# Circuit mechanisms underlying network disruption and temporal processing deficits in Alzheimer's > **NIH NIH R01** · UNIVERSITY OF OREGON · 2022 · $659,684 ## Abstract Abstract: Despite substantial knowledge of the molecular and genetic mechanisms contributing to amyloid pathology, very little is known about how these molecular mechanisms affect the operation of neural circuits, and how this disrupts neural computation to ultimately produce behavioral deficits in Alzheimer's. Here we seek to understand the mechanisms underlying two emerging early biomarkers — auditory gap detection deficits and functional disconnection of cortical networks — and how these are mechanistically related to one another. The objective of this proposal is to determine when and how network function is disrupted in auditory and other cortical areas, and how this impairs behavioral gap detection in the 5XFAD mouse model of Alzheimer's. Our central hypothesis is that gap detection deficits result from specific disruption of gap detection circuits in auditory cortex, as a consequence of large-scale network disruption both within and among cortical areas. Aim 1 will determine the computational mechanisms underlying progressive network disruption. Our working hypothesis is that network disruption is not just a global degradation, but occurs specifically as a loss of hub neurons over time, disconnecting modules and cortical areas. Aim 2 will determine how network disruption affects the flow of feedforward and feedback information across the cortical hierarchy. Our working hypothesis is that top-down feedback projections are impaired earlier and more profoundly than feedforward projections. Aim 3 will determine how network disruption impairs the computation of gap selectivity in auditory cortex, and how this impairs gap detection behavior. Our working hypothesis is that gap selectivity is computed in the superficial layers and impacts behavior via output from layer 5. We will test these hypotheses with a combination of chronic mesoscopic 2-photon GCaMP8f imaging, high-density electrophysiology, and quantitative behavior in 5XFAD mice. The proposed research is innovative because it uses novel imaging/electrophysiology approaches to address how molecular pathology disrupts the operation of neural circuits, and how this in turn disrupts neural computation to produce early-onset behavioral deficits. The proposed research is significant because it will provide a detailed cellular- and synaptic-level mechanistic explanation of the nature of large-scale network disruptions in Alzheimer's, and reveal how these disruptions affect specific neural computations in auditory cortical circuits that produce specific behavioral deficits. This understanding will deepen and extend the validity of both gap detection and fMRI functional connectivity measures as early biomarkers for Alzheimer's, and provide insight into the nature of the window of opportunity for potential therapeutic intervention during synaptic network impairment before permanent structural damage occurs. ## Key facts - **NIH application ID:** 10448151 - **Project number:** 1R01AG077681-01 - **Recipient organization:** UNIVERSITY OF OREGON - **Principal Investigator:** Michael Wehr - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $659,684 - **Award type:** 1 - **Project period:** 2022-06-15 → 2027-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10448151 ## Citation > US National Institutes of Health, RePORTER application 10448151, Circuit mechanisms underlying network disruption and temporal processing deficits in Alzheimer's (1R01AG077681-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10448151. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*