HMN 2026: How Babies categorize objects in the brain at just two months old

Babies as young as two months old are able to categorize distinct objects in their brains—much earlier than previously thought—according to new research from neuroscientists at Trinity College Dublin. The research, which combined brain imaging with artificial intelligence models, enriches our understanding of what babies are thinking and how they learn in the earliest months of life.

The study has been published in the journal Nature Neuroscience by a team from Trinity College Institute of Neuroscience (TCIN) and the School of Psychology.

“Parents and scientists have long wondered what goes on in a baby’s mind and what they actually see when they view the world around them. This research highlights the richness of brain function in the first year of life,” explains Dr. Cliona O’Doherty, lead author on the study who conducted the research while in Trinity’s Cusack Lab.

Early insights into infant cognition

“Although at two months, infants’ communication is limited by a lack of language and fine motor control, their minds were already not only representing how things look, but figuring out to which category they belonged. This shows that the foundations of visual cognition are already in place from very early on and much earlier than expected.”

With the assistance of the Coombe and Rotunda Hospitals in Dublin, the FOUNDCOG team recruited 130 two-month-old infants. Lying on a comfy beanbag and wearing sound-canceling headphones, the babies were shown bright, colorful images which kept them engaged for 15–20 minutes. This provided the team with enough time to use functional MRI (fMRI) to measure their patterns of brain activity in response to pictures representing 12 common visual categories, such as cat, bird, rubber duck, shopping cart and tree.

How the infant brain was studied

Artificial intelligence models were then used to characterize how the babies’ brains represented different visual categories by comparing activity patterns along the pathways for visual recognition between the models and the brains.

“This study represents the largest longitudinal study with functional magnetic resonance imaging (fMRI) of awake infants. The rich dataset capturing brain activity opens up a whole new way to measure what babies are thinking at a very early age. It also highlights the potential for neuroimaging and computational models to be used as a diagnostic tool in very young infants,” explains team lead Rhodri Cusack, the Thomas Mitchell Professor of Cognitive Neuroscience at Trinity’s School of Psychology and Trinity College Institute of Neuroscience.

“Babies learn much more quickly than today’s AI models and by studying how they do this, we hope to inspire a new generation of AI models that learn more efficiently, so reducing their economic and environmental costs.”

Implications for medicine and technology

Dr. Anna Truzzi, who now works at Queen’s University Belfast, is also a co-author on the paper. She added, “Until recently, we could not reliably measure how specific areas of the infant brain interpreted visual information. By combining AI and neuroimaging, our study offers a very unique insight, which helps us to understand much more about how babies learn in their first year of life.

“The first year is a period of rapid and intricate brain development. This study provides new foundational knowledge which will help guide early-years education, inform clinical support for neurodevelopmental conditions and inspire more biologically-grounded approaches in artificial intelligence.”

Professor Eleanor Molloy, a neonatologist from Children’s Health Ireland and co-author emphasized the potential of the study’s high success rates for awake neuroimaging: “There is a pressing need for greater understanding of how neurodevelopmental disorders change early brain development, and awake fMRI has considerable potential to address this.”

Dr. O’Doherty is now based at Stanford University and Dr. Anna Truzzi is a Senior Lecturer at the School of Psychology of Queen’s University Belfast.

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