Supersizing the Mind: Embodiment, Action and Cognitive Extension.

Neurological insults, such as congenital blindness, deafness, amputation, and stroke, often result in surprising and impressive behavioural changes. Cortical reorganisation, which refers to preserved brain tissue taking on a new functional role, is often invoked to account for these behavioural changes. Here, we revisit many of the classical animal and patient cortical remapping studies that spawned this notion of reorganisation. We highlight empirical, methodological, and conceptual problems that call this notion into doubt. We argue that appeal to the idea of reorganisation is attributable in part to the way that cortical maps are empirically derived. Specifically, cortical maps are often defined based on oversimplified assumptions of ‘winner-takes-all’, which in turn leads to an erroneous interpretation of what it means when these maps appear to change. Conceptually, remapping is interpreted as a circuit receiving novel input and processing it in a way unrelated to its original function. This implies that neurons are either pluripotent enough to change what they are tuned to or that a circuit can change what it computes. Instead of reorganisation, we argue that remapping is more likely to occur due to potentiation of pre-existing architecture that already has the requisite representational and computational capacity pre-injury. This architecture can be facilitated via Hebbian and homeostatic plasticity mechanisms. Crucially, our revised framework proposes that opportunities for functional change are constrained throughout the lifespan by the underlying structural ‘blueprint’. At no period, including early in development, does the cortex offer structural opportunities for functional pluripotency. We conclude that reorganisation as a distinct form of cortical plasticity, ubiquitously evoked with words such as ‘take-over’’ and ‘rewiring’, does not exist.

Against cortical reorganisation

Abstract Traditional and new disciplines converge in suggesting that the parietal lobe underwent a considerable expansion during human evolution. Through the study of endocasts and shape analysis, paleoneurology has shown an increased globularity of the braincase and bulging of the parietal region in modern humans, as compared to other human species, including Neandertals. Cortical complexity increased in both the superior and inferior parietal lobules. Emerging fields bridging archaeology and neuroscience supply further evidence of the involvement of the parietal cortex in human-specific behaviors related to visuospatial capacity, technological integration, self-awareness, numerosity, mathematical reasoning and language. Here, we complement these inferences on the parietal lobe evolution, with results from more classical neuroscience disciplines, such as behavioral neurophysiology, functional neuroimaging, and brain lesions; and apply these to define the neural substrates and the role of the parietal lobes in the emergence of functions at the core of material culture, such as tool-making, tool use and constructional abilities. 

/pdf/the-parietal-lobe-evolution-and-the-emergence-of-material-195brg73.pdf

The parietal lobe evolution and the emergence of material culture in the human genus

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both “Cartesian theaters” and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).

https://www.mdpi.com/1099-4300/23/6/783/pdf

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again.

We review four current computational models that simulate the response of mechanoreceptors in the glabrous skin to tactile stimulation. The aim is to inform researchers in psychology, sensorimotor science and robotics who may want to implement this type of quantitative model in their research. This approach proves relevant to understanding of the interaction between skin response and neural activity as it avoids some of the limitations of traditional measurement methods of tribology, for the skin, and neurophysiology, for tactile neurons. The main advantage is to afford new ways of looking at the combined effects of skin properties on the activity of a population of tactile neurons, and to examine different forms of coding by tactile neurons. Here, we provide an overview of selected models from stimulus application to neuronal spiking response, including their evaluation in terms of existing data, and their applicability in relation to human tactile perception.

/pdf/skin-and-mechanoreceptor-contribution-to-tactile-input-for-44zmbupc.pdf

Skin and Mechanoreceptor Contribution to Tactile Input for Perception: A Review of Simulation Models

Somatosensory cortex efficiently processes touch located beyond the body

Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Though it seems straightforward, this simple representation belies the complex link between an activation in somatosensory Area 3b and the associated touch location on the body. Any isolated activation is spatially ambiguous without a neural decoder that can read its position within the entire map, though how this is computed by neural networks is unknown. We propose that somatosensory cortex implements multilateration, a common computation used by surveying and GPS systems to localize objects. Specifically, to decode touch location on the body, the somatosensory system estimates the relative distance between the afferent input and the body9s joints. We show that a simple feedforward neural network which captures the receptive field properties of somatosensory cortex implements a Bayes-optimal multilateral decoder via a combination of bell-shaped (Area 3b) and sigmoidal (Areas 1/2) tuning curves. Simulations demonstrated that this decoder produced a unique pattern of localization variability between two joints that was not produced by other known neural decoders. Finally, we identify this neural signature of multilateration in actual psychophysical experiments, suggesting that it is a candidate computational mechanism underlying tactile localization.

/pdf/a-neural-surveyor-in-somatosensory-cortex-3dl7041qsf.pdf

A neural surveyor in somatosensory cortex

1 Numerous studies have suggested that tools become incorporated into a representation of our body. 2 A prominent hypothesis suggests that our brain re-uses body-based computations when we use tools. 3 However, little is known about how this is implemented at the neural level. Here we used the ability 4 to localize touch on both tools and body parts as a case study to fill this gap. Neural oscillations in the 5 alpha (8-13 Hz) and beta (15-25 Hz) frequency bands are involved in mapping touch on the body in 6 distinct reference frames. Alpha activity reflects the mapping of touch in external coordinates, whereas 7 beta activity reflects the mapping of touch in skin-centered coordinates. Here, we aimed at pinpointing 8 the role of these oscillations during tool-extended sensing. We recorded participants’ oscillatory 9 activity while tactile stimuli were applied to either hands or the tips of hand-held rods. The posture of 10 the hands/tool-tips was uncrossed or crossed at participants’ body midline in order for us to 11 disentangle brain responses related to different coordinate systems. We found that alpha-band activity 12 was modulated similarly across postures when localizing touch on hands and on tools, reflecting the 13 position of touch in external space. Source reconstruction also indicated a similar network of cortical 14 regions involved for tools and hands. Our findings strongly suggest that the brain uses similar 15 oscillatory mechanisms for mapping touch on the body and tools, supporting the idea of neural 16 processes being repurposed for tool-use. 17 SIGNIFICANCE STATEMENT 1 Tool use is one of the defining traits of humankind. Tools allow us to explore our environment and 2 expand our sensorimotor abilities. A prominent hypothesis suggests that our brain re-uses body-based 3 neural processing to swiftly adapt to the use of tools. However, little is known about how this is 4 implemented at the neural level. In the present study we used the ability to map touch on both tools 5 and body parts as a case study to fill this gap. We found that the brain uses similar oscillatory 6 mechanisms for mapping touch on a hand-held tool and on the body. These results provide novel and 7 compelling support to the idea that neural processes devoted to body-related information are re8 purposed for tool-use. 9

Alpha oscillations reflect similar mapping mechanisms for localizing touch on 1 hands and tools 2 Abbreviated title : Similar tactile mapping processes for body and tools 3

It has been suggested that our brain re-uses body-based computations to localize touch on tools, but the neural implementation of this process remains unclear. Neural oscillations in the alpha and beta frequency bands are known to map touch on the body in external and skin-centered coordinates, respectively. Here, we pinpointed the role of these oscillations during tool-extended sensing by delivering tactile stimuli to either participants' hands or the tips of hand-held rods. To disentangle brain responses related to each coordinate system, we had participants' hands/tool tips crossed or uncrossed at their body midline. We found that midline crossing modulated alpha (but not beta) band activity similarly for hands and tools, also involving a similar network of cortical regions. Our findings strongly suggest that the brain uses similar oscillatory mechanisms for mapping touch on the body and tools, supporting the idea that body-based neural processes are repurposed for tool use. 

Alpha oscillations reflect similar mapping mechanisms for localizing touch on hands and tools

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Somatosensory cortex efficiently processes touch located beyond the body

A neural surveyor in somatosensory cortex

Alpha oscillations reflect similar mapping mechanisms for localizing touch on 1 hands and tools 2 Abbreviated title : Similar tactile mapping processes for body and tools 3

Alpha oscillations reflect similar mapping mechanisms for localizing touch on hands and tools