I am Juan Linde-Domingo a cognitive neuroscientist fascinated by the intricate ways the human mind forms, stores, and retrieves memories. Currently, I hold a Ramón y Cajal Fellowship at the University of Granada and CIMCYC, where I lead research on memory representation using a multidisciplinary toolkit that includes neuroimaging, eye tracking, and behavioral analyses. I am a member of the Memory and Language Research Group and the BIKE cluster. I like drawing and playing video games.
I’ve long been fascinated by how the brain transforms visual input into internal representations (how what we see becomes something the mind can store, interpret, and use). My earlier work explored the oscillatory dynamics that shape this transformation during encoding and, more recently, I’ve been investigating how we recognize visually ambiguous stimuli: what features in the input drive recognition, and how the brain constructs stable perceptual representations from uncertain or degraded information.
mr.cone and mr rod
is this HC riding a theta horse?
However, my love for visual perception is only part of the story. I’m equally interested in understanding the dynamics of episodic and working memory—how internal representations evolve over time, and how they differ from, or align with, those formed through perception. A key focus of my recent work is on the representational match needed for effective memory reactivation: what makes a cue successful in bringing a memory back to life, and how predictive alignment between past and present shapes this process.
time to do science!
AWAKE is a research project exploring how we can more effectively reactivate episodic memories by aligning retrieval cues with the current state of a memory—not just how it was originally encoded. Drawing on behavioral data, eye tracking and neuroimaging, the project introduces the Dynamic Cueing Hypothesis, which proposes that successful memory retrieval depends on matching the evolving nature of memory traces. This work pushes beyond traditional static cueing models, offering new insights into how memories transform over time