scholarly journals A dynamical model for generating synthetic data to quantify active tactile sensing behavior in the rat

2021 ◽  
Vol 118 (27) ◽  
pp. e2011905118
Author(s):  
Nadina O. Zweifel ◽  
Nicholas E. Bush ◽  
Ian Abraham ◽  
Todd D. Murphey ◽  
Mitra J. Z. Hartmann
Keyword(s):  
Synthetic Data ◽  
Sensory Information ◽  
Principal Component ◽  
Dynamic Responses ◽  
Natural Environments ◽  
Tactile Information ◽  
Sensorimotor Processing ◽  
Input Signals ◽  
Geometry Simulation ◽  
The Brain

As it becomes possible to simulate increasingly complex neural networks, it becomes correspondingly important to model the sensory information that animals actively acquire: the biomechanics of sensory acquisition directly determines the sensory input and therefore neural processing. Here, we exploit the tractable mechanics of the well-studied rodent vibrissal (“whisker”) system to present a model that can simulate the signals acquired by a full sensor array actively sampling the environment. Rodents actively “whisk” ∼60 vibrissae (whiskers) to obtain tactile information, and this system is therefore ideal to study closed-loop sensorimotor processing. The simulation framework presented here, WHISKiT Physics, incorporates realistic morphology of the rat whisker array to predict the time-varying mechanical signals generated at each whisker base during sensory acquisition. Single-whisker dynamics were optimized based on experimental data and then validated against free tip oscillations and dynamic responses to collisions. The model is then extrapolated to include all whiskers in the array, incorporating each whisker’s individual geometry. Simulation examples in laboratory and natural environments demonstrate that WHISKiT Physics can predict input signals during various behaviors, currently impossible in the biological animal. In one exemplary use of the model, the results suggest that active whisking increases in-plane whisker bending compared to passive stimulation and that principal component analysis can reveal the relative contributions of whisker identity and mechanics at each whisker base to the vibrissotactile response. These results highlight how interactions between array morphology and individual whisker geometry and dynamics shape the signals that the brain must process.

Modulation of Dorsal Spinocerebellar Responses to Limb Movement. I. Effect of Serotonin

2003 ◽  
Vol 90 (5) ◽  
pp. 3361-3371 ◽  
Author(s):  
G. Bosco ◽  
A. Rankin ◽  
R. E. Poppele
Keyword(s):  
Brain Stem ◽  
Sensory Information ◽  
Principal Component ◽  
Kinematic Parameters ◽  
Axis Orientation ◽  
Lower Trunk ◽  
Spinal Circuitry ◽  
Before And After ◽  
Different Response ◽  
The Brain

Spinocerebellar neurons (DSCT) receive converging sensory information from various sensory receptors in the hindlimbs and lower trunk. Previous studies have shown that sensory processing by DSCT neurons results in a representation of global hindlimb kinematic parameters such as the length and the orientation of the limb axis. In addition to the sensory input, the DSCT circuitry also receives a descending input from the raphe nuclei in the brain stem. Recent studies have demonstrated that the raphe serotonergic terminals synapse directly on DSCT neurons and exert a differential modulatory influence on their sensory inputs. We examined the role of serotonergic modulation on the DSCT representation of hindlimb kinematic parameters by recording DSCT activity during passive hindlimb movements before and after perturbing serotonergic transmission. We used two types of perturbation: electrical stimulation of the raphe areas in the brain stem to release serotonin in the spinal cord (42 neurons) and intravenous administration of serotonergic agonists or antagonists, mostly the 5HTP2 antagonist ketanserin (30 neurons). We found that movement responses were altered in ∼70% of the DSCT units studied with each protocol. Changes could include shifts in mean firing rate, increases or decreases in response amplitude, and changes in response waveform. We used a principal component analysis (PCA) to examine waveform components and to determine how they contributed to the response waveform changes caused by serotonin perturbation. Such changes could be explained by new or different response components that might indicate a modification in the data processing or by a different weighting of existing components that might indicate a modification of synaptic weighting. The results were consistent with the second alternative. We found that the same underlying response components could account for both control responses and those altered by serotonin perturbations. The observed changes in waveform could be entirely accounted for by a re-weighting of response components. In particular, the changes observed after raphe stimulation could be accounted for by selective changes in the weighting of the first principal component (PC) with only minor changes of the weighting of the second PC. Because these response components were shown previously to correlate with the limb axis orientation and length trajectories respectively, the finding is consistent with the idea that limb axis length and orientation information are processed separately within the spinal circuitry.

scholarly journals Saccadic suppression as a perceptual consequence of efficient sensorimotor estimation

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Frédéric Crevecoeur ◽  
Konrad P Kording
Keyword(s):  
Visual Information ◽  
Movement Time ◽  
Sensory Information ◽  
Saccadic Eye Movements ◽  
Saccadic Suppression ◽  
Bayesian Estimator ◽  
Sensorimotor Processing ◽  
Visual Hierarchy ◽  
And Control ◽  
The Brain

Humans perform saccadic eye movements two to three times per second. When doing so, the nervous system strongly suppresses sensory feedback for extended periods of time in comparison to movement time. Why does the brain discard so much visual information? Here we suggest that perceptual suppression may arise from efficient sensorimotor computations, assuming that perception and control are fundamentally linked. More precisely, we show theoretically that a Bayesian estimator should reduce the weight of sensory information around the time of saccades, as a result of signal dependent noise and of sensorimotor delays. Such reduction parallels the behavioral suppression occurring prior to and during saccades, and the reduction in neural responses to visual stimuli observed across the visual hierarchy. We suggest that saccadic suppression originates from efficient sensorimotor processing, indicating that the brain shares neural resources for perception and control.

scholarly journals Saccadic suppression as a perceptual consequence of efficient sensorimotor estimation

2017 ◽  
Author(s):  
F. Crevecoeur ◽  
K. P. Kording
Keyword(s):  
Visual Information ◽  
Movement Time ◽  
Sensory Information ◽  
Saccadic Eye Movements ◽  
Saccadic Suppression ◽  
Bayesian Estimator ◽  
Sensorimotor Processing ◽  
Visual Hierarchy ◽  
And Control ◽  
The Brain

AbstractHumans perform saccadic eye movements two to three times per second. When doing so, the nervous system strongly suppresses sensory feedback for extended periods of time in comparison with the movement time. Why does the brain discard so much visual information? Here we suggest that perceptual suppression may arise from efficient sensorimotor computations, assuming that perception and control are fundamentally linked. More precisely, we show that a Bayesian estimator should reduce the weight of sensory information around the time of saccades, as a result of signal dependent noise and of sensorimotor delays. Such reduction parallels the behavioral suppression occurring prior to and during saccades, and the reduction in neural responses to visual stimuli observed across the visual hierarchy. We suggest that saccadic suppression originates from efficient sensorimotor processing, indicating that the brain shares neural resources for perception and control.

scholarly journals Modulation of tactile feedback for the execution of dexterous movement

2021 ◽  
Author(s):  
James M Conner ◽  
Andrew Bohannon ◽  
Masakazu Igarashi ◽  
James Taniguchi ◽  
Nicholas Baltar ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Molecular Genetic ◽  
Sensory Information ◽  
Tactile Feedback ◽  
Inhibitory Neurons ◽  
Tactile Information ◽  
Inhibitory Circuits ◽  
Complementary Pattern ◽  
Local Circuits ◽  
The Brain

While dexterity relies on the constant transmission of sensory information, unchecked feedback can be disruptive to behavior. Yet how somatosensory feedback from the hands is regulated as it first enters the brain, and whether this modulation exerts any influence on movement, remain unclear. Leveraging molecular-genetic access in mice, we find that tactile afferents from the hand recruit neurons in the brainstem cuneate nucleus whose activity is modulated by distinct classes of local inhibitory neurons. Selective manipulation of these inhibitory circuits can suppress or enhance the transmission of tactile information, affecting behaviors that rely on movement of the hands. Investigating whether these local circuits are subject to top-down control, we identify distinct descending cortical pathways that innervate cuneate in a complementary pattern. Somatosensory cortical neurons target the core tactile region of cuneate, while a large rostral cortical population drives feed-forward inhibition of tactile transmission through an inhibitory shell. These findings identify a circuit basis for tactile feedback modulation, enabling the effective execution of dexterous movement.

scholarly journals Human Ability to Discriminate Direction of Three-Dimensional Force Stimuli Applied to the Finger Pad

2011 ◽  
Vol 105 (2) ◽  
pp. 541-547 ◽  
Author(s):  
Alessandro Panarese ◽  
Benoni B. Edin
Keyword(s):  
Three Dimensional ◽  
Sensory Information ◽  
Skin Surface ◽  
Tactile Information ◽  
Discrimination Ability ◽  
Human Ability ◽  
The Brain ◽  
Fingertip Forces ◽  
Finger Pad ◽  
Volar Surface

Sensory information from tactile mechanoreceptors located in the glabrous skin of the hand is crucial for skillful object exploration and manipulation. These mechanoreceptors reliably encode the direction of fingertip forces, and the brain certainly relies on this information in both sensorimotor and cognitive tasks. In this study, we examined human ability to discriminate the direction of force stimuli applied to the volar surface of the index fingertip on the basis of tactile information only. We show that humans can discriminate three-dimensional (3D) force stimuli whose directions differ by an angle as small as 7.1° in the plane tangential to the skin surface. Moreover, we found that the discrimination ability was mainly affected by the time-varying phases of the stimulus, because adding a static plateau phase to the stimulus improved the discrimination threshold only to a limited extent.

Relation Between Level of Prefrontal Activity and Subject's Performance

1999 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Laurence Casini ◽  
Françoise Macar ◽  
Marie-Hélène Giard
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Practice Phase ◽  
Trained Subjects ◽  
Anagram Task ◽  
Economic Information ◽  
Long Duration ◽  
Level Of Activity ◽  
The Brain ◽  
Processing Mechanism

Abstract The experiment reported here was aimed at determining whether the level of brain activity can be related to performance in trained subjects. Two tasks were compared: a temporal and a linguistic task. An array of four letters appeared on a screen. In the temporal task, subjects had to decide whether the letters remained on the screen for a short or a long duration as learned in a practice phase. In the linguistic task, they had to determine whether the four letters could form a word or not (anagram task). These tasks allowed us to compare the level of brain activity obtained in correct and incorrect responses. The current density measures recorded over prefrontal areas showed a relationship between the performance and the level of activity in the temporal task only. The level of activity obtained with correct responses was lower than that obtained with incorrect responses. This suggests that a good temporal performance could be the result of an efficacious, but economic, information-processing mechanism in the brain. In addition, the absence of this relation in the anagram task results in the question of whether this relation is specific to the processing of sensory information only.

Measuring the World

2018 ◽  
Author(s):  
Ann-Sophie Barwich
Keyword(s):  
Sensory Information ◽  
Network Models ◽  
Model System ◽  
Stimulus Input ◽  
Expectancy Effects ◽  
Neural Network Models ◽  
Perceptual Object ◽  
External Objects ◽  
The Common ◽  
The Brain

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes.

scholarly journals Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

2021 ◽  
Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Mri ◽  
Similarity Measures ◽  
Principal Component ◽  
Brain Anatomy ◽  
Morphological Operations ◽  
Mr Images ◽  
Tilt Correction ◽  
Brain Mr Images ◽  
The Brain

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

scholarly journals Distress Regulates Different Pathways in the Brain of Common Carp: A Preliminary Study

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 585
Author(s):  
Alexander Burren ◽  
Constanze Pietsch
Keyword(s):  
Gene Regulation ◽  
Common Carp ◽  
Binding Protein ◽  
Principal Component ◽  
Brain Regions ◽  
Point Estimation ◽  
Early Gene ◽  
Important Species ◽  
Preliminary Study ◽  
The Brain

In this study, a stress trial was conducted with common carp, one of the most important species in aquaculture worldwide, to identify relevant gene regulation pathways in different areas of the brain. Acute distress due to exposure to air significantly activated the expression of the immediate early gene c-fos in the telencephalon. In addition, evidence for regulation of the two corticotropin-releasing factor (crf) genes in relation to their binding protein (corticotropin-releasing hormone-binding protein, crh-bp) is presented in this preliminary study. Inferences on the effects of due to exposure to air were obtained by using point estimation, which allows the prediction of a single value. This constitutes the best description to date of the previously generally unknown effects of stress in different brain regions in carp. Furthermore, principal component analyses were performed to reveal possible regulation patterns in the different regions of the fish brain. In conclusion, these preliminary studies on gene regulation in the carp brain that has been influenced by exposure to a stressor reveal that a number of genes may be successfully used as markers for exposure to unfavourable conditions.

scholarly journals The emulation theory of representation: Motor control, imagery, and perception

2004 ◽  
Vol 27 (3) ◽  
pp. 377-396 ◽  
Author(s):  
Rick Grush
Keyword(s):  
Motor Control ◽  
Sensory Feedback ◽  
Sensory Input ◽  
Neural Circuits ◽  
Sensory Information ◽  
The Body ◽  
Feedback Delay ◽  
Run Off ◽  
Effects Of Feedback ◽  
The Brain

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.

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