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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 (< l/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 Stimulation was withdrawn when a desired SR success ratio was achieved.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. Index Terms--Cultured neuronal networks, electrical stimulation, multielectrode arrays (MEAs), synaptic plasticity.

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. Index Terms--Cultured neuronal networks, functional connectivity, multielectrode arrays (MEAs), network bursts, spontaneous activity.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We have studied the effect of imprinting a new stimulus-response (SR) relationship into a neuronal network cultured on a multi electrode array (MEA). We have used the Conditional Repetitive Stimulation (CRS) algorithm introduced by Shahaf et al in 2004. In this algorithm focal electrical stimulation is delivered at a low rate (<<1 Hz) and is withdrawn when a desired response is observed. We confirmed that CRS could train the network to strengthen an initially weak SR relationship. With the acquisition of a new SR relationship, we studied its effect on network activity. Specifically, spontaneously occurring network bursts measured before, during and after training were analyzed. The total firing rate within bursts was estimated with a temporal resolution of milliseconds (burst profiles). We have shown earlier that these profiles change shape on a time base of several hours during spontaneous development. We show that the rate of change of the profiles during training (i.e. CRS) was higher than when no stimulation was applied.

Learning, or more generally, plasticity may be studied using cultured neuronal networks on multi electrode arrays. Many protocols have been proposed to change connectivity in such networks. So far, only one of these protocols, proposed by Shahaf and Marom, aimed to change the input-output relationship of a selected connection in the network. Although the results were quite promising, the experiments appeared difficult to repeat and the 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 significant learning effect indeed. We frequently found learning curves that initially declined as in the original results, but then increased again before finally settling at a low level.