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9.40  Intro to Neural Computation

Spring 2015

Instructors: Michale S Fee, Daniel Zysman

TAs: Gregory A. Ciccarelli, Benjamin Matthew Deen, Alexander J E Kell, Emily Lambert Mackevicius, Eduardo A Maury, Abra H Shen

Lecture:  TR10.30-12  (46-3002)        

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Announcements

Summer tutorials in computational neuroscience topics

Dear class,

This summer, I've organized a series of tutorials related to BCS topics. The tutorials are geared towards grad students and postdocs, but this class will have prepared you well, so you're definitely welcome to come if you're around. You can sign up here:

https://docs.google.com/forms/d/1MZ9xl6zSA6RgjVbOWfUuGisZgFzBY9obEudEOdTaaP4/viewform

Here is the information:

June 9th, 46-3189, 4pm-6pm: Bayesian methods, brain and cog perspectives
Taught by: Mehrdad Jazayeri, Josh Tenenbaum, Sam Gershman, Evan Remington, and Devika Narain

June 10th, 46-3189, 4pm-6pm: Learning in recurrent neural networks
Taught by: Larry Abbott

June 17th, 46-3189, 4pm-6pm: Learning in deep neural networks
Taught by: Phillip Isola

Each tutorial will consist of a short lecture, and then 'office hours' time to work through practice problems, and discuss problems people want help with in their own research. Food will be provided.

Also, see some of you at office hours tonight! (7pm, 46-5056)

Emily M.

Announced on 19 May 2015  9:56  a.m. by Emily Lambert Mackevicius

Office hours

Come to 46-4062 for office hours tonight at 7:30.

Announced on 23 February 2015  7:16  p.m. by Emily Lambert Mackevicius

Recitation 3

Recitation 3 is today! We will cover:

1. Integrate and fire, Activation curve, refractory period.
2. I-V curves, the role of voltage dependent conductances, basics of HH.

Review lecture notes and readings. We will be doing problems on the board this time (no MATLAB).

Announced on 18 February 2015  12:28  p.m. by Emily Lambert Mackevicius

Recitation 2 Instructions

Recitation 2 is tomorrow afternoon, and I've posted instructions under Materials>Recitation 2>Recitation 2 instructions.

Please read the instructions ahead of time, and remember to bring your laptop. We will be using MATLAB again.

If you have questions before recitation, please post on piazza.

Announced on 10 February 2015  2:07  p.m. by Emily Lambert Mackevicius

Rescheduled: Emily's brain lunch talk

My talk has been rescheduled to next Tuesday, February 17th @12pm in 46-3189. Lunch is provided. Here's the abstract:

Brain Lunch
Speaker: Emily Mackevicius, Fee Lab

TITLE: Aligning auditory and motor representations of syllable onsets in songbird vocal learning

ABSTRACT: How does the brain learn to produce complex sequences of behavior? Does it break them down into simpler pieces? How are behavioral goals represented, and translated into the actions that produce those goals? Songbirds learn to imitate the songs of tutors they heard as juveniles. Juvenile song starts off as unstructured babbling, then becomes more structured with the introduction of a stereotyped ‘protosyllable’. New syllables emerge through the differentiation of this protosyllable into multiple syllable types, until the song crystalizes into an adult song composed of 3-7 distinct syllables.

My work focuses on understanding how the brain of a young bird learns the motor commands for each new syllable it acquires. My recordings suggest that auditory and motor representations of song are both organized around syllables as units. Specifically, I have recorded in nucleus interface (NIf), a cortical region at the interface between the auditory and motor systems, and find NIf neurons burst at or just before the onsets of syllables both during singing and when juveniles are listening to their tutor song. Some NIf neurons are selective for particular syllable types. By aligning to syllable onsets, NIf could “chunk” songs into syllables each of which is accessible as a discrete unit in both auditory and motor representations. I have analyzed the role of NIf in the emergence of motor programs for new syllable types in downstream premotor circuits, and suggest a simple mechanism by which timing learned in one domain (listening to a tutor) could be transferred to support learning in a new domain (singing). I will describe both experimental and modeling results.

Announced on 05 February 2015  1:08  p.m. by Emily Lambert Mackevicius

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