Events

CaImAn is an open-source software platform that provides optimized and scalable routines to process imaging data with the goal of extracting the activity of each neuron. CaImAn handles multiple imaging modalities (voltage, calcium, endoscopic, multiphoton, volumetric) and analysis settings (batch/offline vs online/real-time). Mesmerize is a new organizational and visualization framework that allows for efficient and streamlined analysis using CaImAn algorithms, and enables users with minimal programming experience to use CaImAn effectively. CaImAn is very popular among neuroscientists world-wide, but its widespread dissemination, the efficient use of its routines, and the opportunities provided by Mesmerize, require access to training opportunities. We will address this challenge by establishing a workshop at the Flatiron Institute, Simons Foundation. Application deadline: November 6, 2022.

The IBRO-Simons Computational Neuroscience Imbizo, or isiCNI is an opportunity for African and international students to learn about cutting edge research techniques in computational neuroscience. The format of the school will be a combination of intensive lectures on advanced topics in computational and theoretical neuroscience as well as practical exercises in simulation and data analysis. In addition, students will perform a mini-research project under the supervision of one of the school tutors, to be presented at the end of the school. Application deadline: Thursday 20 Oct 2022

Neuromatch Academy teaches computational techniques crucial for success in academia and industry. It serves thousands of students each year with hundreds of teaching assistants. Students learn by solving problems in small groups and by running group projects; they learn in many languages in an incredibly supportive environment. We run a Computational Neuroscience and a Deep Learning course, which will happen in parallel for 3 weeks. Student and TA applications accepted March 28th to April 20th.

This event aims to bring together spike sorting developers and experts to tackle open and unsolved spike sorting issues and to move the spike sorting field forward in an open and highly collaborative fashion. Come join the developers of popular spike sorting tools including YASS, SpikeInterface, SpyKING CIRCUS, Mountainsort, and many more.

The event will take place both at the Flatiron Institute and virtually.

The Simons Collaboration on the Global Brain hosts a Global group meeting to bring together postdocs and PhD students interested in neural coding and dynamics to discuss ideas and data. This quarter's speaker is:

James Roach
Postdoctoral Researcher, Churchland Laboratory
University of California, Los Angeles
Two roles for choice selective inhibition in decision-making circuits

The Simons Collaboration on the Global Brain hosts a Boston-area group meeting to bring together postdocs and PhD students interested in neural coding and dynamics. This month's speaker is:

Rishi Rajalingham
Postdoctoral Fellow, Jazayeri Laboratory
McGovern Institute for Brain Research
Massachusetts Institute of Technology
The role of mental simulation in primate physical inference abilities

The Simons Collaboration on the Global Brain hosts an NY-area group meeting to bring together postdocs and PhD students interested in neural coding and dynamics to discuss ideas and data. This month's speaker is:

Justin D Yao
Postdoctoral Associate, Sanes Laboratory
New York University
Transformation of sound encoding to auditory decisions

The Simons Collaboration on the Global Brain hosts a West Coast group meeting to bring together postdocs and PhD students interested in neural coding and dynamics.

This month's speaker is:

Will Liberti
Postdoctoral Fellow, UC Berkeley
A stable hippocampal code for stable spatial behaviors

The Ascona 2022 Neuronal Circuits Meeting will present work on how specific neuronal circuits encode information and drive behavior, on how brain systems interact to produce specific functions, on the developmental and genetic basis of circuit function, on circuit function in social behaviors, on the function of neuromodulatory systems in animal behavior, and on how circuit adjustments and brain states influence learning and behavior. Application deadline: April 30th, 2022

The Neuromatch Conference is focused on Computational Neuroscience broadly construed, following in the model of the first two NMC events. The scope includes machine learning work that has an explicit biological link. The main series of talks will be hosted within Crowdcast. Instead of posters, we offer flash talks, which are brief pre-recorded videos, and dedicated meet up times for discussion within discord. Submission deadline: September 05, 2022.

This meeting brings some of the top global researchers at the interface of neuroscience and AI to the University of Washington. The 4-day meeting will feature sessions on reinforcement learning, brain-computer interfaces, and more. Registration is open at https://www.neuroaiseattle.com/. This event will be held virtually and in-person at the University of Washington.

September 28th, 2022: Virtual Data Showcase

October 3-5, 2022: Allen Institute, Seattle, WA, USA

The DANDI Archive now has over 90 publicly available neurophysiology datasets, standardized using NWB, including cutting edge data produced by the OpenScope project which has been designed and packaged to enable secondary analysis. Come to the Allen Institute to learn how to access and analyze these datasets efficiently and work together or solo on a re-analysis project of your design. Software developers and scientists will be available to assist attendees on their projects. Explore the datasets at https://dandiarchive.org. Applications are due June 17.

Each year, scientists from around the world congregate to discover new ideas, share their research, and experience the best the field has to offer. Attend so you can: present research, network with scientists, attend sessions and events, and browse the exhibit hall. Proposal submission is open through January 25. Abstract submission will open on Wednesday, June 1 and will close on Wednesday, June 15 at 5 p.m. EDT.

Recent advances in deep neural networks (DNNs), combined with open, easily-accessible implementations, have made DNNs a powerful, versatile method used widely in both machine learning and neuroscience. These advances in practical results, however, have far outpaced a formal understanding of these networks and their training. The dearth of rigorous analysis for these techniques limits their usefulness in addressing scientific questions and, more broadly, hinders systematic design of the next generation of networks. Recently, long-past-due theoretical results have begun to emerge from researchers in a number of fields. The purpose of this conference is to give visibility to these results, and those that will follow in their wake, to shed light on the properties of large, adaptive, distributed learning architectures, and to revolutionize our understanding of these systems. Abstract submissions due August 1, 2022.