Biology subjects

Blum, K. P.

Publications and source records attributed to Blum, K. P..

5 recordsLinked to original sources

bioRxiv2026

Flexible integration of corollary discharge and sensory feedback signals in somatosensory cortex

Motor control depends on the continuous integration of motor and sensory signals to maintain accurate estimates of body state, yet neural evidence for this integration remains elusive. Here, we investigated the interaction of motor corollary discharge and proprioceptive feedback signals in area 2 of monkey somatosensory cortex during voluntary and externally-perturbed reaching tasks. Though single neurons had mixed responses to corollary discharge and sensory feedback, we disentangled these signals at the population level to discover they occupy approximately orthogonal subspaces. Integrating information across these subspaces enabled accurate body state estimation prior to feedback arrival during voluntary movements. Moreover, the orthogonal population geometry of corollary discharge and sensory feedback enabled cancellation of movement-related signals to improve the decoding of external perturbations. Together, these results identified orthogonality as a population-level coding strategy for flexible integration of motor and sensory signals to support multiple distinct computations.

neuroscience↗

bioRxiv2022

History-dependent muscle resistance to stretch remains high after small, posturally-relevant pre-movements

The contributions of intrinsic muscle fiber resistance during mechanical perturbations to standing and other postural behaviors are unclear. Muscle stiffness, a traditional metric for estimating muscles intrinsic resistance to stretch, is known to vary depending on the current level and history of the muscles activation, as well as the muscles recent movement history; this property has been referred to as history dependence or muscle thixotropy. However, we currently lack sufficient data about the degree to which muscle stiffness is modulated across posturally-relevant characteristics of muscle stretch and activation. Here, we characterized the history dependence of muscles resistance to stretch in single, permeabilized, activated, muscle fibers in posturally-relevant stretch conditions and activation levels. We used a classic paired muscle stretch paradigm, varying the amplitude of a "conditioning" triangular stretch-shorten cycle followed by a "test" ramp-and-hold imposed after a variable inter-stretch interval. We tested low (<15%), intermediate (15-50%) and high (>50%) muscle fiber activation levels, evaluating short-range stiffness and total impulse in the test stretch. Muscle fiber resistance to stretch remained high at conditioning amplitudes of <1% L0 and inter-stretch intervals of >1 s, characteristic of healthy standing postural sway. A ~70% attenuation of muscle resistance to stretch was reached at conditioning amplitudes of >3% L0 and inter-stretch intervals of <0.1s, characteristic of larger, faster postural sway in balance-impaired individuals. Overall, amplitude and inter-stretch interval interact to disrupt myofilaments such that intrinsic resistance to stretch is attenuated if the stretch is large enough and/or frequent enough. Summary StatementIntrinsic muscle fiber resistance to stretch is preserved after small, slow pre-movements based on healthy postural sway, but markedly reduced as pre-movements increase to emulate abnormal postural sway.

physiology↗

bioRxiv2021

Predicting proprioceptive cortical anatomy and neural coding with topographic autoencoders

Proprioception is one of the least understood senses, yet fundamental for the control of movement. Even basic questions of how limb pose is represented in the somatosensory cortex are unclear. We developed a topographic variational autoencoder with lateral connectivity (topo-VAE) to compute a putative cortical map from a large set of natural movement data. Although not fitted to neural data, our model reproduces two sets of observations from monkey centre-out reaching: 1. The shape and velocity dependence of proprioceptive receptive fields in hand-centered coordinates despite the model having no knowledge of arm kinematics or hand coordinate systems. 2. The distribution of neuronal preferred directions (PDs) recorded from multi-electrode arrays. The model makes several testable predictions: 1. Encoding across the cortex has a blob-and-pinwheel-type geometry of PDs. 2. Few neurons will encode just a single joint. Our model provides a principled basis for understanding of sensorimotor representations, and the theoretical basis of neural manifolds, with applications to the restoration of sensory feedback in brain-computer interfaces and the control of humanoid robots. Author SummaryIt is well established that proprioception is essential for effective for motor control, yet our understanding of proprioceptive coding in somatosensory cortex is far behind that of more established sensory modalities such as vision and touch. Here, we use unsupervised learning of a deep neural network imposed with biological constraints to reproduce coding properties of proprioceptive neurons in area 2 of primary somatosensory cortex. With this model, we demonstrate that the tendency for area 2 neurons in close physical proximity to share similar directional tuning can be explained by local topographic organisation driven by Mexican hat lateral effects, a phenomenon that is otherwise unobservable with the spatial resolution of available electrode microarray recordings. This provides, to the best of our knowledge, the first evidence of local topographic organisation in area 2 proprioceptive neurons. We also predict that the structure of proprioceptive receptive fields are typically multi-joint rather than single-joint in nature and provide, to the best of our knowledge, and find that our model best reproduces the tuning properties of neural data when training on natural kinematic recordings, rather than those from a stereotyped task, underlining the importance of training on data that reflect the natural distribution of sensory stimuli.

neuroscience↗

bioRxiv2019

Diverse muscle spindle firing properties emerge from multiscale muscle mechanics

AO_SCPLOWBSTRACTC_SCPLOWDespite decades of research, we lack a mechanistic framework capable of predicting how movement-related signals are transformed into the diversity of muscle spindle afferent firing patterns observed experimentally, particularly in naturalistic behaviors. Here, a biophysical model demonstrates that well-known firing characteristics of muscle spindle Ia afferents - including dependence on movement history, and nonlinear scaling with muscle stretch velocity - emerge from first principles of muscle contractile mechanics. Further, mechanical interactions of the muscle spindle with muscle-tendon dynamics reveal how motor commands to the muscle (alpha drive) versus muscle spindle (gamma drive) can cause highly variable and complex activity during active muscle contraction and muscle stretch that defy simple explanation. Depending on the neuromechanical conditions, the muscle spindle model output appears to "encode" aspects of muscle force, yank, length, stiffness, velocity, and/or acceleration, providing an extendable, multiscale, biophysical framework for understanding and predicting proprioceptive sensory signals in health and disease.

neuroscience↗

bioRxiv2018

Noncontractile tissue forces mask muscle fiber forces underlying muscle spindle Ia afferent firing rates in stretch of relaxed rat muscle

Stretches of relaxed cat and rat muscle elicit similar history-dependent muscle spindle Ia firing rates that resemble history-dependent forces seen in single activated muscle fibers (Nichols and Cope, 2004). During stretch of relaxed cat muscle, whole musculotendon forces exhibit history-dependence that mirror history-dependent muscle spindle firing rates, where both muscle force and muscle spindle firing rates are elevated in the first stretch in a series of stretch-shorten cycles (Blum et al., 2017). By contrast, rat musculotendon are only mildly history-dependent and do not mirror history-dependent muscle spindle firing rates in the same way (Haftel et al., 2004). We hypothesized that history-dependent muscle spindle firing rates elicited in stretch of relaxed rat muscle would mirror history-dependent muscle fiber forces, which are masked by noncontractile tissue at the level of whole musculotendon force. We removed noncontractile tissue force contributions from the recorded musculotendon force using an exponentially-elastic tissue model. We then show that the remaining estimated muscle fiber force resembles history-dependent muscle spindle firing rates recorded simultaneously. These forces also resemble history-dependent forces recorded in stretch of single activated fibers and attributed to muscle cross-bridge mechanisms (Campbell and Moss, 2000). Our results suggest that history-dependent muscle spindle firing in both rats and cats arise from stretch of cross-bridges in muscle fibers.

neuroscience↗