Cognition Without Neural Representation: Dynamics of a Complex System

Embodied essentialism in the reconstruction of the animal sign in robot animal design

Robot animals are important for the interpretation of the biological world. In this paper, I show that specific design solutions for robot animal signs usually privilege the overall perception of biological systems (and animal signs in general) as machinic entities, which ignores the role of identity self-generation and sustainability, the hallmark of biological signs. Animal signs are semiotic systems that operate roughly on three subsystems: affordance mapping (related with niche construction and embeddedness), essence categorization, displaying co-enabling relations within the animal system, and sensorimotor autonomy. Of these interrelated systems, the first two are commonly associated with robot animal design and conceptualization, whereas the third one suffers from the unsolved AI design problem of engineering true context-dependent sensitivity. As a result, a semiotic blindness toward biological organisms has derived in dissociated perceptions of robot animals as objects that emulate their biological counterparts through both biomorphic affordance design (biomorphism) and bioinspired task completion. Robot signs are thus confined to the realm of techno myths populating experimental settings narratives, which contributes to a diminishing awareness of biological diversity and animal uniqueness for the construction and preservation of the Umwelt.

Nine insights from internet engineering that help us understand brain network communication

Philosophers have long recognized the value of metaphor as a tool that opens new avenues of investigation. By seeing brains as having the goal of representation, the computer metaphor in its various guises has helped systems neuroscience approach a wide array of neuronal behaviors at small and large scales. Here I advocate a complementary metaphor, the internet. Adopting this metaphor shifts our focus from computing to communication, and from seeing neuronal signals as localized representational elements to seeing neuronal signals as traveling messages. In doing so, we can take advantage of a comparison with the internet's robust and efficient routing strategies to understand how the brain might meet the challenges of network communication. I lay out nine engineering strategies that help the internet solve routing challenges similar to those faced by brain networks. The internet metaphor helps us by reframing neuronal activity across the brain as, in part, a manifestation of routing, which may, in different parts of the system, resemble the internet more, less, or not at all. I describe suggestive evidence consistent with the brain's use of internet-like routing strategies and conclude that, even if empirical data do not directly implicate internet-like routing, the metaphor is valuable as a reference point for those investigating the difficult problem of network communication in the brain and in particular the problem of routing.

May the 4C's be with you: an overview of complexity-inspired frameworks for analysing resting-state neuroimaging data

Competing and complementary models of resting-state brain dynamics contribute to our phenomenological and mechanistic understanding of whole-brain coordination and communication, and provide potential evidence for differential brain functioning associated with normal and pathological behaviour. These neuroscientific theories stem from the perspectives of physics, engineering, mathematics and psychology and create a complicated landscape of domain-specific terminology and meaning, which, when used outside of that domain, may lead to incorrect assumptions and conclusions within the neuroscience community. Here, we review and clarify the key concepts of connectivity, computation, criticality and coherence-the 4C's-and outline a potential role for metastability as a common denominator across these propositions. We analyse and synthesize whole-brain neuroimaging research, examined through functional magnetic imaging, to demonstrate that complexity science offers a principled and integrated approach to describe, and potentially understand, macroscale spontaneous brain functioning.