Skip to main content

Advertisement

SpringerLink
Log in

Neural Representations Observed

  • Published:
Minds and Machines Aims and scope Submit manuscript

Abstract

The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Notes

  1. This is not an exhaustive list. For instance, we won't discuss neural representation of space (Andersen et al. 1997; Moser et al. 2008).

  2. Similar notions of representation are defended by Shepard and Chipman (1970), Swoyer (1991), Cummins (1996), Grush (2004), O'Brien and Opie (2004), Ryder (2004, forthcoming), Bartels (2006), Waskan (2006), Ramsey (2007), Bechtel (2008), Churchland (2012), Shagrir (2012), Isaac (2013), Hohwy (2013), Clark (2016), Morgan (2014) and Neander (2017, Chap. 8).

  3. For a fuller treatment, see Hubel and Wiesel (2005), Rodieck (1998) and Wandell (1995).

  4. Technically, the inequality states that if X → Y → Z is a Markov Chain, then I(X; Y) ≥ I(X; Z), where I() is mutual information. Using this to theorize about internal states of the animal assumes that the behavior of the animal in the working memory task depends on some internal state of the animal after the stimulus was presented. This is easy enough to demonstrate by removing the brain of the animal.

  5. Note that humans beat dogs by a good order of magnitude. One study presented 10,000 pictures to passive observers in one sitting, and they were later able to recognize them with 90% accuracy (Standing 1973).

  6. Note that ablating M1 does not always lead to permanent paresis, but more short-lived and subtle motor deficits (Schwartzman 1978). Sometimes such ablations show no notable motor deficits, but instead deficits in motor learning (Kawai et al. 2015, though see Castro 1972; Makino et al. 2017). Such results undermine simple stories in which M1 is the final common output driving all movement. Some of the most recalcitrant movement deficits such as Parkinson's disease result from damage to subcortical structures like the basal ganglia. As discussed briefly at the end of this section, motor control is distributed across multiple cortical and subcortical areas, and the focus on M1 here is a convenience meant to keep the discussion contained, not an endorsement of strict localizationist theories of M1 motor control.

  7. Discussions of explicit/implicit coding have always taken place in the sensory system, so it is not actually clear if these are the correct standards to use for M1, which tends to send its outputs to muscles and central pattern generators (Kalaska 2009).

  8. Note that ‘implicit’ is not the same as ‘distributed’ or ‘population’ code. ‘Implicit' implies ‘population' but not vice versa. Even in Georgopoulos' work, perhaps the locus classicus of explicit motor representations, to know the velocity of the animal's arm you must know the firing rate of the population of M1 neurons. That is, everyone in the game accepts that motor control involves a distributed code.

  9. Sometimes these terms are used differently. For instance, ‘corollary discharge’ is sometimes taken to be the output of a forward model (see below). However, the two terms are typically used as synonyms in the literature. For instance, "A ubiquitous strategy is to route copies of movement commands to sensory structures. These signals, which are referred to as corollary discharge (CD), influence sensory processing in myriad ways" (Crapse and Sommer 2008). It would be a mistake to conclude, as (Clark 2016) does, that a paper doesn't support the existence of efference copy just because it uses the phrase 'corollary discharge'.

  10. Why would such plasticity be useful in the electric fish? The local EM fields produced by the same EOD can change depending on changes in water resistivity, or if the animal is swimming, or spending considerable time next to a nonconducting surface such as a rock or air at the water's surface (Bell 1982), so the sensory consequences of the EOD are likely malleable enough that it is helpful to learn them (Bell 1981).

References

  • Adams, F., & Aizawa, K. (2010). Causal theories of mental content. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2010 Edition). https://plato.stanford.edu/archives/spr2010/entries/content-causal/.

  • Albright, T. D. (1984). Direction and orientation selectivity of neurons in visual area MT of the macaque. Journal of Neurophysiology, 52(6), 1106–1130.

    Article  Google Scholar 

  • Alexander, G. E., & Crutcher, M. D. (1990). Preparation for movement: Neural representations of intended direction in three motor areas of the monkey. Journal of Neurophysiology, 64(1), 133–150.

    Article  Google Scholar 

  • Andersen, R. A., Snyder, L. H., Bradley, D. C., & Xing, J. (1997). Multimodal representation of space in the posterior parietal cortex and its use in planning movements. Annual Review of Neuroscience, 20, 303–330. https://doi.org/10.1146/annurev.neuro.20.1.303.

    Article  Google Scholar 

  • Anscombe, E. (1957). Intention. Ithaca, NY: Cornell University Press.

    Google Scholar 

  • Armstrong, D. M. (1973). Belief, truth, and knowledge. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Awater, H., Kerlin, J. R., Evans, K. K., & Tong, F. (2005). Cortical representation of space around the blind spot. Journal of Neurophysiology, 94(5), 3314–3324. https://doi.org/10.1152/jn.01330.2004.

    Article  Google Scholar 

  • Azim, E., Jiang, J., Alstermark, B., & Jessell, T. M. (2014). Skilled reaching relies on a V2a propriospinal internal copy circuit. Nature, 508(7496), 357–363. https://doi.org/10.1038/nature13021.

    Article  Google Scholar 

  • Azzi, J. C., Gattass, R., Lima, B., Soares, J. G., & Fiorani, M. (2015). Precise visuotopic organization of the blind spot representation in primate V1. Journal of Neurophysiology, 113(10), 3588–3599. https://doi.org/10.1152/jn.00418.2014.

    Article  Google Scholar 

  • Bartels, A. (2006). Defending the structural concept of representation. Theoria, 21(55), 7–19.

    MathSciNet  MATH  Google Scholar 

  • Bastian, J. (1996). Plasticity in an electrosensory system. I. General features of a dynamic sensory filter. Journal of Neurophysiology, 76(4), 2483–2496.

    Article  Google Scholar 

  • Bauer, R. H., & Fuster, J. M. (1976). Delayed-matching and delayed-response deficit from cooling dorsolateral prefrontal cortex in monkeys. Journal of Comparative and Physiological Psychology, 90(3), 293–302.

    Article  Google Scholar 

  • Baylor, D. A. (1987). Photoreceptor signals and vision. Proctor lecture. Investigative Ophthalmology & Visual Science, 28(1), 34–49.

    Google Scholar 

  • Bechtel, W. (2008). Mental mechanisms: Philosophical perspectives on cognitive neuroscience. London: Routledge.

    Google Scholar 

  • Bechtel, W. (2016). Investigating neural representations: The tale of place cells. Synthese, 193(5), 1287–1321.

    Article  Google Scholar 

  • Beer, R., & Williams, P. (2014). Information processing and dynamics in minimally cognitive agents. Cognitive Science, 39, 1–38.

    Article  Google Scholar 

  • Bell, C. C. (1981). An efference copy which is modified by reafferent input. Science, 214(4519), 450–453.

    Article  Google Scholar 

  • Bell, C. C. (1982). Properties of a modifiable efference copy in an electric fish. Journal of Neurophysiology, 47(6), 1043–1056.

    Article  Google Scholar 

  • Bell, C. C., Libouban, S., & Szabo, T. (1983). Pathways of the electric organ discharge command and its corollary discharges in mormyrid fish. Journal of Comparative Neurology, 216(3), 327–338. https://doi.org/10.1002/cne.902160309.

    Article  Google Scholar 

  • Bialek, W., & Rieke, F. (1992). Reliability and information transmission in spiking neurons. Trends in Neurosciences, 15(11), 428–434.

    Article  Google Scholar 

  • Bickle, J. (2003). Philosophy and neuroscience: A Ruthlessly reductive approach. Dordrecht: Kluwer.

    Book  Google Scholar 

  • Blasdel, G. G. (1992). Orientation selectivity, preference, and continuity in monkey striate cortex. Journal of Neuroscience, 12(8), 3139–3161.

    Google Scholar 

  • Bolhuis, J. J., & Everaert, M. (2013). Birdsong, speech, and language: Exploring the evolution of mind and brain. Cambridge, MA: MIT Press.

    Google Scholar 

  • Bolkan, S. S., Stujenske, J. M., Parnaudeau, S., Spellman, T. J., Rauffenbart, C., Abbas, A. I., et al. (2017). Thalamic projections sustain prefrontal activity during working memory maintenance. Nature Neuroscience, 20(7), 987–996. https://doi.org/10.1038/nn.4568.

    Article  Google Scholar 

  • Boone, W., & Piccinini, G. (2016). The cognitive neuroscience revolution. Synthese, 193(5), 1509–1534.

    Article  Google Scholar 

  • Born, R. T., & Bradley, D. C. (2005). Structure and function of visual area MT. Annual Review of Neuroscience, 28, 157–189. https://doi.org/10.1146/annurev.neuro.26.041002.131052.

    Article  Google Scholar 

  • Bourget, D., & Mendelovici, A. (2017). Phenomenal intentionality. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2017 Edition) (forthcoming). https://plato.stanford.edu/archives/spr2017/entries/phenomenal-intentionality/.

  • Brainard, M. S., & Doupe, A. J. (2002). What songbirds teach us about learning. Nature, 417(6886), 351–358. https://doi.org/10.1038/417351a.

    Article  Google Scholar 

  • Brandom, R. B. (1994). Making it explicit: Reasoning, representing, and discursive commitment. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Brecht, M., Schneider, M., Sakmann, B., & Margrie, T. W. (2004). Whisker movements evoked by stimulation of single pyramidal cells in rat motor cortex. Nature, 427(6976), 704–710. https://doi.org/10.1038/nature02266.

    Article  Google Scholar 

  • Briggman, K. L., Helmstaedter, M., & Denk, W. (2011). Wiring specificity in the direction-selectivity circuit of the retina. Nature, 471(7337), 183–188. https://doi.org/10.1038/nature09818.

    Article  Google Scholar 

  • Brooks, R. (1991). Intelligence without representation. Artificial Intelligence, 47(1–3), 139–159.

    Article  Google Scholar 

  • Brooks, J. X., Carriot, J., & Cullen, K. E. (2015). Learning to expect the unexpected: Rapid updating in primate cerebellum during voluntary self-motion. Nature Neuroscience, 18(9), 1310–1317. https://doi.org/10.1038/nn.4077.

    Article  Google Scholar 

  • Buchanan, T. S., Lloyd, D. G., Manal, K., & Besier, T. F. (2004). Neuromusculoskeletal modeling: Estimation of muscle forces and joint moments and movements from measurements of neural command. Journal of Applied Biomechanics, 20(4), 367–395.

    Article  Google Scholar 

  • Bullock, T. H. (1982). Electroreception. Annual Review of Neuroscience, 5, 121–170. https://doi.org/10.1146/annurev.ne.05.030182.001005.

    Article  Google Scholar 

  • Burge, T. (2010). Origins of objectivity. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Burnston, D. C. (2016a). Computational neuroscience and localized neural function. Synthese, 193(12), 3741–3762.

    Article  MathSciNet  Google Scholar 

  • Burnston, D. C. (2016b). A contextualist approach to functional localization in the brain. Biology and Philosophy, 31(4), 527–550.

    Article  Google Scholar 

  • Butterfill, S. A., & Sinigaglia, C. (2014). Intention and motor representation in purposive action. Philosophy and Phenomenological Research, 88(1), 119–145.

    Article  Google Scholar 

  • Carlson, B. A. (2002). Neuroanatomy of the mormyrid electromotor control system. Journal of Comparative Neurology, 454(4), 440–455. https://doi.org/10.1002/cne.10462.

    Article  Google Scholar 

  • Castro, A. J. (1972). The effects of cortical ablations on digital usage in the rat. Brain Research, 37(2), 173–185.

    Article  Google Scholar 

  • Cerminara, N. L., Apps, R., & Marple-Horvat, D. E. (2009). An internal model of a moving visual target in the lateral cerebellum. Journal of Physiology, 587(2), 429–442. https://doi.org/10.1113/jphysiol.2008.163337.

    Article  Google Scholar 

  • Chang, H. (2004). Inventing temperature: Measurement and scientific progress. New York: Oxford University Press.

    Book  Google Scholar 

  • Chang, H. T., Ruch, T. C., & Ward, A. A., Jr. (1947). Topographical representation of muscles in motor cortex of monkeys. Journal of Neurophysiology, 10(1), 39–56.

    Article  Google Scholar 

  • Chang, L., & Tsao, D. Y. (2017). The code for facial identity in the primate brain. Cell, 169(6), 1013–1028. https://doi.org/10.1016/j.cell.2017.05.011.

    Article  Google Scholar 

  • Chemero, A. (2009). Radical embodied cognitive science. Cambridge, MA: MIT Press.

    Google Scholar 

  • Chomsky, N. (1995). Language and nature. Mind, 104, 1–61.

    Article  Google Scholar 

  • Churchland, P. S. (1986). Neurophilosophy: Toward a unified science of the mind-brain. Cambridge, MA: The MIT Press.

    Google Scholar 

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

    Google Scholar 

  • Churchland, P. M. (2012). Plato’s camera: How the physical brain captures a landscape of abstract universals. Cambridge, MA: MIT Press.

    Google Scholar 

  • Churchland, M. M., Cunningham, J. P., Kaufman, M. T., Ryu, S. I., & Shenoy, K. V. (2010). Cortical preparatory activity: Representation of movement or first cog in a dynamical machine? Neuron, 68(3), 387–400. https://doi.org/10.1016/j.neuron.2010.09.015.

    Article  Google Scholar 

  • Churchland, P. S., & Sejnowski, T. J. (1992). The computational brain. Cambridge, MA: MIT Press.

    MATH  Google Scholar 

  • Cisek, P., & Kalaska, J. F. (2010). Neural mechanisms for interacting with a world full of action choices. Annual Review of Neuroscience, 33, 269–298. https://doi.org/10.1146/annurev.neuro.051508.135409.

    Article  Google Scholar 

  • Clark, A. (1993). Associative engines: Connectionism, concepts, and representational change. Cambridge, MA: MIT Press.

    Google Scholar 

  • Clark, A. (1997). The dynamical challenge. Cognitive Science, 21, 461–481.

    Article  Google Scholar 

  • Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Clark, A., & Toribio, J. (1994). Doing without representing? Synthese, 101, 401–431.

    Article  Google Scholar 

  • Collins, T. (2010). Extraretinal signal metrics in multiple-saccade sequences. Journal of Vision, 10(14), 7. https://doi.org/10.1167/10.14.7.

    Article  Google Scholar 

  • Colombo, M. (2014). Neural representationalism, the hard problem of content and vitiated verdicts. A reply to Hutto & Myin (2013). Phenomenology and the Cognitive Sciences, 13(2), 257–274.

    Article  Google Scholar 

  • Confais, J., Kim, G., Tomatsu, S., Takei, T., & Seki, K. (2017). Nerve-specific input modulation to spinal neurons during a motor task in the monkey. Journal of Neuroscience, 37(10), 2612–2626. https://doi.org/10.1523/JNEUROSCI.2561-16.2017.

    Article  Google Scholar 

  • Cover, T. M., & Thomas, J. A. (2006). Elements of information theory (2nd ed.). Hoboken, NJ: Wiley.

    MATH  Google Scholar 

  • Craik, K. (1943). The nature of explanation. Cambridge: Cambridge University Press.

    Google Scholar 

  • Crapse, T. B., & Sommer, M. A. (2008). Corollary discharge across the animal kingdom. Nature Reviews Neuroscience, 9(8), 587–600. https://doi.org/10.1038/nrn2457.

    Article  Google Scholar 

  • Craver, C. F. (2007). Explaining the brain. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Cummins, R. (1983). The nature of psychological explanation. Cambridge, MA: MIT Press.

    Google Scholar 

  • Cummins, R. (1989). Meaning and mental representation. Cambridge, MA: MIT Press.

    Google Scholar 

  • Cummins, R. (1996). Representations, targets, and attitudes. Cambridge, MA: MIT Press.

    Google Scholar 

  • Daniel, P. M., & Whitteridge, D. (1961). The representation of the visual field on the cerebral cortex in monkeys. Journal of Physiology, 159, 203–221.

    Article  Google Scholar 

  • Darling, W. G., Pizzimenti, M. A., & Morecraft, R. J. (2011). Functional recovery following motor cortex lesions in non-human primates: Experimental implications for human stroke patients. Journal of Integrative Neuroscience, 10(3), 353–384. https://doi.org/10.1142/S0219635211002737.

    Article  Google Scholar 

  • DeAngelis, G. C., & Newsome, W. T. (1999). Organization of disparity-selective neurons in macaque area MT. Journal of Neuroscience, 19(4), 1398–1415.

    Google Scholar 

  • Denk, W., & Horstmann, H. (2004). Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biology, 2(11), e329. https://doi.org/10.1371/journal.pbio.0020329.

    Article  Google Scholar 

  • Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press.

    Google Scholar 

  • Dennett, D. C. (1991). Consciousness explained. Boston: Little, Brown and Co.

    Google Scholar 

  • Ding, H., Smith, R. G., Poleg-Polsky, A., Diamond, J. S., & Briggman, K. L. (2016). Species-specific wiring for direction selectivity in the mammalian retina. Nature, 535(7610), 105–110. https://doi.org/10.1038/nature18609.

    Article  Google Scholar 

  • Doupe, A. J., & Kuhl, P. K. (1999). Birdsong and human speech: Common themes and mechanisms. Annual Review of Neuroscience, 22, 567–631. https://doi.org/10.1146/annurev.neuro.22.1.567.

    Article  Google Scholar 

  • Dow, B. M., Snyder, A. Z., Vautin, R. G., & Bauer, R. (1981). Magnification factor and receptive field size in foveal striate cortex of the monkey. Experimental Brain Research, 44(2), 213–228.

    Article  Google Scholar 

  • Dowling, J. E. (2012). The retina: An approachable part of the brain (Rev. Ed. ed.). Cambridge, MA: Belknap Press of Harvard University Press.

    Google Scholar 

  • Downey, A. (2017). Predictive processing and the representation wars: A victory for the eliminativist (via fictionalism). Synthese. https://doi.org/10.1007/s11229-017-1442-8.

    Google Scholar 

  • Dretske, F. I. (1981). Knowledge & the flow of information (1st ed.). Cambridge, MA: MIT Press.

    MATH  Google Scholar 

  • Dretske, F. I. (1988). Explaining behavior: Reasons in a world of causes. Cambridge, MA: MIT Press.

    Google Scholar 

  • Egan, F. (2014). How to think about mental content. Philosophical Studies, 170(1), 115–135.

    Article  MathSciNet  Google Scholar 

  • Eliasmith, C. (2001). Attractive and in-discrete: A critique of two putative virtues of the dynamicist theory of mind. Minds and Machines, 11, 417–426.

    Article  Google Scholar 

  • Elsayed, G. F., Lara, A. H., Kaufman, M. T., Churchland, M. M., & Cunningham, J. P. (2016). Reorganization between preparatory and movement population responses in motor cortex. Nature Communications, 7, 13239. https://doi.org/10.1038/ncomms13239.

    Article  Google Scholar 

  • Feldman, D. E. (2012). The spike-timing dependence of plasticity. Neuron, 75(4), 556–571. https://doi.org/10.1016/j.neuron.2012.08.001.

    Article  Google Scholar 

  • Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1(1), 1–47.

    Article  Google Scholar 

  • Ferretti, G. (2016). Through the forest of motor representations. Consciousness and Cognition, 43, 177–196. https://doi.org/10.1016/j.concog.2016.05.013.

    Article  Google Scholar 

  • Fetz, E. E. (1992). Are movement parameters recognizably coded in the activity of single neurons? Behavioral and Brain Sciences, 15, 679–690.

    Google Scholar 

  • Fodor, J. A. (1975). The language of thought. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Fodor, J. A. (1981). Representations: Philosophical essays on the foundations of cognitive science. Cambridge, MA: MIT Press.

    Google Scholar 

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

    Google Scholar 

  • Fodor, J. A. (1990). A theory of content and other essays. Cambridge, MA: MIT Press.

    Google Scholar 

  • Fodor, J. A. (2008). LOT 2: The language of thought revisited. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Forssberg, H., Kinoshita, H., Eliasson, A. C., Johansson, R. S., Westling, G., & Gordon, A. M. (1992). Development of human precision grip. II. Anticipatory control of isometric forces targeted for object’s weight. Experimental Brain Research, 90(2), 393–398.

    Article  Google Scholar 

  • Franklin, A. (2002). Selectivity and discord: Two problems of experiment. Pittsburgh: University of Pittsburgh Press.

    Google Scholar 

  • Franklin, A. (2013). Shifting standards: Experiments in particle physics in the twentieth century. Pittsburgh: University of Pittsburgh Press.

    Google Scholar 

  • Franklin, A., & Perovic, S. (2016). Experiment in physics. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2016 Edition). https://plato.stanford.edu/archives/win2016/entries/physics-experiment/.

  • Frege, G. (1892). Über Sinn und Bedeutung. In Zeitschrift für Philosophie und philosophische Kritik (Vol. 100, pp. 25–50). Translated as ‘On Sense and Reference’ by M. Black in Translations from the Philosophical Writings of Gottlob Frege, P. Geach and M. Black (eds. and trans.), Oxford: Blackwell, third edition, 1980.

  • Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989). Mnemonic coding of visual space in the monkey’s dorsolateral prefrontal cortex. Journal of Neurophysiology, 61(2), 331–349. https://doi.org/10.1152/jn.1989.61.2.331.

    Article  Google Scholar 

  • Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1993a). Dorsolateral prefrontal lesions and oculomotor delayed-response performance: Evidence for mnemonic “scotomas”. Journal of Neuroscience, 13(4), 1479–1497.

    Google Scholar 

  • Funahashi, S., Chafee, M. V., & Goldman-Rakic, P. S. (1993b). Prefrontal neuronal activity in rhesus monkeys performing a delayed anti-saccade task. Nature, 365(6448), 753–756. https://doi.org/10.1038/365753a0.

    Article  Google Scholar 

  • Fuster, J. M., & Alexander, G. E. (1970). Delayed response deficit by cryogenic depression of frontal cortex. Brain Research, 20(1), 85–90.

    Article  Google Scholar 

  • Fuster, J. M., & Alexander, G. E. (1971). Neuron activity related to short-term memory. Science, 173(3997), 652–654.

    Article  Google Scholar 

  • Galison, P. (1987). How experiments end. Chicago: University of Chicago Press.

    Google Scholar 

  • Galison, P. (1997). Image and logic. Chicago: University of Chicago Press.

    Google Scholar 

  • Gallistel, C. R. (1990). Representations in animal cognition: An introduction. Cognition, 37(1–2), 1–22.

    Article  Google Scholar 

  • Gallistel, C. R. (2008). Learning and representation. In J. Byrne (Ed.), Learning and memory: A comprehensive reference (pp. 227–242). Amsterdam: Elsevier.

    Chapter  Google Scholar 

  • Gallistel, C. R., & King, A. P. (2009). Memory and the computational brain: Why cognitive science will transform neuroscience. New York: Wiley.

    Book  Google Scholar 

  • Gandhi, N. J., & Katnani, H. A. (2011). Motor functions of the superior colliculus. Annual Review of Neuroscience, 34, 205–231. https://doi.org/10.1146/annurev-neuro-061010-113728.

    Article  Google Scholar 

  • Ganguly, K., & Carmena, J. M. (2009). Emergence of a stable cortical map for neuroprosthetic control. PLoS Biology, 7(7), e1000153. https://doi.org/10.1371/journal.pbio.1000153.

    Article  Google Scholar 

  • Gardenfors, P. (1996). Cued and detached representations in animal cognition. Behavioral Processes, 35, 263–273.

    Article  Google Scholar 

  • Gardenfors, P. (2005). The detachment of thought. In C. Erneling & D. Johnson (Eds.), Mind as a scientific subject: Between brain and culture (pp. 323–341). Oxford: OUP.

    Google Scholar 

  • Garzon, F. C. (2008). Towards a general theory of antirepresentationalism. The British Journal for the Philosophy of Science, 59(3), 259–292.

    Article  Google Scholar 

  • Gazzaley, A., & Nobre, A. C. (2012). Top-down modulation: Bridging selective attention and working memory. Trends in Cognitive Sciences, 16(2), 129–135. https://doi.org/10.1016/j.tics.2011.11.014.

    Article  Google Scholar 

  • Georgopoulos, A. P., & Ashe, J. (2000). One motor cortex, two different views. Nature Neuroscience, 3(10), 963. https://doi.org/10.1038/79882. (author reply 964–965).

    Article  Google Scholar 

  • Georgopoulos, A. P., Kalaska, J. F., Caminiti, R., & Massey, J. T. (1982). On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. Journal of Neuroscience, 2(11), 1527–1537.

    Google Scholar 

  • Georgopoulos, A. P., Schwartz, A. B., & Kettner, R. E. (1986). Neuronal population coding of movement direction. Science, 233(4771), 1416–1419.

    Article  Google Scholar 

  • Gilbert, C. D., & Li, W. (2013). Top-down influences on visual processing. Nature Reviews Neuroscience, 14(5), 350–363. https://doi.org/10.1038/nrn3476.

    Article  Google Scholar 

  • Gładziejewski, P. (2016). Predictive coding and representationalism. Synthese, 193, 559–582.

    Article  Google Scholar 

  • Gładziejewski, P., & Miłkowski, M. (2017). Structural representations: Causally relevant and different from detectors. Biology and Philosophy, 32(3), 337–355.

    Article  Google Scholar 

  • Godfrey-Smith, P. (1996). Complexity and the function of mind in nature. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Goldberg, M. E., & Wurtz, R. H. (1972). Activity of superior colliculus in behaving monkey. I. Visual receptive fields of single neurons. Journal of Neurophysiology, 35(4), 542–559.

    Article  Google Scholar 

  • Goodale, M. A., & Milner, A. D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1), 20–25.

    Article  Google Scholar 

  • Graziano, M. S. (2016). Ethological action maps: A paradigm shift for the motor cortex. Trends in Cognitive Sciences, 20(2), 121–132. https://doi.org/10.1016/j.tics.2015.10.008.

    Article  Google Scholar 

  • Graziano, M. S., Taylor, C. S., Moore, T., & Cooke, D. F. (2002). The cortical control of movement revisited. Neuron, 36(3), 349–362.

    Article  Google Scholar 

  • Grice, P. (1957). Meaning. Philosophical Review, 66, 377–388.

    Article  Google Scholar 

  • Griffin, D. M., Hoffman, D. S., & Strick, P. L. (2015). Corticomotoneuronal cells are “functionally tuned”. Science, 350(6261), 667–670. https://doi.org/10.1126/science.aaa8035.

    Article  Google Scholar 

  • Grush, R. (2004). The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences, 27(3), 377–396. (discussion 396–442).

    Google Scholar 

  • Hacking, I. (1983). Representing and intervening. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Hahnloser, R. H., & Kotowicz, A. (2010). Auditory representations and memory in birdsong learning. Current Opinion in Neurobiology, 20(3), 332–339. https://doi.org/10.1016/j.conb.2010.02.011.

    Article  Google Scholar 

  • Hallett, M. (2000). Transcranial magnetic stimulation and the human brain. Nature, 406(6792), 147–150. https://doi.org/10.1038/35018000.

    Article  Google Scholar 

  • Hartmann, K., Thomson, E. E., Zea, I., Yun, R., Mullen, P., Canarick, J., et al. (2016). Embedding a panoramic representation of infrared light in the adult rat somatosensory cortex through a sensory neuroprosthesis. Journal of Neuroscience, 36(8), 2406–2424. https://doi.org/10.1523/JNEUROSCI.3285-15.2016.

    Article  Google Scholar 

  • Heiligenberg, W., & Bastian, J. (1984). The electric sense of weakly electric fish. Annual Review of Physiology, 46, 561–583. https://doi.org/10.1146/annurev.ph.46.030184.003021.

    Article  Google Scholar 

  • Herculano-Houzel, S. (2010). Coordinated scaling of cortical and cerebellar numbers of neurons. Frontiers in Neuroanatomy, 4, 12. https://doi.org/10.3389/fnana.2010.00012.

    Google Scholar 

  • Hewitt, A. L., Popa, L. S., Pasalar, S., Hendrix, C. M., & Ebner, T. J. (2011). Representation of limb kinematics in Purkinje cell simple spike discharge is conserved across multiple tasks. Journal of Neurophysiology, 106(5), 2232–2247. https://doi.org/10.1152/jn.00886.2010.

    Article  Google Scholar 

  • Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., et al. (2012). Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 485(7398), 372–375. https://doi.org/10.1038/nature11076.

    Article  Google Scholar 

  • Hodgkin, A. L., & Huxley, A. F. (1939). Action potentials recorded from inside a nerve fibre. Nature, 144, 710–711. https://doi.org/10.1038/144710a0.

    Article  Google Scholar 

  • Hohwy, J. (2013). The predictive mind. New York: Oxford University Press.

    Book  Google Scholar 

  • Holdefer, R. N., & Miller, L. E. (2002). Primary motor cortical neurons encode functional muscle synergies. Experimental Brain Research, 146(2), 233–243. https://doi.org/10.1007/s00221-002-1166-x.

    Article  Google Scholar 

  • Horgan, S., & Tienson, J. (1992). Cognitive systems as dynamical systems. Topoi, 11, 27–43.

    Article  Google Scholar 

  • Horgan, T., & Tienson, J. (1996). Connectionism and the philosophy of psychology. Cambridge, MA: MIT Press.

    Google Scholar 

  • Horgan, T., & Tienson, J. (2002). The intentionality of phenomenology and the phenomenology of intentionality. In D. Chalmers (Ed.), Philosophy of mind: Classical and contemporary readings (pp. 520–933). Oxford: Oxford University Press.

    Google Scholar 

  • Horsley, V. (1907). Dr. Hughlings Jackson’s views of the functions of the cerebellum, as Illustrated by recent research. The British Medical Journal, 1(2414), 803–808.

    Article  Google Scholar 

  • Horsley, V. (1909). The linacre lecture on the function of the so-called motor area of the Brain. The British Medical Journal, 2(2533), 121–132.

    Article  Google Scholar 

  • Hotton, S., & Yoshimi, J. (2010). Extending dynamical systems theory to model embodied cognition. Cognitive Science, 35, 444–479.

    Article  MATH  Google Scholar 

  • Houk, J. C., & Wise, S. P. (1995). Distributed modular architectures linking basal ganglia, cerebellum, and cerebral cortex: Their role in planning and controlling action. Cerebral Cortex, 5(2), 95–110.

    Article  Google Scholar 

  • Hubel, D. H., & Wiesel, T. N. (1968). Receptive fields and functional architecture of monkey striate cortex. Journal of Physiology, 195(1), 215–243.

    Article  Google Scholar 

  • Hubel, D. H., & Wiesel, T. N. (2005). Brain and visual perception: The story of a 25-year collaboration. New York, NY: Oxford University Press.

    Google Scholar 

  • Hughlings Jackson, J. (1867). Remarks on the disorderly movements of chorea and convulsion, and on localisation. Medical Times and Gazette, 2, 669–670.

    Google Scholar 

  • Hughlings Jackson, J. (1868). Notes on the physiology and pathology of the nervous system. Medical Times and Gazette, 2, 696.

  • Hupe, J. M., James, A. C., Payne, B. R., Lomber, S. G., Girard, P., & Bullier, J. (1998). Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons. Nature, 394(6695), 784–787. https://doi.org/10.1038/29537.

    Article  Google Scholar 

  • Hutto, D. D., & Myin, E. (2013). Radicalizing enactivism. Cambridge, MA: MIT Press.

    Google Scholar 

  • Hutto, D. D., & Myin, E. (2014). Neural representations not needed-no more pleas, please. Phenomenology and the Cognitive Sciences, 13(2), 241–256.

    Article  Google Scholar 

  • Inoue, S., & Matsuzawa, T. (2007). Working memory of numerals in chimpanzees. Current Biology, 17(23), R1004–R1005. https://doi.org/10.1016/j.cub.2007.10.027.

    Article  Google Scholar 

  • Isaac, A. (2013). Objective similarity and mental representation. Australasian Journal of Philosophy, 91(4), 683–704.

    Article  Google Scholar 

  • Ito, M. (1970). Neurophysiological aspects of the cerebellar motor control system. International Journal of Neurology, 7(2), 162–176.

    Google Scholar 

  • Johansson, R. S., & Cole, K. J. (1992). Sensory-motor coordination during grasping and manipulative actions. Current Opinion in Neurobiology, 2(6), 815–823.

    Article  Google Scholar 

  • Kakei, S., Hoffman, D. S., & Strick, P. L. (1999). Muscle and movement representations in the primary motor cortex. Science, 285(5436), 2136–2139.

    Article  Google Scholar 

  • Kalaska, J. F. (2009). From intention to action: Motor cortex and the control of reaching movements. Advances in Experimental Medicine and Biology, 629, 139–178. https://doi.org/10.1007/978-0-387-77064-2_8.

    Article  Google Scholar 

  • Kaminski, J., Call, J., & Fischer, J. (2004). Word learning in a domestic dog: evidence for “fast mapping”. Science, 304(5677), 1682–1683. https://doi.org/10.1126/science.1097859.

    Article  Google Scholar 

  • Kandel, E. R. (2006). In search of memory: The emergence of a new science of mind (1st ed.). New York: W. W. Norton & Company.

    Google Scholar 

  • Kandel, E. R. (2013). Principles of neural science (5th ed.). New York: McGraw-Hill.

    Google Scholar 

  • Keijzer, F. A. (1998). Doing without representations which specify what to do. Philosophical Psychology, 11(3), 269–302.

    Article  Google Scholar 

  • Kennedy, A., Wayne, G., Kaifosh, P., Alvina, K., Abbott, L. F., & Sawtell, N. B. (2014). A temporal basis for predicting the sensory consequences of motor commands in an electric fish. Nature Neuroscience, 17(3), 416–422. https://doi.org/10.1038/nn.3650.

    Article  Google Scholar 

  • Kiefer, A., & Hohwy, J. (2017). Content and misrepresentation in hierarchical generative models. Synthese. https://doi.org/10.1007/s11229-017-1435-7.

    Google Scholar 

  • Kirsh, D. (2006). Implicit and explicit representation encyclopedia of cognitive science (pp. 1–4). New York: Wiley.

    Google Scholar 

  • Kitamura, T., Ogawa, S. K., Roy, D. S., Okuyama, T., Morrissey, M. D., Smith, L. M., et al. (2017). Engrams and circuits crucial for systems consolidation of a memory. Science, 356(6333), 73–78. https://doi.org/10.1126/science.aam6808.

    Article  Google Scholar 

  • Koch, C. (2004). The quest for consciousness: A neurobiological approach. Denver, CO: Roberts and Co.

    Google Scholar 

  • Komatsu, H., Kinoshita, M., & Murakami, I. (2000). Neural responses in the retinotopic representation of the blind spot in the macaque V1 to stimuli for perceptual filling-in. Journal of Neuroscience, 20(24), 9310–9319.

    Google Scholar 

  • Konishi, M. (1965). The role of auditory feedback in the control of vocalization in the white-crowned sparrow. Z Tierpsychol, 22(7), 770–783.

    Google Scholar 

  • Korenbrot, J. I. (2012). Speed, sensitivity, and stability of the light response in rod and cone photoreceptors: Facts and models. Progress in Retinal and Eye Research, 31(5), 442–466. https://doi.org/10.1016/j.preteyeres.2012.05.002.

    Article  Google Scholar 

  • Krahe, R., & Maler, L. (2014). Neural maps in the electrosensory system of weakly electric fish. Current Opinion in Neurobiology, 24(1), 13–21. https://doi.org/10.1016/j.conb.2013.08.013.

    Article  Google Scholar 

  • Krauzlis, R. J., Lovejoy, L. P., & Zenon, A. (2013). Superior colliculus and visual spatial attention. Annual Review of Neuroscience, 36, 165–182. https://doi.org/10.1146/annurev-neuro-062012-170249.

    Article  Google Scholar 

  • Kriegel, U. (Ed.). (2013). Phenomenal intentionality. Oxford: Oxford University Press.

    Google Scholar 

  • Kustov, A. A., & Robinson, D. L. (1996). Shared neural control of attentional shifts and eye movements. Nature, 384(6604), 74–77. https://doi.org/10.1038/384074a0.

    Article  Google Scholar 

  • Lacquaniti, F., Borghese, N. A., & Carrozzo, M. (1992). Internal models of limb geometry in the control of hand compliance. Journal of Neuroscience, 12(5), 1750–1762.

    Google Scholar 

  • Lamme, V. A., Super, H., & Spekreijse, H. (1998). Feedforward, horizontal, and feedback processing in the visual cortex. Current Opinion in Neurobiology, 8(4), 529–535.

    Article  Google Scholar 

  • Leavitt, M. L., Mendoza-Halliday, D., & Martinez-Trujillo, J. C. (2017). Sustained activity encoding working memories: Not fully distributed. Trends in Neurosciences, 40(6), 328–346. https://doi.org/10.1016/j.tins.2017.04.004.

    Article  Google Scholar 

  • Leopold, D. A. (2012). Primary visual cortex: Awareness and blindsight. Annual Review of Neuroscience, 35, 91–109. https://doi.org/10.1146/annurev-neuro-062111-150356.

    Article  Google Scholar 

  • Leopold, D. A., & Logothetis, N. K. (1996). Activity changes in early visual cortex reflect monkeys’ percepts during binocular rivalry. Nature, 379(6565), 549–553. https://doi.org/10.1038/379549a0.

    Article  Google Scholar 

  • Lewis, J. E., & Kristan, W. B., Jr. (1998a). A neuronal network for computing population vectors in the leech. Nature, 391(6662), 76–79. https://doi.org/10.1038/34172.

    Article  Google Scholar 

  • Lewis, J. E., & Kristan, W. B., Jr. (1998b). Representation of touch location by a population of leech sensory neurons. Journal of Neurophysiology, 80(5), 2584–2592.

    Article  Google Scholar 

  • Li, P. H., Field, G. D., Greschner, M., Ahn, D., Gunning, D. E., Mathieson, K., et al. (2014). Retinal representation of the elementary visual signal. Neuron, 81(1), 130–139. https://doi.org/10.1016/j.neuron.2013.10.043.

    Article  Google Scholar 

  • Li, C. S., Padoa-Schioppa, C., & Bizzi, E. (2001). Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field. Neuron, 30(2), 593–607.

    Article  Google Scholar 

  • Lisberger, S. G. (2009). Internal models of eye movement in the floccular complex of the monkey cerebellum. Neuroscience, 162(3), 763–776. https://doi.org/10.1016/j.neuroscience.2009.03.059.

    Article  Google Scholar 

  • Liu, L. D., & Pack, C. C. (2017). The contribution of area MT to visual motion perception depends on training. Neuron, 95(2), 436–446. https://doi.org/10.1016/j.neuron.2017.06.024.

    Article  Google Scholar 

  • Lloyd, D. G., & Besier, T. F. (2003). An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. Journal of Biomechanics, 36(6), 765–776.

    Article  Google Scholar 

  • Loar, B. (2003). Phenomenal intentionality as the basis of mental content. In M. Hahn & B. Ramberg (Eds.), Reflections and replies: Essays on the philosophy of Tyler Burge (pp. 229–258). Cambridge, MA: MIT Press.

    Google Scholar 

  • Makino, H., Ren, C., Liu, H., Kim, A. N., Kondapaneni, N., Liu, X., et al. (2017). Transformation of cortex-wide emergent properties during motor learning. Neuron, 94(4), 880–890. https://doi.org/10.1016/j.neuron.2017.04.015.

    Article  Google Scholar 

  • Maley, C. (2017). Toward analog neural computation. Minds and Machines. https://doi.org/10.1007/s11023-017-9442-5.

    Google Scholar 

  • Mandik, P. (2003). Varieties of representation in evolved and embodied neural networks. Biology and Philosophy, 18, 95–130.

    Article  Google Scholar 

  • Mangel, S. C. (1991). Analysis of the horizontal cell contribution to the receptive field surround of ganglion cells in the rabbit retina. Journal of Physiology, 442, 211–234.

    Article  Google Scholar 

  • Marler, P., & Peters, S. (1981). Sparrows learn adult song and more from memory. Science, 213(4509), 780–782. https://doi.org/10.1126/science.213.4509.780.

    Article  Google Scholar 

  • Masland, R. H. (2012). The neuronal organization of the retina. Neuron, 76(2), 266–280. https://doi.org/10.1016/j.neuron.2012.10.002.

    Article  Google Scholar 

  • Matsumoto, M., & Komatsu, H. (2005). Neural responses in the macaque v1 to bar stimuli with various lengths presented on the blind spot. Journal of Neurophysiology, 93(5), 2374–2387. https://doi.org/10.1152/jn.00811.2004.

    Article  Google Scholar 

  • Matyas, F., Sreenivasan, V., Marbach, F., Wacongne, C., Barsy, B., Mateo, C., et al. (2010). Motor control by sensory cortex. Science, 330(6008), 1240–1243. https://doi.org/10.1126/science.1195797.

    Article  Google Scholar 

  • Maunsell, J. H., & van Essen, D. C. (1983). The connections of the middle temporal visual area (MT) and their relationship to a cortical hierarchy in the macaque monkey. Journal of Neuroscience, 3(12), 2563–2586.

    Google Scholar 

  • McFarland, J. M., Bondy, A. G., Saunders, R. C., Cumming, B. G., & Butts, D. A. (2015). Saccadic modulation of stimulus processing in primary visual cortex. Nature Communications, 6, 8110. https://doi.org/10.1038/ncomms9110.

    Article  Google Scholar 

  • Milkowski, M. (2013). Explaining the computational mind. Cambridge, MA: MIT Press.

    Google Scholar 

  • Miller, E. K., Erickson, C. A., & Desimone, R. (1996). Neural mechanisms of visual working memory in prefrontal cortex of the macaque. Journal of Neuroscience, 16(16), 5154–5167.

    Google Scholar 

  • Miller, H., Rayburn-Reeves, R., & Zentall, T. (2009). What do dogs know about hidden objects? Behavioral Processes, 81(3), 439–446.

    Article  Google Scholar 

  • Millikan, R. G. (1984). Language, thought, and other biological categories: New foundations for realism. Cambridge, MA: MIT Press.

    Google Scholar 

  • Millikan, R. G. (1993). White Queen psychology and other essays for alice. Cambridge, MA: MIT Press.

    Google Scholar 

  • Mishkin, M., & Manning, F. J. (1978). Non-spatial memory after selective prefrontal lesions in monkeys. Brain Research, 143(2), 313–323.

    Article  Google Scholar 

  • Mooney, R. (2009). Neural mechanisms for learned birdsong. Learning & Memory, 16(11), 655–669. https://doi.org/10.1101/lm.1065209.

    Article  Google Scholar 

  • Moran, D. W., & Schwartz, A. B. (2000). One motor cortex, two different views. Nature Neuroscience, 3(10), 963. https://doi.org/10.1038/79880. (author reply 963–965).

    Article  Google Scholar 

  • Morgan, A. (2014). Representations gone mental. Synthese, 191(2), 213–244.

    Article  Google Scholar 

  • Morgan, A., & Piccinini, G. (2017). Towards a cognitive neuroscience of intentionality. Minds and Machines. https://doi.org/10.1007/s11023-017-9437-2

    Google Scholar 

  • Mori, S., & Zhang, J. (2006). Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron, 51(5), 527–539. https://doi.org/10.1016/j.neuron.2006.08.012.

    Article  Google Scholar 

  • Morris, R. G., Garrud, P., Rawlins, J. N., & O’Keefe, J. (1982). Place navigation impaired in rats with hippocampal lesions. Nature, 297(5868), 681–683.

    Article  Google Scholar 

  • Moser, E. I., Kropff, E., & Moser, M. B. (2008). Place cells, grid cells, and the brain’s spatial representation system. Annual Review of Neuroscience, 31, 69–89. https://doi.org/10.1146/annurev.neuro.31.061307.090723.

    Article  Google Scholar 

  • Movshon, J. A., & Newsome, W. T. (1996). Visual response properties of striate cortical neurons projecting to area MT in macaque monkeys. Journal of Neuroscience, 16(23), 7733–7741.

    Google Scholar 

  • Muckli, L., & Petro, L. S. (2013). Network interactions: non-geniculate input to V1. Current Opinion in Neurobiology, 23(2), 195–201. https://doi.org/10.1016/j.conb.2013.01.020.

    Article  Google Scholar 

  • Murray, J. D., Jaramillo, J., & Wang, X. J. (2017). Working memory and decision-making in a frontoparietal circuit model. Journal of Neuroscience, 37(50), 12167–12186. https://doi.org/10.1523/JNEUROSCI.0343-17.2017.

    Article  Google Scholar 

  • Mylopoulos, M., & Pacherie, E. (2017). Intentions and motor representations: The interface challenge. Review of Philosophy and Psychology, 8(2), 317–336. https://doi.org/10.1007/s13164-016-0311-6.

    Article  Google Scholar 

  • Nabavi, S., Fox, R., Proulx, C. D., Lin, J. Y., Tsien, R. Y., & Malinow, R. (2014). Engineering a memory with LTD and LTP. Nature, 511(7509), 348–352. https://doi.org/10.1038/nature13294.

    Article  Google Scholar 

  • Neander, K. (2012). Teleological theories of mental content. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2012 Edition). https://plato.stanford.edu/archives/spr2012/entries/content-teleological/.

  • Neander, K. (2017). A mark of the mental: In defense of informational teleosemantics. Cambridge, MA: MIT Press.

    Google Scholar 

  • Newsome, W. T., Britten, K. H., & Movshon, J. A. (1989). Neuronal correlates of a perceptual decision. Nature, 341(6237), 52–54. https://doi.org/10.1038/341052a0.

    Article  Google Scholar 

  • Newsome, W. T., & Pare, E. B. (1988). A selective impairment of motion perception following lesions of the middle temporal visual area (MT). Journal of Neuroscience, 8(6), 2201–2211.

    Google Scholar 

  • Noë, A. (2010). Vision without representation. In N. Gangopadhyay, M. Madary, & F. Spicer (Eds.), Perception, action, and consciousness: Sensiromotor dynamics and two visual systems (pp. 245–256). Oxford: OUP.

    Chapter  Google Scholar 

  • O’Brien, G., & Opie, J. (2004). Notes toward a structuralist theory of mental representation. In H. Clapin, P. Staines, & P. Slezac (Eds.), Representation in mind (pp. 1–20). Amsterdam: Elsevier.

    Google Scholar 

  • Papineau, D. (1984). Representation and explanation. Philosophy of Science, 51, 550–572.

    Article  Google Scholar 

  • Papineau, D. (1993). Philosophical naturalism. Oxford: Blackwell.

    Google Scholar 

  • Penfield, W., & Boldrey, E. (1937). Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain, 60, 389–443. https://doi.org/10.1093/brain/60.4.389.

    Article  Google Scholar 

  • Perrett, D. I., Rolls, E. T., & Caan, W. (1982). Visual neurones responsive to faces in the monkey temporal cortex. Experimental Brain Research, 47(3), 329–342.

    Article  Google Scholar 

  • Pfenning, A. R., Hara, E., Whitney, O., Rivas, M. V., Wang, R., Roulhac, P. L., et al. (2014). Convergent transcriptional specializations in the brains of humans and song-learning birds. Science, 346(6215), 1256846. https://doi.org/10.1126/science.1256846.

    Article  Google Scholar 

  • Phongphanphanee, P., Mizuno, F., Lee, P. H., Yanagawa, Y., Isa, T., & Hall, W. C. (2011). A circuit model for saccadic suppression in the superior colliculus. Journal of Neuroscience, 31(6), 1949–1954. https://doi.org/10.1523/JNEUROSCI.2305-10.2011.

    Article  Google Scholar 

  • Piccinini, G. (forthcoming). Nonnatural mental representation. In K. Dolega, T. Schlicht, J. Smortchkova (Eds.), What are mental representations? Oxford: Oxford University Press.

  • Piccinini, G., & Scarantino, A. (2011). Information processing, computation, and cognition. Journal of Biological Physics, 37(1), 1–38.

    Article  Google Scholar 

  • Pickering, M. J., & Clark, A. (2014). Getting ahead: Forward models and their place in cognitive architecture. Trends in Cognitive Sciences, 18(9), 451–456. https://doi.org/10.1016/j.tics.2014.05.006.

    Article  Google Scholar 

  • Pilley, J., & Reid, A. (2011). Border collie comprehends object names as verbal referents. Behavioral Processes, 86, 184–195.

    Article  Google Scholar 

  • Polonsky, A., Blake, R., Braun, J., & Heeger, D. J. (2000). Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry. Nature Neuroscience, 3(11), 1153–1159. https://doi.org/10.1038/80676.

    Article  Google Scholar 

  • Poulet, J. F., & Hedwig, B. (2003). Corollary discharge inhibition of ascending auditory neurons in the stridulating cricket. Journal of Neuroscience, 23(11), 4717–4725.

    Google Scholar 

  • Poulet, J. F., & Hedwig, B. (2006). The cellular basis of a corollary discharge. Science, 311(5760), 518–522. https://doi.org/10.1126/science.1120847.

    Article  Google Scholar 

  • Prather, J. F., Peters, S., Nowicki, S., & Mooney, R. (2010). Persistent representation of juvenile experience in the adult songbird brain. Journal of Neuroscience, 30(31), 10586–10598. https://doi.org/10.1523/JNEUROSCI.6042-09.2010.

    Article  Google Scholar 

  • Pruszynski, J. A., Omrani, M., & Scott, S. H. (2014). Goal-dependent modulation of fast feedback responses in primary motor cortex. Journal of Neuroscience, 34(13), 4608–4617. https://doi.org/10.1523/JNEUROSCI.4520-13.2014.

    Article  Google Scholar 

  • Purves, D. (2018). Neuroscience (6th ed.). New York: Oxford University Press.

    Google Scholar 

  • Qi, X. L., Katsuki, F., Meyer, T., Rawley, J. B., Zhou, X., Douglas, K. L., et al. (2010). Comparison of neural activity related to working memory in primate dorsolateral prefrontal and posterior parietal cortex. Frontiers in Systems Neuroscience, 4, 12. https://doi.org/10.3389/fnsys.2010.00012.

    Google Scholar 

  • Quintana, J., Yajeya, J., & Fuster, J. M. (1988). Prefrontal representation of stimulus attributes during delay tasks. I. Unit activity in cross-temporal integration of sensory and sensory-motor information. Brain Research, 474(2), 211–221.

    Article  Google Scholar 

  • Raja, V. (2017). A theory of resonance: Towards an ecological cognitive architecture. Minds and Machines. https://doi.org/10.1007/s11023-017-9431-8.

    Google Scholar 

  • Ramirez, S., Liu, X., Lin, P. A., Suh, J., Pignatelli, M., Redondo, R. L., et al. (2013). Creating a false memory in the hippocampus. Science, 341(6144), 387–391. https://doi.org/10.1126/science.1239073.

    Article  Google Scholar 

  • Ramsey, F. P. (1931). The foundations of mathematics, and other logical essays. London: Routledge and Kegan Paul.

    MATH  Google Scholar 

  • Ramsey, W. M. (2007). Representation reconsidered. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Ramsey, W. M. (2016). Untangling two questions about mental representation. New Ideas in Psychology, 40, 3–12.

    Article  Google Scholar 

  • Reijmers, L. G., Perkins, B. L., Matsuo, N., & Mayford, M. (2007). Localization of a stable neural correlate of associative memory. Science, 317(5842), 1230–1233. https://doi.org/10.1126/science.1143839.

    Article  Google Scholar 

  • Richmond, B. J., & Wurtz, R. H. (1980). Vision during saccadic eye movements. II. A corollary discharge to monkey superior colliculus. Journal of Neurophysiology, 43(4), 1156–1167.

    Article  Google Scholar 

  • Riley, M. R., & Constantinidis, C. (2016). Role of prefrontal persistent activity in working memory. Frontiers in Systems Neuroscience. https://doi.org/10.3389/fnsys.2015.00181.

    Google Scholar 

  • Roberts, T. F., Gobes, S. M., Murugan, M., Olveczky, B. P., & Mooney, R. (2012). Motor circuits are required to encode a sensory model for imitative learning. Nature Neuroscience, 15(10), 1454–1459. https://doi.org/10.1038/nn.3206.

    Article  Google Scholar 

  • Robinson, D. L., & Wurtz, R. H. (1976). Use of an extraretinal signal by monkey superior colliculus neurons to distinguish real from self-induced stimulus movement. Journal of Neurophysiology, 39(4), 852–870.

    Article  Google Scholar 

  • Rockland, K. S., & Knutson, T. (2000). Feedback connections from area MT of the squirrel monkey to areas V1 and V2. Journal of Comparative Neurology, 425(3), 345–368.

    Article  Google Scholar 

  • Rodieck, R. W. (1998). The first steps in seeing. Sunderland, MA: Sinauer Associates.

    Google Scholar 

  • Roska, B., & Werblin, F. (2001). Vertical interactions across ten parallel, stacked representations in the mammalian retina. Nature, 410(6828), 583–587. https://doi.org/10.1038/35069068.

    Article  Google Scholar 

  • Rossignol, S., & Bouyer, L. (2004). Adaptive mechanisms of spinal locomotion in cats. Integrative and Comparative Biology, 44(1), 71–79. https://doi.org/10.1093/icb/44.1.71.

    Article  Google Scholar 

  • Rouse, J. (2015). Articulating the world: Conceptual understanding and the scientific image (423 pp.). University of Chicago Press.

  • Rust, N. (2014). Population-based representations: From implicit to explicit. In M. Gazzaniga & G. Ronald (Eds.), The cognitive neurosciences (5th ed., pp. 337–347). Cambridge: MIT Press.

    Google Scholar 

  • Ryder, D. (2004a). SINBAD neurosemantics: A theory of mental representation. Mind and Language, 19(2), 211–240.

    Article  Google Scholar 

  • Ryder, D. (2004b). Models in the brain. Oxford: Oxford University Press.

    Google Scholar 

  • Ryle, G. (1949). The concept of mind. London: Hutchinson’s University Library.

    Google Scholar 

  • Salinas, E., & Abbott, L. F. (1995). Transfer of coded information from sensory to motor networks. Journal of Neuroscience, 15(10), 6461–6474.

    Google Scholar 

  • Salzman, C. D., Britten, K. H., & Newsome, W. T. (1990). Cortical microstimulation influences perceptual judgements of motion direction. Nature, 346(6280), 174–177. https://doi.org/10.1038/346174a0.

    Article  Google Scholar 

  • Salzman, C. D., Murasugi, C. M., Britten, K. H., & Newsome, W. T. (1992). Microstimulation in visual area MT: Effects on direction discrimination performance. Journal of Neuroscience, 12(6), 2331–2355.

    Google Scholar 

  • Sanes, J. R., & Masland, R. H. (2015). The types of retinal ganglion cells: current status and implications for neuronal classification. Annual Review of Neuroscience, 38, 221–246. https://doi.org/10.1146/annurev-neuro-071714-034120.

    Article  Google Scholar 

  • Scarantino, A. (2015). Information as a probabilistic difference maker. Australasian Journal of Philosophy, 93(3), 419–443.

    Article  Google Scholar 

  • Scarantino, A., & Piccinini, G. (2010). Information without truth. Metaphilosophy, 43(3), 313–330.

    Article  Google Scholar 

  • Schenk, T., & Zihl, J. (1997). Visual motion perception after brain damage: I. Deficits in global motion perception. Neuropsychologia, 35(9), 1289–1297.

    Article  Google Scholar 

  • Schneider, S. (2011). The language of thought: A new philosophical direction. Cambridge, MA: MIT Press.

    Book  Google Scholar 

  • Schwartzman, R. J. (1978). A behavioral analysis of complete unilateral section of the pyramidal tract at the medullary level in Macaca mulatta. Annals of Neurology, 4(3), 234–244. https://doi.org/10.1002/ana.410040308.

    Article  Google Scholar 

  • Scott, S. H. (2000). Reply to ‘one motor cortex, two different views’. Nature Neuroscience, 3(10), 964–965. https://doi.org/10.1038/79888.

    Article  Google Scholar 

  • Scott, S. H. (2016). A functional taxonomy of bottom-up sensory feedback processing for motor actions. Trends in Neurosciences, 39(8), 512–526. https://doi.org/10.1016/j.tins.2016.06.001.

    Article  Google Scholar 

  • Searle, J. (1983). Intentionality: An essay in the philosophy of mind. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Sellars, W. (1956). Empiricism and the philosophy of mind. In H. Feigl & M. Scriven (Eds.), Minnesota studies in the philosophy of science (Vol. I, pp. 253–329). Minneapolis, MN: University of Minnesota Press.

    Google Scholar 

  • Sellars, W. (1981). Mental events. Philosophical Studies, 39, 325–345.

    Article  Google Scholar 

  • Sereno, M. I. (2014). Origin of symbol-using systems: speech, but not sign, without the semantic urge. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369(1651), 20130303. https://doi.org/10.1098/rstb.2013.0303.

    Article  Google Scholar 

  • Shadmehr, R., Brandt, J., & Corkin, S. (1998). Time-dependent motor memory processes in amnesic subjects. Journal of Neurophysiology, 80(3), 1590–1597.

    Article  Google Scholar 

  • Shadmehr, R., & Krakauer, J. W. (2008). A computational neuroanatomy for motor control. Experimental Brain Research, 185(3), 359–381. https://doi.org/10.1007/s00221-008-1280-5.

    Article  Google Scholar 

  • Shadmehr, R., Smith, M. A., & Krakauer, J. W. (2010). Error correction, sensory prediction, and adaptation in motor control. Annual Review of Neuroscience, 33, 89–108. https://doi.org/10.1146/annurev-neuro-060909-153135.

    Article  Google Scholar 

  • Shagrir, O. (2012). Structural representations and the brain. The British Journal for the Philosophy of Science, 63(3), 519–545.

    Article  Google Scholar 

  • Shagrir, O. (2017). The brain as an input–output model of the world. Minds and Machines. https://doi.org/10.1007/s11023-017-9443-4.

    Google Scholar 

  • Shea, N. (2007). Consumers need information: Supplementing teleosemantics with an input condition. Philosophy and Phenomenological Research, 75, 404–435.

    Article  Google Scholar 

  • Shea, N. (2014). Exploitable isomorphism and structural representation. Proc Aristot Soc CXIV, 77–92.

  • Shepard, R., & Chipman, S. (1970). Second-order isomorphism of internal representations: Shapes of states. Cognitive Psychology, 1(1), 1–17.

    Article  Google Scholar 

  • Sherrington, C. S. (1910). Flexion-reflex of the limb, crossed extension-reflex, and reflex stepping and standing. Journal of Physiology, 40(1–2), 28–121.

    Article  Google Scholar 

  • Skotko, B. G., Andrews, E., & Einstein, G. (2005). Language and the medial temporal lobe: Evidence from HM’s spontaneous discourse. Journal of Memory and Language, 53(3), 397–415. https://doi.org/10.1016/j.jml.2005.05.003.

    Article  Google Scholar 

  • Soo, F. S., Schwartz, G. W., Sadeghi, K., & Berry, M. J., 2nd. (2011). Fine spatial information represented in a population of retinal ganglion cells. Journal of Neuroscience, 31(6), 2145–2155. https://doi.org/10.1523/JNEUROSCI.5129-10.2011.

    Article  Google Scholar 

  • Sparks, D. L., Lee, C., & Rohrer, W. H. (1990). Population coding of the direction, amplitude, and velocity of saccadic eye movements by neurons in the superior colliculus. Cold Spring Harbor Symposia on Quantitative Biology, 55, 805–811.

    Article  Google Scholar 

  • Spillmann, L. (2014). Receptive fields of visual neurons: The early years. Perception, 43(11), 1145–1176.

    Article  Google Scholar 

  • Sprevak, M. (2013). Fictionalism about neural representations. The Monist, 96, 539–560.

    Article  Google Scholar 

  • Squire, L. R. (2009). The legacy of patient H.M. for neuroscience. Neuron, 61(1), 6–9. https://doi.org/10.1016/j.neuron.2008.12.023.

    Article  Google Scholar 

  • Squire, L. R., Stark, C. E., & Clark, R. E. (2004). The medial temporal lobe. Annual Review of Neuroscience, 27, 279–306. https://doi.org/10.1146/annurev.neuro.27.070203.144130.

    Article  Google Scholar 

  • Squire, L., & Wixted, J. (2015). Remembering. Daedalus, Winter, 2015, 53–66.

    Article  Google Scholar 

  • Staley, K. (1999). Golden events and statistics: What’s wrong with Galison’s image/logic distinction. Perspectives on Science, 7, 196–230.

    Article  MathSciNet  MATH  Google Scholar 

  • Stampe, D. (1977). Toward a causal theory of linguistic representation. In P. A. French, T. E. Uehling Jr., & H. K. Wettstein (Eds.), Midwest studies in philosophy: Studies in the philosophy of language (Vol. 2, pp. 81–102). Minneapolis: University of Minnesota Press.

  • Standing, L. (1973). Learning 10,000 pictures. Quarterly Journal of Experimental Psychology, 25(2), 207–222. https://doi.org/10.1080/14640747308400340.

    Article  Google Scholar 

  • Stangor, C. (2011). Introduction to Psychology. Saylor Academy.

  • Stich, S. (1983). From Folk psychology to cognitive science: The case against belief. Cambridge, MA: MIT Press.

    Google Scholar 

  • Sullivan, J. A. (2009). The multiplicity of experimental protocols: A challenge to reductionist and non-reductionist models of the unity of neuroscience. Synthese, 167, 511–539.

    Article  Google Scholar 

  • Sullivan, J. A. (2010). A role for representation in cognitive neurobiology. Philosophy of Science, 77(5), 875–887.

    Article  Google Scholar 

  • Sussillo, D., Churchland, M. M., Kaufman, M. T., & Shenoy, K. V. (2015). A neural network that finds a naturalistic solution for the production of muscle activity. Nature Neuroscience, 18(7), 1025–1033. https://doi.org/10.1038/nn.4042.

    Article  Google Scholar 

  • Swoyer, C. (1991). Structural representation and surrogative reasoning. Synthese, 87(3), 449.

    Article  MathSciNet  Google Scholar 

  • Takeda, K., & Funahashi, S. (2002). Prefrontal task-related activity representing visual cue location or saccade direction in spatial working memory tasks. Journal of Neurophysiology, 87(1), 567–588. https://doi.org/10.1152/jn.00249.2001.

    Article  Google Scholar 

  • Thomson, E. E., & Kristan, W. B. (2005). Quantifying stimulus discriminability: A comparison of information theory and ideal observer analysis. Neural Computation, 17(4), 741–778. https://doi.org/10.1162/0899766053429435.

    Article  MATH  Google Scholar 

  • Todorov, E. (2000a). Direct cortical control of muscle activation in voluntary arm movements: A model. Nature Neuroscience, 3(4), 391–398. https://doi.org/10.1038/73964.

    Article  Google Scholar 

  • Todorov, E. (2000b). Reply to ‘one motor cortex, two different views’. Nature Neuroscience, 3(10), 964. https://doi.org/10.1038/79886.

    Article  Google Scholar 

  • Todorov, E. (2000c). Reply to ‘one motor cortex, two different views’. Nature Neuroscience, 3(10), 963–964. https://doi.org/10.1038/79884.

    Article  Google Scholar 

  • Tong, F., Nakayama, K., Vaughan, J. T., & Kanwisher, N. (1998). Binocular rivalry and visual awareness in human extrastriate cortex. Neuron, 21, 753–759.

    Article  Google Scholar 

  • Tootell, R. B., Switkes, E., Silverman, M. S., & Hamilton, S. L. (1988). Functional anatomy of macaque striate cortex. II. Retinotopic organization. Journal of Neuroscience, 8(5), 1531–1568.

    Google Scholar 

  • Truccolo, W., Friehs, G. M., Donoghue, J. P., & Hochberg, L. R. (2008). Primary motor cortex tuning to intended movement kinematics in humans with tetraplegia. Journal of Neuroscience, 28(5), 1163–1178. https://doi.org/10.1523/JNEUROSCI.4415-07.2008.

    Article  Google Scholar 

  • Umilta, M. A., Escola, L., Intskirveli, I., Grammont, F., Rochat, M., Caruana, F., et al. (2008). When pliers become fingers in the monkey motor system. Proceedings of the National Academy of Sciences, 105(6), 2209–2213. https://doi.org/10.1073/pnas.0705985105.

    Article  Google Scholar 

  • Ungerleider, L. G., & Desimone, R. (1986). Cortical connections of visual area MT in the macaque. Journal of Comparative Neurology, 248(2), 190–222. https://doi.org/10.1002/cne.902480204.

    Article  Google Scholar 

  • van Gelder, T. (1995). What might cognition be, if not computation. The Journal of Philosophy, 92(7), 345–381.

    Article  Google Scholar 

  • Varela, F. J., Thompson, E., & Rosch, E. (2017). The embodied mind (Revised ed.). Cambridge, MA: MIT Press.

    Google Scholar 

  • Volkinshtein, D., & Meir, R. (2011). Delayed feedback control requires an internal forward model. Biological Cybernetics, 105(1), 41–53. https://doi.org/10.1007/s00422-011-0450-x.

    Article  MathSciNet  MATH  Google Scholar 

  • Wandell, B. A. (1995). Foundations of vision. Sunderland, MA: Sinauer Associates.

    Google Scholar 

  • Waskan, J. (2006). Models and cognition: Prediction and explanation in everyday life and in science. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Watanabe, Y., & Funahashi, S. (2004). Neuronal activity throughout the primate mediodorsal nucleus of the thalamus during oculomotor delayed-responses. I. Cue-, delay-, and response-period activity. Journal of Neurophysiology, 92(3), 1738–1755. https://doi.org/10.1152/jn.00994.2003.

    Article  Google Scholar 

  • Weber, M. (2005). Philosophy of experimental biology. Cambridge: Cambridge University Press.

    Google Scholar 

  • Weber, M. (2014). Experiment in biology. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2014 Edition). https://plato.stanford.edu/archives/win2014/entries/biology-experiment/.

  • Wessberg, J., Stambaugh, C. R., Kralik, J. D., Beck, P. D., Laubach, M., Chapin, J. K., et al. (2000). Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature, 408(6810), 361–365. https://doi.org/10.1038/35042582.

    Article  Google Scholar 

  • White, B. J., Berg, D. J., Kan, J. Y., Marino, R. A., Itti, L., & Munoz, D. P. (2017). Superior colliculus neurons encode a visual saliency map during free viewing of natural dynamic video. Nature Communications, 8, 14263. https://doi.org/10.1038/ncomms14263.

    Article  Google Scholar 

  • Whitlock, J. R., Heynen, A. J., Shuler, M. G., & Bear, M. F. (2006). Learning induces long-term potentiation in the hippocampus. Science, 313(5790), 1093–1097. https://doi.org/10.1126/science.1128134.

    Article  Google Scholar 

  • Wickersham, I. R., Lyon, D. C., Barnard, R. J., Mori, T., Finke, S., Conzelmann, K. K., et al. (2007). Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons. Neuron, 53(5), 639–647. https://doi.org/10.1016/j.neuron.2007.01.033.

    Article  Google Scholar 

  • Williams, D. (2017). Predictive processing and the representation wars. Minds and Machines. https://doi.org/10.1007/s11023-017-9441-6.

    Google Scholar 

  • Wimmer, K., Nykamp, D. Q., Constantinidis, C., & Compte, A. (2014). Bump attractor dynamics in prefrontal cortex explains behavioral precision in spatial working memory. Nature Neuroscience, 17(3), 431–439. https://doi.org/10.1038/nn.3645.

    Article  Google Scholar 

  • Wolpert, D. M., & Miall, R. C. (1996). Forward models for physiological motor control. Neural Networks, 9(8), 1265–1279.

    Article  MATH  Google Scholar 

  • Wolpert, D. M., Miall, R. C., & Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9), 338–347.

    Article  Google Scholar 

  • Xu, H., Han, C., Chen, M., Li, P., Zhu, S., Fang, Y., et al. (2016). Rivalry-like neural activity in primary visual cortex in anesthetized monkeys. Journal of Neuroscience, 36(11), 3231–3242. https://doi.org/10.1523/JNEUROSCI.3660-15.2016.

    Article  Google Scholar 

  • Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M., & Deisseroth, K. (2011). Optogenetics in neural systems. Neuron, 71(1), 9–34. https://doi.org/10.1016/j.neuron.2011.06.004.

    Article  Google Scholar 

  • Zylberberg, J., & Strowbridge, B. W. (2017). Mechanisms of persistent activity in cortical circuits: Possible neural substrates for working memory. Annual Review of Neuroscience, 40, 603–627. https://doi.org/10.1146/annurev-neuro-070815-014006.

    Article  Google Scholar 

Download references

Acknowledgements

ET is grateful to Joseph Rouse, Drew Christie, Matteo Colombo, Willem deVries, Val Dusek, Bryce Huebner, Peter Mandik, Mark Okrent, Carl Sachs, Joey O’Doherty, and Paul Thompson for discussion and comments on previous versions. GP is grateful to Daniel Kramer for correspondence on the topic of this article. This material is partially based upon work supported by the National Science Foundation under Grant No. SES-1654982 to Gualtiero Piccinini.

Author information

Authors and Affiliations

  1. Duke University, Durham, USA

    Eric Thomson

  2. University of Missouri – St. Louis, St. Louis, USA

    Gualtiero Piccinini

Authors
  1. Eric Thomson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gualtiero Piccinini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gualtiero Piccinini.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thomson, E., Piccinini, G. Neural Representations Observed. Minds & Machines 28, 191–235 (2018). https://doi.org/10.1007/s11023-018-9459-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11023-018-9459-4

Keywords

Search

Navigation