Líneas de investigación

• Brain networks subtending cognitive resilience and neural plasticity in aging and preclinical dementia: a translational approach

  Directed by David Bartrés Faz

  The aim is to understand lifestyles and other modifiable factors as well as the brain mechanisms that explain inter individual differences in the capacity to cope with age-related brain changes and initial stages of dementia. The research line combines investigations in humans with those conducted in an animal model of cognitive resilience in dementia, led by Dr Guadalupe Soria, where several measures such as comparable structural and functional neuroimaging data entails a translational aspect.

• Neuroimaging in drug-resistant epilepsy

  Directed by Nuria Bargalló

  Our line of research focuses on the use of advanced neuroimaging techniques for the diagnosis and understanding of epilepsy using advanced magnetic resonance imaging sequences to detect structural and functional abnormalities. Our goal is the localization of brain areas where epileptic seizures originate, facilitating surgical planning. We also investigate the cognitive impairment of patients, such as memory and language as well as its changes after surgery.

• Pain and Emotion Neuroscience

  Directed by Marina López-Solà

  We study neurobiological and psychosocial mechanisms of chronic pain and depression across the lifespan, focusing on women due to their higher risk for nociplastic pain and depression. Using brain imaging, sensory testing, computational tools, wearables, and immune assays, we aim to identify biomarkers of vulnerability, severity, and treatment response, starting in childhood.

• Advanced neuroimaging and AI for modeling neurodegenerative diseases

  Directed by Roser Sala-Llonch

  We focus on the development of cutting-edge methodologies, including algorithms for multimodal neuroimaging data and artificial intelligence, to model neurodegenerative diseases. We apply machine learning and deep learning to neuroimaging data, to develop predictive diagnostic and prognostic models. This includes designing interpretable AI systems that integrate multimodal data, such as imaging, clinical, and genetic information, to create comprehensive models of neurological conditions.

• Neuropsychology and neuroimaging in neurodegenerative diseases

  Directed by Bàrbara Segura

  We aim to identify the mechanisms responsible for cognitive deficits in neurologic diseases using multimodal neuroimaging techniques to contribute to the development of clinically useful imaging biomarkers. We are interested in disentangling the biological basis beyond cognitive and neuroimaging measures as well as exploring their capacity to predict disease evolution and prognosis, mainly to characterize the progression of alpha-synucleinopathies.