Protocol for a pilot and feasibility randomized-controlled trial of four weeks of oral γ-aminobutyric acid (GABA) intake and its effect on pain and sleep in middle-to-older aged adults.

Approximately 1.71 billion people globally live with musculoskeletal pain conditions, including low back pain, knee pain, and neck pain Cieza et al. (2020). In the US, an estimated 20.4% of U.S. adult had chronic pain and 8.0% of U.S. adults had high-impact chronic pain, with higher prevalence associated with advancing age Dahlhamer et al. (2018). On the other hand, between 50 and 70 million US adults have a sleep disorder (American Sleep Association). Although the link between sleep and pain is widely established, the neurobiological mechanisms underlying this relationship have yet to be fully elucidated, specifically within an aged population. As currently available sleep and chronic pain therapies are only partially effective, novel treatment approaches are urgently needed. Given the potential mechanistic role of γ-aminobutyric acid (GABA) in both conditions, and the availability of GABA supplements over the counter, the present proposal will determine the feasibility and acceptability of oral GABA administration in middle-to-older aged adults with chronic pain and sleep disorders as well as characterize the potential neurobiological mechanisms involved in both conditions. Results from the present investigation using a parallel, double-blinded, placebo-controlled study will provide novel preliminary information needed for future translational pain and sleep research.

EECoG-Comp: An Open Source Platform for Concurrent EEG/ECoG Comparisons-Applications to Connectivity Studies.

Electrophysiological Source Imaging (ESI) is hampered by lack of "gold standards" for model validation. Concurrent electroencephalography (EEG) and electrocorticography (ECoG) experiments (EECoG) are useful for this purpose, especially primate models due to their flexibility and translational value for human research. Unfortunately, there is only one EECoG experiments in the public domain that we know of: the Multidimensional Recording (MDR) is based on a single monkey ( www.neurotycho.org ). The mining of this type of data is hindered by lack of specialized procedures to deal with: (1) Severe EECoG artifacts due to the experimental produces; (2) Sophisticated forward models that account for surgery induced skull defects and implanted ECoG electrode strips; (3) Reliable statistical procedures to estimate and compare source connectivity (partial correlation). We provide solutions to the processing issues just mentioned with EECoG-Comp: an open source platform ( https://github.com/Vincent-wq/EECoG-Comp ). EECoG lead fields calculated with FEM (Simbio) for MDR data are also provided and were used in other papers of this special issue. As a use case with the MDR, we show: (1) For real MDR data, 4 popular ESI methods (MNE, LCMV, eLORETA and SSBL) showed significant but moderate concordance with a usual standard, the ECoG Laplacian (standard partial [Formula: see text]); (2) In both monkey and human simulations, all ESI methods as well as Laplacian had a significant but poor correspondence with the true source connectivity. These preliminary results may stimulate the development of improved ESI connectivity estimators but require the availability of more EECoG data sets to obtain neurobiologically valid inferences.

An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats.

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.