Neural Circuits for Navigation: Anatomy, Physiology, and Computational Methods

Course outline:
Dr. Eric Denovellis is a computational neuroscientist, whose work specializes on interpretable algorithms and tools to decode, categorize, and visualize neural representations, particularly in the hippocampal circuit. He is also the co-developer of an open-source neural data management and analysis platform built on a neural data standard, NeurodataWithoutBorders (NWB), and DataJoint. The course will be offered on-site at NCBS. Lectures will be held in person.

2 credit course (total contact hours: 20; total TA hours: 10)

Lecture 1: Hippocampal anatomy and physiology [1.5 hour] – Abhilasha
Lecture 2: Entorhinal cortex anatomy and physiology [1.5 hour] – Abhilasha
Lecture 3: Septo-hippocampal & septo-cortical connections [1.5 hour] – Abhilasha

Lecture 4-5-6-7/ Open data use and visualization [4 hours] – Abhilasha/Eric
- Common data standards in neuroscience and their use (NWB)
- Visualize and characterize LFP
- Visualize and characterize spikes
- Visualize and characterize properties of stimulus (position, sound, movement, etc)

Lecture 8-9-10-11/ Spectral properties of LFP [4 hours] – Abhilasha/Eric
- Signal filtering and preprocessing
- Bandpass filtering of neural data
- Power spectral density (PSD) and frequency-domain analysis
- Relating LFP rhythms to behavioural variables

Lectures 12-13-14-15/ Spike–Stimulus Analysis and Decoding [4 hours] – Eric
- Spike stimulus relationships
- Basic neural decoders 
- Clustered decoding approaches

Lectures 16-17-18-19/ Clusterless Decoding Approaches [4 hours] –Eric
- Decoding of continuous variable (eg, spatial position) from spiking activity
- Decoding discrete variables (e.g. value, choice) from spiking activity
- Assessing decoding accuracy and statistical confidence

Analysis project presentation – Abhilasha/Eric
- Final project presentation and assessment