A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells

Background: In the cerebellar cortex, Purkinje cells are the only output neurons and exhibit two types of discharge. Most Purkinje cell discharges are simple spikes, which are commonly appearing action potentials exhibiting a rich variety of firing patterns with a rate of up to 400 Hz. More infrequent discharges are complex spikes, which consist of a short burst of impulses accompanied by a massive increase in dendritic Ca2+ with a firing rate of around 1 Hz. The discrimination of these spikes in extracellular single-unit recordings is not always straightforward, as their waveforms vary depending on recording conditions and intrinsic fluctuations. New Method: To discriminate complex spikes from simple spikes in the extracellular single-unit data, we developed a semiautomatic spike-sorting method based on divisive hierarchical clustering. Results: Quantitative evaluation using parallel in vivo two-photon Ca2+ imaging of Purkinje cell dendrites indicated that 96.6% of the complex spikes were detected using our spike-sorting method from extracellular single-unit recordings obtained from anesthetized mice. Comparison with Existing Method(s): No reports have conducted a quantitative evaluation of spike-sorting algorithms used for the classification of extracellular spikes recorded from cerebellar Purkinje cells. Conclusions: Our method could be expected to contribute to research in information processing in the cerebellar cortex and the development of a fully automatic spike-sorting algorithm by providing ground-truth data useful for deep learning.

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Differential Purkinje cell simple spike activity and pausing behavior related to cerebellar modules

Journal of Neurophysiology ◽

10.1152/jn.00925.2014 ◽

2015 ◽

Vol 113 (7) ◽

pp. 2524-2536 ◽

Cited By ~ 17

Author(s):

Haibo Zhou ◽

Kai Voges ◽

Zhanmin Lin ◽

Chiheng Ju ◽

Martijn Schonewille

Keyword(s):

Purkinje Cell ◽

Purkinje Cells ◽

Cerebellar Cortex ◽

Spike Activity ◽

Vestibular Nuclei ◽

Simple Spike ◽

Transverse Zone ◽

Cerebellar Modules ◽

Lower Temperature ◽

Cerebellar Purkinje Cells

The massive computational capacity of the cerebellar cortex is conveyed by Purkinje cells onto cerebellar and vestibular nuclei neurons through their GABAergic, inhibitory output. This implies that pauses in Purkinje cell simple spike activity are potentially instrumental in cerebellar information processing, but their occurrence and extent are still heavily debated. The cerebellar cortex, although often treated as such, is not homogeneous. Cerebellar modules with distinct anatomical connectivity and gene expression have been described, and Purkinje cells in these modules also differ in firing rate of simple and complex spikes. In this study we systematically correlate, in awake mice, the pausing in simple spike activity of Purkinje cells recorded throughout the entire cerebellum, with their location in terms of lobule, transverse zone, and zebrin-identified cerebellar module. A subset of Purkinje cells displayed long (>500-ms) pauses, but we found that their occurrence correlated with tissue damage and lower temperature. In contrast to long pauses, short pauses (<500 ms) and the shape of the interspike interval (ISI) distributions can differ between Purkinje cells of different lobules and cerebellar modules. In fact, the ISI distributions can differ both between and within populations of Purkinje cells with the same zebrin identity, and these differences are at least in part caused by differential synaptic inputs. Our results suggest that long pauses are rare but that there are differences related to shorter intersimple spike intervals between and within specific subsets of Purkinje cells, indicating a potential further segregation in the activity of cerebellar Purkinje cells.

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Using deep neural networks to detect complex spikes of cerebellar Purkinje cells

Journal of Neurophysiology ◽

10.1152/jn.00754.2019 ◽

2020 ◽

Vol 123 (6) ◽

pp. 2217-2234

Author(s):

Akshay Markanday ◽

Joachim Bellet ◽

Marie E. Bellet ◽

Junya Inoue ◽

Ziad M. Hafed ◽

...

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Purkinje Cell ◽

Purkinje Cells ◽

Deep Neural Networks ◽

Learning Approach ◽

Sorting Algorithms ◽

Accuracy Level ◽

Cerebellar Purkinje Cells ◽

Complex Spikes

Purkinje cell “complex spikes,” fired at perplexingly low rates, play a crucial role in cerebellum-based motor learning. Careful interpretations of these spikes require manually detecting them, since conventional online or offline spike sorting algorithms are optimized for classifying much simpler waveform morphologies. We present a novel deep learning approach for identifying complex spikes, which also measures additional relevant neurophysiological features, with an accuracy level matching that of human experts yet with very little time expenditure.

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Functional Localization in the Cerebellar Cortex Studied by Quantitative Determinations of Purkinje Cell RNA: I. RNA changes in rat cerebellar Purkinje cells after proprio-and exteroceptive and vestibular stimulation

Acta Physiologica Scandinavica ◽

10.1111/j.1748-1716.1966.tb03307.x ◽

1966 ◽

Vol 67 (2) ◽

pp. 243-252 ◽

Cited By ~ 29

Author(s):

Jan Jarlstedt

Keyword(s):

Purkinje Cell ◽

Purkinje Cells ◽

Cerebellar Cortex ◽

Vestibular Stimulation ◽

Functional Localization ◽

Cerebellar Purkinje Cells ◽

Rna I

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Direct translation of climbing fiber burst-mediated sensory coding into post-synaptic Purkinje cell dendritic calcium

eLife ◽

10.7554/elife.61593 ◽

2020 ◽

Vol 9 ◽

Cited By ~ 1

Author(s):

Seung-Eon Roh ◽

Seung Ha Kim ◽

Changhyeon Ryu ◽

Chang-Eop Kim ◽

Yong Gyu Kim ◽

...

Keyword(s):

Purkinje Cell ◽

Purkinje Cells ◽

Sensory Information ◽

Sensory Coding ◽

Information Coding ◽

Direct Translation ◽

Spike Number ◽

Cerebellar Purkinje Cells ◽

Complex Spikes

Climbing fibers (CFs) generate complex spikes (CS) and Ca2+ transients in cerebellar Purkinje cells (PCs), serving as instructive signals. The so-called 'all-or-none' character of CSs has been questioned since the CF burst was described. Although recent studies have indicated a sensory-driven enhancement of PC Ca2+ signals, how CF responds to sensory events and contributes to PC dendritic Ca2+ and CS remains unexplored. Here, single or simultaneous Ca2+ imaging of CFs and PCs in awake mice revealed the presynaptic CF Ca2+ amplitude encoded the sensory input’s strength and directly influenced post-synaptic PC dendritic Ca2+ amplitude. The sensory-driven variability in CF Ca2+ amplitude depended on the number of spikes in the CF burst. Finally, the spike number of the CF burst determined the PC Ca2+ influx and CS properties. These results reveal the direct translation of sensory information-coding CF inputs into PC Ca2+, suggesting the sophisticated role of CFs as error signals.

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Using deep neural networks to detect complex spikes of cerebellar Purkinje Cells

10.1101/600536 ◽

2019 ◽

Cited By ~ 1

Author(s):

Akshay Markanday ◽

Joachim Bellet ◽

Marie E. Bellet ◽

Ziad M. Hafed ◽

Peter Thier

Keyword(s):

Motor Control ◽

Deep Learning ◽

Action Potential ◽

Purkinje Cell ◽

Purkinje Cells ◽

Local Field ◽

Visual Inspection ◽

Complex Spike ◽

Cerebellar Purkinje Cells ◽

Complex Spikes

AbstractOne of the most powerful excitatory synapses in the entire brain is formed by cerebellar climbing fibers, originating from neurons in the inferior olive, that wrap around the proximal dendrites of cerebellar Purkinje cells. The activation of a single olivary neuron is capable of generating a large electrical event, called “complex spike”, at the level of the postsynaptic Purkinje cell, comprising of a fast initial spike of large amplitude followed by a slow polyphasic tail of small amplitude spikelets. Several ideas discussing the role of the cerebellum in motor control are centered on these complex spike events. However, these events are extremely rare, only occurring 1-2 times per second. As a result, drawing conclusions about their functional role has been very challenging, as even few errors in their detection may change the result. Since standard spike sorting approaches cannot fully handle the polyphasic shape of complex spike waveforms, the only safe way to avoid omissions and false detections has been to rely on visual inspection of long traces of Purkinje cell recordings by experts. Here we present a supervised deep learning algorithm for rapidly and reliably detecting complex spikes as an alternative to tedious visual inspection. Our algorithm, utilizing both action potential and local field potential signals, not only detects complex spike events much faster than human experts, but it also excavates key features of complex spike morphology with a performance comparable to that of such experts.Significance statementClimbing fiber driven “complex spikes”, fired at perplexingly low rates, are known to play a crucial role in cerebellum-based motor control. Careful interpretations of these spikes require researchers to manually detect them, since conventional online or offline spike sorting algorithms (optimized for analyzing the much more frequent “simple spikes”) cannot be fully trusted. Here, we present a deep learning approach for identifying complex spikes, which is trained on local field and action potential recordings from cerebellar Purkinje cells. Our algorithm successfully identifies complex spikes, along with additional relevant neurophysiological features, with an accuracy level matching that of human experts, yet with very little time expenditure.

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Transcranial direct current stimulation of cerebellum alters spiking precision in cerebellar cortex: A modeling study of cellular responses

PLoS Computational Biology ◽

10.1371/journal.pcbi.1009609 ◽

2021 ◽

Vol 17 (12) ◽

pp. e1009609

Author(s):

Xu Zhang ◽

Roeland Hancock ◽

Sabato Santaniello

Keyword(s):

Purkinje Cells ◽

Cerebellar Cortex ◽

Direct Current ◽

Transcranial Direct Current Stimulation ◽

Cellular Response ◽

Cerebellar Neurons ◽

Direct Current Stimulation ◽

Repolarization Phase ◽

Cerebellar Tdcs ◽

Complex Spikes

Transcranial direct current stimulation (tDCS) of the cerebellum has rapidly raised interest but the effects of tDCS on cerebellar neurons remain unclear. Assessing the cellular response to tDCS is challenging because of the uneven, highly stratified cytoarchitecture of the cerebellum, within which cellular morphologies, physiological properties, and function vary largely across several types of neurons. In this study, we combine MRI-based segmentation of the cerebellum and a finite element model of the tDCS-induced electric field (EF) inside the cerebellum to determine the field imposed on the cerebellar neurons throughout the region. We then pair the EF with multicompartment models of the Purkinje cell (PC), deep cerebellar neuron (DCN), and granule cell (GrC) and quantify the acute response of these neurons under various orientations, physiological conditions, and sequences of presynaptic stimuli. We show that cerebellar tDCS significantly modulates the postsynaptic spiking precision of the PC, which is expressed as a change in the spike count and timing in response to presynaptic stimuli. tDCS has modest effects, instead, on the PC tonic firing at rest and on the postsynaptic activity of DCN and GrC. In Purkinje cells, anodal tDCS shortens the repolarization phase following complex spikes (-14.7 ± 6.5% of baseline value, mean ± S.D.; max: -22.7%) and promotes burstiness with longer bursts compared to resting conditions. Cathodal tDCS, instead, promotes irregular spiking by enhancing somatic excitability and significantly prolongs the repolarization after complex spikes compared to baseline (+37.0 ± 28.9%, mean ± S.D.; max: +84.3%). tDCS-induced changes to the repolarization phase and firing pattern exceed 10% of the baseline values in Purkinje cells covering up to 20% of the cerebellar cortex, with the effects being distributed along the EF direction and concentrated in the area under the electrode over the cerebellum. Altogether, the acute effects of tDCS on cerebellum mainly focus on Purkinje cells and modulate the precision of the response to synaptic stimuli, thus having the largest impact when the cerebellar cortex is active. Since the spatiotemporal precision of the PC spiking is critical to learning and coordination, our results suggest cerebellar tDCS as a viable therapeutic option for disorders involving cerebellar hyperactivity such as ataxia.

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Activation of MAP3K DLK and LZK in Purkinje Cells Causes Rapid and Slow Degeneration Depending on Signaling Strength

10.1101/2020.10.09.332940 ◽

2020 ◽

Author(s):

Yunbo Li ◽

Erin M Ritchie ◽

Christopher L. Steinke ◽

Cai Qi ◽

Lizhen Chen ◽

...

Keyword(s):

Alternative Splicing ◽

Purkinje Cell ◽

Purkinje Cells ◽

Leucine Zipper ◽

Activity Levels ◽

Cell Type ◽

Cell Degeneration ◽

Mechanistic Basis ◽

Cerebellar Purkinje Cells ◽

Jnk Activation

SummaryThe conserved MAP3K Dual leucine zipper kinases can activate JNK via MKK4 or MKK7. Vertebrate DLK and LZK share similar biochemical activities and undergo auto-activation upon increased expression. Depending on cell-type and nature of insults DLK and LZK can induce pro-regenerative, pro-apoptotic or pro-degenerative responses, although the mechanistic basis of their action is not well understood. Here, we investigated these two MAP3Ks in cerebellar Purkinje cells using loss- and gain-of function mouse models. While loss of each or both kinases does not cause discernible defects in Purkinje cells, activating DLK causes rapid death and activating LZK leads to slow degeneration. Each kinase induces JNK activation and caspase-mediated apoptosis independent of each other. Significantly, deleting CELF2, which regulates alternative splicing of Mkk7, strongly attenuates Purkinje cell degeneration induced by activation of LZK, but not DLK. Thus, controlling the activity levels of DLK and LZK is critical for neuronal survival and health.

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Purkinje Cell Collaterals Enable Output Signals from the Cerebellar Cortex to Feed Back to Purkinje Cells and Interneurons

Neuron ◽

10.1016/j.neuron.2016.05.037 ◽

2016 ◽

Vol 91 (2) ◽

pp. 312-319 ◽

Cited By ~ 59

Author(s):

Laurens Witter ◽

Stephanie Rudolph ◽

R. Todd Pressler ◽

Safiya I. Lahlaf ◽

Wade G. Regehr

Keyword(s):

Purkinje Cell ◽

Purkinje Cells ◽

Cerebellar Cortex

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Expression of the yes proto-oncogene in cerebellar Purkinje cells.

Molecular and Cellular Biology ◽

10.1128/mcb.9.10.4545 ◽

1989 ◽

Vol 9 (10) ◽

pp. 4545-4549 ◽

Cited By ~ 18

Author(s):

M Sudol ◽

C F Kuo ◽

L Shigemitsu ◽

A Alvarez-Buylla

Keyword(s):

In Situ Hybridization ◽

Purkinje Cell ◽

Gene Product ◽

Purkinje Cells ◽

Immunofluorescent Staining ◽

Cell Degeneration ◽

Functional Studies ◽

Cerebellar Purkinje Cells ◽

The Brain

To identify the kinds of cells in the brain that express the yes proto-oncogene, we examined chicken brains by using immunofluorescent staining and in situ hybridization. Both approaches showed that the highest level of the yes gene product was in cerebellar Purkinje cells. In addition, we analyzed Purkinje cell degeneration (pcd) mutant mice. The level of yes mRNA in cerebella of pcd mutants was four times lower than that found in cerebella of normal littermates. Our studies point to Purkinje cells as an attractive model for functional studies of the yes protein.

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