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Somatosensation

Somatosensation

The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.

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Related Experiment Video

Updated: May 6, 2026

Somatosensory Event-related Potentials from Orofacial Skin Stretch Stimulation

Somatosensory Event-related Potentials from Orofacial Skin Stretch Stimulation

Published on: December 18, 2015

Somatosensory Evoked BOLD-Signals With Ultra-High Temporal Resolution.

Sara Wesolek¹, Till Nierhaus¹, Dirk Ostwald²

¹Neurocomputation and Neuroimaging Unit (NNU), Freie Universität Berlin, Berlin, Germany.

Human Brain Mapping

|March 16, 2026

Summary

This summary is machine-generated.

This study introduces a novel time-resolved approach to analyzing blood oxygen level-dependent (BOLD) signals, achieving ultra-high temporal resolution for brain activity. The method reveals distinct temporal and spatial patterns in the hemodynamic response within the somatosensory system.

Keywords:

4D fMRI S1 S2 fMRI finite impulse response models somatosensory cortex

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Area of Science:

Neuroimaging
Cognitive Neuroscience
Biomedical Engineering

Background:

The blood oxygen level-dependent (BOLD) signal is crucial for fMRI brain activity characterization.
Improving fMRI temporal resolution is key to understanding hemodynamic response spatiotemporal dynamics.
Few methods focus on enhancing temporal resolution for BOLD signal analysis.

Purpose of the Study:

To develop and apply a method for ultra-high temporal resolution BOLD signal analysis.
To investigate the spatiotemporal dynamics of the hemodynamic response.
To characterize temporal and spatial patterns of brain activity during somatosensory stimulation.

Main Methods:

Applied a reordering method to achieve 60 ms temporal resolution.
Utilized a finite impulse response (FIR) model for temporal dynamics preservation.
Employed ANOVA with 4D nonparametric permutation testing for group-level analysis.

Main Results:

Characterized hemodynamic response with distinct temporal and spatial patterns.
Identified significant signal changes across the whole brain over time.
Revealed differences in response shapes within the somatosensory system.

Conclusions:

Introduced a time-resolved approach to BOLD signal analysis.
Demonstrated the utility of ultra-high temporal resolution for hemodynamic response characterization.
Inspired by EEG grand-average techniques for enhanced BOLD signal analysis.