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Neural Signal Processing Are you in the right room? •  How does the brain represent and process informa<on? •  How can we (experimenters) process and understand the signals that we record from the brain? introduc<ons •  Instructors Jacob Robinson – “Nano-­‐Neuro-­‐Naut” (devices interfacing with neural circuits) Caleb Kemere – “Rat-­‐Wrangler” (decoding/interac<ng with neurons in animals) •  Course Asst. Paul Haugen prerequisites •  Excitement about the brain •  Basic probability, (random processes) •  Linear algebra (comfortable with matrix/
vector mul<plica<on and concepts) •  Matlab or other programming Beware – it will get harder! syllabus • 
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Office hours Websites Textbooks Expecta<ons: –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours Websites Textbooks Expecta<ons: Prof. Kemere – MW 9-­‐10 AM Prof. Robinson – TuTh 10:50-­‐11:50 AM also by appointment! –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy 2046 –  Absences – s<ll responsible 2026 syllabus • 
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Office hours Websites Textbooks Expecta<ons: DSP website – assignments, lecture notes Owlspace – “closed” content, data sets, forums, e-­‐submission of HW –  Grading Note -­‐ if you’re not enrolled, we need to give you owlspace access!! –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours Websites Textbooks Expecta<ons: –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours 10% -­‐ Homework (about 8) 50% -­‐ Mid-­‐term Exams Websites 40% -­‐ Final Exam Textbooks ExpectaDons: –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours Turned in by 5pm on due date (late policy). Websites Submit scanned assignment on Textbooks owlspace or paper version to ExpectaDons: Prof. Robinson’s office. –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours HW – work in groups, but everyone turns in their own Websites copy. Textbooks Exams – per-­‐exam policy ExpectaDons: (honor code!) –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – s<ll responsible syllabus • 
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Office hours Websites Textbooks ExpectaDons: –  Grading –  Homework (where/when) –  Exams –  Co-­‐working policy –  Absences – you’re responsible Other classes of interest • 
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Fund. of Cellular/Molecular Neuro (BIOC 3/585) Theore<cal Neuroscience I & II (CAAM 415 & 416) Fund. Nerve and Muscle Electrophys. (ELEC 481) Sensory Neuroengineering (BIOE 4/592) Neural Networks and Informa<on Theory (ELEC 502) Other neuro @ BCM Data Mining and Sta<s<cal Learning (STAT 640) Sta<s<cal Machine Learning (COMP 540) Computer Vision (ELEC 547) ELEC 548 Lecture 1, part 2 Fundamental neurobiology and experimental methods Clerical issues •  Printed slides •  Technology policy Not ok for class Ok for class Real-­‐<me feedback? Coursework? Research experience? What is Neural Signal Processing? ? What is Neural Signal Processing? •  How does the brain represent and process informa<on? •  How can we (experimenters) process and understand the signals that we record from the brain? What can you expect to learn: Part 1 How does the brain represent and process informaOon? The organiza<on of the brain & its components How do the cells within the brain represent and transmit informa<on? Origins of electrical poten<als within cells Modeling a neuron Hodgkin-­‐Huxley model Neurons transmit signals intracellularly by ac<on poten<als Patch clamp Neurons display diverse behavior Neurons transmit signals to other neurons Electrical Synapse Chemical synapse How Does a Neuron Integrate Information?
Synaptic input
Threshold
Integrated inputs
Action potentials
How the brain changes Short Term Plas<city Long Term Plas<city Mechanisms of synap<c plas<city Homeosta<c plas<city Experimental Methods Throughout the course, we will briefly introduce experimental methods used to study cellular and molecular neuroscience •  Electrophysiology •  Imaging •  Gene<c Techniques Big Picture •  Why do “Neural Signal Processing” –  Assis<ve/repara<ve –  Interven<onal/treatment –  Pharmacology development –  Neuromorphic systems/circuits –  Basic science •  What is neural signal processing, actually? assis<ve interven<onal pharmacology neuromorphic Neural Signal Processing IRL braingate memory traces Deep brain s<mula<on canabinoid example Robbe, Buzsaki 2009 SpiNNaker project •  Asynchronous-­‐connected chips model ~1000 neurons ea.. Connect 50,000 chips together? hnp://spectrum.ieee.org/compu<ng/hardware/lowpower-­‐chips-­‐to-­‐model-­‐a-­‐billion-­‐neurons Neural Signal Processing, Actually “Encoding” model => “Decoding” algorithm Kalman Filter: hand posiOon (gaussian) neural signals (gaussian)