An Introduction to Drosophila Neuroscience (Lecture 1) by Katherine Nagel

PROGRAM

ICTP-ICTS WINTER SCHOOL ON QUANTITATIVE SYSTEMS BIOLOGY (ONLINE)

ORGANIZERS
Vijaykumar Krishnamurthy (ICTS-TIFR, India), Venkatesh N. Murthy (Harvard University, USA), Sharad Ramanathan (Harvard University, USA), Sanjay Sane (NCBS-TIFR, India) and Vatsala Thirumalai (NCBS-TIFR, India)

DATE: 06 December 2021 to 17 December 2021

VENUE: Online

How organisms sense the world and generate behaviors is an exciting question that has motivated neuroscientists over more than a century. Neural command for generating behavioral output arises from operations at multiple scales, ranging from the flip-flops of ion channels to dynamics in circuits comprising ensembles of neurons. New tools to genetically manipulate organisms, monitor and perturb neural activity, and advanced microscopy that enables large scale imaging of neurons in vivo have yielded a hitherto unprecedented quantum of data with high resolution. Quantitative approaches are needed to mine these data sets for generating testable hypotheses regarding nervous system function.

This is the tenth school in the series on Quantitative Systems Biology, held alternately at Trieste and Bangalore. The school responds to the strong need, especially at the Ph.D. and postdoc level, for providing scientists with a broad exposure to quantitative problems in the study of living systems. The audience will range from Ph.D. students to young faculty, who either work in this area or plan to do so.

QSB2021 is focussed on Sensori-motor control. The aim of this School is to expose students from different backgrounds to the latest research in systems neuroscience, with an emphasis on the usage of quantitative methods and theory. We will begin the workshop with a brief introduction to neuroscience, including electrical properties of neuronal membranes and single neuronal biophysics. With this foundation in place, we will delve into how circuit dynamics emerge in diverse circuits using invertebrate and vertebrate model organisms as examples. We will cover questions in population coding, variability and stochasticity, and plasticity. We will then introduce students to applications of quantitative tools to neuroscience data sets such as whole-brain imaging data sets or behavioral clustering data sets. Throughout, we will also explore how theory can contribute to a normative understanding of various phenomena, and motivate future experiments.

Scientists and students from all over the world can apply for the School. Researchers from developing countries are particularly encouraged to apply. As the program will be conducted in English, participants should have an adequate working knowledge of this language. There is no registration fee.


SCIENTIFIC ORGANISING COMMITTEE
1. Venkatesh N. Murthy (Harvard University, USA)
2. Sharad Ramanathan (Harvard University, USA)
3. Sanjay P. Sane (NCBS, India)
4. Vatsala Thirumalai (NCBS, India)


SCIENTIFIC ADVISORY COMMITTEE
1. Vijay Balasubramaniam (University of Pennsylvania, USA)
2. Upinder Bhalla (NCBS, India)
3. Antonio Celani (ICTP, Italy)
4. Sanjay Jain (University of Delhi, India)
5. Vijaykumar Krishnamurthy (ICTS, India) (Local organizer)
6. Matteo Marsili (ICTP, Italy)
7. Mukund Thattai (NCBS, India)


Previous editions of this school

2020
2019
2018
2017
2016
2015
2014
2013
2012

CONTACT US: [email protected]
PROGRAM LINK: https://www.icts.res.in/program/qsb2021

Table of Contents (powered by https://videoken.com)
0:02:49 Quantitative high throughput and single fly behaviors
0:04:41 Compact genome
0:05:47 Fast reproduction time
0:08:45 Modular expression systems
0:10:51 Driver line libraries
0:15:09 Effector libraries
0:18:53 Sophisticated developmental tools
0:20:48 Connectomics
0:22:55 An example: From odor encoding to odor learning
0:29:18 Olfaction is a major cue for insects
0:31:51 How do olfactory neurons detect odor molecules?
0:33:15 Each odor is represented by a different pattern of receptor neuron activation
0:35:15 Different smells produce different patterns of brain activation
0:36:40 The mushroom body is required for learned but not innate odor avoidance
0:38:13 The mushroom body maps odor inputs onto motor outputs
0:42:32 Some mushroom body outputs drive attraction and others drive aversion
0:44:06 Each output neuron is modulated by its own dopamine neuron
0:45:28 When dopamine neurons fire after an odor, mushroom body responses to that odor decrease
0:46:23 Neurons that produce innate avoidance are required for attractive memory and vice versa
0:56:29 Another example: Motion vision
0:58:23 Directional motion is computed within the brain
0:59:41 How does this computation happen?
1:01:45 ON and OFF pathways in the visual system
1:02:53 Reconstructing the visual pathway
1:06:37 Electrophysiology from T4/T5 neurons
1:08:22 Inhibition, not multiplication, generates direction selectivity
1:09:42 Matched filters for optic flow
1:10:48 From photoreceptors to feature detectors