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Andrea Navas-Olive

Andrea Navas-Olive


Andrea Navas-Olive is a NOMIS–ISTA Fellow at the Institute of Science and Technology Austria (ISTA), working with the research groups of Peter Jonas  (Cellular Neuroscience) and Tim Vogels (Computational Neuroscience and Neurotheory).

Navas-Olive received her BS degree in physics and MS in computer science and machine learning from the Autonomous University of Madrid (Spain). Motivated to understand how the brain works, she focused her BS thesis on theoretical neuroscience. She joined the lab of Liset M de la Prida, where experimental and computational techniques were merged. Navas-Olive completed her PhD in computational neuroscience in 2023. During her doctoral studies, she focused on the hippocampus, a brain region known to be key for navigation and memory. Her research covered multiple aspects of hippocampal computation, ranging from neuronal input integration using realistic models, to memory-related brain rhythms using machine learning.

As a NOMIS Fellow, Navas-Olive will continue investigating the fundamental mechanisms of memory. In particular, she is interested in understanding how properties of individual synaptic connections affect the memory and processing capacity of the whole hippocampus. For that, she will build a full-scale model (simulating every single neuron) and evaluate how small changes in neuron-to-neuron connections affect hippocampal computations such as memory storage capacity. This can be very useful in, for example, identifying the function of already experimentally measured connectivity patterns. Moreover, she plans to use artificial intelligence to look for new neuronal connectivity motifs that maximize memory storage. Results from these simulations will allow us to better understand how the hippocampus operates by predicting the key circuit features of memory that can be tested experimentally. By combining cutting-edge data analysis to better read circuit mechanisms from experimental data, realistic modelling to flexibly overcome experimental recording limitations, and artificial intelligence for unbiased investigation of the fundamental laws governing microcircuit processing, Navas-Olive presents a circuit-analysis approach that can be used as a blueprint for the investigation of circuit function across the brain.

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