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How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness Thomas Metzinger
a
a
Philosophisches Seminar, Gutenberg Research College, Johannes Gutenberg-Universität, Mainz, Germany Published online: 07 Apr 2014.
Click for updates To cite this article: Thomas Metzinger (2014) How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness, Cognitive Neuroscience, 5:2, 122-124, DOI: 10.1080/17588928.2014.905519 To link to this article: http://dx.doi.org/10.1080/17588928.2014.905519
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
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of recurrent connectionist models. Prediction is intrinsically involved in all of these models, yet perhaps not in quite such an overt and qualitatively distinct manner as in Predictive Processing. Indeed, a recurrent connectionist model such as the Boltzmann machine (e.g., Ackley et al., 1985) has much the same starting point as Bayesian Predictive Processing, with the goal of the model being to minimize differences between the joint distributions of pre- and postsynaptic activity states in the absence of sensorimotor input and those present during active stimulus processing. Predictive Processing models minimize much the same quantity by distributing the basic terms of the related equations in space, utilizing distinct populations of cells (e.g., “prediction error” versus “conditional expectation of perceptual causes”). The Boltzmann machine uses time instead of space, with statistics assessed for the same cells over distinct time windows. In other words, despite having similar goals and capabilities, the Boltzmann machine and other recurrent connectionist models make no distinction between prediction error and other cells, and they use top-down feedback in a simpler, excitatory manner. Imagery is possible in these models through the selective top-down excitation of cells in lower-levels that have corresponding synaptic connections. A range of experimental data suggest that, relative to sensory-driven perception, such topdown feedback results in weaker overall activity levels and a distinct laminar profile of activity (e.g., Lakatos, Chen, O’Connell, Mills, & Schroeder, 2007; O’Craven & Kanwisher, 2000), either of which could serve to distinguish imagery or synesthetic concurrent percepts from veridical perception. Unfortunately, given the similarity of the quantities that these different classes of model are optimizing, we view it as unlikely that additional behavioral experiments will distinguish amongst them. Rather, it will likely require the evaluation of predictions at a neural level.
REFERENCES Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. 1985. A learning algorithm for Boltzmann machines. Cognitive Science, 9, 147–169. doi:10.1207/s15516709cog 0901_7 De Renzi, E. 2000. Disorders of visual recognition. Seminar Neurology, 20, 479–486. doi:10.1055/s-2000-13181 Desimone, R., & Duncan, J. 1995. Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193–222. doi:10.1146/annurev.ne.18. 030195.001205 Gotts, S. J., Chow, C. C., & Martin, A. 2012. Repetition priming and repetition suppression: A case for enhanced efficiency through neural synchronization. Cognitive
Neuroscience, 3(3–4), 227–237 doi:10.1080/17588928. 2012.670617 Grossberg, S. 1987. Competitive learning: From interactive activation to adaptive resonance. Cognitive Science, 11, 23–63. doi:10.1111/j.1551-6708.1987.tb00862.x Lakatos, P., Chen, C.-M., O’Connell, M. N., Mills, A., & Schroeder, C. E. 2007. Neuronal oscillations and multisensory interaction in primary auditory cortex. Neuron, 53, 279–292. doi:10.1016/j.neuron.2006.12.011 O’Craven, K. M., & Kanwisher, N. 2000. Mental imagery of faces and places activates corresponding stimulus-specific brain regions. Journal of Cognitive Neuroscience, 12, 1013–1023. doi:10.1162/08989290051137549
* * *
How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness Thomas Metzinger Philosophisches Seminar, Gutenberg Research College, Johannes Gutenberg-Universität, Mainz, Germany E-mail: [email protected] http://dx.doi.org/10.1080/17588928.2014.905519 Abstract: Seth develops a convincing and detailed internalist alternative to the sensorimotor-contingency theory of perceptual phenomenology. However, there are remaining conceptual problems due to a semantic ambiguity in the notion of “presence” and the idea of “subjective veridicality.” The current model should be integrated with the earlier idea that experiential “realness” and “mind-independence” are determined by the unavailability of earlier processing stages to attention. Counterfactual richness and attentional unavailability may both be indicators of the overall processing level currently achieved, a functional property that normally correlates with epistemic reliability. Perceptual presence as well as phenomenal transparency express epistemic reliability on the level of conscious processing.
What exactly is it that makes the experiential content of some, but not all, conscious states appear as irrevocably real to us? And how can there be degrees in experiential realness? Seth pursues what is known as an
I am grateful to Wanja Wiese and Jennifer Windt for constructive discussion and editorial help. © 2014 Taylor & Francis
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
COMMENTARIES
“intentionalist” strategy in philosophy of mind (Brentano, 1874; Crane, 2009). His strategy is to reduce a specific phenomenal property (namely, “perceptual presence”) to a specific form of representational content, which is carried by dynamical neural representations as described under the predictive processing approach (PP). A phenomenal property is a property of conscious experience, as experientially accessed from a subjective and individual first-person perspective (1PP). Any convincing neuroscientific theory of consciousness will therefore, first, have to tell us what a 1PP is and, second, describe the fine-grained mechanics by which a given phenomenal target property is instantiated in the brain. A first advantage of Seth’s strategy is that it offers us a novel and more precise understanding of what it means that the perceptual contents of conscious experience is appearance only, however immediate and mind-independent it may seem. Perceptual content always is counterfactual content, because the underlying generative models incorporate explicitly counterfactual elements related to how sensory inputs would change on the basis of a broad repertoire of possible actions, even if those actions are not in fact performed. Second, Seth then usefully applies the idea of maximizing the salience of counterfactual representations and thereby arriving at explicit percepts though a process of actively induced circular causality (Friston, Adams, Perrinet, & Breakspear, 2012) to the special case of conscious experience. Third, his proposal is clearly internalist, in good keeping with a widespread consensus among philosophers that phenomenal properties locally supervene on contemporaneous functional and/or physical properties of the brain. Therefore, his proposal opens a route to localist, reductive explanations of high-level phenomenal properties like “realness,” “presence,” or “mind-independence.” While Noё’s persisting conceptual difficulty is to show that interaction with the physical world is metaphysically necessary for presence (and not only causally enabling; cf. Block, 2005), the great advantage of Seth’s new idea is that it allows us to tell a fully internalist story. “Presence” can now be seen to be an entirely local property of brain processes only. Anil Seth’s contribution to the second question mentioned above is that he takes a genuine step forward in isolating the minimal metaphysically sufficient condition for perceptual experience. One conceptual problem with taking “perceptual presence” seriously as a well-defined explanandum for the cognitive neuroscience of consciousness is that it has two major semantic components: “nowness” (i.e., localization in a temporal frame of reference) and “realness” (i.e., being non-representational, and
123
therefore mind-independent). “Veridicality,” strictly speaking, refers to a property of representations and is exactly not what one wants in explaining either of those two components, because the target phenomenology is not one of having a “subjectively veridical” representation of reality, but of now being directly in touch with reality itself. Interestingly, only if the conscious brain explicitly treats information as unreliable do we find the converse effect, namely, subjective non-veridicality. In experiencing synesthetic concurrents or pseudo-hallucinations, subjects are typically aware that they are experiencing a misrepresentation, something that is unreliable and somehow “in the mind.” A third, and related, conceptual complication is that we also find presence and the associated gradient of realness in the human self-model, with the bodily self being perceived as real and present, while the cognitive self-model is experienced as comprised of representations. However, there are now at least two competing internalist approaches for the conscious experience of “realness.” Both are grounded in empirical data, and both tell a specific microfunctional story about what is sufficient for perceptual presence. Seth claims that “unreal” conscious contents depend on counterfactually poor generative models of their external causes, lacking a corresponding rich worldrelated statistical structure for such models to learn. But the older theory of “phenomenal transparency” says that it is the accessibility of earlier processing stages for attentional processing that leads to phenomenal “unrealness” (see Metzinger, 2003a, 3.2.7 and Metzinger, 2003b for details). “Transparency” refers to a property of conscious representations, namely, that they are not experienced as representations. Therefore, the subject of experience feels as if being in direct and immediate contact with their content. Transparent conscious representations create the phenomenology of naive realism. An opaque phenomenal representation is one that is experienced as a representation, for example, in pseudo-hallucinations, synesthetic concurrents, or lucid dreams. Unconscious representations are neither transparent nor opaque. Moreover, there exists a graded spectrum between transparency and opacity, determining the variable phenomenology of “mind-independence” or “realness.” This phenomenology of “realness” can be analyzed as the phenomenal transparency of certain conscious representations, i.e., as the fact that the system has no introspective access to non-intentional properties of its own representations, that it is necessarily unaware of the construction process. If we now move from the representationalist to the functionalist level of analysis, we may interpret
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
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experiential “realness” as the Bayes-optimality, counterfactual richness, or plain dynamical stability of the generative models employed, or perhaps also as the claim that further optimization of precision expectations is not possible. My own claim is that transparency is the phenomenal signature of epistemic reliability. Two other excellent, empirically well-documented examples are avatars in experimentally induced fullbody illusions (Blanke, 2012; Lenggenhager, Tadi, Metzinger, & Blanke, 2007) and the transition from two-dimensional hypnagogic images at sleep-onset to the fully realistic and immersive dream state (Windt, 2010, forthcoming). The neural avatar model is counterfactually poor, just as visual hypnagogic imagery is, and their “realness” exactly increases together with the sense of identification and the degree of experienced self-location in a spatiotemporal reference frame. Just like mental imagery, they initially lack perceptual presence, but may gradually gain this quality (cf. Table 2, bottom line). We may interpret shifts of this kind as the weakening of a high-level prior of image-hood, for example, by saying that the visually perceived avatar is a counterfactually shallow body model, because interoceptive sensations cannot be predicted (Seth, 2013). But we could also say that the brain has recognized that, although visually compatible, it is only a unimodal precursor to a full-blown selfmodel, just as two-dimensional hypnagogic imagery or the synesthete’s concurrents are immediately detected as probably belonging to an earlier processing stage, in which spatial properties are still poorly expressed by intermediate-level HGMs. Insofar as the brain has to extract features that are invariant under counterfactual manipulation, the corresponding epistemic reliability—i.e., the degree of certainty that the system has successfully isolated and latched onto an invariant property of reality —increases with the counterfactual richness of a model. What decreases is the probability for the existence of features that actually do change under non-represented counterfactual manipulations. Therefore, the degree of counterfactual richness may be an indicator of the overall processing level currently achieved—a highly relevant functional property that directly correlates with epistemic reliability. This property can (and must) itself be predicted by high-level models. Perceptual presence as well as transparency therefore express epistemic reliability on the level of conscious processing. My second, and much more speculative, proposal is that, at any given point in time, it is exactly the region of maximal invariance and reliability that constitutes the origin of the 1PP.
REFERENCES Blanke, O. (2012). Multisensory brain mechanisms of bodily self-consciousness. Nature Reviews. Neuroscience, 13(8), 556–571. Block, N. (2005). Review of “Action in Perception”, by Alva Noë. Journal of Philosophy, 102(5). Brentano, F. C. (1874). Psychologie vom empirischen Standpunkte. Leipzig: Duncker & Humblot. Crane, T. (2009). Intentionalism. In A. Beckermann & B. P. McLaughlin (Eds.), Oxford Handbook to the Philosophy of Mind (pp. 474–493). Oxford University Press. Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012). Perceptions as hypotheses: Saccades as experiments. Frontiers in Psychology, 3, doi:10.3389/fpsyg.2012.00151 Lenggenhager, B., Tadi, T., Metzinger, T., & Blanke, O. (2007). Video ergo sum: Manipulating bodily selfconsciousness. Science, 317(5841), 1096–1099. doi:10.1126/science.1143439 Metzinger, T. (2003a). Being no one: The self-model theory of subjectivity. Cambridge, MA: MIT Press. Metzinger, T. (2003b). Phenomenal transparency and cognitive self-reference. Phenomenology and the Cognitive Sciences, 2(4), 353–393. doi:10.1023/B: PHEN.0000007366.42918.eb Seth, A. K. (2013). Interoceptive inference, emotion, and the embodied self. Trends in Cognitive Sciences, 17(11), 565–573. doi:10.1016/j.tics.2013.09.007 Windt, J. M. (2010). The immersive spatiotemporal hallucination model of dreaming. Phenomenology and the Cognitive Sciences, 9(2), 295–316. doi:10.1007/s11097-010-9163-1 Windt, J. M. (forthcoming). Dreaming: A conceptual framework for philosophy of mind and empirical research. Cambridge, MA: MIT Press.
* * *
Constructing priors in synesthesia Tessa M. van Leeuwen1,2 1 Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany 2 Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany E-mail: [email protected] http://dx.doi.org/10.1080/17588928.2014.905520 Abstract: A new theoretical framework (PPSMC) applicable to synesthesia has been proposed, in which the discrepancy
This study was funded by LOEWE—Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). © 2014 Taylor & Francis
Cognitive Neuroscience Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/pcns20
How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness Thomas Metzinger
a
a
Philosophisches Seminar, Gutenberg Research College, Johannes Gutenberg-Universität, Mainz, Germany Published online: 07 Apr 2014.
Click for updates To cite this article: Thomas Metzinger (2014) How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness, Cognitive Neuroscience, 5:2, 122-124, DOI: 10.1080/17588928.2014.905519 To link to this article: http://dx.doi.org/10.1080/17588928.2014.905519
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
122
COMMENTARIES
of recurrent connectionist models. Prediction is intrinsically involved in all of these models, yet perhaps not in quite such an overt and qualitatively distinct manner as in Predictive Processing. Indeed, a recurrent connectionist model such as the Boltzmann machine (e.g., Ackley et al., 1985) has much the same starting point as Bayesian Predictive Processing, with the goal of the model being to minimize differences between the joint distributions of pre- and postsynaptic activity states in the absence of sensorimotor input and those present during active stimulus processing. Predictive Processing models minimize much the same quantity by distributing the basic terms of the related equations in space, utilizing distinct populations of cells (e.g., “prediction error” versus “conditional expectation of perceptual causes”). The Boltzmann machine uses time instead of space, with statistics assessed for the same cells over distinct time windows. In other words, despite having similar goals and capabilities, the Boltzmann machine and other recurrent connectionist models make no distinction between prediction error and other cells, and they use top-down feedback in a simpler, excitatory manner. Imagery is possible in these models through the selective top-down excitation of cells in lower-levels that have corresponding synaptic connections. A range of experimental data suggest that, relative to sensory-driven perception, such topdown feedback results in weaker overall activity levels and a distinct laminar profile of activity (e.g., Lakatos, Chen, O’Connell, Mills, & Schroeder, 2007; O’Craven & Kanwisher, 2000), either of which could serve to distinguish imagery or synesthetic concurrent percepts from veridical perception. Unfortunately, given the similarity of the quantities that these different classes of model are optimizing, we view it as unlikely that additional behavioral experiments will distinguish amongst them. Rather, it will likely require the evaluation of predictions at a neural level.
REFERENCES Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. 1985. A learning algorithm for Boltzmann machines. Cognitive Science, 9, 147–169. doi:10.1207/s15516709cog 0901_7 De Renzi, E. 2000. Disorders of visual recognition. Seminar Neurology, 20, 479–486. doi:10.1055/s-2000-13181 Desimone, R., & Duncan, J. 1995. Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193–222. doi:10.1146/annurev.ne.18. 030195.001205 Gotts, S. J., Chow, C. C., & Martin, A. 2012. Repetition priming and repetition suppression: A case for enhanced efficiency through neural synchronization. Cognitive
Neuroscience, 3(3–4), 227–237 doi:10.1080/17588928. 2012.670617 Grossberg, S. 1987. Competitive learning: From interactive activation to adaptive resonance. Cognitive Science, 11, 23–63. doi:10.1111/j.1551-6708.1987.tb00862.x Lakatos, P., Chen, C.-M., O’Connell, M. N., Mills, A., & Schroeder, C. E. 2007. Neuronal oscillations and multisensory interaction in primary auditory cortex. Neuron, 53, 279–292. doi:10.1016/j.neuron.2006.12.011 O’Craven, K. M., & Kanwisher, N. 2000. Mental imagery of faces and places activates corresponding stimulus-specific brain regions. Journal of Cognitive Neuroscience, 12, 1013–1023. doi:10.1162/08989290051137549
* * *
How does the brain encode epistemic reliability? Perceptual presence, phenomenal transparency, and counterfactual richness Thomas Metzinger Philosophisches Seminar, Gutenberg Research College, Johannes Gutenberg-Universität, Mainz, Germany E-mail: [email protected] http://dx.doi.org/10.1080/17588928.2014.905519 Abstract: Seth develops a convincing and detailed internalist alternative to the sensorimotor-contingency theory of perceptual phenomenology. However, there are remaining conceptual problems due to a semantic ambiguity in the notion of “presence” and the idea of “subjective veridicality.” The current model should be integrated with the earlier idea that experiential “realness” and “mind-independence” are determined by the unavailability of earlier processing stages to attention. Counterfactual richness and attentional unavailability may both be indicators of the overall processing level currently achieved, a functional property that normally correlates with epistemic reliability. Perceptual presence as well as phenomenal transparency express epistemic reliability on the level of conscious processing.
What exactly is it that makes the experiential content of some, but not all, conscious states appear as irrevocably real to us? And how can there be degrees in experiential realness? Seth pursues what is known as an
I am grateful to Wanja Wiese and Jennifer Windt for constructive discussion and editorial help. © 2014 Taylor & Francis
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
COMMENTARIES
“intentionalist” strategy in philosophy of mind (Brentano, 1874; Crane, 2009). His strategy is to reduce a specific phenomenal property (namely, “perceptual presence”) to a specific form of representational content, which is carried by dynamical neural representations as described under the predictive processing approach (PP). A phenomenal property is a property of conscious experience, as experientially accessed from a subjective and individual first-person perspective (1PP). Any convincing neuroscientific theory of consciousness will therefore, first, have to tell us what a 1PP is and, second, describe the fine-grained mechanics by which a given phenomenal target property is instantiated in the brain. A first advantage of Seth’s strategy is that it offers us a novel and more precise understanding of what it means that the perceptual contents of conscious experience is appearance only, however immediate and mind-independent it may seem. Perceptual content always is counterfactual content, because the underlying generative models incorporate explicitly counterfactual elements related to how sensory inputs would change on the basis of a broad repertoire of possible actions, even if those actions are not in fact performed. Second, Seth then usefully applies the idea of maximizing the salience of counterfactual representations and thereby arriving at explicit percepts though a process of actively induced circular causality (Friston, Adams, Perrinet, & Breakspear, 2012) to the special case of conscious experience. Third, his proposal is clearly internalist, in good keeping with a widespread consensus among philosophers that phenomenal properties locally supervene on contemporaneous functional and/or physical properties of the brain. Therefore, his proposal opens a route to localist, reductive explanations of high-level phenomenal properties like “realness,” “presence,” or “mind-independence.” While Noё’s persisting conceptual difficulty is to show that interaction with the physical world is metaphysically necessary for presence (and not only causally enabling; cf. Block, 2005), the great advantage of Seth’s new idea is that it allows us to tell a fully internalist story. “Presence” can now be seen to be an entirely local property of brain processes only. Anil Seth’s contribution to the second question mentioned above is that he takes a genuine step forward in isolating the minimal metaphysically sufficient condition for perceptual experience. One conceptual problem with taking “perceptual presence” seriously as a well-defined explanandum for the cognitive neuroscience of consciousness is that it has two major semantic components: “nowness” (i.e., localization in a temporal frame of reference) and “realness” (i.e., being non-representational, and
123
therefore mind-independent). “Veridicality,” strictly speaking, refers to a property of representations and is exactly not what one wants in explaining either of those two components, because the target phenomenology is not one of having a “subjectively veridical” representation of reality, but of now being directly in touch with reality itself. Interestingly, only if the conscious brain explicitly treats information as unreliable do we find the converse effect, namely, subjective non-veridicality. In experiencing synesthetic concurrents or pseudo-hallucinations, subjects are typically aware that they are experiencing a misrepresentation, something that is unreliable and somehow “in the mind.” A third, and related, conceptual complication is that we also find presence and the associated gradient of realness in the human self-model, with the bodily self being perceived as real and present, while the cognitive self-model is experienced as comprised of representations. However, there are now at least two competing internalist approaches for the conscious experience of “realness.” Both are grounded in empirical data, and both tell a specific microfunctional story about what is sufficient for perceptual presence. Seth claims that “unreal” conscious contents depend on counterfactually poor generative models of their external causes, lacking a corresponding rich worldrelated statistical structure for such models to learn. But the older theory of “phenomenal transparency” says that it is the accessibility of earlier processing stages for attentional processing that leads to phenomenal “unrealness” (see Metzinger, 2003a, 3.2.7 and Metzinger, 2003b for details). “Transparency” refers to a property of conscious representations, namely, that they are not experienced as representations. Therefore, the subject of experience feels as if being in direct and immediate contact with their content. Transparent conscious representations create the phenomenology of naive realism. An opaque phenomenal representation is one that is experienced as a representation, for example, in pseudo-hallucinations, synesthetic concurrents, or lucid dreams. Unconscious representations are neither transparent nor opaque. Moreover, there exists a graded spectrum between transparency and opacity, determining the variable phenomenology of “mind-independence” or “realness.” This phenomenology of “realness” can be analyzed as the phenomenal transparency of certain conscious representations, i.e., as the fact that the system has no introspective access to non-intentional properties of its own representations, that it is necessarily unaware of the construction process. If we now move from the representationalist to the functionalist level of analysis, we may interpret
Downloaded by [Chinese University of Hong Kong] at 22:23 16 February 2015
124
COMMENTARIES
experiential “realness” as the Bayes-optimality, counterfactual richness, or plain dynamical stability of the generative models employed, or perhaps also as the claim that further optimization of precision expectations is not possible. My own claim is that transparency is the phenomenal signature of epistemic reliability. Two other excellent, empirically well-documented examples are avatars in experimentally induced fullbody illusions (Blanke, 2012; Lenggenhager, Tadi, Metzinger, & Blanke, 2007) and the transition from two-dimensional hypnagogic images at sleep-onset to the fully realistic and immersive dream state (Windt, 2010, forthcoming). The neural avatar model is counterfactually poor, just as visual hypnagogic imagery is, and their “realness” exactly increases together with the sense of identification and the degree of experienced self-location in a spatiotemporal reference frame. Just like mental imagery, they initially lack perceptual presence, but may gradually gain this quality (cf. Table 2, bottom line). We may interpret shifts of this kind as the weakening of a high-level prior of image-hood, for example, by saying that the visually perceived avatar is a counterfactually shallow body model, because interoceptive sensations cannot be predicted (Seth, 2013). But we could also say that the brain has recognized that, although visually compatible, it is only a unimodal precursor to a full-blown selfmodel, just as two-dimensional hypnagogic imagery or the synesthete’s concurrents are immediately detected as probably belonging to an earlier processing stage, in which spatial properties are still poorly expressed by intermediate-level HGMs. Insofar as the brain has to extract features that are invariant under counterfactual manipulation, the corresponding epistemic reliability—i.e., the degree of certainty that the system has successfully isolated and latched onto an invariant property of reality —increases with the counterfactual richness of a model. What decreases is the probability for the existence of features that actually do change under non-represented counterfactual manipulations. Therefore, the degree of counterfactual richness may be an indicator of the overall processing level currently achieved—a highly relevant functional property that directly correlates with epistemic reliability. This property can (and must) itself be predicted by high-level models. Perceptual presence as well as transparency therefore express epistemic reliability on the level of conscious processing. My second, and much more speculative, proposal is that, at any given point in time, it is exactly the region of maximal invariance and reliability that constitutes the origin of the 1PP.
REFERENCES Blanke, O. (2012). Multisensory brain mechanisms of bodily self-consciousness. Nature Reviews. Neuroscience, 13(8), 556–571. Block, N. (2005). Review of “Action in Perception”, by Alva Noë. Journal of Philosophy, 102(5). Brentano, F. C. (1874). Psychologie vom empirischen Standpunkte. Leipzig: Duncker & Humblot. Crane, T. (2009). Intentionalism. In A. Beckermann & B. P. McLaughlin (Eds.), Oxford Handbook to the Philosophy of Mind (pp. 474–493). Oxford University Press. Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012). Perceptions as hypotheses: Saccades as experiments. Frontiers in Psychology, 3, doi:10.3389/fpsyg.2012.00151 Lenggenhager, B., Tadi, T., Metzinger, T., & Blanke, O. (2007). Video ergo sum: Manipulating bodily selfconsciousness. Science, 317(5841), 1096–1099. doi:10.1126/science.1143439 Metzinger, T. (2003a). Being no one: The self-model theory of subjectivity. Cambridge, MA: MIT Press. Metzinger, T. (2003b). Phenomenal transparency and cognitive self-reference. Phenomenology and the Cognitive Sciences, 2(4), 353–393. doi:10.1023/B: PHEN.0000007366.42918.eb Seth, A. K. (2013). Interoceptive inference, emotion, and the embodied self. Trends in Cognitive Sciences, 17(11), 565–573. doi:10.1016/j.tics.2013.09.007 Windt, J. M. (2010). The immersive spatiotemporal hallucination model of dreaming. Phenomenology and the Cognitive Sciences, 9(2), 295–316. doi:10.1007/s11097-010-9163-1 Windt, J. M. (forthcoming). Dreaming: A conceptual framework for philosophy of mind and empirical research. Cambridge, MA: MIT Press.
* * *
Constructing priors in synesthesia Tessa M. van Leeuwen1,2 1 Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany 2 Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany E-mail: [email protected] http://dx.doi.org/10.1080/17588928.2014.905520 Abstract: A new theoretical framework (PPSMC) applicable to synesthesia has been proposed, in which the discrepancy
This study was funded by LOEWE—Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). © 2014 Taylor & Francis
