- Bowers, J.S. (2002). Challenging the widespread assumption that connectionism and distributed representations go hand-in-hand. Cognitive Psychology, 45, 413-445.
- Bowers, J.S. (2009). On the biological plausibility of grandmother cells: Implications for neural network theories in psychology and neuroscience. Psychological Review, 116, 220–251.
- Bowers, J.S. (2010). More on grandmother cells and the biological implausibility of PDP models of cognition: A reply to Plaut and McClelland (2010) and Quian Quiroga and Kreiman (2010). Psychological Review, 117, 300–306. doi:10.1037/a0018047
- Bowers, J.S. (2017). Parallel Distributed Processing theory in the age of deep networks. Trends in Cognitive Science. https://doi.org/10.1016/j.tics.2017.09.013
- Chang, L., & Tsao, D. Y. (2017). The Code for Facial Identity in the Primate Brain. Cell, 169(6), 1013-1028.
- Gross, C. G. (2002). Genealogy of the “grandmother cell”. The Neuroscientist, 8(5), 512-518.
- Konorski, J. (1967). Integrative activity of the brain: an interdisciplinary approach. Chicago: University of Chicago Press.
- Page, M. P. A. (2000). Connectionist modeling in psychology: A localist manifesto. Behavioral and Brain Sciences, 23, 443–512.
- Page, M. P. A (2017). Localist models are compatible with information measures, sparseness indices, and complementary-learning systems in the brain. Language, Cognition and Neuroscience, 32(3), 366-379.
- Plaut, D.C., and McClelland, J.L. (2010). Locating object knowledge in the brain: Comment on Bower’s (2009) attempt to revive the grandmother cell hypothesis. Psychological Review, 117, 284–288. doi:10.1037/a0017101
- Quian Quiroga, R., and Kreiman, G. (2010). Measuring sparseness in the brain: Comment on Bowers (2009). Psychological Review, 117, 291–297. doi:10.1037/a0016917
- Quian Quiroga in a “Leading Edge Previews” article in the same issue: Quiroga, R. Q. (2017). How Do We Recognize a Face? Cell, 169(6), 975-977.
- Rossion, B., & Taubert, J. (2017). Commentary: The Code for Facial Identity in the Primate Brain. Frontiers in Human Neuroscience, 11, 550.
- Thorpe, S. (1995). Localized versus distributed representations. In M. A. Arbib (Ed.), The handbook of brain theory and neural networks. Cambridge, MA: MIT Press
Some additional papers detailing the biological and computational plausibility of grandmother cells.
- Barlow, H. (1972). Single units and sensation: A neuron doctrine for perceptual psychology. Perception, 1, 371–394.
- Barlow, H. B. (1985). The 12th Bartlett Memorial Lecture: The role of single neurons in the psychology of perception. Quarterly Journal of Experimental Psychology: Section A. Human Experimental Psychology, 37, 121–145.
- Berkeley, I. S. N., Dawson, M. R. W., Medler, D. A., Schopflocher, D. P., & Hornsby, L. (1995). Density plots of hidden unit activations reveal interpretable bands. Connection Science, 7, 167–186.
- Bowers, J. S. (2017). Grandmother cells and localist representations: A review of current thinking. Language, Cognition, & Neuroscience 32, 257-273. DOI: 10.1080/23273798.2016.1267782
- Bowers, J. S., Vankov, I. I., Damian, M. F., & Davis, C. J. (2014). Neural networks learn highly selective representations in order to overcome the superposition catastrophe. Psychological Review, 121, 248-261.
- Bowers, J. S., Vankov, I. I., Damian, M. F., & Davis, C. J. (2016). Why do some neurons in cortex respond to information in a selective manner? Insights from artificial neural networks. Cognition, 148, 47-63.
- Masquelier, T., & Thorpe, S. J. (2007). Unsupervised learning of visual features through spike timing dependent plasticity. PLoS computational biology, 3(2), e31.
- Thorpe, S. (1989). Local vs. distributed coding. Intelletica, 8, 3–40.