Center Seminars & Workshops
Events
Pilhwa Lee
(Morgan State University)
Fundamentals of the second-order flows from synaptic excitability to neuronal circuitry and connectivity
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This talk covers some efforts to extend the formalism of informational flow from the first-order and mono-layers to the second-order and double-layers, as well as symmetry and
skew-symmetry in manifolds focusing on our synaptic excitability, neuronal circuitry, and
connectivity.
The first part is about the immersed boundary method with advection-electrodiffusion
retaining the non-electroneutral space charge layers along the fluctuating membrane.
This is realized with regularized singular integrals as chemical potential barriers. In local
mesh refinement, the second-order interpolation is prescribed at the coarse-fine
interface. When the concentration gets diluted, the ionic transport is represented by a
stochastic transition in the second order on lattice spaces. In the microenvironment of
compression, the Eulerian-Lagrangian interaction is turned into a port-Hamiltonian
formalism. Foldable rigidity (origami) and wrinkling dynamics will be introduced shortly.
The next is about the neuronal circuitry of the hypothalamus for characterizing energy
balance. In pubertal maturation, the ventral premammillary nucleus (PMv), the upstream
for energy sensing in the reproductive axis, shows a developmental plasticity in the
connectome. The role of the dopamine transporter is characterized by the integration of
single RNA-seq data and conductance electrophysiology models and recapitulates the
awakening of ovulation and fertility. A working model on pregnancy will be introduced
briefly.
Finally, the up-scaling of synaptic transmission and dendritic integration is represented
by covariance matrices of brain connectivity. In the presence of the uncertainty
principle, the divergence between two brain states or subjects is defined from dynamical
systems points of view of optimal transport, applicable in the classes of two-sample
tests, classification, and regression with kernel methods. Specifically, sliced
Wasserstein flows on covariance matrices are reformulated from Liouville PDE with
normalizing flows on manifolds. Some signatures of competence are shown in the
computation of the Wasserstein barycenter with openness to high-dimensional sparsity.
04:00 PM -
DRL 4C6
Petia Vlahovska
(Northwestern University)
Curvature dynamics of biomembranes: role of membrane viscosity and interleaflet friction
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Lipid bilayers are the main structural component of the membranes that shape and compartmentalize cells. Cell architecture is highly dynamic and membranes' conformation changes dramatically in processes such as movement, division, and vesicle trafficking. Fluidity plays essential role in the structural malleability and diversity of static shapes of membranes. However, its importance in the dynamics of membrane deformations is less appreciated.
Membrane bending by thermal or active forces is commonly assumed to be damped by viscous losses in the surrounding medium. In this talk, I will present our recent experimental and theoretical work where we demonstrated that dissipation within the membrane controls the undulation dynamics of nonplanar membranes with a radius of curvature smaller than the Saffman-Delbruck length. Using flickering spectroscopy of giant vesicles made of DPPC:Cholesterol and pure diblock-copolymer bilayer membranes, the signature of membrane dissipation was detected in curvature fluctuations [1]. We extend the theoretical analysis to submicron liposomes, where lipid density fluctuations, which arise from the stretching and compression of the monolayer leaflets, and intermonolayer friction become important. The results highlight the crucial role of intramembrane dissipation in cellular membrane remodeling and in the thermally driven curvature fluctuations of submicron liposomes.
[1] HA Faizi, R Granek, PM Vlahovska “Curvature fluctuations of fluid vesicles reveal hydrodynamic dissipation within the bilayer”, PNAS, 121 (44), e2413557121 (2024)
04:00 PM -
DRL 4C6
Yohsuke Murase
(RIKEN Advanced Institute for Computational Science)
11:00 AM -
Carolyn Lynch Laboratory 202