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The song control system of song birds is an excellent model for studying brain plasticity and has thus far been extensively analyzed by histological and electrophysiological methods. However, these approaches do not provide a global view of the brain and/or do not allow repeated measures, which are necessary to establish correlations between alterations in neural substrate and behavior. Application of in vivo manganese-enhanced MRI enabled us for the first time to visualize the song control system repeatedly in the same bird, making it possible to quantify dynamically the volume changes in this circuit as a function of seasonal and hormonal influences. In this review, we introduce and explore the song control system of song birds as a natural model for brain plasticity to validate a new cutting edge technique, which we called 'repeated dynamic manganese enhanced MRI' or D-MEMRI. This technique is based on the use of implanted permanent cannulaefor accurate repeated manganese injections in a defined target area-and the subsequent MRI acquisition of the dynamics of the accumulation of manganese in projection brain targets. A compilation of the D-MEMRI data obtained thus far in this system demonstrates the usefulness of this new method for studying brain plasticity. In particular it is shown to be a perfect tool for long-term studies of morphological and functional responses of specific brain circuits to changes in endocrine conditions. The method was also successfully applied to obtain quantitative measures of changes in activity as a function of auditory stimuli in different neuronal populations of a same nucleus that project to different targets. D-MEMRI, combined with other MRI techniques, clearly harbors potential for unraveling seasonal, hormonal, pharmacological or even genetically driven changes in a neuronal circuit, by simultaneously measuring changes in morphology, activity and connectivity.

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In this paper, a method is developed that reconstructs a high resolution image from an arbitrary set of multi-slice 3D MR images with a high in-plane resolution and a low through-plane resolution. Such images are often recorded to increase the efficiency of the acquisition. With a model of the acquisition of MR images, which is improved compared to previous super-resolution methods for MR images, a large system with linear equations is obtained. With the conjugated gradient method and this linear system, a high resolution image is reconstructed from MR images of an object. Also, a new and efficient method to apply an affine transformation to multi-dimensional images is presented. This method is used to efficiently reconstruction the high resolution image from multislice MR images with arbitrary orientations of the slices.