The plurality of neurosemantics

  • Vivian M. De La Cruz
  • Alessio Plebe
Keywords: Neurosemantics, neurocomputational models, language, representation, computation, cortex, population coding

Abstract

Neurosemantics is a relatively new approach to investigating the construction of linguistic meaning. In recent years, neurosemantics has been used in two different ways. One regards the meaning of the electrical and the chemical activities going on in neural circuits, or according to what we call the “the semantics of neurons” approach. The second, regards the type of semantics studied for years in philosophy: the meaning of language, but with the added intention of explaining in neural computational terms, what happens when people listen to and understand utterances. We think neurosemantics, understood as the construction of linguistic meaning in neural terms, requires an assumption of continuity.  This is because the physiological strategies upon which language are based are no different in nature, to those by which neurons create non-linguistic conceptual systems. This continuity can subsist defending two different controversial notions, that of representation and computation.

In our work, we explore neurosemantics according to the second sense or approach mentioned above, but in doing so, we address much of the first sense or approach as well, in that we believe that the capacity of neural circuits in humans to support linguistic meaning, hinges on their peculiar role of coding experience.  In this paper, we illustrate examples of linguistic phenomena that can be explained through the employment of these two concepts and briefly describe neurocomputational models that have simulated how this phenomena might be instantiated in the brain.

References

BECHTEL, W., & RICHARDSON, R. C. (1993), Discovering complexity: Decomposition and localization as scientific research strategies, Princeton University Press, Princeton (NJ).

BLACK, A. W., & TAYLOR, P. A. (1997), The festival speech synthesis system: System documenta- tion. Technical report HCRC/TR-83, Human Communication Research Centre, University of Edinburgh, Edinburgh.

BRAILLARD, P.-A., & MALATERRE, C. (2015), Explanation in biology: An introduction, in P.-A. BRAILLARD & C. MALATERRE (eds.), Explanation in biology, history, philosophy and theory of the life sciences, Springer-Verlag, Berlin, pp. 1-28.

BREIDBACH, O. (2007), «Neurosemantics, neurons and system theory», in Theory Bioscience, 126, pp. 23-33.

CHALUPA, L., & WERNER, J. (eds.), (2003), The visual neurosciences, MIT Press, Cambridge (MA).

CHURCH, A. (1941), The calculi of lambda conversion, Princeton (NJ), Princeton University Press.

CHURCHLAND, P. M. (1989), A neurocomputational perspective: The nature of mind and the structure of science, MIT Press, Cambridge (MA).

CHURCHLAND, P. S., & SEJNOWSKI, T. (1994), The computational brain, MIT Press, Cambridge (MA).

CHURCHLAND, P. M. (2001), Neurosemantics: On the mappings of minds and the portrayal of worlds, in K. WHITE (ed.), The emergence of mind, Fondazione Carlo Erba, Milan.

CRAVER, C. F. (2007), Explaining the brain: mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford (UK).

CUMMINS, R. (1989), Meaning and mental representation, MIT Press, Cambridge (MA).

DAYAN, P., & ABBOTT, L. F. (2001), Theoretical neuroscience, MIT Press, Cambridge (MA).

DEHAENE, S. (2014), Consciousness and the brain: Deciphering how the brain codes our thoughts, Viking Adult, New York.

DOUGLAS, R. J., MARTIN, K. A., & WHITTERIDGE, D. (1989), «A canonical microcircuit for neocortex», in Neural Computation, 1, pp. 480-488.

FELDMAN, J. A. (2006), From molecule to metaphor: A neural theory of language, MIT Press, Cambridge.

FELLEMAN, D. J., & VAN ESSEN, D. C. (1991), «Distributed hierarchical processing in the primate cerebral cortex», in Cerebral Cortex, 1, pp. 1-47.

FODOR, J. (1975), The language of thought, Harvard University Press, Cambridge (MA).

FODOR, J. (1981), Representations: Philosofical essay on the foundation of cognitive science, MIT Press, Cambridge (MA).

FODOR, J. (1987), Psychosemantics: The problem of meaning in the philosophy of mind, MIT Press, Cambridge (MA).

FODOR, J. (1990), A theory of content and other essays, Cambridge University Press, Cambridge (UK).

FRESCO, N. (2014), Physical computation and cognitive science, Springer-Verlag, Berlin.

FUSTER, J. M. (2008), The prefrontal cortex, Academic Press, New York 20084.

HINTON, G. E., MCCLELLAND, J. L., & RUMELHART, D. E. (1986), Distributed representations, in D. E. RUMELHART & J. L. MCCLELLAND (eds.), Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1, pp. 77-109, MIT Press, Cambridge (MA).

HUBEL, D., & WIESEL, T. (1959), «Receptive fields of single neurones in the cat’s striate cortex», in Journal of Physiology, 148, pp. 574-591.

HUBEL, D., & WIESEL, T. (1968), «Receptive fields and functional architecture of mokey striate cortex», in Journal of Physiology, 195, pp. 215-243.

HUME, D. (1748), An enquiry concerning human understanding, A. Millar, London.

KAPLAN, D. M. (2011), «Explanation and description in computational neuroscience», in Synthese, 183, pp. 339-373.

KAPLAN, D. M., & CRAVER, C. F. (2011), Towards a mechanistic philosophy of neuroscience, in S. FRENCH & J. SAATSI (eds.), Continuum companion to the philosophy of science, pp. 268-292, Continuum Press, London.

Kleene, S. C. (1936), «General recursive functions of natural numbers», in Mathematische Annalen, 112, pp. 727-742.

KOHONEN, T., & HARI, R. (2000), «Where the abstract feature maps of the brain might come from» in Trends in Neurosciences, 22, pp. 135-139.

KRANTZ, D., LUCE, D., SUPPES, P., & TVERSKY, A. (1971), Foundations of measurement – volume i additive and polynomial representations, Academic Press, New York.

KRUBITZER, L. (1995), «The organization of neocortex in mammals: are species differences really so different?» in Trends in Neuroscience, 8, pp. 408-417.

LUCE, D., KRANTZ, D., SUPPES, P., & TVERSKY, A. (1990), Foundations of measurement – volume iii representation, axiomatization, and invariance, Academic Press, New York.

MACHAMER, P., DARDEN, L., & CRAVER, C. F. (2000), «Thinking about mechanisms», in Philosophy of Science, 67, pp. 1-84.

MASTRONARDE, D. N. (1983), «Correlated firing of retinal ganglion cells: I. Spontaneously active inputs in X- and Y-cells», in Journal of Neuroscience, 14, pp. 409-441.

MIŁKOWSKI, M. (2013), Explaining the computational mind, MIT Press, Cambridge (MA).

MORGAN, A. (2014), «Representations gone mental», in Synthese, 191, pp. 213-244.

MOUNTCASTLE, V. (1957), «Modality and topographic properties of single neurons in cats somatic sensory cortex», in Journal of Neurophysiology, 20, pp. 408-434.

NELSON, R. J. (2002), The somatosensory system: deciphering the brain’s own body image, CRC Press, Boca Raton (FL).

PICCININI, G. (2015), Physical computation: A mechanistic account, Oxford University Press, Oxford (UK).

PLEBE, A., & DE LA CRUZ, V. M. (2014), Color seeing and speaking – effects of biology, environment and language, in ANDERSON W., BIGGAM, C. P., HOUGH, C., & KAY, C. (eds.), Colour studies. A broad spectrum, John Benjamins, Amsterdam, pp. 291-306.

PLEBE, A., & DE LA CRUZ, V. M. (2016), Neurosemantics – neural processes and the construction of linguistic meaning, Springer, Berlin.

PULVERMÜLLER, F. (2002), The neuroscience of language: On brain circuits of words and serial order, Cambridge University Press, Cambridge (UK).

PULVERMÜLLER, F. (2012), «Meaning and the brain: The neurosemantics of referential, interactive, and combinatorial knowledge», in Journal of Neurolinguistics, 25, pp. 423-459.

PUTNAM, H. (1960), Minds and machines, in HOOK S. (ed.), Dimensions of mind, New York University Press, New York.

RAMSEY, W. M. (2007), Representation reconsidered, Cambridge University Press, Cambridge (UK).

RUSSELL, B. (1927), The analysis of matter, Harcourt, London.

RYDER, D. (2004), «Sinbad neurosemantics: A theory of mental representation», in Minds and Machines, 19, pp. 211-240.

SEJNOWSKI, T. J., Koch, C., & Churchland, P. S. (1988), «Computational neuroscience», in Science, 241, p. 1299.

SHAGRIR, O. (2012), «Structural representations and the brain», in British Journal for the Philosophy of Science, 63, pp. 519-545.

SPREVAK, M. (2011), «William m. ramsey, representation reconsidered», in British Journal for the Philosophy of Science, 62, pp. 669-675.

STOCKMAN, A., & BRAINARD, D. H. (2010), Color vision mechanisms, in BASS M. (ed.), OSA handbook of optics, McGraw Hill, New York, Sections 11.1–11.104.

SUPPES, P., KRANTZ, D., LUCE, D., & TVERSKY, A. (1989), Foundations of measurement – volume ii geometrical, threshold, and probabilistic representations, Academic Press, New York.

SWOYER, C. (1991), «Structural representation and surrogative reasoning», in Synthese, 87, pp. 449-508.

THIVIERGE, J.-P., & MARCUS, G. F. (2007), «The topographic brain: from neural connectivity to cognition», in Trends in Neuroscience, 30, pp. 251-259.

TOOTELL, R. B., SILVERMAN, M. S., HAMILTON, S. L., SWITKES, E., & DE VALOIS, R. (1988), «Functional anatomy of the macaque striate cortex. V. spatial frequency», in Journal of Neuroscience, 8, pp. 1610-1624.

TOOTELL, R. B., SWITKES, E., SILVERMAN, M. S., & HAMILTON, S. L. (1988), «Functional anatomy of the macaque striate cortex. III. color», in Journal of Neuroscience, 8, pp. 1531-1568.

TURING, A. (1936), «On computable numbers, with an application to the Entscheidungsproblem», in Proceedings of the London Mathematical Society, 42, pp. 230-265.

VERPLAETSE, J., SCHRIJVER, J. D., VANNESTE, S., & BRAECKMAN, J. (eds.). (2009), The moral brain essays on the evolutionary and neuroscientific aspects of morality, Springer-Verlag, Berlin.

WIESEL, T., & HUBEL, D. (1965), «Binocular interaction in striate cortex of kittens reared with artificial squint», in Journal of Neurophysiology, 28, pp. 1041-1059.

How to Cite
De La Cruz, V. M. and Plebe, A. (1) “The plurality of neurosemantics”, Rivista Italiana di Filosofia del Linguaggio, 00. Available at: http://160.97.104.70/index.php/rifl/article/view/449 (Accessed: 22December2024).