Human mechanosensation: From 1st-order neurone to somatosensory cortex

Funded by: MRC

The peripheral somatosensory system transmits nerve impulses pertaining to tactile, proprioceptive, thermal, nociceptive and affective sensations. There have been significant advances over the past few years, from genetic labelling studies to the development of brain-computer interfaces for neuroprosthetics, that are changing the way we think about the role of the somatosensory system in health and disease.

Our research is focussed on the ‘tactile somatosensory system’ (tSSS), recognizing that neocortical representation of the body surface is a dynamic process, and that body-part representations reorganise in response to alterations in the patterns of activation of 1st -order low threshold mechanosensory (LTM) neurones in the skin; this reorganisation can occur over seconds to months. Discriminative touch is encoded by a number of specialised LTMs that can be broadly divided into different classes depending on their adaptation rate (rapid vs. slow) and receptive fields (large vs. small).

There are many basic questions underlying human tactile processing that remain unanswered. Here, we propose to build on recent theoretical and technical advances in the SomAffect lab at LJMU and the Sir Peter Mansfield Magnetic Resonance Centre at the University of Nottingham to carry out novel studies in humans that, importantly, have no animal equivalent.

human_mechanosensationFor example, we can now perform ultra-high field functional MRI (UHF-fMRI – 7T) (see figure) and magnetoencephalography (MEG) studies during both vibrotactile and single-unit intraneural microstimulation (INMS) of peripheral nerve afferents that will allow us to explore the relationships between bespoke patterns of stimulation in 1st order neurons, their perceptual consequences, and cortical/areal correlates within 1o and 2o somatosensory cortex (SI and SII). The latter does not simply pre-process inputs for higher order integration, but dynamically responds to bottom-up and top-down inputs that are critically dependent on levels of attention and context.

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