The effects of levodopa and ongoing deep brain stimulation on subthalamic beta oscillations in Parkinson's disease

Experimental Neurology 226 (2010) 120–127

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The effects of levodopa and ongoing deep brain stimulation on subthalamic beta oscillations in Parkinson's disease Gaia Giannicola a, Sara Marceglia a, Lorenzo Rossi a, Simona Mrakic-Sposta a, Paolo Rampini b, Filippo Tamma c, Filippo Cogiamanian d, Sergio Barbieri d, Alberto Priori a,e,⁎ a

Centro Clinico per la Neurostimolazione, le Neurotecnologie ed i Disordini del Movimento, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milan, Italy Unità Operativa di Neurochirurgia Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy Unità Operativa Neurologia, Ospedale “F. Miulli”, Acquaviva delle Fonti, Bari, Italy d Unità Operativa di Neurofisiopatologia Clinica, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy e Università degli Studi di Milano, Dipartimento di Scienze Neurologiche, Milan, Italy b c

a r t i c l e

i n f o

Article history: Received 27 April 2010 Revised 20 July 2010 Accepted 7 August 2010 Available online 14 August 2010 Keywords: Local field potentials Deep brain stimulation Subthalamic oscillations Levodopa Beta rhythm Parkinson's disease

a b s t r a c t Local field potentials (LFPs) recorded through electrodes implanted in the subthalamic nucleus (STN) for deep brain stimulation (DBS) in patients with Parkinson's disease (PD) show that oscillations in the beta frequency range (8–20 Hz) decrease after levodopa intake. Whether and how DBS influences the beta oscillations and whether levodopa- and DBS-induced changes interact remains unclear. We examined the combined effect of levodopa and DBS on subthalamic beta LFP oscillations, recorded in nine patients with PD under four experimental conditions: without levodopa with DBS turned off; without levodopa with DBS turned on; with levodopa with DBS turned on; and with levodopa with DBS turned off. The analysis of STNLFP oscillations showed that whereas levodopa abolished beta STN oscillations in all the patients (p = 0.026), DBS significantly decreased the beta oscillation only in five of the nine patients studied (p = 0.043). Another difference was that whereas levodopa completely suppressed beta oscillations, DBS merely decreased them. When we combined levodopa and DBS, the levodopa-induced beta disruption prevailed and combining levodopa and DBS induced no significant additive effect (p = 0.500). Our observations suggest that levodopa and DBS both modulate LFP beta oscillations. © 2010 Elsevier Inc. All rights reserved.

Introduction When patients with Parkinson's disease (PD) undergo deep brain stimulation (DBS) motor symptoms improve by almost 60% and antiparkinsonian therapy decreases from 37% to 69% (Benabid et al., 2009). After patients undergo DBS some motor fluctuations persist (Ford et al., 2004; Ostergaard et al., 2002; Romito et al., 2009) but when antiparkinsonian medication is reduced to the minimum they disappear (Weinberger et al., 2006). The question therefore arises whether subthalamic nucleus (STN) DBS induces levodopa-like effects, acts synergically with and could therefore replace medication

Abbreviations: ANOVA, analysis of variance; CI, confidence interval; CT-MRI, computed tomography-magnetic resonance imaging; DBS, deep brain stimulation; DFT, discrete time Fourier transform; LFP, local field potential; PSD, power spectral density; SD, standard deviation; STFT, short time Fourier transform; STN, subthalamic nucleus; SP, spectral power; UPDRS III, unified Parkinson's disease rating scale, part III, motor part. ⁎ Corresponding author. Dipartimento di Scienze Neurologiche, Centro Clinico per la Neurostimolazione, le Neurotecnologie ed i Disordini del Movimento Ospedale Maggiore Policlinico, Via F. Sforza 35, Milan 20122 Italy. Fax: +39 02 5503 3855. E-mail address: [email protected] (A. Priori). 0014-4886/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.expneurol.2010.08.011

(Vingerhoets et al., 2002) or whether DBS and levodopa act independently and differ in their mechanisms of action (Anon, 2001). Whereas clinical studies can analyze only changes in patients' clinical manifestations after levodopa and DBS, studies analyzing neuronal activity provide a deeper insight. Levodopa produces remarkable changes in patterns of electrical activity within the STN and basal ganglia. In particular, local field potentials (LFPs) recorded from DBS electrodes implanted and reflecting presynaptic and postsynaptic activity in large neuronal populations show that STN oscillations respond to levodopa intake in patients with PD (Alonso-Frech et al., 2006; Brown and Williams, 2005; Levy et al., 2002; Priori et al., 2004). STN activity patterns oscillate over a wide frequency range, from low-frequency (2–7 Hz), to beta (13–35 Hz), high-gamma (70–90 Hz), and very-high frequency bands around 300 Hz (Alonso-Frech et al., 2006; Brown and Williams, 2005; Foffani et al., 2003; Levy et al., 2002; Priori et al., 2004). Given their relationship with STN neuronal discharges (Kuhn et al., 2005; Weinberger et al., 2006) and their ability to respond to motor and non-motor stimuli (Brucke et al., 2007; Foffani et al., 2005; Kuhn et al., 2008a, 2004; Levy et al., 2002; Marceglia et al., 2009) LFP beta oscillations have received major attention in the effort to describe patient's clinical state and seek new insights into basal

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ganglia pathophysiology in movement disorders. Beta (13–35 Hz) oscillatory activity, especially in the lower frequency range (Marceglia et al., 2006a; Priori et al., 2004), and its non-linear interactions are disrupted by levodopa (Brown and Williams, 2005; Levy et al., 2002; Marceglia et al., 2006a; Priori et al., 2004); the beta pattern also displays gender-related differences, women having greater beta activity than men (Marceglia et al., 2006b); beta amplitude- and frequencymodulations have been described during voluntary movement execution (Foffani et al., 2005; Kuhn et al., 2004; Levy et al., 2002) and during action observation (Alegre et al., 2010; Marceglia et al., 2009); and finally, beta oscillations are also related to arousal, being modulated during sleep (Urrestarazu et al., 2009). Whether and how DBS influences STN beta oscillations is more controversial. Some investigators reported decreased beta oscillations after short-term and long-term STN DBS, both in the STN itself and in the target nucleus for STN efferents, the globus pallidus internus (GPi) (BronteStewart et al., 2009; Brown et al., 2004; Kuhn et al., 2008b; Wingeier et al., 2006). Conversely, we failed to confirm this result, recording after STN DBS (Foffani et al., 2006) and during STN DBS (Rossi et al., 2007, 2008). We also reported that low-frequency oscillations increased both during (Rossi et al., 2008) and after STN-DBS (Priori et al., 2006). Despite some controversial results, beta STN oscillations correlate with pharmacological and electrical therapies (Priori et al., 2004; Rossi et al., 2007, 2008) and motor and non-motor tasks (Brucke et al., 2007; Foffani et al., 2005; Kuhn et al., 2008a; Levy et al., 2002; Rosa et al., 2010) and are crucial to understand the dynamics underlying the combined levodopa- and DBS-induced oscillatory changes in patients with PD. In addition, because STN LFPs can be directly recorded from the implanted electrode also when the patient is in a chronic condition, STN oscillatory activity could be used in novel closed-loop DBS systems able to change stimulation parameters automatically adapting them to patient's clinical state (Marceglia et al., 2007b; Rosa et al., 2010). In this paper, aiming to clarify the mechanism underlying the action of DBS in PD, we investigated changes induced by levodopa and DBS on STN beta LFP oscillations, in nine patients with PD under four experimental conditions: without levodopa without DBS; without levodopa with DBS turned on; with levodopa with DBS turned on; and with levodopa with DBS turned off. Materials and methods Patients Nine patients (five women, four men) with idiopathic PD, hospitalized in the Neurosurgery Unit of the Fondazione IRCCS Ca'

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Granda Ospedale Maggiore Policlinico of Milan and fulfilling the specific inclusion criteria for DBS treatment (LIMPE, 2003) were studied after informed consent, and local institutional review board approval. The study conformed to the Declaration of Helsinki. All patients were bilaterally implanted in the STN with macroelectrodes for DBS (model 3389 Medtronic, Minneapolis, MN, USA). Clinical details are reported in Table 1. Surgical procedures STN coordinates were obtained by direct visualization through a computerized tomographic-magnetic resonance imaging (CT-MRI) fusion-based technique before surgery, as extensively reported elsewhere (Egidi et al., 2002; Rampini et al., 2003). The STN position was estimated by matching the CT-MRI fused images with a digitized stereotactic atlas. During surgery, the implant position was assessed by microrecordings from exploratory microelectrodes and by clinically assessing the effects induced by stimulation through the same exploratory microelectrodes and also from the implanted macroelectrodes (Priori et al., 2003). The implanted 3389 Medtronic electrode has four cylindrical contacts (1.27 mm in diameter, 1.5 mm in length, placed 2 mm apart, center-to-center) denominated 0–1–2–3, beginning from the more caudal contact. In all nuclei studied the position of contact 1 was consistent with placement in the optimal functional target. The optimal functional target was assessed through electrophysiological monitoring procedures designed also to evaluate the neuronal signal along the trajectories and to assess DBS-induced changes in rigidity in different electrode locations. The position where rigidity decrease was maximal with a good therapeutic window (threshold for side effects N 1.5 * threshold for clinical effect) was considered as the optimal functional target (Table 2) (Marceglia et al., 2010). Experimental protocol and LFP recordings LFP activity was recorded from five women and four men (nine nuclei) with PD 3 days after DBS electrode implantation while the wires were still accessible before being connected to the high-frequency stimulator. Signals were recorded during DBS or levodopa stimulation or both. Each postoperative experimental session lasted approximately 1 h during which patients sat comfortably in an armchair. The experimental session began after overnight withdrawal of antiparkinsonian medication (off levodopa). The experimental protocol consisted of the following six steps (Fig. 1): (1) impedance of the recording contact pair: impedances were evaluated through an impedance meter at 30 Hz

Table 1 Patients' clinical details. Hoehn and Yahr presurgery

Levodopa equivalent dose before surgery (mg/day)*

Dopamine agonist before surgery

Enzymatic Inhibitor before surgery**

4/108 4/108 2/108 0/108 5/108

2.5 3 2 2.5 3

900 1610 1150 1512.5 1300

– pramipexole ropinirole – ropinirole

22/108

3/108

2.5

1305

pramipexole

25/108 27/108 18/108

2/108 4/108 2/108

2.5 3 4

925 900 1200

– – –

carbidopa entacapone – carbidopa carbidopa entacapone carbidopa entacapone carbidopa carbidopa carbidopa entacapone

Patient

Age

Gender

Years of disease

UPDRS III presurgery OFF

ON

1 2 3 4 5

49 48 61 63 61

F F F F F

7 8 9 13 5

20/108 17/108 18/108 19/108 22/108

6

55

M

7

7 8 9

48 62 61

M M M

8 16 10

UPDRS: Unified Parkinson's Disease Rating Scale. (*) Preoperative levodopa equivalent dose expressed in mg/day represented the sum of levodopa and dopamine agonist. Dopamine agonist equivalent doses were calculated with the following equivalences: 100 mg levodopa = 2 mg apomorphine = 1 mg pergolide = 1.5–2 mg cabergoline = 1 mg pramipexole = 10 mg bromocriptine = 5 mg ropinirole (LIMPE, 2003). (**) Inhibitor of enzyme involved in degrading levodopa (Enzymatic Inhibitor): catechol-O-methyl transferase inhibitor (COMTI); monoamine oxidase inhibitor (MAOI); Dopa decarboxylase inhibitor (DDCI).

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Table 2 Electrode position details. Patient

1 2 3 4 5 6 7 8 9

Stimulated side

Right Right Left Left Right Right Right Left Right

Stereotactic coordinates

Optimal functional target position

AP

Lat

Vert

Ring

Slide

Trajectory

Distance from planned target (mm)

−4.0 8.0 7.0 0.0 −10.0 −3.0 8.0 9.0 5.0

9.5 6.5 −13.0 −7.5 11.0 11.0 10.0 −12.0 17.0

−8.0 −27.0 −10.0 −38.0 −29.0 −25.0 −10.0 −20.0 −17.0

49 55 60 65 55 55 61 57 56

13 15 17 19 20 15 18 17 15

C C C PL C C C C C

−1.0 + 3.0 0.0 + 2.5 + 3.0 0.0 + 1.0 + 2.5 + 1.0

(Model EZM 4, Grass, USA) (Rosa et al., 2010); (2) stimulation threshold: clinical assessment of optimal stimulation intensity followed by a pause for rest; (3) baseline recording: LFP recording before stimulation and without levodopa for 5 min (med off, stim off); (4) DBS on: LFP recording during DBS and without levodopa for 10 min (med off, stim on); (5) levodopa medication intake with DBS turned on: LFPs were recorded for as long as necessary for levodopa to achieve its clinical effect (about 30 min) and a further 10 min after patients reached the levodopa on condition (med on, stim on); and (6) DBS off: LFPs were recorded for 5 min after DBS was turned off and the patients were still in the “on” levodopa condition (med on, stim off). To distinguish between the clinical effects induced by DBS and levodopa only one nucleus was stimulated per patient. The threshold for therapeutic and side effects of DBS was established by an experienced neurologist on the body side contralateral to the stimulated nucleus and, in general, resembled that seen in the intraoperative monitoring procedures. The clinical effect of levodopa was determined on the body side contralateral to the non-stimulated nucleus. The nucleus contralateral to the most affected body side was chosen for stimulation. Monopolar STN-DBS was delivered through contact 1, placed in the optimal functional target as detailed in the foregoing, and differential LFP recordings were acquired between contacts 0 and 2 in the stimulated side through the FilterDBS system (Rossi et al., 2007). For electrical stimulation we used a constant voltage stimulator (Dual Screen, Medtronic) and DBS was delivered with a pulse width of 60 μs and frequency of 130 Hz at a stimulation strength for clinical effects. For pharmacological stimulation we delivered a clinically effective levodopa dose according to individual patient's therapy (Table 1). The FilterDBS device for artifact-free recording (Rossi et al., 2007) was connected to contacts 0–2 on the 3389 Medtronic electrode leaving contact 1 (target STN contact) free for DBS delivery. The signal was amplified (50,000×) and filtered (0.5–45 Hz) through FilterDBS, then

DBS efficacy (% decrease of rigidity)

100 90–100 70–80 90–100 90–100 90 90–100 90 100

digitalized (Micro 1401 Cambridge Electronic Design, Cambridge, England), with sampling rate of 2500 Hz and 12 bit quantization with 5 V range and stored on a computer for further analysis. A skin Ag/AgCl electrode (RedDot, 3M, USA) was used as recording reference. Data analysis Data were analyzed off-line with Matlab software (version 7.3, The Mathworks, Natick, MA, USA). The oscillatory activity from the STN was quantified in the frequency domain by power spectral analysis of the recorded LFP using a non-parametric approach based on the discrete Fourier transform (DFT). Each spectrum was estimated on 100 s long data in the following four states of interest: prestimulation (med off, stim off), after 4 min of DBS without levodopa (med off, stim on), after levodopa began to act and DBS on (med on, stim on), and after turning off DBS with levodopa (med on, stim off) (Fig. 1). More specifically, spectra were calculated using Welch's averaged, modified periodogram method (Welch, 1967) implemented by the Matlab function “pwelch”. The signal, composed of n samples, was divided into K segments obtained by windowing the signal with a Hanning window W( j) and for each segment the modified periodogram Ik was calculated from the DFT coefficients Ak(n). Each segment was L = 128 samples in length, to obtain a frequency resolution of 0.98 Hz.

Ak ðnÞ =

1 1 L−1 −2πjn ∑ X ð jÞW ð jÞe L ; i = ð−1Þ2 L J=0 k

IK ðfn Þ =

L 2 jA ðnÞj ; K = 1; 2; 3; …; K; fn U k

Fig. 1. Experimental protocol. The gray arrows on the top represent the four local field potential (LFP) recording conditions (100 s LFP recording each): before stimulation (med off, stim off); without levodopa with DBS on (med off, stim on); on levodopa with DBS on (med on, stim on); and on levodopa with DBS off (med on, stim off). The black arrow is time (in minutes). The time arrow highlights DBS turning on and off, levodopa intake and the approximate time when the levodopa effect begins.

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=

n L 1 L−1 2 ; n = 1; 2; 3; …; ; U = ∑ W ð jÞ L 2 L j=0

The power spectral density (PSD) of each signal was obtained by averaging the periodogram calculated in each segment. To account for the high inter-subject variability, the PSD in each nucleus was normalized by the total spectral power of the 2–45 Hz frequency range in the med off–stim off condition, considered as baseline. LFP activity in the beta band was then quantified by estimating the spectral power, calculated as SPB =

∑ PSDð f Þ f ∈B

where B is the band of interest (8–20 Hz) and SPB is the spectral power. The beta band considered included also the alpha band (Marceglia et al., 2006b; Rosa et al., 2010). To detect the time course of beta modulation during the whole experimental session, data were analyzed with a time-frequency approach (short time Fourier transform, STFT). PSD was calculated each second, starting 4 min before DBS was turned on, and ending 4 min after DBS was turned off, with a frequency resolution of 0.17 Hz. DBS on and off transient states (1 min before and 1 min after DBS was turned on/off) were studied with the same approach using a time resolution of 1 s and a frequency resolution of 0.25 Hz. Identifying the beta peak Before DBS and levodopa induced changes, each nucleus was characterized to detect a peak in the beta range. To do so, the mean and standard deviation (SD) of the PSD in the 6–48 Hz band in each nucleus were considered to obtain the threshold for significant spectral peaks (95% confidence interval, CI: mean ± 1.97 SD). PSD values in the beta band exceeding this threshold were considered as a significant peak. The central beta band frequency was calculated as the frequency displaying the highest PSD value. Statistical analysis Statistical analysis was performed both considering the whole population (N = 9 nuclei) and considering only the females (N = 5 nuclei), that are known to have more beta activity (Marceglia et al., 2006b). A two-way repeated measures analysis of variance (ANOVA) of the LFP logarithmic beta power was run for each condition (med off, stim off; med off, stim on; med on, stim on; med on, stim off) with factors “stimulation condition” (within factor, two levels: levodopa and DBS) and “stimulation state” (within factor, two levels: ON and OFF). Tukey honest significant test was used for post hoc analysis; differences were considered significant at p b 0.05. To determine how DBS influenced beta activity in the female group (N = 5) the non-parametric Wilcoxon paired test was applied on the (med off, stim off) vs. (med off, stim on) condition and on the (med on, stim on) vs. (med on, stim off) condition. Differences were considered significant at p b 0.05. Pearson's linear correlation coefficient was calculated (p b 0.05) between impedance values of the contact pair used for recording (0–2) and individual beta powers to assess the dependency of beta on the recording condition (Rosa et al., 2010). Pearson's coefficient was also used to study the correlation between disease stage, rated by the Hoehn and Yahr scale (Table 1) and individual beta powers to assess the dependency of beta activity on the disease stage. Results Before DBS, without levodopa, spectral analysis showed that in six of the nine STN nuclei studied, beta band frequencies exceeded the

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threshold (see Identifying the beta peak) (Table 3). Of these six nuclei, five were female and only one was male. No significant differences were found in central beta frequencies for the studied nuclei (Table 3). Correlation analysis between impedances and logarithmic beta power showed that beta power was independent from the impedance value (R2 = 0.24, p = 0.179). Similarly, correlation analysis between disease stage and beta power showed that beta power was independent from the disease stage (R2 = 0.22, p = 0.195). Data for the whole population (N = 9 nuclei) showed that levodopa significantly decreased beta power oscillations (mean [AU] ± 95% CI: med off, stim off: 1.39 ± 0.13, med off, stim on: 1.39 ± 0.24, med on, stim on: 1.24 ± 0.22, med on, stim off: 1.11 ± 0.16) whereas DBS left them almost unchanged. Two-way repeated measures ANOVA identified as the only significant factor “stimulation state” (p = 0.026) whereas the “stimulation condition” factor and the interaction between the two factors were not (factor “stimulation condition”: p = 0.693; interaction “stimulation condition” × “stimulation state” p = 0.167) (Fig. 2a and b). Whereas before levodopa, the grand-average power spectra showed a clear beta peak (med off, stim off and med off, stim on), after levodopa intake, in the on condition, the peak disappeared (med on, stim on and med on, stim off). Conversely, before DBS, power spectra for the five female subjects invariably showed an unmistakable beta peak, after DBS, beta power decreased significantly (med off stim off: 1.44 ± 0.12 vs. med off stim on: 1.21 ± 0.04, p = 0.043, Fig. 2c and d). A further analysis disclosed that before DBS, all five nuclei exceeded the threshold for a significant beta peak and when DBS was turned on, the significant peak remained, thus indicating that DBS did not abolish the beta peak, but decreased it (Fig. 2c). Conversely, when DBS was turned off, beta activity slightly, though not significantly, increased (med on, stim on: 1.024 ± 0.14 vs. med on, stim off: 1.14 ± 0.15, p = 0.500). Data for the time course of beta modulations during the whole experiment in each female patient showed that beta band power decreased during DBS, but decreased most prominently after levodopa intake (Fig. 3). In the transient state when DBS was turned on, beta power decreased, whereas when DBS was turned off it increased. When DBS was turned on or off beta band power changed almost immediately. In the only male nucleus with a beta peak, beta band power increased during DBS. The PSD during DBS exceeded the cutoff value (Fig. 4). Discussion Our results showed that whereas levodopa abolished the subthalamic beta LFP oscillations in all the patients with PD studied, DBS decreased beta oscillations only in some patients all of whose LFP recordings already showed high beta activity at baseline. Another difference was that, whereas levodopa completely suppressed LFP beta oscillations, DBS merely decreased them. When we combined DBS and

Table 3 Nuclei characterization. Nucleus

Beta

1 2 3 4 5 6 7 8 9

× × × × × × nf nf nf

Central frequency OFF–OFF

OFF–ON

14.6 11.7 15.6 13.6 16.6 15.6 – – –

15.6 11.7 19.5 11.7 16.6 11.7 – – –

× = significant beta peak found. nf = significant beta peak not found.

Impedance (kΩ)

med OFF stim ON

med ON stim ON

med ON stim OFF

8.8 11.4 11.2 11.3 10.6 11.5 11.0 10.4 7.1

↓ ↓↓ ↓ ↓ ↓ ↑ ↑↑↑ ↑↑ ↑↑↑

↓↓↓ ↓↓↓ ↓↓ ↓↓↓ ↓↓↓ ↑↑ ↑↑ ↑↑↑ ↑↑

↓↓ ↓ ↓↓ ↓↓ ↓↓ ↓ ↓ ↓ ↓

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Fig. 2. Population results. (a) Grand average (nine nuclei) of the power spectral density (PSD) in the four experimental conditions: prestimulation (med off, stim off—black, solid line); levodopa off and DBS on (med off, stim on—dark gray, solid line); levodopa on and DBS on (med on, stim on—black, dashed line); levodopa on and DBS off (med on, stim off— light gray, solid line). y-axis: normalized PSD (arbitrary units, logarithmic scale); x-axis: frequency (Hz, linear scale). Frequency resolution: 0.98 Hz. (b) Histograms represent logarithmic beta power for each condition on the whole population, nine nuclei (black = med off, stim off; dark gray = med off, stim on; gray = med on, stim on; light gray = med on, stim off). Error bars represent the confidence interval of the estimated mean (1.96 * SE). *p b 0.05. Note that beta band power decreases when patients are on levodopa, but not when they are on stimulation. (c) Grand average (five nuclei, female population) PSD in the four conditions: prestimulation (med off, stim off—black, solid line); levodopa off and DBS on (med off, stim on—dark gray, solid line); levodopa on and DBS on (med on, stim on—black, dashed line); levodopa on and DBS off (med on, stim off—light gray, solid line). y-axis: normalized PSD (arbitrary units, logarithmic scale); x-axis: frequency (Hz, linear scale). Frequency resolution: 0.98 Hz. (d) Histograms represent logarithmic beta power for the female population, five nuclei in the med off, stim off (black) and in the med off, stim on (dark gray) conditions. Error bars represent the confidence interval of the estimated mean (1.96 * SE). *p b 0.05.

levodopa, the levodopa-induced beta disruption predominated the power spectrum, and DBS combined with levodopa induced no significant additive effect. When we tried to characterize the nuclei studied to detect a beta peak, we found that the beta oscillation was highly variable among the patients studied, and that LFP recordings disclosed a clearly visible beta peak in only six of the nine patients studied. This variability does not depend on methodological differences related to impedance variations in the time elapsing between surgery and recordings, because, confirming previous findings (Rosa et al., 2010), we found no correlation between beta power and recording impedance. Electrodes were positioned in the most effective STN area as proven by intraoperative electrophysiological monitoring, thus excluding the possibility that electrode position influenced this variability (Marceglia et al., 2010). Beta power was also unrelated to the severity of disease and to the disease stage as measured by the UPDRS III and Hoehn and Yahr scale before DBS, because scores were comparable across subjects and no correlation between beta power and disease stage was observed. Even though a potential limitation of this study is the small sample size of patients, this inter-subject variability almost certainly

reflects the previously observed gender-related differences (Marceglia et al., 2006b). Accordingly, STN LFP recordings showed a clear beta peak in all five women studied but in only one of the four men. Another possibility is that patients' arousal state differed during the recording session (Urrestarazu et al., 2009). Despite this variability, levodopa influenced all our patients' STN beta oscillations in a similar manner. This finding is in line with previous studies showing that a clinically effective levodopa dose decreases beta oscillations, particularly those in the low-beta (13– 20 Hz) frequency range (Brown and Williams, 2005; Levy et al., 2002; Marceglia et al., 2006a; Priori et al., 2004). In our experimental protocol, we tested levodopa's clinical effectiveness independently from DBS on the side contralateral to STN DBS. These data suggest that levodopa acts locally on the ability of STN, and possibly also globus pallidus externus (GPe) neurons, to sustain spontaneous oscillations in the beta frequency range (Bevan et al., 2002). Levodopa could therefore shift power from beta to lower frequencies thus explaining why, as suggested by previous evidences, low-frequency oscillations increase after patients receive dopaminergic medication (AlonsoFrech et al., 2006; Priori et al., 2004).

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Fig. 3. Time course of beta power in a single representative nucleus. Subthalamic nucleus-local field potential (STN-LFP) time varying power spectrum in the beta band (8–20 Hz) of the patient 2. (a) Time–frequency plot over the entire experimental session (50 min total time, 42 min of deep brain stimulation, DBS). The black dotted lines, from the left, correspond to turning DBS on, to the clinical effect of levodopa, and to turning DBS off, respectively. Temporal resolution: 1 min; frequency resolution: 0.016 Hz; y-axis: frequency of LFP oscillations in the beta range (8–20 Hz, log scale); x-axis: time (in minutes, linear scale). Oscillation power is the color-coded on the bar on the right (white: high power; black: low power). (b) Transient states when DBS was turned on (left panel) and off (right panel); the time course of beta modulation was evaluated 1 min before to 1 min after DBS on/off. Temporal resolution: 1 s; frequency resolution: 0.24 Hz; the plots are organized as in (a).

Conversely, DBS decreased STN LFP beta oscillations only in those patients with higher beta activity at baseline. Why DBS increased beta activity in one of these patients remains unclear. However, the stimulation effectiveness was proved in all patients: during intraoperative stimulation tests, DBS-induced rigidity decrease was around 90–100%. In addition, during the experimental session, we tested the

Fig. 4. Beta power increase after DBS turning on in a single nucleus. Prestimulation and on DBS power spectral density (PSD) in the subthalamic local field potential (STN-LFP) of a single nucleus (6) on the stimulated side. y-axis: normalized power density (arbitrary units, logarithmic scale); x-axis: frequency (Hz, linear scale). Frequency resolution: 0.98 Hz. Note that the PSD for this nucleus increases when DBS is turned on.

clinical effects of DBS in relieving parkinsonian symptoms by qualitatively evaluating the rigidity decrease, and all patients subjectively reported that their motor condition seemed to improve when DBS was turned on. Hence, the whole effect of DBS is more complex than a simple reduction of the beta activity. Studies in recent years show that high-frequency stimulation, within the therapeutically effective frequency range of human DBS (120–180 Hz), evokes striatal dopamine release (Nimura et al., 2005; Shon et al., 2010). Although DBS could act on local STN beta oscillations thereby decreasing activity also in the GPi (Brown et al., 2004; Meissner et al., 2005), it could also act at neuronal circuit level, partially restoring a more correct input to the STN, normalizing subthalamic oscillation patterns, including beta oscillation (Kuhn et al., 2009). Some evidence shows that an excessive desynchronization in the beta range could be responsible for levodopainduced dyskinesias (Kuhn et al., 2009; Marceglia et al., 2007a), thus suggesting that the destroying action of levodopa on beta oscillation together with the over-boosting action on low-frequency oscillation might represent an excessive shift of the oscillatory pattern inducing hyperkinesias (Alonso-Frech et al., 2006). Alternatively, DBS might drive neuronal activity throughout the whole cortico-basal gangliathalamo cortical circuit, thus normalizing the LFP pattern. In this study, levodopa-induced changes in LFP beta oscillations in parkinsonian patients predominated over DBS-induced changes. And equally important, we observed no significant change, also in the group of patients in whom DBS reduced beta activity between the onlevodopa and on-DBS condition and on-levodopa and off-DBS condition. This was an expected finding given that levodopa is thought to

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increase synaptic plasticity whereas DBS does not (Prescott et al., 2009). Levodopa also decreases STN hyperactivity and increases local vasomotility as measured by functional neuroimaging (Hirano et al., 2008) whereas STN-DBS does not elicit this dissociated effect. Hence, the increased synaptic plasticity induced by levodopa could have caused a “saturation” on the level of STN oscillations that are the expression of synchronous presynaptic and postsynaptic activity. We cannot, however, exclude the possibility that the two therapies combined induced an additive effect because in some patients STN oscillations increased slightly when we turned DBS off (Fig. 3). Observing a similar additive effect in bradykinetic patients (Timmermann et al., 2008) others hypothesized that because levodopa acts primarily on the primary motor cortex, whereas DBS acts predominantly on the supplementary motor area, the two therapies combined could normalize oscillatory activity in both areas at least in those patients showing bradykinesia as predominant symptom. Hence, considering the relatively small number of patients also in our sample, inter-patient variability in the summative effect could explain the lack of statistical significance. The study should be thus extended to a larger number of nuclei to better establish this issue. Finally, these results could be important in developing new adaptive DBS devices able to optimize online stimulation parameters according to the ability of LFPs to reflect the patient's clinical state (Marceglia et al., 2007b; Rossi et al., 2007). If beta activity is too low after levodopa intake, DBS being completely ineffective could be turned off, or, conversely, if beta oscillations become excessive without levodopa, medication could be increased to normalize them. However, given the high variability among patients, also possibly related to the disease stage, the regulation of DBS parameters should be designed on the single patient, after a study of his personal response to the two therapies. Conclusions Our observations suggest that levodopa and DBS both modulate LFP beta oscillations. Disclosures The authors declare that there are no conflicts of interest. Acknowledgments This study was supported by the ERANET-Neuron Grant “PhysiolDBS” (Neuron-48-013), by Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (Milan, Italy), Università degli Studi di Milano (Italy), Ministero della Sanità (Italy), Ministero dell'Università e della Ricerca Scientifica e Tecnologica (Italy). The authors wish to thank Dr. Guglielmo Foffani for his helpful advance advice on data analysis. Simona Mrakic-Sposta is a doctoral student at the Scuola di dottorato di Ricerca di Medicina Molecolare, Dipartimento di Scienze e Tecnologie Biomediche LITA di Segrate, Università degli studi di Milano, Segrate. References Anon, 2001. Deep-brain stimulation of the subthalamic nucleus or the pars interna of the globus pallidus in Parkinson's disease. N. Engl. J. Med. 345, 956–963. Alegre, M., Rodriguez-Oroz, M.C., Valencia, M., Perez-Alcazar, M., Guridi, J., Iriarte, J., Obeso, J.A., Artieda, J., 2010. Changes in subthalamic activity during movement observation in Parkinson's disease: is the mirror system mirrored in the basal ganglia? Clin. Neurophysiol. 121, 414–425. Alonso-Frech, F., Zamarbide, I., Alegre, M., Rodriguez-Oroz, M.C., Guridi, J., Manrique, M., Valencia, M., Artieda, J., Obeso, J.A., 2006. Slow oscillatory activity and levodopainduced dyskinesias in Parkinson's disease. Brain 129, 1748–1757. Benabid, A.L., Chabardes, S., Mitrofanis, J., Pollak, P., 2009. Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson's disease. Lancet Neurol. 8, 67–81.

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