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Updated: May 30, 2026

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
Published on: May 19, 2015
Functional and structural correlates of the aging brain: relating visual cortex (V1) gamma band responses to
William Gaetz1, Timothy P L Roberts, Krish D Singh
1Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA. gaetzw@e-mail.chop.edu
Abstract:
The gamma band response is thought to be a key neural signature of information processing in the mammalian brain, yet little is known about how age-related maturation influences the γ-band response. Recent MRI-based studies have shown that brain maturation is accompanied by clear structural changes in both gray and white matter, yet the correspondence of these changes to brain function is unclear. The objective of this study was to relate visual cortex (V1) γ-band responses to age-related structural change. We evaluated MEG measured γ-band responses to contrast gratings stimuli and structural MRIs from participants observed from two separate research centers (MEG lab at CUBRIC, Cardiff University, UK, and the Lurie Family Foundations MEG Imaging Center, (CHOP) at the Children's Hospital of Philadelphia). Pooled participant data (N = 59) ranged in age from 8.7 to 45.3 years. We assessed linear associations between age and MEG γ-band frequency and amplitude, as well as between age and MRI volumetric parameters of the occipital lobe. Our MEG findings revealed a significant negative correlation for gamma band frequency versus age. Volumetric brain analysis from the occipital lobe also revealed significant negative correlations between age and the cortical thickness of pericalcarine and cuneus areas. Our functional MEG and structural MRI findings shows regionally specific changes due to maturation and may thus be informative for understanding physiological processes of neural development, maturation, and age-related decline. In addition, this study represents (to our knowledge), the first published demonstration of multicenter data sharing across MEG centers.
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