Hierarchical estimation of neural activity through explicit identification of temporally synchronous spikes

Veerabhadrappa, Rakesh; Bhatti, Asim; Berk, Michael; Tye, Susannah J.; Nahavandi, Saeid

doi:10.1016/j.neucom.2016.09.135

Cited by 7 publications

(7 citation statements)

References 25 publications

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“…Mcd files are then converted into txt files (MC_Data tool, MultiChannel System, Reutlingen, Germany) and analyzed by NeuroSigX. The NeuroSigX software uses novel spike sorting and data analysis algorithms to explore the neural spike activity and spatio-temporal behavior of the neuronal network [ 37 , 38 ]. A threshold of 22 μV is employed to maintain the analytical consistency between the preliminary analysis by MC_Rack software and analysis by NeuroSigX.…”

Section: Methodsmentioning

confidence: 99%

Zika virus-induced hyper excitation precedes death of mouse primary neuron

Gaburro

Bhatti

Sundaramoorthy

et al. 2018

Virol J

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BackgroundZika virus infection in new born is linked to congenital syndromes, especially microcephaly. Studies have shown that these neuropathies are the result of significant death of neuronal progenitor cells in the central nervous system of the embryo, targeted by the virus. Although cell death via apoptosis is well acknowledged, little is known about possible pathogenic cellular mechanisms triggering cell death in neurons.MethodsWe used in vitro embryonic mouse primary neuron cultures to study possible upstream cellular mechanisms of cell death. Neuronal networks were grown on microelectrode array and electrical activity was recorded at different times post Zika virus infection. In addition to this method, we used confocal microscopy and Q-PCR techniques to observe morphological and molecular changes after infection.ResultsZika virus infection of mouse primary neurons triggers an early spiking excitation of neuron cultures, followed by dramatic loss of this activity. Using NMDA receptor antagonist, we show that this excitotoxicity mechanism, likely via glutamate, could also contribute to the observed nervous system defects in human embryos and could open new perspective regarding the causes of adult neuropathies.ConclusionsThis model of excitotoxicity, in the context of neurotropic virus infection, highlights the significance of neuronal activity recording with microelectrode array and possibility of more than one lethal mechanism after Zika virus infection in the nervous system.Electronic supplementary materialThe online version of this article (10.1186/s12985-018-0989-4) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Zika virus-induced hyper excitation precedes death of mouse primary neuron

Gaburro

Bhatti

Sundaramoorthy

et al. 2018

Virol J

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“…Raw extracellular recordings comprise of low frequency component (100–300 Hz, Quiroga et al, 2004 ) reflecting transmembrane activity from a population of neurons referred to as local field potential Figures 1A,B and short lived component (3–3.2 ms, Prentice et al, 2011 ; Veerabhadrappa et al, 2017 ) reflecting activity from a neuron or single units referred to as action potentials Figures 1A,B or spikes (Gold et al, 2006 ). To facilitate further analyses related to deciphering activities in the brain, extracting and sorting of spikes referred to as spike sorting is an essential process.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1 shows an overview of the spike sorting algorithm. In general, the spike sorting procedures (Lewicki, 1998 ; Quiroga et al, 2004 ; Prentice et al, 2011 ; Ekanadham et al, 2014 ; Rey et al, 2015 ; Niediek et al, 2016 ; Rossant et al, 2016 ; Veerabhadrappa et al, 2017 ) involve pre-filtering of raw voltage signals to remove field potential ( Figures 1A,B ), detection and extraction of spike events using standard thresholding techniques ( Figure 1C ), representation of spike waveforms by features, such as wavelets (Quiroga et al, 2004 ) or principal component analysis (PCA) (Rossant et al, 2016 ), and identification of unique clusters ( Figure 1D ).…”

Section: Introductionmentioning

confidence: 99%

Compatibility Evaluation of Clustering Algorithms for Contemporary Extracellular Neural Spike Sorting

Veerabhadrappa

Hassan

Zhang

et al. 2020

Front. Syst. Neurosci.

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Deciphering useful information from electrophysiological data recorded from the brain, in-vivo or in-vitro, is dependent on the capability to analyse spike patterns efficiently and accurately. The spike analysis mechanisms are heavily reliant on the clustering algorithms that enable separation of spike trends based on their spatio-temporal behaviors. Literature review report several clustering algorithms over decades focused on different applications. Although spike analysis algorithms employ only a small subset of clustering algorithms, however, not much work has been reported on the compliance and suitability of such clustering algorithms for spike analysis. In our study, we have attempted to comment on the suitability of available clustering algorithms and performance capacity when exposed to spike analysis. In this regard, the study reports a compatibility evaluation on algorithms previously employed in spike sorting as well as the algorithms yet to be investigated for application in sorting neural spikes. The performance of the algorithms is compared in terms of their accuracy, confusion matrix and accepted validation indices. Three data sets comprising of easy, difficult, and real spike similarity with known ground-truth are chosen for assessment, ensuring a uniform testbed. The procedure also employs two feature-sets, principal component analysis and wavelets. The report also presents a statistical score scheme to evaluate the performance individually and overall. The open nature of the data sets, the clustering algorithms and the evaluation criteria make the proposed evaluation framework widely accessible to the research community. We believe that the study presents a reference guide for emerging neuroscientists to select the most suitable algorithms for their spike analysis requirements.

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“…Mcd files are then converted into txt files (MC_Data tool, MultiChannel System, Reutlingen, Germany) and analyzed by NeuroSigX. The NeuroSigX software uses novel spike sorting and data analysis algorithms to explore the neural spike activity and spatio-temporal behavior of the neuronal network 59 . A threshold of 22 µV is employed to maintain the analytical consistency between the preliminary analysis by MC_Rack software and analysis by NeuroSigX.…”

Section: Methodsmentioning

confidence: 99%

Neurotropism and behavioral changes associated with Zika infection in the vector Aedes aegypti

Gaburro

Bhatti

Harper

et al. 2018

Emerging Microbes & Infections

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Understanding Zika virus infection dynamics is essential, as its recent emergence revealed possible devastating neuropathologies in humans, thus causing a major threat to public health worldwide. Recent research allowed breakthrough in our understanding of the virus and host pathogenesis; however, little is known on its impact on its main vector, Aedes aegypti. Here we show how Zika virus targets Aedes aegypti’s neurons and induces changes in its behavior. Results are compared to dengue virus, another flavivirus, which triggers a different pattern of behavioral changes. We used microelectrode array technology to record electrical spiking activity of mosquito primary neurons post infections and discovered that only Zika virus causes an increase in spiking activity of the neuronal network. Confocal microscopy also revealed an increase in synapse connections for Zika virus-infected neuronal networks. Interestingly, the results also showed that mosquito responds to infection by overexpressing glutamate regulatory genes while maintaining virus levels. This neuro-excitation, possibly via glutamate, could contribute to the observed behavioral changes in Zika virus-infected Aedes aegypti females. This study reveals the importance of virus-vector interaction in arbovirus neurotropism, in humans and vector. However, it appears that the consequences differ in the two hosts, with neuropathology in human host, while behavioral changes in the mosquito vector that may be advantageous to the virus.

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Hierarchical estimation of neural activity through explicit identification of temporally synchronous spikes

Cited by 7 publications

References 25 publications

Zika virus-induced hyper excitation precedes death of mouse primary neuron

Zika virus-induced hyper excitation precedes death of mouse primary neuron

Compatibility Evaluation of Clustering Algorithms for Contemporary Extracellular Neural Spike Sorting

Neurotropism and behavioral changes associated with Zika infection in the vector Aedes aegypti

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