Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

Motor control complexity can be dynamically simplified during gait pattern exploration using motor control-based biofeedback

Understanding how the central nervous system coordinates diverse motor outputs has been a topic of extensive investigation. Although it is generally accepted that a small set of synergies underlies many common activities, such as walking, whether synergies are equally robust across a broader array of gait patterns or can be flexibly modified remains unclear. Here, we evaluated the extent to which synergies changed as nondisabled adults (n = 14) explored gait patterns using custom biofeedback. Secondarily, we used Bayesian additive regression trees to identify factors that were associated with synergy modulation. Participants explored 41.1 ± 8.0 gait patterns using biofeedback, during which synergy recruitment changed depending on the type and magnitude of gait pattern modification. Specifically, a consistent set of synergies was recruited to accommodate small deviations from baseline, but additional synergies emerged for larger gait changes. Synergy complexity was similarly modulated; complexity decreased for 82.6% of the attempted gait patterns, but distal gait mechanics were strongly associated with these changes. In particular, greater ankle dorsiflexion moments and knee flexion through stance, as well as greater knee extension moments at initial contact, corresponded to a reduction in synergy complexity. Taken together, these results suggest that the central nervous system preferentially adopts a low-dimensional, largely invariant control strategy but can modify that strategy to produce diverse gait patterns. Beyond improving understanding of how synergies are recruited during gait, study outcomes may also help identify parameters that can be targeted with interventions to alter synergies and improve motor control after neurological injury.NEW & NOTEWORTHY We used a motor control-based biofeedback system and machine learning to characterize the extent to which nondisabled adults can modulate synergies during gait pattern exploration. Results revealed that a small library of synergies underlies an array of gait patterns but that recruitment from this library changes as a function of the imposed biomechanical constraints. Our findings enhance understanding of the neural control of gait and may inform biofeedback strategies to improve synergy recruitment after neurological injury.

Astrocytes Exhibit a Protective Role in Neuronal Firing Patterns under Chemically Induced Seizures in Neuron-Astrocyte Co-Cultures

Astrocytes and neurons respond to each other by releasing transmitters, such as γ-aminobutyric acid (GABA) and glutamate, that modulate the synaptic transmission and electrochemical behavior of both cell types. Astrocytes also maintain neuronal homeostasis by clearing neurotransmitters from the extracellular space. These astrocytic actions are altered in diseases involving malfunction of neurons, e.g., in epilepsy, Alzheimer's disease, and Parkinson's disease. Convulsant drugs such as 4-aminopyridine (4-AP) and gabazine are commonly used to study epilepsy in vitro. In this study, we aim to assess the modulatory roles of astrocytes during epileptic-like conditions and in compensating drug-elicited hyperactivity. We plated rat cortical neurons and astrocytes with different ratios on microelectrode arrays, induced seizures with 4-AP and gabazine, and recorded the evoked neuronal activity. Our results indicated that astrocytes effectively counteracted the effect of 4-AP during stimulation. Gabazine, instead, induced neuronal hyperactivity and synchronicity in all cultures. Furthermore, our results showed that the response time to the drugs increased with an increasing number of astrocytes in the co-cultures. To the best of our knowledge, our study is the first that shows the critical modulatory role of astrocytes in 4-AP and gabazine-induced discharges and highlights the importance of considering different proportions of cells in the cultures.

Neuronal and Astrocytic Regulations in Schizophrenia: A Computational Modelling Study

According to the tripartite synapse model, astrocytes have a modulatory effect on neuronal signal transmission. More recently, astrocyte malfunction has been associated with psychiatric diseases such as schizophrenia. Several hypotheses have been proposed on the pathological mechanisms of astrocytes in schizophrenia. For example, post-mortem examinations have revealed a reduced astrocytic density in patients with schizophrenia. Another hypothesis suggests that disease symptoms are linked to an abnormality of glutamate transmission, which is also regulated by astrocytes (glutamate hypothesis of schizophrenia). Electrophysiological findings indicate a dispute over whether the disorder causes an increase or a decrease in neuronal and astrocytic activity. Moreover, there is no consensus as to which molecular pathways and network mechanisms are altered in schizophrenia. Computational models can aid the process in finding the underlying pathological malfunctions. The effect of astrocytes on the activity of neuron-astrocyte networks has been analysed with computational models. These can reproduce experimentally observed phenomena, such as astrocytic modulation of spike and burst signalling in neuron-astrocyte networks. Using an established computational neuron-astrocyte network model, we simulate experimental data of healthy and pathological networks by using different neuronal and astrocytic parameter configurations. In our simulations, the reduction of neuronal or astrocytic cell densities yields decreased glutamate levels and a statistically significant reduction in the network activity. Amplifications of the astrocytic ATP release toward postsynaptic terminals also reduced the network activity and resulted in temporarily increased glutamate levels. In contrast, reducing either the glutamate release or re-uptake in astrocytes resulted in higher network activities. Similarly, an increase in synaptic weights of excitatory or inhibitory neurons raises the excitability of individual cells and elevates the activation level of the network. To conclude, our simulations suggest that the impairment of both neurons and astrocytes disturbs the neuronal network activity in schizophrenia.

Patterns of whole-body muscle activations following vertical perturbations during standing and walking

BACKGROUND

Falls commonly occur due to losses of balance associated with vertical body movements (e.g. reacting to uneven ground, street curbs). Research, however, has focused on horizontal perturbations, such as forward and backward translations of the standing surface. This study describes and compares muscle activation patterns following vertical and horizontal perturbations during standing and walking, and investigates the role of vision during standing postural responses.

METHODS

Fourteen healthy participants (ten males; 27±4 years-old) responded to downward, upward, forward, and backward perturbations while standing and walking in a virtual reality (VR) facility containing a moveable platform with an embedded treadmill; participants were also exposed to visual perturbations in which only the virtual scenery moved. We collected bilateral surface electromyography (EMG) signals from 8 muscles (tibialis anterior, rectus femoris, rectus abdominis, external oblique, gastrocnemius, biceps femoris, paraspinals, deltoids). Parameters included onset latency, duration of activation, and activation magnitude. Standing perturbations comprised dynamic-camera (congruent), static-camera (incongruent) and eyes-closed sensory conditions. ANOVAs were used to compare the effects of perturbation direction and sensory condition across muscles.

RESULTS

Vertical perturbations induced longer onset latencies and shorter durations of activation with lower activation magnitudes in comparison to horizontal perturbations (p<0.0001). Downward perturbations while standing generated earlier activation of anterior muscles to facilitate flexion (for example, p=0.0005 and p=0.0021 when comparing the early activators, rectus femoris and tibialis anterior, to a late activator, the paraspinals), whereas upward perturbations generated earlier activation of posterior muscles to facilitate extension (for example, p<0.0001 and p=0.0004, when comparing the early activators, biceps femoris and gastrocnemius, to a late activator, the rectus abdominis). Static-camera conditions induced longer onset latencies (p=0.0085 and p<0.0001 compared to eyes-closed and dynamic-camera conditions, respectively), whereas eyes-closed conditions induced longer durations of activation (p=0.0001 and p=0.0008 compared to static-camera and dynamic-camera, respectively) and larger activation magnitudes. During walking, downward perturbations promptly activated contralateral trunk and deltoid muscles (e.g., p=0.0036 for contralateral deltoid versus a late activator, the ipsilateral tibialis anterior), and upward perturbations triggered early activation of trunk flexors (e.g., p=0.0308 for contralateral rectus abdominis versus a late activator, the ipsilateral gastrocnemius). Visual perturbations elicited muscle activation in 67.7% of trials.

CONCLUSION

Our results demonstrate that vertical (vs. horizontal) perturbations generate unique balance-correcting muscle activations, which were consistent with counteracting vertical body extension induced by downward perturbations and vertical body flexion induced by upward perturbations. Availability of visual input appears to affect response efficiency, and incongruent visual input can adversely affect response triggering. Our findings have clinical implications for the design of robotic exoskeletons (to ensure user safety in dynamic balance environments) and for perturbation-based balance and gait rehabilitation.

A Computational Model of Interactions Between Neuronal and Astrocytic Networks: The Role of Astrocytes in the Stability of the Neuronal Firing Rate

Recent research in neuroscience indicates the importance of tripartite synapses and gliotransmission mediated by astrocytes in neuronal system modulation. Although the astrocyte and neuronal network functions are interrelated, they are fundamentally different in their signaling patterns and, possibly, the time scales at which they operate. However, the exact nature of gliotransmission and the effect of the tripartite synapse function at the network level are currently elusive. In this paper, we propose a computational model of interactions between an astrocyte network and a neuron network, starting from tripartite synapses and spanning to a joint network level. Our model focuses on a two-dimensional setup emulating a mixed in vitro neuron-astrocyte cell culture. The model depicts astrocyte-released gliotransmitters exerting opposing effects on the neurons: increasing the release probability of the presynaptic neuron while hyperpolarizing the post-synaptic one at a longer time scale. We simulated the joint networks with various levels of astrocyte contributions and neuronal activity levels. Our results indicate that astrocytes prolong the burst duration of neurons, while restricting hyperactivity. Thus, in our model, the effect of astrocytes is homeostatic; the firing rate of the network stabilizes to an intermediate level independently of neuronal base activity. Our computational model highlights the plausible roles of astrocytes in interconnected astrocytic and neuronal networks. Our simulations support recent findings in neurons and astrocytes in vivo and in vitro suggesting that astrocytic networks provide a modulatory role in the bursting of the neuronal network.

Skin sympathetic nerve activity and the temporal clustering of cardiac arrhythmias

BACKGROUND

Simultaneous noninvasively recorded skin sympathetic nerve activity (SKNA) and electrocardiogram (neuECG) can be used to estimate cardiac sympathetic tone. We tested the hypothesis that large and prolonged SKNA bursts are associated with temporal clustering arrhythmias.

METHODS

We recorded neuECG in 10 patients (69 ± 10 years old) with atrial fibrillation (AF) episodes and in 6 patients (50 ± 13 years old) with ventricular tachycardia (VT) or fibrillation (VF) episodes. Clustering was defined by an arrhythmic episode followed within 1 minute by spontaneous recurrences of the same arrhythmia. The neuECG signals were bandpass filtered between 500-1000 Hz to display SKNA.

RESULTS

There were 22 AF clusters, including 231 AF episodes from 6 patients, and 9 VT/VF clusters, including 99 VT/VF episodes from 3 patients. A total duration of SKNA bursts associated with AF was longer than that during sinus rhythm (78.9 min/hour [interquartile range (IQR) 17.5-201.3] vs. 16.3 min/hour [IQR 14.5-18.5], P = 0.022). The burst amplitude associated with AF in clustering patients was significantly higher than that in nonclustering patients (1.54 μV [IQR 1.35-1.89], n = 114, vs. 1.20 μV [IQR 1.05-1.42], n = 21, P < 0.001). The SKNA bursts associated with VT/VF clusters lasted 9.3 ± 3.1 minutes, with peaks that averaged 1.13 ± 0.38 μV as compared with 0.79 ± 0.11 μV at baseline (P = 0.041).

CONCLUSION

Large and sustained sympathetic nerve activities are associated with the temporal clustering of AF and VT/VF.

FUNDING

This study was supported in part by NIH grants R42DA043391 (THE), R56 HL71140, TR002208-01, R01 HL139829 (PSC), a Charles Fisch Cardiovascular Research Award endowed by Suzanne B. Knoebel of the Krannert Institute of Cardiology (TK and THE), a Medtronic-Zipes Endowment, and the Indiana University Health-Indiana University School of Medicine Strategic Research Initiative (PSC).

Burst Detection Methods

'Bursting', defined as periods of high-frequency firing of a neuron separated by periods of quiescence, has been observed in various neuronal systems, both in vitro and in vivo. It has been associated with a range of neuronal processes, including efficient information transfer and the formation of functional networks during development, and has been shown to be sensitive to genetic and pharmacological manipulations. Accurate detection of periods of bursting activity is thus an important aspect of characterising both spontaneous and evoked neuronal network activity. A wide variety of computational methods have been developed to detect periods of bursting in spike trains recorded from neuronal networks. In this chapter, we review several of the most popular and successful of these methods.

Neural Coding With Bursts-Current State and Future Perspectives

Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a short, high frequency train of spikes, will more reliably cross a synapse, increasing the likelihood of eliciting a postsynaptic spike, depending on the specific short-term plasticity at that synapse. Both the number and the temporal pattern of spikes in a burst provide a coding space that lies within the temporal integration realm of single neurons. Bursts have been observed in many species, including the non-mammalian, and in brain regions that range from subcortical to cortical. Despite their widespread presence and potential relevance, the uncertainties of how to classify bursts seems to have limited the research into the coding possibilities for bursts. The present series of research articles provides new insights into the relevance and interpretation of bursts across different neural circuits, and new methods for their analysis. Here, we provide a succinct introduction to the history of burst coding and an overview of recent work on this topic.