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Chung, S. T.

Publications and source records attributed to Chung, S. T..

2 recordsLinked to original sources

Cortical Dynamics during Contour Integration

Integrating visual elements into contours is important for object recognition. Previous studies emphasized the role that the primary visual cortex (V1) plays in this process. However, recent evidence suggests that contour integration relies on the coordination of hierarchical substrates of cortical regions through recurrent connections. Many previous studies presented the contour at the same onset-time as the trial, which caused the subsequent neural imaging data to incorporate both visual evocation and contour integration activities, and thus confounding the two. In this study, we varied both the contour onset-time and contour fidelity and used EEG to examine the cortical activities under these conditions. Our results suggest that the temporal N300 represents the grouping and integration of visual elements into contours. Before this signature, we observed interhemispheric connections between lateral frontal and posterior parietal regions that were contingent on the contour location and peaked at around 150ms after contour appearance. Also, the magnitudes of connections between medial frontal and superior parietal regions were dependent on the timing of contour onset and peaked at around 250ms after contour onset. These activities appear to be related to the bottom-up and top-down attentional processing during contour integration, respectively, and shed light on how these processes cooperate dynamically during contour integration.

neuroscience↗

Estimating Insulin Sensitivity and Beta-Cell Function from the Oral Glucose Tolerance Test: Validation of a new Insulin Sensitivity and Secretion (ISS) Model

Efficient and accurate methods to estimate insulin sensitivity (SI) and beta-cell function (BCF) are of great importance for studying the pathogenesis and treatment effectiveness of type 2 diabetes. Many methods exist, ranging in input data and technical requirements. Oral glucose tolerance tests (OGTTs) are preferred because they are simpler and more physiological. However, current analytical methods for OGTT-derived SI and BCF also range in complexity; the oral minimal models require mathematical expertise for deconvolution and fitting differential equations, and simple algebraic models (e.g., Matsuda index, insulinogenic index) may produce unphysiological values. We developed a new ISS (Insulin Secretion and Sensitivity) model for clinical research that provides precise and accurate estimates of SI and BCF from a standard OGTT, focusing on effectiveness, ease of implementation, and pragmatism. The model was developed by fitting a pair of differential equations to glucose and insulin without need of deconvolution or C-peptide data. The model is derived from a published model for longitudinal simulation of T2D progression that represents glucose-insulin homeostasis, including post-challenge suppression of hepatic glucose production and first- and second-phase insulin secretion. The ISS model was evaluated in three diverse cohorts including individuals at high risk of prediabetes (adult women with a wide range of BMI and adolescents with obesity). The new model had strong correlation with gold-standard estimates from intravenous glucose tolerance tests and hyperinsulinemic-euglycemic clamp. The ISS model has broad clinical applicability among diverse populations because it balances performance, fidelity, and complexity to provide a reliable phenotype of T2D risk.

physiology↗