Abstract
In this paper, I claim that since (a) there is a cognitively impenetrable (CI) stage of visual perception, namely early vision, and (b) cognitive penetrability (CP) and theory-ladenness are coextensive, the CI of early vision entails that early vision content is theory neutral. This theory-neutral part undermines relativism. In this paper, I consider two objections against the thesis. The one adduces evidence from cases of rapid perceptual learning to undermine my thesis that early vision is CI. The other emphasizes that the early perceptual system, in order to solve various underdetermination problems, relies on certain principles, which may be taken to constitute a sort of a theory about the world that affect early vision, rendering it theory-laden. Both objections purport to show that early vision is CP and theory-laden. Against this thesis, I argue that the evidence on which the two objections are based does not show that early vision is CP and is fully compatible with the view that early vision is CI.
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Notes
Early vision includes a feed forward sweep (FFS) in which signals are transmitted bottom-up and which lasts, in visual areas, for about 100 ms, and a stage at which lateral and recurrent connections between neurons allow recurrent processing. This sort of recurrent processing, which starts at about 80 ms, is restricted within visual areas and does not involve signals from higher cognitive centers. Lamme (2003) calls it local recurrent processing (LRP). LRP culminates at about 120–130 ms. After that, signals from higher executive centers including mnemonic circuits intervene and modulate perceptual processing and this signals the onset of global recurrent processing (GRP). In what follows I refer to “early vision” and “perception” interchangeably unless I state otherwise.
At a first glance the parallelism between epistemic and causal relations seems counterintuitive. After all, two contents can stand in an epistemic relation in the absence of any causal relationship between their respective contents. For example, A believes that p and B believes that p without A having ever met or spoken to B or without A coming to believe p from the same source as B. In this case, there is no causal relation between the two belief states of A and B and, yet, the contents of the two states are identical, and, thus, are epistemically related. Examples like these suggest that causal relations between states are orthogonal to the epistemic relations between their contents. However, I am not talking about the epistemic relations between contents in general but about the epistemic relations between the cognitive and perceptual contents of the same individual when she is viewing a visual scene. With this restriction, the parallelism between causal relations among states and epistemic relations among contents of the individual makes perfect sense.
In this paper, I discuss the effects of visual memory and familiarity that affect the visual circuits in the sort-term, affecting the micro-circuitry of the visual areas. I have argued elsewhere (Raftopoulos 2009) that the perceptual learning that affects in the long-term the visual system and can (re)structure the macro-circuitry of the visual areas does not entail that perception is theory-laden.
The P3 waveform of ERPs is elicited about 250–600 ms and is generated in many areas in the brain, including higher visual areas, and is associated with cognitive processing and the subjects’ reports. P3 may signify the consolidation of the representation of the object(s) in working memory.
The terms “phenomenal seeing” and “doxastic seeing” are construed as in Dretske (1995).
Even if one focuses on points that do not bias one or the other interpretation, the percept flips over between the two interpretations. (Long and Toppino 2004) That is, there is no neutral personal level representation of the whole figure.
References
Burge, T. (2010). Origins of objectivity. Oxford: Clarendon Press.
Chaumon, M., Drouet, V., & Tallon-Baudry, C. (2008). Unconscious associative memory affects visual processing before 100 ms. Journal of Vision, 8(3), 1–10.
Churchland, P. M. (1988). Perceptual plasticity and theoretical neutrality: A reply to Jerry Fodor. Philosophy of Science, 55, 167–187.
Crouzet, S. M., Kirchner, H., & Thorpe, S. J. (2010). Fast saccades toward faces: Face detection in just 100 ms. Journal of Vision, 10(4), 16., 1–17.
Delmore, A., Rousselet, G. A., Mace, M. J.-M., & Fabre-Thorpe, M. (2004). Interaction of top-down and bottom up processing in the fast visual analysis of natural scenes. Cognitive Brain Research, 19, 103–113.
Dilworth, J. (2005). The double content of perception. Synthese, 146, 225–243.
Dretske, F. (1995). Naturalizing the mind. Cambridge, MA: The MIT University Press.
Duhem, P. (1914). The aim and structure of physical theory (2nd ed.) (P. P. Wiener, Trans.). New York: Atheneum.
Fabre-Thorpe, M., Delorme, A., Marlot, C., & Thorpe, S. (2001). A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes. Journal of Cognitive Neuroscience, 13, 171–180.
Ferster, D. (1981). A comparison of binocular depth mechanisms in areas 17 and 18 of the cat visual cortex. The Journal of Physiology, 311, 623–655.
Gregory, R. (1974). Concepts and mechanisms of perception. New York: Charles Scribners and Sons.
Grill-Spector, K., Henson, R., & Martin, A. (2006). Repetition and the brain: Neural models of stimulus-specific effects. Trends in Cognitive Sciences, 10, 14–23.
Grill-Spector, K., Kushnir, T., Hendler, T., Edelman, S., Itzchak, Y., & Malach, R. (1998). A sequence of object-processing stages revealed by fMRI in the Human occipital lobe. Human Brain Mapping, 6, 316–328.
Hanson, N. R. (1958). Patterns of discovery. Cambridge: Cambridge University Press.
Haugeland, J. (1998). Having thought. Cambridge: Harvard University Press.
Johnson, J. S., & Olshausen, B. A. (2005). The earliest EEG signatures of object recognition in a cued-target task are postesensory. Journal of Vision, 5, 299–312.
Kirchner, H., & Thorpe, S. J. (2006). Ultra-rapid object detection with saccadic movements: Visual processing speed revisited. Vision Research, 46, 1762–1776.
Kitcher, P. (2001). Real realism: The Galilean strategy. Philosophical Review, 110(2), 151–199.
Koch, C., & Poggio, T. (1987). Biophysics of computational systems: Neurons synapses, and membranes. In G. M. Edelman, W. E. Gall, & W. M. Cowan (Eds.), Synaptic function. New York: Wiley.
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: Chicago University Press.
Lamme, V. A. F. (2003). Why visual attention and awareness are different. Trends in Cognitive Sciences, 7(1), 12–18.
Lamme, V. A. F., Super, H., Landman, R., Roelfsema, P. R., & Spekreijse, H. (2000). The role of primary visual cortex (V1) in visual awareness. Vision Research, 40, 1507–1521.
Liu, H., Agam, Y., Madsen, J. R., & Krelman, G. (2009). Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron, 62, 281–290.
Long, G. M., & Toppino, Th C. (2004). Enduring interest in perceptual ambiguity: Alternating views of reversible figures. Psychological Bulletin, 130(5), 748–768.
Lyons, J. C. (2011). Circularity, reliability, and the cognitive penetrability of perception. Philosophical Issues, 21, 289–311.
Marr, D. (1982). Vision: A computational investigation into human representation and processing of visual information. San Francisco, CA: Freeman.
Peterson, M. (2003). Overlapping partial configurations in object memory. In M. Peterson & G. Rhodes (Eds.), Perception of faces, objects, and scenes: Analytic and holistic processes. New York, NY: Oxford University Press.
Peterson, M., & Enns, J. (2005). The edge complex: Implicit memory for figure assignment in shape perception. Perception and Psychophysics, 67(4), 727–740.
Peterson, M., & Skow Grant, E. (2003). Memory and learning in figure-ground perception. In B. Ross & D. Irwin (Eds.), Cognitive vision: Psychology of learning and motivation (Vol. 42, pp. 1–34). New York: Elsevier Science.
Poggio, G. F., & Talbot, W. H. (1981). Mechanisms of static and dynamic stereopsis in foveal cortex of the rhesus monkey. The Journal of Physiology, 315, 469–492.
Pylyshyn, Z. (1999). Is vision continuous with cognition? Behavioral and Brain Sciences, 22, 341–365.
Quine, W. V. O. (1960). Word and object. Cambridge, MA: The MIT Press.
Raftopoulos, A. (1999). Newton’s experimental proofs as eliminative reasoning. Erkenntnis, 50(1), 95–125.
Raftopoulos, A. (2001a). Is perception informationally encapsulated? The issue of the theory-ladenness of perception. Cognitive Science, 25, 423–451.
Raftopoulos, A. (2001b). Reentrant pathways and the theory-ladenness of observation. Philosophy of Science, 68, 187–200.
Raftopoulos, A. (2009). Cognition and perception. Cambridge, MA: The MIT Press.
Raftopoulos, A. (2011). Ambiguous figures and representationalism. Synthese, 181(3), 489–514.
Raftopoulos, A., & Muller, V. (2006). Nonconceptual demonstrative reference. Philosophy and Phenomenological Research, 72(2), 251–285.
Schaffer, S. (1989). Glass works: Newton’s prisms and the uses of experiment. In D. Gooding, T. Pinch, & S. Schaffer (Eds.), The uses of experiment: Studies in the natural sciences. Cambridge: Cambridge University Press.
Spelke, E. S. (1990). Principles of object perception. Cognitive Science, 14, 29–56.
Thorpe, S., Fize, D., & Marlot, C. (1996). Speed of processing in the human visual system. Nature, 381, 520–522.
Torralba, A., & Oliva, A. (2003). Statistics of natural image categories. Network, 14, 391–412.
Treisman, A., & Kanwisher, N. G. (1998). Perceiving visually presented objects: Recognition, awareness, and modularity. Current Opinions in Neurobiology, 8, 218–226.
Turnbull, H. W. (Ed.). (1959). The correspondence of Isaak Newton (Vol. 3). Cambridge: Cambridge University Press.
Ulmann, A., & Richards, W. (Eds.). (1990). Image understanding. Norwood, NJ: Ablex.
Ullman, S., Vidal-Naquet, M., & Sali, E. (2002). Visual features of intermediate complexity and their use in classification. Nature Neuroscience, 5(7), 682–687.
VanRullen, R., & Thorpe, S. J. (2001). The time course of visual processing: From early perception to decision making. Journal of Cognitive Neuroscience, 13, 454–461.
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Raftopoulos, A. The Cognitive Impenetrability of Perception and Theory-Ladenness. J Gen Philos Sci 46, 87–103 (2015). https://doi.org/10.1007/s10838-015-9288-6
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DOI: https://doi.org/10.1007/s10838-015-9288-6