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Based on previous findings in humans and rhesus monkeys suggesting that diazepam has asymmetrical effects on frontal lobe activity and other literature supporting a role for the benzodiazepine system in the mediation of individual differences in anxiety and fearfulness, the relation between asymmetrical changes in scalp-recorded regional brain activity in response to diazepam and the temperamental dimension of behavioral inhibition indexed by freezing time in 9 rhesus monkeys was examined. Animals showed greater relative left-sided frontal activation in response to diazepam compared with the preceding baseline. The magnitude of this shift was strongly correlated with an aggregate measure of freezing time (r = .82). The implications of these findings for understanding the role of regional differences in the benzodiazepine system in mediating individual differences in fearfulness are discussed.
We present a new sparse shape modeling framework on the Laplace-Beltrami (LB) eigenfunctions. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes by forming a Fourier series expansion. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we propose to filter out only the significant eigenfunctions by imposing l1-penalty. The new sparse framework can further avoid additional surface-based smoothing often used in the field. The proposed approach is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shapes in the normal population. In addition, we show how the emotional response is related to the anatomy of the subcortical structures.
We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination of basis functions. The basic properties of the representation are investigated in connection with a self-adjoint partial differential equation and the traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, a new iterative residual fitting (IRF) algorithm is developed. Its computational and numerical implementation issues are discussed in detail. The computer codes are also available at http://www.stat.wisc.edu/-mchung/softwares/weighted.SPHARM/weighted-SPHARM.html. As an illustration, the WFS is applied i n quantifying the amount ofgray matter in a group of high functioning autistic subjects. Within the WFS framework, cortical thickness and gray matter density are computed and compared.