| Machine learning classifiers and fMRI: a tutorial overview F Pereira, T Mitchell, M Botvinick Neuroimage 45 (1), S199-S209, 2009 | 1967 | 2009 |
| Learning to decode cognitive states from brain images TM Mitchell, R Hutchinson, RS Niculescu, F Pereira, X Wang, M Just, ... Machine learning 57 (1), 145-175, 2004 | 1014* | 2004 |
| Toward a universal decoder of linguistic meaning from brain activation F Pereira, B Lou, B Pritchett, S Ritter, S Gershman, N Kanwisher, ... Nature Communications 9 (963), 2018 | 362 | 2018 |
| Revealing the multidimensional mental representations of natural objects underlying human similarity judgements M Hebart, C Zheng, F Pereira, C Baker Nature Human Behaviour, 2020 | 228 | 2020 |
| Information mapping with pattern classifiers: a comparative study F Pereira, M Botvinick Neuroimage 56 (2), 476-496, 2011 | 190 | 2011 |
| A comparative evaluation of off-the-shelf distributed semantic representations for modelling behavioural data F Pereira, S Gershman, S Ritter, M Botvinick Cognitive neuropsychology 33 (3-4), 175-190, 2016 | 164 | 2016 |
| Semantic projection recovers rich human knowledge of multiple object features from word embeddings G Grand, IA Blank, F Pereira, E Fedorenko Nature human behaviour 6 (7), 975-987, 2022 | 158* | 2022 |
| Reproducibility distinguishes conscious from nonconscious neural representations A Schurger, F Pereira, A Treisman, JD Cohen Science 327 (5961), 97-99, 2010 | 157 | 2010 |
| Data‐driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders CJ Vaidya, X You, S Mostofsky, F Pereira, MM Berl, L Kenworthy Journal of Child Psychology and Psychiatry 61 (1), 51-61, 2020 | 101 | 2020 |
| Generating text from functional brain images F Pereira, G Detre, M Botvinick Frontiers in human neuroscience 5, 72, 2011 | 99* | 2011 |
| Distinguishing grammatical constructions with fMRI pattern analysis K Allen, F Pereira, M Botvinick, AE Goldberg Brain and language 123 (3), 174-182, 2012 | 89 | 2012 |
| Closed-form supervised dimensionality reduction with generalized linear models I Rish, G Grabarnik, G Cecchi, F Pereira, GJ Gordon Proceedings of the 25th International Conference on Machine learning, 832-839, 2008 | 85 | 2008 |
| Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments F Pereira, M Botvinick, G Detre Artificial intelligence 194, 240-252, 2013 | 82 | 2013 |
| Detecting significant multidimensional spatial clusters D Neill, A Moore, F Pereira, TM Mitchell Advances in Neural Information Processing Systems 17, 969-976, 2004 | 77 | 2004 |
| Network, anatomical, and non-imaging measures for the prediction of ADHD diagnosis in individual subjects JW Bohland, S Saperstein, F Pereira, J Rapin, L Grady Frontiers in systems neuroscience 6, 78, 2012 | 71 | 2012 |
| The support vector decomposition machine F Pereira, G Gordon Proceedings of the 23rd international conference on Machine learning, 689-696, 2006 | 68 | 2006 |
| Knowing what you know in brain segmentation using Bayesian deep neural networks P McClure, N Rho, JA Lee, JR Kaczmarzyk, CY Zheng, SS Ghosh, ... Frontiers in Neuroinformatics 13, 2019 | 63 | 2019 |
| Cell-type-specific recruitment of GABAergic interneurons in the primary somatosensory cortex by long-range inputs S naskar, J Qi, F Pereira, C Gerfen, S Lee cell reports 34 (8), 2021 | 53 | 2021 |
| Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest J Gonzalez-Castillo, C Caballero-Gaudes, N Topolski, DA Handwerker, ... NeuroImage 202, 116129, 2019 | 53 | 2019 |
| Assessment of traumatic brain injury F Pereira, B Odry, HE Cetingul US Patent 9,265,441, 2016 | 45 | 2016 |
Matthew BotvinickGoogle DeepMind, Yale Law School, University College London在 google.com 的电子邮件经过验证
