לוח שנה משולב

Working memory (WM), the process through which information is transiently maintained and manipulated over a brief period of time, is essential for most cognitive functions. However, the mechanisms underlying the generation and stability of WM neuronal representations at the population level remain elusive. To uncover these mechanisms, we trained head-fixed mice to perform  an olfactory working memory task and used optogenetics to delineate circuits causal for behavioral performance. We used mesoscopic and light bead  two photon imaging to record from up to 35,000 secondary motor cortical neurons simulataneously across multiple days and show differential stabilization of different task parameters with learning and practice of the task. We find that cortical working memory representations causal for task performance are highly volatile but only stabilize after multiple days of practice well after task learning. We hypothesize that representational drift soon after learning may allow for higher levels of flexibility for new task rules. 
I will also review some of the new open-source tools developed for large-scale imaging of neural activity patterns in freely behaving animals.

Text-conditioned image editing has recently attracted considerable interest. However, most methods are currently either limited to specific editing types (e.g., object overlay, style transfer), or apply to synthetically generated images, or require multiple input images of a common object. In this paper we demonstrate, for the very first time, the ability to apply complex (e.g., non-rigid) text-guided semantic edits to a single real image. For example, we can change the posture and composition of one or multiple objects inside an image, while preserving its original characteristics. Our method can make a standing dog sit down or jump, cause a bird to spread its wings, etc. — each within its single high-resolution natural image provided by the user. Contrary to previous work, our proposed method requires only a single input image and a target text (the desired edit). It operates on real images, and does not require any additional inputs (such as image masks or additional views of the object). Our method, which we call "Imagic", leverages a pre-trained text-to-image diffusion model for this task. It produces a text embedding that aligns with both the input image and the target text, while fine-tuning the diffusion model to capture the image-specific appearance. We demonstrate the quality and versatility of our method on numerous inputs from various domains, showcasing a plethora of high quality complex semantic image edits, all within a single unified framework

Fundamental understanding of physiological processes that occur at biological membranes, such as membrane fusion, necessitates addressing not only the biochemical aspects, but also biophysical aspects such as membrane mechanical properties and membrane curvature. In this talk, I will show how we combine membrane model systems, micropipette aspiration, optical tweezers and confocal fluorescence microscopy to study membrane shaping and membrane fusion processes. I will describe a new tool we developed, where we form membrane bilayers supported on polystyrene microspheres which can be trapped and manipulated using optical tweezers. Using this approach, we demonstrate successful measurements of the interaction forces between the Spike protein of SARS CoV-2 and its human receptor, ACE2. We further use bead-supported membranes interacted with aspirated vesicles to reveal the inhibitory effect of membrane tension on hemifusion. I will also describe a particular case of membrane shaping during the formation of the newly discovered organelle termed migrasome. We show that tetraspanin proteins involved in migrasome formation strongly partition into curved membrane tethers, and we reveal a novel, two-step process of migrasome biogenesis.