A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo

Multi-shank 1024 channels active SiNAPS probe for large multi-regional topographical electrophysiological mapping of neural dynamics

Implantable active dense CMOS neural probes unlock the possibility of spatiotemporally resolving the activity of hundreds of single neurons in multiple brain circuits to investigate brain dynamics. Mapping neural dynamics in brain circuits with anatomical structures spanning several millimeters, however, remains challenging. Here, we demonstrate the first CMOS neural probe for mapping intracortical neural dynamics (both LFPs and spikes) in awake, behaving mice from an area >4 mm2. By taking advantage of the modularity of our SiNAPS technology, we realized an eight shanks probe with 1024 electrode channels arranged on each shank in regular arrays with an electrode pitch <30 μm. Low-noise recordings from all electrodes at 20 kHz/channel demonstrate a field of view spanning the 2D lattice of the entire mice hippocampal circuit, together with cortical and thalamic regions. This arrangement allows combining large population unit recording across distributed networks with precise intra- and interlaminar/nuclear mapping of the oscillatory dynamics.

A fully automatic multichannel neural spike sorting algorithm with spike reduction and positional feature

Objective: The sorting of neural spike data recorded by multichannel and high channel neural probes such as Neuropixels, especially in real-time, remains a significant technical challenge. Most neural spike sorting algorithms focus on sorting neural spikes post-hoc for high sorting accuracy-but reducing the processing delay for fast sorting, potentially even live sorting, is generally not possible with these algorithms.Approach: Here we report our Graph nEtwork Multichannel sorting (GEMsort) algorithm, which is largely based on graph network, to allow rapid neural spike sorting for multiple neural recording channels. This was accomplished by two innovations: In GEMsort, duplicated neural spikes recorded from multiple channels were eliminated from duplicate channels by only selecting the highest amplitude neural spike in any channel for subsequent processing. In addition, the channel from which the representative neural spike was recorded was used as an additional feature to differentiate between neural spikes recorded from different neurons having similar temporal features.Main results: Synthetic and experimentally recorded multichannel neural recordings were used to evaluate the sorting performance of GEMsort. The sorting results of GEMsort were also compared with two other state-of-the-art sorting algorithms (Kilosort and Mountainsort) in sorting time and sorting agreements.Significance: GEMsort allows rapidly sort neural spikes and is highly suitable to be implemented with digital circuitry for high processing speed and channel scalability.

Analgesic effect of Botulinum toxin in neuropathic pain is sodium channel independent

Botulinum neurotoxin type A BoNT/A is used off-label as a third line therapy for neuropathic pain. However, the mechanism of action remains unclear. In recent years, the role of voltage-gated sodium channels (Nav) in neuropathic pain became evident and it was suggested that block of sodium channels by BoNT/A would contribute to its analgesic effect. We assessed sodium channel function in the presence of BoNT/A in heterologously expressed Nav1.7, Nav1.3, and the neuronal cell line ND7/23 by high throughput automated and manual patch-clamp. We used both the full protein and the isolated catalytic light chain LC/A for acute or long-term extracellular or intracellular exposure. To assess the toxin's effect in a human cellular system, we differentiated induced pluripotent stem cells (iPSC) into sensory neurons from a healthy control and a patient suffering from a hereditary neuropathic pain syndrome (inherited erythromelalgia) carrying the Nav1.7/p.Q875E-mutation and carried out multielectrode-array measurements. Both BoNT/A and the isolated catalytic light chain LC/A showed limited effects in heterologous expression systems and the neuronal cell line ND7/23. Spontaneous activity in iPSC derived sensory neurons remained unaltered upon BoNT/A exposure both in neurons from the healthy control and the mutation carrying patient. BoNT/A may not specifically be beneficial in pain syndromes linked to sodium channel variants. The favorable effects of BoNT/A in neuropathic pain are likely based on mechanisms other than sodium channel blockage and new approaches to understand BoNT/A's therapeutic effects are necessary.

Altered Functional Responses of the Retina in B6 Albino Tyrc/c Mice

Purpose

Mammals with albinism present low visual discrimination ability and different proportions of certain retinal cell subtypes. As the spatial resolution of the retina depends on the visual field sampling by retinal ganglion cells (RGCs) based on the convergence of upstream cell inputs, it could be affected in albinism and thus modify the RGC function.

Methods

We used the Tyrc/c line, a mouse model of oculocutaneous albinism type 1 (OCA1), carrying a tyrosinase mutation, and previously characterized by a total absence of pigment and severe visual deficits. To assess their retinal function, we recorded the light responses of hundreds of RGCs ex vivo using multi-electrode array (MEA). We estimated the receptive field (RF)-center diameter of Tyr+/c and Tyrc/c RGCs using a checkerboard stimulation before simultaneously stimulating the center and surround of RGC RFs with full-field flashes.

Results

Following checkerboard stimulation, the RF-center diameters of RGCs were indistinguishable between Tyrc/c and Tyr+/c retinas. Nevertheless, RGCs from Tyrc/c retinas presented more OFF responses to full-field flashes than RGCs from Tyr+/c retinas. Unlike Tyr+/c retinas, very few OFF-center RGCs switched polarity to ON or ON-OFF responses after full-field flashes in Tyrc/c retinas, suggesting a different surround suppression in these retinas.

Conclusions

The retinal output signal is affected in Tyrc/c retinas, despite intact RF-center diameters of their RGCs. Adaptive mechanisms during development are probably responsible for this change in RGC responses, related to the absence of ocular pigments.

Neural manifolds in V1 change with top-down signals from V4 targeting the foveal region

High-dimensional brain activity is often organized into lower-dimensional neural manifolds. However, the neural manifolds of the visual cortex remain understudied. Here, we study large-scale multi-electrode electrophysiological recordings of macaque (Macaca mulatta) areas V1, V4, and DP with a high spatiotemporal resolution. We find that the population activity of V1 contains two separate neural manifolds, which correlate strongly with eye closure (eyes open/closed) and have distinct dimensionalities. Moreover, we find strong top-down signals from V4 to V1, particularly to the foveal region of V1, which are significantly stronger during the eyes-open periods. Finally, in silico simulations of a balanced spiking neuron network qualitatively reproduce the experimental findings. Taken together, our analyses and simulations suggest that top-down signals modulate the population activity of V1. We postulate that the top-down modulation during the eyes-open periods prepares V1 for fast and efficient visual responses, resulting in a type of visual stand-by state.

Temporal pattern recognition in retinal ganglion cells is mediated by dynamical inhibitory synapses

A fundamental task for the brain is to generate predictions of future sensory inputs, and signal errors in these predictions. Many neurons have been shown to signal omitted stimuli during periodic stimulation, even in the retina. However, the mechanisms of this error signaling are unclear. Here we show that depressing inhibitory synapses shape the timing of the response to an omitted stimulus in the retina. While ganglion cells, the retinal output, responded to an omitted flash with a constant latency over many frequencies of the flash sequence, we found that this was not the case once inhibition was blocked. We built a simple circuit model and showed that depressing inhibitory synapses were a necessary component to reproduce our experimental findings. A new prediction of our model is that the accuracy of the constant latency requires a sufficient amount of flashes in the stimulus, which we could confirm experimentally. Depressing inhibitory synapses could thus be a key component to generate the predictive responses observed in the retina, and potentially in many brain areas.

Natural phasic inhibition of dopamine neurons signals cognitive rigidity

When animals unexpectedly fail, their dopamine neurons undergo phasic inhibition that canonically drives extinction learning-a cognitive-flexibility mechanism for discarding outdated strategies. However, the existing evidence equates natural and artificial phasic inhibition, despite their spatiotemporal differences. Addressing this gap, we targeted a GABAA-receptor antagonist precisely to dopamine neurons, yielding three unexpected findings. First, this intervention blocked natural phasic inhibition selectively, leaving tonic activity unaffected. Second, blocking natural phasic inhibition accelerated extinction learning-opposite to canonical mechanisms. Third, our approach selectively benefitted perseverative mice, restoring rapid extinction without affecting new reward learning. Our findings reveal that extinction learning is rapid by default and slowed by natural phasic inhibition-challenging foundational learning theories, while delineating a synaptic mechanism and therapeutic target for cognitive rigidity.

Microstimulation reveals anesthetic state-dependent effective connectivity of neurons in cerebral cortex

Introduction

Complex neuronal interactions underlie cortical information processing that can be compromised in altered states of consciousness. Here intracortical microstimulation was applied to investigate anesthetic state-dependent effective connectivity of neurons in rat visual cortex in vivo.

Methods

Extracellular activity was recorded at 32 sites in layers 5/6 while stimulating with charge-balanced discrete pulses at each electrode in random order. The same stimulation pattern was applied at three levels of anesthesia with desflurane and in wakefulness. Spikes were sorted and classified by their waveform features as putative excitatory and inhibitory neurons. Network motifs were identified in graphs of effective connectivity constructed from monosynaptic cross-correlograms.

Results

Microstimulation caused early (<10 ms) increase followed by prolonged (11-100 ms) decrease in spiking of all neurons throughout the electrode array. The early response of excitatory but not inhibitory neurons decayed rapidly with distance from the stimulation site over 1 mm. Effective connectivity of neurons with significant stimulus response was dense in wakefulness and sparse under anesthesia. The number of network motifs, especially those of higher order, increased rapidly as the anesthesia was withdrawn indicating a substantial increase in network connectivity as the animals woke up.

Conclusion

The results illuminate the impact of anesthesia on functional integrity of local cortical circuits affecting the state of consciousness.

Sleep loss diminishes hippocampal reactivation and replay

Memories benefit from sleep1, and the reactivation and replay of waking experiences during hippocampal sharp-wave ripples (SWRs) are considered to be crucial for this process2. However, little is known about how these patterns are impacted by sleep loss. Here we recorded CA1 neuronal activity over 12 h in rats across maze exploration, sleep and sleep deprivation, followed by recovery sleep. We found that SWRs showed sustained or higher rates during sleep deprivation but with lower power and higher frequency ripples. Pyramidal cells exhibited sustained firing during sleep deprivation and reduced firing during sleep, yet their firing rates were comparable during SWRs regardless of sleep state. Despite the robust firing and abundance of SWRs during sleep deprivation, we found that the reactivation and replay of neuronal firing patterns was diminished during these periods and, in some cases, completely abolished compared to ad libitum sleep. Reactivation partially rebounded after recovery sleep but failed to reach the levels found in natural sleep. These results delineate the adverse consequences of sleep loss on hippocampal function at the network level and reveal a dissociation between the many SWRs elicited during sleep deprivation and the few reactivations and replays that occur during these events.

In vivo magnetic recording of single-neuron action potentials Abbreviated title: In vivo magnetic single-neuron action potentials

Measuring fast neuronal signals is the domain of electrophysiology and magnetophysiology. While electrophysiology is easier to perform, magnetophysiology avoids tissue-based distortions and measures a signal with directional information. At the macroscale, magnetoencephalography (MEG) is established, and at the mesoscale, visually evoked magnetic fields have been reported. At the microscale however, while benefits of recording magnetic counterparts of electric spikes would be numerous, they are also highly challenging in vivo. Here, we combine magnetic and electric recordings of neuronal action potentials in anesthetized rats using miniaturized giant magneto-resistance (GMR) sensors. We reveal the magnetic signature of action potentials of well-isolated single units. The recorded magnetic signals showed a distinct waveform and considerable signal strength. This demonstration of in vivo magnetic action potentials opens a wide field of possibilities to profit from the combined power of magnetic and electric recordings and thus to significantly advance the understanding of neuronal circuits.

Retuning of hippocampal representations during sleep

Hippocampal representations that underlie spatial memory undergo continuous refinement following formation1. Here, to track the spatial tuning of neurons dynamically during offline states, we used a new Bayesian learning approach based on the spike-triggered average decoded position in ensemble recordings from freely moving rats. Measuring these tunings, we found spatial representations within hippocampal sharp-wave ripples that were stable for hours during sleep and were strongly aligned with place fields initially observed during maze exploration. These representations were explained by a combination of factors that included preconfigured structure before maze exposure and representations that emerged during θ-oscillations and awake sharp-wave ripples while on the maze, revealing the contribution of these events in forming ensembles. Strikingly, the ripple representations during sleep predicted the future place fields of neurons during re-exposure to the maze, even when those fields deviated from previous place preferences. By contrast, we observed tunings with poor alignment to maze place fields during sleep and rest before maze exposure and in the later stages of sleep. In sum, the new decoding approach allowed us to infer and characterize the stability and retuning of place fields during offline periods, revealing the rapid emergence of representations following new exploration and the role of sleep in the representational dynamics of the hippocampus.

Microstimulation reveals anesthetic state-dependent effective connectivity of neurons in cerebral cortex

Complex neuronal interactions underlie cortical information processing that can be compromised in altered states of consciousness. Here intracortical microstimulation was applied to investigate the state-dependent effective connectivity of neurons in rat visual cortex in vivo. Extracellular activity was recorded at 32 sites in layers 5/6 while stimulating with charge-balanced discrete pulses at each electrode in random order. The same stimulation pattern was applied at three levels of anesthesia with desflurane and in wakefulness. Spikes were sorted and classified by their waveform features as putative excitatory and inhibitory neurons. Microstimulation caused early (<10ms) increase followed by prolonged (11-100ms) decrease in spiking of all neurons throughout the electrode array. The early response of excitatory but not inhibitory neurons decayed rapidly with distance from the stimulation site over 1mm. Effective connectivity of neurons with significant stimulus response was dense in wakefulness and sparse under anesthesia. Network motifs were identified in graphs of effective connectivity constructed from monosynaptic cross-correlograms. The number of motifs, especially those of higher order, increased rapidly as the anesthesia was withdrawn indicating a substantial increase in network connectivity as the animals woke up. The results illuminate the impact of anesthesia on functional integrity of local circuits affecting the state of consciousness.

Trigeminal nerve direct current stimulation causes sustained increase in neural activity in the rat hippocampus

BACKGROUND

Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation method that can modulate many brain functions including learning and memory. Recent evidence suggests that tDCS memory effects may be caused by co-stimulation of scalp nerves such as the trigeminal nerve (TN), and not the electric field in the brain. The TN gives input to brainstem nuclei, including the locus coeruleus that controls noradrenaline release across brain regions, including hippocampus. However, the effects of TN direct current stimulation (TN-DCS) are currently not well understood.

HYPOTHESIS

In this study we tested the hypothesis that stimulation of the trigeminal nerve with direct current manipulates hippocampal activity via an LC pathway.

METHODS

We recorded neural activity in rat hippocampus using multichannel silicon probes. We applied 3 min of 0.25 mA or 1 mA TN-DCS, monitored hippocampal activity for up to 1 h and calculated spikes-rate and spike-field coherence metrics. Subcutaneous injections of xylocaine were used to block TN, while intraperitoneal and intracerebral injection of clonidine were used to block the LC pathway.

RESULTS

We found that 1 mA TN-DCS caused a significant increase in hippocampal spike-rate lasting 45 min in addition to significant changes in spike-field coherence, while 0.25 mA TN-DCS did not. TN blockage prevented spike-rate increases, confirming effects were not caused by the electric field in the brain. When 1 mA TN-DCS was delivered during clonidine blockage no increase in spike-rate was observed, suggesting an important role for the LC-noradrenergic pathway.

CONCLUSION

These results support our hypothesis and provide a neural basis to understand the tDCS TN co-stimulation mechanism. TN-DCS emerges as an important tool to potentially modulate learning and memory.

Spike sorting with Kilosort4

Spike sorting is the computational process of extracting the firing times of single neurons from recordings of local electrical fields. This is an important but hard problem in neuroscience, made complicated by the nonstationarity of the recordings and the dense overlap in electrical fields between nearby neurons. To address the spike-sorting problem, we have been openly developing the Kilosort framework. Here we describe the various algorithmic steps introduced in different versions of Kilosort. We also report the development of Kilosort4, a version with substantially improved performance due to clustering algorithms inspired by graph-based approaches. To test the performance of Kilosort, we developed a realistic simulation framework that uses densely sampled electrical fields from real experiments to generate nonstationary spike waveforms and realistic noise. We found that nearly all versions of Kilosort outperformed other algorithms on a variety of simulated conditions and that Kilosort4 performed best in all cases, correctly identifying even neurons with low amplitudes and small spatial extents in high drift conditions.

Modulation of neural spiking in motor cortex-cerebellar networks during sleep spindles

Sleep spindles appear to play an important role in learning new motor skills. Motor skill learning engages several regions in the brain with two important areas being the motor cortex (M1) and the cerebellum. However, the neurophysiological processes in these areas during sleep, especially how spindle oscillations affect local and cross-region spiking, are not fully understood. We recorded activity from the M1 and cerebellar cortex in 8 rats during spontaneous activity to investigate how sleep spindles in these regions are related to local spiking as well as cross-region spiking. We found that M1 firing was significantly changed during both M1 and cerebellum spindles and this spiking occurred at a preferred phase of the spindle. On average, M1 and cerebellum neurons showed most spiking at the M1 or cerebellum spindle peaks. These neurons also developed a preferential phase-locking to local or cross-area spindles with the greatest phase-locking value at spindle peaks; however, this preferential phase-locking wasn't significant for cerebellar neurons when compared to cerebellum spindles. Additionally, we found the percentage of task-modulated cells in the M1 and cerebellum that fired with non-uniform spike-phase distribution during M1/ cerebellum spindle peaks were greater in the rats that learned a reach-to-grasp motor task robustly. Finally, we found that spindle-band LFP coherence (for M1 and cerebellum LFPs) showed a positive correlation with success rate in the motor task. These findings support the idea that sleep spindles in both the M1 and cerebellum recruit neurons that participate in the awake task to support motor memory consolidation.Significance Statement Neural processing during sleep spindles is linked to memory consolidation. However, little is known about sleep activity in the cerebellum and whether cerebellum spindles can affect spiking activity in local or distant areas. We report the effect of sleep spindles on neuron activity in the M1 and cerebellum-specifically their firing rate and phase-locking to spindle oscillations. Our results indicate that awake practice neuronal activity is tempered during local M1 and cerebellum spindles, and during cross-region spindles, which may support motor skill learning. We describe spiking dynamics in motor networks spindle oscillations that may aid in the learning of skills. Our results support the sleep reactivation hypothesis and suggest that awake M1 activity may be reactivated during cerebellum spindles.

Cortico-cerebellar coordination facilitates neuroprosthetic control

Temporally coordinated neural activity is central to nervous system function and purposeful behavior. Still, there is a paucity of evidence demonstrating how this coordinated activity within cortical and subcortical regions governs behavior. We investigated this between the primary motor (M1) and contralateral cerebellar cortex as rats learned a neuroprosthetic/brain-machine interface (BMI) task. In neuroprosthetic task, actuator movements are causally linked to M1 "direct" neurons that drive the decoder for successful task execution. However, it is unknown how task-related M1 activity interacts with the cerebellum. We observed a notable 3 to 6 hertz coherence that emerged between these regions' local field potentials (LFPs) with learning that also modulated task-related spiking. We identified robust task-related indirect modulation in the cerebellum, which developed a preferential relationship with M1 task-related activity. Inhibiting cerebellar cortical and deep nuclei activity through optogenetics led to performance impairments in M1-driven neuroprosthetic control. Together, these results demonstrate that cerebellar influence is necessary for M1-driven neuroprosthetic control.

Effects of nitrous oxide and ketamine on electrophysiological and molecular responses in the prefrontal cortex of mice: A comparative study

Nitrous oxide (N2O; laughing gas) has recently reported to produce rapid antidepressant effects, but little is known about the underlying mechanisms. We performed transcriptomics, in situ hybridization, and electrophysiological studies to examine the potential shared signatures induced by 1 h inhalation of 50% N2O and a single subanesthetic dose of ketamine (10 mg/kg, i.p.) in the medial prefrontal cortex (mPFC) in adult mice. Both treatments similarly affected the transcription of several negative regulators of mitogen-activated protein kinases (MAPKs), namely, dual specificity phosphatases (DUSPs). The effects were primarily located in the pyramidal cells. Notably, the overall effects of N2O on mRNA expression were much more prominent and widespread compared to ketamine. Ketamine caused an elevation of the spiking frequency of putative pyramidal neurons and increased gamma activity (30-100 Hz) of cortical local field potentials. However, N2O produced no such effects. Spiking amplitudes and spike-to-local field potential phase locking of putative pyramidal neurons and interneurons in this brain area showed no uniform changes across treatments. Our findings suggest that N2O and subanesthetic-dose ketamine target MAPK pathway in the mPFC but produce varying acute electrophysiological responses.

Dissociable neuronal substrates of visual feature attention and working memory

Attention and working memory (WM) are distinct cognitive functions, yet given their close interactions, it is often assumed that they share the same neuronal mechanisms. We show that in macaques performing a WM-guided feature attention task, the activity of most neurons in areas middle temporal (MT), medial superior temporal (MST), lateral intraparietal (LIP), and posterior lateral prefrontal cortex (LPFC-p) displays attentional modulation or WM coding and not both. One area thought to play a role in both functions is LPFC-p. To test this, we optogenetically inactivated LPFC-p bilaterally during different task periods. Attention period inactivation reduced attentional modulation in LPFC-p, MST, and LIP neurons and impaired task performance. In contrast, WM period inactivation did not affect attentional modulation or performance and minimally affected WM coding. Our results suggest that feature attention and WM have dissociable neuronal substrates and that LPFC-p plays a critical role in feature attention, but not in WM.

Mind In Vitro Platforms: Versatile, Scalable, Robust, and Open Solutions to Interfacing with Living Neurons

Motivated by the unexplored potential of in vitro neural systems for computing and by the corresponding need of versatile, scalable interfaces for multimodal interaction, an accurate, modular, fully customizable, and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated is presented. This approach entails a reconfigurable platform that works across multiple industry standards and that enables a complete signal chain, from neural substrates sampled through micro-electrode arrays (MEAs) to data acquisition, downstream analysis, and cloud storage. Built-in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations, spatial topologies, and constitutive materials. Through a dedicated analysis and management software suite, the utility and robustness of this system are demonstrated across neural cultures and applications, including embryonic stem cell-derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging, and long-term recording. Overall, this technology, termed "mind in vitro" to underscore the computing inspiration, provides an end-to-end solution that can be widely deployed due to its affordable (>10× cost reduction) and open-source nature, catering to the expanding needs of both conventional and unconventional electrophysiology.

Inhibition of cannabinoid degradation enhances hippocampal contextual fear memory and exhibits anxiolytic effects

Recent studies have demonstrated the pivotal involvement of endocannabinoids in regulating learning and memory, but the conclusions obtained from different paradigms or contexts are somewhat controversial, and the underlying mechanisms remain largely elusive. Here, we show that JZL195, a dual inhibitor of fatty acid amide hydrolase and monoacylglycerol lipase, can enhance the performance of mice in a contextual fear conditioning task and increase the time spent in open arms in the elevated zero maze (EZM). Although the effect of JZL195 on fear memory could not be inhibited by antagonists of cannabinoid receptors, the effect on the EZM seems to be mediated by CB1R. Simultaneously, hippocampal neurons are hyperactive, and theta oscillation power is significantly increased during the critical period of memory consolidation upon treatment with JZL195. These results suggest the feasibility of targeting the endocannabinoid system for the treatment of various mental disorders.

Spike sorting in the presence of stimulation artifacts: a dynamical control systems approach

Objective. Bi-directional electronic neural interfaces, capable of both electrical recording and stimulation, communicate with the nervous system to permit precise calibration of electrical inputs by capturing the evoked neural responses. However, one significant challenge is that stimulation artifacts often mask the actual neural signals. To address this issue, we introduce a novel approach that employs dynamical control systems to detect and decipher electrically evoked neural activity despite the presence of electrical artifacts.Approach. Our proposed method leverages the unique spatiotemporal patterns of neural activity and electrical artifacts to distinguish and identify individual neural spikes. We designed distinctive dynamical models for both the stimulation artifact and each neuron observed during spontaneous neural activity. We can estimate which neurons were active by analyzing the recorded voltage responses across multiple electrodes post-stimulation. This technique also allows us to exclude signals from electrodes heavily affected by stimulation artifacts, such as the stimulating electrode itself, yet still accurately differentiate between evoked spikes and electrical artifacts.Main results. We applied our method to high-density multi-electrode recordings from the primate retina in anex vivosetup, using a grid of 512 electrodes. Through repeated electrical stimulations at varying amplitudes, we were able to construct activation curves for each neuron. The curves obtained with our method closely resembled those derived from manual spike sorting. Additionally, the stimulation thresholds we estimated strongly agreed with those determined through manual analysis, demonstrating high reliability (R2=0.951for human 1 andR2=0.944for human 2).Significance. Our method can effectively separate evoked neural spikes from stimulation artifacts by exploiting the distinct spatiotemporal propagation patterns captured by a dense, large-scale multi-electrode array. This technique holds promise for future applications in real-time closed-loop stimulation systems and for managing multi-channel stimulation strategies.

A Modular Implementation to Handle and Benchmark Drift Correction for High-Density Extracellular Recordings

High-density neural devices are now offering the possibility to record from neuronal populations in vivo at unprecedented scale. However, the mechanical drifts often observed in these recordings are currently a major issue for "spike sorting," an essential analysis step to identify the activity of single neurons from extracellular signals. Although several strategies have been proposed to compensate for such drifts, the lack of proper benchmarks makes it hard to assess the quality and effectiveness of motion correction. In this paper, we present a benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in the literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying a motion correction algorithm as a preprocessing step in the spike sorting pipeline. We show how important it is to properly estimate the positions of the neurons from extracellular traces in order to correctly estimate the probe motion, compare several interpolation procedures, and highlight what are the current limits for motion correction approaches.

An actor-model framework for visual sensory encoding

A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For example, in visual prostheses, one key aspect of artificial image encoding is to downsample images captured by a camera to a size matching the number of inputs and resolution of the prosthesis. Here, we show that downsampling an image using the inherent computation of the retinal network yields better performance compared to learning-free downsampling methods. We have validated a learning-based approach (actor-model framework) that exploits the signal transformation from photoreceptors to retinal ganglion cells measured in explanted mouse retinas. The actor-model framework generates downsampled images eliciting a neuronal response in-silico and ex-vivo with higher neuronal reliability than the one produced by a learning-free approach. During the learning process, the actor network learns to optimize contrast and the kernel's weights. This methodological approach might guide future artificial image encoding strategies for visual prostheses. Ultimately, this framework could be applicable for encoding strategies in other sensory prostheses such as cochlear or limb.

Grouping cells in primate visual cortex

Our perception of how objects are laid out in visual scenes is remarkably stable, despite rapid shifts in the patterns of light that fall on the retina with each saccade. One mechanism that may help establish perceptual stability is border ownership assignment. Studies in macaque area V2 have identified border ownership neurons that signal which side of a border belongs to a foreground surface. This signal persists for hundreds of milliseconds after border ownership has been rendered ambiguous by deleting the stimulus features that distinguish foreground from background. Remarkably, this signal survives eye movements: border ownership neurons also exhibit border ownership signals de novo when an eye movement places the newly ambiguous border within their receptive field. The grouping cell hypothesis proposes the existence of hypothetical grouping cells in a downstream brain area. These cells would compute persistent proto-object representations and therefore have the properties to endow cells in upstream brain areas with selectivity for border ownership. Such grouping cells have been predicted to show a centripetal and persistent pattern of preferred side of ownership for a border placed parallel to the perimeter of their classical receptive field, and such a centripetal ownership preference pattern should also occur de novo in these same cells if an ambiguous border lands in their receptive field after a saccade. It is unknown if grouping cells exist. Here we used laminar multielectrodes in area V4 - the main source of feedback to V2 - of behaving macaques to determine whether such grouping cells exist. Consistent with the model prediction we find a substantial population of neurons with these properties, in all laminar compartments, and they exhibit a response latency that is short enough to act as the source that endows neurons in V2 with selectivity for border ownership. While grouping cell activity provides information about the location of foreground surfaces, these neurons are, counterintuitively, not as strongly tuned for luminance contrast polarity, a feature of those surfaces, as are border ownership cells. Our data suggest a division of labor in which these newly discovered grouping cells provide spatiotemporal continuity of segmented surfaces whereas border ownership cells link this location information with surface features such as luminance contrast.

A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex

Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties. We record populations of single-unit neural activity in forelimb sensorimotor cortex during prey-capture and spontaneous behavior and use an encoding model incorporating kinematic trajectories and network features to predict single-unit activity during forelimb movements. The contribution of network features depends on structured connectivity within strongly connected functional groups. We identify a context-specific functional group that is highly tuned to kinematics and reorganizes its connectivity between spontaneous and prey-capture movements. In the remaining context-invariant group, interactions are comparatively stable across behaviors and units are less tuned to kinematics. This suggests different roles in producing natural forelimb movements and contextualizes single-unit tuning properties within population dynamics.

Optogenetic targeting of AII amacrine cells restores retinal computations performed by the inner retina

Most inherited retinal dystrophies display progressive photoreceptor cell degeneration leading to severe visual impairment. Optogenetic reactivation of inner retinal neurons is a promising avenue to restore vision in retinas having lost their photoreceptors. Expression of optogenetic proteins in surviving ganglion cells, the retinal output, allows them to take on the lost photoreceptive function. Nonetheless, this creates an exclusively ON retina by expression of depolarizing optogenetic proteins in all classes of ganglion cells, whereas a normal retina extracts several features from the visual scene, with different ganglion cells detecting light increase (ON) and light decrease (OFF). Refinement of this therapeutic strategy should thus aim at restoring these computations. Here we used a vector that targets gene expression to a specific interneuron of the retina called the AII amacrine cell. AII amacrine cells simultaneously activate the ON pathway and inhibit the OFF pathway. We show that the optogenetic stimulation of AII amacrine cells allows restoration of both ON and OFF responses in the retina, but also mediates other types of retinal processing such as sustained and transient responses. Targeting amacrine cells with optogenetics is thus a promising avenue to restore better retinal function and visual perception in patients suffering from retinal degeneration.

Trigeminal nerve direct current stimulation causes sustained increase in neural activity in the rat hippocampus

Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation method that can modulate many brain functions including learning and memory. Recent evidence suggests that tDCS memory effects may be caused by co-stimulation of scalp nerves such as the trigeminal nerve (TN), and not the electric field in the brain. The TN gives input to brainstem nuclei, including the locus coeruleus that controls noradrenaline release across brain regions, including hippocampus. However, the effects of TN direct current stimulation (TN-DCS) are currently not well understood. In this study we hypothesized that TN-DCS manipulates hippocampal activity via an LC-noradrenergic bottom-up pathway. We recorded neural activity in rat hippocampus using multichannel silicon probes. We applied 3 minutes of 0.25 mA or 1 mA TN-DCS, monitored hippocampal activity for up to 1 hour and calculated spikes-rate and spike-field coherence metrics. Subcutaneous injections of xylocaine were used to block TN and intraperitoneal injection of clonidine to block the LC pathway. We found that 1 mA TN-DCS caused a significant increase in hippocampal spike-rate lasting 45 minutes in addition to significant changes in spike-field coherence, while 0.25 mA TN-DCS did not. TN blockage prevented spike-rate increases, confirming effects were not caused by the electric field in the brain. When 1 mA TN-DCS was delivered during clonidine blockage no increase in spike-rate was observed, suggesting an important role for the LC-noradrenergic pathway. These results provide a neural basis to support a tDCS TN co-stimulation mechanism. TN-DCS emerges as an important tool to potentially modulate learning and memory.

Highlights

Trigeminal nerve direct current stimulation (TN-DCS) boosts hippocampal spike ratesTN-DCS alters spike-field coherence in theta and gamma bands across the hippocampus.Blockade experiments indicate that TN-DCS modulated hippocampal activity via the LC-noradrenergic pathway.TN-DCS emerges as a potential tool for memory manipulation.

Figure Graphic Abstract

Investigations on artificially extending the spectral range of natural vision

Organic semiconductors are being explored as retinal prosthetics with the prime attributes of bio-compatibility and conformability for seamless integration with the retina. These polymer-based artificial photoreceptor films are self-powered with light-induced signal strength sufficient to elicit neuronal firing events. The molecular aspect of these semiconductors provides wide spectral tunability. Here, we present results from a bulk heterostructure semiconductor blend with a wide spectral response range. This combination elicits clear spiking activity from a developing blind-chick embryonic retina in the subretinal configuration in response to white light. The response is largely triggered by the blue-green spectral regime rather than the red-NIR regime for the present polymer semiconductor layer attributes.

Hippocampal seizures differentially modulate locus coeruleus activity and result in consistent time-locked release of noradrenaline in rat hippocampus

The locus coeruleus (LC) is a small brainstem nucleus and is the sole source of noradrenaline in the neocortex, hippocampus and cerebellum. Noradrenaline is a powerful neuromodulator involved in the regulation of excitability and plasticity of large-scale brain networks. In this study, we performed a detailed assessment of the activity of locus coeruleus neurons and changes in noradrenergic transmission during acute hippocampal seizures evoked with perforant path stimulation, using state-of-the-art methodology. Action potentials of LC neurons, of which some were identified by means of optogenetics, were recorded in anesthetized rats using a multichannel high-density electrophysiology probe. The seizure-induced change in firing rate differed between LC neurons: 55% of neurons decreased in firing rate during seizures, while 28% increased their firing rate. Topographic analysis of multi-unit activity over the electrophysiology probe showed a topographic clustering of neurons that were inhibited or excited during seizures. Changes in hippocampal noradrenaline transmission during seizures were assessed using a fluorescent biosensor for noradrenaline, GRABNE2m, in combination with fiber photometry, in both anesthetized and awake rats. Although our neuronal recordings indicated both inhibition and excitation of LC neurons during seizures, a consistent release of noradrenaline was observed. Concentrations of noradrenaline increased at seizure onset and decreased during or shortly after the seizure. In conclusion, this study showed consistent but heterogeneous modulation of LC neurons and a consistent time-locked release of hippocampal noradrenaline during acute hippocampal seizures.

Recent strategies for neural dynamics observation at a larger scale and wider scope

The tremendous technical progress in neuroscience offers opportunities to observe a more minor or/and broader dynamic picture of the brain. Moreover, the large-scale neural activity of individual neurons enables the dissection of detailed mechanistic links between neural populations and behaviors. To measure neural activity in-vivo, multi-neuron recording, and neuroimaging techniques are employed and developed to acquire more neurons. The tools introduced concurrently recorded dozens to hundreds of neurons in the coordinated brain regions and elucidated the neuronal ensembles from a massive population perspective of diverse neurons at cellular resolution. In particular, the increasing spatiotemporal resolution of neuronal monitoring across the whole brain dramatically facilitates our understanding of additional nervous system functions in health and disease. Here, we will introduce state-of-the-art neuroscience tools involving large-scale neural population recording and the long-range connections spanning multiple brain regions. Their synergic effects provide to clarify the controversial circuitry underlying neuroscience. These challenging neural tools present a promising outlook for the fundamental dynamic interplay across levels of synaptic cellular, circuit organization, and brain-wide. Hence, more observations of neural dynamics will provide more clues to elucidate brain functions and push forward innovative technology at the intersection of neural engineering disciplines. We hope this review will provide insight into the use or development of recent neural techniques considering spatiotemporal scales of brain observation.

Awake responses suggest inefficient dense coding in the mouse retina

The structure and function of the vertebrate retina have been extensively studied across species with an isolated, ex vivo preparation. Retinal function in vivo, however, remains elusive, especially in awake animals. Here, we performed single-unit extracellular recordings in the optic tract of head-fixed mice to compare the output of awake, anesthetized, and ex vivo retinas. While the visual response properties were overall similar across conditions, we found that awake retinal output had in general (1) faster kinetics with less variability in the response latencies; (2) a larger dynamic range; and (3) higher firing activity, by ~20 Hz on average, for both baseline and visually evoked responses. Our modeling analyses further showed that such awake response patterns convey comparable total information but less efficiently, and allow for a linear population decoder to perform significantly better than the anesthetized or ex vivo responses. These results highlight distinct retinal behavior in awake states, in particular suggesting that the retina employs dense coding in vivo, rather than sparse efficient coding as has been often assumed from ex vivo studies.

Aversive stimulus-tuned responses in the CA1 of the dorsal hippocampus

Throughout life animals inevitably encounter unforeseen threatening events. Activity of principal cells in the hippocampus is tuned for locations and for salient stimuli in the animals' environment thus forming a map known to be pivotal for guiding behavior. Here, we explored if a code of threatening stimuli exists in the CA1 region of the dorsal hippocampus of mice by recording neuronal response to aversive stimuli delivered at changing locations. We have discovered a rapidly emerging, location independent response to innoxious aversive stimuli composed of the coordinated activation of subgroups of pyramidal cells and connected interneurons. Activated pyramidal cells had higher basal firing rate, more probably participated in ripples, targeted more interneurons than place cells and many of them lacked place fields. We also detected aversive stimulus-coupled assemblies dominated by the activated neurons. Notably, these assemblies could be observed even before the delivery of the first aversive event. Finally, we uncovered the systematic shift of the spatial code from the aversive to, surprisingly, the reward location during the fearful stimulus. Our results uncovered components of the dorsal CA1 circuit possibly key for re-sculpting the spatial map in response to abrupt aversive events.

Pynapple, a toolbox for data analysis in neuroscience

Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high-dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience.

Bumetanide induces post-traumatic microglia-interneuron contact to promote neurogenesis and recovery

Although the Na-K-Cl cotransporter (NKCC1) inhibitor bumetanide has prominent positive effects on the pathophysiology of many neurological disorders, the mechanism of action is obscure. Attention paid to elucidating the role of Nkcc1 has mainly been focused on neurons, but recent single cell mRNA sequencing analysis has demonstrated that the major cellular populations expressing NKCC1 in the cortex are non-neuronal. We used a combination of conditional transgenic animals, in vivo electrophysiology, two-photon imaging, cognitive behavioural tests and flow cytometry to investigate the role of Nkcc1 inhibition by bumetanide in a mouse model of controlled cortical impact (CCI). Here, we found that bumetanide rescues parvalbumin-positive interneurons by increasing interneuron-microglia contacts shortly after injury. The longitudinal phenotypic changes in microglia were significantly modified by bumetanide, including an increase in the expression of microglial-derived BDNF. These effects were accompanied by the prevention of CCI-induced decrease in hippocampal neurogenesis. Treatment with bumetanide during the first week post-CCI resulted in significant recovery of working and episodic memory as well as changes in theta band oscillations 1 month later. These results disclose a novel mechanism for the neuroprotective action of bumetanide mediated by an acceleration of microglial activation dynamics that leads to an increase in parvalbumin interneuron survival following CCI, possibly resulting from increased microglial BDNF expression and contact with interneurons. Salvage of interneurons may normalize ambient GABA, resulting in the preservation of adult neurogenesis processes as well as contributing to bumetanide-mediated improvement of cognitive performance.

Functional clustering of neuronal signals with FMM mixture models

The identification of unlabeled neuronal electric signals is one of the most challenging open problems in neuroscience, widely known as Spike Sorting. Motivated to solve this problem, we propose a model-based approach within the mixture modeling framework for clustering oscillatory functional data called MixFMM. The core of the approach is the FMM (Frequency Modulated Möbius) waves, which are non-linear parametric time functions, flexible enough to describe different oscillatory patterns and simple enough to be estimated efficiently. In particular, specific model parameters describe the phase, amplitude and shape of the waveforms. A mixture model is defined using FMM waves as basic functions and gaussian errors, and an EM algorithm is proposed for estimating the parameters. Spike Sorting (SS) has received considerable attention in the literature, and different functional clustering approaches have been considered. We have conducted a fair comparative analysis of the MixFMM with three competitors. Two of them are traditional methods in functional clustering and widely used in Spike Sorting. The third is an approach that has proven superior to many others solving Spike Sorting problems. The datasets used for validation include benchmarking simulated and real cases. The internal and external validation indexes confirm a better performance of the MixFMM on real data sets against the three competitors and an outstanding performance in simulated data against traditional approaches.

Fibroblast growth factor 9 (FGF9)-mediated neurodegeneration: Implications for progressive multiple sclerosis?

AIMS

Fibroblast growth factor (FGF) signalling is dysregulated in multiple sclerosis (MS) and other neurological and psychiatric conditions, but there is little or no consensus as to how individual FGF family members contribute to disease pathogenesis. Lesion development in MS is associated with increased expression of FGF1, FGF2 and FGF9, all of which modulate remyelination in a variety of experimental settings. However, FGF9 is also selectively upregulated in major depressive disorder (MDD), prompting us to speculate it may also have a direct effect on neuronal function and survival.

METHODS

Transcriptional profiling of myelinating cultures treated with FGF1, FGF2 or FGF9 was performed, and the effects of FGF9 on cortical neurons investigated using a combination of transcriptional, electrophysiological and immunofluorescence microscopic techniques. The in vivo effects of FGF9 were explored by stereotactic injection of adeno-associated viral (AAV) vectors encoding either FGF9 or EGFP into the rat motor cortex.

RESULTS

Transcriptional profiling of myelinating cultures after FGF9 treatment revealed a distinct neuronal response with a pronounced downregulation of gene networks associated with axonal transport and synaptic function. In cortical neuronal cultures, FGF9 also rapidly downregulated expression of genes associated with synaptic function. This was associated with a complete block in the development of photo-inducible spiking activity, as demonstrated using multi-electrode recordings of channel rhodopsin-transfected rat cortical neurons in vitro and, ultimately, neuronal cell death. Overexpression of FGF9 in vivo resulted in rapid loss of neurons and subsequent development of chronic grey matter lesions with neuroaxonal reduction and ensuing myelin loss.

CONCLUSIONS

These observations identify overexpression of FGF9 as a mechanism by which neuroaxonal pathology could develop independently of immune-mediated demyelination in MS. We suggest targeting neuronal FGF9-dependent pathways may provide a novel strategy to slow if not halt neuroaxonal atrophy and loss in MS, MDD and potentially other neurodegenerative diseases.

Brain-machine interface learning is facilitated by specific patterning of distributed cortical feedback

Neuroprosthetics offer great hope for motor-impaired patients. One obstacle is that fine motor control requires near-instantaneous, rich somatosensory feedback. Such distributed feedback may be recreated in a brain-machine interface using distributed artificial stimulation across the cortical surface. Here, we hypothesized that neuronal stimulation must be contiguous in its spatiotemporal dynamics to be efficiently integrated by sensorimotor circuits. Using a closed-loop brain-machine interface, we trained head-fixed mice to control a virtual cursor by modulating the activity of motor cortex neurons. We provided artificial feedback in real time with distributed optogenetic stimulation patterns in the primary somatosensory cortex. Mice developed a specific motor strategy and succeeded to learn the task only when the optogenetic feedback pattern was spatially and temporally contiguous while it moved across the topography of the somatosensory cortex. These results reveal spatiotemporal properties of the sensorimotor cortical integration that set constraints on the design of neuroprosthetics.

Spontaneous and Visual Stimulation Evoked Firing Sequences Are Distinct Under Desflurane Anesthesia

Recurring spike sequences are thought to underlie cortical computations and may be essential for information processing in the conscious state. How anesthesia at graded levels may influence spontaneous and stimulus-related spike sequences in visual cortex has not been fully elucidated. We recorded extracellular single-unit activity in the rat primary visual cortex in vivo during wakefulness and three levels of anesthesia produced by desflurane. The latencies of spike sequences within 0-200 ms from the onset of spontaneous UP states and visual flash-evoked responses were compared. During wakefulness, spike latency patterns linked to the local field potential theta cycle were similar to stimulus-evoked patterns. Under desflurane anesthesia, spontaneous UP state sequences differed from flash-evoked sequences due to the recruitment of low-firing excitatory neurons to the UP state. Flash-evoked spike sequences showed higher reliability and longer latency when stimuli were applied during DOWN states compared to UP states. At deeper levels, desflurane altered both UP state and flash-evoked spike sequences by selectively suppressing inhibitory neuron firing. The results reveal desflurane-induced complex changes in cortical firing sequences that may influence visual information processing.

Understanding Neuromodulation Pathways in tDCS: Brain Stem Recordings in Rat During Trigeminal Nerve Direct Current Stimulation

Background

Recent evidence suggests that transcranial direct current stimulation (tDCS) indirectly influences brain activity through cranial nerve pathways, particularly the trigeminal nerve. However, the electrophysiological effects of direct current (DC) stimulation on the trigeminal nerve (DC-TNS) and its impact on trigeminal nuclei remain unknown. These nuclei exert control over brainstem centers regulating neurotransmitter release, such as serotonin and norepinephrine, potentially affecting global brain activity.

Objectives

To investigate how DC-TNS impacts neuronal activity in the principal sensory nucleus (NVsnpr) and the mesencephalic nucleus of the trigeminal nerve (MeV).

Methods

Twenty male Sprague Dawley rats (n=10 each nucleus) were anesthetized with urethane. DC stimulation, ranging from 0.5 to 3 mA, targeted the trigeminal nerve's marginal branch. Simultaneously, single-unit electrophysiological recordings were obtained using a 32-channel silicon probe, comprising three one-minute intervals: pre-stimulation, DC stimulation, and post-stimulation. Xylocaine was administered to block the trigeminal nerve as a control.

Results

DC-TNS significantly increased neuronal spiking activity in both NVsnpr and MeV, returning to baseline during the post-stimulation phase. When the trigeminal nerve was blocked with xylocaine, the robust 3 mA trigeminal nerve DC stimulation failed to induce increased spiking activity in the trigeminal nuclei.

Conclusion

Our results offer initial empirical support for trigeminal nuclei activity modulation via DC-TNS. This discovery supports the hypothesis that cranial nerve pathways may play a pivotal role in mediating tDCS effects, setting the stage for further exploration into the complex interplay between peripheral nerves and neural modulation techniques.

Highlights

Direct current stimulation of the trigeminal nerve (DC-TNS) modulates neural activity in rat NVsnpr and MeV.Xylocaine administration reversibly blocks the DC-TNS effect on neural responses.Trigeminal nerve stimulation should be considered a possible mechanism of action of tDCS.

NeuSort: an automatic adaptive spike sorting approach with neuromorphic models

Objective.Spike sorting, a critical step in neural data processing, aims to classify spiking events from single electrode recordings based on different waveforms. This study aims to develop a novel online spike sorter, NeuSort, using neuromorphic models, with the ability to adaptively adjust to changes in neural signals, including waveform deformations and the appearance of new neurons.Approach.NeuSort leverages a neuromorphic model to emulate template-matching processes. This model incorporates plasticity learning mechanisms inspired by biological neural systems, facilitating real-time adjustments to online parameters.Results.Experimental findings demonstrate NeuSort's ability to track neuron activities amidst waveform deformations and identify new neurons in real-time. NeuSort excels in handling non-stationary neural signals, significantly enhancing its applicability for long-term spike sorting tasks. Moreover, its implementation on neuromorphic chips guarantees ultra-low energy consumption during computation.Significance.NeuSort caters to the demand for real-time spike sorting in brain-machine interfaces through a neuromorphic approach. Its unsupervised, automated spike sorting process makes it a plug-and-play solution for online spike sorting.

Differences in nonlinearities determine retinal cell types

Classifying neurons in different types is still an open challenge. In the retina, recent works have taken advantage of the ability to record from a large number of cells to classify ganglion cells into different types based on functional information. Although the first attempts in this direction used the receptive field properties of each cell to classify them, more recent approaches have proposed to cluster ganglion cells directly based on their response to stimuli. These two approaches have not been compared directly. Here, we recorded the responses of a large number of ganglion cells and compared two methods for classifying them into functional groups, one based on the receptive field properties, and the other one using directly their responses to stimuli with various temporal frequencies. We show that the response-based approach allows separation of more types than the receptive field-based method, leading to a better classification. This better granularity is due to the fact that the response-based method takes into account not only the linear part of ganglion cell function but also some of the nonlinearities. A careful characterization of nonlinear processing is thus key to allowing functional classification of sensory neurons.NEW & NOTEWORTHY In the retina, ganglion cells can be classified based on their response to visual stimuli. Although some methods are based on the modeling of receptive fields, others rely on responses to characteristic stimuli. We compared these two classes of methods and show that the latter provides a higher discrimination performance. We also show that this gain arises from the ability to account for the nonlinear behavior of neurons.

Functional imaging of conduction dynamics in cortical and spinal axons

Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.

A Fast and Effective Spike Sorting Method Based on Multi-Frequency Composite Waveform Shapes

Accurate spike sorting to the appropriate neuron is crucial for neural activity analysis. To improve spike sorting performance, it is essential to fully leverage each processing step, including filtering, spike detection, feature extraction, and clustering. However, compared to the latter two steps that were widely studied and optimized, the filtering process was largely neglected. In this study, we proposed a fast and effective spike sorting method (MultiFq) based on multi-frequency composite waveform shapes acquired through an optimized filtering process. When combined with the classical PCA-Km spiking sorting algorithm, our proposed MultiFq significantly improved its sorting performance and achieved as high performance as the complex Wave-clus did in both the simulated and in vivo datasets. But, the combined method was about 10 times faster than Wave-clus (0.16 s vs. 2.06 s in simulated datasets; 0.46 s vs. 2.03 s in in vivo datasets). Furthermore, we demonstrated the compatibility of our MultiFq by combining it with other sorting algorithms, which consistently resulted in significant improvement in sorting accuracy with the maximum improvement at 35.04%. The above results demonstrated that our proposed method could significantly improve the sorting performance with low computation cost and good compatibility by leveraging the multi-frequency composite waveform shapes.

A Five-Channel Weighted Real-Time Algorithm for High-Density Electrodes Spike Sorting

With the application of high-density neural probes, a neuron can be detected by multiple adjacent probes, and the traditional single-channel spike sorting is no longer suitable. In this paper, we propose a five-channel weighted real-time spike sorting algorithm based on template-matching to process neural signals recorded by high-density probes. This work uses the signals of the center channel and the adjacent four channels to form a five-channel template by weighting, and employs a modified OSort algorithm with unsupervised learning to update the template. We implemented automatic online spike sorting, and tested it with both ground truth recordings and simulated datasets. The experiments show that our algorithm utilizing the information of adjacent channels has a higher sorting accuracy than traditional single-channel spike sorting. The average sorting accuracy reaches 89%, compared to 78% for single-channel.

Fear memory recall involves hippocampal somatostatin interneurons

Fear-related memory traces are encoded by sparse populations of hippocampal principal neurons that are recruited based on their inhibitory-excitatory balance during memory formation. Later, the reactivation of the same principal neurons can recall the memory. The details of this mechanism are still unclear. Here, we investigated whether disinhibition could play a major role in this process. Using optogenetic behavioral experiments, we found that when fear was associated with the inhibition of mouse hippocampal somatostatin positive interneurons, the re-inhibition of the same interneurons could recall fear memory. Pontine nucleus incertus neurons selectively inhibit hippocampal somatostatin cells. We also found that when fear was associated with the activity of these incertus neurons or fibers, the reactivation of the same incertus neurons or fibers could also recall fear memory. These incertus neurons showed correlated activity with hippocampal principal neurons during memory recall and were strongly innervated by memory-related neocortical centers, from which the inputs could also control hippocampal disinhibition in vivo. Nonselective inhibition of these mouse hippocampal somatostatin or incertus neurons impaired memory recall. Our data suggest a novel disinhibition-based memory mechanism in the hippocampus that is supported by local somatostatin interneurons and their pontine brainstem inputs.

Ectopic expression of a mechanosensitive channel confers spatiotemporal resolution to ultrasound stimulations of neurons for visual restoration

Remote and precisely controlled activation of the brain is a fundamental challenge in the development of brain-machine interfaces for neurological treatments. Low-frequency ultrasound stimulation can be used to modulate neuronal activity deep in the brain, especially after expressing ultrasound-sensitive proteins. But so far, no study has described an ultrasound-mediated activation strategy whose spatiotemporal resolution and acoustic intensity are compatible with the mandatory needs of brain-machine interfaces, particularly for visual restoration. Here we combined the expression of large-conductance mechanosensitive ion channels with uncustomary high-frequency ultrasonic stimulation to activate retinal or cortical neurons over millisecond durations at a spatiotemporal resolution and acoustic energy deposit compatible with vision restoration. The in vivo sonogenetic activation of the visual cortex generated a behaviour associated with light perception. Our findings demonstrate that sonogenetics can deliver millisecond pattern presentations via an approach less invasive than current brain-machine interfaces for visual restoration.

Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology

The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.

Precision of neuronal localization in 2D cell cultures by using high-performance electropolymerized microelectrode arrays correlated with optical imaging

Recently, the development of electronic devices to extracellularly record the simultaneous electrical activities of numerous neurons has been blooming, opening new possibilities to interface and decode neuronal activity. In this work, we tested how the use of EDOT electropolymerization to tune post-fabrication materials could optimize the cell/electrode interface of such devices. Our results showed an improved signal-to-noise ratio, better biocompatibility, and a higher number of neurons detected in comparison with gold electrodes. Then, using such enhanced recordings with 2D neuronal cultures combined with fluorescent optical imaging, we checked the extent to which the positions of the recorded neurons could be estimated solely via their extracellular signatures. Our results showed that assuming neurons behave as monopoles, positions could be estimated with a precision of approximately tens of micrometers.

Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology

Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.

Dissociable neuronal substrates of visual feature attention and working memory

Attention and working memory (WM) are distinct cognitive functions, yet given their close interactions, it has been proposed that they share the same neuronal mechanisms. Here we show that in macaques performing a WM-guided feature attention task, the activity of most neurons in areas middle temporal (MT), medial superior temporal (MST), lateral intraparietal (LIP), and posterior lateral prefrontal cortex (LPFC-p) displays either WM coding or attentional modulation, but not both. One area thought to play a role in both functions is LPFC-p. To test this, we optogenetically inactivated LPFC-p bilaterally during the attention or WM periods of the task. Attention period inactivation reduced attentional modulation in LPFC-p, MST, and LIP neurons, and impaired task performance. WM period inactivation did not affect attentional modulation nor performance, and minimally reduced WM coding. Our results suggest that feature attention and WM have dissociable neuronal substrates, and that LPFC-p plays a critical role in attention but not WM.