Antonio Fernandez-Ruiz, PhD

Prize Winner

Position

Assistant Professor Neurobiology and Behavior

Prize

MIND Prize

Cohort

2024

Program

MIND Prize

Institution

Cornell University

Website

braincomputation.org

Project

Restoration of pathological neural dynamics to improve cognition in Alzheimer's disease

Vision

Animals display a remarkable array of complex adaptive behaviors, demonstrating their ability to learn from experience, make new inferences, and flexibly adjust decisions in response to changing environmental demands. These behaviors are supported by the finely tuned dynamics of neuronal ensembles distributed across brain circuits. The primary goal of my research program is to understand the algorithmic and mechanistic underpinnings of flexible natural behavior at the computational, systems, and cellular levels. While the genetic, developmental, and environmental factors underlying brain diseases vary widely, many share common alterations in neural circuit dynamics. I envision that by investigating detailed cellular and circuit mechanisms of cognitive dysfunction in animal models, we will improve our understanding of human diseases and develop more precise therapeutic strategies. To address these challenges and bridge different levels of biological organization, we employ a multidisciplinary approach. A major obstacle are the limitations imposed by current technology. Therefore, a key focus of our efforts is developing novel methods for a more precise interrogation and manipulation of brain circuit dynamics in behaving animals.

About

Antonio Fernandez-Ruiz is an Assistant Professor at Cornell University. He studied physics and biology at the Universities of Sevilla and Madrid, in Spain. He completed his PhD at the University of Madrid, where he developed machine learning methods to study the biophysical basis of brain dynamics. He then moved to New York University to work as a postdoctoral fellow in the laboratory of Gyorgy Buzsaki. His research focused on the neural circuit mechanisms of learning and memory in rodents. His work elucidated how the temporal coordination of excitatory and inhibitory inputs mediates communication between brain areas and supports learning. He developed a novel approach to causally probe the role of specific patterns of neural activity in behavior and used it to demonstrate the key function of neuronal sequence in memory formation. The overarching mission of his lab at Cornell is to understand how neuronal dynamics in distributed brain circuits support complex cognitive functions and how small imbalances can lead to pathological states. His group investigates the algorithmic and mechanistic underpinnings of learning, memory and decision making in health and disease at the computational, circuit, and cellular levels. Antonio is the recipient of the Gruber International Research Award in Neuroscience (SfN), the Blavatnik Award for Young Scientists in the Life Sciences, the Freedman Prize for Exceptional Basic Research (BBRF) and the New Innovator Award (NIH).

The support of the MIND prize will allow us to develop new technology to predict and correct in real time pathological brain activity. Our ultimate goal is improving cognitive deficits in patients with neurodegenerative disease.

Neurodegenerative diseases are characterized by memory deficits. While these diseases are associated with multiple genetic and environmental causes, they involve systematic impairments of information processing in specific neural circuits. However, common pharmacological treatments lack spatial and temporal specificity, resulting in unwanted side effects, and cannot be adjusted rapidly to changes in symptoms. On the other hand, closed-loop methods based on neural activity provide rapid intervention on demand by detecting abnormal neural activity patterns in specific brain circuits. Despite these advantages their application has been limited due to technical challenges.

"Our research aims to uncover general principles of brain function. By focusing on basic neuroscience questions, such as understanding memory, we anticipate laying the groundwork for future disease treatments based on a mechanistic understanding of brain function and disfunction."

In this project I will develop a novel approach to detect and correct pathological brain dynamics in mouse models of Alzheimer’s disease with the goal of reverting their memory deficits. These experiments have the potential to provide a selective therapeutical approach to improve cognitive function in the early stages of Alzheimer’s disease and could pave the way for clinical applications in patients.