Speaker 1: Xinxuan Li

Title

Computational Models of Neurons in Thalamic Reticular Nuclei

Abstract

The thalamic reticular nucleus (TRN), a shell of GABAergic neurons that surrounds the dorsal thalamus, generates and sustains rhythmic oscillations called sleep spindles. Recent evidence has shown that TRN neurons are connected by chemical synapses and gap junctions. Moreover, the primary chemical synapses in TRN modulated by GABAa receptors, have recently been shown to be excitatory instead of inhibitory, as previously suggested. In order to understand how TRN neurons generate and sustain sleep spindles, we develop a Hodgkin-Huxley based computational model of a TRN neuron with the currents and parameters supported by recent experimental data. The resulting computational model of a single TRN neuron demonstrates biophysical behavior. We also introduce the large T-window current model and the small T-window current model as a means of reflecting the known heterogeneity of TRN neurons.  Then  we  use XPP to find a bifurcation  by generating bifurcation structure by varying the reversal potential of the leak channel.

Speaker 2: Rowena Bastero

Title

Performance of Intraclass Correlation Coefficient (icc) as a Reliability Index under various Distributions in Scale Reliability Studies

Abstract

Integral to the quality and usefulness of any research undertaking is the reliability of its results. In aesthetics studies, measurement tools called “scales” are often utilized as objective instruments for determining baseline severity and post-treatment outcomes to evaluate treatment effectiveness. Considering the use of scales for drawing conclusions, it is imperative to ensure consistency through scale reliability studies prior to their use. Often, reliability of a scale is measured using intra-class correlation coefficient (ICC) or weighted kappa, which are affected by the distribution of subjects in each grade of the scale or also known as the base rate problem. This dependence on the distribution not only makes it difficult to compare reliability measures across studies but also poses a problem of potentially producing less reliable indexes. In this research, we propose a standard paradigm that enables comparison of different reliability measures. Additionally, we propose a mechanism that minimizes the imbalance across grades and thus diminishes the impact of the base rate problem on reliability indexes.  Simulated and real-life data are used to show how this method reduces the effect of the base rate problem.