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Nematic liquid crystals exhibit both crystal-like and fluid-like features. In particular, the propagation of an acoustic wave shows an unexpected occurrence of some of the solid-like features at the hydrodynamic level, namely, the…
Background: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic…
Persistent activity is postulated to drive neural network plasticity and learning. To investigate its underlying cellular mechanisms, we developed a biophysically tractable model that explains the emergence, sustenance, and eventual…
Salt is a very common molecule in aqueous environments but the question of whether the interactions of monovalent ions Na^+ and Cl^- ,with the neutral heads of phospholipids are impactful enough to change the membrane rigidity is still a…
Neural variability plays a central role in neural coding and neuronal network dynamics. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in…
We present an account of neuroplasticity with respect to cell-internal processing pathways in relation to membrane and synaptic plasticity. We think traditional synapse-centric, weight-based models of memorization are not sufficient or…
Motivated by frequently reported deviations from stoichiometry in cubic transition metal nitride (TMNx) thin films, the effect of N-vacancy concentration on the elastic properties of cubic TiNx, ZrNx, VNx, NbNx, and MoNx (0.72<x<1.00) is…
Neuronal networking supports complex brain functions, with neurotransmitters facilitating communication through chemical synapses. The release probability of neurotransmitters varies and is influenced by pre-synaptic neuronal activity.…
Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as…
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their electrical resistance in response to stimuli, similar to…
Dislocation nucleation is essential to our understanding of plastic deformation, ductility and mechanical strength of crystalline materials. Molecular dynamics simulation has played an important role in uncovering the fundamental mechanisms…
We investigate theoretically the slow non-exponential relaxation dynamics of the electron glass out of equilibrium, where a sudden change in carrier density reveals interesting memory effects. The self-consistent model of the dynamics of…
Efficient third-order nonlinearities of the Zinc Oxide and Al-doped Zinc Oxide were studied by Third Harmonic Generation (Third Harmonic Generation) Maker fringes to establish the effect Aluminum of Aluminum doping(Al-doping) on the cubic…
We investigate the structural, dielectric relaxation, electric modulus and impedance behavior of Ni-doped NASICON ceramic Na$_{3+2x}$Zr$_{2-x}$Ni$_{x}$Si$_2$PO$_{\rm 12}$ ($x=$ 0.05--0.2) prepared using the solid-state reaction method. The…
Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the…
A biophysical issue how the nuclear size dynamically scales with the cellular size remains mysterious. We develop a theoretical framework in which the interactions between polydisperse biomolecules and the mechanical elasticity of the cell…
In this paper we present a simple microscopic stochastic model describing short term plasticity within a large homogeneous network of interacting neurons. Each neuron is represented by its membrane potential and by the residual calcium…
Recent work in continual learning has highlighted the beneficial effect of resampling weights in the last layer of a neural network (``zapping"). Although empirical results demonstrate the effectiveness of this approach, the underlying…
Biological and artificial learning systems alike confront the plasticity-stability dilemma. In the brain, neuromodulators such as acetylcholine and noradrenaline relieve this tension by tuning neuronal gain and inhibitory gating, balancing…
Effective treatments that prevent or reduce drug relapse vulnerability should be developed to relieve the high burden of drug addiction to society. This will only be possible by enhancing the understanding of the molecular mechanisms…