The Social Brain Paradigm

Abstract

This chapter introduces my perspective on and my model of the social brain. The development of the social brain paradigm reflects a general development from hierarchical to network thinking across the intellectual spectrum during the latter part of the twentieth century. I discuss the evolution of the social intelligence hypothesis into the social brain hypothesis, and the reigning myths about the brain that have obstructed social brain thinking. I review the key developments in the history of neuroscience at its nexus with the life- and social sciences and their connections to social brain research and theory. The chapter ends with a presentation of my model of the social brain as a networked information system situated in and coupled with a social ecology (Appendix 1). In Appendix 2, I review the concept of connectomics, and in Appendix 3, I list links to glossaries on brain terminology to aid readers in understanding the terms used in the text to describe the structure and function of the brain.

Appendices

Appendix 1: The Social Brain Model: The Social Ecology of the Brain

Fig. 5.1

The networked social brain

Figure 5.1 The original version of this model was designed with Sabrina Weiss . I have taken it through a number of revisions designed to keep pace with developments in neuroscience and in social neuroscience and neurosociology. It was designed to graphically represent and expand Clifford Geertz’s argument for the synchronic emergence of brain and culture. In review, then: (1) biological, social, and cultural causal forces are reciprocally intertwined and conjointly causal; (2) human behavioral repertoires emerge from the complex parallel and recursive interactions of cells, genes, neurons, neural nets, organs, biomes, the brain and central nervous system, other elements of the body’s systems and subsystems, and our social interactions in their ecological and umwelt contexts; (3) socialization is re-imagined as a process that simultaneously informs and variably integrates the biological self, the neurological self, and the social self to construct personality and character; (4) each element in the model is a dialectical entity containing its own internal “seeds” of change, and as following a temporal dynamic that may be at different times synchronous or dyssynchronous relative to other elements; (5) each element is conceived as an information system with all systems multiply inter-linked by the circulation of information; (6) the diagonals with double-headed arrows which crisscross the model map the chaotic dynamics and cooperative neural mass discussed by C.A. Skarda and W.J. Freeman (1987, 1990); (7) the unit model is activated in a triad of unit models and it is that triad that is the basic model of brain/mind/culture/world. This reflects the idea that the triad is the basic unit of social life (Restivo et al. 2014: 104n1); and (8) the diagram is the General Connectome . A connectome maps the elements and interconnections in a network. The term has been used specifically in connection with mapping the neural connections in the brain. Connectome s may range in scale from maps of parts of the nervous system to a map of all of the neural interactions in the brain. Partial connectome s have been constructed of the retina and primary visual cortex of the mouse. In line with these developments, my model represents the highest level of the connectome , a connectome of connectome s.

Based on the ideas introduced in the previous chapters I can now offer an initial concept formula for the probability of an “innovative thought.” iT_p = qc² × K + G, where qc² is the amount of cultural capital the person commands and K is a constant that represents the cultural context and network structure the person is embedded in; qc² because doubling the amount of cultural capital, for example, quadruples its impact factor. K = C + N_t. C = Cultural Context, an index that takes into account a variety of demographic, class, gender, and institutional diversity indicators; N = the density and diversity of the network structure of the society. G = the genius cluster quotient at time t. When considering the etiology of behaviors traditionally considered to be genetically grounded, it is now important to recognize that the brain, like humans, arrives on the evolutionary stage always, already, and everywhere, social. Therefore, what we have considered to be linearly transmitted genetic phenomena must now be viewed in the context of a brain that is at no stage of development separated from the social and cultural imperatives that form us. The very notions of “genes” and “genetic” must now be revised in the context of the social brain paradigm.

The next stage in this project is to embed the basic triad of the General Connectome in the nested networks of the social and cultural connectomes locally, regionally, and globally so that we now visualize a Global Connectome driven by the circulation of information across nested networks. On the rationale for a global connectome (my interpretation), see Khanna (2016) on “connectography.”

Appendix 2: Connectomics

A connectome comprehensively maps neural connections in the brain. More broadly, a connectome maps all the neural connections in an organism’s nervous system. Hagmann (2005) and Sporns et al. (2005) independently and simultaneously introduced the term “connectome ,” inspired by the efforts to construct a genome. Connectomics is the science of assembling and analyzing connectome data sets. Hagmann and Sporns discussed research strategies for developing comprehensive structural descriptions of the brain’s networks, a dataset they called the “connectome .” Such a connectome would help us understand the emergence of functional brain states from their structural substrate. Connectomic s, the production and study of connectome s, can be applied at different scales from the full set of neurons and synapses in a part or all of an organism’s nervous system to macro-level descriptions of the connections between all cortical and subcortical structures. The full connectome of the roundworm has been constructed along with partial connectome s of a mouse retina and primary visual cortex.

Appendix 3: Guides to the Technical Brain Terms Used in this Book

• https://www.dana.org/brainglossary/

• https://www.brainfacts.org/glossary

• https://mayfieldclinic.com/pe-anatbrain.htm

• https://www.google.com/search?q=parts+of+the+brain+and+their+functions+chart&safe=off&client=safari&sa=X&rls=en&biw=1218&bih=752&tbm=isch&source=iu&ictx=1&fir=nYBnlzaBiedEcM%253A%252CdE9NmhvLUJFzjM%252C_&vet=1&usg=AI4_-kTdU8tqEE14iJcfb1jdKW-J-0HWcg&ved=2ahUKEwiU3s709YTjAhUMZd8KHR-TDJcQ9QEwBXoECAcQDg#imgrc=_&vet=1

Appendix 4: Bibliographic Notes for Chapter 5

The Social Intelligence Hypothesis

• Websites: for an overview of the social intelligence hypothesis and some initial references to evolution and the social brain see: https://www.sciencedirect.com/topics/psychology/social-intelligence-hypothesis; https://www.sciencedirect.com/science/article/pii/S1364661306003263: more recent examinations of the social intelligence hypothesis suggest the need for a broader theoretical framework that embraces “both inter-specific differences and similarities in cognition; … how selection pressures that are associated with sociality interact with those that are imposed by non-social forms of environmental complexity, and how both types of functional demands interact with phylogenetic and developmental constraints” (Holekamp: https://doi.org/10.1016/j.tics.2006.11.003). For a critical evaluation of the hypothesis by Hemelrijk (2007) see: https://pdfs.semanticscholar.org/8df0/5c96641806c2bc45b220aeb792f563ee6473.pdf

Books, Articles, and Chapters

• Whiten (2000), de Waal et al. (2003), Johnson-Ulrich (2017).

• On the meaning of “monotonic”: In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. In calculus, a function defined as a subset of the real numbers with real values is called monotonic if and only if it is either entirely non-increasing or entirely non-decreasing. That is, a function that increases monotonically does not exclusively have to increase, it simply must not decrease.

The Social Brain Paradigm: Selected References

• The literature on social cognition is relevant here but tends traditionally to be too embedded in the psychological-biological-neuroscience context which trumps the social and cultural contextual approaches. For an important exception, see Fiske and Taylor (2013); the authors are still under the influence of the idea that biology has causal priority over culture; but this is a serious effort to integrate emerging developments in social cognition with developments in social neuroscience, cultural psychology, and applied psychology. On the social brain per se, see Brüne et al. (2003), Dunbar et al. (2010); on social neuroscience, see Cacioppo et al. (2002), Schutt et al. (2015); on neurosociology, see Franks and Smith (1999), Franks and Turner (2013), Pickersgill and Keulen (2012), Barta (2014): this is really an anthropology of consciousness and extremely well done except for Bartra’s effort to save free will.On Issues Surrounding the Idea of the Split Brain

• https://www.health.harvard.edu/blog/right-brainleft-brain-right-; https://brainconnection.brainhq.com/2001/06/26/roger-sperry-the-brains-inside-the-brain

• https://www.inc.com/jessica-stillman/left-brained-v-right-brained-people-is-a-total-myt.htmlThe Chaotic and Anarchic BrainSkarda and Freeman (1987, 1990), Duke and Pritchard (1991), Lehnertz et al. (2000), Soresi (2014), Zapporoli et al. (2015), Carhart-Harris and Friston (2019).

• On the Concept of the Umwelt

• See: Kull (1998), Sebeok (1976), Sebeok and Umlker-Sebeok (1978), and Uexküll, J.v. (1957, 2010/1934), and Uexküll, T.v. (1987).