Biology subjects

Meier, M. L.

Publications and source records attributed to Meier, M. L..

4 recordsLinked to original sources

bioRxiv2025

Stable Somatotopy in Chronic Low Back Pain: Is Cortical Map Reorganization a Myth?

Chronic low back pain (CLBP) has been linked to maladaptive cortical plasticity in sensorimotor regions, which may contribute to pain persistence through less distinct ("smudged") somatotopic maps of afferent input from the back. However, empirical support for such functional reorganization processes, especially in the primary somatosensory cortex (S1), is limited. To delineate precise sensory representations of the back and test for altered somatotopic processing in CLBP, we utilized an MR-compatible pneumatic vibration device and applied frequency-specific vibrotactile stimuli (20 Hz and 80 Hz) at nine thoracolumbar paraspinal sites in 45 patients with CLBP and 41 healthy controls. Representational similarity analysis (RSA) was employed via a whole-brain searchlight method, and the neural representational patterns were contrasted against theoretical models including a segmental (based on anatomical proximity), simple (upper vs. lower back division) and a random model. In addition, a machine learning classifier was trained to predict afferent input from the upper vs lower back in healthy controls and tested in CLBP patients. Both groups displayed well-organized segmental representations spanning somatosensory, motor, and posterior parietal cortices. Posterior parietal regions exhibited the best model fits, followed by S1. No evidence for differences in representational patterns between groups was found. In CLBP patients, these patterns did not show associations with pain duration, severity, fear of movement or self-reported back perception. The classifier, trained on healthy controls, accurately predicted upper vs lower back afferent input in CLBP patients. These findings indicate preserved cortical maps of the back in CLBP, challenging the hypothesis of sensory cortical reorganization in this condition. Significance StatementChronic low back pain (CLBP) is often linked to maladaptive reorganization of somatotopic maps in sensorimotor cortices, providing the mechanistic rationale for therapies like sensory discrimination training to "normalize" these maps and alleviate pain. Using frequency-specific vibrotactile stimulation of the back and multivariate fMRI analysis, we found well-organized, segmental cortical representations in both CLBP patients and healthy controls, with no evidence of group differences. Representational patterns showed no associations with clinical measures such as pain duration or intensity. These findings challenge the cortical reorganization hypothesis in CLBP and suggest sensory training benefits may involve alternative mechanisms.

neuroscience↗

bioRxiv2022

Towards Detailed Cortical Maps of the Human Back with Representational Similarity Analysis

Cortical reorganization and its potential pathological significance are being increasingly studied in musculoskeletal disorders such as chronic low back pain (CLBP) patients. However, detailed sensory-topographic maps of the human back are lacking, and a baseline characterization of such representations, reflecting the somatosensory organization of the healthy back, is needed before exploring potential sensory map reorganization. To this end, a novel pneumatic vibrotactile stimulation method was used to stimulate paraspinal sensory afferents, while studying their cortical representations in unprecedented detail. In 41 young healthy participants, vibrotactile stimulations at 20 Hz and 80 Hz were applied bilaterally at nine lo cations along the thoracolumbar axis while functional magnetic resonance imaging (fMRI) was performed. Model-based whole-brain searchlight representational similarity analysis (RSA) was used to investigate the organizational structure of brain activity patterns evoked by thoracolumbar sensory inputs. A model based on seg mental distances best explained the similarity structure of brain activity patterns that were located in different areas of sensorimotor cortices, including the primary somatosensory and motor cortices and parts of the superior parietal cortex, suggesting that these brain areas process sensory input from the back in a "dermatomal" manner. The current findings provide a sound basis for testing the "cortical map reorganization theory" and its pathological relevance in CLBP. HighlightsO_LIFine-grained cortical activation patterns of paraspinal vibrotactile sensory input were obtained using whole-brain representational similarity analysis. C_LIO_LIThe patterns were well explained using a model reflecting segmental distances along the thoracolumbar axis. C_LIO_LIThe current results provide a solid basis for revisiting the "cortical map reorganization theory" and its pathological significance in chronic low back pain. C_LI

neuroscience↗

bioRxiv2021

In the back of your mind: Cortical mapping of tactile and proprioceptive paraspinal afferent inputs

Topographic organization is a hallmark of vertebrate cortex architecture, characterized by ordered projections of the bodys sensory surfaces onto brain systems. High-resolution functional magnetic resonance imaging (fMRI) has proven itself as a valuable tool to investigate the cortical landscape and its (mal-)adaptive plasticity with respect to various body part representations, in particular extremities such as the hand and fingers. Less is known, however, about the cortical representation of the human back. We therefore validated a novel, MRI-compatible method of mapping cortical representations of sensory afferents of the back, using vibrotactile stimulation at varying frequencies and paraspinal locations, in conjunction with fMRI. We expected high-frequency stimulation to be associated with differential neuronal activity in the primary somatosensory cortex (S1) compared to low-frequency stimulation and that somatosensory representations would differ across the thoracolumbar axis. We found significant differences between neural representations of high- and low-frequency stimulation and between representations of thoracic and lumbar paraspinal locations, in several bilateral S1 sub-regions, and in regions of the primary motor cortex (M1). High-frequency stimulation preferentially activated Brodmann Area (BA) regions BA3a and BA4p, while low-frequency stimulation was more encoded in BA3b and BA4a. Moreover, we found clear topographic differences in S1 for representations of the upper and lower back during high-frequency stimulation. We present the first neurobiological validation of a method for establishing detailed cortical maps of the human back, which might serve as a novel tool to evaluate the pathological significance of neuroplastic changes in clinical conditions such as chronic low back pain. Key pointsO_LIDetailed investigations of cortical representations of somatosensory paraspinal afferents along the thoracolumbar axis are lacking. C_LIO_LIUsing fMRI combined with a novel vibrotactile stimulation device ("pneuVID") we investigated different sensorimotor cortical representations of the back and explored topographic differences between the upper and lower back. C_LIO_LIWe found differential sub-regional sensorimotor neural representations of high- and low-frequency stimulation, as well as revealing initial evidence of the somatotopy of upper and lower paraspinal representations. C_LIO_LIThe current approach might serve as a promising tool to elucidate the role of cortical reorganisation in the pathophysiology of clinical conditions such as chronic low back pain. C_LI

neuroscience↗

bioRxiv2018

Pain-related fear - From different fear constructs to dissociable neural sources

Fear of pain demonstrates significant prognostic value regarding the development of persistent musculoskeletal pain and disability. Its assessment often relies on self-report measures of pain-related fear by a variety of questionnaires. However, based either on \"fear of movement/(re)injury/kinesiophobia\", \"fear avoidance beliefs\" or \"pain anxiety\", pain-related fear constructs seemingly differ while the potential overlap of the questionnaires is unclear. Furthermore, the relationship to other anxiety measures such as state or trait anxiety remains ambiguous. Because the neural bases of fearful and anxious states are well described, advances in neuroimaging such as machine learning on brain activity patterns recorded by functional magnetic resonance imaging might help to dissect commonalities or differences across pain-related fear constructs. We applied a pattern regression approach in 20 non-specific chronic low back pain patients to reveal predictive relationships between fear-related neural information and different pain-related fear questionnaires. More specifically, the applied Multiple Kernel Learning approach allowed generating models to predict the questionnaire scores based on a hierarchical ranking of fear-related neural patterns induced by viewing videos of potentially harmful activities for the back. We sought to find evidence for or against overlapping pain-related fear constructs by comparing the questionnaire prediction models according to their predictive abilities and associated neural contributors. The results underpin the diversity of pain-related fear constructs by demonstrating evidence of non-overlapping neural predictors within fear processing regions. This neuroscientific approach might ultimately help to further understand and dissect psychological pain-related fear constructs.\n\nSignificancePain-related fear, often assessed through self-reports such as questionnaires, has shown prognostic value and clinical utility for a variety of musculoskeletal pain disorders. However, it remains difficult to determine a common underlying construct of pain-related fear due to several proposed constructs among questionnaires. The current study describes a novel neuroscientific approach using machine learning of neural patterns within the fear circuit of chronic low back pain patients that has the potential to identify neural commonalities or differences among the various pain-related fear constructs. Ultimately, this approach might afford a deeper understanding of the suggested constructs and might be also applied to other domains where ambiguity exists between different psychological constructs.

neuroscience↗