Dose and Behavioral Context DependentInhibition of Movement and Basal

Ganglia Neural Activity by��9-Tetrahydrocannabinol During

Spontaneous and Treadmill LocomotionTasks in Rats

L.H. SHI, F. LUO, D.J. WOODWARD, AND J.Y. CHANG*Department of Physiology and Pharmacology, Wake Forest University, School of Medicine, Winston-Salem,

North Carolina 27157

KEY WORDS locomotion; basal ganglia; rats; limb movement; electrophysiology;��9-THC

ABSTRACT The effects of ��9-tetrahydrocannabinole (��9-THC) on locomotor ac-tivities and related basal ganglia neural responses were investigated in rats. A multiple-channel, single unit recording method was used to record neuronal activity in the dorsallateral striatum, the globus pallidus, the subthalamic nucleus, and the substantia nigrapars reticulata simultaneously during spontaneous movement and treadmill locomotion.��9-THC treatment (0.05–2.0 mg/kg, i.p.) dose-dependently decreased spontaneous mo-tor activity and altered walking patterns in treadmill locomotion in that stance time wasincreased and step number was decreased. In parallel with the behavioral effects,��9-THC treatment inhibited neural activity across all four basal ganglia areas recordedduring both motor tests. Further, this inhibition of basal ganglia neural activity wasbehavioral context-dependent. Greater inhibition was found during resting than duringwalking periods in the treadmill locomotion test. ��9-THC treatment also changed firingpatterns in the striatum and globus pallidus. More neurons in these regions dischargedin an oscillatory pattern during treadmill walking with ��9-THC, and the oscillatoryfrequency was similar to that of the step cycle. Synchronized firing patterns were foundin few basal ganglia neurons in the control condition (�1%). Synchronized firing pat-terns increased during the treadmill resting phase after ��9-THC treatment, but stillrepresented a very small proportion of the total neural population (1.9%). The drugtreatment did not change neural responses to the tone cue proceeding treadmill loco-motion. This study demonstrates dose-dependent inhibitory effects of cannabinoid in-jection on motor activity. This effect may be related to the behavioral context-dependentinhibition observed in the basal ganglia system where CB1 receptors are denselydistributed. Synapse 55:1–16, 2005. © 2004 Wiley-Liss, Inc.

INTRODUCTION

Marijuana (Cananbis sativa) is one of the oldestknown psychoactive substances (Maugh, 1982) and re-mains a widely used drug. ��9-tetrahydrocannabinole(��9-THC), the major psychoactive ingredient of mari-juana (Harris et al., 1977), has been the focus of muchresearch to determine the mechanism of drug action inthe central nervous system. To date, two subtypes ofcannabinoid receptors, CB1 and CB2, have been iden-tified (Howlett et al., 1990; Matsuda, 1990; Munro,1993), although CNS responses to cannabinoids are

mediated exclusively by CB1 receptors (Felder andGlass, 1998; Pertwee, 1995). Cannabinoid receptors inthe brain are densely distributed in the basal ganglia

Contract grant sponsor: National Institutes of Health (NIH); Contract grantnumbers: NS-43441, DA-10370 (to J.Y.C.), NS-19608 (to D.J.W.).

*Correspondence to: J.Y. Chang, Department of Physiology and Pharmacol-ogy, Wake Forest University, School of Medicine, Winston-Salem, NC 27157.E-mail jchang@wfubmc.edu

Received 21 May 2004; Accepted 12 August 2004

DOI 10.1002/syn.20088

Published online in Wiley InterScience (www.interscience.wiley.com).

SYNAPSE 55:1–16 (2005)

© 2004 WILEY-LISS, INC.

and the cerebellum, among other regions (Herkenhamet al., 1990; Moldrich and Wenger, 2000; Tsou et al.,1998). Both of these regions are closely associated withthe regulation and coordination of motor activity(Herkenham et al., 1990, 1991). In the striatum (STR),CB1-immunoreactivity is observed not only in mediumspiny neurons, but also in small fiber bundles thatbecome larger as they approach the globus pallidus(GP). Cannabinoid receptors in the substantia nigrapars reticulata (SNr), the entopeduncular nucleus, andthe GP appear to be localized primarily on striatalterminals, since cannabinoid receptor binding in theseregions is significantly reduced following striatal le-sions (Herkenham et al., 1991). The abundant presenceof CB1 receptors provides an anatomical substrate forthe action of cannabinoids in these regions. Numerousreports have indicated that cannabinoids modulate thefunction of the striatonigral (Miller and Walker, 1995;Sanudo-Pena et al., 1996), striatopallidal (Miller andWalker, 1996), and subthalamonigral (Sanudo-Pena etal., 1997) pathways.

Cannabinoids exert complex effects on motor func-tions. In rodents, cannabinoids inhibit motor activityand produce catalepsy (Grunfeld et al., 1969; Holtzmanet al., 1969). Biphasic effects of cannabinoid treatmenton motor activity have been observed in which lowdoses of cannabinoid increased and high doses de-creased spontaneous movement (Carlini et al., 1970;Davis et al., 1972). However, a recent study showed areversed dose–response relationship with motor activ-ity such that a low dose inhibited and a moderate doseincreased motor activity (Sanudo-Pena et al., 2000).These contradictory results may be due to the differentspecies and cannabinoid compounds used in the exper-iments, as well as to the differing experimental proto-cols.

CB1 receptors in the basal ganglia system may beinvolved in pathophysiological processes of a variety ofmovement disorders, and drugs manipulating CB1 re-ceptors have potential therapeutic value. For example,CB1 antagonists enhanced the anti-parkinsonian ac-tion of D2 agonist (Di Marzo et al., 2000) and the CB1antagonist could reduce levodopa-induced dyskinesia(Fox et al., 2002). Other studies suggested that canna-binoids might have therapeutic benefits for Tourette’ssyndrome and dystonia (Consroe et al., 1986; Muller-Vahl et al., 1999). To date, electrophysiological study ofcannabinoid effects on basal ganglia neural activityhas been performed only on anesthetized animals.Miller and Walker (1996, 1998) reported that pallidalcannabinoid receptors mediated inhibition of spontane-ous activity in the GP. Cannabinoid treatment in-creased neural firing rates in the SNr neurons (Millerand Walker 1995). The behavioral significance of theseneural activity changes, however, is not clear.

A combination of behavioral tests with electrophysi-ological analysis is a unique approach to understand-

ing the effect of cannabinoids on motor functions. Inthe present study, we employed a multiple-channel,single unit recording technique to study cannabinoid-induced basal ganglia neural activity and locomotionchanges simultaneously. This method allows us to fur-ther examine the motor effect of different doses of can-nabinoid and to determine behavioral context-depen-dent neural responses in multiple basal gangliaregions. The goal of this study is to gain a new insightinto the basal ganglia neural mechanism underlyingthe motor effect of cannabinoid.

MATERIALS AND METHODSAnimals

Eleven adult male Sprague-Dawley rats weighing350–400 g were used in the experiment. Animals werehoused individually under a reversed dark/light cycle(lights off from 0700 to 1900) for 7 days before surgery.Animals were treated in accordance with the U.S. Pub-lic Health Service Guide for the Care and Use of Lab-oratory Animals. The experiments were approved bythe Institute Animal Care and Use Committee of WakeForest University, Health Sciences.

Surgical procedures

Rats were anesthetized with ketamine (100 mg/kg,i.m.) and xylazine (10 mg/kg, i.m.). An array of eightstainless steel Teflon-insulated microwires (50 �m di-ameter, NB Labs, Denison, TX, and Biographics, Inc.,Winston-Salem, NC), soldered to connecting pins on aheadstage, were stereotaxically lowered bilaterally intodorsal lateral striatum (STR), globus pallidus (GP),subthalamic nucleus (STN), and substantia nigra parsreticulata (SNr). The stereotaxic coordinates used totarget these structures were: 0.5 mm anterior tobregma (A), 3.5 mm lateral (L) to the midline, and3.7 mm ventral (V) to the surface of cortex for the STR;–1.0 mm A, 3.2 mm L, and 6.0 mm V for the GP;–3.5 mm A, 2.5 mm L, and 7.3 mm V for the STN; and–5.4 mm A, 2.0 mm L, and 7.8 mm V for the SNr,according to the atlas of Paxinos and Watson (1986). Inaddition, four ground wires were positioned about2 mm ventral to the cortical surface. The headstagewas secured onto the cranium with dental acrylic andwith skull screws serving as anchors. Animals receivedenrofloxacin (2.5 mg/kg i.m.) before surgery to preventinfection. Animals were housed individually and al-lowed to recover from surgery for at least 10 daysbefore being subjected to the experiment.

Behavioral testsSpontaneous motor activity

Spontaneous motor activity was measured in a 33 �33 cm plastic behavioral chamber over a 60-min exper-imental session. Six infrared emitters, mounted 10 cmapart and 3.5 cm above the floor, were used to detect

2 L.H. SHI ET AL.

the rat’s movement (Shi et al., 2004). Ventilation andcomputer fans provided background masking noise andexperiments were performed in dim light in the morn-ing (2 h into the dark cycle). The rat was placed in thebehavioral chamber and a headset for 64 electrodeswas gently connected via a lightweight cable to a mo-tor-assisted 80 channel commutator to record neuralactivity in the basal ganglia regions. The neural andmotor activities were recorded over a 60-min session.The number of beam breaks detected by the infraredsensors served as the measure of spontaneous move-ment. The number of beam breaks for each infraredsensor was inspected to detect any large numbers ofrepetitive beam breaks that can be due to artifactsrelated to breathing, whisking, or grooming. Spontane-ous motor activity was defined as spontaneous movingfrom one infrared sensor to another. Video records(33 ms resolution) were used to monitor rat motor ac-tivity and to detect the repetitive beam breaks due tobreathing and whisking.

Before the start of the spontaneous motor activityexperiment, each rat was habituated daily to the openfield apparatus for a week. Rats were placed in thebehavior chamber for 1 h each day and data werecollected after consistent numbers of beam breaks (lessthan 15% difference in beam counts) were obtainedfrom three sequential sessions. Daily experimental ses-sions began about 2 h into the animals’ dark cycle andlasted about 3 h. Rats received a 0.3 ml saline injection(i.p.) 20 min before each control session to control forthe influence of stress caused by injection. The finalsession with only a saline injection served as the con-trol session. Incremental doses of ��9-THC were theninjected 20 min before each of the experimental ses-sions (0.05 mg, 0.1 mg, 0.5 mg, 1 mg, and 2 mg/kg i.p.).The doses of ��9-THC were given in order of increasingconcentration.

To reduce tolerance development during ��9-THCtreatment, at least two drug-free sessions were in-cluded between successive ��9-THC sessions. The ef-fects of cannabinoid treatment on locomotion and neu-ral activity was assessed in comparison with thecontrol sessions. Different doses of ��9-THC weretested to create dose–response curves for spontaneousmotor activity.

Treadmill locomotion task

Treadmill locomotion sessions were carried out aftercompletion of the spontaneous movement task (Shi etal., 2004). A transparent acrylic box (length 37 � width19 � height 39 cm) was mounted on a conveyer beltdriven by a motor with adjustable speed. The beltserved as the floor of the chamber. Rats were trained towalk at a moderate pace on the treadmill with a con-stant speed (12 cm/s). The treadmill cycle consisted of a20-sec walking phase triggered by an auditory cue anda random 10–30-sec resting period. The cue tone was

presented 1.5 sec before the onset of treadmill walkingand each session lasted 60 min. Control data werecollected after 3–4 days of training when rats exhibiteda smooth walking pattern. Rats received a 0.3 ml salineinjection (i.p.) 20 min before each control session. ��9-THC was injected (2.0 mg/kg i.p.) 20 min before theexperimental sessions. Video records (33 ms resolution)were used to monitor and analyze behavior during thetreadmill sessions.

Electrophysiological recording

Extracellular recordings of the four basal gangliaareas were performed at least 10 days after surgery byconnecting a headstage plug and a lightweight cablebetween a commutator and the implanted microwireassembly. The commutator was assisted by a motorthat senses the direction of the rat’s movement and wasfree to turn as necessary, permitting unrestrictedmovement of the rat in the behavioral chamber. Neu-roelectric signals were passed from the headset assem-blies to programmable amplifiers, filters (0.5 and5 kHz) and a multichannel spike-sorting device. Asmany as 62 neurons from the STR, GP, STN, and theSNr were monitored simultaneously from 64 microelec-trodes. Spike activity, treadmill operation, and infra-red beam breaks were recorded (1 ms resolution) andcontrolled with the data acquisition software Magnet(Biographics, Winston-Salem, NC). Spike train activitywas analyzed offline with the PC-based programsStranger (Biographics) and Nex (Plexon, Dallas, TX).

Drugs

��9-THC was obtained under ethanol (Sigma,St. Louis); 2% pluronic acid in 200 proof ethanol wasadded to the ��9-THC solution at a 4:1 ratio. Salinewas then dropped into the mixture until the solutionturned white. The solution was then blown in the dark-room with a nitrogen stream until the ethanol wastotally evaporated. Saline was then added to make thefinal solutions (1 mg/ml or 0.1 mg/ml when 0.05 mg/kgwas needed).

Histology

At the conclusion of the final experimental session,each animal was subjected to the same anesthesia as insurgery. A positive current of 10–20 �A was passedthrough selected microwires for 10–20 sec to depositiron ions. The animal was then sacrificed and perfusedwith 4% paraformaldehyde solution. Coronal sections(45 �m thick) were cut through the STR, GP, STN, andSNr and mounted on slides. Incubation of the mountedsections in a solution containing 5% potassium ferri-cyanide/10% HCl revealed iron deposits (recordingsites) in the form of blue dots. Boundaries of the fourbrain areas were assessed with reference to the ratbrain atlas of Paxinos and Watson (1986).

EFFECTS OF ��9-THC 3

Data analysis

Data were processed offline with Stranger and Nexsoftware for basic analysis and graphics. MatLab(MathWorks, Natick, MA) and SPSS (Chicago, IL) wereused for advanced statistics. Data were analyzed froma single representative session from each rat.

In the spontaneous locomotion task, each sessionconsisted of active and quiescent phases. Motor behav-ior was quantified by calculating the total number ofbeam breaks over the 1-h session, and the total numberof the beam breaks were compared between controlsessions and sessions with each dose of ��9-THC. P �0.05 in Student’s t-test indicated significant compari-sons.

In the treadmill locomotion test, frame-by-framevideo analysis (33 ms resolution) of limb movementwas conducted in both control and ��9-THC treatmentsessions. Two limb movement events were identified byvideo analysis: footfall, defined as the initial paw con-tact with the ground (soft contact), and foot off, definedas the onset of the swing phase (when the paw left theground) (Cohen and Gans, 1975). To allow a more de-scriptive analysis, the step cycle was divided into twomajor phases, stance (paw down) and swing (paw up),defined by the onsets of footfall and foot off, respec-tively (West et al., 1990). All timestamps for limbmovement were compiled and entered into the data fileas event nodes for behavioral and electrophysiologicalanalyses.

To identify the effects of ��9-THC on basal ganglianeural responses, only the 2 mg/kg ��9-THC group waschosen for electrophysiological data analysis since themost evident behavioral effect was found at this dose.In the spontaneous movement test, the session wasdivided into 20-sec segments and beam breaks of eachsegment were counted. Segments without beam breakswere counted as quiescent and segments with morethan five beam breaks were counted as active seg-ments. The mean firing rates of each neuron and theaverage firing rates of neurons within each region werecalculated for the active phases and quiescent phasesin both control and ��9-THC treatment sessions andcomparisons were made between these sessions by Stu-dent’s t-test with a significant difference level of P �0.05.

Within each treadmill session, the mean firing ratesin walking and resting phases were calculated sepa-rately. A sliding-window method was used to measureand compare neural activity changes between walkingand rest phases and between control and ��9-THCtreatment conditions. Counts per bin (0.1 sec bin size)of single neurons during treadmill locomotion werecalculated for each trial. The results were then ex-ported to MatLab. Neural activity was then calculatedby a time window (typically 1 sec, but in some cases250 ms for tone responses with narrow peaks) moving

Fig. 1. Effects of ��9-THC on spontaneous motor activity. A: Spon-taneous motor activity was dose-dependently inhibited by 30–75%with ��9-THC (0.05 to 2 mg/kg). B: Color-coded motor activity incontrol and (C) after 2 mg/kg ��9-THC. Each line represents one ratduring its 60-min experimental session. The number of photo beambreaks is color-coded (high number in red, low number in blue). Asignificant decrease in motor activity was found with 2 mg ��9-THCtreatment (n �11).

4 L.H. SHI ET AL.

at 0.1-sec steps across the duration of the treadmillwalking phase.

The following two arbitrary criteria were used con-currently to detect significant changes in neural firingrates: 1) firing rate changes (increase or decrease) ofgreater than 20% during the time periods measuredcompared with the baseline firing rate measured 10 secbefore the initiation of treadmill walking; 2) analyses ofdifferences in at least three successive steps of themoving window reached a statistically significant level(P � 0.05, Student’s two-tailed t-test). These measuresaccounted for slow and fast firing neurons to show bothsubstantial (100%) and significant changes.

Power spectrum density analysis revealed oscillatoryneural activity. This analysis was carried out duringtreadmill walking and resting phases in both controland ��9-THC treatment sessions. Power spectrum den-sity during each of these phases was computed with a20 Hz or 10 Hz band and a 256 or 128 frequency. Theformula for power spectrum computation is as follows:

Bin size � 1/(2 � maximum frequency)

Number of bin � 2 � number of frequency value

Autocorrelograms were calculated during walking andresting phases to corroborate the results of power spec-trum analysis. The number of neurons that showedoscillatory discharges was compared between controland ��9-THC treatment groups. A chi-square test withP � 0.05 was considered significant.

Principal component analysis (PCA) is a statisticalmethod for reduction and interpretation of multivari-ate data. PCA is essentially a method for recognizingthe information that is distributed across a set of par-tially correlated variables into an equal number of un-correlated principal components. Most of the variancerelated to significant redundant information in thepopulation is consolidated within the first few compo-nents. Valid neurons, selected on the basis of quality ofwaveform and noise-free recording, were used in eachbrain region (with 1 sec bin size) to calculate the PCAwith software from the Nex program (Plexon), and theweighted firing rate of the PCA1 in each brain regionwas sent to MatLab to calculate the time-based powerspectrum.

Cross-correlation analysis was performed during thetreadmill experiment in both control and ��9-THCtreatment conditions. One neuron was selected as thereference neuron and all other neurons recorded withinthat same session were defined as partner neurons forthe cross correlograms. The time of occurrence ofspikes from the reference neuron was set as the 0-sectime point and the partner neuron’s firing within 1 secbefore or after each reference neuron’s spike was plot-

Fig. 2. Neural activity changes associated with active and quies-cent phases of spontaneous motor activity. A: Ratemeter showing theneural activity in the basal ganglia during spontaneous motor activ-ity. Increased neural activity was found in all four basal gangliaregions during the active phase. Increased neural activity was coin-cident with the high number of beam breaks labeled by ticks at thebottom line of the plot. B: Average firing rates in basal ganglia regionsduring active and quiescent phases of the spontaneous motor test.Increases in firing rates were observed in all four basal gangliaregions (mean � SD, **P � 0.01, Student’s t-test).

Fig. 3. Effects of ��9-THC on basal ganglia neural activity duringspontaneous motor activity. Decreases in neural firing rate wereobserved in all four basal ganglia regions following 2 mg/kg ��9-THCinjection. There was no difference in degree of inhibition betweenactive and quiescent phases (**P � 0.01, Student’s t-tests. Active andquiescent phases with ��9-THC vs. control condition).

EFFECTS OF ��9-THC 5

ted using a 1-ms bin size. The significance level of thecross-correlograms was tested using a 95% confidencelevel. Raster plots of the correlograms were examinedcarefully to eliminate any artifacts associated withnonneuronal noise.

RESULTSEffects of ��9-THC on spontaneous

motor activity

When treated with the lowest dose of ��9-THC,0.05 mg/kg, three out of four rats tested exhibitedreduced motor activity. One rat at this low dosagedisplayed a slight increase in motor activity. On av-erage, there was an 18% decrease in beam breaksduring the 1-h experimental session at this dose. Atthe 0.1 mg/kg dose and higher, ��9-THC producedsignificant decreases in motor activity. The effect of��9-THC on spontaneous motor activity was dose-dependent, from 18% inhibition at 0.05 mg/kg to 75%at 2.0 mg/kg (Fig. 1A). Locomotor activity recoveredto the pretreatment levels during the control ses-sions between the drug treatment sessions. Thespontaneous motor activity patterns of the 11 rats inthe control condition, as measured by the number ofbeam breaks, are depicted in Figure 1B with color-coded illustration. Rats typically displayed high lev-els of exploratory behavior early in the session, asdemonstrated by high numbers of beam breakswithin the first 10 min of the session, and thenbecame relatively quiet. Some rats resumed highlevels of activity later in the session. The spontane-ous motor activity patterns of the same 11 ratstreated with 2 mg/kg ��9-THC are depicted in Fig-ure 1C. A significant decrease in spontaneous motoractivity was found at this dose of ��9-THC.

Effects of ��9-THC on basal ganglia neuralactivity during spontaneous movement test

Extracellular single neuron recording was performedin the four basal ganglia regions during spontaneousmotor activity testing. A total of 99 neurons in the STR,83 neurons in the GP, 55 neurons in the SNr, and 36neurons in the STN were recorded from the 11 rats. Inthe control condition, significant increases in firingrates were observed in all four recording regions duringthe active movement phase. The mean firing rates ofactive and quiescent phases in each basal ganglia re-gion are summarized in Figure 2B.

In parallel with the inhibition of motor activity, ��9-THC treatment (2 mg/kg i.p.) significantly decreasedthe mean firing rates in all four basal ganglia regionsduring both active and quiescent phases relative to thecontrol session (Fig. 3). A similar degree of ��9-THC-induced inhibition was found in both the active andquiescent phases in all the basal ganglia regions tested(Fig. 3).

Effects of ��9-THC on treadmill locomotion

A regular walking pattern with smooth, active for-ward steps could be established after 3–4 training ses-sions in the control condition. Rats were mostly quietduring the 10–30-sec random resting period. Slightmovement occurred occasionally during the resting pe-riod, especially in the first few trials as rats exploredthe new environment, but such movement was notcomparable with the continuous, active walking duringthe treadmill walking phase.

��9-THC treatment (2 mg/kg i.p.) markedly alteredrats’ treadmill walking patterns. Drug-treated rats dis-played an irregular walking pattern during the tread-mill walking phase, with periods of motionlessness fol-lowed by periods of larger catching up steps. The

Fig. 4. Effects of ��9-THC on stance and swing times of front and rear limbs during treadmillwalking. A: Step cycle increased and step number decreased after ��9-THC treatment. Both stance (B)and swing (C) times were increased with 2 mg/kg ��9-THC, but only stance time reached significance(*P � 0.05, **P � 0.01, Student’s t-test).

6 L.H. SHI ET AL.

catching up was triggered by the tail touching the rearwall of the treadmill chamber. To quantify this irregu-lar walking pattern, video analysis of limb movementwas made for eight rats during the treadmill walkingphase in both control and ��9-THC treatment condi-tions. In the control condition, the average step cyclewas 0.96 � 0.33 sec. For the forelimb, the means of

stance (when the paw remained on the floor) and swing(when the paw was in the air) phases were 0.72 sec and0.23 sec, respectively. For the hindlimbs, the means forstance and swing were 0.80 sec and 0.16 sec, respec-tively. In the ��9-THC treatment condition, the aver-age step cycle increased to 1.12 � 0.29 sec (P � 0.01 vs.control session, Student’s two-tailed t-test, Fig. 4). ��9-THC-treated rats needed to take larger steps with alonger step cycle to catch up with the treadmill, whichmoved at a constant speed. The means of forelimbstance and swing phases were increased to 0.88 sec and0.25 sec, respectively, with ��9-THC treatment (P �0.01 vs. control session for stance time). The means ofhindlimb stance and swing phases were increased to0.93 sec and 0.18 sec, respectively (P � 0.01 vs. controlsession for stance time, Fig. 4). The number of stepsdecreased from 20 to 18 per trial by ��9-THC treat-ment (P � 0.05, Fig. 4A).

Effect of ��9-THC on neural responses duringtreadmill locomotion task

A total of 291 neurons from 11 rats were recorded inthe treadmill experiment (100 in STR, 88 in GP, 62 inSNr, and 41 in STN). Two major neural responses wereanalyzed in both the control and ��9-THC treatmentconditions. One was associated with the auditory cueand the other was observed during treadmill locomo-tion. Peak responses immediately following the tonecue were observed in all four basal ganglia regions(Fig. 5A). In the control condition, responses rangedfrom 14% of the population in the SNr to about 30% ofthe population in the STR. ��9-THC treatment did notchange neural responses to the tone in any of the fourbasal ganglia regions (Table I).

More prevalent neural responses were found duringthe treadmill locomotion phase. More than half of neu-rons in all recorded regions altered their firing ratesduring the treadmill walking phase in the control con-dition. The most robust response was observed in theSTN, where 90.2% of recorded neurons altered theirfiring rates during treadmill walking. Table I summa-rizes the neuronal responses associated with tone and

Fig. 5. Neural responses during tone presentation and treadmilllocomotion. A: Raster and perievent histogram showing different neu-ral responses to the cue tone (200 ms duration) presented 1.5 secbefore treadmill onset. An STR neuron (left) decreased and an STNneuron (right) increased firing rate upon tone presentation (0 secpoint). B: Different neuronal responses in the basal ganglia regionsduring the treadmill walking phase (from 0–20 sec timestamp). Tran-sient responses at the start and termination of treadmill locomotion ina GP neuron (upper left). A sizable drop in spike discharge occurredimmediately at the start and termination of treadmill walking (ar-rows). An STR neuron exhibited an initial peak of discharge andgradually increased spike activity during the treadmill walking phase(upper right). An SNr neuron increased its firing rate throughout thetreadmill walking period (lower left). An STN neuron increased itsfiring rate with an initial peak (lower right). C: Average firing rates ofeach basal ganglia region during walking and resting phases. Meanfiring rates increased in all regions during the walking phase (**P �0.01 vs. resting phase, Student’s t-test).

EFFECTS OF ��9-THC 7

walking in control and ��9-THC treatment conditions.Examples of neural responses are shown in Figure 5B.The vast majority of neural responses during treadmillwalking were excitatory (increased firing rate) and onlya few neurons decreased their firing rates during tread-mill walking. The GP had the highest number of neu-rons with inhibitory responses (�10% of total neurons).However, even in the GP far more neurons (nearly50%) exhibited excitatory responses during treadmilllocomotion. In general, the mean firing rate of all thebasal ganglia regions increased significantly during thetreadmill walking phase relative to the resting phase(Fig. 5C).

��9-THC treatment affected the mean firing rates ofbasal ganglia neurons during the treadmill experi-ment. Figure 6 summarizes these mean firing ratechanges in each basal ganglia region during treadmillwalking and resting phases. Similar to what had been

found in the spontaneous motor activity test, ��9-THCtreatment generally inhibited basal ganglia neuronsduring both walking and resting phases. In addition,��9-THC elicited different degrees of inhibition duringthe walking vs. resting phases. A higher degree ofinhibition was found during the resting than the walk-ing phase in all four basal ganglia regions (Fig. 6),especially in the STR and GP. In these two regions,differences not only in the mean firing rate, but also inthe number of inhibitory neurons were found betweenresting and walking phases in ��9-THC-treated rats.��9-THC treatment significantly decreased the num-ber of neurons exhibiting inhibitory neural responsesduring the walking phase in comparison with the rest-ing phase in the STR and the GP (Fig. 7).

��9-THC treatment elicited more limb movement-related responses in the STR and GP. Most of theseresponses were excitatory responses (Table II). De-tailed analysis of these responses revealed that a dis-proportional inhibition of neural activity during restvs. walking phases by ��9-THC may be the result ofthe appearance of limb movement-related neural re-sponses during the walking phase (see below).

Effects of ��9-THC treatment on basal ganglianeuronal activity related to limb movement

As described above, ��9-THC caused a prolonged stepcycle during treadmill locomotion. Offline video analysiswas done to timestamp when the forelimb and hindlimbtouched and left the floor. These data were used to createa perievent histogram to reveal the neural responses tolimb movement. A total of 82 neurons in the STR, 74neurons in the GP, 49 neurons in the SNr, and 38 neu-rons in the STN were analyzed to identify limb-relatedneural responses during treadmill walking.

Table II summarizes the limb movement-related neu-ral responses in each basal ganglia region in both controland ��9-THC treatment conditions. Although large num-

TABLE I. Basal ganglia neural responses during the treadmill task in control and ��9-THC treatment conditions

Brainarea

Total numberof neurons

Toneresponding

neurons

Treadmill walking

Totalresponding

neurons Initiation Excitatory InhibitoryInhibitory/Excitatory Termination

N% oftotal N

% oftotal N

% oftotal N

% oftotal N

% oftotal

Ratio �

100 N% oftotal

STR 100 control 33 33.0 74 74.0 28 28.0 61 61.0 4 4.0 6.6 9 9.0THC 33 33.0 87* 87.0 34 34.0 76* 76.0 6 6.0 7.9 8 8.0

GP 88 control 19 21.6 57 64.8 23 26.1 41 46.6 10 11.4 24.4 7 8.0THC 16 18.2 74** 84.1 23 26.1 55* 62.5 7 7.9 12.7 12 13.6

SNr 62 control 10 16.1 49 79.0 25 40.3 39 62.9 4 6.4 10.2 3 4.8THC 12 19.4 50 80.6 24 38.7 46 74.2 1 1.6 2.2 3 4.8

STN 41 control 13 32.0 37 90.2 25 61.0 36 87.8 1 2.4 2.8 0 0THC 13 32.0 38 92.7 27 65.8 38 92.7 1 2.4 2.6 4 9.8

In both control and ��9-THC treatment conditions, more STR neurons were responsive to the tone cue preceding the start of treadmill walking, and more STNneurons responded during the treadmill walking phase. Total responding neurons refers to the number of neurons that responded at least once at different phasesof treadmill walking. Initial responses refer to the transient neural responses that occurred at initiation of walking. Excitatory and inhibitory responses refer to thecontinuous responses during the 20-sec treadmill walking phase. Termination responses refer to the transient responses at the termination of the treadmill walkingphase. There were significantly more neurons in the STR and GP responding to treadmill walking after ��9-THC treatment (chi-square test, P � 0.01 for GP; P �0.05 for STR), and in these two brain regions the number of neurons with excitatory responses increased after ��9- THC treatment (chi-square test, P � 0.05).

Fig. 6. ��9-THC treatment (2.0 mg/kg) inhibited basal gangliaactivity during walking and resting phases of the treadmill experi-ment. ��9-THC caused a more potent inhibition during the restingthan the walking period (**P � 0.01, ��9-THC vs. control. ##P � 0.01,resting vs. walking phase with ��9-THC).

8 L.H. SHI ET AL.

Fig. 7. ��9-THC changed the typeof neural responses during treadmilllocomotion. A: Populations of neu-rons exhibited excitatory, inhibitory,or no responses during treadmillwalking and resting phases. Overall,inhibitory neurons greatly outnum-bered excitatory neurons. Signifi-cantly more inhibitory neurons wereobserved in the resting phase in theSTR and GP (**P � 0.01, *P � 0.05,chi-square test). This difference innumber of inhibitory neurons wasdue to the different action of ��9-THC during walking vs. restingphases. B: An STR neuron with dif-ferent responses to ��9-THC treat-ment during walking and restingphases. A slightly increased firingrate was observed during the tread-mill walking phase in the control con-dition (from 0–20 sec, top panel).��9-THC inhibited responses duringthe resting phase (–10 to 0 sec and20–30 sec, middle panel). A similarneural response pattern appearedfollowing ��9-THC treatment (bot-tom panel). Comparison of the con-trol (solid line), the ��9-THC (dashedline), and the recovery after ��9-THCsessions (dotted line) reveals a selec-tive decrease in firing rate during theresting phase in the ��9-THC session(P � 0.01, ANOVA). C: A similar re-sponse pattern, selective inhibition of��9-THC during resting phase, wasobserved in this GP neuron.

EFFECTS OF ��9-THC 9

bers of treadmill locomotion-related neurons were found,there were fewer neurons with limb movement-relatedresponses in the control condition. ��9-THC treatmentelicited more limb movement-related neural responses inall four regions (Table II, Fig. 8), but increases in limbmovement-related neurons only differed significantly inthe STR and GP (chi-square test, P � 0.05).

Oscillatory and synchronized neural activityin the basal ganglia regions during

treadmill locomotion

The oscillatory firing pattern was measured bypower spectrum analysis during treadmill walking andresting phases. In the control condition only a fewneurons displayed oscillatory neural firing patternsduring the treadmill walking phase (�5%). ��9-THCtreatment increased the number of neurons displaying

an oscillatory firing pattern in all basal ganglia regionsstudied, but the increase was significant only in theSTR and GP (Table III, chi-square test, P � 0.05).Examples of the oscillatory firing pattern are shown inFigure 9. The oscillation frequency is around 1 Hz,similar to the step cycle of treadmill walking. A time-based power spectrum, using weighted firing rate gen-erated from the principal component analysis (PCA 1),revealed that this oscillatory firing pattern occurredonly during treadmill walking (not resting) in the STRand GP (Fig. 9C,D). As to the question of whether allthe limb movement-related neurons oscillated duringwalking phase, the results showed that many limbmovement-related neurons did not oscillate in the con-trol condition during walking, whereas significantlymore limb movement-related neurons exhibited oscil-latory firing patterns with ��9-THC treatment (TableIV). This dissociation between limb movement and os-cillatory neural responses is depicted in Figure 10.

Synchronized activity was analyzed by the pairwisecross-correlograms method for all simultaneously re-corded neurons of the basal ganglia regions. Correlatedactivity was found between neurons in the followingtwo categories: 1) intraregional cross-correlations (be-tween neurons within the same region); 2) interre-gional correlations (between neurons in different re-gions). In the control condition, among a total of 3,502pairs of neurons from 311 neurons recorded, only 48(1.4%) and 37 (1%) significant cross-correlations wereobserved between neuron pairs during treadmill walk-ing and resting phase, respectively. No significant dif-ference was detected between these two phases. In the��9-THC treatment condition, 66 (1.9%) and 63 (1.8%)significant cross-correlations were observed betweenneuron pairs during walking and resting phases, re-spectively. In general, ��9-THC treatment resultedin more neural correlation during resting phase(P � 0.05 vs. control condition, chi-square test). Withregard to each type of cross-correlation (there were 10types of intrainterregional cross-correlations from fourbasal ganglia regions, e.g., cross-correlation betweenSTR and GP, STN and SNr neurons, etc.), there wasno significant difference between the control and��9-THC-treated conditions for each type of thesecross-correlations (Fig. 11).

TABLE II. Neural responses associated with limb movement in each basal ganglia regionduring treadmill walking in control and ��9-THC treatment conditions

Brain regions

STR GP SNr STN

Num % Num % Num % Num %

Control 18 22.0 7 9.4 3 6.1 2 5.2THC 30* 36.6 16* 21.6 8 16.3 4 10.5total 82 74 49 38

Neurons in different regions showed different response percentages to limb movement during treadmill walking incontrol and ��9-THC conditions. Neurons were generally more responsive to limb movement after ��9-THC treatment,but increases were significant only in the STR and GP (chi-square test, P � 0.05).

Fig. 8. Limb movement-related neural activity induced by ��9-THC treatment. A: Activity of an STR neuron in relation to limbmovement in control (top) and ��9-THC treatment (bottom) condi-tions. The timestamp of the front paw touching the floor was used asa reference event to create this raster and perievent histogram. Neu-ral activity did not change in control conditions. Biphasic neuralresponses were found. Spike activity first increased and then de-creased around the event of paw contact at 0 sec. B: An example oflimb movement-related neural responses in a GP neuron. In this case,��9-THC treatment induced a robust response before paw contact.

10 L.H. SHI ET AL.

Histological localization of recording sites

Potassium ferricyanide staining revealed the record-ing sites as blue dots in the STR, GP, STN, and SNr.Figure 12 shows the locations of recording sites in-cluded in this report.

DISCUSSION

Cannabinoid receptors are localized on the cell bod-ies and neuronal processes of striatal neurons thatproject to the SNr and GP (Herkenham et al., 1991).They have also been found in the terminals of thesubthalamo-nigral glutaminergic pathway. In situ hy-bridization revealed low to moderate levels of CB1 re-ceptor mRNA in the majority of the neurons in the STN(Mailleux and Vanderhaeghen, 1992). Such abundantcannabinoid receptors in the basal ganglia may ac-count, at least in part, for their effects on motor activ-ity. Early studies demonstrated a biphasic effect ofcannabinoids on spontaneous movement: low doses ofcannabinoids caused increases in motor activity, whilehigh doses inhibited motor activity (Abel, 1970; Daviset al., 1972; Sulcova et al., 1998). Presently, uniformand dose-dependent inhibition of spontaneous motoractivity was found when animals were treated with��9-THC from 0.05 to 2.0 mg/kg. The lack of an exci-tatory effect of the low dose of ��9-THC here may bedue to the differences in animal species (rats vs. mice)or chemical components (��9-THC vs. anandamide)used. Our finding, however, is in line with other reportsindicating a similar dose-dependent decrease in spon-taneous motor activity and force-time trajectory (Carli-nin et al., 1970; McLaughlin et al., 2000).

We recently developed a rat model to evaluate motoractivity in which unilateral DA-lesioned rats display aki-nesia during treadmill walking (Chang et al., 2003). Thistreadmill model was used in this study to evaluate theeffects of cannabinoid treatment on locomotion. The loco-motor behavior of rats treated with ��9-THC was unlikethat of DA-lesioned rats. DA-lesioned rats displayed aki-nesia and were pushed back to the rear wall of the tread-mill chamber and then struggled to catch up with thetreadmill. On the other hand, ��9-THC treatment in-duced an irregular movement characterized by a shortperiod of immobility followed by large catch-up stepswhen the tail of the animal touched the wall of the cham-

ber. As a result, stance time (when the paw was in contactwith the floor) in ��9-THC-treated rats was increasedsignificantly in comparison with the control condition,when steps were smooth and regular. This is in sharpcontrast with DA depletion conditions in which swingtime (when the paw was in the air) is decreased (unpubl.obs.). Different limb movement patterns between dopa-mine depletion and ��9-THC treatment conditions sug-gest that ��9-THC treatment does not induce akinesia intreadmill locomotion. A common mechanism may accountfor the effects of ��9-THC on both the spontaneous andtreadmill locomotion tests. In both conditions the rat isreluctant to move, resulting in an 80% reduction in spon-taneous movement and sensory triggered (tail touch),involuntary treadmill walking with altered steps.

In this and our previous studies, tight coupling of basalganglia neural activity with motor activity was observedin control conditions (Shi et al., 2004). Significant in-creases in discharge rates across the basal ganglia wereobserved during both spontaneous and treadmill move-ment. This uniform increase in activity does not directlyfit the classical model of basal ganglia thalamocorticalpathways (Alexander et al., 1990). Rather, these findingssuggest a regulatory role of the basal ganglia to provideactive background for information processing in basalganglia thalamocortical pathways (Shi et al., 2004). Basalganglia neural responses during motor activity observedin these studies provide a control for studying drug andpathophysiological actions on movement and relatedbasal ganglia neural responses.

Information on basal ganglia neural responses tocannabinoids in behaving animals is lacking. Thepresent study employed a multiple-site, single-unit re-cording method to study the neural and behavioralresponses to cannabinoid treatment in awake, freelymoving rats. In line with the robust decrease in motoractivity, ��9-THC treatment at the most behaviorallyeffective dose (2 mg/kg) significantly reduced neuralactivity in all four basal ganglia regions studied.Neurons inhibited greatly outnumbered those excitedby ��9-THC (Fig. 7) and average firing rates weredecreased by ��9-THC in the four basal ganglia regions(Fig. 6). These results demonstrate pronounced canna-binoid inhibition of basal ganglia activity at a dose thatinhibits motor activity.

TABLE III. Effects of ��9-THC on oscillatory firing patterns in the basal gangliaduring treadmill walking

Brain regions

STR GP SNr STN

Num % Num % Num % Num %

Control 5 5.0 1 1.1 3 4.8 1 2.4THC 27 27.0** 8* 9.1 3 4.8 0 0After THC 4 4.0 0 0 2 3.2 1 2.4total 100 88 62 41

Fewer neurons exhibited oscillatory firing in the control than the ��9-THC condition in the STR and GP.*P � 0.05, **P � 0.01, chi-square test when compared with control.

EFFECTS OF ��9-THC 11

Fig. 9. ��9-THC induced oscillatory firing patterns in the basal gan-glia. A: Example neural responses in STR during control and ��9-THCtreatment conditions. Neural activity increased with treadmill walkingduring both control and ��9-THC treatment conditions (top). Powerspectrum analysis revealed a peak �1 Hz during the treadmill walkingphase in the ��9-THC treatment condition (middle). An autocorrelogramshows multiple peaks at 1-sec intervals during treadmill walking in the��9-THC treatment condition (bottom). B: An example GP neuron dis-playing a similar oscillatory firing pattern during the treadmill walking

phase with ��9-THC. C: Time-based power spectrum analysis of ensem-ble neural activity in the STR. The analysis is based on the principalcomponent 1 from six neurons simultaneously recorded in the STRduring the treadmill test. A low-frequency oscillation appeared duringthe treadmill walking phase in the ��9-THC treatment condition (indi-cated by arrows). D: The same analysis performed in five simultaneouslyrecorded GP neurons revealed oscillatory firing during the treadmill onphase with ��9-THC treatment.

The STR is an input station of the basal ganglia withboth excitatory cortical and dopaminergic nigral affer-ents. A limited number of in vitro studies have inves-tigated cannabinoid effects on striatal neural activity.Cannabinoids can inhibit both inhibitory GABA (Hoff-man and Lupica, 2001; Szabo et al., 1998) and excita-tory glutamate release (Gerdeman and Lovinger, 2001;Huang et al., 2001; Robbe et al., 2001) in the synapsesof medium spiny neurons of the STR. The net outcomeof these opposite effects on neural activity is unclear. Itmay depend on the cannabinoid dose and interaction ofthe STR with other brain structures in the context ofongoing behavioral activity (discussed below). Theoverall decrease in striatal firing rate may be due to thedominant inhibition of cortical glutamatergic input tothe striatum as suggested by in vitro studies (Gerde-man and Lovinger, 2001; Huang et al., 2001; Robbe etal., 2001). Such inhibition could be the result of directinhibition of cortical neurons or of presynaptic effectson the cortical projection terminals.

The GP (in rat) is part of an indirect pathway whichreceives striatal GABAergic input and sends inhibitoryGABAergic projections to the STN. Abundant CB1 re-ceptors are located in the afferent striatal terminals inthe GP. Behavioral studies have indicated that the GPplays a critical role in cannabinoid regulation of motorfunction. Intra-GP cannabinoid injection induced ipsi-lateral turning in the rat (Sanudo-Pena and Walker,1998), and bilateral injection of ��9-THC into the GPcould induce catalepsy in the rat (Pertwee andWichens, 1991). An in vitro slice demonstration ofGABA uptake blockade in the GP by ��9-THC suggeststhat such effects may be mediated via effects onGABAergic transmission (Maneuf et al., 1996). Extra-cellular recording in anesthetized rats showed thatsystemic and local cannabinoid administration inhib-ited spontaneous firing rates of GP neurons (Miller andWalker, 1996, 1998). This finding is similar to ourfindings in awake, behaving rats. Cannabinoid inhibi-tion of GP neurons may be due to accumulation ofGABA in the synaptic cleft or to dampened excitatoryinput from the STN.

The STN is a pivotal structure in the basal gangliaand the only structure comprised of neurons with anexcitatory neurotransmitter. CB1 receptors and theirmRNA have been found in the STN (Mailleux and

Vanderhaeghen, 1992). To our knowledge, there is noelectrophysiological study of STN neural response tocannabinoids. Only an indirect study has been done toexamine the effects of cannabinoids on SNr responsesto STN activation. In that study, WIN55.212-2, a can-nabinoid agonist, blocked SNr neural responses tobicuculline-induced STN activation (Sanudo-Pena andWalker, 1997). Another study demonstrated ipsilateralturning behavior with intra-STN cannabinoid agonistinjection (Miller et al., 1998). Marked inhibition wasfound in the STN in our study. The mechanism ofcannabinoid inhibition is unknown. It could be theresult of inhibition of glutamate release from corticalinputs, or intrinsic inhibitory effects. Cannabinoidssuppress inward sodium current and N-type calciumcurrent in neuroblastoma cells, which may account forsome of their inhibitory effects in the CNS (Caulfieldand Brown, 1992; Mackie and Hill, 1992; Turkanis etal., 1991a,b). Furthermore, potassium A currents areactivated by cannabinoids in the hippocampus (Dead-wyler et al., 1993). The alteration in the activation ofthe A current maintains the cell near the resting mem-brane potential. This action of cannabinoids couldcounteract the effects of fast, transient, depolarizingaction potentials in the hippocampus and other brainregions. Cannabinoid inhibition of STN neurons maypartially account for the inhibition in its projectionareas, the GP and SNr, as observed in this study.

The SNr, together with the internal GP, are thebasal ganglia output stations and neural activitychanges in these regions are thought to be responsiblefor a variety of movement disorders such as Parkin-son’s disease and dystonia. Previous studies have re-ported an increase in spontaneous neural activity inthe SNr by local and systemic administration of can-nabinoid agonists in anesthetized rats (Miller andWalker, 1995; Tersigni and Rosenberg, 1996). Localinjection of SR 141716A, a cannabinoid antagonist,significantly decreased SNr neural activity, suggestingthat endogenous cannabinoids may exert tonic regula-tion of striato-nigral transmission by inhibiting GABArelease into the SNr (Tersigni and Rosenberg, 1996;Wallmichrath and Szebo, 2002a). In an in vitro study,Wallmichrath and Szebo (2002b) demonstrated thatcannabinoid agonism decreased the amplitude of inter-nal capsule stimulation-induced IPSPs, but did not

TABLE IV. Relationship between limb movement-related and oscillatory neuronsin control and ��9-THC treatment conditions

Brain regions

STR GP SNr STN

limb osc limb osc limb osc limb osc

Control 18 5** 12 1 3 3 2 1THC 30 27 25 8 8 3 4 0

��9-THC treatment increased limb movement associated and oscillatory neuronal activity in the STR and GP. Not alllimb movement responsive neurons were oscillatory. The proportion of oscillatory neurons increased significantly in theSTR with ��9-THC treatment.**Chi-square test, P � 0.01 when compared with control.

EFFECTS OF ��9-THC 13

influence spontaneous IPSPs or the neural firing ratein the SNr. Other studies, however, found that thecannabinoid receptor agonist WIN 55.212-2 could in-duce hyperpolarization and inhibit spontaneous firingof SNr neurons in whole cell patch clamp recording,suggesting postsynaptic cannabinoid inhibition of SNrneurons (Chan et al., 1998). The inhibition of SNrneurons observed in the present study could be the

result of such a postsynaptic inhibitory cannabinoidaction or a decreased excitatory input from the STN.The implication of this nigral inhibition on motor ac-tivity is not clear. In theory, a decrease in basal gangliaoutput is associated with hyperkinetic conditions suchas dystonia while an increase in basal ganglia GABAer-gic output is associated with hypokinetic conditionssuch as Parkinson’s disease. However, experimentaldata vary substantially with regard to SNr neural re-sponses. Increased, decreased and unchanged firingrates have been reported in these conditions (Hutchi-son et al., 2003; Rohlfs et al., 1997; Sanderson et al.,1986; Vitek, et al., 1999; Wichmann et al., 1999). It isnoteworthy that in addition to neural firing rateschanges, changes in firing patterns in the basal gangliaalso play a critical role in regulating motor function(Brown, 2003; Raz et al., 2000).

Interestingly, the effects of cannabinoids on basalganglia neural activity were dependent on the rats’behavioral state. ��9-THC exerted more inhibitionduring the resting than the walking condition in thetreadmill locomotion test. This differential degree ofinhibition may be the result of behaviorally dependentactivation of synaptic connections. It is possible thatthe motor cortex is activated during forced treadmillwalking and thus increases the release of glutamate in

Fig. 10. Dissociation of limb movement relatedneural activity and oscillatory firing. An examplecase with similar limb movement-related neuralresponses exhibited with different oscillatory firingpatterns is shown. An STR and GP neuron wererecorded simultaneously during the treadmill test.They both exhibited robust limb movement-relatedactivity when the front paw left the floor at time 0(top). However, power spectrum and autocorrelo-gram analyses revealed that the STR neuron hadan oscillatory firing pattern, whereas the GP neu-ron did not (middle and bottom).

Fig. 11. Cross-correlation between basal ganglia neurons during con-trol and ��9-THC treatment conditions. Cross-correlograms of 3,502pairs were analyzed. These pairs were between D (dorsal striatum), G(GP), S (SNr), and T (STN). ��9-THC treatment increased cross-corre-lated neurons in the resting phase of the treadmill test. However, thisincreased population accounted for �2% of total population.

14 L.H. SHI ET AL.

cortico-striatal and cortico-subthalamic terminalswhich may to some extent offset the inhibitory effectsof ��9-THC. The present finding that ��9-THC greatlyincreased limb movement-related neural responses inthe STR, the region with direct sensorimotor corticalinput, is consistent with this hypothesis.

Oscillatory firing patterns were increased by ��9-THCtreatment in the STR and GP. The frequency of oscilla-tion is very similar to that of step circle (�1 Hz). Thesimilar frequency and coincident increases in oscillatoryand limb movement-related firing in the STR and GPstrongly suggest that the oscillation is the result of in-creased limb movement-related neural responses. It isnot clear why some limb movement-related neurons didnot exhibit oscillatory firing patterns, whereas other neu-rons with similar limb movement-related activity in thesame animal did. It may be related to the precise codingof a subset of limb movement by individual neurons.According to classical theory, normal information flow inthe basal ganglia consists of parallel, separate processes(Alexander et al., 1990). Basal ganglia malfunction isthus expected to disrupt such parallel processing andcause “cross-talk” between neurons of different basal gan-glia regions. A study in primates revealed an increase insynchronized basal ganglia neural activity in parkinso-nian conditions (Raz et al., 2000). In the present study, asignificant increase in synchronized activity among basalganglia neurons was found after ��9-THC treatment;however, such a small proportion of synchronized neu-rons (�2%) calls into question the functional significanceof this increase.

Basal ganglia integrate sensorimotor processes andauditory tone-induced responses. In the present study,��9-THC did not affect sensory responses at the dosethat significantly changed movement and motor-re-lated neural activity. This finding suggests that canna-binoid treatment in the basal ganglia does not appre-ciably affect sensory processing.

In summary, electrophysiological and behavioral ef-fects of ��9-THC were studied in rats. ��9-THC induceddose-dependent inhibition of spontaneous movement andaltered treadmill walking patterns. Uniform inhibitionwas found in all the major basal ganglia regions in bothspontaneous and treadmill locomotion tests. The degreeof inhibition was dependent on the behavioral context.That is, a higher degree of inhibition was found duringresting than walking. Limb movement-related neural fir-ing and oscillatory firing were increased by ��9-THCtreatment. The observed broad inhibition of basal ganglianeural activity and motor functions suggests a sedativeeffect of cannabinoid agonism on basal ganglia neuralprocessing and motor functions.

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