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OBJECTIVES: To investigate the clinimetric properties and clinical utility of the AsTex((R)), a new clinical tool for evaluation of hand sensation following stroke. DESIGN: The AsTex((R)) was administered on two occasions separated by a week to appraise test-retest reliability, and by three assessors on single occasion to establish inter-rater reliability. Pilot normative values were collected in an age-stratified sample. Clinical utility was evaluated based on ease of administration, ceiling and floor effects, and responsiveness to sensory recovery. PARTICIPANTS: Test-retest (n = 31) and inter-rater (n = 31) reliability and normative values (n = 95) for the AsTex((R)) were established in neurologically normal participants aged 18-85 years. Test-retest reliability was investigated in 22 individuals a mean of 46 months (range 12-125) post stroke and clinical utility was evaluated in an additional 24 subacute stroke participants a mean of 29.4 days (range 12-41) post stroke. MAIN MEASURE: The AsTex((R)). RESULTS: The AsTex((R)) demonstrated excellent test-retest (intraclass correlation coefficient (ICC) = 0.98, 95% confidence interval (95% CI) = 0.97-0.99) and inter-rater reliability (ICC = 0.81, 95% CI = 0.73-0.87) in neurologically normal participants. Test-retest reliability of the AsTex((R)) in individuals following stroke was excellent (ICC = 0.86, 95% CI = 0.68-0.94). The AsTex((R)) was simple to administer, demonstrated small standard error of measurement (0.14 mm), minimal floor and ceiling effects (12.5% and 8.3%) and excellent responsiveness (standardized response mean = 0.57) in subacute stroke participants. CONCLUSION: The AsTex((R)) is a reliable, clinically useful and responsive tool for evaluating hand sensation following stroke. [ABSTRACT FROM AUTHOR]

Examines the responses of fingertip tactile afferents to objects and surface curvature. Use of microneurograph to record impulses from tactile afferents; Stimulation of a standard site on the finger; Relationship between the location of the receptive fields and the response patterns.

Examines the directional encoding of fingertip force by human tactile afferents. Generation of time varying fingertip forces in various directions; Application of stimuli to test site under three-dimensional force control using computer-controlled stimulator; Location of the receptive fields on the phalanx.

How complex tactile sensations are encoded by populations of afferent mechanoreceptors is currently not well understood. While much is known about how individual afferents respond to prescribed stimuli, their behavior as a population distributed across the fingertip has not been well described. In this study, tactile afferent mechanoreceptors in monkey fingertips were mechanically stimulated, using a flat disc shaped probe, with several magnitudes of normal force (1.8, 2.2 and 2.5 N) and torque (2.0 and 3.5 mNm), in clockwise and anticlockwise directions. Afferent nerve responses were acquired from 58 slowly-adapting (SA) type-I and 25 fast-adapting (FA) type-I isolated single cutaneous mechanoreceptive afferents, recorded from the median nerve. At 10 ms time intervals after the application of torque begins, a multiple regression model was trained and evaluated to estimate the magnitude of the applied normal force and torque. Averaged results over the 200 ms period after the torque reaches its maximum indicate that SA-I and FA-I afferents can both estimate the applied torque value. FA-I afferents gave the lowest estimation error mean and standard deviation of -0.051 ± 0.334 mNm for a target torque of 2.0 mNm, and 0.003 ± 0.414 mNm for a target torque of 3.5 mNm. However, while SA-I afferents could estimate normal force well, there was no significant difference (ANOVA, p=0.173) in the FA-I estimates of normal force, as this force had already been held constant for one second before the torque loading phase under analysis began.

Torsional loads are ubiquitous during everyday dextrous manipulations. We examined how information about torque is provided to the sensorimotor control system by populations of tactile afferents. Torsional loads of different magnitudes were applied in clockwise and anticlockwise directions to a standard central site on the fingertip. Three different background levels of contact (grip) force were used. The median nerve was exposed in anaesthetized monkeys and single unit responses recorded from 66 slowly adapting type-I (SA-I) and 31 fast adapting type-I (FA-I) afferents innervating the distal segments of the fingertips. Most afferents were excited by torque but some were suppressed. Responses of the majority of both afferent types were scaled by torque magnitude applied in one or other direction, with the majority of FA-I afferent responses and about half of SA-I afferent responses scaled in both directions. Torque direction affected responses in both afferent types, but more so for the SA-I afferents. Latencies of the first spike in FA-I afferent responses depended on the parameters of the torque. We used a Parzen window classifier to assess the capacity of the SA-I and FA-I afferent populations to discriminate, concurrently and in real-time, the three stimulus parameters, namely background normal force, torque magnitude and direction. Despite the potentially confounding interactions between stimulus parameters, both the SA-I and the FA-I populations could extract torque magnitude accurately. The FA-I afferents signalled torque magnitude earlier than did the SA-I afferents, but torque direction was extracted more rapidly and more accurately by the SA-I afferent population.

Control of tangential force plays a key role in everyday manipulations. In anesthetized monkeys, forces tangential to the skin were applied at a range of magnitudes comparable to those used in routine manipulations and in eight different directions. The paradigm used enabled separation of responses to tangential force from responses to the background normal force. For slowly adapting type I (SAI) afferents, tangential force responses ranged from excitatory through no response to suppression, with both a static and dynamic component. For fast adapting type I (FAI) afferents, responses were dynamic and excitatory only. Responses of both afferent types were scaled by tangential force magnitude, elucidating the neural basis for previous human psychophysical scaling data. Most afferents were direction selective with a range of preferred directions and a range in sharpness of tuning. Both the preferred direction and the degree of tuning were independent of the background normal force. Preferred directions were distributed uniformly over 360 degrees for SAI afferents, but for FAI afferents they were biased toward the proximo-ulnar direction. Afferents from all over the glabrous skin of the distal segment of the finger responded; there was no evident relationship between the position of an afferent's receptive field on the finger and its preferred direction or its degree of tuning. Nor were preferred directions biased either toward or away from the receptive field center. In response to the relatively large normal forces, some afferents saturated and others did not, regardless of the positions of their receptive fields. Total afferent response matched human psychophysical scaling functions for normal force.

When humans manipulate objects, the sensorimotor system coordinates three-dimensional forces to optimize and maintain grasp stability. To do this, the CNS requires precise information about the magnitude and direction of load force (tangential to skin surface) plus feedback about grip force (normal to skin). Previous studies have shown that there is rapid, precise coordination between grip and load forces that deteriorates with digital nerve block. Obviously, mechanoreceptive afferents innervating fingerpad skin contribute essential information. We quantify human capacity to scale tangential and normal forces using only cutaneous information. Our paradigm simulated natural manipulations (a force tangential to the skin superimposed on an indenting force normal to the skin). Precisely controlled forces were applied by a custom-built stimulator to an immobilized fingerpad. Using magnitude estimation, subjects (n = 8) scaled the magnitude of tangential force (0.25-2.8 N) in two experiments (normal force, 2.5 and 4 N, respectively). Performance was unaffected by normal force magnitude and tangential force direction. Moreover, when both normal (2-4 N) and tangential forces were varied in a randomized-block factorial design, the relationship between applied and perceived tangential force remained near linear, with a minor but statistically significant nonlinearity. Our subjects could also discriminate small differences in tangential force, and this was the case for two different reference stimuli. In both cases, the Weber fraction was 0.16. Finally, scaling functions for magnitude estimates of normal force (1-5 N) were also approximately linear. These data show that the cutaneous afferents provide a wealth of precise information about both normal and tangential force.

For humans to manipulate an object successfully, the motor control system must have accurate information about parameters such as the shape of the stimulus, its position of contact on the skin, and the magnitude and direction of contact force. The same information is required for perception during haptic exploration of an object. Much of these data are relayed by the mechanoreceptive afferents innervating the glabrous skin of the digits. Single afferent responses are modulated by all the relevant stimulus parameters. Thus, only in complete population reconstructions is it clear how each of the parameters can be signaled to the brain independently when many are changing simultaneously, as occurs in most normal movements or haptic exploration. Modeling population responses reveals how resolution is affected by neural noise and intrinsic properties of the population such as the pattern and density of innervation and the covariance of response variability.

Most objects that we grasp, lift and further manipulate are curved, with curvatures of the same order of magnitude as those of the fingertips. Tactile information pertaining to such 'gross' geometrical features of objects are used in the automatic control of fingertip actions. We analyzed responses from 172 human tactile afferents distributed over the entire terminal phalanx when spherically shaped surfaces were applied to a standard site on the fingertip; the curvatures and force magnitudes and directions used were representative of everyday manipulations. Nearly all SA-I, SA-II and FA-I afferents responded, and for more than 80% of these afferents the response intensity was correlated with curvature. The correlation was positive for approximately half the afferents and negative for the other half, resulting in a curvature contrast signal within the populations of tactile afferents; afferents terminating at the sides and end of the fingertip tended to show negative correlations. For nearly all afferents, curvature and force direction had interactive effects. Changing the direction of force affected an afferent's sensitivity to curvature and vice versa. We conclude that recognition of such shapes takes advantage of signals originating from tactile afferents distributed over the entire terminal phalanx, and that both the direction of fingertip forces and the curvatures of objects contacted during natural manipulations influence the afferents' responses. Consequently, if humans are able to perceive independently curvature and force direction from signals in tactile afferents, then the CNS must possess mechanisms that disentangle interactions between these and other parameters of stimuli on the fingertips.

Analysis of population responses in the tactile system requires a step beyond the isomorphic representations that are commonly presented. Using a simple model based on our data for spheres contacting the fingerpad, we illustrate how the parameters of the population itself have a profound effect on the fidelity of neural representations or codes. The effects of these parameters, such as innervation density, variability of sensitivity, type and covariance of noise are not apparent from single unit responses and, at least at present, require a theoretical or modeling approach of some sort.

In most manipulations, we use our fingertips to apply time-varying forces to the target object in controlled directions. Here we used microneurography to assess how single tactile afferents encode the direction of fingertip forces at magnitudes, rates, and directions comparable to those arising in everyday manipulations. Using a flat stimulus surface, we applied forces to a standard site on the fingertip while recording impulse activity in 196 tactile afferents with receptive fields distributed over the entire terminal phalanx. Forces were applied in one of five directions: normal force and forces at a 20 degrees angle from the normal in the radial, distal, ulnar, or proximal directions. Nearly all afferents responded, and the responses in most slowly adapting (SA)-I, SA-II, and fast adapting (FA)-I afferents were broadly tuned to a preferred direction of force. Among afferents of each type, the preferred directions were distributed in all angular directions with reference to the stimulation site, but not uniformly. The SA-I population was biased for tangential force components in the distal direction, the SA-II population was biased in the proximal direction, and the FA-I population was biased in the proximal and radial directions. Anisotropic mechanical properties of the fingertip and the spatial relationship between the receptive field center of the afferent and the stimulus site appeared to influence the preferred direction in a manner dependent on afferent type. We conclude that tactile afferents from the whole terminal phalanx potentially contribute to the encoding of direction of fingertip forces similar to those that occur when subjects manipulate objects under natural conditions.

When the flat faces of a coin are grasped between thumb and index finger, a "curved edge" is felt. Analogous curved edges were generated by our stimuli, which comprised the flat face of segments of annuli applied passively to immobilized fingers. Humans could scale the curvature of the annulus and could discriminate changes in curvature of approximately 20 m(-1). The responses of single slowly adapting type I afferents (SAIs) recorded in anesthetized monkeys could be quantified by the product of two factors: their sensitivity and a spatial profile dependent only on the radius of the annulus. This allowed us to reconstruct realistic SAI population responses that included noise, variation in fiber sensitivity, and varying innervation patterns. The critical question was how relatively small populations ( approximately 70 active fibers) can encode edge curvature with such precision. A template-matching approach was used to establish the accuracy of edge representation in the population. The known large interfiber variability in sensitivity had no effect on curvature resolution. Neural resolution was superior to human performance until large levels of central noise were present showing that, unlike simple detection, spatial processing is limited centrally. In contrast to the behavior of mean response codes, neural resolution improved with increasing covariance in noise. Surprisingly, resolution for any single population varied considerably with small changes in the position of the stimulus relative to the SAI matrix. Overall innervation density was not as critical as the spacing of receptive fields at right angles to the edge.

The aim of this study was to determine the acuity of the peripheral tactile system for gaps and to determine how stimulus orientation may impact on this. We quantified the ability of humans to discriminate small differences in gap width using a forced-choice task. Stimuli were presented passively to the distal fingerpad in a region where the skin ridges all run approximately in the same direction. Two standard gap widths were used (2 and 2.9 mm), and the comparison gap widths were larger than the standard gaps. With the gap axis parallel to the skin ridges, the average difference limen was approximately 0.2 mm for both standards. We examined the effect of stimulus orientation by asking subjects to discriminate between a smooth surface and a grating (ridge width, 1.5 mm; groove width, 0. 75 mm). They were able to discriminate the two surfaces when the axis of the grooves was parallel to the skin ridges, but performance was below threshold in the orthogonal orientation. The underlying neural mechanisms were investigated using the gap stimuli to activate single slowly adapting type I mechanoreceptive afferents (SAIs) innervating the fingerpads of anesthetized monkeys. The edges of the gap produced response peaks, and the gap resulted in a trough in the receptive field profiles. The response magnitude at the peaks was greater, and at the troughs was smaller, for larger gap widths and also when the axis of the gap was parallel to the skin ridges as compared with the orthogonal orientation. Simulated SAI population responses showed that response profiles were distorted by variation in afferent sensitivity and by neural noise. Using signal detection theory, based on a neural measure of the gaps computed over the active population, the acuity of the SAIs under realistic population conditions was compared with human performance. These analyses showed how parameters like afferent sensitivity, the pattern and density of innervation, and noise impact on performance and why their impact is different for the two stimulus orientations investigated. The greatest limitation was imposed by noise that is independent of response magnitude, and this effect was greater for stimuli oriented orthogonal to the skin ridges than for the parallel orientation.

The central part of the fingerpad in anesthetized monkeys was stimulated by spheres varying in curvature indented into the skin. Responses were recorded from single slowly adapting type I primary afferent fibers (SAIs) innervating the sides and end of the distal segment of the stimulated finger. Although these afferents had receptive field centers that were remote from the stimulus, their responses were substantial. Increasing the curvature of the stimulus resulted in an increased response for most afferents. In general, responses increased most between stimuli with curvatures of 0 (flat) and 80.6 m(-1), with further increases in curvature having progressively smaller effects on the response. We calculated an index of sensitivity to changes in curvature; this index varied widely among the afferents but for most it was less than the index calculated for afferents innervating the fingerpad in the vicinity of the stimulus. Responses of all the SAIs increased when the contact force of the stimulus increased. An index of sensitivity to changes in contact force varied widely among the afferents but in all cases was greater than the index calculated for SAIs from the fingerpad itself. Neither the curvature sensitivity nor the force sensitivity of an afferent was related in any obvious way to the location of its receptive field center on the digit. There was only a minor correspondence between an afferent's sensitivity to force and its sensitivity to curvature. The large number of afferents innervating the border regions of the digit do respond to stimuli contacting the central fingerpad; they convey some information about the curvature of the stimulus and substantial information about contact force.

The capacity of a population of primary afferent fibers to signal information about a sphere indenting the fingerpad is limited by factors such as the inhomogeneity of sensitivity among the afferents, the pattern and density of innervation, and the effects of noise (response variability). Using experimental data recorded from single slowly adapting type I afferents (SAIs), we simulated the response of the SAI population to such a stimulus. The human ability to discriminate stimulus curvature, location, and force has been quantified previously. We devised three neural measures, treating them as surrogates for the real neural measures underlying human performance, and explored how population parameters usually overlooked in neural coding studies affect such measures. Variation in sensitivity among SAIs is large; this distorts population response profiles markedly but has no significant impact on the neural measures. Two classes of noise were introduced, one dependent on and the other independent of the level of neural activity. Resolution of the model was compared with discrimination in humans. Correlation of noise among neurons had different effects for the different measures. An increase in correlation decreased resolution in the measure for force but improved resolution in the measure for position. Increasing innervation density (1) always increased resolution for position and (2) increased resolution for force if noise was uncorrelated but had diminishing effects as correlation increased. Correlation and innervation density had complex effects on the measure for curvature, depending on the class of noise. Nonuniformity in the pattern of innervation had negligible effects on resolution.

When we manipulate objects in everyday tasks, there are variations in the shape of the grasped surfaces, and the loads that potentially destabilize the grasp include time-varying linear forces and torques tangential to the grasped surfaces. Previous studies of the control of fingertip forces for grasp stability have dealt principally with flat grip surfaces and linear force loads. Here, we studied the regulation of grip force with changes in curvature of grasped surfaces and changes in tangential torque applied by the index finger and thumb when humans lifted an object and rotated it about the horizontal grip axis through an angle of 65 degrees. The curvatures of the matched pair of spherical surfaces varied from -50 m-1 (concave with radius 20 mm) to 200 m-1 (convex with radius 5 mm). The applied tangential torque at the orientation of 65 degrees was varied sixfold. Regardless of the values of curvature and end torque, grip force and tangential torque were coordinated, increasing in parallel throughout the tilt with an approximately linear relationship; the slope of the line increased progressively with increasing surface curvature. This parametric scaling of grip force was directly related to the minimum grip force required to prevent rotational slip, resulting in an adequate safety margin against slip in all cases. We conclude that surface curvature parametrically influences grip force regulation when the digits are exposed to torsional loads. Furthermore, the sensorimotor programs that control the grip force apparently predict the effect of the total load comprising linear forces and tangential torques.

In previous investigations of the control of grasp stability, humans manipulated test objects with flat grasp surfaces. The surfaces of most objects that we handle in everyday activities, however, are curved. In the present study, we examined the influence of surface curvature on the fingertip forces used when humans lifted and held objects of various weights. Subjects grasped the test object between the thumb and the index finger. The matching pair of grasped surfaces were spherically curved with one of six different curvatures (concave with radius 20 or 40 mm; flat; convex with radius 20, 10, or 5 mm) and the object had one of five different weights ranging from 168 to 705 g. The grip force used by subjects (force along the axis between the 2 grasped surfaces) increased with increasing weight of the object but was modified inconsistently and incompletely by surface curvature. Similarly, the duration and rate of force generation, when the grip and load forces increased isometrically in the load phase before object lift-off, were not influenced by surface curvature. In contrast, surface curvature did affect the minimum grip forces required to prevent frictional slips (the slip force). The slip force was smaller for larger curvatures (both concave and convex) than for flatter surfaces. Therefore the force safety margin against slips (difference between the employed grip force and the slip force) was higher for the higher curvatures. We conclude that surface curvature has little influence on grip force regulation during this type of manipulation; the moderate changes in slip force resulting from changes in curvature are not fully compensated for by changes in grip force.

When a human grasps a cylindrical object, feedback on the orientation of the cylinder with respect to the axes of the digits is crucial for successful manipulation of the object. We measured the ability of humans to discriminate the orientations of cylinders passively contacting the fingerpad. For a cylinder of curvature of 521 m-1 (radius, 1.92 mm) subjects were able to discriminate, at the 75% level, orientation differences of 5.4 degrees; for a less curved cylinder (curvature, 172 m-1; radius, 5.81 mm) the difference limen decreased to 4.2 degrees. The neural mechanisms underlying the determination of tactile orientation were investigated by recording the responses of single slowly adapting type I afferents (SAIs) innervating the fingerpads of anesthetized monkeys. When cylinders were stepped across the receptive field of an SAI, the resulting response profiles were Gaussian in shape; the shape corresponded to the shape of the cylinder, increasing in height and decreasing in width for more curved cylinders. All SAIs had the same underlying profile shape except for a multiplicative constant determined by the sensitivity of the individual afferent. Thus it was possible to reconstruct the response of the population of active SAIs in the fingerpad. Changing the orientation of the cylinder resulted in a rotation of the population response, but the change in angle of the population response was greater than the change in orientation of the cylinder. This discrepancy increased as the orientation of the cylinder moved closer to the orientation of the axis of the finger and was more pronounced for the less curved cylinder. Measured contact areas between the cylinders and the skin were elliptical, with orientations exceeding those of the cylinder; again the differences were greater for the less curved cylinder and for orientations closer to that of the finger axis. The human discrimination performance could be explained in terms of the SAI population responses.

Isolated responses were recorded from fibers in the median nerves of human subjects by using microneurography. Mechanoreceptive afferent fibers with receptive fields on the fingerpads were selected. The fingers were immobilized and spherical stimuli were applied passively to the receptive field with a contact force of 40-, 60-, or 80-g weight. The radii of the spheres were 1.92, 2.94, 5.81, or 12.4 mm or infinity (flat); the corresponding curvatures, given by the reciprocal of the radii, were 694, 340, 172, 80.6, or 0 m-1, respectively. When the spheres were applied to the receptive field center of slowly adapting type I afferents (SAIs), the response increased as the curvature of the sphere increased and also increased as the contact force increased. All SAIs behaved in the same way except for a scaling factor proportional to the sensitivity of the afferent. When a sphere was located at different positions in the receptive field, the shape of the resulting response profile reflected the shape of the sphere; for more curved spheres the profile was higher and narrower (increased peak and decreased width). Slowly adapting type II afferents (SAIIs) showed different response characteristics from the SAIs when spheres were applied to their receptive field centers. As the curvature of the stimulus increased from 80.6 to 172 m-1, the response increased. However, further increases in curvature did not result in further increases in response. An increase in contact force resulted in an increase in the response of SAIIs; this increase was proportionately greater than it was for SAIs. For SAIIs, the shape of the receptive field profile did not change when the curvature of the stimulus changed. For fast-adapting type I afferents (FAIs), the responses were small and did not change systematically with changes in curvature or contact force. Fast-adapting type II afferents (FAIIs) did not respond to our stimuli. Human SAIs, FAIs, and FAIIs behaved like monkey SAIs, FAIs, and FAIIs, respectively. The response of the SAI population contains accurate information about the shape of the sphere and its position of contact on the finger and also indicates contact force. Conversely, whereas SAIIs possess a greater capacity to encode changes in contact force, they provide only coarse information on local shape.

A forced choice paradigm was used to measure the capacity of human subjects to discriminate the curvature of stimuli applied passively to the skin of an immobilized finger. The stimuli consisted of spherically curved segments with a base radius of 2.5 mm; thus the area of contact with the fingerpad skin was approximately 19.6 mm2 for all stimuli. There were 2 series of experiments. In series 1, the standard surface had a curvature of 286 m-1 (radius of curvature 3.5 mm); subjects were able to discriminate an increase in curvature of about 13%. In series 2, the standard had a curvature of 154 m-1 (radius 6.5 mm); subjects were able to discriminate an increase in curvature of about 18%. Thus, even when the contact area between the surface and the skin was invariant, humans were able to discriminate small changes in curvature using only information from the cutaneous receptors.

Stimuli with spherically curved surfaces were presented passively to the fingerpads of human subjects. There were 28 stimuli, consisting of all combinations of 4 different curvatures and 7 different contact forces; these were presented in random order. Subjects scaled their perceived magnitude of the contact force using magnitude estimation. Perceived force increased markedly with an increase in experimentally applied contact force. An increase in curvature resulted in a slight increase in perceived contact force. Thus, when humans are passively presented with objects changing in both shape and contact force, they are able to extract information about the force. Because of the passive nature of the task, all such information must be conveyed to the brain by the cutaneous mechanoreceptors.

Spherically curved surfaces were applied, with controlled force, to the fingerpads of human subjects; their fingers were immobilized. The curvature of the surfaces was characterised by the reciprocal of the radius of curvature. In scaling experiments, the subjects' perceived magnitude of curvature increased markedly with an increase in the curvature of the stimulus. An increase in contact force resulted in a slight decrease in perceived curvature. Four discrimination experiments were performed using a forced choice paradigm. Subjects could discriminate, at the 75% level, a flat surface (zero curvature) from a convex curvature of 4.9 m-1 (radius of curvature 204 mm) and from a concave curvature of 5.4 m-1 (radius 185 mm). When discriminating 2 convex spherical surfaces, subjects could discriminate a curvature of 144 m-1 from a curvature of 158 m-1 (radii 6.95 and 6.33 mm respectively), and could discriminate a curvature of 287 m-1 from one of 319 m-1 (radii 3.48 and 3.13 mm respectively); the Weber fraction is about 0.1. Contact areas between the curved surfaces and the fingerpad skin were estimated. There was approximate correspondence between contact areas and the scaling functions.

Spatial summation of responses in striate neurons in cats under N2O/O2 anaesthesia was examined quantitatively both along the line of the optimal stimulus orientation (length summation) using moving light bars and single light and dark edge stimuli, and at right angles to the optimal orientation (width summation) using stationary flashing bars. Activity profiles and length-response curves were prepared from simple, complex and hypercomplex I and II cells. An activity profile indicates the responsiveness of a cell at locations along the length of its receptive field. The activity profiles from all cell types were usually well fitted by Gaussian functions. Length summation occurs both in end-free (simple and complex) and, to a lesser extent, in end-stopped (hypercomplex I and II) cells over a wide range of stimulus contrasts (0.13 to 0.95). The linearity of length summation was tested either by comparing the recorded length-response curves with the curves predicted from the linear integration of the activity profiles or by comparing the response to the activation of two regions of the receptive field with the sum of the responses to each region activated separately. Although length summation was usually non-linear (either greater than or less than direct proportionality) it was more nearly linear in complex than it was in simple and hypercomplex I cells. Mechanisms responsible for non-linear length summation were studied, including a threshold for discharge, response saturation and summation of end-zone inhibition. Complex cells show little width summation for bars wider than 0.3 degrees. In simple and hypercomplex I cells there was also relatively little width summation either in an ON or an OFF discharge region at contrasts above about 0.4 but at lower contrasts width summation may be apporximately linear. Spatial summation of responses does not appear to be a useful characteristic for distinguishing one striate cell type from another.

The ability of human subjects to discriminate plane metal plates of different thickness was measured using of forced-choice paradigm. The plates, made by electroplating a thin layer of copper onto flat brass shims, were gripped between the thumb and the index finger. Subjects were presented with either 2 standard plates (0.2 mm thick), or a standard plate and a test plate that was slightly thicker, and were required in state which alternative had occurred. When the edges of the plates could not be touched, a difference in thickness of about 0.075 mm could be discriminated. Surprisingly, when the edges were included in the grip, performance did not improve. All hypotheses of strategies used by the subjects required them to sense the angles of the finger joints with a precision of about 0.1 degrees.

Skin on the fingertips of humans and monkeys was stimulated by a probe vibrating with a sinusoidal displacement. The probe and the skin were illuminated stroboscopically and were viewed through a dissecting microscope. The stroboscope was triggered by the sinusoidal generator via a digital delay, so that the position of both the probe and the skin could be measured at regular intervals during the cycle. Six frequencies and 3 amplitudes of vibration were used. During a portion of the cycle the probe and the skin separated, so that the skin waveform was a clipped sinusoid. An increase in stimulus frequency increased the fraction of the cycle during which the probe and the skin were separated. Adding a static pre-indentation to the vibration reduced this fraction, and for this condition a decrease in vibratory amplitude also decreased the fraction. Thus the skin motion contained harmonics that were not present in the probe motion, and the harmonic content differed for different stimulus conditions.

Following our earlier study on direction selectivity in simple cells (5), the present findings on complex cells made it possible to compare the direction selectivity in the two types of striate cell. Common properties were found in the dimension of the smallest stimulus displacement giving a direction-selective response and in the role of inhibition in suppressing the response as the stimulus moved in the nonpreferred direction. However, the effectiveness of this inhibition varied in the two cell types since it suppressed both driven and spontaneous activity in the simple cell, but only driven firing in the complex cell. It is argued that direction selectivity must enter the response before the complex cell if the inhibition responsible for it's generation fails to influence the spontaneous activity of the cell. The consequences of this finding are considered in the terms of parallel or sequential processing of visual information in striate cortex.

Most simple cells in the striate cortex of the cat are direction selective, firing to broadside movement of an optimally oriented edge or bar in one direction of motion and not the other. The smallest stimulus displacement for which a direction-selective discrimination can be made cannot be smaller than the threshold for the detection of the displacement itself. It is shown that retinal image quality is an important limiting factor in respect to the thresholds both for stimulus displacement and direction selectivity.

A case of total anomalous pulmonary venous connection to the portal vein is described. The diagnosis was suspected clinically, supported by the echocardiogram, and confirmed by cardiac catheterisation, angiocardiography, and contrast echocardiography. An echo-free space lying behind the left atrium initially was thought to represent the common pulmonary vein. However, contrast echocardiography showed that this space was not the anomalous vein but probably an artefact. This paper shows that the origins of intracardiac echoes cannot always be assumed from a simple comparison of echocardiography with angiocardiographic or necropsy findings. In some cases it is necessary to introduce a marker into the echocardiogram which unequivocally originates from, and, therefore, localises, the structure under examination. Contrast echocardiography provides such a marker.

1. Using a multi-histogram technique forty-seven response-velocity curves were prepared for a variety of visual stimuli presented to twenty-one cells in the striate cortex of the anaesthetized, paralysed cat. 2. The character of each velocity-response curve varied according to the measurement used in assessing a response. Reasons are advanced for sampling the response over a single bin of short duration at the peak of the discharge in each average response histogram. 3. The sharpness of tuning varied markedly throughout the population of cells but it was not possible to establish any definitive class differences. 4. For simple and complex cell categories there was considerable overlap in both the range of effective stimulus velocities and the distribution of the optimal velocities. An observation not emphasized in the past was that some simple cells responded to very fast stimuli while a number of complex cells were driven by very slowly moving stimuli. 5. Generally changes in stimulus parameters such as the polarity of contrast of a moving edge, its orientation or direction of movement produced only slight modifications in the profile of the velocity-response curve. 6. The abolition of the response of simple cells that failed to be driven by rapidly moving stimuli was shown to be due to the entry of the stimulus into the inhibitory flank distal to the discharge region. When the movement of the stimulus was confined to the discharge region there was little evidence of velocity dependence in the response. The duration over which the inhibition from the distal flank remained effective was evaluated for representative simple cells.

Human subjects were required to differentiate grating surfaces of alternating grooves and ridges by moving a finger back and forth across the surface. Their discriminative capacities were measured, as well as the movement and force profiles that they selected. To measure discrimination, a forced choice paradigm was used in which three surfaces were presented on each trial. Two surfaces were the same (standards) and the subject was required to indicate which of the three surfaces (the comparison) differed from the other two. Two series of surfaces were used with standards whose spatial periods were 770 and 1002 mu, respectively. Subjects were able to discriminate, at the 75% correct level, two gratings which differed in spatial period by the order of 5%. When tangential movement between the surface and the finger was eliminated, and only radial contact permitted, discrimination was degraded and the 75% correct levels increased to the order of 10%. Subjects were free to choose their own patterns of finger movement and of contact force between finger and surface. Movement was measured cinematographically. For all subjects movement patterns were close to sinusoidal, with frequencies in the range of 4.0 Hz and with mean velocities of the order of 160 mm/s. Patterns of contact force were measured by a force transducer. For all subjects the force varied rhythmically in synchrony with movement, but the patterns and magnitudes varied with the subject. Gratings were scaled for perceived roughness by a magnitude estimation technique: the relationship between perceived roughness and grating period was monotonic.

The stimulator allows textured surfaces to be moved sinusoidally across the skin of the fingerpad. Sinusoidal motion is produced by a "scotch yolk" driven by a DC motor. The amplitude of movement is adjustable up to a maximum of 80 mm peak to peak and the frequency is continuously adjustable from 0.1 Hz to 2.0 Hz. Movement of the surface is monitored by an optical transducer and contact force between the finger and the surface is monitored by a strain gauge bridge. The stimulator is simple and robust and is suitable for both neurophysiological and psychophysical experiments in animals and humans.