לוח שנה משולב

How do biological networks evolve and expand? We study these questions in the context of the plant collaborative-non-self recognition self-incompatibility system. Self-incompatibility evolved to avoid self-fertilization among plants. It relies on specific molecular recognition between highly diverse proteins expressed in the female and male reproductive organs, such that the combination of proteins an individual possesses determines its mating partners, defining distinct ‘mating specificities’. Although a few dozen mating specificities are known from population surveys, previous models struggled to pinpoint the evolutionary trajectories by which new specificities evolved. We construct a novel theoretical framework, synthesizing evolutionary and biophysical models, that crucially affords interaction promiscuity and multiple distinct partners per protein, as is seen in empirical findings. We demonstrate spontaneous self-organization of the population into distinct 'classes' with full between-class compatibility and a dynamic long-term balance between class emergence and decay.Our work highlights the importance of molecular recognition promiscuity to network evolvability. Promiscuity was found in additional systems suggesting that our framework could be more broadly applicable. FOR THE LATEST UPDATES AND CONTENT ON SOFT MATTER AND BIOLOGICAL PHYSICS AT THE WEIZMANN, VISIT OUR WEBSITE: https://www.biosoftweizmann.com/  

Mesoscale eddies dominate global ocean kinetic energy and are responsible for efficiently transferring ocean properties. The influence of ocean eddies in the western boundary currents on storm tracks has been studied in recent years, and their importance in regulating mid-latitude precipitation is now recognized. Unlike western boundary currents, mesoscale eddies in the Mediterranean Sea (MS) are smaller and less intense. Yet, the MS is rich in mesoscale activity, and its proximity to densely populated regions suggests that even a small change may have a large impact, which remains underexplored. In this talk, I present several recent studies in which we investigated the interactions between mesoscale eddies and cyclones in the Mediterranean region. These studies focused on specific Mediterranean tropical-like cyclones (medicanes), analyzing their evolution under different sea conditions using observations and model simulations. We find that mesoscale eddies in the MS can change the intensity and track of cyclones and, consequently, affect their resulting rainfall distribution over land. In general, warm-core eddies tend to intensify cyclones and increase precipitation above them relative to cold-core eddies. Additionally, we observe a general increase in surface ocean biogeochemical properties, such as phytoplankton and chlorophyll, following cyclone passages. This increase is driven by upwelling and vertical mixing, though the relative importance of these processes differs between warm- and cold-core eddies.

Understanding the input-output function of principal cortical neurons and their role in network dynamics is a key milestone in decoding how information is represented and processed in the cortex. Pyramidal neurons act as complex computational units, integrating the activity of thousands of synaptic inputs and transforming them into output patterns. These computations are primarily carried out within an elaborate dendritic tree, which receives extensive synaptic input and converts it into a neural code. However, the nature of dendritic computations in vivo during behaviorally relevant tasks remains unclear.In this talk, I will present our recent findings on the dendritic mechanisms used by layer 5 pyramidal tract (PT) neurons to encode motor information in vivo during various motor tasks. Using two-photon calcium imaging in head-fixed mice, along with a custom experimental and analytical pipeline, we achieved unprecedented resolution in correlating dendritic structure with function. I will discuss how different types of PT neurons process and represent motor information, how these properties are shaped during learning, and the role of thalamocortical inputs in modulating both learning and representation.

Classical computers use stable and long-lived units of information, called bits, to perform computations. In contrast, quantum computers rely on qubits. The downside is that qubits are intrinsically much more prone to error. Two of the biggest challenges in building a practical quantum computer are extending the lifetime of qubits and better detection of errors. In this seminar, I will present our recent work on improving by an order of magnitude the coherence time of a superconducting qubit. A key aspect of this breakthrough was the creation of a large Schrödinger cat state with more than 1,000 photons, which can be used for error correction in quantum systems. In the second part of the talk, I will introduce a novel method for real-time error detection, where we continuously monitor the state of a superconducting element to detect and correct qubit dephasing as it occurs. These developments are important steps towards improving the reliability and performance of quantum systems.