Listar BCBL por autor "Nara, Sanjeev"
Mostrando ítems 1-5 de 5
-
Decoding numeracy and literacy in the human brain: insights from MEG and MVPA
Nara, Sanjeev; Raza, Haider; Carreiras, Manuel; Molinaro, Nicola (NATURE, 2023)Numbers and letters are the fundamental building blocks of our everyday social interactions. Previous studies have focused on determining the cortical pathways shaped by numeracy and literacy in the human brain, partially ... -
Early language dissociation in bilingual minds: magnetoencephalography evidence through a machine learning approach
Molinaro, Nicola; Nara, Sanjeev; Carreiras, Manuel (OXFORD, 2024)Does neural activity reveal how balanced bilinguals choose languages? Despite using diverse neuroimaging techniques, prior studies haven’t provided a definitive solution to this problem. Nonetheless, studies involving ... -
Language experience shapes predictive coding of rhythmic sound sequences
Morucci, Piermatteo; Nara, Sanjeev; Lizarazu, Mikel; Martin, Clara; Molinaro, Nicola (eLife Sciences Publications, 2024)Perceptual systems heavily rely on prior knowledge and predictions to make sense of the environment. Predictions can originate from multiple sources of information, including contextual short-term priors, based on ... -
Spatiotemporal dynamics of postoperative functional plasticity in patients with brain tumors in language areas
Lizarazu, Mikel; Gil Robles, Santiago; Pomposo, Iñigo; Nara, Sanjeev; Amoruso, Lucia; Quiñones, Ileana; Carreiras, Manuel (Brain and Language, 2020)Postoperative functional neuroimaging provides a unique opportunity to investigate the neural mechanisms that facilitate language network reorganization. Previous studies in patients with low grade gliomas (LGGs) in ... -
Temporal uncertainty enhances suppression of neural responses to predictable visual stimuli
Nara, Sanjeev; Lizarazu, Mikel; Richter, Craig G; Dima, Diana C; Cichy, Radoslaw M; Bourguignon, Mathieu; Molinaro, Nicola (NeuroImage, 2021)Contextual information triggers predictions about the content ( “what ”) of environmental stimuli to update an in- ternal generative model of the surrounding world. However, visual information dynamically changes across ...