Integrated Calendar

The Burger-Sarnak method shows that the restriction of an automorphic representation of a reductive group to a reductive subgroup has automorphic support. Clozel has conjectured a qualitative refinement of this result, which was first verified and quantified in the GLn case by Venkatesh. In this talk I will describe my thesis which extended this result to classical groups.

Aggression is an innate social behavior essential for competing for resources, securing mates, defending territory and protecting the safety of oneself and family. In the last decade, significant progress has been made towards an understanding of the neural circuit underlying aggression using a set of modern neuroscience tools. Here, I will talk about our recent progress in the study of aggression.


Zoom link to join-
https://weizmann.zoom.us/j/96608033618?pwd=SEdJUkR2ZzRBZ3laUUdGbWR1VFJTdz09

Meeting ID: 966 0803 3618
Password: 564068

Host: Dr. Rita Schmidt rita.schmidt@weizmann.ac.il tel: 9070

Zoom Link: https://weizmann.zoom.us/j/96221353497?pwd=OWppT1ExY1Ewcm8zSGt4MzcvNWNiUT09

The central aim of the research is to understand how the molecular and nanoscale interactions between two natural biopolymers, fiber-forming protein-silk and conductive polysaccharide-pectin, shaping the physical properties of macro-scale composite material.

Neural circuits display complex spatiotemporal patterns of activity on the millisecond timescale during behavior. Understanding how these activity patterns drive behavior is a fundamental problem in neuroscience, and remains a major challenge due to the complexity of their spatiotemporal dynamics. The ability to manipulate activity in genetically defined sets of neurons on the millisecond timescale using optogenetics has provided a powerful new tool for making causal links between neuronal activity and behavior. I will discuss novel approaches that combine simultaneous two-photon calcium imaging and two-photon targeted optogenetic photostimulation with the use of a spatial light modulator (SLM) to provide ‘all-optical’ readout and manipulation of the same neurons in vivo. This approach enables reading and writing of activity in neural circuits with single-cell resolution and single action potential precision during behavior. I will describe the power, limitations and future potential of this approach; and discuss how it can be used to address many important problems in neuroscience, including transforming our search for the neural code and the links between neural circuit activity and behavior.


Zoom link to join-
https://weizmann.zoom.us/j/96608033618?pwd=SEdJUkR2ZzRBZ3laUUdGbWR1VFJTdz09

Meeting ID: 966 0803 3618
Password: 564068

Host: Dr. Rita Schmidt rita.schmidt@weizmann.ac.il tel: 9070

Decision making is a fundamental ability to human life. Even the simplest decision we make requires integration of multiple factors in our brain, such as prior knowledge, information from the environment, emotions and many more. Despite many years of research and numerous important and ground-breaking findings on how learning and decision-making are generated in our brain, a lot of knowledge is still required for a comprehensive understanding of it. My research initiated from the motivation to understand the unique contribution of valence (rewards and punishments) – when presented as feedback during learning – to perception and decision-making. For that purpose, I studied multiple groups of individuals under different experimental conditions created to elucidate behavioral and neural responses to rewards and punishments. I asked how prediction errors (PE, the difference between expected and received outcomes) bias the perception of time, and how valence and information from feedback, factors that are often indistinguishable, differently guide decision making in a multi-choice environment. Using functional MRI and computational models, I found that positive and negative PEs, known to drive learning, bias the perception of time in opposite directions. Positive PEs induce change in the perceived time so it seems longer compared to a neutral condition (no PE). In contrast, when a negative PE is detected, time is perceived to be shorter. My results identify the Putamen, a structure that receives dopaminergic projections and is involved in time perception, as the brain region that likely drives this bias and underlies the interaction between time perception and prediction-errors.
In addition, I demonstrated that knowing the outcome valence in advance can enable an information-based decision making, namely one that is not affected by the valence itself and is driven only by the information available in the environment. Because uncertainty regarding choice increases when more options are available to choose from, a ‘right’ feedback provides more information to the learning process, compared to a ‘wrong’ feedback. This was accompanied by a differential activation in the ACC, PFC and striatum. Importantly, in this context, punishment avoidance is equally rewarding, and indeed I found that choice behavior and the neural networks underlying choice and feedback processing are similar in the two scenarios – for punishments and rewards. Overall, my work develops and suggests computational and neural mechanisms for specific roles of the information carried by prediction-errors. These findings can enhance our understanding of the fundamental roles of valence and information gain during learning and decision making.

Zoom link to join: https://weizmann.zoom.us/j/92234357805?pwd=aVkrR21CSUVtVS9tSEJYRDkwOFRidz09

Meeting ID: 922 3435 7805
Password: 648092