Recommended Reading

This is a list of “core” papers that everyone should be familiar with. Please feel free to recommend some!

Semantic Memory

  • Explaining our theory:
    • Fernandino, L. et al. Concept representation reflects multimodal abstraction: A framework for embodied semantics. Cereb Cortex 26, 2018–2034 (2016). [PDF]
    • Binder, J. R. et al. Toward a brain-based componential semantic representation. Cognitive Neuropsych 33, 130–74 (2016). [PDF]
  • Explaining the opposing theory:
    • Patterson, K., Nestor, P. J. & Rogers, T. T. Where do you know what you know? The representation of semantic knowledge in the human brain. Nat Rev Neurosci 8, 976–987 (2007). [PDF]
    • Ralph, M. A. L., Jefferies, E., Patterson, K. & Rogers, T. T. The neural and computational bases of semantic cognition. Nat Rev Neurosci 18, 42–55 (2016). [PDF]
  • The theoretical basis of our theory:
    • Barsalou, L. W. Grounded Cognition. Annu Rev Psychol 59, 617–645 (2008). [PDF]
    • Simmons, W. K. & Barsalou, L. W. The similarity-in-topography principle: reconciling theories of conceptual deficits. Cognitive Neuropsych 20, 451–486 (2010). [PDF]
    • Meyer, K. & Damasio, A. Convergence and divergence in a neural architecture for recognition and memory. Trends Neurosci 32, 376–82 (2009). [PDF]

BCI

  • One of the prominent groups that has decoded speech from the motor cortex:
    • Makin, J. G., Moses, D. A. & Chang, E. F. Machine translation of cortical activity to text with an encoder–decoder framework. Nat Neurosci 23, 575–582 (2020). [PDF]
    • Moses, D. A. et al. Neuroprosthesis for decoding speech in a paralyzed person with anarthria. New Engl J Med 385, 217–227 (2021). [PDF]

Machine Learning

  • Convolutional Networks: Szegedy, C. et al. Going deeper with convolutions. Arxiv (2014). [PDF]
  • Residual Networks: He, K., Zhang, X., Ren, S. & Sun, J. Deep Residual Learning for Image Recognition. Arxiv (2015). [PDF]
  • The Transformer: Vaswani, A. et al. Attention Is All You Need. Arxiv (2017). [PDF]
  • GPT: Radford, A., Narasimhan, K., Salimans, T. & Sutskever, I. Improving language understanding by generative pre-training. (2018). [PDF]