ECBM E6070 Topics in Neuroscience and Deep Learning: Computing with Brain Circuits of Model Organisms
| Lecturer: | Professor Aurel A. Lazar | |
| Office hours: | Tuesdays, 4:00 - 6:00 PM, EST, online | |
| E-mail address: | tab "at" ee.columbia.edu | |
| Class Web Site: | Offered by CourseWorks | |
| TA/CA: | Bruce Yi Bu and Shashwat Shukla | |
| Office hours: | Thursdays, 7:00 PM - 8:00 PM (Subject to Change), EST, Online | |
| E-mail address: | tba "at" columbia.edu | |
| Day and Time: | Mondays, 7:00 PM - 9:30 PM | |
| Class Location: | 614 Schermerhorn Hall | |
| Credits for course: | 3 points | |
| PREQ: | A course in computational neuroscience (e.g., BMEB W4020) or deep learning (e.g., ECBM E4040). Extensive Python programming experience or the instructor’s approval. Prior exposure to interactive computing (e.g., JupyterLab) and parallel programming (e.g., PyCUDA) is a plus. | |
| Description: | The Functional Map of the Fruit Fly Brain Modeling the brain of model organisms with an emphasis on the fruit fly. The Fruit Fly Brain Observatory. Structural modeling of the Drosophila brain using cell-type, connectome, synaptome and activity maps with BrainMapsViz. Building the functional map and accelerating the discovery of the functional logic of the Drosophila brain with FlyBrainLab. From Sensory Coding in Early Vision to Directing Movement Pathways and Circuits of the Early Visual System. Phototransduction and Spatio-Temporal Encoding in the Drosophila Retina. Contrast Gain Control in the Photoreceptor and Amacrine Cell Layer. Canonical Motion Detection Circuits. The Functional Role of the Central Complex. Canonical Navigation Circuits in the Central Complex. From Odorant Transduction to Learning and Memory in Early Olfaction Pathways and Circuits of the Early Olfactory System. Odorant Transduction and Combinatorial Encoding in the Drosophila Antenna. Predictive Coding in the Antennal Lobe. The Functional Role of the Mushroom Body. Canonical Circuits for Associative Learning and Memory in the Mushroom Body. Projects in Computing with Brain Circuits Two projects based on material covered in [1] From Sensory Coding in Early Vision to Directing Movement, and [2] From Odorant Transduction to Learning and Memory in Early Olfaction. |
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| RCMD Text(s): | Lectures Notes (slides, chapters) will be made available on CourseWorks.
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| Logistics: | Students will complete homework assignments and projects in teams of up to 2 members. | |
| Homework: | 6 assignments, mostly writing Python code for execution on CPUs or executing already implemented Python code modules on GPUs. | |
| Paper(s): | --- | |
| Projects: | 2 individual projects (see above) | |
| Midterm Exam: | --- | |
| Final Exam: | --- | |
| Grading: | The homework grade is based on the average of the best 5 out of 6 assignments. The final grade has 3 components: 1/5 homework, 2/5 project #1 and 2/5 project #2. | |
| Hardware REQS: | Laptop for demos. | |
| Software REQS: | Fruit Fly Brain Observatory Resources | |
