Biology subjects

Yger, P.

Publications and source records attributed to Yger, P..

10 recordsLinked to original sources

bioRxiv2026

Opening the black box: a modular approach to spike sorting

Spike sorting is an algorithmic process that extracts the activity of individual neurons from extracellular electrophysiology recordings. With the ballooning use of high density probes, such as Neuropixels, this essential processing step is increasingly becoming time consuming and computationally expensive. Although many software tools have been proposed to address spike sorting, they are usually constructed and benchmarked as monolithic "black boxes", making it difficult to factor out the effects of individual algorithmic steps on the final outcome, especially when varying datasets and parameters. To address this issue, we developed a modular and common framework to develop, benchmark and assemble the key computational steps that are used in state-of-the-art spike sorting algorithms. Relying on fast and efficient ground truth generation of biophysically plausible recordings, we show that we are able to individually benchmark and precisely quantify the performance of different steps in a spike sorting pipeline (i.e. peak detection, feature extraction and clustering, and template matching). We then leverage these results to create a modular, component-based spike sorter that can outperform Kilosort 4 on dense and large simulated recordings and produce similar quantitative results on real data. In addition, we find that the major bottleneck of all modern spike sorting pipelines is in the physical motion of probes, regardless of the drift-correction strategy. The component-based spike sorting framework presented here has the potential to foster community engagement in the field by lowering the barrier to contributions and providing a flexible yet powerful framework to construct end-to-end spike sorting solutions.

neuroscience↗

bioRxiv2025

BIN1 expression in the presynaptic compartment leads to isoform-specific synaptotoxicity

Alzheimers disease (AD) is characterized by a strong genetic predisposition and by an early loss of synaptic connectivity that strongly correlates with cognitive deficit. Some genetic determinants could contribute to synapse frailty toward AD pathology. However, the role of genetic determinants in AD pathogenesis remains poorly understood at the synaptic level. Here, we show that the expression of an isoform of the major AD susceptibility gene BIN1 in the presynaptic compartment results in synaptic loss. Using electrophysiology, we observed an early loss of synaptic transmission upon BIN1 isoform 1 (BIN1iso1) expression in Drosophila retinal photoreceptor neurons. This was not observed for the other human BIN1 isoforms tested, isoform 8 and isoform 9. Structural analysis of photoreceptor neuron synapses shows a strong accumulation of abnormally large vesicles in the presynaptic compartment, reminiscent of this same isoform-induced endosome defects in cell bodies. In addition, the expression of BIN1iso1 in motoneurons of the Drosophila neuromuscular junction alters the morphology of synaptic boutons, with a greater number and a smaller size of synaptic boutons, and the appearance of satellite boutons. As opposed to endosomal defects in cell body, modulating the Rab11 recycling endosome regulator did not prevent BIN1iso1 synaptotoxicity. To test if synaptic deficits are conserved in a mammalian model and to assert a presynaptic vs postsynaptic role for BIN1, we used rat primary neurons cultured in microfluidic devices that restrict gene expression modulation in particular neuron populations. We found a loss of synaptic connectivity only when expressing BIN1iso1 in the presynaptic compartment, which was confirmed by microelectrode array analysis. Together, our results suggest that BIN1 expression in the presynaptic terminal, but not the postsynaptic terminal leads to an isoform-specific, deleterious effect on synaptic integrity. BIN1 synaptotoxicity could contribute to the synapse loss observed early in AD. This supports the idea that genetic determinants could make synapses prone to failure in AD.

neuroscience↗

bioRxiv2023

A modular approach to handle in-vivo 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 an exhaustive benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying 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. Significance statement

neuroscience↗

bioRxiv2022

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. In an attempt to do so, we used a promoter that targets gene expression to a specific interneuron of the retina called the AII amacrine cell. The AII amacrine cell simultaneously activates the ON pathway and inhibits 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.

neuroscience↗

bioRxiv2022

Differences in non-linearities 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 a large number of cells to classify ganglion cells into different types based on functional information. While 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 standard 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 types, one based on the receptive field properties, and the other one using their responses to standard stimuli. We show that the stimulus-based approach allows separating more types than the receptive field-based method, leading to a better classification. This better granularity is due to the fact that the stimulus-based method takes into account not only the linear part of ganglion cell function, but also non-linearities. A careful characterization of non-linear processing is thus key to allow functional classification of sensory neurons.

neuroscience↗

bioRxiv2021

How do spike collisions affect spike sortingperformance?

Recently, a new generation of devices have been developed to record neural activity simultaneously from hundreds of electrodes with a very high spatial density, both for in vitro and in vivo applications. While these advances enable to record from many more cells, they also dramatically increase the amount overlapping "synchronous" spikes (colliding in space and/or in time), challenging the already complicated process of spike sorting (i.e. extracting isolated single-neuron activity from extracellular signals). In this work, we used synthetic ground-truth recordings to quantitatively benchmark the performance of state-of-the-art spike sorters focusing specifically on spike collisions. Our results show that while modern template-matching based algorithms are more accurate than density-based approaches, all methods, to some extent, failed to detect synchronous spike events of neurons with similar extracellular signals. Interestingly, the performance of the sorters is not largely affected by the the spiking activity in the recordings, with respect to average firing rates and spike-train correlation levels.

neuroscience↗

bioRxiv2021

Decoding activity in Broca's area predicts the occurrence of auditory hallucinations across subjects

BACKGROUNDFunctional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we developed a novel automatized fMRI-capture procedure for AVHs in schizophrenia patients. METHODSWe used a previously validated, but labor-intensive, personalized fMRI-capture method to train a linear classifier using machine-learning techniques. We benchmarked the performances of this classifier on 2320 AVH periods vs. resting-state periods obtained from schizophrenia patients with frequent symptoms (n=23). We characterized patterns of BOLD activity that were predictive of AVH both within- and between-subjects. Generalizability was assessed with a second independent sample gathering 2000 AVH labels (n=34 schizophrenia patients), while specificity was tested with a nonclinical control sample performing an auditory imagery task (840 labels, n=20). RESULTSOur between-subject classifier achieved high decoding accuracy (area-under-the-curve, AUC = 0.85) and discriminated AVH from rest and verbal imagery. Optimizing the parameters on the first schizophrenia dataset and testing its performance on the second dataset led to a 0.85 out-of-sample AUC (0.88 for the converse test). We showed that AVH detection critically depends on local BOLD activity patterns within Brocas area. CONCLUSIONSOur results demonstrate that it is possible to reliably detect AVH-states from BOLD signals in schizophrenia patients using a multivariate decoder without performing complex regularization procedures. These findings constitute a crucial step toward brain-based treatments for severe drug-resistant hallucinations.

neuroscience↗

bioRxiv2019

Micro-electrode in vivo signatures of human periventricular heterotopia

Periventricular nodular heterotopia (PNH) is a malformation of cortical development that frequently causes drug-resistant epilepsy. The epileptogenicity of ectopic neurons in PNH as well as their role in generating interictal and ictal activity is still a matter of debate. We report the first in vivo microelectrode recording of heterotopic neurons in humans. Highly consistent interictal patterns (IPs) were identified within the nodules: 1) Periodic Discharges PLUS Fast activity (PD+F), Sporadic discharges PLUS Fast activity (SD+F), and 3) epileptic spikes (ES). Neuronal firing rates were significantly modulated during all IPs, suggesting that multiple IPs were generated by the same local neuronal populations. Furthermore, firing rates closely followed IP morphologies. Among the different IPs, SD+FA pattern was found only in the three nodules that were actively involved in seizure generation, but was never observed in the nodule that did not take part in ictal discharges. On the contrary, PD+F and ES were identified in all nodules. Units that were modulated during the IPs were also found to participate in seizures, increasing their firing rate at seizure onset and maintaining an elevated rate during the seizures. Together, nodules in PNH are highly epileptogenic, and show several IPs that provide promising pathognomonic signatures of PNH. Furthermore, our results show that PNH nodules may well initiate seizures. HighlightsO_LIFirst in vivo microelectrode description of local epileptic activities in human PNH C_LIO_LIRecordings revealed multiple microscopic epileptic interictal patterns C_LIO_LIFiring rates of all detected units were significantly modulated during all interictal patterns C_LIO_LISeizures recruited the same units that are involved in interictal activity C_LI

pathology↗

bioRxiv2019

Axonal Na+ channels detect and transmit levels of input synchrony in local brain circuits

Sensory processing requires mechanisms of fast coincidence-detection to discriminate synchronous from asynchronous inputs. Spike-threshold adaptation enables such a discrimination but is ineffective in transmitting this information to the network. We show here that presynaptic axonal sodium channels read and transmit precise levels of input synchrony to the postsynaptic cell by modulating the presynaptic action potential (AP) amplitude. As a consequence, synaptic transmission is facilitated at cortical synapses when the presynaptic spike is produced by synchronous inputs. Using dual soma-axon recordings, imaging, and modeling, we show that this facilitation results from enhanced AP amplitude in the axon due to minimized inactivation of axonal sodium-channels. Quantifying local circuit activity and using network modeling, we found that spikes induced by synchronous inputs produced a larger effect on network activity than spikes induced by asynchronous inputs. Therefore, this input-synchrony dependent facilitation (ISF) may constitute a powerful mechanism regulating spike transmission.

neuroscience↗

bioRxiv2016

Recent progress in multi-electrode spike sorting methods

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms.

neuroscience↗