Integrated Calendar

Brain-computer interfaces (BCI), have important applications both in medicine and as a research tool. Typically, BCIs rely on electrode arrays to capture electrical signals, which are then processed by algorithms to translate neural activity into actions of an external device. However, these electrophysiological techniques are often inadequate for tracking large populations of the same neurons over timescales longer than ~1 day. To address this, we developed calcium imaging-based BCI for freely behaving mice, facilitating continuous recording and analysis of specific neuronal populations over extended periods. This BCI allowed investigating the long-term neuronal coding dynamics in the hippocampus, revealing changes in neuronal population activity both within and across days. I am hopeful that this BCI will advance studies on spatial cognition and long-term memory.

The communication of plants with their environment is crucial for their survival. Plants are known to use light, odors, and touch to communicate with other organisms, including plants and animals. Yet, acoustic communication is almost unexplored in plants, despite its potential adaptive value. This is the topic of the current talk. We have started exploring plant bioacoustics - what plants hear, and what they “say”. I will describe two major projects: in the first we study plant hearing, testing the responses of flowers to sounds of pollinators; in the second we investigate plant sound emission - we have shown that different species of plants emit brief ultrasonic signals, especially under stress. Using AI we can interpret these sounds and identify plant species and stress condition from the sounds. Potential implications of these projects for plant ecology, evolution and agriculture will be discussed.

One of the major open problems in complexity theory is proving super-logarithmic lower bounds on the depth of circuits. Karchmer, Raz, and Wigderson (Computational Complexity 5(3/4), 1995) suggested approaching this problem by proving that depth complexity of a composition of two functions is roughly the sum of their individual depth complexities. They showed that the validity of this conjecture would imply the desired lower bounds. 

The intuition that underlies the KRW conjecture is that composition should behave like a "direct-sum problem", in a certain sense, and therefore the depth complexity of the composition should be the sum of the individual depth complexities. Nevertheless, there are two obstacles toward turning this intuition into a proof: first, we do not know how to prove that the composition must behave like a direct-sum problem

Animal movements are complex, high-dimensional, and lead to many different consequences. Thus, efficiently quantifying the behavior and uncovering the underlying representation used by the animal pose a great challenge. Tracking freely behaving zebrafish larvae using a high-speed camera and analyzing their movements, we reveal that zebrafish movements can be described using exactly two parameters. Mapping all possible two-dimensional movement representations, we identified the representation used by the fish. We show that fish do not trivially represent distance and angles as separate parameters, but rather mix them nonlinearly. Moreover, when hunting, this specific nonlinear relation depends on the prey angle and further dictates a particular set of potential movements. These results uncover, for the first time, the underlying action selection principles of hunting behavior, suggesting that behind this seemingly complex behavior there is a simple and low-dimensional process.

Understanding mechanisms of work for a wide range of applied nanomaterials begins with identifying “active units” in operating conditions, zooming in on the “active sites” and ends with a model explaining their role for functioning of the material or device. There are two main hurdles that we are particularly interested in overcoming: 1) heterogeneity of active species and sites and 2) their dynamics that can be directly responsible for their mechanisms. One possible method, ideally suitable for capitalizing on these challenges for rational design of new catalytic pathways, is the Aufhebung (sublation) principle from the Hegelian dialectics. It describes the process of advancing knowledge by integrating the two opposites: the thesis and antithesis. We adopt this principle to leverage the inherent heterogeneity of catalytic active species and active sites in metal catalysts for understanding and predicting new catalytic pathways for CO and CO2 conversion reactions. Starting with atomically dispersed (the thesis) Pt on ceria support, we use multimodal, operando characterization for monitoring formation of nanoparticles (the antithesis), identify reaction active species and unique active sites at the metal-support interface. With this knowledge, we design the “single-atoms” catalysts (synthesis) possessing the same active sites and enhanced stability in reaction conditions. I will highlight the role of oxygen vacancies for enhancing the dynamicity of Pt atoms and opening new reaction pathways for direct and reverse water gas shift reactions and CO oxidation reaction.

In three-dimensional space, elementary particles are divided between fermions and bosons according to the properties of symmetry of the wave function describing the state of the system when two particles are exchanged. When exchanging two fermions, the wave function acquires a phase, φ=π. On the other hand, in the case of bosons, this phase is zero, φ=0. This difference leads to deeply distinct collective behaviors between fermions, which tend to exclude themselves, and bosons which tend to bunch together. The situation is different in two-dimensional systems which can host exotic quasiparticles, called anyons, which obey intermediate quantum statistics characterized by a phase φ varying between 0 and π [1,2].

For example in the fractional quantum Hall regime, obtained by applying a strong magnetic field perpendicular to a two-dimensional electron gas, elementary excitations carry a fractional charge [3,4] and have been predicted to obey fractional statistics [1,2] with an exchange phase φ=π/m (where m is an odd integer). Using metallic gates deposited on top of the electron gas, beam-splitters of anyon beams can be implemented. I will present how the fractional statistics of anyons can be revealed in collider geometries, where anyon sources are placed at the input of a beam-splitter [5,6]. The partitioning of anyon beams is characterized by the formation of packets of anyons at the splitter output. This results in the observation of strong negative correlations of the electrical current, which value is governed by the anyon fractional exchange phase φ [5,7].


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[3] R. de Picciotto et al., Nature 389, 162–164 (1997).
[4] L. Saminadayar, D. C. Glattli, Y. Jin, B. Etienne, Phys. Rev. Lett. 79, 2526–2529 (1997)
[5] B. Rosenow, I. P. Levkivskyi, B. I. Halperin, Phys. Rev. Lett. 116, 156802 (2016).
[6] H. Bartolomei et al. Science 368, 173-177 (2020).
[7] Lee, JY.M., Sim, HS, Nature Communications 13, 6660 (2022).