לוח שנה משולב

The idea that complex liquid-air interfaces laden with surfactants, colloids, or polymer molecules, possess rheological properties that differ from those of the bulk sub-phase has been suggested 150 years ago. Yet, even today we are still struggling with the means to properly measure these properties. In this talk we will first explore the reasons to worry at all about the properties of the interface, examine some of the consequences of interfacial rheology, and revisit a century old technique - the unjustifiably named “Langmuir trough”, pointing out some experimental peculiarities.

An arrangement of particles is said to be "hyperuniform" if its density fluctuations over large distances are strongly suppressed relative to a random configuration. Crystals, for example, are hyperuniform. Recently, several disordered materials have been found to be hyperuniform. Examples are sheared suspensions and emulsions, and, possibly, random close packings of particles. We show that externally driven particles in a liquid suspension (as in sedimentation, for example) self-organize hyperuniformly in certain directions relative to the external force. This dynamic hyperuniformity arises from the long-range coupling, induced by the force and carried by the fluid, between the concentration of particles and their velocity field. We obtain the general requirements, which the coupling should satisfy in order for this phenomenon to
occur. Under other conditions (e.g., for certain particle shapes), the
coupling can lead to the opposite effect -- enhancement of density
fluctuations and instability. We confirm these analytical results in a
simple two-dimensional simulation.

During development, neurons need to couple their robust axonal growth with their energetic balance. The mechanisms that regulate this coupling are largely unknown. Here we show that sensory neurons that lack Liver Kinase B1 (LKB1), a master regulator of energy homeostasis, exhibit reduced axonal growth and branching. Biochemical analysis of these LKB1 KO neurons revealed metabolic irregularities, manifested by axonal reduction in ATP levels. Genomic analysis uncovered downregulation in Efhd1 (EF-Hand Domain Family Member D1), a mitochondrial Ca2+-binding protein in the LKB1 KO sensory neurons. Strikingly, genetic ablation of Efhd1 caused a decrease in the axonal ATP levels and activation of the AMPK (AMP-activated protein kinase) pathway in sensory neurons. Moreover, we detected shortened mitochondria at the axonal growth cones and activation of the mitophagy regulator ULK (Unc-51 like autophagy activating kinase). Suggesting that Efhd1 is an important regulator of the axonal mitochondria. Notably, these metabolic dysfunctions were manifested by reduced axonal growth in vitro, and axonal branching defects and enhanced neuronal death in vivo. Overall, our work uncovers a new metabolic pathway that couples mitochondrial and axonal growth through Efhd1.

Stability of mRNA molecules is generally considered to be an intrinsic and constant feature of every distinct transcript. This study investigated the effect of transcription on the stabilities of multiple human and mouse mRNAs. We found that transcription positively regulates mRNA stability, rendering efficiently transcribed messengers less prone to degradation. Being independent of either translation or expression levels, this phenomenon is based exclusively on the co-transcriptionally deposited m6A modification, length of poly(A) tails, and the preferential activity of the CCR4-Not complex toward m6A-marked transcripts. Moreover, we demonstrate that upon large-scale transcriptional changes, such as during stress response or differentiation, the cell dynamically regulates its degradation machinery to buffer the global levels of mRNAs. We found this phenomenon to affect stabilities of virtually all tested mRNAs, thus providing transcription an additional regulatory pathway to globally impact mRNA stability. Overall, we conclude that transcription is a primary regulator of mRNA degradation in eukaryotic cells. We postulate that mRNA stability is a flexible epigenetic feature that is continuously and dynamically adjusted to transcriptional fluctuations in order to fine-tune gene expression in the ever-changing conditions.

In classic models of vision, vision proceeds in a hierarchical fashion, from low-level analysis (edges and lines) to figural processing (shapes and objects). Low-level processing determines high-level processing. Here, we show that shape processing determines basic visual processing as much as the other way around. For example, we presented a vernier stimulus and asked observers to indicate its offset direction. Performance strongly deteriorated when the vernier was surrounded by a square, in line with most models of vision. Surprisingly, performance improved when more squares were added. This improvement of performance can hardly be explained by classic models of vision, which predict a further deterioration of performance. We propose that shape interactions precede low-level processing in a recurrent fashion. Using high density EEG and trans-cranial magnetic stimulation (TMS), we show how good Gestalt emerges during recurrent, unconscious processing within 420ms. The outcome of this processing, i.e., the conscious percept, determines, paradoxically, what is usually referred to as early visual processing.

I will discuss recent work on the neural circuitry underlying model-free and model-based reinforcement learning (RL). While there has been considerable focus on dopamine and its action in the striatum, particularly for model-free RL, our recent work has shown that the amygdala also plays an important role in these processes. We have further found that the amygdala and striatum learn in parallel. However, the amygdala learns more rapidly than the striatum. Therefore, each structure tends to be optimized for different reward environments. Overall, the work in our lab outlines roles for multiple neural circuits spanning cortical-basal ganglia-thalamocortical loops, as well as the amygdala’s interaction with these circuits, in RL.