The issue of chunking information is a way of having an entire data-set represented by one concept or idea (Miller 1956). Unconscious information (or thinking-fast, Kahneman 2011) assumes a high level of abstraction. For instance, Einstein’s ‘E = mc^2’, subsumes the data and analysis previously contemplated by Einstein and the details of the analysis become unconscious, such that they are stored in condensed—and hence more manageable—form in the neocortex and the cerebellum, as well as in data books and articles and on computers and so on (Clark 1998; Varela et al. 1991). In a like manner, (as discussed in an earlier chapter) when one executes an express saccade within a sensory context (Schiller and Tehovnik 2015), the sensory context is an abstraction of the sensory environment, the details of which can remain unconscious until alterations need to be made to the abstraction.

The cerebellum, unlike the neocortex, deals with the sensory and motor realities of the external world (i.e., the environment) and the internal world (i.e., the organs of the body) by transforming sensory mappings into muscle depictions (Tehovnik et al. 2021). Indeed, in humans the number of neurons/connections within the cerebellum is extreme at 2.8 x 10^14 synapses, which is comparable to the 1.6 x 10^14 synapses of the neocortex (Huang 2008; Tang et al. 2001).[1] A book, its pages, its paragraphs, its sentences, its words, and its alphabet comprise a language, and quantitative data committed to tables and graphs are condensed to a general equation, such as E = mc^2, that collectively comprise mathematics. Based on what we know about the differences between the cerebellum and the neocortex (Tehovnik et al. 2021; Hasanbegović 2024), the former, the cerebellum, has a record of all the sensory-motor details supporting each abstraction which is continuously updated via sensory feedback and stored as an efference copy representation, whereas the latter, the neocortex, has an explicit representation of an abstraction (Corkin 2002; Bell et al. 1997; De Zeeuw 2021; Loyola et al. 2019; Shadmehr 2020; Squire et al. 2001; Tehovnik et al. 2021; Wang et al. 2023).

It is noteworthy that ‘E = mc^2’ by itself represents very little information at 7.5 bits (i.e.,1.5 bits per symbol times 5 symbols, Reed and Durlach 1998), which can be uttered within one second. But the data that this expression is based on are enormous and found mainly outside of Einstein’s brain in libraries and in current (or retired) laboratories. It must be stressed that the reason mammals including humans have a large number of neurons and synapses is mainly for internal use (rather than to drive the muscles), and it is this internal use that has allowed exceptional people such as Einstein to come up with expressions like ‘E = mc^2’, which captures a fundamental reality about the universe. Finally, Einstein’s deductions had as much to do with how his brain stored and analyzed information[2], as it did with how he used the external world of graphs and mathematics to arrive at his abstractions, plus his ability to communicate clearly with colleagues and eventually with the rest of the world.[3]

Footnotes:

[1] In mammals, the number of neurons in the cerebellum is typically four times greater than the number of neurons in the neocortex (Herculano-Houzel 2009, 2011). However, in the case of the elephant, the cerebellum has over 40 times more neurons as compared to the number of neurons in the neocortex (Herculano-Houzel et al. 2014).

[2] There was nothing extraordinary about Einstein’s brain other than it having a somewhat enlarged parietal cortex (Kremer 2015). Perhaps, size is not as important as synaptic connectivity (Hebb 1948), which determines how one looks at and analyzes the world. In the case of Einstein, this propensity could have been present from birth but for sure was shaped by his pre-university experiences.

[3] It is well appreciated that a concept or idea is built on lots of empirical data which often takes years to assemble. Indeed, this commitment of intellectual labor per concept is what causes theorists to succumb to their theories, e.g., Skinner could never accept the transition from behaviorism to cognition (see: Skinner 1957 versus Chomsky 1959). And both schools of thought ignored biology, but this disregard is over because of the successes of neuroscience (Hubel and Wiesel 1977; O’Keefe and Nadel 1978; Schiller and Tehovnik 2015) and the biological sciences (Dawkins 1976; Noble and Noble 2023).