Integrated Calendar

The vestibular system detects self-motion and in turn generates reflexes that are crucial for our daily activities, such as stabilizing the visual axis (gaze) and maintaining head and body posture. In addition, the vestibular system provides us with our subjective sense of movement and orientation in space. The loss vestibular function due to aging, injury, or disease produces dizziness, postural imbalance, and an increased risk of falls – all symptoms that profoundly impair quality of life.

In this talk, I will describe how the brain processes vestibular information in natural conditions. Notably, our work has established how early stages of processing encode vestibular stimuli and integrate them with extra-vestibular cues – for example proprioceptive and premotor information to ensure accurate perception and behaviour. Our experiments have revealed that while vestibular afferents respond identically to externally-generated and actively-generated self-motion, this is not the case at first central stage of sensory processing. Neurons mediating the vestibulo-spinal reflexes, as well as ascending thalamocortical pathways, are robustly activated during externally-generated motion, however their sensory response are cancelled during actively-generated movements. Our work has further revealed that this cancellation of actively-generated vestibular input occurs only in conditions where the actual sensory signal matches the brain’s internal estimate of the expected sensory consequences of active movement. Moreover, when unexpected vestibular inputs becomes persistent during voluntary motion, a cerebellar-based cancellation mechanism is rapidly updated to re-enable the vital distinction between self-generated and externally-applied stimulation to ensure the maintenance of posture and stable perception. In contrast, vestibular pathways mediating the vestibulo-ocular reflex, employ a different strategy. In this pathway, head velocity is robustly encoded whenever the goal is to stabilize gaze, but when the goal is to voluntarily redirect gaze an efferent copy of the gaze command suppresses the efficacy of this reflex pathway. Taken together, these findings have important implications for understanding the neural basis of perception and action during self-motion.

Abstract
Polyamines are essential polycations present in all living cells. Polyamine levels are maintained from the diet and de-novo synthesis, and their decline with age is associated with various pathologies. Here we found that polyamine levels oscillate in a daily manner. Both clock- and feeding-dependent mechanisms regulate the daily accumulation of key enzymes in polyamine biosynthesis through rhythmic binding of BMAL1:CLOCK to conserved DNA elements. In turn, polyamines control the circadian period in cultured cells and animals by regulating the interaction between the core clock repressors PER2 and CRY1. Importantly, we show that the decline in polyamine levels with age in mice is associated with a longer circadian period that can be reversed upon polyamine supplementation in the diet. Our findings suggest a cross talk between circadian clocks and polyamines biosynthesis that participate in circadian control, and open new possibilities for nutritional interventions against the decay in clock’s function with age.


Highlights
• Diurnal regulation of polyamine biosynthesis by circadian clock and feeding.
• Polyamine levels regulate the circadian period in cultured cells and mice.
• Polyamines modulate the interaction between the core clock proteins PER2 and CRY1.
• Lengthening of the circadian period with age can be reversed by polyamines.

Conventional analytical size exclusion chromatography (SEC), often used to determine the solution molecular weight of proteins, is subject to inherent limitations and errors. Multi-angle light scattering (MALS) is a first-principles technique for determining the molar mass and size of macromolecules and nanoparticles in solution, independently of conformation. In combination with SEC, MALS overcomes these obstacles to characterize the biophysical properties of proteins and other biomolecules, including molecular weight, size, native oligomeric state, dynamic equilibria and degradation products.

This seminar will present the failure modes of analytical SEC, fundamentals of SEC-MALS and examples of applications to a variety of proteins including IgG, insulin, glycoproteins, membrane proteins and protein complexes as well as viruses and virus-like particles. It will touch on the importance of protein quality control for reproducible science and provide a glimpse into how MALS can analyze complicated protein-protein interactions.

The detection of visual motion is a fundamental neuronal computation that serves many critical behavioral roles, such as encoding of self-motion or figure-ground discrimination. For a neuron to extract directionally selective (DS) motion information from inputs that are not motion selective it is essential to integrate across multiple spatially distinct inputs. This integration step has been studied for decades in both vertebrate and invertebrate visual systems and given rise to several competing computational models. Recent studies in Drosophila have identified the 4th-order neurons, T4 and T5, as the first neurons to show directional selectivity. Due to the small size of these neurons, recordings have been restricted to the use of calcium imaging, limiting timescale and direct measurement of inhibition. These limitations may prevent a clear demonstration of the neuronal computation underlying DS, since it may depend on millisecond-timescale interactions and the integration of excitatory and inhibitory signals. In this study, we use whole cell in-vivo recordings and customized visual stimuli to examine the emergence of DS in T4 cells. We record responses both to a moving bar stimulus and to its components: single position bar flashes. Our results show that T4 cells receive both excitatory and inhibitory inputs, as predicted by a classic circuit model for motion detection. Furthermore, we show that by implementing a passive compartment model of a T4 cell, we can account not only for the DS response of the cell, but also for its dynamics.