This topic explores how spike trains can be extracted, measured, and modeled from neuronal recordings. You will learn to investigate the firing patterns of individual neurons and neural populations using raster plots, peristimulus time histograms, cross-correlograms, Poisson-based generative models, and coherence-based analyses. Using real and simulated electrophysiological data, you will connect the foundations of spike analysis to practical workflows for filtering, peak detection, clustering, and spike sorting with the scientific Python ecosystem.
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How do we extract, measure, and model spike trains from neuronal recordings? Using real and simulated electrophysiological data, you will investigate the firing patterns of individual neurons and neural populations. You will explore descriptive techniques such as raster plots, peristimulus time histograms (PSTHs), and cross-correlograms, alongside statistical approaches including Poisson-based generative models and coherence-based analyses.
Spike analysis turns raw voltage traces into interpretable measurements of neural activity, so every step matters: filtering, detection, sorting, quality control, alignment, summary statistics, and modeling. Early processing decisions affect raster plots, PSTHs, cross-correlograms, and population-level interpretations. This topic connects an intuitive understanding of the methods with reproducible Python workflows.
For this approach, familiarity with Python and Jupyter notebooks is required. Consult the event page for its specific setup and requirements.
Practical examples use Python’s scientific stack (NumPy, SciPy, Pandas, and Scikit-learn) and neuroscience-specific tools to connect these methods to experimental data. You will simulate neurons using NEST, learn to organize electrophysiological data with Neo and analyze them with the Elephant toolbox. You will also work with the EBRAINS Collaboratory cloud environment to explore the full spike analysis pipeline, including filtering, peak detection, clustering based on principal component analysis (PCA), and spike sorting, using both first-principles implementations and established workflows from SpikeInterface.
Explore upcoming dates and details from previous events.
This four-week online course covers the visualization and analysis of spike trains with Python, including their variability and correlations, as well as spike sorting and …
Learn to simualte, extract and analyze and neural spiking data using Python's core scentific stack as well as neuroscience-specific libraries in a hand-on 3-day workshop.
Supporting high school students with data analysis workshops and research mentoring for Germany's premier neuroscience competition.
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Check important behavior automatically so research code can be changed with confidence.
Practices · Teaching
0 topics with recorded teaching · 0 recorded and scheduled offerings
Tests make scientific assumptions and expected behavior explicit, and help catch regressions as analysis code develops.
Covered in our robust software and AI-assisted development topics; individual offerings are not yet attributed to this practice.
0 past offerings · 0 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentMachine Learning(M)EEG AnalysisNeural Spike AnalysisRobust and Reusable Software
Check the shape, types, units, and assumptions of research data before using it.
Practices · Teaching
0 topics with recorded teaching · 0 recorded and scheduled offerings
Explicit validation turns data assumptions into checks that can catch missing values, inconsistent metadata, and unexpected inputs before analysis.
Covered through data organization and robust software topics; individual offerings are not yet attributed to this practice.
0 past offerings · 0 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: Programming and Data AcquisitionAI-Assisted Software DevelopmentArrays and Numerical ComputingCalcium Imaging AnalysisDataframes and StatisticsLocal Field Potential (LFP) AnalysisMachine Learning(M)EEG AnalysisNeural Spike AnalysisRobust and Reusable Software
Comprehensive library for creating static, animated, and interactive visualizations
Libraries · Teaching
6 topics with recorded teaching · 19 recorded and scheduled offerings
Matplotlib is the foundational plotting library for Python, offering complete control over every aspect of your figures. It's publication-ready out of the box and integrates seamlessly with NumPy and Pandas, making it essential for visualizing research data.
Recorded in topic offerings; consult the dated event links for availability.
15 past offerings · 4 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) Analysis(M)EEG AnalysisNeural Spike Analysis
The fundamental package for scientific computing with Python
Libraries · Teaching
8 topics with recorded teaching · 26 recorded and scheduled offerings
NumPy is the foundation of the scientific Python ecosystem. It provides powerful n-dimensional array objects and tools for working with these arrays. Nearly every scientific Python package builds on NumPy, making it essential for data analysis, numerical computing, and scientific research.
Recorded in topic offerings; consult the dated event links for availability.
21 past offerings · 5 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingCalcium Imaging AnalysisDataframes and StatisticsLocal Field Potential (LFP) AnalysisMachine Learning(M)EEG AnalysisNeural Spike AnalysisRobust and Reusable Software
Standardized format for neuroscience data sharing and archival
Data formats · Not currently taught
0 topics with recorded teaching · 0 recorded and scheduled offerings
NWB is the emerging standard for neuroscience data sharing, required by many NIH BRAIN Initiative grants. It provides a unified format for diverse data types (ephys, imaging, behavior) with rich metadata, enabling tool interoperability and compliance with FAIR principles.
Relevant to the topic landscape; no explicit recorded offering is currently attributed to this item.
0 past offerings · 0 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Calcium Imaging AnalysisLocal Field Potential (LFP) Analysis(M)EEG AnalysisNeural Spike Analysis
Powerful data analysis and manipulation library for Python
Libraries · Teaching
5 topics with recorded teaching · 16 recorded and scheduled offerings
Pandas provides intuitive data structures (DataFrames) for working with tabular data, making it easy to clean, analyze, and visualize datasets. It's the go-to tool for exploratory data analysis and handling experimental results in research.
Recorded in topic offerings; consult the dated event links for availability.
14 past offerings · 2 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsDataframes and StatisticsLocal Field Potential (LFP) AnalysisNeural Spike Analysis
General-purpose programming language widely used for scientific computing and research software.
Languages & frameworks · Teaching
10 topics with recorded teaching · 33 recorded and scheduled offerings
Python combines a readable language with a mature scientific ecosystem, making it a practical default for research data analysis, automation, and teaching.
Recorded in topic offerings; consult the dated event links for availability.
26 past offerings · 7 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: Programming and Data AcquisitionAI-Assisted Software DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsCalcium Imaging AnalysisDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) AnalysisMachine Learning(M)EEG AnalysisNeural Spike AnalysisRobust and Reusable Software
Machine learning library for Python with tools for classification, regression, clustering, and dimensionality reduction
Libraries · Teaching
3 topics with recorded teaching · 6 recorded and scheduled offerings
Scikit-learn provides a consistent, easy-to-use interface for machine learning in Python. It's perfect for analyzing neuroscience data: clustering neurons, reducing dimensionality of neural responses, and classifying behavioral states.
Recorded in topic offerings; consult the dated event links for availability.
4 past offerings · 2 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentMachine Learning(M)EEG AnalysisNeural Spike Analysis
Scientific computing library providing optimization, signal processing, and statistical functions
Libraries · Teaching
5 topics with recorded teaching · 14 recorded and scheduled offerings
SciPy builds on NumPy to provide a comprehensive collection of algorithms for scientific computing. Its signal processing tools are essential for analyzing neural recordings, while its optimization and statistical functions support data analysis and modeling across neuroscience research.
Recorded in topic offerings; consult the dated event links for availability.
9 past offerings · 5 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingCalcium Imaging AnalysisLocal Field Potential (LFP) AnalysisMachine Learning(M)EEG AnalysisNeural Spike Analysis
Unified framework for spike sorting and electrophysiology analysis integrating multiple spike sorters
Libraries · Teaching
1 topics with recorded teaching · 3 recorded and scheduled offerings
SpikeInterface provides a single, unified interface to run and compare multiple spike sorting algorithms. It standardizes the spike sorting workflow from preprocessing through quality metrics, making it easier to process extracellular recordings.
Recorded in topic offerings; consult the dated event links for availability.
2 past offerings · 1 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentNeural Spike Analysis
Cloud workspace for collaborative neuroscience projects, combining hosted JupyterLab, shared storage, documentation, and communication services
Tools & platforms · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
The EBRAINS Collaboratory combines hosted JupyterLab, shared storage, documentation, and team management in workspaces designed for neuroscience. It is worth exploring when a course or project needs a shared cloud environment with direct access to EBRAINS tools and resources.
Recorded in scheduled neuroscience offerings; consult the dated event links for availability.
0 past offerings · 1 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Calcium Imaging AnalysisNeural Spike Analysis
Electrophysiology analysis toolkit for spike train analysis, LFP processing, and neural data statistics
Libraries · Teaching
2 topics with recorded teaching · 5 recorded and scheduled offerings
Elephant provides a comprehensive suite of analysis methods specifically designed for electrophysiology data. It handles spike trains, continuous signals, and their relationships with proper units and data structures, making complex analyses reproducible and standardized.
Recorded in topic offerings; consult the dated event links for availability.
3 past offerings · 2 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentLocal Field Potential (LFP) AnalysisNeural Spike Analysis
Python package for working with electrophysiology data, providing common data structures and I/O for various formats
Libraries · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Neo provides standardized data structures for electrophysiology that bridge different recording systems and analysis tools. It handles metadata, units, and relationships between data types, making your analysis code more portable and maintainable.
Recorded in topic offerings; consult the dated event links for availability.
1 past offerings · 0 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Calcium Imaging AnalysisLocal Field Potential (LFP) Analysis(M)EEG AnalysisNeural Spike Analysis
Fast DataFrame library with eager and lazy APIs for tabular data processing.
Libraries · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Polars is useful when tabular workflows need more speed, lower memory use, or lazy query planning while remaining approachable for Python users.
Recorded in topic offerings; consult the dated event links for availability.
1 past offerings · 0 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: Dataframes and StatisticsNeural Spike AnalysisRobust and Reusable Software
Python package for handling probe layouts and channel configurations in electrophysiology
Libraries · Not currently taught
0 topics with recorded teaching · 0 recorded and scheduled offerings
ProbeInterface provides a standardized way to describe electrode probe geometries (Neuropixels, tetrodes, etc.). It handles the complex spatial layouts and wiring of modern high-density probes, making it easier to visualize and analyze multi-channel recordings.
Relevant to the topic landscape; no explicit recorded offering is currently attributed to this item.
0 past offerings · 0 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Neural Spike Analysis
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