Bayesian varying-effects vector autoregressive models for inference of brain connectivity networks and covariate effects in pediatric traumatic brain injury.

In this article, we develop an analytical approach for estimating brain connectivity networks that accounts for subject heterogeneity. More specifically, we consider a novel extension of a multi-subject Bayesian vector autoregressive model that estimates group-specific directed brain connectivity networks and accounts for the effects of covariates on the network edges. We adopt a flexible approach, allowing for (possibly) nonlinear effects of the covariates on edge strength via a novel Bayesian nonparametric prior that employs a weighted mixture of Gaussian processes.

Contextual features in the developing hippocampus: A representational similarity analysis.

Functional divisions of labor in support of memory have been reported along the anterior-posterior axis of the hippocampus. However, little is known about how the developing hippocampus represents associative memories along this axis. The present research employed representational similarity analysis to ask whether developmental differences exist in the extent to which the anterior versus the posterior hippocampus represent features of the context and associative memories.

BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks.

In this paper we propose BVAR-connect, a variational inference approach to a Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. The modeling framework uses a Bayesian variable selection approach that flexibly integrates multi-modal data, in particular structural diffusion tensor imaging (DTI) data, into the prior construction. The variational inference approach we develop allows scalability of the methods and results in the ability to estimate subject- and group-level brain connectivity networks over whole-brain parcellations of the data.

Developmental differences in hippocampal and cortical contributions to episodic retrieval.

Episodic memory, or the ability to form and retrieve conscious memories about specific past events, improves during childhood. Previous adult neuroimaging results indicate a central role of the hippocampus in episodic retrieval, but it is not clear whether the contribution of the hippocampus changes during development. Traditionally, developmental improvements in episodic retrieval have been thought to depend on strategic processes mediated by the prefrontal cortex (PFC), a region that is considered to have a protracted course of development relative to the hippocampus.

Developmental differences in medial temporal lobe function during memory encoding.

The ability to recollect details about past events improves during childhood. Most researchers favor the view that this improvement depends largely on the development of the prefrontal cortex, which is thought to have a protracted course of development relative to the medial temporal lobes (MTL). The primary goal of the present study was to test the hypothesis that the development of detail recollection is also associated with changes in MTL function.

Diabetic ketoacidosis and memory dysfunction in children with type 1 diabetes.

Objective: We tested the hypothesis that diabetic ketoacidosis (DKA) results in memory deficits typical of hypoxic/ischemic injury because recent studies suggest that cerebral metabolic changes similar to those observed in hypoxic/ischemic cerebral injury are observed in children with DKA, even without symptoms suggesting cerebral injury.

Study Design: Thirty-three children with type 1 diabetes mellitus (T1DM) and a history of DKA and 29 children with T1DM without a history of DKA were enrolled from an academic hospital pediatric endocrinology clinic. These groups were comparable on demographic and disease-related variables.