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The Binding Problem
Abstract
Our brains process visual data in segregated, specialized cortical areas. As is commonly remarked, the brain processes the what and the where of its environment in separate, distal locations. Indeed, regarding the what information that the brain computes, it responds to edges, colors, and movements using different neuronal pathways. Moreover, so far as we can tell, there are no true association areas in our cortices. There are no convergence zones where information is pooled and united; there are no central neural areas dedicated to information exchange. Still, the visual features that we extract separately have to come together in some way, since our experiences are of these features united together into a single unit. The binding problem is explaining how our brains do that, given the serial, distributed nature of our visual processing. How do our minds know to join the perception of a shape with the perception of its color to give us the single, unified experience of a colored object?
... While [6] targets panpsychist theories only, ref. [7] has shown the problem applies also to other theories of consciousness. In addition to citations in this section, the binding problem is discussed widely elsewhere in the context of experiential binding, e.g., [8][9][10][11]. ...
... For instance, while an individual unit remains the locus of awareness, the content of that awareness might incorporate some set of that unit's direct 'single edge' causal relationships, albeit not the units on the other end of those relationships (which simply reintroduces the need for a phenomenal binding mechanism). This approach may be worth pursuing, but needs to contend with the prevailing neuroscientific view that our conscious experience seems to reflect information in multiple parts of the brain and there does not appear to be one specific micro unit where all consciously experienced information collects (e.g., [9]). It also needs to contend with the prevailing view in particle-based physics that whatever the ultimate units of reality turn out to be, they are likely to have only modest informational complexity. ...
Theories of consciousness grounded in neuroscience must explain the phenomenal binding problem, e.g., how micro-units of information are combined to create the macro-scale conscious experience common to human phenomenology. An example is how single ‘pixels’ of a visual scene are experienced as a single holistic image in the ‘mind’s eye’, rather than as individual, separate, and massively parallel experiences, corresponding perhaps to individual neuron activations, neural ensembles, or foveal saccades, any of which could conceivably deliver identical functionality from an information processing point of view. There are multiple contested candidate solutions to the phenomenal binding problem. This paper explores how the metaphysical infrastructure of Integrated Information Theory (IIT) v4.0 can provide a distinctive solution. The solution—that particular entities aggregable from multiple units (‘complexes’) define existence—might work in a static picture, but introduces issues in a dynamic system. We ask what happens to our phenomenal self as the main complex moves around a biological neural network. Our account of conscious entities developing through time leads to an apparent dilemma for IIT theorists between non-local entity transitions and contiguous selves: the ‘dynamic entity evolution problem’. As well as specifying the dilemma, we describe three ways IIT might dissolve the dilemma before it gains traction. Clarifying IIT’s position on the phenomenal binding problem, potentially underpinned with novel empirical or theoretical research, helps researchers understand IIT and assess its plausibility. We see our paper as contributing to IIT’s current research emphasis on the shift from static to dynamic analysis.
... A tal proposito, è possibile individuare un problema caratteristico, da tempo presente nel campo della filosofia della mente e delle neuroscienze, che si potrebbe rielaborare a partire anche da questo lavoro: si tratta del cosiddetto binding problem, ovvero come sia possibile che dall'eterogeneità di informazioni che il cervello elabora costantemente, attraverso distinti processi neurali relativamente indipendenti, emerga un'esperienza singola, sintetica, coerente e integrata, così come appare a noi. 7 Tuttavia, il problema del passaggio dall'unitarietà neurale a quella fenomenica non è così scontato. Infatti, l'indicazione di precise correlazioni tra l'evento cosciente soggettivo e la determinata attivazione neuronale non è sufficiente per inferire una relazione diretta o tra proprietà fenomeniche e fisiche. ...
Despite the theoretical and epistemological complexities involved in dealing with the phenomenon of consciousness, the author describes defines a pragmatic and experimental methodology, based on a two-dimensional neurocognitive approach. Indeed, in order to avoid the hard problem of consciousness, it would be better to focus on the real problem, i.e. on mechanisms that can be empirically observed, leaving out all of the epistemic and phenomenological features of conscious states. The idea of a hierarchical relationship between the level (wakefulness) and the content (awareness) of consciousness could give rise to an interpretation which justifies both the unity and, at the same time, the phenomenal variety of consciousness. However, studies on sleep, REM phase and nightmares might challenge at least the strong version of this hypothetical relationship between different features of consciousness. Furthermore, it is important to consider whether a two-dimensional perspective, rather than a three-dimensional one, would be sufficient to exhaustively define all the objective features of consciousness.
... One of the core themes in cognitive science consists in the endeavour to achieve an integrated theory of cognition, which requires integrative mechanisms explaining how the information processing occurring simultaneously in spatially segregated (sub-)cortical areas is coordinated and bound together to give rise to coherent perceptual and symbolic representations (Engel and Singer 2001;Singer 2013a). This so-called "(general) binding problem" (Hardcastle 1998;Hummel 1999;Singer 1999a;Sougné 2003;von der Malsburg 2001), that is, the problem of dynamically representing conjunctions of informational elements, from the most basic perceptual representations ("feature binding") to the most complex cognitive representations like symbol structures ("variable binding"), appears to be solved by temporal integrative mechanisms. In other words, one of the coordinating mechanisms appears to be the temporal synchronization of neural Correspondence: harald.maurer@informatik.uni-tuebingen.de ...
Based on the mathematics of nonlinear Dynamical System Theory, neurocognition can be analyzed by convergent fluid and transient neurodynamics in abstract n-dimensional system phase spaces in the form of nonlinear vector fields, vector streams or vector flows (the so-called “vectorial form”). This processual or dynamical perspective on cognition, including the dynamical binding mechanisms in cognitive neuroarchitectures, has the advantage of a more accurately modeling of the transient cognitive processes. Thus, neurocognition can be considered as being organized by integrative synchronization mechanisms which best explain the liquid flow of neurocognitive information orchestrated in a network of positive and/or negative feedback loops in the subcortical and cortical areas. The human neurocognitive system can be regarded as a nonlinear, dynamical and open nonequilibrium system. This new fluid or liquid perspective in cognitive science and cognitive neuroscience can be regarded as a contribution towards bridging the gap between the discrete, abstract symbolic description of propositions in the mind, and their continuous, numerical implementation in self-organizing neural networks modelling the neural information processing in the human brain.
If we were to connect two individuals’ brains together, how would this affect the individuals’ conscious experiences? In particular, it is possible for two people to share any of their conscious experiences; to simultaneously enjoy some token experiences while remaining distinct subjects? The case of the Hogan twins—craniopagus conjoined twins whose brains are connected at the thalamus—seems to show that this can happen. I argue that while practical empirical methods cannot tell us directly whether or not the twins share conscious experiences, considerations about the locality of content processing in the brain entails that they most likely do so.
We observe that approaches to intersubjectivity, involving mirror neurons and involving emulation and prediction, have eclipsed discussion of those same mechanisms for achieving coordination between the two hemispheres of the human brain. We explore some of the implications of the suggestion that the mutual modelling of the two situated hemispheres (each hemisphere ‘second guessing’ the other) is a productive place to start in understanding the phylogenetic and ontogenetic development of cognition and of intersubjectivity.
Neuronal activity in a two-dimensional net is analyzed in the neighborhood of an instability. Bifurcation theory and group theory are used to demonstrate the existence of a variety of doubly-periodic patterns, hexagons, rolls, etc., as solutions to the field equations for the net activity. It is suggested that these simple geometric patterns are the cortical concomitants of the "form constants" seen during visual hallucinosis.
A fundamental step in visual pattern recognition is the establishment of relations between spatially separate features. Recently, we have shown that neurons in the cat visual cortex have oscillatory responses in the range 40-60 Hz (refs 1, 2) which occur in synchrony for cells in a functional column and are tightly correlated with a local oscillatory field potential. This led us to hypothesize that the synchronization of oscillatory responses of spatially distributed, feature selective cells might be a way to establish relations between features in different parts of the visual field. In support of this hypothesis, we demonstrate here that neurons in spatially separate columns can synchronize their oscillatory responses. The synchronization has, on average, no phase difference, depends on the spatial separation and the orientation preference of the cells and is influenced by global stimulus properties.
Primary visual coding can be characterized by the receptive field (RF) properties of single neurons. Subject of this paper is our search for a global, second coding step beyond the RF-concept that links related features in a visual scene. In recent models of visual coding, oscillatory activities have been proposed to constitute such linking signals. We tested the neurophysiological relevance of this hypothesis for the visual system. Single and multiple spikes as well as local field potentials were recorded simultaneously from several locations in the primary visual cortex (A17 and A18) using 7 or 19 individually advanceable fiber-microelectrodes (250 or 330 microns apart). Stimulus-evoked (SE)-resonances of 35-85 Hz were found in these three types of signals throughout the visual cortex when the primary coding channels were activated by their specific stimuli. Stimulus position, orientation, movement direction and velocity, ocularity and stationary flicker caused specific SE-resonances. Coherent SE-resonances were found at distant cortical positions when at least one of the primary coding properties was similar. Coherence was found 1) within a vertical cortex column, 2) between neighbouring hypercolumns, and 3) between two different cortical areas. We assume that the coherence of SE-resonances is mediated by recurrent excitatory intra- and inter-areal connections via phase locking between assemblies that represent the linking features of the actual visual scene. Visually related activities are, thus, transiently labelled by a temporal code that signalizes their momentary association.
Given what we know about the segregated nature of the brain and the relative absence of multi-modal association areas in the cortex, how percepts become unified is not clear. However, if we could work out how and where the brain joins together segregated outputs, we would have a start in localizing the neuronal processes that correlate with conscious perceptual experiences. In this essay, I critically examine data relevant for understanding the neurophysiological underpinnings of perception. In particular, I examine the possibility that 40 Hz. oscillatory firing patterns in cortex are important lower-level neuronal events related to perceptual experiences. I suggest that `binding' - understood as a process of hooking together disparate psychological units - reduces to a property inherent in the structure of our brain's firing patterns. However, this reduction may not reflect the firing rates of individual cells, but instead a `higher level' order superimposed on individual cells' activity.
Recent âconnectionistâ models provide a new explanatory alternative to the digital computer as a model for brain function. Evidence from our EEG research on the olfactory bulb suggests that the brain may indeed use computational mechanisms like those found in connectionist models. In the present paper we discuss our data and develop a model to describe the neural dynamics responsible for odor recognition and discrimination. The results indicate the existence of sensory- and motor-specific information in the spatial dimension of EEG activity and call for new physiological metaphors and techniques of analysis. Special emphasis is placed in our model on chaotic neural activity. We hypothesize that chaotic behavior serves as the essential ground state for the neural perceptual apparatus, and we propose a mechanism for acquiring new forms of patterned activity corresponding to new learned odors. Finally, some of the implications of our neural model for behavioral theories are briefly discussed. Our research, in concert with the connectionist work, encourages a reevaluation of explanatory models that are based only on the digital computer metaphor.
Illusory conjunctions are the incorrect perceptual combination of briefly presented colors and shapes. In the neon colors illusion, achromatic figures take on the color of an overlaid grid of colored lines. Both illusions are explained by a theory that assumes (a) poor location information or poor spatial resolution for some aspects of visual information and (b) that the spatial location of features is constrained by perceptual organization. Computer simulations demonstrate that the mechanisms suggested by the theory are useful in veridical perception and they are sufficient to produce illusory conjunctions. The theory suggests mechanisms that economically encode visual information in a way that filters noise and fills in missing data. Issues related to neural implementation are discussed. Four experiments illustrate the theory. Illusory conjunctions are shown to be affected by objective stimulus organization, by subjective organization, and by the linguistic structure of ambiguous Hebrew words. Neon colors are constrained by linguistic structure in the same way as illusory conjunctions.
In perceiving objects we may synthesize conjunctions of separable features by directing attention serially to each item in turn (A. Treisman and G. Gelade, Cognitive Psychology, 1980, 12, 97–136). This feature-integration theory predicts that when attention is diverted or overloaded, features may be wrongly recombined, giving rise to “illusory conjunctions.” The present paper confirms that illusory conjunctions are frequently experienced among unattended stimuli varying in color and shape, and that they occur also with size and solidity (outlined versus filled-in shapes). They are shown both in verbal recall and in simultaneous and successive matching tasks, making it unlikely that they depend on verbal labeling or on memory failure. They occur as often between stimuli differing on many features as between more similar stimuli, and spatial separation has little effect on their frequency. Each feature seems to be coded as an independent entity and to migrate, when attention is diverted, with few constraints from the other features of its source or destination.
The development of the concept of feature binding as fundamental to neural dynamics has made possible recent advances in the modeling of difficult problems of perception and brain function. Major weaknesses of past neural modeling (most prominently its inability to work with natural stimuli and its 'learning-time' barrier) have been traced back to improper treatment of the binding issue. Signal synchrony is now seen as playing a major role in binding. Inclusion of temporal binding in neural models has led to recent breakthroughs in solving important perceptual problems. Among them is perceptual segmentation, invariant object recognition and natural language parsing, as well as overcoming the 'learning-time' barrier.
Distinctive neural oscillations may link separate brain regions that are responding to the same object. Researchers are now identifying the sources of these vibrations.