Randall J. Nelson

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

SummaryRecordings 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 putamen and 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”. These modality-dependent and direction-dependent differences in the PMA onset of neostriatal neurons may reflect the responsiveness of these neurons to somatosensory inputs (e.g., load conditions and vibratory stimulation) that were associated with the behavioral task. These data confirm observations made by other investigators that a substantial proportion of neurons in the putamen exhibit movement-related changes in discharge rate that are initiated prior to task-related changes in EMG activity, and they further suggest that this PMA may be initiated sufficiently early to influence even the earliest task-related activity of cortical neurons.

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 (∼11%) discharged rhythmically (at ∼30 Hz) during maintained wrist position. During the initiation of vibratory-cued movements, neuronal activity usually decreased at ∼25 ms after vibration onset followed by an additional decrease in activity at ∼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.

High-frequency vibratory sensitive neurons in monkey primary somatosensory cortex : entrained and nonentrained responses to vibration during the performance of vibratory-cued hand movements

The activity of high-frequency vibratory sensitive (HFVS) neurons was recorded in monkey primary somatosensory cortex (SI) while animals performed wrist flexions and extensions in response to 57-Hz or 127-Hz palmar vibration. HFVS neurons were distinguished by their exquisite responsiveness to the higher frequency vibration (127 Hz). These neurons probably received input from Pacinian afferents. Systematic selection of HFVS neurons was made using K-means cluster analysis of neuronal firing rates during stimulating at 127 Hz and 57 Hz. HFVS neurons constituted ∼4% of all recorded cells and more frequently were found in areas 3b, 1, and 2 (∼5% of total in each area) than in area 3a (∼1%). Using circular-statistics analyses for nonuniformity of discharges over the vibratory cycle, HFVS neurons were split into two groups of vibration-entrained neurons (E1 and E2 neurons) and one group of nonentrained neurons (NE neurons). E1 neurons were entrained to vibration at both 127 Hz and 57 Hz, whereas E2 neurons were entrained only at one of these vibratory frequencies. Vibration-entrained neurons often exhibited multimodal distributions of interspike intervals (ISIs), with the modes at multiples of the period of vibration. In addition, for these neurons, ISI clusters in joint interval plots commonly had diagonal orientations that were indicative of negative serial correlations of the ISIs, a feature of extrinsically driven rhythmic activity. HFVS neurons located in areas 3a, 3b, and 1 responded to vibration onset at shorter latencies (16.5+1.6, 19.8±5.9, and 21.4±6.4 ms, respectively, during 127-Hz stimulation) than those located in area 2 (35.6±13.8 ms). These observations are consistent with a scheme in which HFVS area 2 neurons receive their inputs from more anterior areas of SI. Moreover, entrained neurons exhibited shorter response latencies than nonentrained neurons. During 127-Hz stimulation, response latencies were 17.3±3.0, 17.5±2.6, and 25.7±6.4 ms for E1, E2, and NE neurons, respectively, located in areas 3a, 3b, and 1. Thus, entrained and nonentrained HFVS neurons may belong to different hierarchical stages of information processing.

Motor Planning under Unpredictable Reward: Modulations of Movement Vigor and Primate Striatum Activity

Although reward probability is an important factor that shapes animals behavior, it is not well understood how the brain translates reward expectation into the vigor of movement [reaction time (RT) and speed]. To address this question, we trained two monkeys in a RT task that required wrist movements in response to vibrotactile and visual stimuli, with a variable reward schedule. Correct performance was rewarded in 75% of the trials. Monkeys were certain that they would be rewarded only in the trials immediately following withheld rewards. In these trials, the animals responded sooner and moved faster. Single-unit recordings from the dorsal striatum revealed modulations in neural firing that reflected changes in movement vigor. First, in the trials with certain rewards, striatal neurons modulated their firing rates earlier. Second, magnitudes of changes in neuronal firing rates depended on whether or not monkeys were certain about the reward. Third, these modulations depended on the sensory modality of the cue (visual vs. vibratory) and/or movement direction (flexions vs. extensions). We conclude that dorsal striatum may be a part of the mechanism responsible for the modulation of movement vigor in response to changes of reward predictability.

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

SummaryWhen monkeys make wrist movements in response to vibration of their hands, primary somatosensory (SI) cortical neurons that adapt quickly to the vibratory stimulus often exhibit two temporally separate types of activity. Initially, these neurons respond to the stimulus. They then cease discharging, only to resume firing prior to the movement. This activation, cessation and reactivation occurs even though the sensory stimulus remains on until after the movement is begun. The first change in activity is most likely related to sensory input. The second, which has been called premovement activity, may have a sensory component as well as one related to the upcoming movement. We wanted to test the hypothesis that the premovement activity exhibited when vibration is present represents both a reactivation of a neurons vibratory response and the premovement activity that normally occurs when vibration is absent. We also wanted to determine if area 3b and 1 quickly adapting (QA) neurons show similar or different activity patterns during the initiation and execution of sensory triggered wrist movements. Four monkeys were trained to make wrist flexion and extension movements in response to vibratory stimuli delivered to the handle which the animals used to control the behavioral paradigm. Two of the four monkeys also made similar wrist movements following visual cues. We found that the premovement activity of QA neurons located in area 1 (but not area 3b) is comprised of a sensory-related component as well as a movement-related component. The magnitude of these individual components differs in relationship to a neurons receptive field type, the movement direction and the external force imposed on the stimulated forelimb. Premovement activity of area 3b and area 1 QA neurons occurs at the same time prior to movement, regardless of whether visual or vibratory cues are used to trigger wrist movements. This activity occurs at about the same time as others have observed elevations in the threshold for tactile perception, suggesting that premovement activity and changes in sensory responsiveness before movement may be related. These and previous findings are used to construct a model which may predict the firing patterns of SI QA neurons during behavioral tasks. These findings also suggest that areas 3b and 1 may have different roles in processing task-related somatosensory information.

Ensuring due process in the IACUC and animal welfare setting: Considerations in developing noncompliance policies and procedures for institutional animal care and use committees and institutional officials

Every institution that is involved in research with animals is expected to have in place policies and procedures for the management of allegations of noncompliance with the Animal Welfare Act and the U.S. Public Health Service Policy on the Humane Care and Use of Laboratory Animals. We present here a model set of recommendations for institutional animal care and use committees and institutional officials to ensure appropriate consideration of allegations of noncompliance with federal Animal Welfare Act regulations that carry a significant risk or specific threat to animal welfare. This guidance has 3 overarching aims: 1) protecting the welfare of research animals; 2) according fair treatment and due process to an individual accused of noncompliance; and 3) ensuring compliance with federal regulations. Through this guidance, the present work seeks to advance the cause of scientific integrity, animal welfare, and the public trust while recognizing and supporting the critical importance of animal research for the betterment of the health of both humans and animals.—Hansen, B. C., Gografe, S., Pritt, S., Jen, K.‐L. C., McWhirter, C. A., Barman, S. M., Comuzzie, A., Greene, M., McNulty, J. A., Michele, D. E., Moaddab, N., Nelson, R. J., Norris, K., Uray, K. D., Banks, R., Westlund, K. N., Yates, B. J., Silverman, J., Hansen, K. D., Redman, B. Ensuring due process in the IACUC and animal welfare setting: considerations in developing noncompliance policies and procedures for institutional animal care and use committees and institutional officials. FASEB J. 31, 4216–4225 (2017). www.fasebj.org

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.

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.

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.

Response to Protocol Review scenario: should no good deed go unpunished?

enucleated one eye and treated that animal appropriately. Only then did she contact the weekend call veterinarian. She had the expertise and approval to anesthetize mice and treat wounds, just not under these circumstances. After the fact, the veterinarian agreed in principle with the treatment. However, the injuries were not so severe that immediate treatment precluded veterinary consultation. This is a question of timing. Had Stein contacted the veterinarian first, the situation would have been less problematic for the IACUC. The Guide for the Care and Use of Laboratory Animals reminds us that “[a] veterinarian or the veterinarian’s designee must be available to expeditiously assess the animal’s condition, treat the animal, investigate unexpected death, or advise on euthanasia”1. Hindsight is 20/20, but if the veterinarian had been consulted before the mouse was treated, she could and used an elaborate emotional story to try to sway the IACUC into believing that she was doing a good deed.