Calibrated inference of spiking from calcium ΔF/F data using deep networks

Robust Offline Spike Sorter

Python implementation of signal processing techniques and K-means clustering to sort spikes.

SpikeAgent is a multimodal LLM-based AI agent that automates and standardizes the spike sorting pipeline

NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch

Software for high density electrophysiology

Set traps, catch bad frames. Enhanced Unity CPU profiler with spike detection, selective frame capture, and pluggable filters.

A retail analytics capstone that converts transactions into a calendar intelligence system. It quantifies day-of-week and monthly seasonality, builds a baseline expected revenue model, detects event-like spike days using robust residual z-scores, and explains spikes via transactions, units, AOV, and category mix, with a Streamlit dashboard+exports.

Download Data from https://bit.ly/3g8RUmi

Python Jupyter notebook for Neuralink Patent No. US 2021/0012909 A1, titled "Real-Time Neural Spike Detection"

PASER: Processing and Analysis Schemes for Extracellular Recordings

This repository contains extensive tools and scripts for processing and analyzing neurophysiological signals. The primary focus is on various critical aspects of neurophysiological data handling, including spike detection, feature extraction, clustering, and firing rate analysis.

UK day-ahead electricity price prediction using weather-driven renewables forecasting + ML (XGBoost/SVR), including spike detection + battery arbitrage evaluation.

[TNSRE-2021] Official implementation of "A Unified Optimization Model of Feature Extraction and Clustering for Spike Sorting"

Simulates and analyzes brain signal data using NumPy. Pure Python project focused on data logic and signal patterns.

Quantal analysis for autocalibration of inferred spike rates from calcium imaging

Version-0 >> A Python-based network monitoring tool that logs traffic, detects spikes or high usage, stores data in MySQL, and sends email alerts when thresholds are exceeded.

Neural network-based approach for detecting spikes in high-density neural data using Multi-Layer Perceptron models

Digital Signal Processing in Electroencephalography signals. Spike detection with threshold method and isolation with windowing. Temporal and spectral feature extraction. Classification in three neurons.

ML workflow designed for processing neurophysiological MEA data