These encoding model fits revealed a new map of visual body-part selectivity, which overlapped with somatotopic tuning across the FBA, EBA and, strikingly, the visual word form area (VWFA). 19/n

To address this, we combined the Natural Scenes Dataset with a pose-detection algorithm fit a body-part tuning encoding model. This allowed us to generate a map of visual body part preference, organised along a similar toe-to-tongue axis as the somatotopic connectivity maps. 18/n

We did indeed find evidence for an alignment between visual field tuning and body part tuning beyond that expected by chance. We found this mostly dorsally and in the superior portion of EBA. 16/n

But do these bodily maps predict anything about visual function? For instance, could lower body part tuning (e.g. toes) predict lower visual field tuning? Such an alignment might facilitate interactions with the environment. 15/n

Yes! Throughout dorsolateral visual cortex, we see several body-part gradients separated by reversals. These maps were consistent across hemispheres and subject splits. 14/n

We then repeated our somatosensory connectivity analyses separately on a movie section involving human agents and another without any humans. This demonstrated that somatotopic responses are not generic, but driven by movie content, specifically that featuring human action. 12/n

Our analysis allows us to contrast somatotopic and retinotopic explained variance. All dorsolateral (but not ventral!) visual regions were characterised by multimodal topographic connectivity. These regions care as much or more about the body as they do the visual scene! 11/n

We find that movie watching led to increased somatotopic connectivity in the somatosensory network outlined above. But strikingly, we now also find that dorsolateral visual cortex has structured connectivity with S1. Look at that red band across visual cortex! 10/n

Body part tuning revealed multiple somatotopic gradients and body-part tuning biases that are typically only revealed by exogenous stimulation (e.g. brushing people). Critically, we show that these same detailed principles can be revealed in the absence of sensory input! 7/n

Since this method uses one part of the brain to explain another, we can fit these models to any data - even with no stimulus! Analysing 7T resting state data from the HCP, we found signals in a large cortical network were predicted by somatotopic connectivity with S1. 6/n

This allows us to 'project' the visual field or body part tuning of V1 and S1 onto the rest of the brain. We’re performing connectivity-derived retinotopic and somatotopic mapping, which allows us to find higher-level sensory maps throughout the brain. 5/n

When seeing bodily experiences, our brain responds 'as if' it simulates the observed tactile experience as our own. We know that e.g. viewing fingers being touched can activate finger-selective regions of primary somatosensory cortex (S1) (tinyurl.com/vissom3b) 2/n