Trait-Like Brain Activity during Adolescence Predicts Anxious Temperament in Primates

Early theorists (Freud and Darwin) speculated that extremely shy children, or those with anxious temperament, were likely to have anxiety problems as adults. More recent studies demonstrate that these children have heightened responses to potentially threatening situations reacting with intense defensive responses that are characterized by behavioral inhibition (BI) (inhibited motor behavior and decreased vocalizations) and physiological arousal. Confirming the earlier impressions, data now demonstrate that children with this disposition are at increased risk to develop anxiety, depression, and comorbid substance abuse. Additional key features of anxious temperament are that it appears at a young age, it is a stable characteristic of individuals, and even in non-threatening environments it is associated with increased psychic anxiety and somatic tension. To understand the neural underpinnings of anxious temperament, we performed imaging studies with 18-fluoro-deoxyglucose (FDG) high-resolution Positron Emission Tomography (PET) in young rhesus monkeys. Rhesus monkeys were used because they provide a well validated model of anxious temperament for studies that cannot be performed in human children. Imaging the same animal in stressful and secure contexts, we examined the relation between regional metabolic brain activity and a trait-like measure of anxious temperament that encompasses measures of BI and pituitary-adrenal reactivity. Regardless of context, results demonstrated a trait-like pattern of brain activity (amygdala, bed nucleus of stria terminalis, hippocampus, and periaqueductal gray) that is predictive of individual phenotypic differences. Importantly, individuals with extreme anxious temperament also displayed increased activity of this circuit when assessed in the security of their home environment. These findings suggest that increased activity of this circuit early in life mediates the childhood temperamental risk to develop anxiety and depression. In addition, the findings provide an explanation for why individuals with anxious temperament have difficulty relaxing in environments that others perceive as non-stressful

Correction methods for missing data in sinograms of the HRRT PET scanner

© 2003 The Institute of Electrical and Electronics Engineers, Inc

Performance evaluation of the 32-module quadHIDAC small-animal PET scanner

© 2005 The Society of Nuclear Medicin

Experimental Evaluation of Depth-of-Interaction Correction in a Small-Animal Positron Emission Tomography Scanner

Human and small-animal positron emission tomography (PET) scanners with cylindrical geometry and conventional detectors exhibit a progressive reduction in radial spatial resolution with increasing radial distance from the geometric axis of the scanner. This “depth-of-interaction” (DOI) effect is sufficiently deleterious that many laboratories have devised novel schemes to reduce the magnitude of this effect and thereby yield PET images of greater quantitative accuracy. Here we examine experimentally the effects of a particular DOI correction method (dual-scintillator phoswich detectors with pulse shape discrimination) implemented in a small-animal PET scanner by comparing the same phantom and same mouse images with and without DOI correction. The results suggest that even this relatively coarse, two-level estimate of radial gamma ray interaction position significantly reduces the DOI parallax error. This study also confirms two less appreciated advantages of DOI correction: a reduction in radial distortion and radial source displacement as a source is moved toward the edge of the field of view and a resolution improvement detectable in the central field of view likely owing to improved spatial sampling

Correction methods for missing data in sinograms of the HRRT PET scanner

The high resolution research tomograph (HRRT) is a 3-D PET scanner designed for human brain and small animal imaging. The HRRT consists of eight panel detector heads that are separated by gaps of 17 mm resulting in gaps in the sinogram. Furthermore, gaps can result from detector-block failure. To prevent artifacts in the reconstruction when using Fourier rebinning (FORE), filling the data gaps is required. The purpose of this study was to evaluate the accuracy of three gap filling methods: a) bilinear interpolation of sinogram data; b) a model-based method in which an intermediate volume is reconstructed [2-D ordered subsets expectation maximization (2-D OSEM)] based on direct planes only, after which this image is forward projected to fill the gaps; c) an improved model-based method in which gaps are first filled using interpolation, then reconstructed using FORE + 2-D OSEM and forward projected. The improved model-based method out-performs interpolation, but requires more computation time