Musicians often say that they not only hear, but also “feel” music. To explore the contribution of tactile information in “feeling” musical rhythm, we investigated the degree that auditory and tactile inputs are integrated in humans performing a musical meter recognition task. Subjects discriminated between two types of sequences, ‘duple’ (march-like rhythms) and ‘triple’ (waltz-like rhythms) presented in three conditions: 1) Unimodal inputs (auditory or tactile alone), 2) Various combinations of bimodal inputs, where sequences were distributed between the auditory and tactile channels such that a single channel did not produce coherent meter percepts, and 3) Simultaneously presented bimodal inputs where the two channels contained congruent or incongruent meter cues. We first show that meter is perceived similarly well (70%–85%) when tactile or auditory cues are presented alone. We next show in the bimodal experiments that auditory and tactile cues are integrated to produce coherent meter percepts. Performance is high (70%–90%) when all of the metrically important notes are assigned to one channel and is reduced to 60% when half of these notes are assigned to one channel. When the important notes are presented simultaneously to both channels, congruent cues enhance meter recognition (90%). Performance drops dramatically when subjects were presented with incongruent auditory cues (10%), as opposed to incongruent tactile cues (60%), demonstrating that auditory input dominates meter perception. We believe that these results are the first demonstration of cross-modal sensory grouping between any two senses.

In the present study, we examined the neural mechanisms underlying crossmodal working memory by analyzing scalp-recorded event-related potentials (ERPs) from normal human subjects performing tactile-tactile unimodal or tactile-auditory crossmodal delay tasks that consisted of stimulus-1 (S-1, tactile), interval (delay), and stimulus-2 (S-2, tactile or auditory). We hypothesized that there are sequentially discrete task-correlated changes in ERPs representing neural processes of tactile working memory, and in addition, significant differences would be observed in ERPs between the unimodal task and the crossmodal task.

In comparison to the ERP components in the unimodal task, two late positive ERP components (LPC-1 and LPC-2) evoked by the tactile S-1 in the delay of the crossmodal task were enhanced by expectation of the associated auditory S-2 presented at the end of the delay. Such enhancement might represent neural activities involved in crossmodal association between the tactile stimulus and the auditory stimulus. Later in the delay, a late negative component (LNC) was observed. The amplitude of LNC depended on information retained during the delay, and when the same information was retained, this amplitude was not influenced by modality or location of S-2 (auditory S-2 through headphones, or tactile S-2 on the left index finger). LNC might represent the neural activity involved in working memory. The above results suggest that the sequential ERP changes in the present study represent temporally distinguishable neural processes, such as the crossmodal association and crossmodal working memory.

We describe a computer-controlled tactile stimulator for use in human psychophysical and monkey neurophysiological studies of 3-D shape perception. The stimulator is constructed primarily of commercially available parts, as well as a few custom-built pieces for which we will supply diagrams upon request. There are two components to the stimulator: a tactile component and a hand positioner component. The tactile component consists of multiple stimulating units that move about in a Cartesian plane above the restrained hand. Each stimulating unit contains a servo-controlled linear motor with an attached small rotary stepper motor, allowing arbitrary stimulus shapes to contact the skin through vibration, static indentation, or scanning. The hand positioner component modifies the conformation of the restrained hand through a set of mechanical linkages under motorized control. The present design controls the amount of spread between digits two and three, the spread between digits four and three, and the degree to which digit three is flexed or extended, thereby simulating different conformations of the hand in contact with objects. This design is easily modified to suit the needs of the experimenter. Because the two components of the stimulator are independently controlled, the stimulator allows for parametric study of the mechanoreceptive and proprioceptive contributions to 3-D tactile shape perception.

A subpopulation of neurons in primate somatosensory cortex signal the direction in which objects move across the skin of the fingertips.

Invariant representations of stimulus features are thought to play an important role in producing stable percepts of objects. In the present study, we assess the invariance of neural representations of tactile motion direction with respect to other stimulus properties. To this end, we record the responses evoked in individual neurons in somatosensory cortex of primates, including areas 3b, 1, and 2, by three types of motion stimuli, namely scanned bars and dot patterns, and random dot displays, presented to the fingertips of macaque monkeys. We identify a population of neurons in area 1 that is highly sensitive to the direction of stimulus motion and whose motion signals are invariant across stimulus types and conditions. The motion signals conveyed by individual neurons in area 1 can account for the ability of human observers to discriminate the direction of motion of these stimuli, as measured in paired psychophysical experiments. We conclude that area 1 contains a robust representation of motion and discuss similarities in the neural mechanisms of visual and tactile motion processing.

Author Summary

When we physically interact with an object, our hands convey information about the shape of the object, its texture, its compliance, and its thermal properties. This information allows us to manipulate tools and to recognize objects based on tactile exploration alone. One of the hallmarks of tactile object recognition is that it involves movement between the skin and the object. In this study, we investigate how the direction in which objects move relative to the skin is represented in the brain. Specifically, we scan a variety of stimuli, including bars and dot patterns, across the fingers of non-human primates while recording the evoked neuronal activity. We find that a population of neurons in somatosensory cortex encodes the direction of moving stimuli regardless of the shape of the stimuli, the speed at which they are scanned across the skin, or the force with which they contact the skin. We show that these neurons can account for our ability to perceive the direction of motion of tactile stimuli.

Recent studies using electrocorticographic (ECoG) recordings in humans have shown that functional activation of cortex is associated with an increase in power in the high-gamma frequency range (∼60–200 Hz). Here we investigate the neural correlates of this high-gamma activity in local field potential (LFP). Single units and LFP were recorded with microelectrodes from the hand region of macaque SII cortex while vibrotactile stimuli of varying intensities were presented to the hand. We found that high-gamma power in the LFP was strongly correlated with the average firing rate recorded by the microelectrodes, both temporally and on a trial-by-trial basis. In comparison, the correlation between firing rate and low-gamma power (40–80 Hz) was much smaller. In order to explore the potential effects of neuronal firing on ECoG, we developed a model to estimate ECoG power generated by different firing patterns of the underlying cortical population and studied how ECoG power varies with changes in firing rate versus the degree of synchronous firing between neurons in the population. Both an increase in firing rate and neuronal synchrony increased high-gamma power in the simulated ECoG data. However, ECoG high-gamma activity was much more sensitive to increases in neuronal synchrony than firing rate.

Neuronal oscillations in the gamma frequency range have been reported in many cortical areas, but the role they play in cortical processing remains unclear. We tested a recently proposed hypothesis that the intensity of sensory input is coded in the timing of action potentials relative to the phase of gamma oscillations, thus converting amplitude information to a temporal code. We recorded spikes and local field potential (LFP) from secondary somatosensory (SII) cortex in awake monkeys while presenting a vibratory stimulus at different amplitudes. We developed a novel technique based on matching pursuit to study the interaction between the highly transient gamma oscillations and spikes with high time-frequency resolution. We found that spikes were weakly coupled to LFP oscillations in the gamma frequency range (40−80 Hz), and strongly coupled to oscillations in higher gamma frequencies. However, the phase relationship of neither low-gamma nor high-gamma oscillations changed with stimulus intensity, even with a ten-fold increase. We conclude that, in SII, gamma oscillations are synchronized with spikes, but their phase does not vary with stimulus intensity. Furthermore, high-gamma oscillations (>60 Hz) appear to be closely linked to the occurrence of action potentials, suggesting that LFP high-gamma power could be a sensitive index of the population firing rate near the microelectrode.

Objective:

To study the role of gamma oscillations (>30 Hz) in selective attention using subdural electrocorticography (ECoG) in humans.

Methods:

We recorded ECoG in human subjects implanted with subdural electrodes for epilepsy surgery. Sequences of auditory tones and tactile vibrations of 800 ms duration were presented asynchronously, and subjects were asked to selectively attend to one of the two stimulus modalities in order to detect an amplitude increase at 400 ms in some of the stimuli.

Results:

Event-related ECoG gamma activity was greater over auditory cortex when subjects attended auditory stimuli and was greater over somatosensory cortex when subjects attended vibrotactile stimuli. Furthermore, gamma activity was also observed over prefrontal cortex when stimuli appeared in either modality, but only when they were attended. Attentional modulation of gamma power began ∼400 ms after stimulus onset, consistent with the temporal demands on attention. The increase in gamma activity was greatest at frequencies between 80 and 150 Hz, in the so-called high gamma frequency range.

Conclusions:

There appears to be a strong link between activity in the high-gamma range (80-150 Hz) and selective attention.

Significance:

Selective attention is correlated with increased activity in a frequency range that is significantly higher than what has been reported previously using EEG recordings.

The generation and presentation of tactile stimuli presents a unique challenge. Unlike vision and audition, in which standard equipment such as monitors and audio systems can be used for most experiments, tactile stimuli and/or stimulators often have to be tailor-made for a given study. Here, we present a novel tactile stimulator designed to present arbitrary spatio-temporal stimuli to the skin. The stimulator consists of 400 pins, arrayed over a 1 cm2 area, each under independent computer control. The dense array allows for an unprecedented number of stimuli to be presented within an experimental session (e.g., up to 1200 stimuli per minute) and for stimuli to be generated adaptively. The stimulator can be used in a variety of modes and can deliver indented and scanned patterns as well as stimuli defined by mathematical spatio-temporal functions (e.g., drifting sinusoids). We describe the hardware and software of the system, and discuss previous and prospective applications.

Neurons in area 3b have been previously characterized using linear spatial receptive fields with spatially separated excitatory and inhibitory regions. Here, we expand on this work by examining the relationship between excitation and inhibition along both spatial and temporal dimensions and comparing these properties across anatomical areas. To that end, we characterized the spatiotemporal receptive fields (STRFs) of 32 slowly adapting type 1 (SA1) and 21 rapidly adapting peripheral afferents and of 138 neurons in cortical areas 3b and 1 using identical random probe stimuli. STRFs of peripheral afferents consist of a rapidly appearing excitatory region followed by an in-field (replacing) inhibitory region. STRFs of SA1 afferents also exhibit flanking (surround) inhibition that can be attributed to skin mechanics. Cortical STRFs had longer time courses and greater inhibition compared with peripheral afferent STRFs, with less replacing inhibition in area 1 neurons compared with area 3b neurons. The greater inhibition observed in cortical STRFs point to the existence of underlying intracortical mechanisms. In addition, the shapes of excitatory and inhibitory lobes of both peripheral and cortical STRFs remained mostly stable over time, suggesting that their feature selectivity remains constant throughout the time course of the neural response. Finally, the gradual increase in the proportion of surround inhibition from the periphery to area 3b to area 1, and the concomitant decrease in response linearity of these neurons indicate the emergence of increasingly feature-specific response properties along the somatosensory pathway.

The detailed structure of multidigit receptive fields (RFs) in somatosensory cortical areas such as the SII region has not been investigated previously using systematically controlled stimuli. Recently (Fitzgerald et al., 2004), we showed that the SII region comprises three adjoining fields: posterior, central, and anterior. Here we characterize the RF structures of the 928 neurons that were reported in that study using a motorized oriented bar that was indented into the 12 finger pads of digits 2–5. Most (81%) of the neurons were responsive to the oriented bar stimuli, and 81% of those neurons had RFs that spanned multiple digits. Furthermore, the RFs varied greatly in size, shape, and complexity. Some RFs contained only excitatory finger pads, some contained only inhibitory pads, and some contained both types of pads. A subset of the neurons (23%) showed orientation tuning within one or more pads. The RFs spread across different digits more than within individual digits, and the responsive finger pads for a given neuron tended to cluster together within the hand. Distal and lateral finger pads were better represented than proximal and medial finger pads. Furthermore, neurons in the posterior, central, and anterior SII region fields contained different proportions of RF types. These results collectively indicate that most SII region neurons are selective for different stimulus forms either within single finger pads or across multiple pads. We hypothesize that these RFs represent the kernels underlying the representation of tactile shape.

The detailed functional organization of the macaque second somatosensory cortex (SII) is not well understood. Here we report the results of a study of the functional organization of the SII hand region that combines microelectrode mapping using hand-held stimuli with single-unit recordings using a motorized, computer-controlled tactile oriented bar. The data indicate that the SII hand region extends ~10 mm in the anteroposterior (AP) dimension, primarily within the upper bank of the lateral sulcus. Furthermore, we find evidence that this region consists of multiple functional fields, with a central field containing neurons that are driven well by cutaneous stimuli, flanked by an anterior field and a posterior field that each contain neurons that are driven well by proprioceptive stimuli and less well by cutaneous stimuli. The anterior field extends ~4 –5 mm AP, the central field extends ~3– 4 mm, and the posterior field extends ~3 mm. Data from the motorized stimulator indicate that neurons in the central field are more responsive to oriented bars, more frequently exhibit orientation tuning, and have larger receptive fields than neurons in the anterior and posterior fields. We speculate that the three putative fields play different functional roles in tactile perception; the anterior and posterior fields process information that involves both proprioceptive and cutaneous input such as sensorimotor integration or stereognosis, whereas the central field processes primarily cutaneous information.

Orientation tuning has been studied extensively in the visual system, but little is known about it in the somatosensory system. Here we investigate tuning in the second somatosensory (SII) region using a motorized stimulator that presented a small oriented bar to the 12 finger pads of digits 2–5 (D2–D5) of the macaque monkey. A subset (23%; n = 218) of the 928 SII region neurons [the same 928 neurons studied by Fitzgerald et al. (2004, 2006)] exhibited tuning, and most of these were tuned on one or two finger pads. All eight 22.5° separated orientations were represented as the preferred orientation of multiple neurons, although not necessarily in equal numbers. A measure of bandwidth indicated that tuning in the SII region is sharp and is similar to the tuning observed in visual cortical areas. In addition, two-dimensional Gaussians that were fit to the tuning curves had very high r2 values, indicating that most tuning curves are both unimodal and symmetrical with respect to their preferred orientation. Most tuned neurons had additional untuned pads, although the responsiveness of these pads tended to be less than the responsiveness of tuned pads. Neurons with multiple tuned pads tended to have similar preferred orientations on their tuned pads, which can be interpreted as evidence for integration of information across fingers or as a form of positional invariance. Finally, comparison of the tuning properties showed that there are small but significant differences between the posterior, central, and anterior fields of the SII region.

We investigate the position invariant receptive field properties of neurons in the macaque second somatosensory (SII) cortical region. Previously we reported that many SII region neurons show orientation tuning in the center of multiple finger pads of the hand and further that the tuning is similar on different pads, which can be interpreted as position invariance. Here we study the receptive field properties of a single finger pad for a subset (n = 61) of those 928 neurons, using a motorized oriented bar that we positioned at multiple locations across the pad. We calculate both vector fields and linear receptive fields of the finger pad to characterize the receptive field properties that give rise to the tuning, and we perform an additional regression analysis to quantify linearity, invariance, or both in individual neurons. We show that orientation tuning of SII region neurons is based on a variety of mechanisms. For some neurons, the tuning is explained by simple excitatory regions, simple inhibitory regions, or some combination of these structures. However, a large fraction of the neurons (n = 20 of 61, 33%) show position invariance that is not explained well by their linear receptive fields. Finding invariance within a finger pad, coupled with the previous result of similar tuning on different pads, indicates that some SII region neurons may exhibit similar tuning throughout large regions of the hand. We hypothesize that invariant neurons play an important role in tactile form recognition.

There have been three main ideas about the basic law of psychophysics. In 1860, Fechner used Weber’s law to infer that the subjective sense of intensity is related to the physical intensity of a stimulus by a logarithmic function (the Weber-Fechner law). A hundred years later, Stevens refuted Fechner’s law by showing that direct reports of subjective intensity are related to the physical intensity of stimuli by a power law. MacKay soon showed, however, that the logarithmic and power laws are indistinguishable without examining the underlying neural mechanisms. Mountcastle and his colleagues did so, and, on the basis of transducer functions obeying power laws, inferred that subjective intensity must be related linearly to the neural coding measure on which it is based. In this review, we discuss these issues and we review a series of studies aimed at the neural mechanisms of a very complex form of subjective experience—the experience of roughness produced by a textured surface. The results, which are independent of any assumptions about the form of the psychophysical law, support the idea that the basic law of psychophysics is linearity between subjective experience and the neural activity on which it is based.

Our previous studies on scalp-recorded event-related potentials (ERPs) showed that somatosensory N140 evoked by a tactile vibration in working memory tasks was enhanced when human subjects expected a coming visual stimulus that had been paired with the tactile stimulus. The results suggested that such enhancement represented the cortical activities involved in tactile-visual crossmodal association. In the present study, we further hypothesized that the enhancement represented the neural activities in somatosensory and frontal cortices in the crossmodal association. By applying independent component analysis (ICA) to the ERP data, we found independent components (ICs) located in the medial prefrontal cortex (around the anterior cingulate cortex, ACC) and the primary somatosensory cortex (SI). The activity represented by the IC in SI cortex showed enhancement in expectation of the visual stimulus. Such differential activity thus suggested the participation of SI cortex in the task-related crossmodal association. Further, the coherence analysis and the Granger causality spectral analysis of the ICs showed that SI cortex appeared to cooperate with ACC in attention and perception of the tactile stimulus in crossmodal association. The results of our study support with new evidence an important idea in cortical neurophysiology: higher cognitive operations develop from the modality-specific sensory cortices (in the present study, SI cortex) that are involved in sensation and perception of various stimuli.