Abstract
Standard semantic information processing models—information in; information processed; information out (in the form of utterances or actions)—lend themselves to standard models of the functioning of the brain in terms, e.g., of threshold-switch neurons connected via classical synapses. That is, in terms of sophisticated descendants of McCulloch and Pitts models (Bull Math Biophys 7:115–133, 1943). I argue that both the cognition and the brain sides of this framework are incorrect: cognition and thought are not constituted as forms of semantic information processing, and the brain does not function in terms of passive input processing units (e.g., threshold switch neurons or connectionist nodes) organized as neural nets. An alternative framework is developed that models cognition and thought not in terms of semantic information processing, and, correspondingly, models brain functional processes also not in terms of semantic information processing. As alternative to such models: (1) I outline a pragmatist oriented, interaction based (rather than reception or input-processing based), model of representation; (2) derive from this model a fundamental framework of constraints on how the brain must function; (3) show that such a framework is in fact found in the brain, and (4) develop the outlines of a broader model of how mental processes can be realized within this alternative framework. Part I of this discussion focuses on some criticisms of standard modeling frameworks for representation and cognition, and outlines an alternative interactivist, pragmatist oriented, model. In part II, the focus is on the fact that the brain does not, in fact, function in accordance with standard passive input processing models—e.g., information processing models. Instead, there are multiple endogenously active processes at multiple spatial and temporal scales across multiple kinds of cells. A micro-functional model that accounts for, and even predicts, these multi-scale phenomena in generating emergent representation and cognition is outlined. That is, I argue that the interactivist model of representation outlined offers constraints on how the brain should function that are in fact empirically found, and, in reverse, that the multifarious details of brain functioning entail the pragmatist representational model—a very strong interrelationship. In the sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the model presented here: sometimes called the predictive brain approach.
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Notes
Einstein (1990, p. 31).
Note that representation did not exist 13+ billion years ago, and it does now. So it has to have emerged. Any model that cannot account for the emergence of representation is thereby refuted.
Technically, transduction refers to a change in the form of energy. How that could possibly generate a representation, e.g., a sensation, is just as mysterious as how the signet ring impression could do so.
“Transduction, remember, is the function that Descartes assigned to the pineal gland.” (Haugeland 1998, p. 223).
I have (in this discussion) skipped over a preliminary normative emergence—that of normative function. I argue that normative function emerges naturally in living systems, in a manner differing from the standard etiological model of function, and that interaction indication is the crucial (normative) function from which representation emerges (Bickhard 1993, 2004, 2009a; Christensen and Bickhard 2002). Interaction indication is the interface between functional normativity and representational normativity.
This is just an illustration, and leaves multiple issues unaddressed. For example, how can abstractions, such as the number three, be represented within an interactivist framework? The answer is again roughly Piagetian in spirit, though with more changes from Piaget than for small physical objects (Bickhard 2009a). The general programme of modeling the myriad kinds of representational phenomena requires addressing each kind in its own terms.
There are numerous models today that posit effects of action on perception, but not that attempt to model the emergent constitution of representation in terms of (potential) (inter)action. Piaget is among the few who have made that attempt.
The central idea is that processes that are inherently far from thermodynamic equilibrium must be maintained, perhaps via (recursive) self-maintenance, in those far from equilibrium relationships with their environments. Examples range from candle flames to living organisms. Maintenance of such far from equilibrium conditions is, thus, contributory to—normatively functional for—the existence of the system (Bickhard 2009a).
There can also be a distinction between the anticipation and the environmental conditions that would support it. It is the latter conditions that might be called implicit ‘content’.
The impossibility of emergent representation in standard models, e.g., information semantics models, is reflected in arguments for the innatism of a base level of representations (Fodor 1981). But such a position assumes that representation emerged in evolution, and there is no model of how that could occur, nor is there any argument that such evolutionary emergence could not also occur in a single organism’s learning and development (Bickhard 2009c). Instead:
I am inclined to think that the argument has to be wrong, that a nativism pushed to that point becomes unsupportable, that something important must have been left aside. What I think it shows is really not so much an a priori argument for nativism as that there must be some notion of learning that is so incredibly different from the one we have imagined that we don’t even know what it would be like as things now stand. Fodor in Piatelli-Palmarini (1980, p. 269).
The second (macro-level) part of the brain model is discussed in the second of this pair of papers.
The literature on astrocytes has expanded dramatically in the last decades: e.g., Bushong et al. (2004), Chvátal and Syková (2000), Hertz and Zielker (2004), Nedergaard et al. (2003), Newman (2003), Perea and Araque (2007), Ransom et al. (2003), Slezak and Pfreiger (2003), Verkhratsky and Butt (2007), Viggiano et al. (2000).
Note that some models may posit a dynamics by which the threshold per se can be changed. So, in that sense, the threshold is passive relative to whatever changes it, but the focus here is on the sense in which the threshold is passive relative to its inputs, and that form of passivity holds whether or not the threshold per se can be changed.
This is a simplification of a more complex dynamics: (1) there are not just two levels, but, rather, a range of temporal and spatial scales of processes, and (2) influences occur from faster to slower as well as from slower to faster. But the focus here is on the sense in which the slower processes set parameters for faster processes, and that is an asymmetric functional relationship. Faster processes can influence slower processes, but, because they are faster, they do so with a kind of moving average of activity, if at all. Furthermore, as will be discussed in the second paper, the slower processes tend to be modulated by processes external to the local domains, and, thus, potentially less malleable to the influences of local faster processes.
E.g., Zacks et al. (2007).
In doing so, they participate in larger scale oscillatory/modulatory processes. They do not engage in the transmission of semantic information.
Such coupling via larger scale processes will be a meta-modulation of local coupling modulations among small scale processes that occur via shared local extra-cellular environments.
New non-standard modulatory phenomena are today discovered with startling frequency, and these need to be integrated into an overall model. The interactivist model is uniquely suited to be able to address this integration. It is an ongoing, always-under-construction, project.
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Thanks are due to Cliff Hooker for comments on an earlier version of this paper.
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Bickhard, M.H. Toward a Model of Functional Brain Processes I: Central Nervous System Functional Micro-architecture. Axiomathes 25, 217–238 (2015). https://doi.org/10.1007/s10516-015-9275-x
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DOI: https://doi.org/10.1007/s10516-015-9275-x