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Jarocka, E.

Publications and source records attributed to Jarocka, E..

2 recordsLinked to original sources

Mechanoreceptive Aβ primary afferents discriminate naturalistic social touch inputs at a functionally relevant time scale

Interpersonal touch is an important part of our social and emotional interactions. How these physical, skin-to-skin touch expressions are processed in the peripheral nervous system is not well understood. From single-unit microneurography recordings in humans, we evaluated the capacity of six subtypes of cutaneous afferents to differentiate perceptually distinct social touch expressions. By leveraging conventional statistical analyses and classification analyses using convolutional neural networks and support vector machines, we found that single units of multiple A{beta} subtypes, especially slowly adapting type II (SA-II) and fast adapting hair follicle afferents (HFA), can reliably differentiate the skin contact of those expressions at accuracies similar to those perceptually. Rapidly adapting field (Field) afferents exhibit lower accuracies, whereas C-tactile (CT), fast adapting Pacinian corpuscles (FA-II), and muscle spindle (MS) afferents can barely differentiate the expressions, despite responding to the stimuli. We then identified the most informative firing patterns of SA-II and HFA afferents spike trains, which indicate that an average duration of 3-4 s of firing provides sufficient discriminative information. Those two subtypes also exhibit robust tolerance to shifts in spike-timing of up to 10 ms. A greater shift in spike-timing, however, drastically compromises an afferents discrimination capacity, and can change a firing patterns envelope to resemble that of another expression. Altogether, the findings indicate that SA-II and HFA afferents differentiate the skin contact of social touch at time scales relevant for such interactions, which is 1-2 orders of magnitude longer than those relevant for discriminating non-social touch inputs.

neuroscience↗

Human first-order tactile neurons can resolve spatial details on the scale of single fingerprint ridges

Fast-adapting type 1 (FA-1) and slow-adapting type 1 (SA-1) first-order tactile neurons provide detailed spatiotemporal tactile information when we touch objects with fingertips. The distal axon of these neuron types branches in the skin and innervates many receptor organs associated with fingerprint ridges (Meissner corpuscles and Merkel cell neurite complexes, respectively), resulting in heterogeneous receptive fields that include many highly sensitive zones or subfields. Using raised dots that tangentially scanned a neurons receptive field, here we examined the spatial resolution capacity of FA-1 and SA-1 neurons afforded by their heterogeneous receptive fields and its constancy across scanning speed and direction. We report that the resolution of both neuron types on average corresponds to a spatial period of [~]0.4 mm and provide evidence that a subfields spatial selectivity arises because its associated receptor organ measures mechanical events limited to a single fingerprint ridge. Accordingly, the sensitivity topography of a neurons receptive fields is quite stable over repeated mappings and over scanning speeds representative of real-world hand use. The sensitivity topography is substantially conserved also for different scanning directions, but the subfields can be relatively displaced by direction-dependent shear deformations of the skin surface. Significance StatementThe branching of the distal axon of first-order tactile neurons with receptor-organs associated with fingerprint ridges (Meissner and Merkel end-organs) results in cutaneous receptive fields composed of several distinct subfields spread across multiple ridges. We show that the spatial selectivity of the subfields typically corresponds to the dimension of the ridges ([~]0.4 mm) and that neurons subfield layout is well preserved across tangential movement speeds and directions representative of natural use of the fingertips. We submit that the receptor-organ underlying a subfield essentially measures mechanical events at an individual ridge. That neurons receive convergent input from multiple subfields does not preclude the possibility that spatial details can be resolved on the scale of single fingerprint ridges by a population code.

neuroscience↗