Beta Frequency Oscillations in the Subthalamic Nucleus Are Not Sufficient for the Development of Symptoms of Parkinsonian Bradykinesia/Akinesia in Rats

Christina Behrend Swan; Derek J Schulte; David T Brocker; Warren M Grill

doi:10.1523/ENEURO.0089-19.2019

. 2019 Oct 21;6(5):ENEURO.0089-19.2019. doi: 10.1523/ENEURO.0089-19.2019

Beta Frequency Oscillations in the Subthalamic Nucleus Are Not Sufficient for the Development of Symptoms of Parkinsonian Bradykinesia/Akinesia in Rats

Christina Behrend Swan ^1,², Derek J Schulte ¹, David T Brocker ¹, Warren M Grill ^1,^3,^✉

PMCID: PMC6817717 PMID: 31540998

Abstract

Substantial correlative evidence links the synchronized, oscillatory patterns of neural activity that emerge in Parkinson’s disease (PD) in the beta (β) frequency range (13–30 Hz) with bradykinesia in PD. However, conflicting evidence exists, and whether these changes in neural activity are causal of motor symptoms in PD remains unclear. We tested the hypothesis that the synchronized β oscillations that emerge in PD are causal of symptoms of bradykinesia/akinesia. We designed patterns of stimulation that mimicked the temporal characteristics of single unit β bursting activity seen in PD animals and humans. We applied these β-patterned stimulation patterns along with continuous low-frequency and high-frequency controls to the subthalamic nucleus (STN) of intact and 6-OHDA-lesioned female Long–Evans and Sprague-Dawley rats. β-Patterned paradigms were superior to low-frequency controls at induction of β power in downstream substantia nigra reticulata (SNr) neurons and in ipsilateral motor cortex. However, we did not detect deleterious effects on motor performance across a wide battery of validated behavioral tasks. Our results suggest that β frequency oscillations (BFOs) may not be sufficient for the generation of bradykinesia/akinesia in PD.

Keywords: β band oscillations, bradykinesia, Parkinson’s disease

Significance Statement

We explored whether a causal link exists between the synchronized, 13–30 Hz (β band) oscillations that emerge in Parkinson’s disease (PD) and symptoms of bradykinesia/akinesia. The results provide not only for a better understanding of disease pathophysiology but also offer insights into the development of improved and novel treatments for PD. Our study suggests that β frequency oscillations (BFOs) are not causally related to bradykinesia/akinesia in PD.

Introduction

The execution of voluntary movement relies on the coordinated generation, refinement, and relay of neural signals by a network of cortical and subcortical structures. In Parkinson’s disease (PD) deterioration of the dopaminergic nigrostriatal projection from death of substantia nigra compacta (SNc) neurons disrupts this network and engenders symptoms of bradykinesia/akinesia, rigidity, rest tremor, and postural instability (Dauer and Przedborski, 2003; Alves et al., 2008; Holtbernd and Eidelberg, 2012). Loss of nigral dopaminergic input to the striatum results in significant changes in neural firing rates and patterns including increases in burst and oscillatory firing, as well as excessive synchronization of firing within and across nuclei in the cortico-basal ganglia loop (Brown et al., 2001; Levy et al., 2002; Kühn et al., 2005). While the neural mechanisms underlying the motor symptoms of PD are unknown, particular attention has been given to synchronized, oscillatory neural activity occurring in a frequency band of 13–30 Hz, termed the β band, as these oscillations seem to be correlated with symptoms of bradykinesia in PD (Kühn et al., 2008). Indeed, treatments that improve bradykinesia, including levodopa administration or deep brain stimulation (DBS), also disrupt the β band oscillations that are seen throughout the cortico-basal ganglia loop, including in the subthalamic nucleus (STN; Levy et al., 2002; Kühn et al., 2006, 2008; Dorval et al., 2010; Delaville et al., 2015). While the origin of β oscillatory activity in PD is still unknown, the STN (Plenz and Kital, 1999; Gatev et al., 2006; Stein and Bar-Gad, 2013), the striatum (McCarthy et al., 2011), and the motor cortex (Yamawaki et al., 2008) have been postulated to be involved in the generation of β band oscillations in PD. Regarding the STN, STN DBS at 20 Hz in PD patients reduced finger tapping rates (i.e., increased bradykinesia) as compared to 0 Hz and 50 Hz DBS (Chen et al., 2007). Such observations suggest a causal link between STN β band oscillations and symptoms of bradykinesia and akinesia in PD. Conversely, animal models of PD demonstrated emergence of bradykinetic/akinetic symptoms before development of β band oscillations (Degos et al., 2009). Chronic administration of a dopamine receptor blocker to intact rats resulted in an immediate increase in akinetic symptoms, but an increase in β oscillatory power in primary sensorimotor cortex was not seen until the fourth day of treatment (Degos et al., 2009). If symptoms of bradykinesia/akinesia can be dissociated from β band oscillations, these oscillations may be an epiphenomenon.

We tested the hypothesis that a causal relationship exists between STN β band oscillations and symptoms of bradykinesia/akinesia in PD. We designed stimulation patterns to mimic the oscillatory burst firing seen in single STN neurons in human PD patients (Levy et al., 2002) and animal models of PD (Mallet et al., 2008). We applied these stimulation patterns to a biophysically-based computational model of the intact cortico-basal ganglia-thalamic loop (Kumaravelu et al., 2016) and assessed changes in β power in the activity of model globus pallidus internus (GPi) neurons. We then applied the stimulation patterns to the STN of healthy (intact) and parkinsonian (lesioned) rats and quantified entrainment of downstream neurons and effects on motor performance. The stimulation patterns increased β frequency power (BFP) in both the computational model and healthy rats. However, we did not detect deleterious effects of the patterns on rat motor performance. Our findings challenge the notion of a causal link between STN β band oscillations and symptoms of bradykinesia/akinesia in PD and suggest that STN β band oscillations are not sufficient for the development of these symptoms in PD.

Materials and Methods

We first applied patterns of stimulation confirmed to induce β oscillatory power in a model cortico-basal ganglia circuit to the STN of intact rats. We used intact rats to apply our patterns to a “naive substrate,” as intact rats lack excessively synchronized endogenous β oscillations that would confound any BFP generated by our patterns (Fig. 1). In the second phase of our study we applied our patterns to 6-OHDA-lesioned animals treated with levodopa doses titrated to disrupt endogenous BFP. The goal of this approach was to exploit the changes in circuit dynamics that occur in PD while controlling the source of BFP. The Duke University Institutional Animal Care and Use Committee approved all animal care and experimental procedures. Animals were housed in Duke University Division of Laboratory Animal Resources managed housing with unrestricted access to food and water except as detailed below for food reward-motivated behavioral tasks.

. Experimental design to assess the effects of betaergic DBS on neural activity and motor function. (1) Different temporal patterns of STN stimulation were applied in random order to intact rats. The effects on downstream SNr single units and M1 ECoG were recorded to quantify induced β. Rats performed a variety of behavioral tasks during betaergic stimulation to assess impact of stimulation on bradykinesia/akinesia. (2) Rats were then unilaterally lesioned via injection of 6-OHDA into the MFB. Betaergic stimulation patterns were again applied in random order, and the effect on SNr single units was recorded. The performance of 6-OHDA-lesioned rats was assessed in all behavioral tasks with and without 130-Hz stimulation. (3) Finally, 6-OHDA-lesioned rats were treated with levodopa, and the effect of betaergic stimulation patterns on SNr units was recorded. The performance of levodopa-treated 6-OHDA rats in the adjusting steps and skilled forelimb reaching task was quantified during different patterns of betaergic stimulation. LD = levodopa, IBF = Intra-Burst Frequency, BEF = Burst Envelope Frequency.

Chronic electrode implants

Anesthesia was induced in 10 female Long–Evans and 25 female Sprague Dawley rats (250–350 g) using a mixture of 7% sevoflurane and 2 l min⁻¹ O₂ and maintained during surgery using 2.5–3.5% sevoflurane in 1–1.5 l min⁻¹ O₂. Paw pinch withdrawal, heart rate, and peripheral capillary oxygen saturation were monitored to ensure appropriate anesthetic depth. All cranial implants were performed using a Kopf stereotaxic frame with stereotaxic coordinates determined from a rat brain atlas (Paxinos and Watson, 2005). Rats were implanted unilaterally with a 23-gauge cannula in the medial forebrain bundle [MFB; from bregma: anterior-posterior (AP) –2.0 mm, medial-lateral (ML) ±2.0 mm; from brain surface: dorsal-ventral (DV) –7.0 mm]; a four-channel stimulating microelectrode array (MEA) in the STN (AP –3.6 mm, ML ±2.6 mm; from brain surface: DV: –6.8 to –7.2 mm); and a 16-channel recording MEA in the substantia nigra reticulata (SNr; AP –5.8 mm, ML ±2.3 mm; from brain surface: DV –6.8 to –7.2 mm). The STN stimulating MEA was comprised of 2 × 2 75 μm 10-kΩ platinum-iridium (Pt-Ir) electrodes with an interelectrode spacing of 300 μm (Microprobes for Life Science). Intraoperative recordings using a single 0.5-MΩ tungsten microelectrode were conducted to confirm the stereotaxic location of the STN before placement of the 2 × 2 MEA in the STN. The SNr recording MEA was comprised of 4 × 4 125-μm 0.5-MΩ Pt-Ir electrodes with interelectrode spacing of 250 μm (Microprobes). Intraoperative recordings were performed as the 4 × 4 array was advanced to confirm the depth of SNr. All unilaterally placed implants were localized to the same hemisphere. Nine stainless steel bone screws were affixed to the skull. Three of these bone screws were placed over bilateral primary motor cortex (M1; AP +2.5 mm, ML ±2.5 mm) and unilateral primary somatosensory cortex (S1; AP –1.0 mm, ML 3.0 mm). Electrocorticogram (ECoG) signals were measured by wiring these bone screws to an additional connector in the headcap. A bone screw over the cerebellar cortex served as a reference for neural recordings. Dental acrylic was used to secure all implants to the bone screws. Animals recovered for one week before any additional procedures were performed.

Stimulation parameters

We designed different temporal patterns of electrical stimulation to mimic the oscillatory burst firing seen in PD patients and parkinsonian animal models, including both regular and irregular “β” bursting paradigms. We applied three regular and one irregular β bursting paradigms, low (15, 20, 25 Hz) and high (225 Hz) frequency continuous stimulation patterns, which served as “control” patterns to the bursting paradigms, during behavioral tasks and neural recordings, yielding a total of eight experimental stimulation patterns. The regular β bursting paradigms were non-varying patterns with fixed burst envelope frequency (BEF), intraburst frequency (IBF), and number of pulses per burst (Fig. 1). We selected BEFs of 15, 20, and 25 Hz, which corresponded approximately to the peak frequencies of β oscillatory activity of STN neurons seen in parkinsonian non-human primates (Moran et al., 2012), human PD patients (Kühn et al., 2008; Bronte-Stewart et al., 2009; Eusebio and Brown, 2009), and 6-OHDA-lesioned rats (Sharott et al., 2005), respectively. For each BEF we used an IBF of 225 Hz and five pulses per burst based on analysis of published recordings of STN single unit burst firing in PD patients (Levy et al., 2000, 2002). An IBF of 225 Hz is consistent with IBFs in STN neurons of PD patients, which have been seen to range from 75 to over 200 Hz (Birdno and Grill, 2008; Gale et al., 2009; Welter et al., 2011).

We designed the irregular β bursting paradigm through computational optimization using a genetic algorithm (Brocker et al., 2017). The irregular β bursting paradigm was parameterized as a binary string. Each element represented a time bin of 1.5 ms. A “0” represented no stimulation and a “1” represented stimulation. The optimization objective was to determine the appropriate arrangement of 1s and 0s that maximized β band oscillatory power in the firing of model GPi neurons in the computational model of the intact basal ganglia (See section Computational model). The fitness function was equal to the maximum power in the β band of GPi neuron firings averaged over time and across GPi cells. The most “fit” patterns were mated using fitness proportionate selection. The resulting stimulation train had a BEF of ∼15 Hz, an IBF of ∼700 Hz, a varying number of pulses per burst, and an average number of total pulses per second of 225 (Fig. 1).

All stimulation patterns were comprised of charged-balanced, symmetric biphasic pulses of 90 μs/phase. MATLAB (R2009a, The MathWorks) was used to digitize stimulation pattern templates and drive a voltage-to-current stimulus isolator (A-M Systems). Bipolar stimulation was delivered through the stimulating MEA to the STN. Amplitudes for each animal ranged from 20 to 150 μA. The maximum stimulation amplitude chosen for each animal was the amplitude at a continuous stimulation frequency of 130 Hz that induced circling contralateral to the hemisphere to which stimulation was applied but minimized additional motor effects such as paw tremor or rearing. For behavioral studies, a single amplitude, the maximum determined for each animal, was applied for each stimulation pattern. For neural recording studies with stimulation, the applied amplitudes ranged from a submotor threshold amplitude, usually 20–25 μA, to the maximum amplitude determined for that animal. In summary, we applied eight stimulation patterns across a range of amplitudes during neural recordings and a variety of behavioral tasks. Three regular bursting and one irregular bursting pattern were designed to mimic STN unit bursting activity seen in PD humans and rats. Three low-frequency patterns matching the BEFs of the regular bursting patterns (15, 20, 25 Hz) were applied to serve as controls that had β spectral frequency but no bursts. A high-frequency pattern matching the IBF of the regular bursting patterns (225 Hz) was applied as an additional control.

Computational model

The regular bursting, irregular bursting, and continuous frequency stimulation patterns were applied to the STN model neurons in a biophysically-based model of the cortico-basal ganglia-thalamic network (Kumaravelu et al., 2016). The model was comprised of a network of single compartment Hodgkin-Huxley type neurons representing regular spiking excitatory neurons and fast-spiking interneurons in cortex; direct (dopamine-type 1 receptor dominant) and indirect (dopamine-type 2 receptor dominant) medium spiny neurons of the striatum; STN; globus pallidus externus (GPe); GPi; and thalamus, and 59 cells of each cell type were included in the model. Multiple amplitudes were tested to span the range from no STN cell activation to activation of all model STN neurons. The pulse width of each monophasic pulse was fixed at 180 μs. Simulations were implemented in MATLAB R2014a with equations solved using the forward Euler method with a time step of 0.025 ms and a simulation length of 10 s (Kumaravelu et al., 2016).

The output measure was the peak power of β band oscillatory activity averaged across all model GPi neurons. The averaged peak β band power was calculated by first generating the average multi-taper spectrogram of the spike times of all GPi neurons using Chronux (chronux.org) with MATLAB R2014a. A sliding window of 1 s and a step size of 0.1 s was used. Second, at each time point of the averaged spectrogram, the peak power between 13 and 30 Hz was extracted. Finally, all maximum power values across time were averaged to generate the average maximum β band power for a given stimulation train pattern and amplitude.

Code accessibility

Our model of the cortico-basal ganglia-thalamic network is available for download on Model DB, accession number 206232.

Behavioral tests before unilateral 6-OHDA lesion

Healthy (dopamine-intact) rats performed a variety of behavioral tasks after recovery from chronic electrode implantation to assess for induction of bradykinetic/akinetic symptoms by stimulation of the STN with any of the patterns. To mitigate that a single metric from one behavioral task may alone not be sensitive enough to detect stimulation induced symptoms, we used a constellation of previously validated quantitative behavioral outcomes. These tasks are widely used to assess the degree of bradykinetic/akinetic impairment in rodent models of PD, are sensitive to varying degrees of SNc dopaminergic cell loss, and should detect changes in motor function induced by applied β-patterned stimulation paradigms. The stimulation patterns tested and the number of animals that performed each behavioral task are detailed in Table 1.

Table 1.

Stimulation patterns tested in model simulations, healthy (intact) animals, and 6-OHDA-treated animals

Pattern	Model	Bar test	Open field test	Adjusting steps test	Forelimb use asymmetry test	Skilled forelimb reaching test
Intact animals
No stimulation	X	7	9	8	5	8
Irregular β	X	5	5	7	5	5
B15 IBF225	X	5	6	7	3	6
B20 IBF225	X	5	5	5		5
B25 IBF225	X	5	6	7	3	6
Regular 15 Hz	X	7	8	6	3	5
Regular 20 Hz	X	5	5	5		5
Regular 25 Hz	X	5	6	7		6
Regular 225 Hz	X	7	9	7	3	5
6-OHDA-treated animals
No stimulation	X	9	5	6	3	4
Regular 130 Hz		9	5	3	3	3
6-OHDA levodopa + stimulation experiments
Levodopa (LD)				3		3
LD + irregular β				3		3
LD + B15 IBF225				3		3
LD + B20 IBF225				3		3
LD + B25 IBF225				3		3
LD + regular 15 Hz				3		3
LD + regular 20 Hz				3		3
LD + regular 25 Hz				3		3
LD + regular 225 Hz				3		3

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Bar test

The bar test detects forelimb akinesia, which develops prominently in the 6-OHDA rat model of PD with >90% dopaminergic SNc cell loss (Duty and Jenner, 2011). When placed in an abnormal upright posture with forelimbs gripping a bar typically 5–10 cm above the ground, 6-OHDA-lesioned rats will take longer to release the bar than unlesioned rats (Duty and Jenner, 2011). The goal in using this behavioral task was to determine whether the unilaterally applied β-patterned stimulation paradigms preferentially caused generation of contralateral forelimb bradykinetic or akinetic symptoms as compared to no stimulation and continuous stimulation controls. For this test, dopamine-intact animals were placed in a 36 × 24 cm clear plastic chamber with a 0.5-cm diameter bar 10 cm above the ground in a dim room. Animals received unilateral STN stimulation at the maximum amplitude determined for that animal. An experimental session alternated between blocks of no stimulation and blocks of stimulation such that each stimulation block was bracketed by a no stimulation block. Each block was comprised of “pre-trial” and “trial” periods. For a given block, the animal experienced a pre-trial period of 3 min of either no stimulation or a specific pattern of stimulation. After 3 min elapsed, the trial period began. If the block was a stimulation block, stimulation continued uninterrupted from the pre-trial period through the trial period. The animal was placed such that it was standing upright on its hind paws while its forepaws gripped the bar (see Fig. 6A). The total time each paw spent on the bar was measured as a function of stimulation paradigm. A trial ended after either three placements on the bar were quantified or 300 s elapsed. The order in which stimulation patterns were presented was randomized between experimental sessions. An experimental session lasted 1–2 h depending on an animal’s performance. For each animal, the total time each paw spent on the bar was averaged for each stimulation pattern. An increase in length of time on bar for the paw contralateral to the stimulated hemisphere as compared to the ipsilateral paw and the no stimulation result was interpreted as generation of bradykinetic/akinetic symptoms.

Figure 6. — Effect of STN stimulation patterns on performance in bar test. “Contralateral” refers to the side of the body contralateral to the brain hemisphere to which stimulation was applied. Error bars indicate mean ± SE. Patterns not sharing the same letter are significantly different from each other (p < 0.05). A, Rat was placed in an upright position with its forepaws resting on a bar 10 cm above the ground. B, Length of time on bar as a function of stimulation pattern, lesion state, and forepaw. Two-way RMANOVA performed on healthy (intact) animal data were not significant in length of time on bar for pattern (p = 0.92), paw (p = 0.34), or pattern × paw (p = 0.74). See Table 1 for n for each pattern. A statistically significant difference in length of time on bar between baseline 6-OHDA-treated animal (n = 9) contralateral paw performance and intact animal (n = 7) baseline contralateral paw performance was found (p < 0.0001, Wilcoxon rank sum test). A statistically significant difference in length of time on bar between baseline 6-OHDA-treated animal performance (n = 9) performance and performance of 6-OHDA-treated animals with 130-Hz stimulation was found (p < 0.0001, Wilcoxon rank sum test).

Open field test

The open field test assesses spontaneous locomotor activity and is sensitive enough to discriminate between motor deficits caused by complete (>90% SNc dopaminergic cell loss) and incomplete (∼70% SNc dopaminergic cell loss) lesions in the 6-OHDA rat model of PD (Carvalho et al., 2013). 6-OHDA-lesioned animals exhibit less motor activity than intact animals in an open field (Carvalho et al., 2013). The goal was to determine whether unilaterally applied β-patterned stimulation paradigms preferentially caused a decrease in movement speed or a decrease in the number of movement initiation episodes as compared to no stimulation and continuous stimulation controls. Dopamine-intact rats were placed in a dark 20 cm in diameter cylinder, and an infrared camera captured all movements (see Fig. 7A). Animals received unilateral STN stimulation at the maximum amplitude determined for that animal. An experimental session alternated between blocks of no stimulation and blocks of stimulation such that each stimulation block was bracketed by a no stimulation block. Each block was 3 min long. An experimental session was limited to 60 min to minimize overall experiment duration. As such, during each experimental session, one to two β bursting paradigms in addition to the corresponding low and high-frequency continuous control patterns were applied. Additional experimental sessions were performed after a rest period of ∼5–7 d to avoid habituation of the animal to the chamber. The order in which stimulation patterns were presented was re-randomized between experimental sessions. Videos were analyzed using TopScan version 2.0 (CleverSystems, Inc.) and MATLAB. Average linear speed, average number of pauses per second, and average pause length were measured, and results were normalized for each animal to the no stimulation results to facilitate comparison across animals. A significant decrease in average linear speed and a significant increase in average pause length and average number of pauses per second as compared to the no stimulation results was interpreted as generation of bradykinesia/akinesia.

Figure 7. — Effect of STN stimulation patterns on performance in open field test. Error bars indicate mean ± SE. Patterns not sharing the same letter are significantly different from each other (p < 0.05). A, Rat was placed in a dark cylindrical chamber and its movements were video recorded. B, Linear speed as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.15). See Table 1 for n for each pattern. An unpaired t test performed on 6-OHDA-treated animal (n = 5) baseline performance versus intact animal (n = 9) baseline performance found no significant effect of lesion state (p = 0.72). A paired t test performed on 6-OHDA-treated animal data (n = 5) found no significant effect of 130-Hz stimulation (p = 0.54). C, Number of pauses per second as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.16). See Table 1 for n for each pattern. An unpaired t test performed on 6-OHDA-treated animal (n = 5) baseline performance versus intact animal (n = 9) baseline performance found no significant effect of lesion state (p = 0.11). A paired t test performed on 6-OHDA-treated animal data (n = 5) found no significant effect of 130-Hz stimulation (p = 0.22). D, Pause length as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.44). See Table 1 for n for each pattern. An unpaired t test performed on 6-OHDA-treated animal (n = 5) baseline performance versus intact animal (n = 9) baseline performance found no significant effect of lesion state (p = 0.17). A paired t test performed on 6-OHDA-treated animal data (n = 5) found no significant effect of 130-Hz stimulation (p = 0.30).

Adjusting steps test

The adjusting steps test assesses forelimb akinesia in dopamine-depleted rats and can detect a forelimb motor deficit at a striatal dopamine depletion levels of 80% or greater (Chang et al., 1999). When suspended vertically such that the body weight is supported by the forelimbs, a 6-OHDA-lesioned rat will drag its affected forelimb rather than making adjusting steps to support its weight when dragged backwards or laterally (Chang et al., 1999; Fleming, 2009; Glajch et al., 2012). The goal was to determine whether unilaterally applied β-patterned stimulation paradigms preferentially caused an increase in akinesia in the contralateral forelimb as compared to no stimulation and continuous stimulation controls. Dopamine-intact rats were gripped around the hips to immobilize the hindlimbs and suspended vertically on a 77 × 16 cm glass plank such that the animal supported its weight through its forepaws (see Fig. 8A). A video camera positioned below the glass plank recorded all forelimb movements. Animals were dragged backwards, and the number of backward steps the animal made with each forepaw along the length of the glass plank was recorded. The animal performed three to five trials of this task. The animal then was returned to its home cage and received unilateral STN stimulation at the maximum amplitude determined for that animal for 5 min. While STN stimulation continued, each animal performed three to five additional trials of this task. A single pattern of stimulation was applied during an experimental session, which typically lasted 30 min, and animals were given at least 3 h of rest in between experimental sessions. A decrease in forelimb adjusting steps for the forelimb contralateral to the stimulated hemisphere as compared to the ipsilateral forelimb and the no stimulation result was interpreted as generation of bradykinesia/akinesia.

Figure 8. — Effect of STN stimulation patterns on performance in adjusting steps test. “Contralateral” refers to the side of the body contralateral to the brain hemisphere to which stimulation was applied. Error bars indicate mean ± SE. Patterns not sharing the same letter are significantly different from each other (p < 0.05). A, The rat was suspended such that its forepaws bore its weight as it was dragged backwards along a clear glass surface. Adjusting steps were video recorded from below. B, Number of forepaw adjusting steps made as a function of stimulation pattern, lesion state, and forepaw. Two-way RMANOVA performed on intact animal data were not significant for pattern (p = 0.48), paw (p = 0.28), or pattern × paw (p = 0.10). See Table 1 for n for each pattern. Two-way RMANOVA performed between intact animal data (n = 8) and baseline 6-OHDA-treated animal data (n = 6) found significant effects of lesion state (p = 0.0498), paw (p = 0.039), and lesion state × paw (p = 0.0007). *Post hoc* Tukey’s test on lesion state × paw interaction found significant differences between 6-OHDA-treated and intact animal contralateral paw performance (p = 0.0041) and between 6-OHDA-treated animal contralateral and ipsilateral paw performance (p = 0.0003). Two-way RMANOVA performed on 6-OHDA-treated animal data found a significant effect of pattern (p = 0.019), a significant effect of paw (p = 0.024), but no significant interaction term. C, Number of forepaw adjusting steps made by levodopa-treated 6-OHDA rats as a function of stimulation pattern, drug state, and forepaw. An unpaired t test performed on contralateral paw performance with (n = 3) and without (n = 6) levodopa and without applied stimulation found a significant effect of drug state (p = 0.0001). Two-way RMANOVA performed on levodopa-treated 6-OHDA rats was not significant for pattern (p = 0.31), paw (p = 0.10), or pattern × paw (p = 0.13). See Table 1 for n for each pattern.

Forelimb use asymmetry test

The forelimb use asymmetry test assesses forelimb akinesia in dopamine-depleted rats, and performance in this task correlates with the amount of striatal dopamine depletion (Connor et al., 1999; Fleming, 2009). When placed in a narrow cylinder, 6-OHDA-lesioned rats will avoid using the affected forelimb during vertical exploration of the cylinder (Schallert et al., 2000; Fleming, 2009). The goal was to determine whether unilaterally applied β-patterned stimulation paradigms preferentially caused a decrease in limb use preference in the contralateral forelimb during vertical exploration as compared to no stimulation and continuous stimulation controls. Dopamine-intact rats were placed in their home cage for 1 h in a dark room to acclimate to the environment. After 1 h, rats received either no stimulation or unilateral STN stimulation with a single pattern for 5 min. Rats were then placed in a 20 cm in diameter × 30 cm high clear cylinder for 5–10 min (see Fig. 9A). If stimulation was applied in a given experimental session, it continued for the full duration of the task. Animals were videotaped during the task, and mirrors were used to capture a 360° view of animal exploration of the cylinder. During rears the numbers of single and bilateral forepaw touches to the cylinder wall were quantified. Additionally, on descending from a rear, the rat’s preference for using one or both forepaws to support its weight was quantified. Animals were given 7 d of rest between experimental sessions to diminish habituation to the cylinder. A decrease in use of the forelimb contralateral to the stimulated hemisphere on vertical exploration and landings as compared to the ipsilateral forelimb and the no stimulation result was interpreted as generation of bradykinesia/akinesia.

Figure 9. — Effect of STN stimulation patterns on performance in the forelimb use asymmetry test. “Contralateral” refers to the side of the body contralateral to the brain hemisphere to which stimulation was applied. Error bars indicate mean ± SE. Patterns not sharing the same letter are significantly different from each other (p < 0.05). A, Rat was placed in a clear cylinder and vertical exploration of the cylinder was video recorded. B, Preferred forelimb use in vertical exploration as a function of stimulation pattern and lesion state. Two-way RMANOVA performed on intact animal data revealed a significant effect of paw (p = 0.026), but no significant effect of pattern (p = 0.55) or pattern × paw (p = 0.72). See Table 1 for n for each pattern. *Post hoc* Tukey’s test on factor paw found bilateral touches during vertical exploration to be significantly greater than contralateral paw touches across all stimulation patterns in intact animals (n = 8, p = 0.021). Two-way RMANOVA performed on intact (n = 8) versus 6-OHDA-treated (n = 3) animal baseline performance found no significant effect of paw (p = 0.10), lesion state (p = 0.98), or paw × lesion state (p = 0.34). Two-way RMANOVA performed on 6-OHDA-treated (n = 3) animal data found no significant effect of paw (p = 0.53), pattern (p = 0.42), or paw × pattern (p = 0.44) with 130-Hz stimulation. C, Preferred forelimb use in landing as a function of stimulation pattern and lesion state. Two-way RMANOVA performed on intact animal data found a significant effect of paw (p = 0.021), but no significant effect of pattern (p = 0.36) or pattern × paw (p = 0.32). See Table 1 for n for each pattern. *Post hoc* Tukey’s test on factor paw found bilateral forelimb use during landings to be significantly greater than ipsilateral forelimb use in landings across all stimulation patterns in intact animals (p = 0.032). Two-way RMANOVA performed on intact (n = 8) versus 6-OHDA-treated (n = 3) animal baseline performance found no significant effect of paw (p = 0.06), lesion state (p = 0.87), or paw × lesion state (p = 0.45). Two-way RMANOVA performed on 6-OHDA-treated (n = 3) animal data found no significant effect of paw (p = 0.07), pattern (p = 0.42), or paw × pattern (p = 0.44) with 130-Hz stimulation.

Skilled forelimb reaching test

A skilled forelimb reaching task was conducted using the Vulintus MotoTrak System (Hays et al., 2013). Animals were placed in a 36 × 24 × 16 cm acrylic chamber with a narrow slot at one end positioned so as to restrict performance to a specific forelimb. A lever on a motorized track was positioned at or just outside of the slot, and animals were trained to depress the lever twice within a certain time window to receive a food reward (see Fig. 10A). Impaired animals demonstrate longer interpress intervals, fewer presses per trials, and fewer successes (Hays et al., 2013).

Figure 10. — Effect of STN stimulation pattern on performance in the skilled forelimb reaching test. Error bars indicate mean ± SE. Patterns not sharing the same letter are significantly different from each other (p < 0.05). A, Rat was placed in a clear chamber with a slot to allow it to grasp and depress a lever using only the forelimb contralateral to stimulation or lesioned hemisphere. B, Total number of trials per experimental session as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found a significant effect of pattern (p = 0.0024). See Table 1 for n for each pattern. *Post hoc* Tukey’s test on factor pattern found significant differences between baseline and the following patterns: irregular β (p = 0.044), B20IBF225 (p = 0.035), B25IBF225 (p = 0.021), and regular 225 Hz (p = 0.0025). One-way unpaired t test performed on 6-OHDA-treated (n = 4) animal baseline performance versus intact animal (n = 8) performance found a significant effect of lesion state (p = 0.0003). One-way matched pairs t test performed on 6-OHDA-treated animal data with (n = 3) and without (n = 3) 130-Hz stimulation found a near significant effect of stimulation (p = 0.11). C, Percentage of trials resulting in pellet dispensation as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.30). See Table 1 for n for each pattern. One-way unpaired t test performed on 6-OHDA-treated (*n =* 4) animal baseline performance versus intact animal (n = 8) performance found a significant effect of lesion state (p = 0.0025). One-way matched pairs t test performed on 6-OHDA-treated animal data with (n = 3) and without (n = 3) 130-Hz stimulation found a significant effect of 130-Hz stimulation (p = 0.017). D, Minimum interpress interval as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.21). See Table 1 for n for each pattern. One-way unpaired t test performed on 6-OHDA-treated (n = 4) animal baseline performance versus intact animal (n = 8) performance found a significant effect of lesion state (p = 0.041). One-way matched pairs t test performed on 6-OHDA-treated animal data with (n = 3) and without (n = 3) 130-Hz stimulation found no significant effect of 130-Hz stimulation (p = 0.24). E, Initiation to hit peak latency as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found no significant effect of pattern (p = 0.44). See Table 1 for n for each pattern. One-way unpaired t test performed on 6-OHDA-treated (n = 4) animal baseline performance versus intact animal (n = 8) performance found a near significant effect of lesion state (p = 0.07). One-way matched pairs t test performed on 6-OHDA-treated animal data with (n = 3) and without (n = 3) 130-Hz stimulation found no significant effect of 130-Hz stimulation (p = 0.17). F, Mean press duration as a function of stimulation pattern and lesion state. One-way RMANOVA performed on intact animal data found a significant effect of pattern (p = 0.037), but *post hoc* Tukey’s test found no significant differences among patterns. See Table 1 for n for each pattern. One-way unpaired t test performed on 6-OHDA-treated (n = 4) animal baseline performance versus intact animal (n = 8) performance found a near significant effect of lesion state (p = 0.15). One-way matched pairs t test performed on 6-OHDA-treated animal data with (n = 3) and without (n = 3) 130-Hz stimulation found no significant effect of 130-Hz stimulation (p = 0.20).

The goal was to determine whether unilaterally applied β-patterned stimulation preferentially caused impairment in the forelimb contralateral to the stimulated hemisphere during lever presses as compared to no stimulation and continuous stimulation controls. Dopamine-intact rats were restricted to 12 g of food per day until their body weight was between 85% and 90% of their free feeding weight. During an experimental session, a rat was placed in its home cage in a dark room and received unilateral STN stimulation at the maximum amplitude determined for that animal for 5 min. The rat then was placed in the experimental chamber while stimulation continued. The animal was allowed 30 min in the experimental chamber to perform the task. A successful trial was defined as two lever presses within a 0.5-s window with the lever positioned 1.0 cm outside of the chamber. Interpress interval, mean press duration, initiation of press to hit peak latency, and success rate to a successful trial were calculated. A maximum of two experimental sessions were performed per day, and animals rested for at least 3 h between sessions. Sessions without stimulation were conducted on an identical timeline to those with stimulation. An increase in interpress interval, mean press duration, and initiation of press to hit peak latency and a decrease in success rate were interpreted as generation of bradykinesia/akinesia.

6-OHDA lesioning

Eleven animals were rendered hemi-parkinsonian through unilateral administration of the neurotoxin 6-hydroxydopamine hydrobromide (6-OHDA, Sigma-Aldrich) via the MFB cannula to evoke unilateral degeneration of dopaminergic neurons in the nigrostriatal pathway (Tieu, 2011). As 6-OHDA also will selectively destroy noradrenergic neurons, 30 min before 6-OHDA administration animals were pre-treated with intraperitoneal injections of 5-mg/kg desipramine (Sigma-Aldrich) to protect nonadrenergic neurons and 50-mg/kg pargyline (Sigma-Aldrich) to inhibit monoamine oxidase activity (McConnell et al., 2012; So et al., 2012). Anesthesia was induced using a mixture of 7% sevoflurane in 2 l min⁻¹ O₂ and maintained using 2.5–3.5% sevoflurane in 1–1.5 l min⁻¹ O₂. Animals were positioned in a Kopf stereotactic frame for intracerebral injection. Immediately before infusion, 5-mg 6-OHDA was dissolved into 2 mL 0.02% ascorbic saline (Sigma-Aldrich) stored at 4°C to produce a final concentration of 10 mM. Ten microliters of 6-OHDA solution were administered through the MFB cannula using a Hamilton syringe at a rate of 2 μl/min. Animals were given one week to recover. Animals that did not exhibit unilateral motor symptoms after the recovery period were re-infused with 6-OHDA a maximum of two additional times.

Methamphetamine-induced circling test

One week after injection of 6-OHDA, each rat was injected with a methamphetamine solution (Sigma-Aldrich) at a concentration of 1.5–2.5 mg/kg intraperitoneally and placed in a 20 cm in diameter × 30 cm high cylinder within a dark chamber. Animals with severe unilateral lesions of dopaminergic pathways will circle ipsilateral to the lesion after administration of methamphetamine (Ungerstedt and Arbuthnott, 1970). The activity of the animal was monitored using an infrared lamp and camera for 2 h, and during this time blocks of high-frequency stimulation were applied for 60 s with 120 s of rest between each stimulation pattern (McConnell et al., 2012). TopScan version 2.0. was used to determine the position of each animal within the cylinder for each video frame. From this information, the angular velocity of each animal with and without stimulation was calculated using MATLAB. Based on previous histologic analysis, animals that circled at a rate of at least 3 turns/min with no stimulation were deemed to have had >90% loss of dopaminergic neurons in the SNc (Ungerstedt and Arbuthnott, 1970; Fang et al., 2006; So et al., 2012), which was defined as a successful lesioning procedure. Animals that did not meet this criterion were re-lesioned up to two additional times.

Post-lesion behavioral positive controls

After confirmation of successful lesion via the methamphetamine-induced circling test, baseline performance and performance with continuous 130-Hz stimulation were assessed in the bar test, the open field test, the adjusting steps test, the forelimb use asymmetry test, and the skilled forelimb reaching test. The amplitude for 130-Hz stimulation was consistent with that used for each animal before the lesioning procedure. Assessing motor performance under these conditions provided a threshold for generation of parkinsonian symptoms through use of β-patterned stimulation for each behavioral task. The number of animals that performed each positive control task can be found in Table 1.

Post-lesion β-patterned stimulation behavioral assessments

Rats were pre-treated with 15 mg/kg of benserazide hydrochloride (intraperitoneal; Sigma-Aldrich), a peripheral DOPA decarboxylase inhibitor, and L-3,4-dihydroxyphenylalanine methyl ester hydrochloride (levodopa; 15–19 mg/kg, i.p., Sigma-Aldrich). Doses of levodopa were selected for each animal that disrupted cortical M1 power ipsilateral to the lesion (See section Neuronal recordings after unilateral 6-OHDA lesion) but did not make the animal dyskinetic. The adjusting steps test and the skilled forelimb reaching task were administered to assess performance for a drug only baseline and during β-patterned and control stimulation. The patterns assessed are detailed in Table 1.

Neuronal recordings

Sixteen single unit channels were recorded from the SNr, and three ECoG channels, M1 bilaterally and S1 from the hemisphere contralateral to STN implant, were recorded simultaneously using a multichannel acquisition processor system (Plexon, Inc.). The rat was placed in an open top chamber within a Faraday cage, and recordings were performed while the rat was awake and freely roaming the chamber. The three ECoG channels were also recorded after 6-OHDA lesion and used to titrate doses of levodopa as described below. The voltage signal used to drive the stimulus isolator was recorded simultaneously with the neural signals on an analog input channel to enable precise time-locking of the stimulation input to the neural recordings in subsequent analyses. For single unit recordings gain and filter settings were: gain = 20,000, filter = 150 Hz to 8.8 kHz, sampling rate = 40 kHz, and for LFP recordings, gain and filter settings were: gain = 2500–5000, filter = 150 Hz to 8.8 kHz, sampling rate = 20 kHz.

Neuronal recordings before unilateral 6-OHDA lesion

Recording sessions were 3–4 h in length, and all patterns listed in Table 1 were applied during an experimental session. A single pattern block consisted of 90–120 s of no stimulation, 90–120 s of applied stimulation, and 90–120 s of no stimulation while single units were recorded from SNr. ECoG also was recorded simultaneously from bilateral M1 and contralateral S1. Each pattern was applied at three to four amplitudes, ranging from 25 μA to the highest tolerated amplitude for each animal. The order in which patterns and amplitudes were presented was randomized. Each animal participated in up to four recording sessions. Pattern and amplitude presentation were re-randomized between sessions.

Neuronal recordings after unilateral 6-OHDA lesion

Two types of recording sessions were conducted. Although unilateral motor impairment can be detected shortly after 6-OHDA lesion increases in BFP appear to emerge after presentation of motor symptoms (Degos et al., 2009). We were able to detect β frequency peaks in ipsilateral M1 ECoG approximately three weeks post-lesion (Fig. 2A). Before emergence of this peak, stimulation and SNr unit recording sessions were performed in a manner identical to the recordings done in intact rats. Each animal participated in up to two experimental sessions. Pattern and amplitude were re-randomized between experimental sessions.

Figure 2. — Sample post-6-OHDA lesion ipsilateral M1 ECoG recordings. Insets show a magnified view of β frequency range results. A, Progressive increase in ipsilateral M1 β frequency activity as a function of days post-6-OHDA lesion. B, Disruption of ipsilateral M1 β frequency activity as a function of time from injection of levodopa (LDOPA).

After emergence of a β peak in ipsilateral M1 ECoG, different doses of levodopa were administered during different recording sessions until sustained depression of ipsilateral M1 BFP was observed (Fig. 2B). As peak drug effect in the rat lasts approximately 2 h (Putterman et al., 2007), stimulation and SNr unit recording sessions then proceeded as without drug pre-treatment but were executed only at the maximum amplitude to allow for all patterns to be applied within the same recording session.

Single unit recording analysis

Single units were sorted online using SortClient and were classified further using Offline Sorter (Plexon, Inc.). Timestamps of unit activity were imported into MATLAB for analysis. Interspike interval (ISI) histograms of unit activity were calculated for the baseline and stimulation periods. Artifact timestamps were extracted from the recorded voltage input signal and used to calculate interpulse interval (IPI) histograms and peri-stimulus time histograms (PSTHs). A virtual PSTH was calculated for the pre-stimulation time period by shifting the artifact timestamps to align with the beginning of the pre-stimulation recording period. Blanking periods of 0.7 ms before through 2 ms after the artifact timestamp were applied to eliminate the possibility of a portion of the artifact wave form being counted as a unit timestamp. These blanking periods were applied to the virtual PSTHs, as well. For burst stimulation patterns, PSTHs were aligned to the last pulse in each burst to assess activity in the interburst interval. A bin width of 0.2 s was used to generate the bin axes for both virtual and stimulation PSTHs. The change in unit activity from pre-stimulation baseline was determined by transforming the stimulation PSTH bin counts to z-scores relative to the virtual PSTH bin counts according to the following formula, where i represents a single stimulation PSTH bin value:

Z_{s t i m} (i) = \frac{(P S T H_{s t i m} (i) - \bar{P S T H_{v i r t u a l}})}{σ_{v i r t u a l}} .

A threshold of four standard deviations from the mean (Z_stim(i) ≥ 4, p < 0.001) was chosen to distinguish strong, statistically significant changes in unit activity from the pre-stimulation baseline in the normalized stimulation PSTH (Fig. 3).

Figure 3. — Calculation of normalized PSTH. Artifact timestamps were used to create a PSTH for the stimulation period and a virtual PSTH for the pre-stimulation period. Bin counts for the stimulation PSTH were converted to z-scores using the virtual PSTH bin counts to determine statistically significant changes in activity due to applied STN stimulation.

To determine whether single unit activity in the SNr was entrained to stimulation in the STN, the excitatory effective pulse fraction (eEPF) was calculated using the normalized PSTH (Agnesi et al., 2015). The EPF is a ratio (range: 0–1) that relates the number of single unit firings evoked by a stimulus pulse at a consistent latency within the IPI to the number of unit firings evoked by a “virtual” stimulus pulse at the same latency during a baseline period. This latency within the IPI is referred to as a phase and represents at least two consecutive time bins with a statistically significant increase in single unit activity from the baseline period. The eEPF was designed for a stimulation site and recording site linked by a glutamatergic monosynaptic projection, as are the STN and SNr, and is calculated as follows for each identified IPI phase (Agnesi et al., 2015):

e E P F = \frac{p f s - p f s b}{n u m b e r o f s t i m u l u s p u l s e s - p f s b},

where pfs represents the number of stimuli during the stimulation period followed by a single unit spike and pfsb represents the number of shifted stimulus pulses followed by a single unit spike during the pre-stimulation period. An eEPF was calculated for all distinct IPI phases of the normalized stimulation PSTH with statistically significant increases in unit activity from the pre-stimulation period (Fig. 3). If multiple distinct IPI phases were present in a single normalized stimulation PSTH, then the eEPFs for these phases were averaged to assess the overall effect of stimulation pattern and amplitude.

The change in BFP in SNr unit activity as a result of STN stimulation was quantified through calculation of multi-taper spectra using the Chronux data package for MATLAB. Spectra were calculated for both the pre-stimulation and stimulation time periods using averaging over 15- to 20-s windows (six time segments per recording period), five Slepian data tapers, a bandpass range of 1–58 Hz, and 0.04-Hz frequency resolution. To account for the effect of amplifier blanking, an individualized blanking period was determined for each unit. Using the lowest amplitude stimulation recording for each unit, a PSTH was created without pre-determined blanking and the length of time between a stimulation pulse and the first unit spike was found. This individualized blanking period was then imposed on the pre-stimulation recording for each unit; any spikes occurring within this time period following a virtual pulse were deleted. These blanking periods ranged from 0.6 to 2 ms and avoided introduction of artificial BFP into the spectra. After calculation of pre-stimulation and during stimulation spectra, the percentage of total power in the β band was quantified. Each power value was divided by the sum of all power values to convert it to a fraction of total power. The percentage of total power in the β band was then equal to the sum of each scaled power value in the range of 13–30 Hz. The difference between the percentage of total power in the β band with and without stimulation for each amplitude, frequency pattern, and single unit was determined.

ECoG recording analysis

Three ECoG channels–bilateral M1 and S1 contralateral to the implanted STN–were recorded during stimulation in ten intact animals. Our goal was to quantify the amount of BFP induced by stimulation in ipsilateral M1 ECoG given the connections between STN and motor cortex (Gatev et al., 2006; Delaville et al., 2015). While projections between ipsilateral primary somatosensory cortex and STN have been identified in the rat, contralateral projections have not been identified (Canteras et al., 1988). To distinguish inducement of physiologic β power from the effect of stimulation artifact, the effects seen in ipsilateral M1 ECoG were referenced to contralateral S1 ECoG data as described below.

Ipsilateral M1 and contralateral S1 continuous data were imported into MATLAB and divided into pre-stimulation and with stimulation segments. ECoG segments recorded during stimulation were high-pass filtered using a three-pole Butterworth filter with a 2-Hz cutoff frequency. Stimulus artifacts were digitally blanked via linear interpolation from 0.1 to 1.5 ms after the start of a stimulus pulse. The data were then divided into segments of repeating IPIs and averaged to determine an average evoked response to stimulation. This average evoked response was subtracted from the overall dataset to reduce spectral power at the stimulation frequencies (Brocker et al., 2017). Finally, the data again were bandpass filtered using a three-pole Butterworth filter between 2 and 100 Hz. ECoG segments recorded before stimulation underwent only both rounds of filtering.

Multi-taper spectra were calculated for ipsilateral M1 and contralateral S1 ECoG channels for both pre-stimulation and during stimulation time segments. Spectra were calculated using averaging over 5-s windows, three Slepian data tapers, and a bandpass range of 3–55 Hz. As with the single unit spectra, the percentage of total power in the β band was quantified for both pre-stimulation and during stimulation spectra. The difference between the percentage of total power in the β band with and without stimulation for each amplitude and stimulation pattern was calculated for both ipsilateral M1 and contralateral S1 spectra. Finally, the percentage of total power in the β band during stimulation for contralateral S1 ECoG was subtracted from the percentage of total power in the β band during stimulation for ipsilateral M1 ECoG (See section Pre-6-OHDA ECoG Recordings).

Histology

Histologic analysis was conducted to determine the location of all implanted electrode arrays as well as the extent of the 6-OHDA lesion. Each animal was deeply anesthetized with urethane (1.8 g/kg, i.p.) and transcardially perfused with cold PBS followed by 10% formalin. The head was removed and post-fixed in 10% formalin overnight at 4°C. The following day, the brain was removed and placed in a 30% sucrose solution and stored at 4°C until it sank, usually ∼48 h. The left hemisphere was dyed to assist in hemispherical identification of brain slices. Brains were then placed in optimal cutting temperature compound (OCT, Tissue Tek) and frozen to –80°C. A cryostat at approximately –20°C was used to cut 50-μm serial coronal slices.

To identify implanted electrode tip locations, a cresyl violet stain was used. Brain slices were rinsed in PBS, mounted onto microscope slides, and left to dry overnight. Mounted slices were de-fatted by placing slides in forward and then backward through a series of solutions for 3 min each: distilled water, 70% ethanol, 95% ethanol × 2, 100% ethanol × 2, Histoclear × 2. Slides were then stained in a 0.1% cresyl violet solution (Sigma-Aldrich) for ∼30 min, dried, and coverslipped. Slides were visually inspected using a light microscope to locate electrode tips. Rats were excluded from analysis if stimulating electrode tips were not located within the STN (Fig. 4).

Figure 4. — Histologic analysis of STN electrode positions. A, Light microscopy image of cresyl violet stained brain slice. Dashed line denotes outline of STN. Arrows indicate electrode track. B–I, Locations of STN electrode tips. Each circle (●) or triangle (▲) indicates the location of the deepest electrode tip for one animal. Only animals with electrode tips in the STN (●) were included in analysis. Animals with electrode tips outside of the STN (▲) were excluded from analysis.

To visualize the extent of the 6-OHDA lesion, a fluorescent immunostaining protocol was used. Slices were rinsed three times in a 1× PBS solution and incubated for 1 h at 4°C in a 1× PBS-based solution containing 8% normal goat serum (Jackson ImmunoResearch) and 1% Triton X-100 (VWR). Slices were rinsed three times in 1× PBS for 5 min each and then incubated overnight at 4°C in a primary 1× PBS-based solution containing 2% normal goat serum and 0.2% anti-tyrosine hydroxylase (anti-TH; monoclonal mouse IgG1; 1:500; Sigma-Aldrich). Slices were again rinsed three times in 1× PBS for 5 min each and then incubated for 1 h in a secondary 1× PBS-based solution containing 2% normal goat serum, 0.5% Triton X-100, and 0.2% Alexa Fluor 594 goat anti-mouse IgG1 (Life Technologies). Slices were then rinsed three times in 1× PBS for 5 min each and coverslipped with SouthernBiotech DAPI-Fluoromount-G (Fisher Scientific).

Experimental design and statistical analyses

All animal data are expressed as mean ± SE with n = the number of animals and reported for each behavioral test in Table 1. To determine significance in behavioral performance metrics, animal data were analyzed using repeated measures ANOVA (RMANOVA), unpaired t tests, and paired t tests as appropriate with fixed factors including paw, pattern, amplitude, lesion state, and/or drug state depending on the particular behavior test and animal ID as the random variable. The Shapiro-Wilk test was used to test normality of the data, which was found to be normal or near normal. Given the robustness of ANOVA both to distributions with significant departures from normality and to small sample sizes (Pearson, 1931; Normal, 2010; Blanca et al., 2017), we used parametric statistics for the majority of our data. Wilcoxon rank sum tests were used to analyze censored data (bar test). Interpretation of the effects of stimulation on neural data were made using ANOVA with fixed factors including pattern, amplitude, lesion state, and/or drug state as appropriate. Where ANOVAs and RMANOVAs were found to be significant, post hoc tests to distinguish differences among factor levels were the Student’s t test if a factor had only two levels or the Tukey’s honest significant difference (HSD) if a factor had greater than two levels. The alpha level chosen for statistical significance was 0.05.

Results

Histologic analysis of electrode locations and 6-OHDA lesions

Verification of stimulation electrode tip locations in STN is shown in Figure 4. Only animals with electrode tips located in the STN were included in behavioral and neural analyses. For 3/35 animals, brains were not available for histologic processing. Previously recorded videos of behavioral response to 130-Hz stimulation were used to determine whether to include these animals in subsequent analyses, as a contralateral turning response to high-frequency stimulation correlates very strongly with successful targeting of the STN (So et al., 2012).

Effects of β-patterned stimulation: model cortico-basal ganglia-thalamic loop

The amount of β band power in the “healthy” model cortico-basal ganglia-thalamic loop was affected by stimulation pattern and the fraction of total cells activated with a significant interaction between pattern and fraction of cells activated (Fig. 5G); statistics are reported in Figure 5 and Table 2. While some BFP was present in the model network in the healthy state (Fig. 5G), β bursting rhythms were not present in the STN or GPi cell populations (Fig. 5A,C,D). When β-patterned stimulation was applied to model STN neurons, β band rhythms were seen in model STN and GPi neurons (Fig. 5B,E,F). Post hoc testing revealed that while continuous low-frequency stimulation paradigms at β band frequencies did increase averaged peak β band power, irregular and regular β stimulation paradigms increased β band power beyond that generated by continuous low-frequency stimulation (Fig. 5G). Also, continuous high-frequency stimulation suppressed power in the β band with increasing STN neuron activation as compared to the healthy model baseline and the “PD” model baseline (Fig. 5G). After confirming generation of BFP in the computational model, these same patterns were applied to healthy rats to quantify any resulting deteriorations in motor performance as well as to document an increase in BFP in SNr unit activity.

Figure 5. — Effect of stimulation patterns on neuronal activity in a biophysically-based computational model of the basal ganglia. A, Model STN neuron voltage output with no applied STN input. B, Model STN neuron voltage output with pattern B25 IBF225 applied to STN and 100% STN cell activation (n = 59 cells). C, Model GPi neuron voltage output with no applied STN input. D, Averaged spectrogram of GPi neuron voltage output with no applied STN input (n = 59 cells). E, Model GPi neuron voltage output with pattern B25 IBF225 applied to STN and 100% STN neuron activation. Inset, Burst activity in GPi neuron in response to burst patterned STN input. F, Averaged spectrogram of GPi neuron voltage output with pattern B25 IBF225 applied to STN and 100% STN neuron activation (n = 59 cells). G, Mean maximum power in the β band as a function of fraction of STN neurons activated and stimulation pattern. Dashed black line (“healthy baseline”) and solid black line (“PD baseline”) indicate baseline GPi β band power with no applied STN stimulation when model is run in either healthy or parkinsonian states, respectively. Two-way ANOVA performed on log-transformed data revealed a significant effect of pattern (p < 0.0001), log(fraction of activated STN cells; p < 0.0001), and a significant interaction term (p < 0.0001). *Post hoc* Tukey’s test found a significant difference between the increase in log(mean max β) caused by each bursting pattern, both regular and irregular, in the model as compared to the increase caused by each continuous low-frequency patterns (p < 0.0001 for all comparisons). Additionally, *post hoc* Tukey’s test found a significant difference between regular 225 Hz and Healthy Baseline (p < 0.0001) and between regular 225 Hz and PD baseline (p < 0.0001). Error bars indicate mean ± SD (n = 10 simulations).

Table 2.

Two-way ANOVA of the effects of β-patterned stimulation and fraction of total cells activated on the amount of β band power in the healthy biophysical circuit model of the cortico-basal ganglia-thalamic loop

Parameter	p value	F	df
Stimulation pattern	<0.0001	1118.4	9,34.7
Log(fraction of total cells activated)	<0.0001	729.3	1,2.51
Interaction term	<0.0001	314.0	9,9.73

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Effects of β-patterned STN stimulation on behavior in healthy rats

We administered five widely used motor tasks to maximize our ability to detect induction of bradykinesia/akinesia due to β-patterned stimulation. Although most of these tasks were sensitive to differences in performance between intact and 6-OHDA-lesioned rats, we did not detect stimulation-induced deteriorations in motor performance in healthy rats.