Skip to main content Accessibility help

Codes, functions, and causes: A critique of Brette's conceptual analysis of coding

  • David Barack (a1) and Andrew Jaegle (a1)


Brette argues that coding as a concept is inappropriate for explanations of neurocognitive phenomena. Here, we argue that Brette's conceptual analysis mischaracterizes the structure of causal claims in coding and other forms of analysis-by-decomposition. We argue that analyses of this form are permissible and conceptually coherent and offer essential tools for building and developing models of neurocognitive systems like the brain.



Hide All
Cummins, R. (1975) Functional analysis. Journal of Philosophy 72(20):741–65.
Dennett, D. C. (1981) Brainstorms: Philosophical essays on mind and psychology: MIT Press.
Funahashi, K.-i. & Nakamura, Y. (1993). Approximation of dynamical systems by continuous time recurrent neural networks. Neural Networks 6(6):801–06.
Geman, S., & Geman, D. (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-6(6):721–41. doi:10.1109/TPAMI.1984.4767596.
Graves, A. (2013) Generating sequences with recurrent neural networks. arXiv:1308.0850 [cs.NE].
Heess, N., Sriram, S., Lemmon, J., Merel, J., Wayne, G., Tassa, Y., Erez, T., Wang, Z., Ali Eslami, S. M., Riedmiller, M. J. & Silver, D. (2017) Emergence of locomotion behaviours in rich environments. arXiv:1707.02286 [cs.AI].
Levine, S., Finn, C., Darrell, T. & Abbeel, P. (2016) End-to-end training of deep visuomotor policies. The Journal of Machine Learning Research 17(1):1334–73.
Lycan, W. G. (1981) Form, function, and feel. The Journal of Philosophy 78(1):2450.
Marr, D. (1982a) Vision. Henry Holt.
Oppenheim, A. V. & Schafer, R. W. (2013) Discrete-time signal processing (3rd edition). Pearson.
Rice, C. (2015) Moving beyond causes: Optimality models and scientific explanation. Noûs 49(3):589615.
Roth, S. & Black, M. J. (2005) Fields of experts: A framework for learning image priors. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) 2:860–7. IEEE.
Ryle, G. (1949) The concept of mind. University of Chicago Press.
Santoro, A., Hill, F., Barrett, D., Raposo, D., Botvinick, M. & Lillicrap, T. (2019) Is coding a relevant metaphor for building AI? arXiv:1904.10396 [q-bio.NC].
Schäfer, A. M. & Zimmermann, H. G. (2007) Recurrent neural networks are universal approximators. In: Artificial Neural Networks – ICANN 2006, ed. Kollias, S. D., Stafylopatis, A., Duch, W. & Oja, E.. Lecture Notes in Computer Science, 4131.
Shannon, C. E. & Weaver, W. (1963) The mathematical theory of communication. University of Illinois Press.
Srivastava, N., Mansimov, E. & Salakhutdinov, R. (2015) Unsupervised learning of video representations using LSTMs. Proceedings of Machine Learning Research 37:843–52.
van den Oord, A., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A. & Kavukcuoglu, K. J. S. (2016) WaveNet: A generative model for raw audio. arXiv:1609.03499n[cs.SD].
van den Oord, A., Kalchbrenner, N. & Kavukcuoglu, K. (2016) Pixel recurrent neural networks. Proceedings of Machine Learning Research 48:1727–36.
Walsh, D. M. & Ariew, A. (1996) A taxonomy of functions. Canadian Journal of Philosophy 26(4):493514.

Codes, functions, and causes: A critique of Brette's conceptual analysis of coding

  • David Barack (a1) and Andrew Jaegle (a1)


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed