John Hernandez - US grants

Navajo Technical University (NTU) is one of the nation's largest tribal colleges and a leader in delivering academic and research programs for Native Americans. NTU students have access to a plethora of academic programs including strong programs in Science, Technology, Engineering, and Math (STEM). However, NTU and the residents of the Navajo Nation are not well connected to the Internet and to the larger research and education community. Connectivity limitations, especially at Navajo community centers and at their homes, restrict NTU's ability to collaborate and contribute in the ever-growing integrated global research and education environment. There is a fundamental lack of Internet connectivity with sufficient bandwidth to successfully participate in the ever-increasing distance or online learning courses/programs.

This proposal will increase Wide Area Network connectivity by connecting NTU to the Front Range GigaPoP (FRGP) regional network at much higher network speeds with dedicated bandwidth for NTU research and academic projects. The proposal addresses distance education challenges by implementing an advanced wireless test bed to deliver NTU distance education courses to Chapter Houses, tribal libraries, and other community anchor locations. This proposal engages the country's largest tribal university and is a collaboration with New Mexico and Arizona Tribal Colleges and Universities. It leverages a strong existing regional relationship with the FRGP, and it provides an organizational model for other tribal colleges to adopt a similar technology and associated collaborations. The proposal emphasizes needs and requirements-gathering meetings, followed by design and training workshops, which will benefit regional Native American community.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PROJECT SUMMARY/ ABSTRACT Individual variation in alcohol preference and self-administration facilitates compulsive alcohol seeking behavior. However, the circuit identity and function underlying individual variability in alcohol self-administration behaviors is still not well understood. The goal of this proposal is to identify subtle behavioral features, fundamental circuitry principles and neurophysiological dynamics underlying alcohol preference in the tractable model system Drosophila melanogaster. Aim 1 will employ a computer vision and machine learning approach to identify subtle behaviors that relate to alcohol preference and alcohol avoidance. In this Aim I hypothesize that animals that express alcohol preference display enhanced seeking behavior, in particular in response to alcohol self- administration whereas lower alcohol preference will manifest through avoidance and reduced locomotion. Aim 2 will employ thermogenetic inactivation, using the GAL4/UAS system, of learning and memory brain circuits we believe play a direct role in encoding alcohol preference. In this Aim I hypothesize that inactivation of our identified learning and memory brain circuits will directly suppress the expression of alcohol preference in flies. Aim 3 will investigate how the neurophysiological dynamics of our identified circuit differs between alcohol preferers and abstainers. I hypothesize that, in my identified circuit, alcohol exposure will result in robust neurophysiological responses in alcohol-preferers and that we will observe the opposite in alcohol abstainers. This work will provide a framework for predicting general circuit principles for escalation of alcohol self- administration in more complex brains, which is in alignment with NIAAA?s mission to support behavioral research on the causes of alcoholism and alcohol-related problems.