Jan Stegenga

Exergaming for balance training of elderly: state of the art and future developments

Fall injuries are responsible for physical dysfunction, significant disability, and loss of independence among elderly. Poor postural control is one of the major risk factors for falling but can be trained in fall prevention programs. These however suffer from low therapy adherence, particularly if prevention is the goal. To provide a fun and motivating training environment for elderly, exercise games, or exergames, have been studied as balance training tools in the past years. The present paper reviews the effects of exergame training programs on postural control of elderly reported so far. Additionally we aim to provide an in-depth discussion of technologies and outcome measures utilized in exergame studies. Thirteen papers were included in the analysis. Most of the reviewed studies reported positive results with respect to improvements in balance ability after a training period, yet few reached significant levels. Outcome measures for quantification of postural control are under continuous dispute and no gold standard is present. Clinical measures used in the studies reviewed are well validated yet only give a global indication of balance ability. Instrumented measures were unable to detect small changes in balance ability as they are mainly based on calculating summary statistics, thereby ignoring the time-varying structure of the signals. Both methods only allow for measuring balance after the exergame intervention program. Current developments in sensor technology allow for accurate registration of movements and rapid analysis of signals. We propose to quantify the time-varying structure of postural control during gameplay using low-cost sensor systems. Continuous monitoring of balance ability leaves the user unaware of the measurements and allows for generating user-specific exergame training programs and feedback, both during one game and in timeframes of weeks or months. This approach is unique and unlocks the as of yet untapped potential of exergames as balance training tools for community dwelling elderly.

Analysis of Cultured Neuronal Networks Using Intraburst Firing Characteristics

It is an open question whether neuronal networks, cultured on multielectrode arrays, retain any capability to usefully process information (learning and memory). A necessary prerequisite for learning is that stimulation can induce lasting changes in the network. To observe these changes, one needs a method to describe the network in sufficient detail, while stable in normal circumstances. We analyzed the spontaneous bursting activity that is encountered in dissociated cultures of rat neocortical cells. Burst profiles (BPs) were made by estimating the instantaneous array-wide firing frequency. The shape of the BPs was found to be stable on a time scale of hours. Spatiotemporal detail is provided by analyzing the instantaneous firing frequency per electrode. The resulting phase profiles (PPs) were estimated by aligning BPs to their peak spiking rate over a period of 15 min. The PPs reveal a stable spatiotemporal pattern of activity during bursts over a period of several hours, making them useful for plasticity and learning studies. We also show that PPs can be used to estimate conditional firing probabilities. Doing so, yields an approach in which network bursting behavior and functional connectivity can be studied.

The Effect of Slow Electrical Stimuli to Achieve Learning in Cultured Networks of Rat Cortical Neurons

Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neurons on multi electrode arrays. Several protocols have been proposed to affect connectivity in such networks. One of these protocols, proposed by Shahaf and Marom, aimed to train the input-output relationship of a selected connection in a network using slow electrical stimuli. Although the results were quite promising, the experiments appeared difficult to repeat and the training protocol did not serve as a basis for wider investigation yet. Here, we repeated their protocol, and compared our ‘learning curves’ to the original results. Although in some experiments the protocol did not seem to work, we found that on average, the protocol showed a significantly improved stimulus response indeed. Furthermore, the protocol always induced functional connectivity changes that were much larger than changes that occurred after a comparable period of random or no stimulation. Finally, our data shows that stimulation at a fixed electrode induces functional connectivity changes of similar magnitude as stimulation through randomly varied sites; both larger than spontaneous connectivity fluctuations. We concluded that slow electrical stimulation always induced functional connectivity changes, although uncontrolled. The magnitude of change increased when we applied the adaptive (closed-loop) training protocol. We hypothesize that networks develop an equilibrium between connectivity and activity. Induced connectivity changes depend on the combination of applied stimulus and initial connectivity. Plain stimuli may drive networks to the nearest equilibrium that accommodates this input, whereas adaptive stimulation may direct the space for exploration and force networks to a new balance, at a larger distance from the initial state.

Suitability of Kinect for measuring whole body movement patterns during exergaming

Exergames provide a challenging opportunity for home-based training and evaluation of postural control in the elderly population, but affordable sensor technology and algorithms for assessment of whole body movement patterns in the home environment are yet to be developed. The aim of the present study was to evaluate the use of Kinect, a commonly available video game sensor, for capturing and analyzing whole body movement patterns. Healthy adults (n=20) played a weight shifting exergame under five different conditions with varying amplitudes and speed of sway movement, while 3D positions of ten body segments were recorded in the frontal plane using Kinect and a Vicon 3D camera system. Principal Component Analysis (PCA) was used to extract and compare movement patterns and the variance in individual body segment positions explained by these patterns. Using the identified patterns, balance outcome measures based on spatiotemporal sway characteristics were computed. The results showed that both Vicon and Kinect capture >90% variance of all body segment movements within three PCs. Kinect-derived movement patterns were found to explain variance in trunk movements accurately, yet explained variance in hand and foot segments was underestimated and overestimated respectively by as much as 30%. Differences between both systems with respect to balance outcome measures range 0.3-64.3%. The results imply that Kinect provides the unique possibility of quantifying balance ability while performing complex tasks in an exergame environment.

Network bursts in cortical cultures are best simulated using pacemaker neurons and adaptive synapses

One of the most specific and exhibited features in the electrical activity of dissociated cultured neural networks (NNs) is the phenomenon of synchronized bursts, whose profiles vary widely in shape, width and firing rate. On the way to understanding the organization and behavior of biological NNs, we reproduced those features with random connectivity network models with 5,000 neurons. While the common approach to induce bursting behavior in neuronal network models is noise injection, there is experimental evidence suggesting the existence of pacemaker-like neurons. In our simulations noise did evoke bursts, but with an unrealistically gentle rising slope. We show that a small subset of ‘pacemaker’ neurons can trigger bursts with a more realistic profile. We found that adding pacemaker-like neurons as well as adaptive synapses yield burst features (shape, width, and height of the main phase) in the same ranges as obtained experimentally. Finally, we demonstrate how changes in network connectivity, transmission delays, and excitatory fraction influence network burst features quantitatively.

The Effect of Learning on Bursting

We have studied the effect that learning a new stimulus-response (SR) relationship had within a neuronal network cultured on a multielectrode array. For training, we applied repetitive focal electrical stimulation delivered at a low rate (Lt1/s). Stimulation was withdrawn when a desired SR success ratio was achieved. It has been shown elsewhere, and we verified that this training algorithm, named conditional repetitive stimulation (CRS), can be used to strengthen an initially weak SR. So far, it remained unclear what the role of the rest of the network during learning was. We therefore studied the effect of CRS on spontaneously occurring network bursts. To this end, we made profiles of the firing rates within network bursts. We have earlier shown that these profiles change shape on a time base of several hours during spontaneous development. We show here that profiles of summed activity, called burst profiles, changed shape at an increased rate during CRS. This suggests that the whole network was involved in making the changes necessary to incorporate the desired SR relationship. However, a local (path-specific) component to learning was also found by analyzing profiles of single-electrode-activity phase profiles. Phase profiles that were not part of the SR relationship changed far less during CRS than the phase profiles of the electrodes that were part of the SR relationship. Finally, the manner in which phase profiles changed shape varied and could not be linked to the SR relationship.

Exergames for unsupervised balance training at home: A pilot study in healthy older adults

Exercise videogames (exergames) are gaining popularity as tools for improving balance ability in older adults, yet few exergames are suitable for home-based use. The purpose of the current pilot study was to examine the effects of a 6-week unsupervised home-based exergaming training program on balance performance. Ten community dwelling healthy older adults (age: 75.9 ± 7.2 years) played a newly developed ice skating exergame for six weeks at home. In the game, the speed and direction of a virtual ice skater on a frozen canal were controlled using lateral weight shifts, which were captured using Kinect. Sway characteristics during quiet standing in eyes open (EO), eyes closed (EC) and dual task (DT) conditions were assessed in time and frequency domain before, and after two, four and six weeks of training. Balance was also evaluated using the narrow ridge balance test (NRBT). Multilevel modeling was applied to examine changes in balance ability. Participants played 631 (± 124)min over the intervention period and no subjects dropped out. Balance in terms of sway characteristics improved on average by 17.4% (EO) and 23.3% (EC) after six weeks of training (p<0.05). Differences in rate of improvement (p<0.05) were observed between participants. No intervention effects were found for quiet standing in DT conditions and on the NRBT. In conclusion, the pilot study showed that unsupervised home-based exergaming is feasible in community dwelling older adults, but also that participants do not benefit equally from the program, thereby emphasizing the need for more personalized exergame training programs.

Phase-dependent effects of stimuli locked to oscillatory activity in cultured cortical networks.

The archetypal activity pattern in cultures of dissociated neurons is spontaneous network-wide bursting. Bursts may interfere with controlled activation of synaptic plasticity, but can be suppressed by the application of stimuli at a sufficient rate. We sinusoidally modulated (4 Hz) the pulse rate of random background stimulation (RBS) and found that cultures were more active, burst less frequently, and expressed oscillatory activity. Next, we studied the effect of phase-locked tetani (four pulses, 200 s(-1)) on network activity. Tetani were applied to one electrode at the peak or trough of mRBS stimulation. We found that when tetani were applied at the peak of modulated RBS (mRBS), a significant potentiation of poststimulus histograms (PSTHs) occurred. Conversely, tetani applied at the trough resulted in a small but insignificant depression of PSTHs. In addition to PSTHs, electrode-specific firing rate profiles within spontaneous bursts before and after mRBS were analyzed. Here, significant changes in firing rate profiles were found only for stimulation at the peak of mRBS. Our study shows that rhythmic activity in culture is possible, and that the network responds differentially to strong stimuli depending on the phase at which they are delivered. This suggests that plasticity mechanisms may be differentially accessible in an oscillatory state.

High-frequency electrical stimulation suppresses cholinergic accumbens interneurons in acute rat brain slices through GABAB receptors

The nucleus accumbens is selected as a surgical target in deep brain stimulation for treating refractory obsessive‐compulsive disorder (OCD). One of the therapeutic benefits of this procedure is that the abnormal hyper‐functioning prefrontal cortex of patients with OCD is restored during stimulation. One hypothesis regarding the mechanism of deep brain stimulation is that the neuronal electrophysiological properties are directly altered by electrical stimulation; another hypothesis assumes that the stimulation induces selective neuron transmitter release, such as γ‐aminobutyric acid (GABA). In this study, we used multi‐electrode arrays with electrode size of 40 × 40 μm to record electrophysiological signals from the large nucleus accumbens neurons in acute rat brain slices while applying electrical stimulation simultaneously. We revealed that high‐frequency stimulation (HFS, 140 Hz) suppressed the spontaneous neuronal firing rate significantly, whereas low‐frequency stimulation (LFS, 10 Hz) did not. Both HFS and LFS have no effect on neuronal firing pattern or on neuronal oscillation synchrony. GABAB receptor antagonism reversed the HFS‐provoked neuronal inhibition, whereas GABAA receptor blockade failed to affect it. The recorded neurons were pharmacologically identified to be cholinergic interneurons. We propose that HFS has a direct suppressive effect on the identified accumbal acetylcholine (ACh) interneurons by enhancing GABA release in the stimulated region. Potentially, suppressed ACh interneurons decrease the disinhibiting function of medium‐sized spiny neurons in the striato‐thalamo‐cortical circuit. This finding might give an indication of the mechanism of the therapeutic effect of HFS in nucleus accumbens on restoring the abnormal hyperactive prefrontal cortex status in OCD.

Experimental analysis and computational modeling of interburst intervals in spontaneous activity of cortical neuronal culture

Rhythmic bursting is the most striking behavior of cultured cortical networks and may start in the second week after plating. In this study, we focus on the intervals between spontaneously occurring bursts, and compare experimentally recorded values with model simulations. In the models, we use standard neurons and synapses, with physiologically plausible parameters taken from literature. All networks had a random recurrent architecture with sparsely connected neurons. The number of neurons varied between 500 and 5,000. We find that network models with homogeneous synaptic strengths produce asynchronous spiking or stable regular bursts. The latter, however, are in a range not seen in recordings. By increasing the synaptic strength in a (randomly chosen) subset of neurons, our simulations show interburst intervals (IBIs) that agree better with in vitro experiments. In this regime, called weakly synchronized, the models produce irregular network bursts, which are initiated by neurons with relatively stronger synapses. In some noise-driven networks, a subthreshold, deterministic, input is applied to neurons with strong synapses, to mimic pacemaker network drive. We show that models with such “intrinsically active neurons” (pacemaker-driven models) tend to generate IBIs that are determined by the frequency of the fastest pacemaker and do not resemble experimental data. Alternatively, noise-driven models yield realistic IBIs. Generally, we found that large-scale noise-driven neuronal network models required synaptic strengths with a bimodal distribution to reproduce the experimentally observed IBI range. Our results imply that the results obtained from small network models cannot simply be extrapolated to models of more realistic size. Synaptic strengths in large-scale neuronal network simulations need readjustment to a bimodal distribution, whereas small networks do not require such changes.