This topic brings together methods for analyzing and visualizing local field potentials (LFPs) alongside spike and behavioral data. You will learn how spectral analysis, current source density (CSD) analysis, and spike-field coherence can reveal complementary aspects of population-level neural activity. Using real-world, multi-area Neuropixels recordings, you will connect the foundations of signal processing to practical Python workflows for preprocessing and visualizing signals, synchronizing data streams, and investigating interactions across brain areas.
Expected and helpful background knowledge for joining an event on this topic.
Local field potentials (LFPs) are extracellular voltage signals generated by the combined transmembrane currents of neuronal populations. Their interpretation depends on understanding how recording conditions, preprocessing choices, and nearby neural processes shape the signal. This topic connects LFP analysis with spike and behavioral data.
Reliable LFP analysis requires attention to signal quality, neurophysiological interpretation, and reproducible computation. Filtering choices, line noise, synchronization, reference schemes, and behavioral alignment all influence power spectra and coherence estimates. This topic connects analytical methods with the practical checks needed to interpret results with confidence.
For this approach, familiarity with Python and Jupyter notebooks is required. Consult the event page for its specific setup and requirements.
Using real-world, multi-area Neuropixels recordings and simulations, you will explore spectral analysis, current source density (CSD) analysis, and spike-field coherence. Practical examples use scientific Python libraries such as NumPy, SciPy, Pandas, Elephant and LFPy to preprocess and synchronize data streams. You will use Matplotlib to create clear, interpretable visualizations of raw traces, power spectra, CSD maps, and spike-field relationships while examining how plotting choices influence interpretation.
Explore upcoming dates and details from previous events.
This four-week online course covers the analysis and interpretation of local field potentials with Python, including current source density, filtering, spectral decomposition, …
An introduction to Python, Numpy, Matplotlib, and Pandas
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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
Open-source Python package for exploring, visualizing, and analyzing MEG and EEG data
Libraries · Teaching
1 topics with recorded teaching · 3 recorded and scheduled offerings
MNE-Python provides a comprehensive, well-documented toolkit for processing electrophysiological data. It handles the full analysis pipeline from raw recordings to publication-ready results, with strong support for time-frequency analysis, source localization, and connectivity measures.
Recorded in topic offerings; consult the dated event links for availability.
2 past offerings · 1 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Local Field Potential (LFP) Analysis(M)EEG 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
Record and reproduce the software environment used for an analysis or application.
Practices · Teaching
0 topics with recorded teaching · 0 recorded and scheduled offerings
Declared dependencies and lock files help collaborators rerun analyses and distinguish environment changes from changes in scientific results.
Covered through our computing environment and research workflow 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 DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsCalcium Imaging AnalysisDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) AnalysisMachine LearningRobust and Reusable Software
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
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 library for simulating extracellular potentials and related brain signals from multicompartment neuron models
Libraries · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
LFPy connects multicompartment NEURON models with predictions of extracellular potentials and other observable signals. It is worth exploring when an analysis needs to relate cellular or network activity to simulated electrode measurements while keeping the biophysical assumptions explicit.
Recorded in a scheduled local-field-potential offering; consult the dated event link for availability.
0 past offerings · 1 upcoming offerings
Related themes: Neural Data Analysis
Related topics: Local Field Potential (LFP) 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
Statistical functions and probability distributions from SciPy's stats module.
Libraries · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
SciPy Stats provides a broad, scriptable foundation for distributions, statistical tests, random variables, and summary statistics used throughout scientific Python workflows.
Recorded in topic offerings; consult the dated event links for availability.
0 past offerings · 1 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: Arrays and Numerical ComputingDataframes and StatisticsLocal Field Potential (LFP) Analysis(M)EEG Analysis
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