Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback allows learning voluntary control over specific brain areas by means of operant conditioning and has been shown to decrease pain perception. To further increase the effect of rt-fMRI neurofeedback on pain, we directly compared two different target regions of the pain network, notably the anterior insular cortex (AIC) and th...

Following in the recent work of Hurvich and Tsai (1989, 1991, 1993) and Hurvich, Shumway, and Tsai (1990), we propose a corrected variant of AIC developed for the purpose of small-sample state-space model selection. Our variant of AIC utilizes bootstrapping in the state-space framework (Stoffer and Wall (1991)) to provide an estimate of the expected Kullback-Leibler discrepancy between the mode...

The AIC and its modifications have been proposed for selecting the degree in a polynomial growth curve model under a large-sample framework when the sample size n is large, but the dimension p is fixed. In this paper, first we propose high-dimensional AIC (denoted by HAIC) which is an asymptotic unbiased estimator of the risk under a high-dimensional framework such that p/n → c ∈ [0, 1). It is ...

The aim of this study was to evaluate whether structural differences in the insula and anterior cingulate cortex (ACC), two critical areas of the "salience network," co-exist in adolescents with attention deficit hyperactivity disorder (ADHD) compared with healthy controls (HC). In addition we aimed to determine if structural changes within these regions correlate with attention and inhibitory ...

Inter-cell Co-Channel Interference (ICCI) is a severe problem suffered by cell-edge users in multi-cell OFDMA system, an adaptive interference coordination (AIC) algorithm based on Iterative Water-Filling (IWF) algorithm for multi-cell is proposed. Cell-edge users and cell-center users have different priorities. The resource allocated to cell-edge users is adjusted after each convergence. The c...

In this paper, the problem of variable selection in linear regression is considered. This problem involves choosing the most appropriate model from the candidate models. Variable selection criteria based on estimates of the Kullback-Leibler information are most common. Akaike’s AIC and bias corrected AIC belong to this group of criteria. The reduction of the bias in estimating the Kullback-Leib...