Long-Lasting Desynchronization Effects of Coordinated Reset Stimulation Improved by Random Jitters

Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands.

Long range synchronization within the enteric nervous system underlies propulsion along the large intestine in mice

How the Enteric Nervous System (ENS) coordinates propulsion of content along the gastrointestinal (GI)-tract has been a major unresolved issue. We reveal a mechanism that explains how ENS activity underlies propulsion of content along the colon. We used a recently developed high-resolution video imaging approach with concurrent electrophysiological recordings from smooth muscle, during fluid propulsion. Recordings showed pulsatile firing of excitatory and inhibitory neuromuscular inputs not only in proximal colon, but also distal colon, long before the propagating contraction invades the distal region. During propulsion, wavelet analysis revealed increased coherence at ~2 Hz over large distances between the proximal and distal regions. Therefore, during propulsion, synchronous firing of descending inhibitory nerve pathways over long ranges aborally acts to suppress smooth muscle from contracting, counteracting the excitatory nerve pathways over this same region of colon. This delays muscle contraction downstream, ahead of the advancing contraction. The mechanism identified is more complex than expected and vastly different from fluid propulsion along other hollow smooth muscle organs; like lymphatic vessels, portal vein, or ureters, that evolved without intrinsic neurons.

HMGB1, neuronal excitability and epilepsy

Epilepsy is a common neurological disease caused by synchronous firing of hyperexcitable neurons. Currently, anti-epileptic drugs remain the main choice to control seizure, but 30% of patients are resistant to the drugs, which calls for more research on new promising targets. Neuroinflammation is closely associated with the development of epilepsy. As an important inflammatory factor, high mobility group protein B1 (HMGB1) has shown elevated expression and an increased proportion of translocation from the nucleus to the cytoplasm in patients with epilepsy and in multiple animal models of epilepsy. HMGB1 can act on downstream receptors such as Toll-like receptor 4 and receptor for advanced glycation end products, thereby activating interleukin (IL)-1β and nuclear factor kappa-B (NF-κB), which in turn act with glutamate receptors such as the N-methyl-D-aspartate (NMDA) receptors to aggravate hyperexcitability and epilepsy. The hyperexcitability can in turn stimulate the expression and translocation of HMGB1. Blocking HMGB1 and its downstream signaling pathways may be a direction for antiepileptic drug therapy. Here, we review the changes of HMGB1-related pathway in epileptic brains and its role in the modulation of neuronal excitability and epileptic seizure. Furthermore, we discuss the potentials of HMGB1 as a therapeutic target for epilepsy and provide perspective on future research on the role of HMGB1 signaling in epilepsy.

Predicting synchronous firing of large neural populations from sequential recordings

A major goal in neuroscience is to understand how populations of neurons code for stimuli or actions. While the number of neurons that can be recorded simultaneously is increasing at a fast pace, in most cases these recordings cannot access a complete population: some neurons that carry relevant information remain unrecorded. In particular, it is hard to simultaneously record all the neurons of the same type in a given area. Recent progress have made possible to profile each recorded neuron in a given area thanks to genetic and physiological tools, and to pool together recordings from neurons of the same type across different experimental sessions. However, it is unclear how to infer the activity of a full population of neurons of the same type from these sequential recordings. Neural networks exhibit collective behaviour, e.g. noise correlations and synchronous activity, that are not directly captured by a conditionally-independent model that would just put together the spike trains from sequential recordings. Here we show that we can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling. From just the spiking response of each ganglion cell to a repeated stimulus, and a few pairwise recordings, we could predict the noise correlations using copulas, and then the full activity of a large population of ganglion cells of the same type using maximum entropy modeling. Remarkably, we could generalize to predict the population responses to different stimuli with similar light conditions and even to different experiments. We could therefore use our method to construct a very large population merging cells’ responses from different experiments. We predicted that synchronous activity in ganglion cell populations saturates only for patches larger than 1.5mm in radius, beyond what is today experimentally accessible.

Dynamic Transitions in Neuronal Network Firing Sustained by Abnormal Astrocyte Feedback

Astrocytes play a crucial role in neuronal firing activity. Their abnormal state may lead to the pathological transition of neuronal firing patterns and even induce seizures. However, there is still little evidence explaining how the astrocyte network modulates seizures caused by structural abnormalities, such as gliosis. To explore the role of gliosis of the astrocyte network in epileptic seizures, we first established a direct astrocyte feedback neuronal network model on the basis of the hippocampal CA3 neuron-astrocyte model to simulate the condition of gliosis when astrocyte processes swell and the feedback to neurons increases in an abnormal state. We analyzed the firing pattern transitions of the neuronal network when astrocyte feedback starts to change via increases in both astrocyte feedback intensity and the connection probability of astrocytes to neurons in the network. The results show that as the connection probability and astrocyte feedback intensity increase, neuronal firing transforms from a nonepileptic synchronous firing state to an asynchronous firing state, and when astrocyte feedback starts to become abnormal, seizure-like firing becomes more severe and synchronized; meanwhile, the synchronization area continues to expand and eventually transforms into long-term seizure-like synchronous firing. Therefore, our results prove that astrocyte feedback can regulate the firing of the neuronal network, and when the astrocyte network develops gliosis, there will be an increase in the induction rate of epileptic seizures.

Polysynaptic inhibition between striatal cholinergic interneurons shapes their network activity patterns in a dopamine-dependent manner

Striatal activity is dynamically modulated by acetylcholine and dopamine, both of which are essential for basal ganglia function. Synchronized pauses in the activity of striatal cholinergic interneurons (ChINs) are correlated with elevated activity of midbrain dopaminergic neurons, whereas synchronous firing of ChINs induces local release of dopamine. The mechanisms underlying ChIN synchronization and its interplay with dopamine release are not fully understood. Here we show that polysynaptic inhibition between ChINs is a robust network motif and instrumental in shaping the network activity of ChINs. Action potentials in ChINs evoke large inhibitory responses in multiple neighboring ChINs, strong enough to suppress their tonic activity. Using a combination of optogenetics and chemogenetics we show the involvement of striatal tyrosine hydroxylase-expressing interneurons in mediating this inhibition. Inhibition between ChINs is attenuated by dopaminergic midbrain afferents acting presynaptically on D2 receptors. Our results present a novel form of interaction between striatal dopamine and acetylcholine dynamics.

Insulin potentiates the synchronous firing of arcuate nucleus Kiss1 neurons that protects against diet-induced obesity

Kisspeptin neurons in the hypothalamic arcuate nucleus (Kiss1ARH) co-express kisspeptin, neurokinin B, dynorphin and provide an episodic, excitatory drive to gonadotropin-releasing hormone (GnRH) neurons, which is critical for pubertal development and fertility. Previously, we showed that high frequency firing of Kiss1ARH neurons co-releases NKB and dynorphin onto neighboring Kiss1ARH neurons to generate a slow excitatory postsynaptic potential (EPSP) that entrains intermittent, synchronous firing of Kiss1ARH neurons (Qiu et al., 2016). Presently, we discovered that insulin significantly increased the amplitude of the slow EPSP, which we documented is mediated by TRPC5 channels, and augmented synchronous GCaMP6s ([Ca]i) oscillations in Kiss1ARH neurons. Deletion of the endoplasmic reticulum calcium-sensing protein stromal interaction molecule 1 in Kiss1ARH neurons amplified insulin’s actions and protected ovariectomized female mice from developing obesity and glucose intolerance with high-fat dieting. Therefore, insulin appears to be critical for facilitating synchronous firing of Kiss1ARH neurons and coordinating energy homeostasis with fertility.

The effect of A1R agonist on epileptiform activity in organotypic slices

Epilepsy is a common neurological disorder but resistance to pharmacotherapy makes it necessary the development of novel antiepileptic drugs (AEDs). An A1 adenosine receptor (A1R) agonist, MRS5474, possesses anticonvulsant activity in an animal model (Tosh et al.,2012-J.Med.Chem., 55,8075), without the cardiac side effects common to other A1R agonists, leading us to hypothesise that it could operate through a mechanism different from classical A1R agonists. We thus tested this hypothesis in an ex vivo model of epileptogenesis in rhinal cortex -hippocampus organotypic slices (Magalhães et al., 2018-J.Neuroinflam.15:203). MRS5474 (250nM) was incubated during 1h with slices under depolarizing ([K + ] o =8.5mM) or non-depolarizing ([K + ] o =3mM) conditions. Interestingly, MRS5474 decreased by 6615% (n=4, P<0.05) the number of bursts from slices under high K + but not under normal K + . Event frequency, amplitude and burst duration were not affected. The canonical A1R agonist, N 6 -cyclopentyladenosine (30nM, n=4) prevented burst-like activity (number of bursts decreased to zero, spike amplitude markedly reduced) even under non-depolarizing conditions. Our results showing that MRS5474 prevents spontaneous neuronal firing only under depolarizing conditions, suggest that it may predominantly influence spontaneous synchronous firing of stressed neurons, sparing non-injured ones. This renders this compound with presumably less side effects than other A1R agonists and currently available AEDs.