Binding problem

From HandWiki
Revision as of 17:11, 8 February 2024 by Dennis Ross (talk | contribs) (linkage)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Short description: Unanswered question in the study of consciousness

The consciousness and binding problem is the problem of how objects, background and abstract or emotional features are combined into a single experience.[1]

The binding problem refers to the overall encoding of our brain circuits for the combination of decisions, actions, and perception. It is considered a "problem" due to the fact that no complete model exists.

The binding problem can be subdivided into four problems of perception, used in neuroscience, cognitive science, and the philosophy of mind. It includes general considerations on coordination, the subjective unity of perception, and variable binding.[2]

General considerations on coordination

Summary of problem

Attention is crucial in determining which phenomena appear to be bound together, noticed, and remembered.[3] This specific binding problem is generally referred to as temporal synchrony. At the most basic level, all neural firing and its adaptation depends on specific consideration to timing (Feldman, 2010). At a much larger level, frequent patterns in large scale neural activity are a major diagnostic and scientific tool.[4]

Synchronization theory and research

A popular hypothesis mentioned by Peter Milner, in his 1974 article A Model for Visual Shape Recognition, has been that features of individual objects are bound/segregated via synchronization of the activity of different neurons in the cortex.[5][6] The theory, called binding-by-synchrony (BBS), is hypothesized to occur through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented.[7] Empirical testing of the idea was brought to light when von der Malsburg proposed that feature binding posed a special problem that could not be covered simply by cellular firing rates.[8] However, it has been shown this theory may not be a problem since it was revealed that the modules code jointly for multiple features, countering the feature-binding issue.[9] Temporal synchrony has been shown to be the most prevalent when regarding the first problem, "General Considerations on Coordination," because it is an effective method to take in surroundings and is good for grouping and segmentation. A number of studies suggested that there is indeed a relationship between rhythmic synchronous firing and feature binding. This rhythmic firing appears to be linked to intrinsic oscillations in neuronal somatic potentials, typically in the gamma range around 40 – 60 hertz.[10] The positive arguments for a role for rhythmic synchrony in resolving the segregational object-feature binding problem have been summarized by Singer.[11] There is certainly extensive evidence for synchronization of neural firing as part of responses to visual stimuli.

However, there is inconsistency between findings from different laboratories. Moreover, a number of recent reviewers, including Shadlen and Movshon[6] and Merker[12] have raised concerns about the theory being potentially untenable. Thiele and Stoner found that perceptual binding of two moving patterns had no effect on synchronization of the neurons responding to two patterns: coherent and noncoherent plaids.[13] In the primary visual cortex, Dong et al. found that whether two neurons were responding to contours of the same shape or different shapes had no effect on neural synchrony since synchrony is independent of binding condition.

Shadlen and Movshon[6] raise a series of doubts about both the theoretical and the empirical basis for the idea of segregational binding by temporal synchrony. There is no biophysical evidence that cortical neurons are selective to synchronous input at this point of precision and cortical activity with synchrony this precise is rare. Synchronization is also connected to endorphin activity. It has been shown that precise spike timing may not be necessary to illustrate a mechanism for visual binding and is only prevalent in modeling certain neuronal interactions. In contrast, Seth[14] describes an artificial brain-based robot that demonstrates multiple, separate, widely distributed neural circuits, firing at different phases,showing that regular brain oscillations at specific frequencies are essential to the neural mechanisms of binding.

Goldfarb and Treisman[15] point out that a logical problem appears to arise for binding solely via synchrony if there are several objects that share some of their features and not others. At best synchrony can facilitate segregation supported by other means (as von der Malsburg acknowledges).[16]

A number of neuropsychological studies suggest that the association of color, shape and movement as "features of an object" is not simply a matter of linking or "binding", but shown to be inefficient to not bind elements into groups when considering association[17] and give extensive evidence for top-down feedback signals that ensure that sensory data are handled as features of (sometimes wrongly) postulated objects early in processing. Pylyshyn[18] has also emphasized the way the brain seems to pre-conceive objects from which features are to be allocated to which are attributed continuing existence even if features such as color change. This is because visual integration increases over time and indexing visual objects helps to ground visual concepts.

Feature integration theory

Summary of problem

The visual feature binding problem refers to the question of why we do not confuse a red circle and a blue square with a blue circle and a red square. The understanding of the circuits in the brain stimulated for visual feature binding is increasing. A binding process is required for us to accurately encode various visual features in separate cortical areas.

In her feature integration theory, Treisman suggested that one of the first stages of binding between features is mediated by the features' links to a common location. The second stage is combining individual features of an object that requires attention, and selecting that object occurs within a "master map" of locations. Psychophysical demonstrations of binding failures under conditions of full attention provide support for the idea that binding is accomplished through common location tags.[19]

An implication of these approaches is that sensory data such as color or motion may not normally exist in "unallocated" form. For Merker:[20] "The 'red' of a red ball does not float disembodied in an abstract color space in V4." If color information allocated to a point in the visual field is converted directly, via the instantiation of some form of propositional logic (analogous to that used in computer design) into color information allocated to an "object identity" postulated by a top-down signal as suggested by Purves and Lotto (e.g. There is blue here + Object 1 is here = Object 1 is blue) no special computational task of "binding together" by means such as synchrony may exist. (Although Von der Malsburg[21] poses the problem in terms of binding "propositions" such as "triangle" and "top", these, in isolation, are not propositional.)

How signals in the brain come to have propositional content, or meaning, is a much larger issue. However, both Marr[22] and Barlow[23] suggested, on the basis of what was known about neural connectivity in the 1970s that the final integration of features into a percept would be expected to resemble the way words operate in sentences.

The role of synchrony in segregational binding remains controversial. Merker[20] has recently suggested that synchrony may be a feature of areas of activation in the brain that relates to an "infrastructural" feature of the computational system analogous to increased oxygen demand indicated via BOLD signal contrast imaging. Apparent specific correlations with segregational tasks may be explainable on the basis of interconnectivity of the areas involved. As a possible manifestation of a need to balance excitation and inhibition over time it might be expected to be associated with reciprocal re-entrant circuits as in the model of Seth et al.[14] (Merker gives the analogy of the whistle from an audio amplifier receiving its own output.)

Experimental work

Visual feature binding is suggested to have a selective attention to the locations of the objects. If indeed spatial attention does play a role in binding integration it will do so primarily when object location acts as a binding cue. A study's findings has shown that functional MRI images indicate regions of the parietal cortex involved in spatial attention, engaged in feature conjunction tasks in single feature tasks. The task involved multiple objects being shown simultaneously at different locations which activated the parietal cortex. Whereas when multiple objects are shown sequentially at the same location the parietal cortex was less engaged.[24]

Behavioral experiments

Defoulzi et al. Investigated feature binding through two feature dimensions, to disambiguate whether a specific combination of color and motion direction is perceived as bound or unbound. Two behaviorally relevant features, including color and motion belonging to the same object, are defined as the "bound" condition. Whereas the "unbound" condition has features that belong to different objects. Local field potentials were recorded from the lateral prefrontal cortex(lPFC) in monkeys and were monitored during different stimulus configurations. The findings suggest a neural representation of visual feature binding in 4 to 12 Hertz frequency bands. It is also suggested that transmission of binding information is relayed through different lPFC neural subpopulations. The data shows a behavioral relevance of binding information that is linked to the animal's reaction time. This includes the involvement of the prefrontal cortex targeted by the dorsal and ventral visual streams in binding visual features from different dimensions (color and motion).[25]

It is suggested that the visual feature binding consists of two different mechanisms in visual perception. One mechanism consists of agonistic familiarity of possible combinations of features integrating several temporal integration windows. It is speculated that this process is mediated by neural synchronization processes and temporal synchronization in the visual cortex. The second mechanism is mediated by familiarity with the stimulus and is provided by attentional top-down support from familiar objects. [26]

Consciousness and binding

Summary of problem

Smythies[27] defines the combination problem, also known as the subjective unity of perception, as "How do the brain mechanisms actually construct the phenomenal object?". Revonsuo[1] equates this to "consciousness-related binding", emphasizing the entailment of a phenomenal aspect. As Revonsuo explores in 2006,[28] there are nuances of difference beyond the basic BP1:BP2 division. Smythies speaks of constructing a phenomenal object ("local unity" for Revonsuo) but philosophers such as Descartes, Leibniz, Kant and James (see Brook and Raymont)[29] have typically been concerned with the broader unity of a phenomenal experience ("global unity" for Revonsuo) – which, as Bayne[30] illustrates may involve features as diverse as seeing a book, hearing a tune and feeling an emotion. Further discussion will focus on this more general problem of how sensory data that may have been segregated into, for instance, "blue square" and "yellow circle" are to be re-combined into a single phenomenal experience of a blue square next to a yellow circle, plus all other features of their context. There is a wide range of views on just how real this "unity" is, but the existence of medical conditions in which it appears to be subjectively impaired, or at least restricted, suggests that it is not entirely illusory.[31]

There are many neurobiological theories about the subjective unity of perception. Different visual features such as color, size, shape, and motion are computed by largely distinct neural circuits but we experience an integrated whole. The different visual features interact with each other in various ways. For example, shape discrimination of objects is strongly affected by orientation but only slightly affected by object size.[32] Some theories suggest that global perception of the integrated whole involves higher order visual areas.[33] There is also evidence that the posterior parietal cortex is responsible for perceptual scene segmentation and organization.[34] Bodies facing each other are processed as a single unit and there is increased coupling of the extrastriate body area (EBA) and the posterior superior temporal sulcus (pSTS) when bodies are facing each other.[35] This suggests that the brain is biased towards grouping humans in twos or dyads.[36]

History

Early philosophers Descartes and Leibniz[37] noted that the apparent unity of our experience is an all-or-none qualitative characteristic that does not appear to have an equivalent in the known quantitative features, like proximity or cohesion, of composite matter. William James[38] in the nineteenth century, considered the ways the unity of consciousness might be explained by known physics and found no satisfactory answer. He coined the term "combination problem", in the specific context of a "mind-dust theory" in which it is proposed that a full human conscious experience is built up from proto- or micro-experiences in the way that matter is built up from atoms. James claimed that such a theory was incoherent, since no causal physical account could be given of how distributed proto-experiences would "combine". He favoured instead a concept of "co-consciousness" in which there is one "experience of A, B and C" rather than combined experiences. A detailed discussion of subsequent philosophical positions is given by Brook and Raymont (see 26). However, these do not generally include physical interpretations.

Whitehead[39] proposed a fundamental ontological basis for a relation consistent with James's idea of co-consciousness, in which many causal elements are co-available or "compresent" in a single event or "occasion" that constitutes a unified experience. Whitehead did not give physical specifics but the idea of compresence is framed in terms of causal convergence in a local interaction consistent with physics. Where Whitehead goes beyond anything formally recognized in physics is in the "chunking" of causal relations into complex but discrete "occasions". Even if such occasions can be defined, Whitehead's approach still leaves James's difficulty with finding a site, or sites, of causal convergence that would make neurobiological sense for "co-consciousness". Sites of signal convergence do clearly exist throughout the brain but there is a concern to avoid re-inventing what Daniel Dennett[40] calls a Cartesian Theater or single central site of convergence of the form that Descartes proposed.

Descartes's central "soul" is now rejected because neural activity closely correlated with conscious perception is widely distributed throughout the cortex. The remaining choices appear to be either separate involvement of multiple distributed causally convergent events or a model that does not tie a phenomenal experience to any specific local physical event but rather to some overall "functional" capacity. Whichever interpretation is taken, as Revonsuo[1] indicates, there is no consensus on what structural level we are dealing with – whether the cellular level, that of cellular groups as "nodes", "complexes" or "assemblies" or that of widely distributed networks. There is probably only general agreement that it is not the level of the whole brain, since there is evidence that signals in certain primary sensory areas, such as the V1 region of the visual cortex (in addition to motor areas and cerebellum), do not contribute directly to phenomenal experience.

Experimental work on the biological basis of binding

fMRI work

Stoll and colleagues conducted an fMRI experiment to see whether participants would view a dynamic bistable stimulus globally or locally.[33] Responses in lower visual cortical regions were suppressed when participants viewed the stimulus globally. However, if global perception was without shape grouping, higher cortical regions were suppressed. This experiment shows that higher order cortex is important in perceptual grouping.

Grassi and colleagues used three different motion stimuli to investigate scene segmentation or how meaningful entities are grouped together and separated from other entities in a scene.[34] Across all stimuli, scene segmentation was associated with increased activity in the posterior parietal cortex and decreased activity in lower visual areas. This suggests that the posterior parietal cortex is important for viewing an integrated whole.

EEG work

Mersad and colleagues used an EEG frequency tagging technique to differentiate between brain activity for the integrated whole object and brain activity for parts of the object.[41] The results showed that the visual system binds two humans in close proximity as part of an integrated whole. These results are consistent with evolutionary theories that face-to-face bodies are one of the earliest representations of social interaction.[36] It also supports other experimental work showing that body-selective visual areas respond more strongly to facing bodies.[42]

Electron tunneling

Experiments have shown that ferritin and neuromelanin in fixed human substantia nigra pars compacta (SNc) tissue are able to support widespread electron tunneling.[43] Further experiments have shown that ferritin structures similar to ones found in SNc tissue are able to conduct electrons over distances as great as 80 microns, and that they behave in accordance with Coulomb blockade theory to perform a switching or routing function.[44][45] Both of these observations are consistent with earlier predictions that are part of a hypothesis that ferritin and neuromelanin can provide a binding mechanism associated with an action selection mechanism,[46] although the hypothesis itself has not yet been directly investigated. The hypothesis and these observations have been applied to Integrated Information Theory.[47]

Modern theories

Daniel Dennett[40] has proposed that our sense that our experiences are single events is illusory and that, instead, at any one time there are "multiple drafts" of sensory patterns at multiple sites. Each would only cover a fragment of what we think we experience. Arguably, Dennett is claiming that consciousness is not unified and there is no phenomenal binding problem. Most philosophers have difficulty with this position (see Bayne)[30] but some physiologists agree with it. In particular, the demonstration of perceptual asynchrony in psychophysical experiments by Moutoussis and Zeki,[48][49] when color is perceived before orientation of lines and before motion by 40 and 80 ms, respectively, constitutes an argument that, over these very short time periods, different attributes are consciously perceived at different times, leading to the view that at least over these brief periods of time after visual stimulation, different events are not bound to each other, leading to the view of a disunity of consciousness,[50] at least over these brief time intervals. Dennett's view might be in keeping with evidence from recall experiments and change blindness purporting to show that our experiences are much less rich than we sense them to be – what has been called the Grand Illusion.[51] However, few, if any, other authors suggest the existence of multiple partial "drafts". Moreover, also on the basis of recall experiments, Lamme[52] has challenged the idea that richness is illusory, emphasizing that phenomenal content cannot be equated with content to which there is cognitive access.

Dennett does not tie drafts to biophysical events. Multiple sites of causal convergence are invoked in specific biophysical terms by Edwards[53] and Sevush.[54] In this view the sensory signals to be combined in phenomenal experience are available, in full, at each of multiple sites. To avoid non-causal combination each site/event is placed within an individual neuronal dendritic tree. The advantage is that "compresence" is invoked just where convergence occurs neuro-anatomically. The disadvantage, as for Dennett, is the counter-intuitive concept of multiple "copies" of experience. The precise nature of an experiential event or "occasion", even if local, also remains uncertain.

The majority of theoretical frameworks for the unified richness of phenomenal experience adhere to the intuitive idea that experience exists as a single copy, and draw on "functional" descriptions of distributed networks of cells. Baars[55] has suggested that certain signals, encoding what we experience, enter a "Global Workspace" within which they are "broadcast" to many sites in the cortex for parallel processing. Dehaene, Changeux and colleagues[56] have developed a detailed neuro-anatomical version of such a workspace. Tononi and colleagues[57] have suggested that the level of richness of an experience is determined by the narrowest information interface "bottleneck" in the largest sub-network or "complex" that acts as an integrated functional unit. Lamme[52] has suggested that networks supporting reciprocal signaling rather than those merely involved in feed-forward signaling support experience. Edelman and colleagues have also emphasized the importance of re-entrant signaling.[58] Cleeremans[59] emphasizes meta-representation as the functional signature of signals contributing to consciousness.

In general, such network-based theories are not explicitly theories of how consciousness is unified, or "bound" but rather theories of functional domains within which signals contribute to unified conscious experience. A concern about functional domains is what Rosenberg[60] has called the boundary problem; it is hard to find a unique account of what is to be included and what excluded. Nevertheless, this is, if anything is, the consensus approach.

Within the network context, a role for synchrony has been invoked as a solution to the phenomenal binding problem as well as the computational one. In his book, The Astonishing Hypothesis,[61] Crick appears to be offering a solution to BP2 as much as BP1. Even von der Malsburg,[62] introduces detailed computational arguments about object feature binding with remarks about a "psychological moment". The Singer group[63] also appear to be interested as much in the role of synchrony in phenomenal awareness as in computational segregation.

The apparent incompatibility of using synchrony to both segregate and unify might be explained by sequential roles. However, Merker[20] points out what appears to be a contradiction in attempts to solve the subjective unity of perception in terms of a functional (effectively meaning computational) rather than a local biophysical, domain, in the context of synchrony.

Functional arguments for a role for synchrony are in fact underpinned by analysis of local biophysical events. However, Merker[20] points out that the explanatory work is done by the downstream integration of synchronized signals in post-synaptic neurons: "It is, however, by no means clear what is to be understood by 'binding by synchrony' other than the threshold advantage conferred by synchrony at, and only at, sites of axonal convergence onto single dendritic trees..." In other words, although synchrony is proposed as a way of explaining binding on a distributed, rather than a convergent, basis the justification rests on what happens at convergence. Signals for two features are proposed as bound by synchrony because synchrony effects downstream convergent interaction. Any theory of phenomenal binding based on this sort of computational function would seem to follow the same principle. The phenomenality would entail convergence, if the computational function does.

The assumption in many of the quoted models suggest that computational and phenomenal events, at least at some point in the sequence of events, parallel each other in some way. The difficulty remains in identifying what that way might be. Merker's[20] analysis suggests that either (1) both computational and phenomenal aspects of binding are determined by convergence of signals on neuronal dendritic trees, or (2) that our intuitive ideas about the need for "binding" in a "holding together" sense in both computational and phenomenal contexts are misconceived. We may be looking for something extra that is not needed. Merker, for instance, argues that the homotopic connectivity of sensory pathways does the necessary work.

Cognitive science and binding

In modern connectionism cognitive neuroarchitectures are developed (e.g. "Oscillatory Networks",[64] "Integrated Connectionist/Symbolic (ICS) Cognitive Architecture",[65] "Holographic Reduced Representations (HRRs)",[66] "Neural Engineering Framework (NEF)"[67]) that solve the binding problem by means of integrative synchronization mechanisms (e.g. the (phase-)synchronized "Binding-by-synchrony (BBS)" mechanism) (1) in perceptual cognition ("low-level cognition"): This is the neurocognitive performance of how an object or event that is perceived (e.g., a visual object) is dynamically "bound together" from its properties (e.g., shape, contour, texture, color, direction of motion) as a mental representation, i.e., can be experienced in the mind as a unified "Gestalt" in terms of Gestalt psychology ("feature binding", feature linking"), (2) and in language cognition ("high-level cognition"): This is the neurocognitive performance of how a linguistic unit (e.g. a sentence) is generated by relating semantic concepts and syntactic roles to each other in a dynamic way so that one can generate systematic and compositional symbol structures and propositions that are experienced as complex mental representations in the mind ("variable binding").[68][69][70][71]

Shared intentionality and binding

According to Igor Val Danilov,[72] knowledge about neurophysiological processes during Shared intentionality can reveal insights into the binding problem and even the perception of object development since intentionality succeeds before organisms confront the binding problem. Indeed, at the beginning of life, the environment is the cacophony of stimuli: electromagnetic waves, chemical interactions, and pressure fluctuations. Because the environment is uncategorised for the organisms at this beginning stage of development, the sensation is too limited by the noise to solve the cue problem–relevant stimulus cannot overcome the noise magnitude if it passes through the senses. While very young organisms need to combine objects, background and abstract or emotional features into a single experience for building the representation of the surrounded reality, they cannot distinguish relevant sensory stimuli independently to integrate them into object representations. Even the embodied dynamical system approach cannot get around the cue to noise problem. The application of embodied information requires an already categorised environment onto objects–holistic representation of reality–which occurs through (and only after the emergence of) perception and intentionality.[73][74]

See also

References

  1. 1.0 1.1 1.2 Revonsuo, A.; Newman, J. (Jun 1999). "Binding and consciousness.". Conscious Cogn 8 (2): 123–7. doi:10.1006/ccog.1999.0393. PMID 10447994. 
  2. Feldman, Jerome (2012). "The neural binding problem". Cognitive Neurodynamics 7 (1): 1–11. doi:10.1007/s11571-012-9219-8. PMID 24427186. 
  3. Vroomen, Jean; Keetels, Mirjam (May 2010). "Perception of intersensory synchrony: A tutorial review" (in en). Attention, Perception, & Psychophysics 72 (4): 871–884. doi:10.3758/APP.72.4.871. ISSN 1943-3921. PMID 20436185. 
  4. The Neural Binding Problem(s) Jerome Feldman ... – Icsi.berkeley.edu. https://www.icsi.berkeley.edu/pubs/ai/ICSI_NBPs12.pdf.
  5. Milner, Peter M. (1974). "A model for visual shape recognition." (in en). Psychological Review 81 (6): 521–535. doi:10.1037/h0037149. ISSN 1939-1471. PMID 4445414. http://doi.apa.org/getdoi.cfm?doi=10.1037/h0037149. 
  6. 6.0 6.1 6.2 Shadlen MN, Movshon JA (September 1999). "Synchrony unbound: a critical evaluation of the temporal binding hypothesis". Neuron. 24 (1): 67–77, 111–25. doi:10.1016/S0896-6273(00)80822-3. PMID 10677027.
  7. Romera, Miguel; Talatchian, Philippe; Tsunegi, Sumito; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Cros, Vincent et al. (2022-02-15). "Binding events through the mutual synchronization of spintronic nano-neurons" (in en). Nature Communications 13 (1): 883. doi:10.1038/s41467-022-28159-1. ISSN 2041-1723. PMID 35169115. Bibcode2022NatCo..13..883R. 
  8. von der Malsburg, C. (1981). "The Correlation Theory of Brain Function". MPI Biophysical Chemistry, Internal Report 81–2. Reprinted in Models of Neural Networks II (1994), E. Domany, J.L. van Hemmen, and K. Schulten, eds. (Berlin: Springer).
  9. Di Lollo, Vincent (2012-06-01). "The feature-binding problem is an ill-posed problem" (in en). Trends in Cognitive Sciences 16 (6): 317–321. doi:10.1016/j.tics.2012.04.007. ISSN 1364-6613. PMID 22595013. https://www.sciencedirect.com/science/article/pii/S1364661312000988. 
  10. Engel, Andreas K.; Konig, Peter; Gray, Charles M.; Singer, Wolf (July 1990). "Stimulus-Dependent Neuronal Oscillations in Cat Visual Cortex: Inter-Columnar Interaction as Determined by Cross-Correlation Analysis" (in en). European Journal of Neuroscience 2 (7): 588–606. doi:10.1111/j.1460-9568.1990.tb00449.x. ISSN 0953-816X. PMID 12106294. https://onlinelibrary.wiley.com/doi/10.1111/j.1460-9568.1990.tb00449.x. 
  11. Singer, Wolf (2007-12-10). "Binding by synchrony" (in en). Scholarpedia 2 (12): 1657. doi:10.4249/scholarpedia.1657. ISSN 1941-6016. Bibcode2007SchpJ...2.1657S. 
  12. Merker, Bjorn (2013-03-01). "Cortical gamma oscillations: the functional key is activation, not cognition" (in en). Neuroscience & Biobehavioral Reviews 37 (3): 401–417. doi:10.1016/j.neubiorev.2013.01.013. ISSN 0149-7634. PMID 23333264. https://www.sciencedirect.com/science/article/pii/S0149763413000146. 
  13. Dong, Yi; Mihalas, Stefan; Qiu, Fangtu; Heydt, Rüdiger von der; Niebur, Ernst (2008-05-03). "Synchrony and the binding problem in macaque visual cortex" (in en). Journal of Vision 8 (7): 30.1–16. doi:10.1167/8.7.30. ISSN 1534-7362. PMID 19146262. PMC 2647779. https://jov.arvojournals.org/article.aspx?articleid=2193657. 
  14. 14.0 14.1 Seth, A. K. (2004). "Visual Binding Through Reentrant Connectivity and Dynamic Synchronization in a Brain-based Device". Cerebral Cortex 14 (11): 1185–1199. doi:10.1093/cercor/bhh079. PMID 15142952. 
  15. Goldfarb, L.; Treisman, A. (Mar 2013). "Counting multidimensional objects: implications for the neural-synchrony theory". Psychological Science. 24 (3): 266–71. doi:10.1177/0956797612459761. PMID 23334446. S2CID 13448695.
  16. von der Malsburg, C. (Sep 1999). "The what and why of binding: the modeler's perspective" (PDF). Neuron. 24 (1): 95–104, 111–25. doi:10.1016/s0896-6273(00)80825-9. PMID 10677030
  17. von der Malsburg, Christoph. "The What and Why of Binding: The Modeler's Perspective." Cogprints, 1 September 1999, https://web-archive.southampton.ac.uk/cogprints.org/1488/.
  18. Pylyshyn, Zenon W (2001-06-01). "Visual indexes, preconceptual objects, and situated vision" (in en). Cognition. Objects and Attention 80 (1): 127–158. doi:10.1016/S0010-0277(00)00156-6. ISSN 0010-0277. PMID 11245842. https://www.sciencedirect.com/science/article/pii/S0010027700001566. 
  19. Treisman, A.; Gelade, G. (1980), "A feature integration theory of attention.", Cognitive Psychology 12 (1): 97–136, doi:10.1016/0010-0285(80)90005-5, PMID 7351125, http://homepage.psy.utexas.edu/homepage/class/Psy355/Gilden/treisman.pdf 
  20. 20.0 20.1 20.2 20.3 20.4 Merker B (March 2013). "Cortical gamma oscillations: the functional key is activation, not cognition". Neurosci Biobehav Rev 37 (3): 401–17. doi:10.1016/j.neubiorev.2013.01.013. PMID 23333264. 
  21. C. von der Malsburg (1999). The what and why of binding: The modeler's perspective Neuron. pp. 95–104. 
  22. Marr, D. C. (1982) Vision. New York, Freeman.
  23. Barlow, H. (1972). "Single units and sensation: A neuron doctrine for perceptual psychology?". Perception 1 (4): 371–394. doi:10.1068/p010371. PMID 4377168. 
  24. Shafritz, Keith M.; Gore, John C.; Marois, René (6 August 2002). "The role of the parietal cortex in visual feature binding" (in en). Proceedings of the National Academy of Sciences 99 (16): 10917–10922. doi:10.1073/pnas.152694799. PMID 12149449. Bibcode2002PNAS...9910917S. 
  25. Parto Dezfouli, Mohsen; Schwedhelm, Philipp; Wibral, Michael; Treue, Stefan; Daliri, Mohammad Reza; Esghaei, Moein (1 April 2021). "A neural correlate of visual feature binding in primate lateral prefrontal cortex" (in en). NeuroImage 229: 117757. doi:10.1016/j.neuroimage.2021.117757. PMID 33460801. 
  26. Bernhard, Hommel. "When an object is more than a binding of its features: Evidence for two mechanisms of visual feature integration". Leiden University Institute for Psychological Research, and Leiden Institute for Brain and Cognition, Leiden, The Netherlands. https://bernhard-hommel.eu/Integrating%20features%20and%20objects.pdf. 
  27. Smythies, John R. (John Raymond) (1994). The walls of Plato's cave : the science and philosophy of (brain, consciousness, and perception. Aldershot; Brookfield, USA: Avebury. ISBN 978-1-85628-882-8. OCLC 30156912. 
  28. Revonsuo, A, (2006) Inner Presence: Consciousness as a biological phenomenon. Cambridge, MA: MIT Press.
  29. The Unity of Consciousness. Stanford Encyclopaedia of Philosophy. http://plato.stanford.edu/entries/consciousness-unity/
  30. 30.0 30.1 Bayne, T. and Chalmers, D. (2003) What is the unity of consciousness? In Cleeremans, A. The Unity of consciousness, Binding, Integration and Dissociation, Oxford University Press.
  31. Parra, Mario A.; Abrahams, Sharon; Logie, Robert H.; Méndez, Luis G.; Lopera, Francisco; Della Sala, Sergio (2010-09-01). "Visual short-term memory binding deficits in familial Alzheimer's disease". Brain 133 (9): 2702–2713. doi:10.1093/brain/awq148. ISSN 0006-8950. PMID 20624814. 
  32. Norman, J. Farley; Swindle, Jessica M.; Jennings, L. RaShae; Mullins, Elizabeth M.; Beers, Amanda M. (June 2009). "Stereoscopic shape discrimination is well preserved across changes in object size". Acta Psychologica 131 (2): 129–135. doi:10.1016/j.actpsy.2009.03.009. ISSN 1873-6297. PMID 19389660. 
  33. 33.0 33.1 Stoll, Susanne; Finlayson, Nonie J.; Schwarzkopf, D. Samuel (2020-10-15). "Topographic signatures of global object perception in human visual cortex". NeuroImage 220: 116926. doi:10.1016/j.neuroimage.2020.116926. ISSN 1053-8119. PMID 32442640. 
  34. 34.0 34.1 Grassi, Pablo R.; Zaretskaya, Natalia; Bartels, Andreas (2018-08-08). "A Generic Mechanism for Perceptual Organization in the Parietal Cortex". The Journal of Neuroscience 38 (32): 7158–7169. doi:10.1523/JNEUROSCI.0436-18.2018. ISSN 1529-2401. PMID 30006362. 
  35. Bellot, Emmanuelle; Abassi, Etienne; Papeo, Liuba (2021-03-31). "Moving Toward versus Away from Another: How Body Motion Direction Changes the Representation of Bodies and Actions in the Visual Cortex". Cerebral Cortex 31 (5): 2670–2685. doi:10.1093/cercor/bhaa382. ISSN 1460-2199. PMID 33401307. 
  36. 36.0 36.1 Papeo, Liuba (November 2020). "Twos in human visual perception". Cortex; A Journal Devoted to the Study of the Nervous System and Behavior 132: 473–478. doi:10.1016/j.cortex.2020.06.005. ISSN 1973-8102. PMID 32698947. https://osf.io/yuxza/. 
  37. Kulstad, Mark; Carlin, Laurence (2020), Zalta, Edward N., ed., Leibniz's Philosophy of Mind (Winter 2020 ed.), Metaphysics Research Lab, Stanford University, https://plato.stanford.edu/archives/win2020/entries/leibniz-mind/, retrieved 2022-06-09 
  38. James, William (1890-01-01). The principles of psychology Vol. I. New York : Holt. p. 145. https://archive.org/details/in.ernet.dli.2015.210224. 
  39. Whitehead, A. N. (1929) Process and Reality. 1979 corrected edition, edited by David Ray Griffin and Donald W. Sherburne, Free Press. ISBN:0-02-934570-7
  40. 40.0 40.1 Dennett, Daniel (1981). Brainstorms: Philosophical Essays on Mind and Psychology. MIT Press. ISBN 0262540371. https://books.google.com/books?id=_xwObaAZEwoC. 
  41. Mersad, Karima; Caristan, Céline (2021-09-17). "Blending into the Crowd: Electrophysiological Evidence of Gestalt Perception of a Human Dyad". Neuropsychologia 160: 107967. doi:10.1016/j.neuropsychologia.2021.107967. ISSN 1873-3514. PMID 34303717. 
  42. Abassi, Etienne; Papeo, Liuba (2020-01-22). "The Representation of Two-Body Shapes in the Human Visual Cortex". The Journal of Neuroscience 40 (4): 852–863. doi:10.1523/JNEUROSCI.1378-19.2019. ISSN 1529-2401. PMID 31801812. 
  43. Rourk, Christopher J. (May 2019). "Indication of quantum mechanical electron transport in human substantia nigra tissue from conductive atomic force microscopy analysis". Biosystems 179: 30–38. doi:10.1016/j.biosystems.2019.02.003. ISSN 0303-2647. PMID 30826349. http://dx.doi.org/10.1016/j.biosystems.2019.02.003. 
  44. Rourk, Christopher; Huang, Yunbo; Chen, Minjing; Shen, Cai (2021-08-12). "Indication of Strongly Correlated Electron Transport and Mott Insulator in Disordered Multilayer Ferritin Structures (DMFS)". Materials 14 (16): 4527. doi:10.3390/ma14164527. ISSN 1996-1944. PMID 34443050. Bibcode2021Mate...14.4527R. 
  45. Labra-Muñoz, Jacqueline A.; de Reuver, Arie; Koeleman, Friso; Huber, Martina; van der Zant, Herre S. J. (2022-05-15). "Ferritin-Based Single-Electron Devices". Biomolecules 12 (5): 705. doi:10.3390/biom12050705. ISSN 2218-273X. PMID 35625632. 
  46. Rourk, Christopher John (September 2018). "Ferritin and neuromelanin "quantum dot" array structures in dopamine neurons of the substantia nigra pars compacta and norepinephrine neurons of the locus coeruleus". Biosystems 171: 48–58. doi:10.1016/j.biosystems.2018.07.008. ISSN 0303-2647. PMID 30048795. 
  47. Rourk, Chris (2022-01-06). "Application of the Catecholaminergic Neuron Electron Transport (CNET) Physical Substrate for Consciousness and Action Selection to Integrated Information Theory". Entropy 24 (1): 91. doi:10.3390/e24010091. ISSN 1099-4300. PMID 35052119. Bibcode2022Entrp..24...91R. 
  48. Moutoussis, K.; Zeki, S. (1997-03-22). "A direct demonstration of perceptual asynchrony in vision". Proceedings of the Royal Society of London. Series B: Biological Sciences 264 (1380): 393–399. doi:10.1098/rspb.1997.0056. PMID 9107055. 
  49. Moutoussis, K.; Zeki, S. (1997-10-22). "Functional segregation and temporal hierarchy of the visual perceptive systems". Proceedings of the Royal Society of London. Series B: Biological Sciences 264 (1387): 1407–1414. doi:10.1098/rspb.1997.0196. PMID 9364780. 
  50. Zeki, S. (May 2003). "The disunity of consciousness". Trends in Cognitive Sciences 7 (5): 214–218. doi:10.1016/s1364-6613(03)00081-0. ISSN 1364-6613. PMID 12757823. 
  51. Blackmore, S. J.; Brelstaff, G.; Nelson, K.; Troscianko, T. (1995). "Is the richness of our visual world an illusion? Transsaccadic memory for complex scenes". Perception 24 (9): 1075–81. doi:10.1068/p241075. PMID 8552459. 
  52. 52.0 52.1 Lamme, V (2002). "The grand Grand Illusion illusion". Journal of Consciousness Studies 9: 141–157. 
  53. Edwards, J. C. (2005). "Is consciousness only a property of individual cells?". Journal of Consciousness Studies 12: 60–76. http://www.ucl.ac.uk/jonathan-edwards. 
  54. Sevush, S (2006). "Single neuron theory of consciousness". Journal of Theoretical Biology 238 (3): 704–725. doi:10.1016/j.jtbi.2005.06.018. PMID 16083912. Bibcode2006JThBi.238..704S. 
  55. Baars, B. J. (1997), In the Theater of Consciousness New York, Oxford University Press.
  56. Dehaene, S.; Sergent, C.; Changeux, J.-P. (2003). "A neuronal network model linking subjective reports and objective physiological data during conscious perception". Proceedings of the National Academy of Sciences 100 (14): 8520–8525. doi:10.1073/pnas.1332574100. PMID 12829797. Bibcode2003PNAS..100.8520D. 
  57. Balduzzi, D; Tononi, G (2008). "Integrated information in discrete dynamical systems: motivation and theoretical framework". PLOS Comput Biol 4 (6): e1000091. doi:10.1371/journal.pcbi.1000091. PMID 18551165. Bibcode2008PLSCB...4E0091B. 
  58. Edelman, Gerald M. (1993-02-01). "Neural Darwinism: Selection and reentrant signaling in higher brain function" (in en). Neuron 10 (2): 115–125. doi:10.1016/0896-6273(93)90304-A. ISSN 0896-6273. PMID 8094962. 
  59. Cleeremans, A (2011). "The radical plasticity thesis". Frontiers in Psychology 2: 86. doi:10.3389/fpsyg.2011.00086. PMID 21687455. 
  60. Rosenberg, G. (2004) A Place for Consciousness. Oxford, Oxford University Press. ISBN:0-19-516814-3.
  61. Crick, F. (1995) The Astonishing Hypothesis. Scribner Paperback ISBN:0-684-80158-2 ISBN:978-0684801582
  62. von der Malsburg, Ch.; Schneider, W. (1986-05-01). "A neural cocktail-party processor" (in en). Biological Cybernetics 54 (1): 29–40. doi:10.1007/BF00337113. ISSN 1432-0770. PMID 3719028. 
  63. Singer, Wolf (2006-01-25). "Consciousness and the Binding Problem" (in en). Annals of the New York Academy of Sciences 929 (1): 123–146. doi:10.1111/j.1749-6632.2001.tb05712.x. PMID 11349422. https://onlinelibrary.wiley.com/doi/10.1111/j.1749-6632.2001.tb05712.x. 
  64. Werning, M. (2012). Non-symbolic compositional representation and its neuronal foundation: Towards an emulative semantics. In M. Werning, W. Hinzen & E. Machery (eds.), The Oxford handbook of compositionality (pp. 633–654). Oxford University Press. Oxford.
  65. Smolensky, P. & Legendre, G. (2006). The harmonic mind. From neural computation to optimality-theoretic grammar. Vol. 1: Cognitive architecture. Cambridge, MA and London: A Bradford Book, The MIT Press.
  66. Plate, T. A. (2003). Holographic reduced representations. Distributed representation for cognitive structures. Center for the Study of Language and Information. Stanford, CA: Leland Stanford Junior University.
  67. Stewart, T. C. & Eliasmith, C. (2012). Compositionality and biologically plausible models. In W. Hinzen & E. Machery & M. Werning (eds.), The Oxford handbook of compositionality. Oxford University Press. Oxford. 2012. pp. 596–615.
  68. Maurer, H. (2021). Cognitive science: Integrative synchronization mechanisms in cognitive neuroarchitectures of the modern connectionism. CRC Press, Boca Raton/FL, ISBN 978-1-351-04352-6. https://doi.org/10.1201/9781351043526
  69. Maurer, H. (2016). „Integrative synchronization mechanisms in connectionist cognitive neuroarchitectures". Computational Cognitive Science. 2: 3. https://doi.org/10.1186/s40469-016-0010-8
  70. Marcus, G.F. (2001). The algebraic mind. Integrating connectionism and cognitive science. Bradford Book, The MIT Press, Cambridge, ISBN 0-262-13379-2. https://doi.org/10.7551/mitpress/1187.001.0001
  71. Bechtel,W. & Abrahamsen, A.A. (2002). Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks. 2nd Edition. Blackwell Publishers, Oxford.
  72. Val Danilov, Igor (2023-02-17). "Theoretical Grounds of Shared Intentionality for Neuroscience in Developing Bioengineering Systems". OBM Neurobiology 7 (1): 156. doi:10.21926/obm.neurobiol.2301156. https://www.lidsen.com/journals/neurobiology/neurobiology-07-01-156. 
  73. Val Danilov, Igor (2023). "Low-Frequency Oscillations for Nonlocal Neuronal Coupling in Shared Intentionality Before and After Birth: Toward the Origin of Perception" (in en). OBM Neurobiology 7 (4): 1–17. doi:10.21926/obm.neurobiol.2304192. https://www.lidsen.com/journals/neurobiology/neurobiology-07-04-192. 
  74. Val Danilov, Igor (2023). "Shared Intentionality Modulation at the Cell Level: Low-Frequency Oscillations for Temporal Coordination in Bioengineering Systems" (in en). OBM Neurobiology 7 (4): 1–17. doi:10.21926/obm.neurobiol.2304185. https://www.lidsen.com/journals/neurobiology/neurobiology-07-04-185. 

Further reading

  • Zimmer, H. D. (Hubert D.); Mecklinger, Axel.; Lindenberger, Ulman. (2006). Handbook of binding and memory: perspectives from cognitive neuroscience. Oxford; New York: Oxford University Press. ISBN 978-0-19-852967-5. OCLC 63702616.