Relationships between sensory responsiveness and premovement activity of quickly adapting neurons in areas 3b and 1 of monkey primary somatosensory cortex

Somatosensory inputs modulate the excitability of cerebellar-cortical interaction

OBJECTIVE

Transcranial magnetic stimulation (TMS) delivered over the cerebellum 5-7 ms prior to a stimulus over the contralateral primary motor cortex (M1) reduces the excitability of M1 output, a phenomenon termed cerebellar brain inhibition (CBI). The cerebellum receives sensory information for adaptive motor coordination and motor planning. Here, we explored through TMS whether a peripheral electrical stimulus modulates CBI.

METHODS

We studied the effect of right median nerve electrical stimulation (ES) on CBI from right cerebellum (conditioning stimulus, CS) to left M1 (test stimulus, TS) in 12 healthy subjects. The following ES-CS inter-stimulus intervals (ISIs) were tested: 25, 30 and 35 ms. CS-TS ISI was set at 5 ms.

RESULTS

We found significantly weaker CBI when the ES was delivered 25 ms (p < 0.001) and 35 ms (p < 0.001) earlier the CS over the ipsilateral cerebellum and a trend for 30 ms ES-CS ISI (p = 0.07).

CONCLUSIONS

We hypothesize that the activation of cerebellar interneurons together with intrinsic properties of Purkinje cells may be responsible of the decreased CBI when the peripheral stimulation preceded the cerebellar stimulation of 25 and 35 ms.

SIGNIFICANCE

To test the interaction between somatosensory inputs and cerebello-cortical pathway may be important in a variety of motor tasks and neuropsychiatric disorders.

Neuromuscular electrical stimulation-promoted plasticity of the human brain

The application of neuromuscular electrical stimulation (NMES) to paretic limbs has demonstrated utility for motor rehabilitation following brain injury. When NMES is delivered to a mixed peripheral nerve, typically both efferent and afferent fibres are recruited. Muscle contractions brought about by the excitation of motor neurons are often used to compensate for disability by assisting actions such as the formation of hand aperture, or by preventing others including foot drop. In this context, exogenous stimulation provides a direct substitute for endogenous neural drive. The goal of the present narrative review is to describe the means through which NMES may also promote sustained adaptations within central motor pathways, leading ultimately to increases in (intrinsic) functional capacity. There is an obvious practical motivation, in that detailed knowledge concerning the mechanisms of adaptation has the potential to inform neurorehabilitation practice. In addition, responses to NMES provide a means of studying CNS plasticity at a systems level in humans. We summarize the fundamental aspects of NMES, focusing on the forms that are employed most commonly in clinical and experimental practice. Specific attention is devoted to adjuvant techniques that further promote adaptive responses to NMES thereby offering the prospect of increased therapeutic potential. The emergent theme is that an association with centrally initiated neural activity, whether this is generated in the context of NMES triggered by efferent drive or via indirect methods such as mental imagery, may in some circumstances promote the physiological changes that can be induced through peripheral electrical stimulation.

Neostriatal Neuronal Activity Correlates Better with Movement Kinematics under Certain Rewards

This study investigated how the activity of neostriatal neurons is related to the kinematics of movement when monkeys performed visually and vibratory cued wrist extensions and flexions. Single-unit recordings of 142/236 neostriatal neurons showed pre-movement activity (PMA) in a reaction time task with unpredictable reward. Monkeys were pseudo-randomly (75%) rewarded for correct performance. A regression model was used to determine whether the correlation between neostriatal neuronal activity and the kinematic variables (position, velocity, and acceleration) of wrist movement changes as a function of reward contingency, sensory cues, and movement direction. The coefficients of determination (CoD) representing the proportion of the variance in neuronal activity explained by the regression model on a trial by trial basis, together with their temporal occurrences (time of best regression/correlation, ToC) were compared across sensory modality, movement direction, and reward contingency. The best relationship (correlation) between neuronal activity and movement kinematic variables, given by the average coefficient of determination (CoD), was: (a) greater during trials in which rewards were certain, called "A" trials, as compared with those in which reward was uncertain called ("R") trials, (b) greater during flexion (Flex) trials as compared with extension (Ext) trials, and (c) greater during visual (VIS) cued trials than during vibratory (VIB) cued trials, for the same type of trial and the same movement direction. These results are consistent with the hypothesis that predictability of reward for correct performance is accompanied by faster linkage between neostriatal PMA and the vigor of wrist movement kinematics. Furthermore, the results provide valuable insights for building an upper-limb neuroprosthesis.

Gating of tactile information through gamma band during passive arm movement in awake primates

To make precise and prompt action in a dynamic environment, the sensorimotor system needs to integrate all related information. The inflow of somatosensory information to the cerebral cortex is regulated and mostly suppressed by movement, which is commonly referred to as sensory gating or gating. Sensory gating plays an important role in preventing redundant information from reaching the cortex, which should be considered when designing somatosensory neuroprosthetics. Gating can occur at several levels within the sensorimotor pathway, while the underlying mechanism is not yet fully understood. The average sensory evoked potential is commonly used to assess sensory information processing, however the assumption of a stereotyped response to each stimulus is still an open question. Event related spectral perturbation (ERSP), which is the power spectrum after time-frequency decomposition on single trial evoked potentials (total power), could overcome this limitation of averaging and provide additional information for understanding the underlying mechanism. To this aim, neural activities in primary somatosensory cortex (S1), primary motor cortex (M1), and ventral posterolateral (VPL) nucleus of thalamus were recorded simultaneously in two areas (S1 and M1 or S1 and VPL) during passive arm movement and rest in awake monkeys. Our results showed that neural activity at different recording areas demonstrated specific and unique response frequency characteristics. Tactile input induced early high frequency responses followed by low frequency oscillations within sensorimotor circuits, and passive movement suppressed these oscillations either in a phase-locked or non-phase-locked manner. Sensory gating by movement was non-phase-locked in M1, and complex in sensory areas. VPL showed gating of non-phase-locked at gamma band and mix of phase-locked and non-phase-locked at low frequency, while S1 showed gating of phase-locked and non-phase-locked at gamma band and an early phase-locked elevation followed by non-phase-locked gating at low frequency. Granger causality (GC) analysis showed bidirectional coupling between VPL and S1, while GC between M1 and S1 was not responsive to tactile input. Thus, these results suggest that tactile input is dominantly transmitted along the ascending direction from VPL to S1, and the sensory input is suppressed during movement through a bottom-up strategy within the gamma-band during passive movement.

Tactile information processing in primate hand somatosensory cortex (S1) during passive arm movement

Motor output mostly depends on sensory input, which also can be affected by action. To further our understanding of how tactile information is processed in the primary somatosensory cortex (S1) in dynamic environments, we recorded neural responses to tactile stimulation of the hand in three awake monkeys under arm/hand passive movement and rest. We found that neurons generally responded to tactile stimulation under both conditions and were modulated by movement: with a higher baseline firing rate, a suppressed peak rate, and a smaller dynamic range during passive movement than during rest, while the area under the response curve was stable across these two states. By using an information theory-based method, the mutual information between tactile stimulation and neural responses was quantified with rate and spatial coding models under the two conditions. The two potential encoding models showed different contributions depending on behavioral contexts. Tactile information encoded with rate coding from individual units was lower than spatial coding of unit pairs, especially during movement; however, spatial coding had redundant information between unit pairs. Passive movement regulated the mutual information, and such regulation might play different roles depending on the encoding strategies used. The underlying mechanisms of our observation most likely come from a bottom-up strategy, where neurons in S1 were regulated through the activation of the peripheral tactile/proprioceptive receptors and the interactions between these different types of information.

Reprogramming movements: extraction of motor intentions from cortical ensemble activity when movement goals change

The ability to inhibit unwanted movements and change motor plans is essential for behaviors of advanced organisms. The neural mechanisms by which the primate motor system rejects undesired actions have received much attention during the last decade, but it is not well understood how this neural function could be utilized to improve the efficiency of brain-machine interfaces (BMIs). Here we employed linear discriminant analysis (LDA) and a Wiener filter to extract motor plan transitions from the activity of ensembles of sensorimotor cortex neurons. Two rhesus monkeys, chronically implanted with multielectrode arrays in primary motor (M1) and primary sensory (S1) cortices, were overtrained to produce reaching movements with a joystick toward visual targets upon their presentation. Then, the behavioral task was modified to include a distracting target that flashed for 50, 150, or 250 ms (25% of trials each) followed by the true target that appeared at a different screen location. In the remaining 25% of trials, the initial target stayed on the screen and was the target to be approached. M1 and S1 neuronal activity represented both the true and distracting targets, even for the shortest duration of the distracting event. This dual representation persisted both when the monkey initiated movements toward the distracting target and then made corrections and when they moved directly toward the second, true target. The Wiener filter effectively decoded the location of the true target, whereas the LDA classifier extracted the location of both targets from ensembles of 50–250 neurons. Based on these results, we suggest developing real-time BMIs that inhibit unwanted movements represented by brain activity while enacting the desired motor outcome concomitantly.

Cortical correlates of fitts' law

Fitts’ law describes the fundamental trade-off between movement accuracy and speed: it states that the duration of reaching movements is a function of target size (TS) and distance. While Fitts’ law has been extensively studied in ergonomics and has guided the design of human–computer interfaces, there have been few studies on its neuronal correlates. To elucidate sensorimotor cortical activity underlying Fitts’ law, we implanted two monkeys with multielectrode arrays in the primary motor (M1) and primary somatosensory (S1) cortices. The monkeys performed reaches with a joystick-controlled cursor toward targets of different size. The reaction time (RT), movement time, and movement velocity changed with TS, and M1 and S1 activity reflected these changes. Moreover, modifications of cortical activity could not be explained by changes of movement parameters alone, but required TS as an additional parameter. Neuronal representation of TS was especially prominent during the early RT period where it influenced the slope of the firing rate rise preceding movement initiation. During the movement period, cortical activity was correlated with movement velocity. Neural decoders were applied to simultaneously decode TS and motor parameters from cortical modulations. We suggest that sensorimotor cortex activity reflects the characteristics of both the movement and the target. Classifiers that extract these parameters from cortical ensembles could improve neuroprosthetic control.

Monkey primary somatosensory cortical activity during the early reaction time period differs with cues that guide movements

Vibration-related neurons in monkey primary somatosensory cortex (SI) discharge rhythmically when vibratory stimuli are presented. It remains unclear how functional information carried by vibratory inputs is coded in rhythmic neuronal activity. In the present study, we compared neuronal activity during wrist movements in response to two sets of cues. In the first, movements were guided by vibratory cue only (VIB trials). In the second, movements were guided by simultaneous presentation of both vibratory and visual cues (COM trials). SI neurons were recorded extracellularly during both wrist extensions and flexions. Neuronal activity during the instructed delay period (IDP) and the early reaction time period (RTP) were analyzed. A total of 96 cases from 48 neurons (each neuron contributed two cases, one each for extension and flexion) showed significant vibration entrainment during the early RTPs, as determined by circular statistics (Rayleigh test). Of these, 50 cases had cutaneous (CUTA) and 46 had deep (DEEP) receptive fields. The CUTA neurons showed lower firing rates during the IDPs and greater firing rate changes during the early RTPs when compared with the DEEP neurons. The CUTA neurons also demonstrated decreases in activity entrainment during VIB trials when compared with COM trials. For the DEEP neurons, the difference of entrainment between VIB and COM trials was not statistically significant. The results suggest that somatic vibratory input is coded by both the firing rate and the activity entrainment of the CUTA neurons in SI. The results also suggest that when vibratory inputs are required for successful task completion, the activity of the CUTA neurons increases but the entrainment degrades. The DEEP neurons may be tuned before movement initiation for processing information encoded by proprioceptive afferents.

Neuronal activity in monkey primary somatosensory cortex is related to expectation of somatosensory and visual go-cues

The present study was to investigate whether neuronal activity in primary somatosensory cortical areas (SI) differs when monkeys expect go-cues of different sensory modalities. Two monkeys made wrist extensions and flexions after steadily holding wrist at a center position. Movements were guided by increases in vibration to the monkey's palm (VIB), visual targets (VIS), or both in combination (COM). Neuronal activity recorded in SI during the early and late phases (i.e., the first and last 250 ms) of the instructed delay periods (IDP) were analyzed. Of 406 neurons recorded during all three paradigms, 263 (64.8%) showed significant changes in firing rates (FR) between the early and late IDP phases during either VIB or VIS trials and were selected for further analyses. The selected neurons were classified as VIB- or VIS-biased, depending on the paradigm (VIB or VIS) in which the greater FR changes occurred. Both increases and decreases in FRs were observed during the analyzed epochs. Most VIB-biased neurons showed the biggest FR changes during VIB trials and the least during VIS trials. Conversely, most VIS-biased neurons had the biggest FR changes during VIS trials and the least during VIB trials. For both VIB- and VIS-biased neurons, however, the FR changes were intermediate during COM trials. These results suggest that SI neurons play an important role in initiating/executing wrist movements. Neurons involved in wrist movements showed biases to the modality of cueing signals. Most SI neurons were biased to only one sensory modality. The expectation-related FR changes suggest different involvement by SI in movement initiation when tasks are guided by vibratory and visual signals.

Optical imaging of SI topography in anesthetized and awake squirrel monkeys

Orderly topographic maps in the primary somatosensory cortex (SI) serve as an anchor for our understanding of somatosensory cortical organization. However, this view is mostly based on data collected in the anesthetized animal. Less is known about these topographies in the awake primate. Even less is known about the relative activations of different subdivisions of SI (areas 3a, 3b, 1, and 2). Toward the goal of understanding the functional activation of SI, we conducted intrinsic signal optical imaging of areas 3b and 1 in awake squirrel monkeys. Monkeys were imaged repeatedly for a period of >2 years in awake and anesthetized states in response to vibrotactile and electrocutaneous stimuli presented to individual fingerpads. During this period, we found stable somatotopic maps in both the anesthetized and awake states, consistent with electrophysiologically recorded maps in areas 3b and 1 in the anesthetized state. In the awake animal, signal sizes were larger, but variability was greater, leading to decreased signal-to-noise ratios. Topographic activations were larger (in both area and amplitude) in the awake animal, suggesting either a less precise topography and/or more complex integration. This brings into question the role of a precise topographic map during behavior. In addition, whereas in the anesthetized animal strongest imaging signals were obtained from area 3b, in the awake animal, area 1 activation dominated over that in area 3b. Differences in relative dominance of area 3b versus area 1 suggest that inter-areal interactions in the alert animal differ substantially from that in the anesthetized animal.

Detecting neuronal activity changes using an interspike interval algorithm compared with using visual inspection

A universally accepted method for efficiently detecting neuronal activity changes (NACs) in neurophysiological studies has not been established. Visual inspection is still considered to be one of the most reliable methods, although it is limited when it is used for analyzing large quantities of data. In this study, an algorithm that considers interspike intervals (ISIs) was developed to define the onset of NACs. Two criteria, involving the mean and the standard deviation (S.D.) of the ISIs during a control period, were used in the ISI algorithm to evaluate the NACs that occurred during a detection period. The first, an ISI decrease of more than 1 S.D. from the mean ISI of the control period, proved to be an effective criterion for qualifying the increased NACs (firing rate increases). The second, an ISI increase greater than 3 S.D.s, efficiently demarcated periods of decreased NACs (firing rate decreases). Statistically significant correlations between the detection of NAC onset times by the ISI algorithm and the detection of those times by visual inspections were observed after offline analyses of recorded neuronal activity. The present results suggest that this ISI algorithm is a reliable and efficient way of defining the onset of NACs.

Neuronal activity in primary motor cortex differs when monkeys perform somatosensory and visually guided wrist movements

This study was designed to investigate how activity patterns of primary motor cortical (MI) neurons change when monkeys perform the same movements guided by somatosensory and/or visual cues. Two adult male rhesus monkeys were trained to make wrist extensions and flexions after holding a steady position during an instructed delay period lasting 0.5-2.0 s. Monkeys held against a 0.07 Nm load that opposed flexion movements. Wrist movements were guided by vibratory cues (VIB-trials), visual cues (VIS-trials), or both in combination (COM-trials). Extracellular recordings of 188 MI neurons were made during all three paradigms. Individual neurons were counted twice, once for each movement direction, yielding 376 cases. All neurons had significant task-related activity (TRA) changes relative to delay period activity during at least one of the three paradigms. TRA was analyzed to determine if it was different as a function of the sensory cue(s) that initiated movement and that specified movement endpoints. Cases were grouped by whether the TRA changes were greater in VIB- or VIS-trials; this defined their "bias". One hundred and eighteen cases (31.4%) had greater TRA changes in VIB-trials (Vb-neurons), whereas 185 (49.2%) showed greater TRA changes in VIS-trials (Vs-neurons). The remaining 73 cases (19.4%) had similar TRA changes in VIB- and VIS-trials (Nb-neurons). For Vb- and Vs-neurons, earlier TRA onsets and greater TRA changes were observed in the trials for which these neurons were biased. During the COM-trials, the TRA was intermediate. During the trials for which the activity was not biased, the TRA was the least. For Nb-neurons, no significant TRA differences were observed across paradigms. TRA changes of MI neurons may represent movement planning-related inputs from other central, presumably cortical, sources as well as contribute to motor outflow from the cortex. These data suggest that Vb- and Vs-neurons are affected differently by somatosensory- and visually related central inputs, resulting in different TRAs, even for essentially identical movements. Such differences may depend not only on the type of sensory information that initiates movement but also whether that information specifies movement endpoints or might interfere with movement monitoring.

Difference in somatosensory evoked fields elicited by mechanical and electrical stimulations: Elucidation of the human homunculus by a noninvasive method

We recently recorded somatosensory evoked fields (SEFs) elicited by compressing the glabrous skin of the finger and decompressing it by using a photosensor trigger. In that study, the equivalent current dipoles (ECDs) for these evoked fields appeared to be physiologically similar to the ECDs of P30m in median nerve stimulation. We sought to determine the relations of evoked fields elicited by mechanically stimulating the glabrous skin of the great toe and those of electrically produced P40m. We studied SEFs elicited by mechanical and electrical stimulations from the median and tibial nerves. The orientations of dipoles from the mechanical stimulations were from anterior-to-posterior, similar to the orientations of dipoles for P30m. The direction of the dipole around the peak of N20m from median nerve electrical stimulation was opposite to these directions. The orientations of dipoles around the peak of P40m by tibial nerve stimulation were transverse, whereas those by the compression and decompression stimulation of the toe were directed from anterior-to-posterior. The concordance of the orientations in ECDs for evoked fields elicited by mechanical and electrical stimulations suggests that the ECDs of P40m are physiologically similar to those of P30m but not to those of N20m. The discrepancy in orientations in ECDs for evoked field elicited by these stimulations in the lower extremity suggests that electrical and compression stimulations elicit evoked fields responding to fast surface rubbing stimuli and/or stimuli to the muscle and joint.

Somatosensory cell response to an auditory cue in a haptic memory task

Neurons in the monkey's anterior parietal cortex (Brodmann's areas 3a, 3b, 1, and 2) have been reported to retain information from a visual cue that has been associated with a tactile stimulus in a haptic memory task. This cross-modal transfer indicates that neurons in somatosensory cortex can respond to non-tactile stimuli if they are associated with tactile information needed for performance of the task. We hypothesized that neurons in somatosensory cortex would be activated by other non-tactile stimuli signaling the haptic movements--of arm and hand--that the task required. We found such cells in anterior parietal areas. They reacted with short-latency activity changes to an auditory signal (a click) that prompted those movements. Further, some of those cells changed their discharge in temporal correlation with the movements themselves, with the touch of the test objects, and with the short-term memory of those objects for subsequent tactile discrimination. These findings suggest that cells in the somatosensory cortex participate in the behavioral integration of auditory stimuli with other sensory stimuli and with motor acts that are associated with those stimuli.

Tactile feedback contributes to consistency of finger movements during typing

Touch typing movements are typically too brief to use on-line feedback. Yet, previous studies have shown that blocking tactile feedback of the fingertip of typists leads to an increase in typing errors. To determine the contribution of tactile information to rapid fine motor skills, we analyzed kinematics of the right index finger during typing with and without tactile feedback. Twelve expert touch typists copy-typed sentences on a computer keyboard without vision of their hands or the computer screen. Following control trials, their right index fingertip was anesthetized, and sentences were typed again. The movements of the finger were recorded with an instrumented glove and electromagnetic position sensor. During anesthesia, typing errors of that finger increased sevenfold. While the inter-keypress timing and average kinematics were unaffected, there was an increase in variability of all measures. Regression analysis showed that endpoint variability was largely accounted for by start location variability. The results suggest that tactile cues provide information about the start location of the finger, which is necessary to perform typing movements accurately.

Neuronal activity in somatosensory cortex of monkeys using a precision grip. I. Receptive fields and discharge patterns

Three adolescent Macaca fascicularis monkeys weighing between 3.5 and 4 kg were trained to use a precision grip to grasp a metal tab mounted on a low friction vertical track and to lift and hold it in a 12- to 25-mm position window for 1 s. The surface texture of the metal tab in contact with the fingers and the weight of the object could be varied. The activity of 386 single cells with cutaneous receptive fields contacting the metal tab were recorded in Brodmann's areas 3b, 1, 2, 5, and 7 of the somatosensory cortex. In this first of a series of papers, we describe three types of discharge pattern, the receptive-field properties, and the anatomic distribution of the neurons. The majority of the receptive fields were cutaneous and covered less than one digit, and a chi2 test did not reveal any significant differences in the Brodmann's areas representing the thumb and index finger. Two broad categories of discharge pattern cells were identified. The first category, dynamic cells, showed a brief increase in activity beginning near grip onset, which quickly subsided despite continued pressure applied to the receptive field. Some of the dynamic neurons responded to both skin indentation and release. The second category, static cells, had higher activity during the stationary holding phase of the task. These static neurons demonstrated varying degrees of sensitivity to rates of pressure change on the skin. The percentage of dynamic versus static cells was about equal for areas 3b, 2, 5, and 7. Only area 1 had a higher proportion of dynamic cells (76%). A third category was identified that contained cells with significant pregrip activity and included cortical cells with both dynamic or static discharge patterns. Cells in this category showed activity increases before movement in the absence of receptive-field stimulation, suggesting that, in addition to peripheral cutaneous input, these cells also receive strong excitation from movement-related regions of the brain.

Plasticity of primary somatosensory cortex paralleling sensorimotor skill recovery from stroke in adult monkeys

Adult owl and squirrel monkeys were trained to master a small-object retrieval sensorimotor skill. Behavioral observations along with positive changes in the cortical area 3b representations of specific skin surfaces implicated specific glabrous finger inputs as important contributors to skill acquisition. The area 3b zones over which behaviorally important surfaces were represented were destroyed by microlesions, which resulted in a degradation of movements that had been developed in the earlier skill acquisition. Monkeys were then retrained at the same behavioral task. They could initially perform it reasonably well using the stereotyped movements that they had learned in prelesion training, although they acted as if key finger surfaces were insensate. However, monkeys soon initiated alternative strategies for small object retrieval that resulted in a performance drop. Over several- to many-week-long period, monkeys again used the fingers for object retrieval that had been used successfully before the lesion, and reacquired the sensorimotor skill. Detailed maps of the representations of the hands in SI somatosensory cortical fields 3b, 3a, and 1 were derived after postlesion functional recovery. Control maps were derived in the same hemispheres before lesions, and in opposite hemispheres. Among other findings, these studies revealed the following 1) there was a postlesion reemergence of the representation of the fingertips engaged in the behavior in novel locations in area 3b in two of five monkeys and a less substantial change in the representation of the hand in the intact parts of area 3b in three of five monkeys. 2) There was a striking emergence of a new representation of the cutaneous fingertips in area 3a in four of five monkeys, predominantly within zones that had formerly been excited only by proprioceptive inputs. This new cutaneous fingertip representation disproportionately represented behaviorally crucial fingertips. 3) There was an approximately two times enlargement of the representation of the fingers recorded in cortical area 1 in postlesion monkeys. The specific finger surfaces employed in small-object retrieval were differentially enlarged in representation. 4) Multiple-digit receptive fields were recorded at a majority of emergent, cutaneous area 3a sites in all monkeys and at a substantial number of area 1 sites in three of five postlesion monkeys. Such fields were uncommon in area 1 in control maps. 5) Single receptive fields and the component fields of multiple-digit fields in postlesion representations were within normal receptive field size ranges. 6) No significant changes were recorded in the SI hand representations in the opposite (untrained, intact) control hemisphere. These findings are consistent with "substitution" and "vicariation" (adaptive plasticity) models of recovery from brain damage and stroke.

Interactions between motor commands and somatic perception in sensorimotor cortex

For many years, it has been postulated that interactions between motor commands and somatic perception in the sensorimotor cortices exist, but they have been difficult to demonstrate. Recent studies have made demonstration of this interaction easier and suggest that cortical activity related to somatic sensation and perception is modified by movement-generating mechanisms. Corollary discharge and efference copy may also play a role in motor behavior.

Mnemonic neuronal activity in somatosensory cortex

Single-unit activity was recorded from the hand areas of the somatosensory cortex of monkeys trained to perform a haptic delayed matching to sample task with objects of identical dimensions but different surface features. During the memory retention period of the task (delay), many units showed sustained firing frequency change, either excitation or inhibition. In some cases, firing during that period was significantly higher after one sample object than after another. These observations indicate the participation of somatosensory neurons not only in the perception but in the short-term memory of tactile stimuli. Neurons most directly implicated in tactile memory are (i) those with object-selective delay activity, (ii) those with nondifferential delay activity but without activity related to preparation for movement, and (iii) those with delay activity in the haptic-haptic delayed matching task but no such activity in a control visuo-haptic delayed matching task. The results indicate that cells in early stages of cortical somatosensory processing participate in haptic short-term memory.

Rhythmically firing (20-50 Hz) neurons in monkey primary somatosensory cortex: activity patterns during initiation of vibratory-cued hand movements

The activity patterns of rhythmically firing neurons in monkey primary somatosensory cortex (SI) were studied during trained wrist movements that were performed in response to palmar vibration. Of 1,222 neurons extracellularly recorded in SI, 129 cells (approximately 11%) discharged rhythmically (at approximately 30 Hz) during maintained wrist position. During the initiation of vibratory-cued movements, neuronal activity usually decreased at approximately 25 ms after vibration onset followed by an additional decrease in activity at approximately 60 ms prior to movement onset. Rhythmically firing neurons are not likely to be integrate-and-fire neurons because, during activity changes, their rhythmic firing pattern was disrupted rather than modulated. The activity pattern of rhythmically firing neurons was complimentary to that of quickly adapting SI neurons recorded during the performance of this task (Nelson et al., 1991). Moreover, disruptions of rhythmic activity of individual SI neurons were similar to those reported previously for local field potential (LFP) oscillations in sensorimotor cortex during trained movements (Sanes and Donoghue, 1993). However, rhythmic activity of SI neurons did not wax and wane like LFP oscillations (Murthy and Fetz, 1992; Sanes and Donoghue, 1993). It has been suggested that fast (20-50 Hz) cortical oscillations may be initiated by inhibitory interneurons (Cowan and Wilson, 1994; Llinas et al., 1991; Stern and Wilson, 1994). We suggest that rhythmically firing neurons may tonically inhibit quickly adapting neurons and release them from the inhibition at go-cue onsets and prior to voluntary movements. It is possible that rhythmically active neurons may evoke intermittent oscillations in other cortical neurons and thus regulate cortical population oscillations.

Striatal neuronal activity during the initiation and execution of hand movements made in response to visual and vibratory cues

Recordings were obtained from 146 neurons in the neostriatum of rhesus monkeys while they performed wrist movements in response to visual and vibratory cues. Of these, 75 putamena nd 29 caudate neurons exhibited changes in firing rate that were temporally related to the onset of the wrist movements and that began prior to movement onset. This premovement activity (PMA) usually was directionally specific, in that the magnitude or direction of change in firing rates was different during flexion trials as compared to trials involving wrist extension. PMA onset usually preceded movement onset by more than 100 ms and in most instances preceded the average onset of task-related changes in electromyographic (EMG) activity in muscles of the wrist and forelimb. For most neurons, the changes in neuronal activity that began prior to movement were maintained during movement execution. However, approximately one-third of the neurons that exhibited PMA changed their firing rate in the opposite direction, relative to their PMA and to their baseline rate of activity, once the movement began. Several other neurons either exhibited PMA only or they altered their discharge rates during movement execution but did not exhibit PMA. These observations suggest that, despite the close temporal relationship between the onset of PMA and the onset of wrist movement, the neuronal mechanisms mediating the PMA may differ from those that occur during movement execution. The PMA onset of neostriatal neurons occurred earlier in visually cued than in vibratory cued trials. These differences were statistically significant only for flexion trials, however, in which movements were made against a load and in the same direction as the palmar vibratory stimulus. For trials involving wrist extension, PMA onsets for visually cued as compared with vibratory cued trials were not statistically different. These findings contrast with data obtained previously from somatosensory cortical neurons during performance of the same behavioral task. On average, PMA in the putamen began earlier, relative to movement onset, than it did in the somatosensory cortex. Moreover, in the somatosensory cortex, PMA onset occurred earlier in vibratory cued than in visually cued trials, irrespective of movement direction (Nelson 1988; Nelson and Douglas 1989). For putamen neurons, but not for caudate or cortical neurons, the onset of PMA also occurred significantly earlier during extension trials than flexion trials, irrespective of the modality of the "go-cue".(ABSTRACT TRUNCATED AT 400 WORDS)

Sensory response enhancement and suppression of monkey primary somatosensory cortical neurons

Vibratory stimulus-related responses were recorded from monkey primary somatosensory cortical (SI) neurons while animals performed two tasks. In the movement task, vibratory stimuli served as the go-cue for wrist flexion or extension. In the no-movement task, movements normally made in response to vibratory stimuli were extinguished. Area 3a, 3b, and 1 neurons with deep receptive fields (RFs) exhibited greater stimulus-related activity during the movement task than during the no-movement task. Area 3b neurons with cutaneous RFs were similarly enhanced during the movement task, whereas area 1 neurons with cutaneous RFs were less responsive to vibratory stimuli during the movement task. These results suggest that motor-set and/or selective attention may modulate the responsiveness of SI neurons to peripheral stimuli and that changes in sensory responsiveness in SI neurons differ as a function of their cortical location and RF type.