Two-point discrimination assessment of the upper extremities of healthy young Turkish individuals

Objectives: This study aims to measure the two-point discrimination (TPD) values of the upper extremities of healthy young Turkish individuals. Patients and methods: Between March 2016 and June 2016, a total of 60 healthy students (31 males, 29 females; mean age: 22.0±1.7 years; range, 19 to 27 years) were included. Eleven grand upper limb parts which take innervation from the brachial plexus were measured with an esthesiometer. Results: The values at the dominant sides were statistically significantly greater than the non-dominant sides at those areas: upper lateral arm (p=0.001), lower lateral arm (p=0.001), mid-posterior arm (p=0.001), mid-lateral forearm (p=0.001), mid-posterior forearm (p=0.012), skin over the first dorsal interossei muscle (p=0.031), and palmar surface of distal phalanx of the thumb (p=0.045). Both dominant and non-dominant lower lateral arm TPD measurement results increased in males compared to females, indicating a statistically significant difference (p=0.005 and p=0.011, respectively). Also, dominant and non-dominant mid-posterior arm measurement scores were found to statistically significantly increase in males compared to females (p=0.019 and p=0.040, respectively). Conclusion: Our study results show that laterality, with lower values on the non-dominant side, but not the sex, has an effect on TPD. The findings of this study may be useful in establishing the normative data for TPD in the upper extremity parts of healthy young Turkish individuals. © 2022 All right reserved by the Turkish Society of Physical Medicine and Rehabilitation

A Primer on Variational Laplace (VL)

This article details a scheme for approximate Bayesian inference, which has underpinned thousands of neuroimaging studies since its introduction 15 years ago. Variational Laplace (VL) provides a generic approach to fitting linear or non-linear models, which may be static or dynamic, returning a posterior probability density over the model parameters and an approximation of log model evidence, which enables Bayesian model comparison. VL applies variational Bayesian inference in conjunction with quadratic or Laplace approximations of the evidence lower bound (free energy). Importantly, update equations do not need to be derived for each model under consideration, providing a general method for fitting a broad class of models. This primer is intended for experimenters and modellers who may wish to fit models to data using variational Bayesian methods, without assuming previous experience of variational Bayes or machine learning. Accompanying code demonstrates how to fit different kinds of model using the reference implementation of the VL scheme in the open-source Statistical Parametric Mapping (SPM) software package. In addition, we provide a standalone software function that does not require SPM, in order to ease translation to other fields, together with detailed pseudocode. Finally, the supplementary materials provide worked derivations of the key equations

A probabilistic atlas of finger dominance in the primary somatosensory cortex

With the advent of ultra-high field (7T), high spatial resolution functional MRI (fMRI) has allowed the differentiation of the cortical representations of each of the digits at an individual-subject level in human primary somatosensory cortex (S1). Here we generate a probabilistic atlas of the contralateral SI representations of the digits of both the left and right hand in a group of 22 right-handed individuals. The atlas is generated in both volume and surface standardised spaces from somatotopic maps obtained by delivering vibrotactile stimulation to each distal phalangeal digit using a travelling wave paradigm. Metrics quantify the likelihood of a given position being assigned to a digit (full probability map) and the most probable digit for a given spatial location (maximum probability map). The atlas is validated using a leave-one-out cross validation procedure. Anatomical variance across the somatotopic map is also assessed to investigate whether the functional variability across subjects is coupled to structural differences. This probabilistic atlas quantifies the variability in digit representations in healthy subjects, finding some quantifiable separability between digits 2, 3 and 4, a complex overlapping relationship between digits 1 and 2, and little agreement of digit 5 across subjects. The atlas and constituent subject maps are available online for use as a reference in future neuroimaging studies

Finger somatotopy is preserved after tetraplegia but deteriorates over time

Previous studies showed reorganised and/or altered activity in the primary sensorimotor cortex after a spinal cord injury (SCI), suggested to reflect abnormal processing. However, little is known about whether somatotopically specific representations can be activated despite reduced or absent afferent hand inputs. In this observational study, we used functional MRI and a (attempted) finger movement task in tetraplegic patients to characterise the somatotopic hand layout in primary somatosensory cortex. We further used structural MRI to assess spared spinal tissue bridges. We found that somatotopic hand representations can be activated through attempted finger movements in the absence of sensory and motor hand functioning, and no spared spinal tissue bridges. Such preserved hand somatotopy could be exploited by rehabilitation approaches that aim to establish new hand-brain functional connections after SCI (e.g. neuroprosthetics). However, over years since SCI the hand representation somatotopy deteriorated, suggesting that somatotopic hand representations are more easily targeted within the first years after SCI

Fast Event-Related Mapping of Population Fingertip Tuning Properties in Human Sensorimotor Cortex at 7T

fMRI studies that investigate somatotopic tactile representations in the human cortex typically use either block or phase-encoded stimulation designs. Event-related (ER) designs allow for more flexible and unpredictable stimulation sequences than the other methods, but they are less efficient. Here we compared an efficiency-optimized fast ER design (2.8s average intertrial interval, ITI) to a conventional slow ER design (8s average ITI) for mapping voxelwise fingertip tactile tuning properties in the sensorimotor cortex of 6 participants at 7 Tesla. The fast ER design yielded more reliable responses compared to the slow ER design, but with otherwise similar tuning properties. Concatenating the fast and slow ER data, we demonstrate in each individual brain the existence of two separate somatotopically-organized tactile representations of the fingertips, one in the primary somatosensory cortex (S1) on the post-central gyrus, and the other shared across the motor and pre-motor cortices on the pre-central gyrus. In both S1 and motor representations, fingertip selectivity decreased progressively, from narrowly-tuned Brodmann areas 3b and 4a respectively, towards associative parietal and frontal regions that responded equally to all fingertips, suggesting increasing information integration along these two pathways. In addition, fingertip selectivity in S1 decreased from the cortical representation of the thumb to that of the pinky

Bayesian population receptive field modeling in human somatosensory cortex

Somatosensation is fundamental to our ability to sense our body and interact with the world. Our body is continuously sampling the environment using a variety of receptors tuned to different features, and this information is routed up to primary somatosensory cortex. Strikingly, the spatial organization of the peripheral receptors in the body are well maintained, with the resulting representation of the body in the brain being referred to as the somatosensory homunculus. Recent years have seen considerable advancements in the field of high-resolution fMRI, which have enabled an increasingly detailed examination of the organization and properties of this homunculus. Here we combined advanced imaging techniques at ultra-high field (7T) with a recently developed Bayesian population receptive field (pRF) modeling framework to examine pRF properties in primary somatosensory cortex. In each subject, vibrotactile stimulation of the fingertips (i.e., the peripheral mechanoreceptors) modulated the fMRI response along the post-central gyrus and these signals were used to estimate pRFs. We found the pRF center location estimates to be in accord with previous work as well as evidence of other properties in line with the underlying neurobiology. Specifically, as expected from the known properties of cortical magnification, we find a larger representation of the index finger compared to the other stimulated digits (middle, index, little). We also show evidence that the little finger is marked by the largest pRF sizes, and that pRF size increases from anterior to posterior regions of S1. The ability to estimate somatosensory pRFs in humans provides an unprecedented opportunity to examine the neural mechanisms underlying somatosensation and is critical for studying how the brain, body, and environment interact to inform perception and action

Decoding the content of cross-modal influences in the brain

This thesis examined how context and prior experience can shape the neural computations occurring in the human brain, specifically by using pattern classification analysis to decode the content of cross-modal influences in and around the primary somatosensory cortex (S1). In Chapter 2, fMRI was used to investigate whether simply hearing familiar sounds depicting different hand-object interactions could be discriminated in S1, even though stimulus presentation occurred in the auditory domain and no external tactile stimulation occurred. Results found discriminable patterns of activity about the sound of different hand-object interactions in hand-sensitive areas of S1, and not our two control categories of familiar animal vocalizations and unfamiliar pure tones. Chapter 3 aimed to corroborate the cross-modal effects found in the previous fMRI literature using a high temporal resolution neuroimaging technique: EEG. Specifically, EEG was used to examine whether simply viewing images of different familiar visual object categories which imply rich haptic information could be identified in sensorimotor-related oscillatory responses, even though input was from a visual source and no tactile stimulation occurred. Results found the content of different familiar, but not unfamiliar, visual object categories could be discriminated in the mu rhythm oscillatory response, thus establishing a potential oscillatory marker for the cross-modal effects previously observed. Chapter 4 involved an interactive fMRI paradigm using real 3D objects to test whether the primary function of the cross-modal influences previously detected is a likely result of predictive coding mechanisms. Whilst no reliable evidence for an account of predictive coding was found in this experiment, this study provided critical insight into the development of experiments which can directly test the assumptions of predictive coding with real action. The research conducted in this thesis has, therefore, provided significant contributions to the literature regarding our understanding of cross-modal influences and cortical feedback in the human brain. Keywords: cross-modal, cortical feedback, multi-voxel pattern analysis, mu rhythm, predictive coding, primary somatosensory cortex