Abstract
The notion of “hierarchy” is one of the most commonly posited organizational principles in systems neuroscience. To this date, however, it has received little philosophical analysis. This is unfortunate, because the general concept of hierarchy ranges over two approaches with distinct empirical commitments, and whose conceptual relations remain unclear. We call the first approach the “representational hierarchy” view, which posits that an anatomical hierarchy of feed forward, feed-back, and lateral connections underlies a signal processing hierarchy of input-output relations. Because the representational hierarchy view holds that unimodal sensory representations are subsequently elaborated into more categorical and rule-based ones, it is committed to an increasing degree of abstraction along the hierarchy. The second view, which we call “topological hierarchy,” is not committed to different representational functions or degrees of abstraction at different levels. Topological approaches instead posit that the hierarchical level of a part of the brain depends on how central it is to the pattern of connections in the system. Based on the current evidence, we argue that three conceptual relations between the two approaches are possible: topological hierarchies could substantiate the traditional representational hierarchy, conflict with it, or contribute to a plurality of approaches needed to understand the organization of the brain. By articulating each of these possibilities, our analysis attempts to open a conceptual space in which further neuroscientific and philosophical reasoning about neural hierarchy can proceed.
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Notes
- 1.
Hilgetag and Goulas (2020) distinguish four instead of two senses of hierarchy. Although a detailed comparison of both taxonomies is beyond the scope of this chapter, we think that their definitions of hierarchy as laminar projection patterns and as spatial gradients of structural features share the commitments of what we call the “representational” notion of hierarchy (Sect. 6.4.2, Fig. 6.3). Similarly, we think that their definitions of hierarchy in terms of topological projection sequences and as multilevel modular networks share the commitments of what we call the “topological approach” (Sect. 6.3., Fig. 6.4).
- 2.
While we focus on the influence notion of hierarchy, other network investigations employ a more compositional notion of hierarchy as well. For instance, researchers also talk of “hierarchy” if network structure is self-similar, e.g. when smaller modules are nested within larger modules (Hilgetag and Goulas 2020). While it may be interesting to analyze how such “encapsulation hierarchies” relate to compositional hierarchies in the mechanistic literature (Craver 2007, ch. 5), in the following we assume that systems neuroscientists studying encapsulation hierarchies are usually interested in its implications for neural signaling, i.e. on how influential a brain part is within the network (Müller-Linow et al. 2008; Sporns and Betzel 2016).
- 3.
Note that there are methodological issues with identifying functional hubs based on degree alone. In Pearson correlation networks, degree is partially driven by the size and not only the amount of influence a subnetwork has. Thus, nodes in larger brain areas tend to be identified as hubs in because they are part of large physical entities (Power et al. 2013). Yet some areas consistently come out as hubs in functional connectivity studies using different measures, such as anterior and posterior cingulate gyrus of the DMN (van den Heuvel and Sporns 2013).
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We thank audiences at the AISC Midterm Conference 2018 (University of Genoa) and at the Neural Mechanisms web conference 2018, as well as four anonymous reviewers for helpful feedback on earlier versions of this manuscript.
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Burnston, D.C., Haueis, P. (2021). Evolving Concepts of “Hierarchy” in Systems Neuroscience. In: Calzavarini, F., Viola, M. (eds) Neural Mechanisms. Studies in Brain and Mind, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-54092-0_6
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