequency discrimination task, P300 was more equally distributed in late middle-aged adults. We conclude that extensive, dexterous manual work leads to acquisition of tactile expertise and that this expertise might delay, but not counteract, age effects on tactile perception. Comparable neurophysiological changes induced by age and expertise presumably have different underlying mechanisms. Enlarged somatosensory N70 amplitudes might result from reduced inhibition in older adults but from enhanced, specific excitability of the somatosensory cortex in experts. Regarding P300, smaller amplitudes might indicate fewer available resources in older adults and, by contrast, a reduced need to engage as much cognitive effort to the task in experts.

Effects of age and expertise on tactile learning in humans.

Repetitive tactile stimulation is a well‐established tool for inducing somatosensory cortical plasticity and changes in tactile perception. Previous studies have suggested that baseline performance determines the amount of stimulation‐induced learning differently in specific populations. Older adults with lower baseline performance than young adults, but also experts, with higher baseline performance than non‐experts of the same age, have been found to profit most from such interventions. This begs the question of how age‐related and expertise‐related differences in tactile learning are reflected in neurophysiological correlates. In two experiments, we investigated how tactile learning depends on age (experiment 1) and expertise (experiment 2). We assessed tactile spatial and temporal discrimination accuracy and event‐related potentials (ERPs) in 57 persons of different age and expertise groups before and after a 30‐min tactile stimulation intervention. The intervention increased accuracy in temporal (found in experiment 1) and spatial (found in experiment 2) discrimination. Experts improved more than non‐experts in spatial discrimination. Lower baseline performance was associated with higher learning gain in experts and non‐experts. After the intervention, P300 latencies were reduced in young adults and amplitudes were increased in late middle‐aged adults in the temporal discrimination task. Experts showed a steeper P300 parietal‐to‐frontal gradient after the stimulation. We demonstrated that tactile stimulation partially reverses the age‐related decline in late middle‐aged adults and increases processing speed in young adults. We further showed that learning gain depends on baseline performance in both non‐experts and experts. In experts, however, the upper limit for learning seems to be shifted to a higher level.

The P3 parietal-to-frontal shift relates to age-related slowing in a selective attention task

Older adults recruit relatively more frontal as compared to parietal resources in a variety of cognitive and perceptual tasks. It is not yet clear whether this parietal-to-frontal shift is a compensatory mechanism, or simply reflects a reduction in processing efficiency. In this study we aimed to investigate how the parietal-to-frontal shift with aging relates to selective attention. Fourteen young and 26 older healthy adults performed a color Flanker task under three conditions (incongruent, congruent, neutral) and event-related potentials (ERPs) were measured. The P3 was analyzed for the electrode positions Pz, Cz, and Fz as an indicator of the parietal-to-frontal shift. Further, behavioral performance and other ERP components (P1 and N1 at electrodes O1 and O2; N2 at electrodes Fz and Cz) were investigated. First young and older adults were compared. Older adults had longer response times, reduced accuracy, longer P3 latencies, and a more frontal distribution of P3 than young adults. These results confirm the parietal-to-frontal shift in the P3 with age for the selective attention task. Second, based on the differences between frontal and parietal P3 activity the group of older adults was subdivided into those showing a rather equal distribution of the P3 and older participants showing a strong frontal focus of the P3. Older adults with a more frontally distributed P3 had longer response times than participants with a more equally distributed P3. These results suggest that the frontally distributed P3 observed in older adults has no compensatory function in selective attention but rather indicates less efficient processing and slowing with age.

Feedforward compensation for novel dynamics depends on force field orientation but is similar for the left and right arms

There are well-documented differences in the way that people typically perform identical motor tasks with their dominant and the nondominant arms. According to Yadav and Sainburgs (Neuroscience 196: 153-167, 2011) hybrid-control model, this is because the two arms rely to different degrees on impedance control versus predictive control processes. Here, we assessed whether differences in limb control mechanisms influence the rate of feedforward compensation to a novel dynamic environment. Seventy-five healthy, right-handed participants, divided into four subsamples depending on the arm (left, right) and direction of the force field (ipsilateral, contralateral), reached to central targets in velocity-dependent curl force fields. We assessed the rate at which participants developed predictive compensation for the force field using intermittent error-clamp trials and assessed both kinematic errors and initial aiming angles in the field trials. Participants who were exposed to fields that pushed the limb toward ipsilateral space reduced kinematic errors more slowly, built up less predictive field compensation, and relied more on strategic reaiming than those exposed to contralateral fields. However, there were no significant differences in predictive field compensation or kinematic errors between limbs, suggesting that participants using either the left or the right arm could adapt equally well to novel dynamics. It therefore appears that the distinct preferences in control mechanisms typically observed for the dominant and nondominant arms reflect a default mode that is based on habitual functional requirements rather than an absolute limit in capacity to access the controller specialized for the opposite limb.

Three's a crowd: attention, the vertex wave and sensorimotor control

Sudden events deserve our attention, as they can signal potential threat or reward. The rapid detection and, crucially, reaction to salient stimuli might even be a matter of life or death. For instance, animals need to detect the sudden appearance of prey or predator in order to initiate the appropriate response such as hunt, fight, or flight. Also the human nervous system seems to be ideally tuned to react to salient, behaviourally relevant events. For instance, reaction times are shorter for potentially dangerous, more intense, or more rewarding stimuli. Independent of the sensory modality, salient events also elicit a brain response: the vertex wave (e.g. Mouraux & Iannetti, 2009). It is the largest response in the human electroencephalogram (EEG) and it is easily detectable, even on a single trial level. Traditionally, the vertex wave was thought to reflect neural activities related to detection and perception. More recent evidence suggests that the vertex wave might play a role in linking salience detection with motor reaction and thus reflects not a pure perceptual but rather a sensorimotor process. In two previous studies, Iannetti’s group presented first evidence for this hypothesis. Moayedi et al. (2015) found that the vertex wave is related to the execution of defensive actions following noxious stimuli. More recently, Novembre et al. (2018) reported that the vertex wave is coupled with a salience-dependent modulation of constant isometric finger forces. Now, in the current issue of The Journal of Physiology, Kilintari et al. (2018) address the question of whether the vertex wave is functionally linked to behaviour in a more complex visuomotor reaching task. In a series of experiments, healthy human participants were asked to move a finger as quickly and as accurately as possible through five target positions. Somatosensory or auditory stimuli with different levels of salience were presented simultaneously with a visual ‘go’ signal and evoked a vertex wave. For both stimulus modalities, the vertex wave amplitudes were larger when salience was augmented. In parallel to this increase, movement onset times were faster and movements were more accurate. While these results seem to suggest that a larger vertex wave, evoked immediately before movement onset, leads to faster and more accurate visuomotor control, Kilintari et al. took a step further and tested if the spontaneous trial-by-trial variability of the vertex wave is coupled with variability in movement characteristics. Indeed, they found a correlation between vertex wave amplitude and movement onset time, but interestingly, in the opposite direction to that expected. Thus, a trial with a large vertex wave was more likely to be a trial with a longer movement onset time. What does this mean? This becomes clear when also considering the results from a control experiment, where no vertex wave was elicited, but nevertheless a positive correlation between EEG amplitude recorded over the vertex and movement onset time emerged. This suggests that independent of any sudden event, or salience manipulation, brain activity following the ‘go’ signal predicts response time in this visuomotor task. Kilintari et al. argue that this correlation is due to a widespread attention-related ‘processing negativity’, which facilitates the execution of subsequent task-relevant behaviour and overlays the vertex wave. Collectively, these new results confirm that salience increases the vertex wave and can increase motor performance. Yet there seems to be no direct causal link between vertex wave and performance, when the vertex wave is elicited prior to movement onset. More intriguingly, however, the results suggest that attention indirectly reduces the vertex wave, by increasing the processing negativity, which, in turn, relates to reduced movement onset time. The interrelation of focused, endogenous (goal-driven) spatial attention and salient, exogenous (stimulus-driven) stimuli has been studied extensively in vision science (see e.g. Todd & Manaligod, 2018 for a recent review). The current findings build a good starting point to further assess this interaction in sensorimotor control research. Overall Kilintari et al.’s findings do not provide direct support for the hypothesis that the vertex wave links perception and action in visuomotor control following salient events, yet they show something else that is of fundamental importance. They provide an excellent example of how to undertake the difficult challenge of investigating the relation between EEG and behaviour in more complex motor tasks. Kilintari et al. clearly demonstrate the truism that concomitant changes in behaviour and EEG need not imply that the EEG effect is a direct neurophysiological correlate of the behavioural finding. Nevertheless, the question of whether or not the vertex wave influences sensorimotor control in more demanding tasks certainly deserves further attention. Taken together with findings by Novembre et al. (2018), the current results imply that using an ongoing task with a higher demand on visual motor control could be most suitable to further study how visuomotor control is influenced by the vertex wave. A force modulation task with a more demanding target force profile (e.g. sine waves) could be a promising option. More generally, the vertex wave seems to be an ideal candidate to further study the relation between EEG and motor behaviour following salient stimuli, because it is reliably measurable on a single trial level, in stark contrast to other event-related potential components. In sum, this work by Kilintari et al. (2018) strongly emphasises the importance of considering alternative sources of variance due to ongoing, goal-relevant processes, such as attention, motivation or alertness. If we find a way to account for fluctuation in such processes in sensorimotor research, it will be easier to pin the remaining variance to experimental manipulations.

It Pays to Prepare: Human Motor Preparation Depends on the Relative Value of Potential Response Options

Alternative motor responses can be prepared in parallel. Here, we used electroencephalography (EEG) to test whether the parallel preparation of alternative response options is modulated by their relative value. Participants performed a choice response task with three potential actions: isometric contraction of the left, the right, or both wrists. An imperative stimulus (IS) appeared after a warning cue, such that the initiation time of a required action was predictable, but the specific action was not. To encourage advanced preparation, the target was presented 200 ms prior to the IS, and only correct responses initiated within ±100 ms of the IS were rewarded. At baseline, all targets were equally rewarded and probable. Then, responses with one hand were made more valuable, either by increasing the probability that the left or right target would be required (Exp. 1; n = 31) or by increasing the reward magnitude of one target (Exp. 2, n = 36). We measured reaction times, movement vigor, and an EEG correlate of action preparation (value-based lateralized readiness potential) prior to target presentation. Participants responded earlier to more frequent and more highly rewarded targets, and movements to highly rewarded targets were more vigorous. The EEG was more negative over the hemisphere contralateral to the more repeated/rewarded hand, implying an increased neural preparation of more valuable actions. Thus, changing the value of alternative response options can lead to greater preparation of actions associated with more valuable outcomes. This preparation asymmetry likely contributes to behavioral biases that are typically observed toward repeated or rewarded targets.