Descending projections from the cortex to subcortical structures are critical for auditory plasticity, including the ability for central neurons to adjust their frequency tuning to relevant and meaningful stimuli. We show that focal electrical stimulation of primary auditory cortex in guinea pigs produces excitatory responses in the central nucleus of the inferior colliculus (CNIC) with two tonotopic patterns: a narrow tuned pattern that is consistent with previous findings showing direct frequency-aligned projections; and a broad tuned pattern in which the auditory cortex can influence multiple frequency regions. Moreover, excitatory responses could be elicited in the caudomedial portion along the isofrequency laminae of the CNIC but not in the rostrolateral portion. This descending organization may underlie or contribute to the ability of the auditory cortex to induce changes in frequency tuning of subcortical neurons as shown extensively in previous studies.

The brain is a densely interconnected network that relies on populations of neurons within and across multiple nuclei to code for features leading to perception and action. However, the neurophysiology field is still dominated by the characterization of individual neurons, rather than simultaneous recordings across multiple regions, without consistent spatial reconstruction of their locations for comparisons across studies. There are sophisticated histological and imaging techniques for performing brain reconstructions. However, what is needed is a method that is relatively easy and inexpensive to implement in a typical neurophysiology lab and provides consistent identification of electrode locations to make it widely used for pooling data across studies and research groups. This paper presents our initial development of such an approach for reconstructing electrode tracks and site locations within the guinea pig inferior colliculus (IC) to identify its functional organization for frequency coding relevant for a new auditory midbrain implant (AMI). Encouragingly, the spatial error associated with different individuals reconstructing electrode tracks for the same midbrain was less than 65 μm, corresponding to an error of ~1.5% relative to the entire IC structure (~4–5 mm diameter sphere). Furthermore, the reconstructed frequency laminae of the IC were consistently aligned across three sampled midbrains, demonstrating the ability to use our method to combine location data across animals. Hopefully, through further improvements in our reconstruction method, it can be used as a standard protocol across neurophysiology labs to characterize neural data not only within the IC but also within other brain regions to help bridge the gap between cellular activity and network function. Clinically, correlating function with location within and across multiple brain regions can guide optimal placement of electrodes for the growing field of neural prosthetics.

Medical images such as magnetic resonance (MR) imaging provide valuable information for cancer detection, diagnosis, and prognosis. In addition to the anatomical information these images provide, machine learning can identify texture features from these images to further personalize treatment. This study aims to evaluate the use of texture features derived from T 1 -weighted post contrast scans to classify different types of brain tumors and predict tumor growth rate in a preclinical mouse model. To optimize prediction models this study uses varying gray-level co-occurrence matrix (GLCM) sizes, tumor region selection and different machine learning models. Using a random forest classification model with a GLCM of size 512 resulted in 92%, 91%, and 92% specificity, and 89%, 85%, and 73% sensitivity for GL261 (mouse glioma), U87 (human glioma) and Daoy (human medulloblastoma), respectively. A tenfold cross-validation of the classifier resulted in 84% accuracy when using the entire tumor volume for feature extraction and 74% accuracy for the central tumor region. A two-layer feedforward neural network using the same features is able to predict tumor growth with 16% mean squared error. Broadly applicable, these predictive models can use standard medical images to classify tumor type and predict tumor growth, with model performance, varying as a function of GLCM size, tumor region, and tumor type.

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Background Cranial radiotherapy (CRT) is an important part of brain tumor treatment, and although highly effective, survivors suffer from long-term cognitive side effects. In this study we aim to establish late-term imaging markers of CRT-induced brain injury and identify functional markers indicative of cognitive performance. Specifically, we aim to identify changes in executive function, brain metabolism, and neuronal organization. Methods Male Sprague Dawley rats were fractionally irradiated at 28 days of age to a total dose of 30 Gy to establish a radiation-induced brain injury model. Animals were trained at 3 months after CRT using the 5-choice serial reaction time task. At 12 months after CRT, animals were evaluated for cognitive and imaging changes, which included positron emission tomography (PET) and magnetic resonance imaging (MRI). Results Cognitive deficit with signs of neuroinflammation were found at 12 months after CRT in irradiated animals. CRT resulted in significant volumetric changes in 38% of brain regions as well as overall decrease in brain volume and reduced gray matter volume. PET imaging showed higher brain glucose uptake in CRT animals. Using MRI, irradiated brains had an overall decrease in fractional anisotropy, lower global efficiency, increased transitivity, and altered regional connectivity. Cognitive measurements were found to be significantly correlated with six image features that included myelin integrity and local organization of the neural network. Conclusions These results demonstrate that CRT leads to late-term morphological changes, reorganization of neural connections, and metabolic dysfunction. The correlation between imaging markers and cognitive deficits can be used to assess late-term side effects of brain tumor treatment and evaluate efficacy of new interventions.

We examined the relationship between weight changes after preoperative glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment and weight changes from the start of medical weight management (MWM) until 12 months after bariatric surgery in patients with type 2 diabetes in a retrospective cohort study. A total of 45 patients (64.4% women, median [interquartile range] age 49 [45-60] years) were included. The median (interquartile range) weight loss from start of MWM until 12 months post-surgery was 17.9% (13.0%-29.3%). GLP-1RA treatment during MWM resulted in 5.0% (1.9%-7.7%) weight loss. Weight loss during GLP-1RA treatment predicted weight loss from the start of MWM until 12 months post-surgery, but not postoperative weight loss after adjustment. The proportion of weight loss from start of MWM to 12 months post-surgery attributed to GLP-1RA treatment was negatively associated with that attributed to surgery, after adjustment. In conclusion, weight change after GLP-1RA treatment predicted the weight loss achieved by a combination of MWM and bariatric surgery, but not weight loss induced by surgery only. Failure to lose weight after GLP-1RA treatment should not be considered a barrier to undergoing bariatric surgery.

Positron emission tomography using 18F-Fluro-deoxy-glucose (18F-FDG) is a useful tool to detect regions of inflammation in patients. We utilized this imaging technique to investigate the kinetics of gastrointestinal recovery after radiation exposure and the role of bone marrow in the recovery process. Male Sprague-Dawley rats were either sham irradiated, irradiated with their upper half body shielded (UHBS) at a dose of 7.5 Gy, or whole body irradiated (WBI) with 4 or 7.5 Gy. Animals were imaged using 18F-FDG PET/CT at 5, 10 and 35 days post-radiation exposure. The gastrointestinal tract and bone marrow were analyzed for 18F-FDG uptake. Tissue was collected at all-time points for histological analysis. Following 7.5 Gy irradiation, there was a significant increase in inflammation in the gastrointestinal tract as indicated by the significantly higher 18F-FDG uptake compared to sham. UHBS animals had a significantly higher activity compared to 7.5 Gy WBI at 5 days post-exposure. Animals that received 4 Gy WBI did not show any significant increase in uptake compared to sham. Analysis of the bone marrow showed a significant decrease of uptake in the 7.5 Gy animals 5 days post-irradiation, albeit not observed in the 4 Gy group. Interestingly, as the metabolic activity of the gastrointestinal tract returned to sham levels in UHBS animals it was accompanied by an increase in metabolic activity in the bone marrow. At 35 days post-exposure both gastrointestinal tract and bone marrow 18F-FDG uptake returned to sham levels. 18F-FDG imaging is a tool that can be used to study the inflammatory response of the gastrointestinal tract and changes in bone marrow metabolism caused by radiation exposure. The recovery of the gastrointestinal tract coincides with an increase in bone marrow metabolism in partially shielded animals. These findings further demonstrate the relationship between the gastrointestinal syndrome and bone marrow recovery, and that this interaction can be studied using non-invasive imaging modalities.

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