Integrated Calendar

Interfaces between systems with different properties are a common feature of Nature. However, the physics of interactions across such interfaces is often neglected. In this talk, I will focus on the case of biological tissue-tissue interfaces and show they can exhibit emergent electrical excitability, a phenomenon that has not been explored before. Using cultured cells and optical tools, I have found that interfaces between tissues with dissimilar electrophysiological properties can behave differently compared to the tissues on either side. In particular, the interface between non-excitable tissues can become excitable. Excitability of cells therefore depends on their position, not just the proteins they express. Moreover, my simulations reveal that interface excitability is extremely robust to parametric variation. I will briefly discuss the roots of this difference in the structures of the underlying dynamical systems, and will show examples of other excitable systems that can exhibit interfacial excitation, such as predator-prey dynamics and oscillating chemical reactions.

The recent breakthrough in the detection of gravitational waves (GWs)
from merging black hole (BH) and neutron star (NS) binaries by
advanced LIGO/Virgo has generated renewed interest in understanding
the formation mechanisms of merging compact binaries, from the
evolution of massive stellar binaries and triples in the galactic
fields, dynamical interactions in dense star clusters to binary
mergers in AGN disks. I will review these different formation
channels, and discuss how observations of spin-orbit misalignments,
eccentricities, masses and mass ratios in a sample of merging binaries
by aLIGO can constrain various formation channels. The important roles
of space-borne gravitational wave detectors (LISA, TianQin, Taiji etc)
will also be discussed.

A plethora of studies have pointed to sensory plasticity in the adult visual system, documenting long-term improvements in perception. Such perceptual learning is enabled by repeated practice, inducing use-dependent plasticity in early visual areas and their readouts. I will discuss results from our lab challenging the fundamental assumption in low-level perceptual learning that only 'practice makes perfect', indicating that brief reactivations of visual memories induce efficient rapid perceptual learning. Utilizing behavioral psychophysics, brain stimulation and neuroimaging, we aim to reveal the neurobehavioral mechanisms by which brief exposure to learned information modulates brain plasticity and supports rapid learning processes. In parallel, we investigate how these learning mechanisms operate across domains, for example by testing the hypothesis that similar inherent mechanisms may also result in maladaptive consequences, when brief reactivations occur spontaneously as intrusive enhanced memories following negative events. Unraveling the mechanisms of this new form of rapid learning could set the foundations to enhance learning in daily life when beneficial, and to downregulate maladaptive consequences of negative memories.

This talk will present our recent work on the observation of super-radiance in a cloud of cold
atoms and the implementation of the driven Dicke model in free space. We start from an
elongated cloud of laser cooled atoms that we excite either perpendicularly or along its
main axis. This situation bears some similarities with cavity quantum electrodynamics: here
the cavity mode is replaced by the diffraction mode of the elongated cloud. We observe
superradiant pulses of light after population inversion. When exciting the cloud along the
main axis, we observe the Dicke super-radiant phase transition predicted 40 years ago and
never observed in free space. We also measure the statistics of the emitted light and find
that it has the properties predicted for a super-radiant laser.

Plastic (irreversible) deformation of crystals requires disrupting the crystalline order, which happens through nucleation and motion of topological line defects called dislocations. Interactions between dislocations lead to the formation of complex networks that, in turn, dictate the mechanical response of the crystal. The severe difficulty in atomic systems to simultaneously resolve the emerging macroscopic deformation and the evolution of these networks impedes our understanding of crystal plasticity. To circumvent this difficulty, we explore crystal plasticity by using colloidal crystals; the micrometer size of the particles allows us to visualize the deformation process in real-time and on the single particle level.
In this talk, I will focus on two classical problems: instability of epitaxial growth and strain hardening of single crystals. In direct analogy to epitaxially grown atomic thin films, we show that colloidal crystals grown on mismatched templates to a critical thickness relax the imposed strain by nucleation of dislocations. Our experiments reveal how interactions between dislocations lead to an unexpectedly sharp relaxation process. I will then show that colloidal crystals can be strain-hardened by plastic shear; the yield strength increases with the dislocation density in excellent accord with the classical Taylor equation, originally developed for atomic crystals. Our experiments reveal the underlying mechanism for Taylor hardening and the conditions under which this mechanism fails.

Social interactions are remarkably dynamic, requiring individuals to understand not only how their behavior may affect others but also how others may respond in return. In humans, social interactions are also often dominated by processes such as language and theory of mind which allow us to communicate complex thoughts and beliefs. Understanding the basic cellular processes that underlie social behavior or by which individuals communicate, however, has remained a challenge. Here, I describe naturalistic approaches developed in animals and humans that aim of investigating these questions. First, by developing an ethologically based group task in three-interacting rhesus macaques, I describe representations of other’s behavior by neurons in the prefrontal cortex, reflecting the other’s identities, their interactions, actions, and outcomes. I also show how these cells collectively represent the interaction between specific group members and how they enable mutually beneficial social behavior. Second, by recording from neurons in the human prefrontal cortex during language-based tasks, I describe neurons that reliably encode information about others’ beliefs across richly varying scenarios and that distinguish self- from other-belief-related representations. By further following their encoding dynamics, I also describe how these cells represent the contents of the others’ beliefs and predict whether they are true or false. Finally, I describe how these cell ensembles track linguistic information during natural speech processing and how language can be used to ask specific questions about the single-cellular constructs that underlie social reasoning. Together, these studies reveal cellular mechanisms for interactive social behavior in animals and humans and highlight the prospective use of naturalistic approaches in social neuroscience.