information bottleneck
for Temporal Binding
An open source software package for the information theoretic analysis of neural data
This tool helps neuroscientists understand how neural systems process and transmit information by leveraging principles from information theory.
NeuroInfoAnalytics is an advanced software package designed for the precise information-theoretic analysis of neural data. By leveraging cutting-edge computational methods, our platform empowers researchers to decode the intricate communication and computational strategies of neural systems.
Why Choose NeuroInfoAnalytics?
Rigorous Information-Theoretic Framework:
Measure neural encoding, transmission, and decoding processes using Shannon entropy, mutual information, and other robust metrics.
Customizable Data Pipelines:
Seamlessly analyze spike trains, local field potentials, and other neural signals across various experimental paradigms.
Multi-Dimensional Analysis:
Unlock insights into temporal, spatial, and population-level dynamics of neural data.
User-Friendly Interface:
Accessible tools for neuroscientists at all levels, from intuitive GUI-based workflows to scriptable APIs for advanced users.
Applications:
- Sensory Coding: Understand how neural circuits encode environmental stimuli.
- Brain-Computer Interfaces (BCI): Optimize neural signal interpretation for enhanced control.
- Neuroinformatics: Integrate with existing data repositories and computational pipelines.
- Neurodegenerative Disease Research: Investigate disruptions in neural communication.
The tool is based on the Information Bottleneck (IB) principle, which aims to compress input data while preserving relevant information about the output.
It identifies optimal trade-offs between compression (reducing data complexity) and prediction (retaining essential features for accurate outputs).
ibTB specializes in analyzing temporal dynamics in neural data, making it suitable for time-series data from neuroscience experiments, like EEG or spike trains.
It assesses how neural signals are temporally organized to encode information about external stimuli or internal states.
