Neuronal Activity in Somatosensory Cortex of Monkeys Using a Precision Grip. II. Responses to Object Texture and Weights

Iran Salimi, Thomas Brochier, and Allan M. Smith

Centre de Recherche en Sciences Neurologiques, Département de Physiologie, Université de Montréal, Montreal, Quebec H3C 3J7, Canada


    ABSTRACT
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Abstract
Introduction
Methods
Results
References

Salimi, Iran, Thomas Brochier, and Allan M. Smith. Neuronal activity in somatosensory cortex of monkeys using a precision grip. II. Responses to object texture and weights. Three monkeys were trained to lift and hold a test object within a 12- to 25-mm position window for 1 s. The activity of single neurons was recorded during performance of the task in which both the weight and surface texture of the object were systematically varied. Whenever possible, each cell was tested with three weights (15, 65, and 115 g) and three textures (smooth metal, fine 200 grit sandpaper, and rough 60 grit sandpaper). Of 386 cells recorded in 3 monkeys, 45 cells had cutaneous receptive fields on the index or thumb or part of the thenar eminence and were held long enough to be tested in all 9 combinations of texture and weight. Recordings were made for the entire anterior-posterior extent of the thumb and index finger areas in somatosensory cortex including area 7b. However, the statistical analysis required a selection of only those cells for which nine complete recording conditions were available limiting the sample to cells in areas 2, 5, and 7b. Significant differences in the grip force accompanied 98% of the changes in texture and 78% of the changes in weight. Increasing the object weight also increased the force tangential to the skin surface as measured by the load or lifting force. The peak discharge during lifting was judged to be the most sensitive index of cell activity and was analyzed with a two-way analysis of variance (ANOVA). In addition, peak cell discharge was normalized to allow comparisons among different combinations of texture and weight as well as comparisons among different neurons. Overall, the peak firing frequency of 87% of the cells was significantly modulated by changes in object texture, but changes in object weight affected the peak activity of only 58% of the cells. Almost all (17/18, 94%) of the static cells were influenced by the object texture, and 81% of the dynamic cells that were active only briefly at grip and lift onset were modulated by texture. For some cells, surface texture had a significant effect on neuronal discharge that was independent of the object weight. In contrast, weight-related responses were never simple main effects of the weight alone and appeared instead as significant interactions between texture and weight. Four neurons either increased or decreased activity in a graded fashion with surface structure (roughness) regardless of the object weight (P < 0.05). Ten other neurons showed increases or decreases in response to one or two textures, which might represent either a graded response or a tuning preference for a specific texture. The firing frequency of the majority (31/45) of neurons reflected an interaction of both texture and weight. The cells with texture-related but weight-independent activities were thought to encode surface characteristics that are largely independent of the grip and lifting forces used to manipulate the object. Such constancies could be used to construct internal representations or mental models for planning and controlling object manipulation.


    INTRODUCTION
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Abstract
Introduction
Methods
Results
References

Johansson and Westling (1984) were the first to demonstrate that in a grasping, lifting, and holding task, subjects adjusted the grip force for both the weight and the texture of the grasped object. They also showed that local anesthesia of the finger tips disrupted the ability of subjects to adjust their grip force to different textures, although compensation for object weight was relatively unaffected. Later, Cadoret and Smith (1996) used adhesive and lubricant coatings to dissociate the effects of surface texture from friction and confirmed that friction, not texture, was the significant parameter influencing grip force.

Johansson and Westling (1987) and Westling and Johansson (1987) recorded from tactile afferents of the median nerve in a grasping task. Although the subjects responded to changes in surface friction with little tangential movement between the hand and the object, the responses of rapidly adapting afferents encoded the changes in the slip ratio (the inverse of the coefficient of friction). In a study of grip force adjustments provoked by sudden tangential force perturbations, Macefield et al. (1996) emphasized that modulation of the fast adapting afferent activity at different periods in the task seemed particularly important to match the rate of load force changes to the grip force application rate.

In the motor cortex, Picard and Smith (1992a,b) found neurons with cutaneous receptive fields that responded to a variety of different object textures and weights. These responses were thought to have arisen from direct input from the primary somatosensory cortex into motor cortex. For this reason in the present study, we attempted to investigate the effects of textures and weights on the activity of single neurons in the primary somatosensory cortex. The objective was to compare cortical activity with the discharge patterns of primary afferents to better understand how the somatosensory cortex extracts and transforms information about object texture and weight from primary afferent signals.


    METHODS
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Abstract
Introduction
Methods
Results
References

The data described here were obtained by the same procedures described in the previous paper (Salimi et al. 1999). Briefly, three adolescent Maccaca fascicularis monkeys were trained to grasp, lift, and hold an experimental object within narrow position limits. The surface of the object could be covered with different textures, and its weight could be adjusted. Single-cell activity from the postcentral somatosensensory cortex, grip and load forces, and the object displacement were digitized and stored on a laboratory computer. Whenever possible, each cell was tested with three weights (15, 65, and 115 g) and three textures (smooth metal, fine-grained sandpaper 200 grains/in., and coarse-grained sandpaper 60 grains/in.) for a total of nine combinations of texture and weight. The grit on the sandpaper surfaces was composed of cubic crystals of aluminum oxide glued to a paper background providing two distinct but relatively homogeneous textures. The finer aluminum oxide crystals measured ~130 µm per side, a dimension too small to detect the orientation of individual crystals. In contrast, the coarser grains measured ~420 µm per side, and the differences in the orientation of the crystals were detectable with the finger tip.

Blocks of ~35 trials were recorded for each condition, and the 9 conditions of texture and weight were presented in blocks but in random order. The receptive-field testing and histological verification of the recording sites were described in the previous paper (Salimi et al. 1999). Briefly, the cells were classified as dynamic units if the increase in their discharge frequency was limited to the duration of the dynamic phase of the task, whereas static neurons exhibited an increased and sustained discharge throughout both the dynamic and static phases of the task.

Data analysis

The data were analyzed by both graphic and statistical procedures. For each condition of texture and weight, averaged grip and load forces were displayed, as were trial-by-trial activity rasters and peristimulus time histograms of the activity. On each trial peak frequency, which always occurred between the onset of grip force and the time of arrival within the position window, a more sensitive measure of neuronal excitability than the activity averaged over the time of skin contact was found and was therefore selected as the principal measure of neuronal activity. For every cell, the peak frequencies from each trial were analyzed, both within and between conditions, with a two-way analysis of variance (ANOVA). Similar analyses were also applied to the peak grip and the peak load forces. A Tukey's HSD test for pair-wise comparisons was subsequently used to determine which combinations of texture and weight were significantly different (P < 0.05) from each other.

Because the average firing frequency differed from cell to cell, the mean peak firing rates in each condition were compared using a Z-score normalization. The peak activity was measured separately for all the trials in each of the nine conditions of texture and weight, and then a mean value of the cell activity was calculated in each condition. The grand mean was calculated on all the trials of the nine conditions. For a given unit the mean activity in each condition was then expressed as a standard deviation from the activity grand mean for that unit [Z = (x - -X)/SD].


    RESULTS
Top
Abstract
Introduction
Methods
Results
References

General description

As described in the companion paper (Salimi et al. 1999), a total of 386 cells modulated their discharge during grasping and lifting. However, of these, only 45 cells were held long enough to be tested in 9 different combinations of object texture and weight and were subjected to a two-way ANOVA. All of these cells had cutaneous receptive fields on the thumb or index finger in contact with the manipulandum surface. In a few cases the receptive field covered the proximal phalange of digits 1 and 2 and part of the thenar eminence or the webbing between the two digits. The locations, receptive fields, and response properties of these cells are presented in a companion paper (Salimi et al. 1999). Although we sampled the whole anterio-posterior extent of the digit area in the postcentral gyrus and part of the posterior parietal cortex (area 7b), the 45 cells having 9 test conditions were confined to areas 2, 5, and 7.

Changes in object texture or weight produced significant differences (2-way ANOVA, P < 0.05) in the applied grip force for all nine conditions (Table 1). The effect of texture was greater than the effect of weight on the normalized average peak grip force for all conditions for 45 cells (Fig. 1A). As expected, the peak grip force was highest for the smooth metal surface and lowest for coarse sandpaper, but the difference in peak grip force between the 15-g and the 115-g weight was not significant. Moreover, the changes in grip force displayed a monotonic decrease with increased roughness, but changes in weight did not show a significant monotonic relation.


                              
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Table 1. Effect of texture and weight on normalized peak discharge, peak grip force, and peak load force



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Fig. 1. Mean normalized peak grip force for all trials (A) and corresponding mean peak discharge (B) calculated for all 45 cells on the same trials as a function of both surface structure and weight during the dynamic phase of the task.

Using a similar approach, we normalized the mean peak activity within each condition to determine whether somatosensory cortical cells were generally more active with rougher textures and heavier weights. Figure 1B shows that there was no obviously biased relationship between any particular combination of texture and weight and neural activity that was common to all the cells.

Overall, the two-way ANOVAs followed by pair-wise comparison indicated that texture had a significant effect (P < 0.05) on peak discharge rate for 39/45 (87%) cells (see Table 1). This relationship was significant in 94% of the cells with static discharge patterns and 81% of the cells with dynamic discharge patterns. Changes in weight resulted in a significant modification of the discharge of 58% of the cells examined (67% of the cells with static discharge patterns and 52% of the cells with dynamic discharge patterns). However, no simple, graded relationships were found between discharge and object weight. For 31/45 (69%) of the cells, a significant interaction between texture and weight was found (Table 2) This interaction occurred almost equally among the static and dynamic cells (72 and 67%, respectively).


                              
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Table 2. Activity patterns in response to changes in texture and weight

Statistical analysis did not show any significant relationship between the recording site and the response to the changes in texture and the weight for the sample of 45 cells in this study.

Activity patterns in response to changes in object texture and weight

Although no obvious relationship was found between the size and location of the receptive fields and the activity related to texture or weight, two broad response categories emerged from the statistical analyses. These were cells with activity related to texture that were weight independent and cells with texture effects that were weight dependent. Among the cells showing weight-independent effects, some responded differently to all three textures (as shown by Tukey's HSD test); others changed in response to only one texture.

The first and most easily understood is the weight-independent group (n = 14, Table 2). In this group, four cells displayed unidirectional, graded increases or decreases in discharge frequency with each change in surface texture from smooth metal to the coarsest sandpaper. Increasing the weight had no significant effect on the discharge rate for these neurons. The responses were reproducible and unambiguous. The additional 10 weight-independent cells displayed graded increases in their activity as a function of changes in surface textures for only 2 of the 3 surface conditions tested. Again, the object weight had no effect on the discharge rate of these cells, which appeared to be selectively sensitive to specific surface textures.

Another group of 31 cells displayed a wide variety of changes in response to both texture and weight (Table 2). Although not a homogeneous category, cells showing interactions between texture and weight were the most common (31/45 or 69%).

Weight-independent texture effects

GRADED RESPONSES TO THE CHANGES IN THREE TEXTURES. Of the 45 cells showing changes in response to texture and weight, only 4 demonstrated statistically different graded responses to all 3 textures for all 3 weights. Figure 2 shows a cell for which the peak discharge frequency increased with increases in the surface irregularity. The activity was lowest with the smooth metal and increased significantly with fine sandpaper and then increased further with the change to the coarser sandpaper (Tukey's HSD, P < 0.01). The changes in grip force observed with changes in weight were smaller than those observed with changes in texture. An ANOVA showed significant activity changes for object texture but not for object weight. Note also that the activity of this cell increased as the grip force decreased, demonstrating that an increase in cell activity is not an invariable consequence of an increase in grip force and consequently increased pressure on the receptive field. Figure 3A illustrates the graded increase in peak discharge rate with increasing surface coarseness for the same cell regardless of the object weight.



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Fig. 2. Increased firing frequency of a cortical dynamic cell associated with increased surface irregularity. The thin force and displacement traces are for 15-g object weights, the medium thickness for 65-g weights, and the thickest traces for 115-g weights. The mean peak firing frequency of this cell was significantly higher with the grit size 60 sandpaper (see Fig. 3A). There is additional activity associated with object release. The increase in discharge rate was not correlated with either the object weight or grip force. The figurine of the hand in the top left shows the location of the receptive field of this cell on digit 2.



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Fig. 3. Normalized peak activities of various cells in response to lifting 3 textures and 3 weights. A: cell from Fig. 2 with a graded increase in activity as a function of surface irregularity regardless of the object weight. B: the cell shown in Fig. 4 has a graded decrease in activity as a function of surface irregularity regardless of the object weight. C: the cell from Fig. 5 increased peak frequency in an exponential manner and only in response to the coarsest sandpaper for all 3 weights. D: the cell shown in Fig. 6 has the highest firing rate in response to contact with intermediate grit size 200 sandpaper for all 3 weights. E: cell from Fig. 7 for which a texture effect was observed with the 65- and 115-g weights but not when the object weighed 15 g. F: the cell from Fig. 8 with a relatively small graded increase in activity in response to weight but only when the contact surface is smooth metal. When the surface structure was either of the 2 sandpaper textures, the discharge did not show unidirectional changes.

In contrast, the activity shown in Fig. 4 from a different neuron in area 2 had the opposite response to texture. This cortical dynamic cell with a small receptive field on the index finger displayed the highest discharge rate with the smooth metal surface, and increasing the surface irregularity resulted in a corresponding and proportional decrease in the cell's activity (Tukey's HSD, P < 0.01). This relation is seen more clearly in the normalized activity presented in Fig. 3B, which demonstrates that the activity of this cell was significantly modulated by surface smoothness regardless of the weight lifted. In spite of the weight-independent discharge of these cells, a two-way ANOVA showed that the peak grip force was significantly modulated with both weight and texture during these recordings.



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Fig. 4. Increased firing frequency of a cortical dynamic cell associated with surface smoothness. The trace thickness follows the same conventions as Fig. 2. The mean peak firing frequency of this cell was significantly higher when the contact surface was smooth metal (see Fig. 3B). The location and boundary of the receptive field on digit 2 is shown on the top left inset of the hand figurine.

SIGNIFICANT RESPONSES TO A SINGLE TEXTURE. An additional 10 cells (Table 2) demonstrated statistically significant main effects of texture, but the changes were limited to only one texture as shown by the pair-wise comparison test. Also object weight did not appear to affect the discharge of these cells. Figures 5 and 3C illustrate the changes in one cell's activity in response to changes in texture. As is shown both in the activity histograms (Fig. 5) and the normalized discharge (Fig. 3C), this cell responded most vigorously to the coarsest sandpaper regardless of the object weight. When grit size decreased from 60 to 200, the response declined, but changing to smooth metal produced no significant further decline in the cell's activity (Tukey's HSD, P < 0.01). For this cell no significant modulation occurred in response to changes in weight. This dynamic cell had a small receptive field on the second phalange of the index finger and was located in area 7b.



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Fig. 5. Activity histogram of a cortical dynamic cell responding only to the coarsest sandpaper surface (see Fig. 3C). The trace thickness follows the same conventions as Fig. 2. The location and boundary of the receptive field on the distal phalangeal segment of digit 2 is shown in the hand figurine in the top left.

Another example of a cell having significantly different responses to only one texture is illustrated in Fig. 6, and the normalized activity of the same cell is shown in Fig. 3D. This dynamic cell had a receptive field on the index finger and was located in area 2. The cell discharged most with the fine-grained sandpaper for all three weights. Changing the texture to either smooth metal or rough sandpaper decreased the activity significantly in all three weight conditions (Tukey's HSD, P < 0.01). About 18% (8/45) of the cells responded best to the intermediate surface coarseness.



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Fig. 6. Activity of a cortical dynamic cell associated with surface texture. The trace thickness follows the same conventions as in Fig. 2. The mean peak firing frequency of this cell was significantly higher with the intermediate grit size 200 sandpaper for each of the 3 weights (see Fig. 3D). The receptive field of this cell shown in the top left covered part of the 2 distal phalangeal segments of the index.

Weight-dependent texture effects

INTERACTIVE EFFECTS OF WEIGHT AND TEXTURE. Although most cells displayed statistically significant responses in our task, the majority of the responses (31/45 or 69%) were neither simple nor monotonically graded. Instead, the ANOVA confirmed that there were frequently significant interactions between object weight and texture that influenced the cell's discharge. Some of these interactions displayed distinct response patterns.

Figure 7 illustrates the mean force traces and average responses for a cell illustrating one type of interaction between weight and texture. The normalized peak discharge of the same cell for each condition is shown in Fig. 3E. Although no effect of texture was observed with the 15-g weight, increasing the object weight to 65 or 115 g resulted in a significant modulation of cell activity across the three textures (Tukey's HSD, P < 0.01). The highest discharge rate occurred when the smooth metal surface was combined with the 115-g weight. This dynamic cell, located in area 5, had a relatively large receptive field covering part of the thumb and index fingers plus the webbing between the fingers.



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Fig. 7. Activity of a cortical dynamic cell associated with an interaction between surface structure and weight (see Fig. 3E). The trace thickness follows the same conventions as in Fig. 2. This cell had a small receptive field on the 1st phalange of the index shown on the figurine of the hand in the top left.

Figure 8 illustrates the static discharge pattern of a neuron with a cutaneous receptive field covering the thumb and thenar eminence located in area 5. Figure 3F illustrates the normalized peak activity of this same neuron. Peak discharge increased with increasing object weight, but only with the smooth metal surface. When either of the sandpaper textures contacted the receptive field, the relationship between neural response and object weight disappeared. We found no consistent relationship between discharge frequency and weight that was applicable to all three textures. In contrast, within the three conditions for a single weight, the range of textures did elicit some consistent relationships. Some were linear or monotonic, whereas others were either exponential or cosine relationships to object texture. However, the activity of other neurons revealed complex interactions between texture and weight, which could not be easily described. The study was limited to cells having cutaneous receptive fields on the thumb or index finger, and cells with receptive fields on fingers 3, 4, and 5 were not recorded. Within this group, there were no obvious differences in the distribution of the types of responses rostrocaudally across cytoarchitectonic areas under study.



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Fig. 8. Activity of a static neuron in cortical area 5 with a graded response to only 1 weight (see Fig. 3F). The trace thickness follows the same conventions as in Fig. 2. This cell had a receptive field that covered the glabrous skin of the thumb and thenar eminence.

As previously mentioned (Fig. 1A), the changes in weight had a less marked effect on the grip force than changes in texture. However, increasing the weight increased the inertia during lifting and the gravitational force exerted during stationary holding. Despite these differences, changes in weight modified the peak activity in only 26/45 (58%) of the cells, and no simple relationships were found over the range of weights tested. Weight-related effects were invariably affected by texture.

Discussion

Our objective was to search for patterns of neuronal activity from single somatosensory neurons encoding weight and surface texture during isometric grasping and lifting. In this regard, the sandpaper textures were, without doubt, complex stimuli. To the touch, there was a large subjective difference between grit size 60 and 200. Grit 200 feels uniform and relatively smooth, whereas the grit 60 feels uneven and very rough. These surfaces are not really comparable with the Braille-like beads embossed on flat surfaces used in some studies. Instead, the size of the surface asperities were more like the smaller surface structures used by DiCarlo et al. (1998), although the overall intergrain separation was considerably less. Unfortunately, the present study did not include any cells from area 3b, which was the region studied by DiCarlo et al. (1998), although in both studies the skin was subjected to both normal and tangential forces. However, another major difference between these two studies is that in grasping and lifting, the normal forces were adjusted to minimize slip on the skin, whereas in the stroking study the normal pressure was held constant at ~30 g, and the tangential stroking velocity was constant at 40 mm/s.

Texture, weight, and grip force

Despite the minimal slip in our conditions, the results show that changes in texture evoke significant changes in the discharge rate of 87% of cells in the somatosensory cortex. Under these conditions the neurons appeared to encode surface texture to a greater degree than object weight. Changes in texture evoked changes in peak grip force 98% of the time, whereas increasing the object weight resulted in an increase in peak grip force only 78% of the time. That is, within the range of parameters explored in the present study, slippery surfaces evoked higher grip forces than increasing the object weight. Although the increased inertial load accompanying increases in object weight required higher tangential forces during both lifting and holding, this changed neuronal activity in only 58% (26/45) of the cells (52% of dynamic cells and 67% of static cells).

Unlike peripheral afferent activity, cells in somatosensory cortex did not always increase activity with increases in pressure normal to the skin surface, nor did they always increase activity with the size of the surface asperities. Figure 1B indicates that factors such as weight and slipperiness, which elicit higher grip force, are not invariably associated with increased peak discharge from cells in the somatosensory cortex.

Weight-independent responses to textures

Peak discharge was modulated by texture in a graded fashion independent of object weight, in ~31% of the cells analyzed. Some demonstrated a graded relationship between peak discharge and two or three surfaces. Others showed higher activity with only one texture. These effects were independent of object weight, at least for the range of weights used in the present study. Such cells may provide texture-invariant signals for grasped objects that are relatively independent of the normal and tangential forces used to manipulate the object. Although the proportion of neurons showing these properties is small, their physiological significance may be much greater than the proportion reported here would suggest.

Earlier studies have emphasized that neural responses covary with increased spacing between asperities (Burton and Sinclair 1994; Darian-Smith et al. 1982, 1985; Jiang et al. 1997; Sinclair and Burton 1991). Although the 1- to 3-mm spacings were considerably greater than the closely spaced grains used in this study, our results agree with these findings. Although one-half the cells in the present study displayed their highest firing frequency with the roughest texture, an equal number responded in the opposite direction. Similar cells were described in somatosensory cortex by Sinclair and Burton (1991) and in motor cortex by Picard and Smith (1992a). Picard and Smith (1992b) suggested that increased firing frequency in response to decreased surface friction would be useful in providing a positive feedback signal essential for triggering the increased force necessary to lift and hold a smooth object.

Activity profiles tuned to particular textures

The cells showing greater activity in response to a single texture might be tuned to particular aspects of the surface structure such as the grit size. Alternatively, they may be related to particular combinations of excitatory and inhibitory receptive fields as suggested by DiCarlo et al. (1998). The cells shown in Figs. 5, 6, and 3, C and D, demonstrate a significant change in responsiveness for only one of the three surface textures. Sinclair et al. (1996) described tuning curves for S1 cells of the monkeys and suggested that they reflected the selective sensitivity of the cutaneous mechanoreceptors to specific groove widths. They argued that the tuning curves shifted when the force normal to the skin surface was altered and that some responses saturated as a result of the additive effects of groove width, contact force, and velocity. In our study, increasing the object weight (which changed the tangential force and to a lesser degree the force normal to the skin) failed to produce any significant change in the responses of these cells. Therefore cells in our study with a higher response to only one texture appeared to have tuning curves that were nearly identical for three different object weights.

Interactive effects of weight with texture

When using a similar precision grip task but without lifting, Wannier et al. (1991) reported that the activities of some S1 neurons with cutaneous, slowly adapting receptive fields stimulated by pinching were clearly correlated with the pinch force or pressure applied normal to the skin surface. The observations of the present study using the smooth metal surface (as shown in Figs. 8 and 3F), were in close agreement with those of Wannier et al. (1991). However, this correlation was not maintained for the two textured sandpaper surfaces. It appears that some aspect of the surface structure modified the otherwise graded response to pressure normal to the skin surface. As a consequence, object weight did not emerge as a significant main effect on the peak discharge in the statistical analysis of any of the 45 cells. The ANOVA revealed a significant texture by weight interaction for 62% of the cells. That is weight was only a significant influence on peak discharge with some but not all textures.

General conclusions

In spite of the fact that greater object weights required greater tangential lifting forces, the surface texture (and presumably friction) had a much stronger effect than weight on both peak grip force and the peak discharge of somatosensory cortical neurons. Some neurons had higher peak activity with the smooth surface, whereas others were more active with the rougher sandpaper. In general, the activity of cells showing weight-independent responses to texture did not resemble the activity of single peripheral afferents. Instead, these neurons demonstrated activity patterns that suggested a convergence of peripheral afferents, supporting the hypothesis that the somatosensory cortex plays an important role in texture recognition (DiCarlo et al. 1998). The results of the present study imply that the activity of some neurons in the somatosensory cortex can generate invariant responses to different surface textures that are maintained over a fairly wide range of object weights. That is, the activity patterns show a texture constancy. Moreover, neurons having both the dynamic and static activity patterns described in the companion paper (Salimi et al. 1999) were related to particular changes in either texture or weight. These specific texture and weight responses were remarkably similar to the texture-related weight-independent response seen in the motor cortex by Picard and Smith (1992a,b). This similarity supports the inference that somatosensory cortical discharge patterns represent a transformation of peripheral afferent signals into texture constancies through a process of convergence and transformation of afferents signals. These texture invariances may form the basis of the internal representations of object surfaces relayed to the motor cortex for the dexterous handling of familiar objects.


    ACKNOWLEDGMENTS

We thank Drs. C. E. Chapman and R. W. Dykes, and two anonymous reviewers for valuable comments on the manuscript. We also express our gratitude for the technical contributions of the late R. Bouchoux, and J. Jodoin, G. Mercier, L. Lessard, C. Gauthier, and D. Cyr.

This research was supported by a Medical Research Council of Canada grant to the research group in the neurological sciences at the Université de Montréal. A studentship award to I. Salimi from the Fonds pour la Formation de Chercheurs et l'Aide à la Recherche Center is gratefully acknowledged.


    FOOTNOTES

Address for reprint requests: A. M. Smith, Dépt. de Physiologie, Université de Montréal, Montreal, Quebec H3C 3J7, Canada.

Received 21 November 1997; accepted in final form 23 October 1998.


    REFERENCES
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Abstract
Introduction
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References

0022-3077/99 $5.00 Copyright © 1999 The American Physiological Society