Engineering an in vitro retinothalamic nerve model.

Understanding the retinogeniculate pathway in vitro can offer insights into its development and potential for future therapeutic applications. This study presents a Polydimethylsiloxane-based two-chamber system with axon guidance channels, designed to replicate unidirectional retinogeniculate signal transmission in vitro. Using embryonic rat retinas, we developed a model where retinal spheroids innervate thalamic targets through up to 6 mm long microfluidic channels. Using a combination of electrical stimulation and functional calcium imaging we assessed how channel length and electrical stimulation frequency affects thalamic target response. In the presented model we integrated up to 20 identical functional retinothalamic neural networks aligned on a single transparent microelectrode array, enhancing the robustness and quality of recorded functional data. We found that network integrity depends on channel length, with 0.5-2 mm channels maintaining over 90% morphological and 50% functional integrity. A reduced network integrity was recorded in longer channels. The results indicate a notable reduction in forward spike propagation in channels longer than 4 mm. Additionally, spike conduction fidelity decreased with increasing channel length. Yet, stimulation-induced thalamic target activity remained unaffected by channel length. Finally, the study found that a sustained thalamic calcium response could be elicited with stimulation frequencies up to 31 Hz, with higher frequencies leading to transient responses. In conclusion, this study presents a high-throughput platform that demonstrates how channel length affects retina to brain network formation and signal transmission in vitro.

Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.

Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.

Integration of white matter architecture to stereo-EEG better describes epileptic spike propagation.

OBJECTIVE: Stereo-electroencephalography (SEEG)-derived epilepsy networks are used to better understand a patient's epilepsy; however, a unimodal approach provides an incomplete picture. We combine tractography and SEEG to determine the relationship between spike propagation and the white matter architecture and to improve our understanding of spike propagation mechanisms. METHODS: Probablistic tractography from diffusion imaging (dMRI) of matched subjects from the Human Connectome Project (HCP) was combined with patient-specific SEEG-derived spike propagation networks. Two regions-of-interest (ROIs) with a significant spike propagation relationship constituted a Propagation Pair. RESULTS: In 56 of 59 patients, Propagation Pairs were more often tract-connected as compared to all ROI pairs (p < 0.01; d = -1.91). The degree of spike propagation between tract-connected ROIs was greater (39 ± 21%) compared to tract-unconnected ROIs (31 ± 18%; p < 0.0001). Within the same network, ROIs receiving propagation earlier were more often tract-connected to the source (59.7%) as compared to late receivers (25.4%; p < 0.0001). CONCLUSIONS: Brain regions involved in spike propagation are more likely to be connected by white matter tracts. Between nodes, presence of tracts suggests a direct course of propagation, whereas the absence of tracts suggests an indirect course of propagation. SIGNIFICANCE: We demonstrate a logical and consistent relationship between spike propagation and the white matter architecture.

Modelling the effect of ephaptic coupling on spike propagation in peripheral nerve fibres.

Experimental and theoretical studies have shown that ephaptic coupling leads to the synchronisation and slowing down of spikes propagating along the axons within peripheral nerve bundles. However, the main focus thus far has been on a small number of identical axons, whereas realistic peripheral nerve bundles contain numerous axons with different diameters. Here, we present a computationally efficient spike propagation model, which captures the essential features of propagating spikes and their ephaptic interaction, and facilitates the theoretical investigation of spike volleys in large, heterogeneous fibre bundles. We first lay out the theoretical basis to describe how the spike in an active axon changes the membrane potential of a passive axon. These insights are then incorporated into the spike propagation model, which is calibrated with a biophysically realistic model based on Hodgkin-Huxley dynamics. The fully calibrated model is then applied to fibre bundles with a large number of axons and different types of axon diameter distributions. One key insight of this study is that the heterogeneity of the axonal diameters has a dispersive effect, and that a higher level of heterogeneity requires stronger ephaptic coupling to achieve full synchronisation between spikes.

Probabilistic Spike Propagation for Efficient Hardware Implementation of Spiking Neural Networks.

Spiking neural networks (SNNs) have gained considerable attention in recent years due to their ability to model temporal event streams, be trained using unsupervised learning rules, and be realized on low-power event-driven hardware. Notwithstanding the intrinsic desirable attributes of SNNs, there is a need to further optimize their computational efficiency to enable their deployment in highly resource-constrained systems. The complexity of evaluating an SNN is strongly correlated to the spiking activity in the network, and can be measured in terms of a fundamental unit of computation, viz. spike propagation along a synapse from a single source neuron to a single target neuron. We propose probabilistic spike propagation, an approach to optimize rate-coded SNNs by interpreting synaptic weights as probabilities, and utilizing these probabilities to regulate spike propagation. The approach results in 2.4-3.69× reduction in spikes propagated, leading to reduced time and energy consumption. We propose Probabilistic Spiking Neural Network Application Processor (P-SNNAP), a specialized SNN accelerator with support for probabilistic spike propagation. Our evaluations across a suite of benchmark SNNs demonstrate that probabilistic spike propagation results in 1.39-2× energy reduction with simultaneous speedups of 1.16-1.62× compared to the traditional model of SNN evaluation.

Intermittent Failure of Spike Propagation in Primary Afferent Neurons during Tactile Stimulation.

Primary afferent neurons convey somatosensory information to the CNS. Low-threshold mechanoreceptors are classified as slow-adapting (SA) or rapid-adapting (RA) based on whether or not they spike repetitively during sustained tactile stimulation; the former are subclassified as Type 1 or 2 based on the regularity of their spiking. Recording in vivo from DRGs of mice, we observed irregular- and regular-spiking units consistent with SA1 and SA2 low-threshold mechanoreceptors, but some units, which we labeled "semiregular," did not fit cleanly into the existing classification scheme. Analysis of their spiking revealed integer-multiple patterning in which spike trains comprised a fundamental interspike interval and multiples thereof. Integer-multiple-patterned spiking was reproduced by randomly removing spikes from an otherwise regular spike train, suggesting that semiregular units represent SA2 units in which some spikes are "missing." We hypothesized that missing spikes arose from intermittent failure of spikes to initiate or to propagate. Intermittent failure of spike initiation was ruled out by several observations: integer-multiple-patterned spiking was not induced by intradermal lidocaine, was independent of stimulus modality (mechanical vs optogenetic), and could not be reproduced in a conductance-based model neuron given constant input. On the other hand, integer-multiple-patterned spiking was induced by application of lidocaine to the DRG, thus pinpointing intermittent failure of spike propagation as the basis for integer-multiple-patterned spiking. Indeed, half of all SA2 units exhibited some missing spikes, mostly at low rate (<5%), which suggests that axons are efficient in using the lowest safety factor capable of producing near-perfect propagation reliability.SIGNIFICANCE STATEMENT The impedance mismatch at axon branch points can impede spike propagation. Reliability of spike propagation across branch points remains an open question and is especially important for primary afferents whose spikes must cross a T-junction to reach the CNS. Past research on propagation reliability has relied almost entirely on simulations and in vitro experiments. Here, recording in vivo, we linked a distinctive pattern of spiking to the intermittent failure of spike propagation at the T-junction. The rarity of failures argues that safety factor is high under physiological conditions, yet the occurrence of such failures argues that safety factor is just high enough to ensure near-perfect reliability, consistent with a good balance between propagation reliability and energy efficiency.

Epileptiform discharge propagation: Analyzing spikes from the onset to the peak.

OBJECTIVE: To investigate how often discharge propagation occurs within the spikes recorded in patients evaluated for epilepsy surgery, and to assess its impact on the accuracy of source imaging. METHODS: Data were analyzed from 50 consecutive patients who had presurgical workup. Discharge propagation was analyzed using sequential voltage-maps of the averaged spikes, and principal components analysis. When propagation was detected, sources were modeled both at onset and peak. RESULTS: Propagation occurred in half of the patients. The median time of propagation between onset and peak was 17 ms. In 60% of the cases with propagation (15/25 patients) this remained in the same sub-lobar area where onset occurred. The accuracy of source imaging in cases of propagating spikes was 67% when only analyzing onset or peak. This was lower as compared to cases without propagation (79%). Combining source imaging at onset and at peak increased the accuracy to 83% for the propagating spikes. CONCLUSIONS: Propagation occurs often in patients with focal epilepsy, evaluated for surgery. In 40% of the propagating cases, the source of onset and peak were in different sub-lobar regions. SIGNIFICANCE: For optimal clinical utility, sources should be modeled both at onset and at peak epochs of the spikes.

Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings.

Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered.

A Lognormal Recurrent Network Model for Burst Generation during Hippocampal Sharp Waves.

The strength of cortical synapses distributes lognormally, with a long tail of strong synapses. Various properties of neuronal activity, such as the average firing rates of neurons, the rate and magnitude of spike bursts, the magnitude of population synchrony, and the correlations between presynaptic and postsynaptic spikes, also obey lognormal-like distributions reported in the rodent hippocampal CA1 and CA3 areas. Theoretical models have demonstrated how such a firing rate distribution emerges from neural network dynamics. However, how the other properties also display lognormal patterns remain unknown. Because these features are likely to originate from neural dynamics in CA3, we model a recurrent neural network with the weights of recurrent excitatory connections distributed lognormally to explore the underlying mechanisms and their functional implications. Using multi-timescale adaptive threshold neurons, we construct a low-frequency spontaneous firing state of bursty neurons. This state well replicates the observed statistical properties of population synchrony in hippocampal pyramidal cells. Our results show that the lognormal distribution of synaptic weights consistently accounts for the observed long-tailed features of hippocampal activity. Furthermore, our model demonstrates that bursts spread over the lognormal network much more effectively than single spikes, implying an advantage of spike bursts in information transfer. This efficiency in burst propagation is not found in neural network models with Gaussian-weighted recurrent excitatory synapses. Our model proposes a potential network mechanism to generate sharp waves in CA3 and associated ripples in CA1 because bursts occur in CA3 pyramidal neurons most frequently during sharp waves.

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons.

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs.

Normal and abnormal electrical propagation in the small intestine.

As in other muscular organs, small intestinal motility is determined to a large degree by the electrical activities that occur in the smooth muscle layers of the small intestine. In recent decades, the interstitial cells of Cajal, located in the myenteric plexus, have been shown to be responsible for the generation and propagation of the electrical impulse: the slow wave. It was also known that the slow waves as such do not cause contraction, but that the action potentials ('spikes') that are generated by the slow waves are responsible for the contractions. Recording from large number of extracellular electrodes simultaneously is one method to determine origin and pattern of propagation of these electrical signals. This review reports the characteristics of slow wave propagation through the intestinal tube, the occurrence of propagation blocks along its length, which explains the well-known decrease in frequency, and the specific propagation pattern of the spikes that follow the slow waves. But the value of high-resolution mapping is highest in discovering and analysing mechanisms of arrhythmias in the gut. Most recently, circus movements (also called 're-entries') have been described in the small intestine in several species. Moreover, several types of re-entries have now been described, some similar to what may occur in the heart, such as functional re-entries, but others more unique to the small intestine, such as circumferential re-entry. These findings seem to suggest the possibilities of hitherto unknown pathologies that may be present in the small intestine.

Clinical application of spatiotemporal distributed source analysis in presurgical evaluation of epilepsy.

Magnetoencephalography (MEG), which acquires neuromagnetic fields in the brain, is a useful diagnostic tool in presurgical evaluation of epilepsy. Previous studies have shown that MEG affects the planning intracranial electroencephalography placement and correlates with surgical outcomes by using a single dipole model. Spatiotemporal source analysis using distributed source models is an advanced method for analyzing MEG, and has been recently introduced for analyzing epileptic spikes. It has advantages over the conventional single dipole analysis for obtaining accurate sources and understanding the propagation of epileptic spikes. In this article, we review the source analysis methods, describe the techniques of the distributed source analysis, interpretation of source distribution maps, and discuss the benefits and feasibility of this method in evaluation of epilepsy.

Clinical value of magnetoencephalographic spike propagation represented by spatiotemporal source analysis: correlation with surgical outcome.

OBJECTIVE: To investigate the correlation between spike propagation represented by spatiotemporal source analysis of magnetoencephalographic (MEG) spikes and surgical outcome in patients with temporal lobe epilepsy. METHODS: Thirty-seven patients were divided into mesial (n=27) and non-mesial (n=10) groups based on the presurgical evaluation. In each patient, ten ipsilateral spikes were averaged, and spatiotemporal source maps of the averaged spike were obtained by using minimum norm estimate. Regions of interest (ROIs) were created including temporoparietal, inferior frontal, mesial temporal, anterior and posterior part of the lateral temporal cortex. We extracted activation values from the source maps and the threshold was set at half of the maximum activation at the peak latency. The leading and propagated areas of the spike were defined as those ROIs with activation reaching the threshold at the earliest and at the peak latencies, respectively. Surgical outcome was assessed based on Engel's classification. Binary variables were created from leading areas (restricted to the anterior and mesial temporal ROIs or not) and from propagation areas (involving the temporoparietal ROI or not), and for surgical outcome (Class I or not). Fisher's exact test was used for significance testing. RESULTS: In total and mesial group, restricted anterior/mesial temporal leading areas were correlated with Class I (p<0.05). Temporoparietal propagation was correlated with Class II-IV (p<0.05). For the non-mesial group, no significant relation was found. CONCLUSIONS: Spike propagation patterns represented by spatiotemporal source analysis of MEG spikes may provide useful information for prognostic implication in presurgical evaluation of epilepsy.

Comparison of Source Characteristics between Typical and Atypical Rolandic Epilepsy in Childhood / 대한간질학회지

PURPOSE: has been reported that benign rolandic epilepsy of childhood (BRE) does not always show benign nature in a clinical course. We hypothesized that children with atypical feature showed different characteristics of dipole sources of rolandic spikes. METHODS: Twenty-nine children with BRE were enrolled. Twenty patients showed typical features of BRE (typical BRE group). Nine patients were classified as atypical BRE, because each met one or more of the following criteria:(i) neurodevelopmental abnormalities such as mental retardation or delayed development;(ii) abnormal neuroimaging findings; and (iii) poor seizure control. Routine waking and sleep EEG recordings were obtained for at least 30 min from each patients, using a 32-channel digital EEG machine. Centrotemporal spikes were averaged which was used to do dipole source localization. The source location was estimated within a four-shell ellipsoidal model of the head. Voltage topography, orientation and propagation pattern of dipole source, as well as clinical characteristics were compared between two groups. RESULTS: The clinical characteristics such as age, sex, seizure onset age, and seizure outcome were same in both groups. The negative maximum of spikes was mainly on the central and temporal electrodes in both groups. Two thirds of patients in each group demonstrated dipole sources with tangential orientation. 40% of the typical BRE revealed two sources indicating propagation of spikes around rolandic areas, which was not observed in atypical group. The pattern of propagation was mostly from tangential to radial in anterior direction. CONCLUSIONS: These results suggest that the pathophysiological mechanism generating centrotemporal spikes of atypical BRE is different from that of typical ones.