In-vivo Recordings Research Articles

Spike-based computational primitives to reproduce neural dynamics in the parietal cortex during motor preparation

Abstract Biologically plausible spiking neural network models of sensory cortices can be instrumental in understanding and validating their principles of computation.
 Models based on Cortical Computational Primitives (CCPs), such as Hebbian plasticity and Winner-Take-All (WTA) networks, have already been successful in this approach.
 However, the specific nature and roles of CCPs in sensorimotor cortices during cognitive tasks are yet to be fully deciphered.
 The evolution of motor intention in the Posterior Parietal Cortex (PPC) before arm-reaching movements is a well-suited cognitive process to assess the effectiveness of different CCPs.
 To this end, we propose a biologically plausible model composed of heterogeneous spiking neurons which implements and combines multiple CCPs, such as multi-timescale learning and soft WTA modules.
 By training the model to replicate the dynamics of in-vivo recordings from non-human primates, we show how it is effective in generating meaningful representations from unbalanced input data, and in faithfully reproducing the transition from motor planning to action selection.
 Our findings elucidate the importance of distributing spike-based plasticity across multi-timescales, and provide an explanation for the role of different CCPs in models of frontoparietal cortical networks for performing multisensory integration to efficiently inform action execution.

Localization of neurons from extracellular footprints

Background:High density microelectrode arrays (HD-MEAs) are now widely used for both in-vitro and in-vivo recordings, as they allow spikes from hundreds of neurons to be recorded simultaneously. Since extracellular recordings do not allow visualization of the recorded neurons, algorithms are needed to estimate their physical positions, especially to track their movements when the are drifting away from recording devices. New Method:The objective of this study was to evaluate the performance of multiple algorithms for neuron localization solely from extracellular traces (MEA recordings), either artificial or obtained from mouse retina. The algorithms compared included center-of-mass, monopolar, and grid-based algorithms. The first method is a barycenter calculation. The second algorithm infers the position of the cell using triangulation with the assumption that the neuron behaves as a monopole. Finally, grid-based methods rely on comparing the recorded spike with a projection of spikes of hypothetical neurons with different positions. Results:The Grid-Based algorithm yielded the most satisfactory outcomes. The center-of-mass exhibited a minimal computational cost, yet its average localization was suboptimal. Monopolar algorithms gave cell localizations with an average error of less than 10μm, but they had considerable variability and a high computational cost. For the grid-based method, the variability was smaller, with satisfactory performance and low computational cost. Comparison with Existing Method(s):The accuracy of the different localization methods benchmarked in this article had not been properly tested with ground-truth recordings before. Conclusion:The objective of this article is to provide guidance to researchers on the selection of optimal methods for localizing neurons based on MEA recordings.

Physical exercise mediates cortical synaptic protein lactylation to improve stress resilience

Lactate is a critical metabolite during the body's adaption to exercise training, which effectively relieves anxiety-like disorders. The biological mechanism of lactate in the exercise-mediated anxiolytic effect has, however, not been comprehensively investigated. Here, we report that exercise-induced lactate markedly potentiates the lactylation of multiple synaptic proteins, among which synaptosome-associated protein 91 (SNAP91) is the critical molecule for synaptic functions. Both anatomical evidence and invivo recording data showed that the lactylation of SNAP91 confers resilience against chronic restraint stress (CRS) via potentiating synaptic structural formation and neuronal activity in the medial prefrontal cortex (mPFC). More interestingly, exercise-potentiated lactylation of SNAP91 is necessary for the prevention of anxiety-like behaviors in CRS mice. These results collectively suggest a previously unrecognized non-histone lactylation in the brain for modulating mental functions and provide evidence for the brain's metabolic adaption during exercise paradigms.

Hepatocyte Growth Factor Delivery to Injured Cervical Spinal Cord Using an Engineered Biomaterial Protects Respiratory Neural Circuitry and Preserves Functional Diaphragm Innervation.

A major portion of spinal cord injury (SCI) cases occur in the cervical region, where essential components of the respiratory neural circuitry are located. Phrenic motor neurons (PhMNs) housed at cervical spinal cord level C3-C5 directly innervate the diaphragm, and SCI-induced damage to these cells severely impairs respiratory function. In this study, we tested a biomaterial-based approach aimed at preserving this critical phrenic motor circuitry after cervical SCI by locally delivering hepatocyte growth factor (HGF). HGF is a potent mitogen that promotes survival, proliferation, migration, repair, and regeneration of a number of different cell and tissue types in response to injury. We developed a hydrogel-based HGF delivery system that can be injected into the intrathecal space for local delivery of high levels of HGF without damaging the spinal cord. Implantation of HGF hydrogel after unilateral C5 contusion-type SCI in rats preserved diaphragm function, as assessed by invivo recordings of both compound muscle action potentials and inspiratory electromyography amplitudes. HGF hydrogel also preserved PhMN innervation of the diaphragm, as assessed by both retrograde PhMN tracing and detailed neuromuscular junction morphological analysis. Furthermore, HGF hydrogel significantly decreased lesion size and degeneration of cervical motor neuron cell bodies, as well as reduced levels surrounding the injury site of scar-associated chondroitin sulfate proteoglycan molecules that limit axon growth capacity. Our findings demonstrate that local biomaterial-based delivery of HGF hydrogel to injured cervical spinal cord is an effective strategy for preserving respiratory circuitry and diaphragm function.

A 0.00179 mm2/Ch Chopper-Stabilized TDMA Neural Recording System With Dynamic EOV Cancellation and Predictive Mixed-Signal Impedance Boosting.

This article presents a digitally-assisted multi-channel neural recording system. The system uses a 16-channel chopper-stabilized Time Division Multiple Access (TDMA) scheme to record multiplexed neural signals into a single shared analog front end (AFE). The choppers reduce the total integrated noise across the modulated spectrum by 2.4 × and 4.3 × in Local Field Potential (LFP) and Action Potential (AP) bands, respectively. In addition, a novel impedance booster based on Sign-Sign least mean squares (LMS) adaptive filter (AF) predicts the input signal and pre-charges the AC-coupling capacitors. The impedance booster module increases the AFE input impedance by a factor of 39 × with a 7.1% increase in area. The proposed system obviates the need for on-chip digital demodulation, filtering, and remodulation normally required to extract Electrode Offset Voltages (EOV) from multiplexed neural signals, thereby achieving 3.6 × and 2.8 × savings in both area and power, respectively, in the EOV filter module. The Sign-Sign LMS AF is reused to determine the system loop gain, which relaxes the feedback DAC accuracy requirements and saves 10.1 × in power compared to conventional oversampled DAC truncation-error ΔΣ-modulator. The proposed SoC is designed and fabricated in 65 nm CMOS, and each channel occupies 0.00179 mm2 of active area. Each channel consumes 5.11 μW of power while achieving 2.19 μVrms and 2.4 μVrms of input referred noise (IRN) over AP and LFP bands. The resulting AP band noise efficiency factor (NEF) is 1.8. The proposed system is verified with acute in-vivo recordings in a Sprague-Dawley rat using parylene C based thin-film platinum nanorod microelectrodes.

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus.

Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states. Namely, we find that DOWN states during SWS force the population activity to be more recurrent, deterministic, and less random than during REM sleep or wakefulness, which, in turn, leads to less complex field recordings. Importantly, when we exclude DOWN states from the analysis, the recordings during wakefulness and sleep become indistinguishable: the spiking activity in all the states collapses to a common scaling. We complement these results by implementing a critical branching model of the cortex, which shows that inducing DOWN states to only a percentage of neurons is enough to generate a decrease in complexity that replicates SWS.

A neural circuit for regulating a behavioral switch in response to prolonged uncontrollability in mice

Persistence in the face of failure helps to overcome challenges. But the ability to adjust behavior or even give up when the task is uncontrollable has advantages. How the mammalian brain switches behavior when facing uncontrollability remains an open question. We generated two mouse models of behavioral transition from action to no-action during exposure to a prolonged experience with an uncontrollable outcome. The transition was not caused by pain desensitization or muscle fatigue and was not a depression-/learned-helplessness-like behavior. Noradrenergic neurons projecting to GABAergic neurons within the orbitofrontal cortex (OFC) are key regulators of this behavior. Fiber photometry, microdialysis, mini-two-photon microscopy, and tetrode/optrode invivo recording in freely behaving mice revealed that thereduction of norepinephrine and downregulation of alpha 1 receptor in the OFC reduced the numberandactivity of GABAergic neurons necessary for driving action behavior resulting in behavioral transition. These findings define a circuit governing behavioral switch in response to prolonged uncontrollability.

Simulations approaching data: cortical slow waves in inferred models of the whole hemisphere of mouse

The development of novel techniques to record wide-field brain activity enables estimation of data-driven models from thousands of recording channels and hence across large regions of cortex. These in turn improve our understanding of the modulation of brain states and the richness of traveling waves dynamics. Here, we infer data-driven models from high-resolution in-vivo recordings of mouse brain obtained from wide-field calcium imaging. We then assimilate experimental and simulated data through the characterization of the spatio-temporal features of cortical waves in experimental recordings. Inference is built in two steps: an inner loop that optimizes a mean-field model by likelihood maximization, and an outer loop that optimizes a periodic neuro-modulation via direct comparison of observables that characterize cortical slow waves. The model reproduces most of the features of the non-stationary and non-linear dynamics present in the high-resolution in-vivo recordings of the mouse brain. The proposed approach offers new methods of characterizing and understanding cortical waves for experimental and computational neuroscientists.

Asymmetric mechanotransduction by hair cells of the zebrafish lateral line

In the lateral line system, water motion is detected by neuromast organs, fundamental units that are arrayed on a fish's surface. Each neuromast contains hair cells, specialized mechanoreceptors that convert mechanical stimuli, in the form of water movement, into electrical signals. The orientation of hair cells' mechanosensitive structures ensures that the opening of mechanically gated channels is maximal when deflected in a single direction. In each neuromast organ, hair cells have two opposing orientations, enabling bi-directional detection of water movement. Interestingly, Tmc2b and Tmc2a proteins, which constitute the mechanotransduction channels in neuromasts, distribute asymmetrically so that Tmc2a is expressed in hair cells of only one orientation. Here, using both invivo recording of extracellular potentials and calcium imaging of neuromasts, we demonstrate that hair cells of one orientation have larger mechanosensitive responses. The associated afferent neuron processes that innervate neuromast hair cells faithfully preserve this functional difference. Moreover, Emx2, a transcription factor required for the formation of hair cells with opposing orientations, is necessary to establish this functional asymmetry within neuromasts. Remarkably, loss of Tmc2a does not impact hair cell orientation but abolishes the functional asymmetry as measured by recording extracellular potentials and calcium imaging. Overall, our work indicates that oppositely oriented hair cells within a neuromast employ different proteins to alter mechanotransduction to sense the direction of water motion.

Recording electrical activity from the brain of behaving octopus

Octopuses, which are among the most intelligent invertebrates,1,2,3,4 have no skeleton and eight flexible arms whose sensory and motor activities are at once autonomous and coordinated by a complex central nervous system.5,6,7,8 The octopus brain contains a very large number of neurons, organized into numerous distinct lobes, the functions of which have been proposed based largely on the results of lesioning experiments.9,10,11,12,13 In other species, linking brain activity to behavior is done by implanting electrodes and directly correlating electrical activity with observed animal behavior. However, because the octopus lacks any hard structure to which recording equipment can be anchored, and because it uses its eight flexible arms to remove any foreign object attached to the outside of its body, invivo recording of electrical activity from untethered, behaving octopuses has thus far not been possible. Here, we describe a novel technique for inserting a portable data logger into the octopus and implanting electrodes into the vertical lobe system, such that brain activity can be recorded for up to 12h from unanesthetized, untethered octopuses and can be synchronized with simultaneous video recordings of behavior. In the brain activity, we identified several distinct patterns that appeared consistently in all animals. While some resemble activity patterns in mammalian neural tissue, others, such as episodes of 2Hz, large amplitude oscillations, have not been reported. By providing an experimental platform for recording brain activity in behaving octopuses, our study is a critical step toward understanding how the brain controls behavior in these remarkable animals.

Sensory regulation of absence seizures in a mouse model of Gnb1 encephalopathy

Absence seizures, manifested by spike-wave discharges (SWD) in the electroencephalogram, display synchronous reciprocal excitation between the neocortex and thalamus. Recent studies have revealed that inhibitory neurons in the reticular thalamic (RT) nucleus and excitatory thalamocortical (TC) neurons are two subcortical players in generating SWD. However, the signals that drive SWD-related activity remain elusive. Here, we show that SWD predominately occurs during wakefulness in several mouse models of absence epilepsy. In more focused studies of Gnb1 mutant mice, we found that sensory input regulates SWD. Using invivo recording, we demonstrate that TC cells are activated prior to the onset of SWD and then inhibited during SWD. On the contrary, RT cells are slightly inhibited prior to SWD, but are strongly activated during SWD. Furthermore, chemogenetic activation of TC cells leads to the enhancement of SWD. Together, our results indicate that sensory input can regulate SWD by activating the thalamocortical pathway.

VMHvllCckar cells dynamically control female sexual behaviors over the reproductive cycle

Sexual behavior is fundamental for the survival of mammalian species and thus supported by dedicated neural substrates. The ventrolateral part of ventromedial hypothalamus (VMHvl) is an essential locus for controlling female sexual behaviors, but recent studies revealed the molecular complexity and functional heterogeneity of VMHvl cells. Here, we identify the cholecystokinin A receptor (Cckar)-expressing cells in the lateral VMHvl (VMHvllCckar) as the key controllers of female sexual behaviors. The inactivation of VMHvllCckar cells in female mice diminishes their interest in males and sexual receptivity, whereas activating these cells has the opposite effects. Female sexual behaviors vary drastically over the reproductive cycle. Invivo recordings reveal reproductive-state-dependent changes in VMHvllCckarcell spontaneous activity and responsivity, with the highest activity occurring during estrus. These invivo response changes coincide with robust alternation in VMHvllCckar cell excitability and synaptic inputs. Altogether, VMHvllCckar cells represent a key neural population dynamically controlling female sexual behaviors over the reproductive cycle.

A Comparison of Delay-and-Add and Maximum Likelihood Estimation for Velocity-Selective Recording Using Multi-Electrode Cuffs.

Extracting information from the peripheral nervous system with implantable devices remains a significant challenge that limits the advancement of closed-loop neural prostheses. Linear electrode arrays can record neural signals with both temporal and spatial selectivity, and velocity selective recording using the delay-and-add algorithm can enable classification based on fibre type. The maximum likelihood estimation method also measures velocity and is frequently used in electromyography but has never been applied to electroneurography. Therefore, this study compares the two algorithms using in-vivo recordings of electrically evoked compound action potentials from the ulnar nerve of a pig. The performance of these algorithms was assessed using the velocity quality factor (Q-factor), computational time and the influence of the number of channels. The results show that the performance of both algorithms is significantly influenced by the number of channels in the recording array, with accuracies ranging from 77% with only two channels to 98% for 11 channels. Both algorithms were comparable in accuracy and Q-factor for all channels, with the delay-and-add having a slight advantage in the Q-factor.

Adaptation of the Two-CAP Method for Conduction Velocity Distribution Estimation in Multi-Channel Recordings.

Closed-loop neural interfaces capable of both stimulating and recording from peripheral nerves have the potential to enhance the long-term efficacy of neural implants. One challenge associated with closed loop interfaces is the accurate estimation of the distribution of active fibre conduction velocities (DCV) when recording the immediate effect of stimulation. DCV estimation has been performed in monopolar surface recordings using the Two-CAP method. This work extends the Two-CAP method and demonstrates its application to bipolar in-vivo recordings made with multiple-electrode arrays. A sensitivity analysis was conducted using simulated data with ground truth to ascertain the stability and limits of the algorithm before experimental data was examined. The sensitivity analysis highlighted that recording distance shows a considerable impact on the performance of this extended Two-CAP method, as well as the velocity interval chosen when creating the model. The in-vivo data was also compared against an equivalent simulated model, and a relatively low mean squared error was obtained when comparing the two distributions.

Delivery fidelity of the REACT (REtirement in ACTion) physical activity and behaviour maintenance intervention for community dwelling older people with mobility limitations

BackgroundFidelity assessment of behaviour change interventions is vital to understanding trial outcomes. This study assesses the delivery fidelity of behaviour change techniques used in the Retirement in ACTion (REACT) randomised controlled trial. REACT is a community-based physical activity (PA) and behaviour maintenance intervention to prevent decline of physical functioning in older adults (≥ 65 years) at high risk of mobility-related disability in the UK.MethodsThe delivery fidelity of intervention behaviour change techniques and delivery processes were assessed using multi-observer coding of purposively sampled in-vivo audio recordings (n = 25) of health behaviour maintenance sessions over 12-months. Delivery fidelity was scored using a modified Dreyfus scale (scores 0–5) to assess competence and completeness of delivery for each technique and delivery process. “Competent delivery” was defined as a score of 3 points or more for each item. Examples of competent intervention delivery were identified to inform recommendations for future programme delivery and training.ResultsThe mean intervention fidelity score was 2.5 (SD 0.45) with delivery fidelity varying between techniques/processes and intervention groups. Person-centred delivery, Facilitating Enjoyment and Promoting Autonomy were delivered competently (scoring 3.0 or more). There was scope for improvement (score 2.0—2.9) in Monitoring Progress (Acknowledging and Reviewing), Self-Monitoring, Monitoring Progress (Eliciting Benefits of Physical Activity), Goal Setting and Action Planning, Modelling, Supporting Self-Efficacy for Physical Activity and Supporting Relatedness. Managing Setbacks and Problem Solving was delivered with low fidelity. Numerous examples of both good and sub-optimal practice were identified.ConclusionsThis study highlights successes and improvements needed to enhance delivery fidelity in future implementation of the behavioural maintenance programme of the REACT intervention. Future training of REACT session leaders and assessment of delivery fidelity needs to focus on the delivery of Goal setting and Action Planning, Modelling, Supporting Relatedness, Supporting Self-Efficacy for Physical Activity, and Managing Setbacks/ Problem Solving.

Hierarchical data visualization of experimental erythrocyte aggregation employing cross correlation and optical flow applications

Appraisal of microvascular erythrocyte velocity as well as aggregation are critical features of hemorheological assessment. Examination of erythrocyte velocity-aggregate characteristics is critical in assessing disorders associated with coagulopathy. Microvascular erythrocyte velocity can be assessed using various methodologic approaches; however, the shared assessment of erythrocyte velocity and aggregation has not been well described. The purpose of this study therefore is to examine three independent erythrocyte assessment strategies with and without experimentally induced aggregation in order to elucidate appropriate analytic strategy for combined velocity/aggregation assessment applicable to in-vivo capillaroscopy. We employed a hierarchical microfluidic model combined with Bland-Altman analysis to examine agreement between three methodologies to assess erythrocyte velocity appropriate for interpretation of cinematography of in-vivo microvascular hemorheology. We utilized optical and manual techniques as well as a technique which we term transversal temporal cross-correlation (TTC) to observe and measure both erythrocyte velocity and aggregation. In general, optical, manual and TTC agree in estimation of velocity at relatively low flow rate, however with an increase in infusion rate the optical flow method yielded the velocity estimates that were lower than the TTC and manual velocity estimates. We suggest that this difference was due to the fact that slower moving particles close to the channel wall were better illuminated than faster particles deeper in the channel which affected the optical flow analysis. Combined velocity/aggregation appraisal using TTC provides an efficient approach for estimating erythrocyte aggregation appropriate for in-vivo applications. We demonstrated that the optical flow and TTC analyses can be used to estimate erythrocyte velocity and aggregation both in ex-vivo microfluidics laboratory experiments as well as in-vivo recordings. The simplicity of TTC method may be advantageous for developing velocity estimate methods to be used in the clinic. The trade-off is that TTC estimation cannot capture features of the flow based on optical flow analysis of individually tracked particles.

Spectrum dependency to rate and spike timing in neuronal spike trains

BackgroundSpike trains are series of interspike intervals in a specific order that can be characterized by their probability distributions and order in time which refer to the concepts of rate and spike timing features. Periodic structure in the spike train can be reflected in oscillatory activities. Thus, there is a direct link between oscillator activities and the spike train. The proposed methods are to investigate the dependency of emerging oscillatory activities to the rate and the spike timing features. MethodFirst, the circular statistics methods were compared to Fast Fourier Transform for best estimation of spectra. Second, two statistical tests were introduced to help make decisions regarding the dependency of spectrum, or individual frequencies, onto rate and spike timing. Third, the methodology is applied to in-vivo recordings of basal ganglia neurons in mouse, primate, and human. Finally, this novel framework is shown to allow the investigation of subsets of spikes contributing to individual oscillators. ResultsUse of circular statistical methods, in comparison to FFT, minimizes spectral leakage. Using virtual spike trains, the Rate versus Timing Dependency Spectrum Test (or RTDs-Test) permits identifying spectral spike trains solely dependent on the rate feature from those that are also dependent on the spike timing feature. Similarly, the Rate versus Timing Dependency Frequency Test (or RTDf-Test), allows to identify individual oscillators with partial dependency on spike timing. Dependency on spike timing was found for all in-vivo recordings but only in few frequencies. The mapping in frequency and time of dependencies showed a dynamical process that may be organizing the basal ganglia function. ConclusionsThe methodology may improve our understanding of the emergence of oscillatory activities and, possibly, the relation between oscillatory activities and circuitry functions.

Long-term in-vivo recording performance of flexible penetrating microelectrode arrays

Objective. Neural interfaces are an essential tool to enable the human body to directly communicate with machines such as computers or prosthetic robotic arms. Since invasive electrodes can be located closer to target neurons, they have advantages such as precision in stimulation and high signal-to-noise ratio (SNR) in recording, while they often exhibit unstable performance in long-term in-vivo implantation because of the tissue damage caused by the electrodes insertion. In the present study, we investigated the electrical functionality of flexible penetrating microelectrode arrays (FPMAs) up to 3 months in in-vivo conditions. Approach. The in-vivo experiment was performed by implanting FPMAs in five rats. The in-vivo impedance as well as the action potential (AP) amplitude and SNR were analyzed over weeks. Additionally, APs were tracked over time to investigate the possibility of single neuron recording. Main results. It was observed that the FPMAs exhibited dramatic increases in impedance for the first 4 weeks after implantation, accompanied by decreases in AP amplitude. However, the increase/decrease in AP amplitude was always accompanied by the increase/decrease in background noise, resulting in quite consistently maintained SNRs. After 4 weeks of implantation, we observed two distinctive issues regarding long-term implantation, each caused by chronic tissue responses or by the delamination of insulation layer. The results demonstrate that the FPMAs successfully recorded neuronal signals up to 12 weeks, with very stably maintained SNRs, reduced by only 16.1% on average compared to the first recordings, although biological tissue reactions or physical degradation of the FPMA were present. Significance. The fabricated FPMAs successfully recorded intracortical signals for 3 months. The SNR was maintained up to 3 months and the chronic function of FPMA was comparable with other silicon based implantable electrodes.

Altered dopaminergic firing pattern and novelty response underlie ADHD-like behavior of SorCS2-deficient mice

Attention deficit hyperactivity disorder (ADHD) is the most frequently diagnosed neurodevelopmental disorder worldwide. Affected individuals present with hyperactivity, inattention, and cognitive deficits and display a characteristic paradoxical response to drugs affecting the dopaminergic system. However, the underlying pathophysiology of ADHD and how this relates to dopaminergic transmission remains to be fully understood. Sorcs2−/− mice uniquely recapitulate symptoms reminiscent of ADHD in humans. Here, we show that lack of SorCS2 in mice results in lower sucrose intake, indicating general reward deficits. Using in-vivo recordings, we further find that dopaminergic transmission in the ventral tegmental area (VTA) is shifted towards a more regular firing pattern with marked reductions in the relative occurrence of irregular firing in Sorcs2−/− mice. This was paralleled by abnormal acute behavioral responses to dopamine receptor agonists, suggesting fundamental differences in dopaminergic circuits and indicating a perturbation in the balance between the activities of the postsynaptic dopamine receptor DRD1 and the presynaptic inhibitory autoreceptor DRD2. Interestingly, the hyperactivity and drug response of Sorcs2−/− mice were markedly affected by novelty. Taken together, our findings show how loss of a candidate ADHD-risk gene has marked effects on dopaminergic circuit function and the behavioral response to the environment.

Array processing of neural signals recorded from the peripheral nervous system for the classification of action potentials

BackgroundRecording from the peripheral nervous system is key in the development of implantable neural interfaces. Despite a long history of using implantable electrodes for neuro-stimulation, it is difficult to make recordings from the nerves as signal amplitudes are often too small to be detected. Methods exist that are suitable for recording evoked potentials, but these require artificial stimulation of the nerve and thus have limited use in implanted neural interfaces. New methodIn order to address these issues new methods are developed to analyse spontaneously occurring action potentials by extending an approach called velocity selective recording, which uses longitudinally spaced electrodes to record action potentials as they propagate. The new methods using image processing techniques to automatically identify and classify action potentials without any prior knowledge of their morphology. ResultsSimulations are developed to test the methods, and a detailed experimental validation is performed using in-vivo recordings from the L5 dorsal rootlet of rat. Results show that this new approach can discriminate action potentials from both simulated and real recordings and the experimental validation demonstrates an ability to detect dermal stimulation by changes in the firing patterns of different axons. Comparison to existing methodsThis framework, unlike existing methods, is intrinsically suitable for recordings of spontaneous neural activity. Further it improves upon both the computational complexity and the overall performance of existing methods. ConclusionIt is possible to perform on-line discrimination and identification of action potentials without any prior knowledge of their morphology using new image processing inspired methods.