Morphological Neural Computation Restores Discrimination of Naturalistic Textures in Trans-radial Amputees.
Ontology highlight
ABSTRACT:
SUBMITTER: Mazzoni A
PROVIDER: S-EPMC6965126 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:AimTo examine tactile sensitivity in the leg and foot sole of below-knee amputees (diabetic n = 3, traumatic n = 1), and healthy control subjects (n = 4), and examine the association between sensation and balance.MethodVibration perception threshold (VPT; 3, 40, 250Hz) and monofilaments (MF) were used to examine vibration and light touch sensitivity on the intact limb, residual limb, and homologous locations on controls. A functional reach test was performed to assess functional balance.ResultsTactile sensitivity was lower for diabetic amputee subjects compared to age matched controls for both VPT and MF; which was expected due to presence of diabetic peripheral neuropathy. In contrast, the traumatic amputee participant showed increased sensitivity for VPT at 40Hz and 250Hz vibration in both the intact and residual limbs compared to controls. Amputees with lower tactile sensitivity had shorter reach distances compared to those with higher sensitivity.ConclusionChanges in tactile sensitivity in the residual limb of trans-tibial amputees may have implications for the interaction between the amputee and the prosthetic device. The decreased skin sensitivity observed in the residual limb of subjects with diabetes is of concern as changes in skin sensitivity may be important in 1) identification/prevention of excessive pressure and 2) for functional stability. Interestingly, we saw increased residual limb skin sensitivity in the individual with the traumatic amputation. Although not measured directly in the present study, this increase in tactile sensitivity may be related to cortical reorganisation, which is known to occur following amputation, and would support similar findings observed in upper limb amputees.
| S-EPMC5983436 | biostudies-literature
Project description:The vocal behavior of infants changes dramatically during early life. Whether or not such a change results from the growth of the body during development-as opposed to solely neural changes-has rarely been investigated. In this study of vocal development in marmoset monkeys, we tested the putative causal relationship between bodily growth and vocal development. During the first two months of life, the spontaneous vocalizations of marmosets undergo (1) a gradual disappearance of context-inappropriate call types and (2) an elongation in the duration of context-appropriate contact calls. We hypothesized that both changes are the natural consequences of lung growth and do not require any changes at the neural level. To test this idea, we first present a central pattern generator model of marmoset vocal production to demonstrate that lung growth can affect the temporal and oscillatory dynamics of neural circuits via sensory feedback from the lungs. Lung growth qualitatively shifted vocal behavior in the direction observed in real marmoset monkey vocal development. We then empirically tested this hypothesis by placing the marmoset infants in a helium-oxygen (heliox) environment in which air is much lighter. This simulated a reversal in development by decreasing the effort required to respire, thus increasing the respiration rate (as though the lungs were smaller). The heliox manipulation increased the proportions of inappropriate call types and decreased the duration of contact calls, consistent with a brief reversal of vocal development. These results suggest that bodily growth alone can play a major role in shaping the development of vocal behavior.
| S-EPMC5834215 | biostudies-literature
Project description:Previously, in Hermundstad et al., 2014, we showed that when sampling is limiting, the efficient coding principle leads to a 'variance is salience' hypothesis, and that this hypothesis accounts for visual sensitivity to binary image statistics. Here, using extensive new psychophysical data and image analysis, we show that this hypothesis accounts for visual sensitivity to a large set of grayscale image statistics at a striking level of detail, and also identify the limits of the prediction. We define a 66-dimensional space of local grayscale light-intensity correlations, and measure the relevance of each direction to natural scenes. The 'variance is salience' hypothesis predicts that two-point correlations are most salient, and predicts their relative salience. We tested these predictions in a texture-segregation task using un-natural, synthetic textures. As predicted, correlations beyond second order are not salient, and predicted thresholds for over 300 second-order correlations match psychophysical thresholds closely (median fractional error <0.13).
| S-EPMC7494356 | biostudies-literature
Project description:Muscle models and animal observations suggest that physical damping is beneficial for stabilization. Still, only a few implementations of physical damping exist in compliant robotic legged locomotion. It remains unclear how physical damping can be exploited for locomotion tasks, while its advantages as sensor-free, adaptive force- and negative work-producing actuators are promising. In a simplified numerical leg model, we studied the energy dissipation from viscous and Coulomb damping during vertical drops with ground-level perturbations. A parallel spring- damper is engaged between touch-down and mid-stance, and its damper auto-decouples from mid-stance to takeoff. Our simulations indicate that an adjustable and viscous damper is desired. In hardware we explored effective viscous damping and adjustability, and quantified the dissipated energy. We tested two mechanical, leg-mounted damping mechanisms: a commercial hydraulic damper, and a custom-made pneumatic damper. The pneumatic damper exploits a rolling diaphragm with an adjustable orifice, minimizing Coulomb damping effects while permitting adjustable resistance. Experimental results show that the leg-mounted, hydraulic damper exhibits the most effective viscous damping. Adjusting the orifice setting did not result in substantial changes of dissipated energy per drop, unlike adjusting the damping parameters in the numerical model. Consequently, we also emphasize the importance of characterizing physical dampers during real legged impacts to evaluate their effectiveness for compliant legged locomotion.
| S-EPMC7805837 | biostudies-literature
Project description:Radial frequency (RF) patterns are valuable tools for investigations of contour integration and shape discrimination. Under photopic conditions, healthy observers can detect deformations from circularity in RF patterns as small as 3 seconds of arc. Such fine discrimination may be facilitated by cortical curvature detectors or global shape-detecting mechanisms that favor a closed contour. Rods make up 95% of photoreceptors in the retina, but we know very little about how spatial information is processed by rod-mediated pathways. We measured scotopic radial deformation discrimination using both full and partly occluded RF pattern stimuli. We found radial deformation thresholds of around 2-3 minutes of arc for stimuli with a wide range of radii and RFs. When parts of the stimulus were occluded, scotopic thresholds improved up to the point that three or four cycles of modulation were visible; no further improvement occurred with the addition of more visible cycles. When only one to three cycles were visible, an increase in curvature per cycle became important, allowing observers to detect smaller deformations from circularity. Our results indicate that the scotopic radial deformation thresholds for the stimuli tested are not dependent on global circularity cues but are instead mediated by local curvature cues.
| S-EPMC6372011 | biostudies-literature
Project description:Humans are often inconsistent (irrational) when choosing among simple bundles of goods, even without any particular changes to framing or context. However, the neural computations that give rise to such inconsistencies are still unknown. Similar to sensory perception and motor output, we propose that a substantial component of inconsistent behavior is due to variability in the neural computation of value. Here, we develop a novel index that measures the severity of inconsistency of each choice, enabling us to directly trace its neural correlates. We find that the BOLD signal in the vmPFC, ACC, and PCC is correlated with the severity of inconsistency on each trial and with the subjective value of the chosen alternative. This suggests that deviations from rational choice arise in the regions responsible for value computation. We offer a computational model of how variability in value computation is a source of inconsistent choices.
| S-EPMC6450930 | biostudies-literature
Project description:Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and energetically inefficient form of communication. This contrasts sharply with biological neurons that communicate sparingly and efficiently using isomorphic binary spikes. While Spiking Neural Networks (SNNs) can be constructed by replacing the units of an ANN with spiking neurons (Cao et al., 2015; Diehl et al., 2015) to obtain reasonable performance, these SNNs use Poisson spiking mechanisms with exceedingly high firing rates compared to their biological counterparts. Here we show how spiking neurons that employ a form of neural coding can be used to construct SNNs that match high-performance ANNs and match or exceed state-of-the-art in SNNs on important benchmarks, while requiring firing rates compatible with biological findings. For this, we use spike-based coding based on the firing rate limiting adaptation phenomenon observed in biological spiking neurons. This phenomenon can be captured in fast adapting spiking neuron models, for which we derive the effective transfer function. Neural units in ANNs trained with this transfer function can be substituted directly with adaptive spiking neurons, and the resulting Adaptive SNNs (AdSNNs) can carry out competitive classification in deep neural networks without further modifications. Adaptive spike-based coding additionally allows for the dynamic control of neural coding precision: we show empirically how a simple model of arousal in AdSNNs further halves the average required firing rate and this notion naturally extends to other forms of attention as studied in neuroscience. AdSNNs thus hold promise as a novel and sparsely active model for neural computation that naturally fits to temporally continuous and asynchronous applications.
| S-EPMC6332470 | biostudies-literature
Project description:Neuronal activity in the brain is variable, yet both perception and behavior are generally reliable. How does the brain achieve this? Here, we show that the conjunctive coding of multiple stimulus features, commonly known as nonlinear mixed selectivity, may be used by the brain to support reliable information transmission using unreliable neurons. Nonlinearly mixed feature representations have been observed throughout primary sensory, decision-making, and motor brain areas. In these areas, different features are almost always nonlinearly mixed to some degree, rather than represented separately or with only additive (linear) mixing, which we refer to as pure selectivity. Mixed selectivity has been previously shown to support flexible linear decoding for complex behavioral tasks. Here, we show that it has another important benefit: in many cases, it makes orders of magnitude fewer decoding errors than pure selectivity even when both forms of selectivity use the same number of spikes. This benefit holds for sensory, motor, and more abstract, cognitive representations. Further, we show experimental evidence that mixed selectivity exists in the brain even when it does not enable behaviorally useful linear decoding. This suggests that nonlinear mixed selectivity may be a general coding scheme exploited by the brain for reliable and efficient neural computation.
| S-EPMC7048320 | biostudies-literature
Project description:Human observers can rapidly perceive complex real-world scenes. Grouping visual elements into meaningful units is an integral part of this process. Yet, so far, the neural underpinnings of perceptual grouping have only been studied with simple lab stimuli. We here uncover the neural mechanisms of one important perceptual grouping cue, local parallelism. Using a new, image-computable algorithm for detecting local symmetry in line drawings and photographs, we manipulated the local parallelism content of real-world scenes. We decoded scene categories from patterns of brain activity obtained via functional magnetic resonance imaging (fMRI) in 38 human observers while they viewed the manipulated scenes. Decoding was significantly more accurate for scenes containing strong local parallelism compared to weak local parallelism in the parahippocampal place area (PPA), indicating a central role of parallelism in scene perception. To investigate the origin of the parallelism signal we performed a model-based fMRI analysis of the public BOLD5000 dataset, looking for voxels whose activation time course matches that of the locally parallel content of the 4916 photographs viewed by the participants in the experiment. We found a strong relationship with average local symmetry in visual areas V1-4, PPA, and retrosplenial cortex (RSC). Notably, the parallelism-related signal peaked first in V4, suggesting V4 as the site for extracting paralleism from the visual input. We conclude that local parallelism is a perceptual grouping cue that influences neuronal activity throughout the visual hierarchy, presumably starting at V4. Parallelism plays a key role in the representation of scene categories in PPA.
| S-EPMC8782314 | biostudies-literature
Project description:In this work, we study people's ability to discriminate between different 2D textures of walls by passive listening to a pre-recorded tongue click in an auralized echolocation scenario. In addition, the impact of artificially enhancing the early reflection magnitude by 6dB and of removing the direct component while equalizing the loudness was investigated. Listening test results for different textures, ranging from a flat wall to a staircase, were assessed using a 2 Alternative-Forced-Choice (2AFC) method, in which 14 sighted, untrained participants were indicating 2 equally perceived stimuli out of 3 presented stimuli. The average performance of the listening subjects to discriminate between different textures was found to be significantly higher for walls at 5m distance, without overlap between the reflected and direct sound, compared to the same walls at 0.8m distance. Enhancing the reflections as well as removing the direct sound were found to be beneficial to differentiate textures. This finding highlights the importance of forward masking in the discrimination process. The overall texture discriminability was found to be larger for the walls reflecting with a higher spectral coloration.
| S-EPMC8158938 | biostudies-literature