Biology subjects

Medlock, L.

Publications and source records attributed to Medlock, L..

5 recordsLinked to original sources

bioRxiv2025

Adaptation in somatosensory afferents improves rate and temporal coding of vibrotactile stimulus features

Adaptation is a common neural phenomenon wherein sustained stimulation evokes fewer action potentials (spikes) over time. Rather than simply reduce firing rate, adaptation may help neurons form better (i.e. more discriminable) representations of sensory input. To study effects of adaptation in low-threshold mechanoreceptors (LTMRs), we recorded single unit LTMR responses to 30-second-long vibrotactile stimuli with different intensities and frequencies applied to the hind paw of rats. To assess the impact of adaptation on somatosensory encoding, decoders were applied to the initial and late (adapted) phases of population-level responses to assess the decodability (discrimination) of stimulus intensity and frequency. Adaptation-mediated changes in the rate and timing (phase-locking) of spikes were quantified. Rate coding of stimulus intensity was improved by the nonuniform reduction in firing rate across responses to different stimuli, and across neurons. This improvement was absent in simulations with uniform reductions in firing rate, thus revealing the necessity of stimulus-dependent variability in adaptation effects. Spike timing (quantified as interspike intervals) remained highly informative about stimulus frequency throughout stimulation despite the progressive reduction in spike count over time. When the drop in spike count was accounted for, adaptation was found to improve temporal coding of stimulus frequency by increasing the precision of phase-locking. In other words, adaptation improved the precision of spike timing, and this increased the information about stimulus frequency conveyed by each spike. These results show that adaptation, by modulating spiking in different ways, can improve encoding of different stimulus features using different coding schemes. SIGNIFICANCE STATEMENTFiring rate adaptation refers to the progressive reduction in spiking during sustained stimulation. Adaptation is often ascribed to fatigue and could conceivably introduce ambiguity into neural representations by causing (the probability or timing of) spike generation to depend not only on the current stimulus, but also on past stimulation. By recording from rat primary somatosensory afferents during vibrotactile stimulation of the paw, we show that nonuniform adaptation across sets of afferents improves rate-based coding of stimulus intensity. We also show that adaptation improves spike timing (phase-locking to a periodic stimulus) which, in turn, improves temporal coding of stimulus frequency. These results demonstrate that early-stage adaptation improves somatosensory signals relayed centrally.

neuroscience↗

bioRxiv2025

Spinal processing of spatiotemporally diverse tactile stimuli: Implications for allodynia and spinal cord stimulation

Touch is mistakenly perceived as painful when inhibition in the spinal dorsal horn (SDH) is weakened. Disinhibition un-gates a polysynaptic spinal circuit but why mechanical allodynia is predominantly evoked by certain stimuli, like dynamic brushing, remains unclear. To answer this, we incorporated receptive fields (RFs) into a computational model of the SDH to study the processing of stimuli with different spatiotemporal features. Broad stimuli normally suppress output spiking by engaging inhibition from the RF surround, but the efficacy of inhibition depends on the inputs temporal pattern. This is critical since excitatory and inhibitory spinal neurons are preferentially sensitive to synchronous and asynchronous input, respectively. Furthermore, spikes driven by synchronous input are resistant to feedforward inhibition. The combined results explain why broad dynamic touch (e.g. brush or vibration) evokes more allodynia than punctate static touch. Our results also show that asynchronous and spatially disordered input evoked by kilohertz-frequency spinal cord stimulation preferentially activates inhibitory neurons, thus explaining its anti-allodynic effects.

neuroscience↗

bioRxiv2024

Encoding of vibrotactile stimuli by mechanoreceptors in rodent glabrous skin

Somatosensory coding in rodents has been mostly studied in the whisker system and hairy skin, whereas the function of low-threshold mechanoreceptors (LTMRs) in rodent glabrous skin has received scant attention, unlike in primates where glabrous skin has been the focus. The relative activation of different LTMR subtypes carries information about vibrotactile stimuli, as does the rate and temporal patterning of LTMR spikes. Rate coding depends on the probability of a spike occurring on each stimulus cycle (reliability) whereas temporal coding depends on the timing of spikes relative to the stimulus cycle (precision). Using in vivo extracellular recordings in rats and mice, we measured the reliability and precision of LTMR responses to different tactile stimuli including sustained pressure and vibration. Similar to other species, rodent LTMRs were separated into rapid-adapting (RA) or slow-adapting (SA) based on their response to sustained pressure. However, unlike the dichotomous frequency preference characteristic of RAI and RAII afferents in other species, rodent RAs fell along a continuum. Fitting generalized linear models (GLMs) to experimental data reproduced the reliability and precision of rodent RAs. The resulting model parameters highlight key mechanistic differences across the RA spectrum; specifically, the integration window of different RAs transitions from wide to narrow as tuning preferences across the population move from low to high frequencies. Our results show that rodent RAs can support both rate and temporal coding, but their heterogeneity suggests that co-activation patterns play a greater role in population coding than for dichotomously tuned primates RAs. Significance StatementOur sense of touch starts with activation of nerve fibres in the skin. Although response properties of various fibre types are well-established in other species (e.g. primates), quantitative characterization in rats and mice is limited. To fill this gap, we performed a comprehensive electrophysiological investigation into the coding properties of tactile fibres in rodent non-hairy skin and then simulated these fibres to explain differences in their responses. We show that rodent tactile fibres resemble those from other species, but that their heterogeneity at the population level may differ, with potentially important implications for encoding of touch. Simulations reveal intrinsic mechanisms that support this heterogeneity and provide a useful tool to explore somatosensation in rodents.

neuroscience↗

bioRxiv2023

Paresthesia during spinal cord stimulation depends on synchrony of dorsal column axon activation

Spinal cord stimulation (SCS) reduces chronic pain. Conventional (40-60 Hz) SCS engages spinal inhibitory mechanisms by activating low-threshold mechanoreceptive afferents with axons in the dorsal columns (DCs). But activating DC axons typically causes a buzzing sensation (paresthesia) that can be uncomfortable. Kilohertz-frequency (1-10 kHz) SCS produces analgesia without paresthesia and is thought, therefore, not to activate DC axons, leaving its mechanism unclear. Here we show in rats that kilohertz-frequency SCS activates DC axons but causes them to spike less synchronously than conventional SCS. Spikes desynchronize because axons entrain irregularly when stimulated at intervals shorter than their refractory period, a phenomenon we call overdrive desynchronization. Effects of overdrive desynchronization on evoked compound action potentials were verified in simulations, rats, pigs, and a chronic pain patient. Whereas synchronous spiking in DC axons is necessary for paresthesia, asynchronous spiking is sufficient to produce analgesia. Asynchronous activation of DC axons thus produces paresthesia-free analgesia.

neuroscience↗

bioRxiv2021

Multiscale computer model of the spinal dorsal horn reveals changes in network processing associated with chronic pain

Pain-related sensory input is processed in the spinal dorsal horn (SDH) before being relayed to the brain. That processing profoundly influences whether stimuli are correctly or incorrectly perceived as painful. Significant advances have been made in identifying the types of excitatory and inhibitory neurons that comprise the SDH, and there is some information about how neuron types are connected, but it remains unclear how the overall circuit processes sensory input or how that processing is disrupted under chronic pain conditions. To explore SDH function, we developed a computational model of the circuit that is tightly constrained by experimental data. Our model comprises conductance-based neuron models that reproduce the characteristic firing patterns of spinal neurons. Excitatory and inhibitory neuron populations, defined by their expression of genetic markers, spiking pattern, or morphology, were synaptically connected according to available qualitative data. Using a genetic algorithm, synaptic weights were tuned to reproduce projection neuron firing rates (model output) based on primary afferent firing rates (model input) across a range of mechanical stimulus intensities. Disparate synaptic weight combinations could produce equivalent circuit function, revealing degeneracy that may underlie heterogeneous responses of different circuits to perturbations or pathological insults. To validate our model, we verified that it responded to reduction of inhibition (i.e. disinhibition) and ablation of specific neuron types in a manner consistent with experiments. Thus validated, our model offers a valuable resource for interpreting experimental results and testing hypotheses in silico to plan experiments for examining normal and pathological SDH circuit function. Significance StatementWe developed a multiscale computer model of the posterior part of spinal cord gray matter (spinal dorsal horn), involved in perception of touch and pain. The model reproduces several experimental observations and makes predictions about how specific types of spinal neurons and synapses influence projection neurons that send information to the brain. Misfiring of these projection neurons can produce anomalous sensations associated with chronic pain. Our computer model will not only assist in planning future experiments, but will also be useful for developing new pharmacotherapy for chronic pain disorders, connecting the effect of drugs acting at the molecular scale with emergent properties of neurons and circuits that shape the pain experience.

neuroscience↗