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

2019 ◽  
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.

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

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.

Increase in Purkinje cell gain associated with naturally activated climbing fiber input

1983 ◽  
Vol 50 (1) ◽  
pp. 205-219 ◽  
Author(s):  
T. J. Ebner ◽  
Q. X. Yu ◽  
J. R. Bloedel
Keyword(s):  
Purkinje Cell ◽  
Purkinje Cells ◽  
Mossy Fiber ◽  
Climbing Fiber ◽  
Peripheral Stimulus ◽  
Short Term ◽  
Spike Response ◽  
Complex Spike ◽  
Simple Spike ◽  
Complex Spikes

These experiments were designed to test the hypothesis that climbing fiber inputs evoked by a peripheral stimulus increase the responsiveness of Purkinje cells to mossy fiber inputs. This hypothesis was based on a previous series of observations demonstrating that spontaneous climbing fiber inputs are associated with an accentuation of the Purkinje cell responses to subsequent mossy fiber inputs (10, 12). Furthermore, short-term nonpersistent interactions between climbing and mossy fiber inputs have been an important aspect of many theories of cerebellar function (5, 7, 8, 12, 36). Extracellular unitary recordings were made from Purkinje cells in lobule V of decerebrate, unanesthetized cats. To activate mossy and climbing fiber inputs, the forepaw was passively flexed by a Ling vibrator system. A data analysis was developed to sort the simple spike trials into two groups, based on the presence or absence of complex spikes activated by the stimulus. In addition, during those trials in which complex spikes were activated, the simple spike train was aligned on the occurrence of the complex spike. For each simple spike response to the forepaw input, the average firing rate during the response was compared to background both in those trials in which complex spikes were activated and in those in which they were not. The ratio of the response amplitudes in the histograms constructed from these two groups of trials permitted a quantification of the change in responsiveness when climbing fiber inputs were activated. The results show that both excitatory and inhibitory simple spike responses are accentuated when associated with the activation of a complex spike. Using an arbitrary level of a gain change ratio of 120% as indicating a significant modification, 64% of the response components analyzed increased their amplitude when climbing fiber input was present. Simple spike response components occurring prior to complex spike activation were usually not accentuated, although in a few cells the amplitude of this component of the response increased. In addition, in a small number of cells the occurrence of complex spikes was associated with a new simple spike component. For excitatory responses, the magnitude of the gain change ratio was shown to be inversely related to the amplitude of the simple spike response evoked by the mossy fiber inputs. The data obtained is consistent with the hypothesis that the climbing fiber input is associated with an increase in the responsiveness of Purkinje cells to mossy fiber inputs. The increased responsiveness occurs whether the simple spike modulation evoked by the peripheral stimulus is excitatory or inhibitory. The change in responsiveness is short term and nonpersistent. It is argued that the activation of climbing fiber inputs to the cerebellar cortex is associated with an increase in the gain of Purkinje cells to mossy fiber inputs activated by natural peripheral stimuli.

scholarly journals Ethanol effects on the olivocerebellar system

1982 ◽  
Vol 60 (5) ◽  
pp. 610-614 ◽  
Author(s):  
J. G. Sinclair ◽  
G. F. Lo ◽  
D. P. Harris
Keyword(s):  
Purkinje Cell ◽  
Purkinje Cells ◽  
Inferior Olive ◽  
Climbing Fibre ◽  
Complex Spike ◽  
Anaesthetized Rats ◽  
Cerebellar Purkinje Cells ◽  
Cell Synapse

Ethanol (1.5 g/kg i.v.) was found to decrease spontaneous complex spike (CS) activity in cerebellar Purkinje cells in urethane anaesthetized rats while not changing the threshold required to evoke a CS by juxtafastigial stimulation. Thus ethanol does not decrease CS activity by an action at the climbing fibre – Purkinje cell synapse. Tremor induced by harmaline (5 mg/kg i.v.) in unanaesthetized animals was markedly antagonized by ethanol (0.5–2.0 g/kg i.v.) in all animals tested. However, in nine urethane-anaesthetized animals, ethanol markedly reversed the effects of harmaline on Purkinje cells in only two cases and partially reversed the effects in another four cells. Thus, the depressant effects of ethanol on the inferior olive is not totally responsible for the blockade of the harmaline tremor but would account for the decrease in spontaneous CS activity.

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

eLife ◽  
2020 ◽  
Vol 9 ◽  
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.

scholarly journals A Purkinje cell model that simulates complex spikes

2020 ◽  
Author(s):  
Amelia Burroughs ◽  
Nadia L. Cerminara ◽  
Richard Apps ◽  
Conor Houghton
Keyword(s):  
Action Potential ◽  
Purkinje Cell ◽  
Spike Activity ◽  
Cell Model ◽  
Compartment Model ◽  
Complex Spike ◽  
Simple Spike ◽  
Lower Amplitude ◽  
Complex Spikes

AbstractPurkinje cells are the principal neurons of the cerebellar cortex. One of their distinguishing features is that they fire two distinct types of action potential, called simple and complex spikes, which interact with one another. Simple spikes are stereotypical action potentials that are elicited at high, but variable, rates (0 – 100 Hz) and have a consistent waveform. Complex spikes are composed of an initial action potential followed by a burst of lower amplitude spikelets. Complex spikes occur at comparatively low rates (~ 1 Hz) and have a variable waveform. Although they are critical to cerebellar operation a simple model that describes the complex spike waveform is lacking. Here, a novel single-compartment model of Purkinje cell electrodynamics is presented. The simpler version of this model, with two active conductances and a leak channel, can simulate the features typical of complex spikes recorded in vitro. If calcium dynamics are also included, the model can capture the pause in simple spike activity that occurs after complex spike events. Together, these models provide an insight into the mechanisms behind complex spike spikelet generation, waveform variability and their interactions with simple spike activity.

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

2021 ◽  
Author(s):  
Takayuki Michikawa ◽  
Keisuke Isobe ◽  
Shigeyoshi Itohara
Keyword(s):  
Purkinje Cell ◽  
Purkinje Cells ◽  
Quantitative Evaluation ◽  
Cerebellar Cortex ◽  
Single Unit ◽  
Spike Sorting ◽  
Sorting Method ◽  
Single Unit Recordings ◽  
Cerebellar Purkinje Cells ◽  
Complex Spikes

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.

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

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.

scholarly journals Preterm Birth Impedes Structural and Functional Development of Cerebellar Purkinje Cells in the Developing Baboon Cerebellum

2020 ◽  
Vol 10 (12) ◽  
pp. 897
Author(s):  
Tara Barron ◽  
Jun Hee Kim
Keyword(s):  
Preterm Birth ◽  
Action Potential ◽  
Purkinje Cell ◽  
Purkinje Cells ◽  
Late Gestation ◽  
Cerebellar Development ◽  
Layer Width ◽  
Action Potential Waveform ◽  
Developmental Features ◽  
Potential Waveform

Human cerebellar development occurs late in gestation and is hindered by preterm birth. The fetal development of Purkinje cells, the primary output cells of the cerebellar cortex, is crucial for the structure and function of the cerebellum. However, morphological and electrophysiological features in Purkinje cells at different gestational ages, and the effects of neonatal intensive care unit (NICU) experience on cerebellar development are unexplored. Utilizing the non-human primate baboon cerebellum, we investigated Purkinje cell development during the last trimester of pregnancy and the effect of NICU experience following premature birth on developmental features of Purkinje cells. Immunostaining and whole-cell patch clamp recordings of Purkinje cells in the baboon cerebellum at different gestational ages revealed that molecular layer width, driven by Purkinje dendrite extension, drastically increased and refinement of action potential waveform properties occurred throughout the last trimester of pregnancy. Preterm birth followed by NICU experience for 2 weeks impeded development of Purkinje cells, including action potential waveform properties, synaptic input, and dendrite extension compared with age-matched controls. In addition, these alterations impact Purkinje cell output, reducing the spontaneous firing frequency in deep cerebellar nucleus (DCN) neurons. Taken together, the primate cerebellum undergoes developmental refinements during late gestation, and NICU experience following extreme preterm birth influences morphological and physiological features in the cerebellum that can lead to functional deficits.

scholarly journals Changes in the Responses of Purkinje Cells in the Floccular Complex of Monkeys After Motor Learning in Smooth Pursuit Eye Movements

2000 ◽  
Vol 84 (6) ◽  
pp. 2945-2960 ◽  
Author(s):  
Maninder Kahlon ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Purkinje Cells ◽  
Image Motion ◽  
Population Response ◽  
Complex Spike ◽  
Pursuit Eye Movements ◽  
Simple Spike ◽  
Learning Speed ◽  
Complex Spikes ◽  
Spike Firing

We followed simple- and complex-spike firing of Purkinje cells (PCs) in the floccular complex of the cerebellum through learned modifications of the pursuit eye movements of two monkeys. Learning was induced by double steps of target speed in which initially stationary targets move at a “learning” speed for 100 ms and then change to either a higher or lower speed in the same direction. In randomly interleaved control trials, targets moved at the learning speed in the opposite direction. When the learning direction was theon direction for simple-spike responses, learning was associated with statistically significant changes in simple-spike firing for 10 of 32 PCs. Of the 10 PCs that showed significant expressions of learning, 8 showed changes in simple-spike output in the expected direction: increased or decreased firing when eye acceleration increased or decreased through learning. There were no statistically significant changes in simple-spike responses or eye acceleration during pursuit in the control direction. When the learning direction was in the off direction for simple-spike responses, none of 15 PCs showed significant correlates of learning. Although changes in simple-spike firing were recorded in only a subset of PCs, analysis of the population response showed that the same relationship between population firing and eye acceleration obtained before and after learning. Thus learning is associated with changes that render the modified population response appropriate to drive the changed behavior. To analyze complex-spike firing during learning we correlated complex-spike firing in the second, third, and fourth 100 ms after the onset of target motion with the retinal image motion in the previous 100 ms. Data were largely consistent with previous evidence that image motion drives complex spikes with a direction selectivity opposite that for simple spikes. Comparison of complex-spike responses at different times after the onset of control and learning target motions in the learning direction implied that complex spikes could guide learning during decreases but not increases in eye acceleration. Learning caused increases or decreases in the sensitivity of complex spikes to image motion in parallel with changes in eye acceleration. Complex-spike responses were similar in all PCs, including many in which learning did not modify simple-spike responses. Our data do not disprove current theories of cerebellar learning but suggest that these theories would have to be modified to account for simple- and complex-spike firing of floccular Purkinje cells reported here.

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