Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"Spike sorting"”.
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On neural spike sorting with mixture models
… problem we are trying to solve is called neural spike sorting in literature. There are three basic objectives of spike sorting. The first is to estimate the number of neurons which contribute to the recorded neural data. The second is to identify the spikes, i.e. the little curves in the recorded …
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Methods for Ripple Detection and Spike Sorting During Hippocampal Replay
… This necessitates online algorithms for both spike sorting and ripple detection at low latencies. In my work, I have developed and tested an improved method for ripple detection and tested its performance against previous methods. Further, I have optimized a recently proposed spike sorting …
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A Bayesian Approach to Spike Sorting of Neural Data via Source Localization
… a novel mathematical algorithm for extracting spike data and positional information from extracellular electrophysiological neural recordings. By capturing the electrical signals emitted by individual neurons using a thin, conducting probe inserted into the brain of an animal, such recordings …
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A machine learning approach to spike sorting to reveal neuronal signalling defects in models of neurodegeneration
… complex neuronal signals, requiring precise spike sorting for meaningful data extraction. Nevertheless, conventional spike sorting methods face limitations in recognising diverse spike shapes, thereby constraining the full utilisation of the rich dataset acquired from MEA recordings. To …
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Ground truth in ultra-dense neural recording
… record neural activity with multi-electrodes, spike sorting-- the process of attributing spikes to particular neurons-- remains a challenge that typically requires human curation. Due to technical limitations, there have been very few multi-electrode recordings done in concert with techniques …
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Manipulations of spike trains and their impact on synchrony analysis
… from the noisy recordings (referred to as spike sorting) and assessing the significance of the synchrony. This dissertation addresses these issues with two complementary strategies, both founded on the manipulation of point processes under rigorous analytical control. On the one hand I …
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Neurons in Cat Primary Visual Cortex cluster by degree of tuning but not by absolute spatial phase or temporal response phase
… an algorithm that improves the performance of spike-sorting algorithms, for use in analyzing cells recorded using tetrodes. A cluster of spikes corresponding to a putative cell obtained through automatic or manual spike sorting algorithms may contain spikes from other cells with …
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Signal Modeling and Data Reduction for Wireless Brain-Machine Interfaces
… recordings for the validation of algorithms for spike detection and spike sorting. Having set up the geometry of the recording, each neuron is assigned a random spike waveforms from a library of experimentally obtained templates. The contribution of each neuron is generated by adding the …
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Latent variable models for hippocampal sequence analysis
… the case where we only have multiunit (unsorted) spikes. Indeed, spike sorting is challenging, time-consuming, often subjective (not reproducible), and throws away potentially valuable information from unsorted spikes, as well as our certainty about the cluster assignments. It has previously been …
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Variation resolutions for CMOS sensing networks
… associated signal analysis. We will illustrate a spike-sorting method to reliably classify the enteric neural signals which have unique waveform features but large variation in magnitude, timing and duration. The proposed fastDTW spike classification algorithm provides improvements in accuracy and …
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Integrating Biological and Artificial Neural Networks Processing on FPGAs
… and analysis of MEA-acquired signals featuring spike detection and spike sorting on 5,500 recording electrodes b) real-time emulation of a biologically-relevant spiking neural network counting 3,098 Izhikevich neurons and 9.6e6 synaptic interconnections c) real-time execution of spiking neural …
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Advanced Bioelectronic and Microphysiological Systems for Functional Studies of Stem Cell-Derived Neural Models
… electrophysiological analysis, integrating spike sorting, spectral decomposition, and network mapping across longitudinal measurements. Key findings include: • Material and substrate-related effects on 2D stem-cell-derived neuronal growth. • Tau-induced hyperexcitability and synaptic …
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The Automation of Electrophysiological Experiments and Data Analysis
… construction of a robust analysis tool called Spikepy. Whereas TEP is specially designed for the turtle preparation we have, Spikepy is a general-purpose spike-sorting application and framework. Spikepy takes flexibility to the extreme by being a plugin-based framework, yet maintaining a very …
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Mechanisms of Feedback in the Visual System
… a novel threshold for detecting neuronal spikes within a low signal-to-noise environment, as exists in the nucleus isthmi due to its high density of small neuronal cell bodies. Combining this threshold with a recently developed spike sorting procedure enabled us to extract simultaneous …
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Representation Learning on Large-Scale Neural and Healthcare Data: A Practitioner’s Perspective
… variations. Next, we propose a semi-automatic spike sorting algorithm to decompose multi-unit recordings into single-unit activities based on adversarial representation learning that can sort spikes from a small number of labeled examples, thereby mitigating the data-hungry limitation of …
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Reconfigurable System-on-Chip Architecture for Neural Signal Processing
… encoded in the rate of neuronal action potential spikes. Successful performance of a BMI system is tied to the efficiency of its individual processing elements such as spike detection, sorting and decoding. To achieve reliable operation, BMIs are equipped with hundreds of electrodes at the neural …
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A novel device for interrogation of neuron connectivity in acute brain slices
… data acquisition system and, through a robust spike sorting process, successfully identified individual neurons. Neuronal signals were then assessed for temporal and amplitude features to discriminate subtypes of neurons to indicate functional roles within the network. This data was then used …
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A Neural Signal Processor for Low-Latency Spike Inference
… in multi-electrode recordings, at single-spike resolution with low-latency. The system has two parts. The first is a Field-Programmable Gate Array (FPGA)-based Neural Signal Processor (NSP) that receives raw input and generates labelled spikes as output, a process referred to as real-time …
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Mechanisms of Multi-Object Working Memory and Motion Prediction in the Primate Brain
… recordings. This method improves spike-sorting results, helped us recover more neurons from our data, and we hope may help others make the most of their electrophysiology data as well.
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Acquisition systems and decoding algorithms of peripheral neural signals for prosthetic applications
… and performs as the best off-line algorithmfor spike clustering on a synthetic cortical dataset characterized by a reasonable dissimilarity between the spikemorphologies of different neurons. When the real-time requirements are joined to the fulfilment of area and power minimization for …
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