Weekly presentation

Image analysis workshop

Prof Si Wu of Peking University, China will give a talk for the OIST neuroscience online seminars (ONOS) series on the topic of "Visual information processing through the interplay between fast and slow pathways". Prof Wu is a PI of IDG/McGovern Institute for Brain Research and the Center for Life Science at Peking University. He is also the Co-editor-in-chief of Frontiers in Computational Neuroscience.

Inter-unit journal club presentation by Dr Sam Reiter, leader of the Computational Neuroethology Unit, who will discuss a recent article from Nature Methods entitled "EthoLoop: automated closed-loop neuroethology in naturalistic environments"

Meeting link: https://oist.zoom.us/j/95700149323?pwd=VWQxY0FGQmxVQmtUTVZ2SXRnMGx6dz09
Meeting ID: 957 0014 9323
Passcode: 855303

October 22 2020, at 12:00 (room C209 and zoom), Kevin Dorgans (Postdoctoral Scholar at Neuronal Rhythms in Movement Unit led by Marylka Yoe Uusisaari) will give a Talk on "In vitro imaging of subthreshold voltage oscillation in the inferior olive"

PhD Public Presentation

Thursday, September 10th, at 12:00 in C209 and on Zoom, Nobuaki Mizumoto (Evolutionary Genomics Unit led by Tom Bourguignon) will give a Talk on "Evolutionary perspectives of collective behavior in termites"

Speaker:  Chris Bowman, University of Kent

Title: Tautological p-Kazhdan–Lusztig Theory for cyclotomic Hecke algebras

Abstract: We discuss a new explicit isomorphism between (truncations of) quiver Hecke algebras and Elias–Williamson’s diagrammatic endomorphism algebras of Bott–Samelson bimodules. This allows us to deduce that the decomposition numbers of these algebras (including as examples the symmetric groups and generalised blob algebras) are tautologically equal to the associated p-Kazhdan–Lusztig polynomials, provided that the characteristic is greater than the Coxeter number. This allows us to give an elementary and explicit proof of the main theorem of Riche–Williamson’s recent monograph and extend their categorical equivalence to cyclotomic Hecke algebras, thus solving Libedinsky–Plaza’s categorical blob conjecture.

An OIST neuroscience online seminars (ONOS) talk.

Abstract

The visual system is a complex, hierarchically-organised information processing network. Counter-intuitively, successive areas contain less information about a scene, but neural activity is structured to better represent specific information. For example, neurons in primate area MT convey little colour information, but motion direction can be linearly decoded from their activity. The ongoing activity of individual neurons is highly variable, meaning reliable computation depends on collaborative processing across neural populations. However, it remains unclear how visual information is reliably represented across neurons within an area, and how these representations are transformed between areas to extract specific stimulus properties. To address this, we record visually-evoked activity simultaneously from dozens of neurons in V1 and MT in marmosets.

We use decoding techniques to predict stimulus orientation or direction from activity across a neural population. This has allowed us to show that neural representations are affected by stimulus history: recent motion biases predictions in a manner consistent with perceptual illusions; and luminance and contrast changes affect orientation coding, again in a manner consistent with human sensitivity.

We study inter-area communication by comparing the timing of action potentials in V1 with local field potentials (LFP, a population measure of local dendritic activity) in MT. We have shown that action potentials preferentially occur at specific phases of the LFP, and that motion information is best communicated from V1 to MT at specific phases.

Collectively, this suggests that hierarchical information processing depends on action potentials in privileged subsets of neurons occurring in privileged time windows.

Zoom details

Zoom Meeting link:
https://oist.zoom.us/j/95700149323?pwd=VWQxY0FGQmxVQmtUTVZ2SXRnMGx6dz09

Meeting ID: 957 0014 9323
Passcode: 855303