Investigating the Role of Damaged Neural Circuits in Alzheimer’s Disease

Last year, I had the opportunity to lead an in-depth research project on one of the most complex and devastating conditions of our time: Alzheimer’s disease (AD). My paper, “Investigating the Role of Damaged Neural Circuits in Alzheimer’s Disease,” takes a systems neuroscience approach, exploring how Alzheimer’s is increasingly understood as a disease of network failure rather than just a disorder of amyloid plaques or cell death.

My goal was to examine how damaged neural circuits drive cognitive decline in Alzheimer’s, often before traditional biomarkers like amyloid-beta or tau tangles can even be detected. Through a systematic bibliometric review of the 100 most-cited articles in the field, I focused on three key neural systems:

• The hippocampal circuit, central to memory formation

• The basal forebrain cholinergic system, essential for attention and learning

• The default mode network (DMN), which governs introspection and memory retrieval

Key Insights

• Circuit Dysfunction Precedes Symptoms: Disruptions in connectivity — such as loss of synchrony in theta and gamma brain waves — appear before visible structural degeneration, suggesting that Alzheimer’s symptoms emerge from communication breakdowns between regions.

• Synaptic Loss is Universal: Both human and animal studies consistently showed early synaptic degradation and connectivity loss.

• Network Degeneration Hypothesis: This study supports a growing shift toward the “network degeneration hypothesis,” framing Alzheimer’s as a cascading systems-level failure.

• Potential for Early Intervention: Understanding circuit-level changes opens doors to new therapies — such as non-invasive brain stimulation, closed-loop neuromodulation, and AI-powered network mapping — to detect and even stabilize dysfunction early.

I led the entire review and analysis process, from keyword strategy and bibliometric mapping to data visualization and thematic coding. This process gave me a comprehensive view of how the field has evolved, especially with the integration of neuroimaging, electrophysiology, and computational modeling over the last decade.

After completing an research program discovering this topic and using R programming, this year, I was able to publish a complete article on the findings on it. Read the paper here: https://rspublication.com/ijst/2025/e3/12.html