Response Patterns in Second Somatosensory Cortex (SII) of Awake Monkeys to Passively Applied Tactile Gratings

2000 ◽  
Vol 84 (2) ◽  
pp. 780-797 ◽  
Author(s):  
J. R. Pruett ◽  
R. J. Sinclair ◽  
H. Burton
Keyword(s):  
Somatosensory Cortex ◽  
Hand Movement ◽  
Scanning Speed ◽  
Random Force ◽  
Groove Width ◽  
Hand Position ◽  
Sample Population ◽  
Firing Rates ◽  
Passive Touch ◽  
Movement Parameters

This experiment explored the effects of controlled manipulations of three parameters of tactile gratings, groove width (1.07–2.53 mm), contact force (30–90 g), and scanning speed (40–120 mm/s), on the responses of cells in second somatosensory cortex (SII) of awake monkeys that were performing a groove-width classification task with passively presented stimuli. A previous experiment involving an active touch paradigm demonstrated that macaque SII cells code groove-width and hand-movement parameters in their average firing rates. The present study used a passive-touch protocol to remove somatosensory activation related to hand movements that accompany haptic exploration of surfaces. Monkeys maintained a constant hand position while a robotic device delivered stimulation with tactile gratings to a single stabilized finger pad. Single-unit recordings isolated 216 neurons that were retrospectively assigned to SII on histological criteria. Firing patterns for 86 of these SII cells were characterized in detail, while monkeys classified gratings as rough (1.90 and 2.53 mm groove widths) or smooth (1.07 and 1.42 mm groove widths), with trial-wise random, parametric manipulation of force or speed; the monkeys compared 1.07 versus 1.90 mm and 1.42 versus 2.53 mm in alternating blocks of trials. We studied 33 cells with systematic variation of groove width and force, 49 with groove width and speed, and four with all three variables. Sixty-three cells were sensitive to groove width, 43 to force (effects of random force in speed experiments contributed to N), and 34 to speed. Relatively equal numbers of cells changed mean firing rates as positive or negative functions of increasing groove width, force, and/or speed. Cells typically changed mean firing rates for two or three of the independent variables. Effects of groove width, force, and speed were additive or interactive. The variety of response functions was similar to that found in a prior study of primary somatosensory cortex (SI) that used passive touch. The SII sample population showed correlated changes (both positive and negative) in firing rates with increasing groove width and force and to a lesser degree, with increasing groove width and speed. This correlation is consistent with human psychophysical studies that found increasing groove width and force increase perceived roughness magnitude, and it strengthens the argument for SII's direct involvement in roughness perception.

Neural Correlates for Roughness Choice in Monkey Second Somatosensory Cortex (SII)

2001 ◽  
Vol 86 (4) ◽  
pp. 2069-2080 ◽  
Author(s):  
J. R. Pruett ◽  
R. J. Sinclair ◽  
H. Burton
Keyword(s):  
Somatosensory Cortex ◽  
Three Dimensional ◽  
Scanning Speed ◽  
Classification Performance ◽  
Groove Width ◽  
Neural Firing ◽  
Negative Effects ◽  
Firing Rates ◽  
Wide Groove ◽  
Roughness Classification

This experiment explored the relationship between neural firing patterns in second somatosensory cortex (SII) and decisions about roughness of tactile gratings. Neural and behavioral data were acquired while monkeys made dichotomous roughness classifications of pairs of gratings that differed in groove width (1.07 vs. 1.90 and 1.42 vs. 2.53 mm). A computer-controlled device delivered the gratings to a single immobilized finger pad. In one set of experiments, three levels of contact force (30, 60, and 90 g) were assigned to these gratings at random. In another set of experiments, three levels of scanning speed (40, 80, and 120 mm/s) were assigned to these gratings at random. Groove width was the intended variable for roughness. Force variation disrupted the monkeys' groove-width (roughness) classifications more than did speed variation. A sample of 32 SII cells showed correlated changes in firing (positive or negative effects of both variables) when groove width and force increased. While these cells were recorded, the monkeys made roughness classification errors, confusing wide groove-width gratings at low force with narrow groove-width gratings at high force. Three-dimensional plots show how some combinations of groove width and force perturbed the monkeys' trial-wise classifications of grating roughness. Psychometric functions show that errors occurred when firing rates failed to distinguish gratings. A possible interpretation is that when asked to classify grating roughness, the monkeys based classifications on the firing rates of a subset of roughness-sensitive cells in SII. Results support human psychophysical data and extend the roughness range of a model of the effects of groove width and force on roughness. One monkey's SII neural sample (21 cells) showed significant correlation between firing rate response functions for groove width and speed (both correlations either positive or negative). Only that monkey showed a statistically significant interaction between groove width and speed on roughness classification performance. This additional finding adds weight to the argument that SII cell firing rates influenced monkey roughness classifications.

Differential effects of the mode of touch, active and passive, on experience-driven plasticity in the S1 cutaneous digit representation of adult macaque monkeys

2020 ◽  
Vol 123 (3) ◽  
pp. 1072-1089
Author(s):  
Anita Cybulska-Klosowicz ◽  
François Tremblay ◽  
Wan Jiang ◽  
Stéphanie Bourgeon ◽  
El-Mehdi Meftah ◽  
...  
Keyword(s):  
Receptive Field ◽  
Somatosensory Cortex ◽  
Discrimination Task ◽  
Receptive Fields ◽  
Active Touch ◽  
Primary Somatosensory Cortex ◽  
Firing Rates ◽  
Passive Touch ◽  
Passive Exposure ◽  
Area 3B

This study compared the receptive field (RF) properties and firing rates of neurons in the cutaneous hand representation of primary somatosensory cortex (areas 3b, 1, and 2) of 9 awake, adult macaques that were intensively trained in a texture discrimination task using active touch (fingertips scanned over the surfaces using a single voluntary movement), passive touch (surfaces displaced under the immobile fingertips), or both active and passive touch. Two control monkeys received passive exposure to the same textures in the context of a visual discrimination task. Training and recording extended over 1–2 yr per animal. All neurons had a cutaneous receptive field (RF) that included the tips of the stimulated digits (D3 and/or D4). In area 3b, RFs were largest in monkeys trained with active touch, smallest in those trained with passive touch, and intermediate in those trained with both; i.e., the mode of touch differentially modified the cortical representation of the stimulated fingers. The same trends were seen in areas 1 and 2, but the changes were not significant, possibly because a second experience-driven influence was seen in areas 1 and 2, but not in area 3b: smaller RFs with passive exposure to irrelevant tactile inputs compared with recordings from one naive hemisphere. We suggest that added feedback during active touch and higher cortical firing rates were responsible for the larger RFs with behavioral training; this influence was tempered by periods of more restricted sensory feedback during passive touch training in the active + passive monkeys. NEW & NOTEWORTHY We studied experience-dependent sensory cortical plasticity in relation to tactile discrimination of texture using active and/or passive touch. We showed that neuronal receptive fields in primary somatosensory cortex, especially area 3b, are largest in monkeys trained with active touch, smallest in those trained with passive touch, and intermediate in those trained using both modes of touch. Prolonged, irrelevant tactile input had the opposite influence in areas 1 and 2, favoring smaller receptive fields.

Influence of age and movement complexity on kinematic hand movement parameters in childhood and adolescence

2008 ◽  
Vol 26 (7) ◽  
pp. 655-663 ◽  
Author(s):  
Stefan Mark Rueckriegel ◽  
Friederike Blankenburg ◽  
Roland Burghardt ◽  
Stefan Ehrlich ◽  
Günter Henze ◽  
...  
Keyword(s):  
Hand Movement ◽  
Childhood And Adolescence ◽  
Movement Complexity ◽  
Movement Parameters

Role of Primary Somatosensory Cortex in Active and Passive Touch

1996 ◽  
pp. 329-347 ◽  
Author(s):  
C. Elaine Chapman ◽  
François Tremblay ◽  
Stacey A. Ageranioti-Bélanger
Keyword(s):  
Somatosensory Cortex ◽  
Primary Somatosensory Cortex ◽  
Passive Touch

Dynamical Organization of Directional Tuning in the Primate Premotor and Primary Motor Cortex

2003 ◽  
Vol 89 (2) ◽  
pp. 1136-1142 ◽  
Author(s):  
Yoram Ben-Shaul ◽  
Eran Stark ◽  
Itay Asher ◽  
Rotem Drori ◽  
Zoltan Nadasdy ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Hand Movement ◽  
Movement Direction ◽  
Cortical Surface ◽  
Preferred Direction ◽  
Preparation Period ◽  
Direction Of Movement ◽  
The Mean ◽  
Movement Parameters

Although previous studies have shown that activity of neurons in the motor cortex is related to various movement parameters, including the direction of movement, the spatial pattern by which these parameters are represented is still unresolved. The current work was designed to study the pattern of representation of the preferred direction (PD) of hand movement over the cortical surface. By studying pairwise PD differences, and by applying a novel implementation of the circular variance during preparation and movement periods in the context of a center-out task, we demonstrate a nonrandom distribution of PDs over the premotor and motor cortical surface of two monkeys. Our analysis shows that, whereas PDs of units recorded by nonadjacent electrodes are not more similar than expected by chance, PDs of units recorded by adjacent electrodes are. PDs of units recorded by a single electrode display the greatest similarity. Comparison of PD distributions during preparation and movement reveals that PDs of nearby units tend to be more similar during the preparation period. However, even for pairs of units recorded by a single electrode, the mean PD difference is typically large (45° and 75° during preparation and movement, respectively), so that a strictly modular representation of hand movement direction over the cortical surface is not supported by our data.

scholarly journals Functional Roles of Saccades for a Hand Movement

2020 ◽  
Vol 10 (9) ◽  
pp. 3066 ◽  
Author(s):  
Yuki Sakazume ◽  
Sho Furubayashi ◽  
Eizo Miyashita
Keyword(s):  
Visual Information ◽  
Late Phase ◽  
Hand Movement ◽  
Positional Information ◽  
Minimum Variance ◽  
Target Point ◽  
Hand Position ◽  
Movement Trajectory ◽  
Functional Roles ◽  
Feedforward Controller

An eye saccade provides appropriate visual information for motor control. The present study was aimed to reveal the role of saccades in hand movements. Two types of movements, i.e., hitting and circle-drawing movements, were adopted, and saccades during the movements were classified as either a leading saccade (LS) or catching saccade (CS) depending on the relative gaze position of the saccade to the hand position. The ratio of types of the saccades during the movements was heavily dependent on the skillfulness of the subjects. In the late phase of the movements in a less skillful subject, CS tended to occur in less precise movements, and precision of the movement tended to be improved in the subsequent movement in the hitting. While LS directing gaze to a target point was observed in both types of the movements regardless of skillfulness of the subjects, LS in between a start point and a target point, which led gaze to a local minimum variance point on a hand movement trajectory, was exclusively found in the drawing in a less skillful subject. These results suggest that LS and some types of CS may provide positional information of via-points in addition to a target point and visual information to improve precision of a feedforward controller in the brain, respectively.

Reaching-related Neurons in Superior Parietal Area 5: Influence of the Target Visibility

2016 ◽  
Vol 28 (11) ◽  
pp. 1828-1837 ◽  
Author(s):  
Emiliano Brunamonti ◽  
Aldo Genovesio ◽  
Pierpaolo Pani ◽  
Roberto Caminiti ◽  
Stefano Ferraina
Keyword(s):  
Visual Information ◽  
Posterior Parietal Cortex ◽  
Hand Movement ◽  
Visual Signals ◽  
Hand Position ◽  
Movement Initiation ◽  
Starting Position ◽  
Area 5 ◽  
Posterior Parietal ◽  
Target Visibility

Reaching movements require the integration of both somatic and visual information. These signals can have different relevance, depending on whether reaches are performed toward visual or memorized targets. We tested the hypothesis that under such conditions, therefore depending on target visibility, posterior parietal neurons integrate differently somatic and visual signals. Monkeys were trained to execute both types of reaches from different hand resting positions and in total darkness. Neural activity was recorded in Area 5 (PE) and analyzed by focusing on the preparatory epoch, that is, before movement initiation. Many neurons were influenced by the initial hand position, and most of them were further modulated by the target visibility. For the same starting position, we found a prevalence of neurons with activity that differed depending on whether hand movement was performed toward memorized or visual targets. This result suggests that posterior parietal cortex integrates available signals in a flexible way based on contextual demands.

scholarly journals Short-term depression and long-term plasticity together tune sensitive range of synaptic plasticity

2019 ◽  
Author(s):  
Nicolas Deperrois ◽  
Michael Graupner
Keyword(s):  
Synaptic Plasticity ◽  
Firing Rate ◽  
Somatosensory Cortex ◽  
Calcium Transients ◽  
Synaptic Efficacy ◽  
Short Term ◽  
Firing Rates ◽  
Short And Long Term ◽  
Activity Dependent

AbstractSynaptic efficacy is subjected to activity-dependent changes on short- and long time scales. While short-term changes decay over minutes, long-term modifications last from hours up to a lifetime and are thought to constitute the basis of learning and memory. Both plasticity mechanisms have been studied extensively but how their interaction shapes synaptic dynamics is little known. To investigate how both short- and long-term plasticity together control the induction of synaptic depression and potentiation, we used numerical simulations and mathematical analysis of a calcium-based model, where pre- and postsynaptic activity induces calcium transients driving synaptic long-term plasticity. We found that the model implementing known synaptic short-term dynamics in the calcium transients can be successfully fitted to long-term plasticity data obtained in visual- and somatosensory cortex. Interestingly, the impact of spike-timing and firing rate changes on plasticity occurs in the prevalent firing rate range, which is different in both cortical areas considered here. Our findings suggest that short- and long-term plasticity are together tuned to adapt plasticity to area-specific activity statistics such as firing rates.Author summarySynaptic long-term plasticity, the long-lasting change in efficacy of connections between neurons, is believed to underlie learning and memory. Synapses furthermore change their efficacy reversibly in an activity-dependent manner on the subsecond time scale, referred to as short-term plasticity. It is not known how both synaptic plasticity mechanisms – long- and short-term – interact during activity epochs. To address this question, we used a biologically-inspired plasticity model in which calcium drives changes in synaptic efficacy. We applied the model to plasticity data from visual- and somatosensory cortex and found that synaptic changes occur in very different firing rate ranges, which correspond to the prevalent firing rates in both structures. Our results suggest that short- and long-term plasticity act in a well concerted fashion.

scholarly journals Using Nonlinear Dynamics of EEG Signals to Decode Hand Movement Directions Under Bimanual Movement

2021 ◽  
Author(s):  
Jiarong Wang ◽  
Luzheng Bi ◽  
Weijie Fei
Keyword(s):  
Nonlinear Dynamics ◽  
Hand Movement ◽  
Movement Direction ◽  
Bimanual Movement ◽  
Eeg Signals ◽  
Linear Discriminant ◽  
Computer Interfaces ◽  
Opposite Hand ◽  
Movement Parameters ◽  
Human Augmentation

Abstract Background: Decoding hand movement parameters from electroencephalograms (EEG) signals can provide intuitive control for brain-computer interfaces (BCIs). However, most existing studies of EEG-based hand movement decoding are focused on single hand movement. Since the both-hand movement is common in human augmentation systems, to address the decoding of hand movement under the opposite hand movement, we investigate the neural signatures and decoding of the primary hand movement direction from EEG signals under the opposite hand movement. Methods: The decoding model was developed by using an echo state network (ESN) to extract nonlinear dynamics parameters of movement-related cortical potentials (MRCPs) as decoding features and linear discriminant analysis as a classifier. Results: Significant differences in MRCPs between movement conditions with and without an opposite hand movement were found. Furthermore, using the ESN-based models, the decoding accuracies reached 86.03± 7.32% and 88.45± 6.16% under the conditions without and with the opposite hand movement, 20 respectively. Conclusions: These findings showed that the proposed method performed well in decoding the primary hand movement directions under the conditions with and without the opposite hand movement. This study may open a new avenue to decode hand movement parameters from EEG signals and lay a foundation for the future development of BCI-based human augmentation systems.

Neuronal activity in the primary somatosensory cortex in monkeys (Macaca mulatta) during active touch of textured surface gratings: responses to groove width, applied force, and velocity of motion

1991 ◽  
Vol 66 (1) ◽  
pp. 153-169 ◽  
Author(s):  
R. J. Sinclair ◽  
H. Burton
Keyword(s):  
Somatosensory Cortex ◽  
Macaca Mulatta ◽  
Small Sample ◽  
Active Touch ◽  
Applied Force ◽  
Groove Width ◽  
Primary Somatosensory Cortex ◽  
Textured Surface ◽  
Response Patterns ◽  
Force Level

1. In a descriptive survey of primary somatosensory cortex (SI) responses during active touch, two monkeys (Macaca mulatta) were trained to stroke their fingertips over pairs of gratings with constant ridge (250 microns) and varying groove (500-2,900 microns) width (roughness) and to identify the smoother (smaller groove). Speed of hand motion and applied force level during the stroke were monitored and recorded. Transdural single-unit recordings were obtained from areas 3b and 1 of SI while animals performed the task. 2. The statistical sample consisted of 164 single units. Most cells in the sample responded in some fashion during the stroke, including brief increased or decreased activity to 1-mm ridges (touch strips) placed between surface pairs and at ends of each block to serve as touch sensors. These peristroke response patterns were described briefly. Most cells (153/164) responded to grating contact. Three types of responses to groove width were characterized. 1) Response was proportional to groove width in many cells. There was a vigorous response to roughest and none to smoothest surface. Mean firing rates for these cells appeared linearly related to groove width. 2) Graded responses were seen with smaller response differences to the same groove width range as in 1. Responses of some cells of types 1 and 2 were uncorrelated with variations in applied force and velocity of stroke. 3) There were inverse responses to groove width. Greater responses occurred during contact with smoother surfaces. 3. Many cells were influenced by a combination of changes in groove width, force, and/or velocity. Activity of a small sample of cells in area 1 with slowly adapting (SA) response properties was an almost exclusive positive function of variations in force level. Unlike SAs in 3b, responses of these cells were uncorrelated with alterations in groove width or stroke velocity. Velocity effects were almost always associated with response to groove width. Positive velocity cells coded temporal period. Significant velocity effects were not evident in graded or inverse graded cells. Negative force and velocity effects were due to shifts in behavioral strategy. Periodicity related to the spatial period of the grating was found in autocorrelograms of a small number of cells. Finally, responses of some cells were unaffected by changes in groove width, force, or velocity. Some of these were affected by contact with touch strips. Others responded in undifferentiated fashion to the stroke, and their function remains unresolved. Overall, there was a continuum of response patterns. Subgroups of cells were not distinct.(ABSTRACT TRUNCATED AT 400 WORDS)

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