Microelectrode Arrays Modified with Nanocomposites for Monitoring

Jul 5, 2019 - As shown in Figure 7c, the power decreased from 2.06 ± 0.76 mW to 1.12 ... The changes of DA concentration in different brain regions a...
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Microelectrode Arrays Modified with Nanocomposites for Monitoring Dopamine and Spike Firings under Deep Brain Stimulation in Rat Models of Parkinson’s Disease Guihua Xiao,†,‡ Yilin Song,†,‡ Yu Zhang,†,‡ Yu Xing,†,‡ Hongyan Zhao,§ Jingyu Xie,†,‡ Shengwei Xu,†,‡ Fei Gao,†,‡ Mixia Wang,†,‡ Guogang Xing,§ and Xinxia Cai*,†,‡ †

State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, PR China University of Chinese Academy of Sciences, Beijing 100049, PR China § Key Laboratory for Neuroscience, Ministry of Education and Ministry of Public Health Neuroscience Research, Institute and Department of Neurobiology, Peking University, Beijing 100191, PR China

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S Supporting Information *

ABSTRACT: Little is known about the efficacy of deep brain stimulation (DBS) as an effective treatment for Parkinson’s Disease (PD) because of the lack of multichannel neural electrical and chemical detection techniques at the cellular level. In this study, a 7-mm-long and 250-μm-wide microelectrode array (MEA) was fabricated to provide real-time monitoring of dopamine (DA) concentration and neural spike firings in the caudate putamen (CPU) of rats with PD. Platinumn nanoparticles and reduced graphene oxide nanocomposites (Pt/rGO) were modified onto the sensitive microelectrode sites. The detection limit (50 nM) and sensitivity (8.251 pA/μM) met the specific requirements for DA detection in vivo. A single neural spike was isolated due to the high signal-to-noise ratio of the MEA. DBS was applied in the affected side of the globus pallidus internal (GPi) in PD rats. After DBS, the concentration of DA in the bilateral CPU increased markedly. The mean increment of the ipsilateral DA was 7.33 μM (increasing from 0.54 μM to 7.87 μM), which was 2.2-fold higher than the increment in the contralateral side. The mean amplitude of neural spikes in the bilateral CPU decreased more than 10%, and was more obvious in the ipsilateral side where the spike amplitude changed from 169 μV to 134 μV. Spike firing rate decreased by 65% (ipsilateral side) and 51% (contralateral side). The power of the local field potential decreased to 940 μW (ipsilateral side) and 530 μW (contralateral side) in 0−30 Hz. Collectively, our data show that the GPi-DBS plays a significant regulatory role in the bilateral CPU in terms of DA concentration, spike firing, and power; furthermore, the ipsilateral variations of the dual mode signals were more significant than those in the contralateral side. These results provide new detection and stimulation technology for understanding the mechanisms underlying Parkinson’s disease and should, therefore, represent a useful resource for the design of future treatments. KEYWORDS: MEA, dopamine, spikes, DBS, Parkinson’s disease rats, in vivo, nanocomposites

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stimulation in these basal ganglia nuclei has been reported as a clinical treatment, particularly STN-DBS treatment.18 GPi-DBS had been confirmed to represent an acceptable target, but little research has been performed in this structure, largely because of a lack of suitable technology. Dopamine (DA) is the neurotransmitter responsible for the majority of neurological disorders.19 An imbalance of DA level in the basal ganglia of PD patients results in motor disorders.20 Previous authors used a microdialysis probe, an indirect technique, to record neurochemical release.21,22 Using this technique, electrophysiological signals, including local field potential (LFP) and neural spike signals, were recorded using a metal wire microelectrode. These methods focused on single

arkinson’s disease (PD) is one of the most challenging medical problems faced by the elderly; this is predominantly due to the complex pathogenesis of this disease and because we know very little about the mechanism involved.1−3 In recent years, the deep brain stimulation (DBS) technique, as applied in certain basal ganglia nuclei, has become the accepted and effective surgical therapy for PD patients.4−6 A number of publications have investigated the behavioral effects of PD in response to electrical stimulation, such as tremor.7−9 However, the precise mechanism involved is not completely understood due to the lack of research investigating DBS-induced changes at the neuronal level. DBS is hypothesized to alleviate the symptoms of neurological disorders by inhibiting an overactive or dysrhythmic focus.10,11 DBS also provides a special method with which to understand the inherent mechanisms of the basal ganglia loop. The effective DBS targets include the subthalamic nucleus (STN),12,13 the globus pallidus internus (GPi),14,15 and the thalamic ventral intermedius nucleus (Vim).16,17 Electrical © XXXX American Chemical Society

Received: January 24, 2019 Accepted: July 5, 2019 Published: July 5, 2019 A

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Figure 1. Schematic illustration of the fabrication process for SOI wafer probe along with some corresponding optical image. (a) Silicon dioxide grown on SOI wafer by wet oxidation. (b) Metallization and lift-off of Ti/Pt (10 nm/200 nm) metal layer. (c) SiO2/Si3N4 (300 nm/500 nm) deposition and patterned by photolithography. (d) Electrode opening via CHF3 reactive ion etching (RIE). (e) Electrode shape patterned. (f) Etching 30 μm Si by plasma deep etching. (g) Protecting front electrode by BN 303 and black adhesive glue. (h) Wet etching back silicon in 50% KOH solution. (i) Electrode release. (j) Optical image after metal layer lift-off. (k) Optical image after RIE. (l) Electrode released from wafer.

Figure 2. Micrographs of MEAs and their implantation location on the skull. (a) Structure of an MEA with nine recording microelectrodes for DA detection (Ch9) and electrophysiology detection (Ch1−Ch8), as viewed under a microscope. (b) Morphology of the microelectrode modified with Pt/rGO and characterized by scanning electron microscopy (SEM). (c) Location of the two MEAs and the stimulation electrode for GPi-DBS on the rat skull. (d) X-ray photoelectron spectroscopy full survey of electrode surface coated with Pt/rGO. (e) X-ray photoelectron spectroscopy full survey of electrode surface coated with Pt/rGO/Nafion.

MEAs were implanted into the bilateral caudate putamen (CPU) of PD rats to record variations in DA concentration and electrophysiology during GPi-DBS.

mode electrode recording such as single-unit activities or neurochemical release.23,24 In order to understand brain neuronmodulation in a direct manner, it is necessary to use a microelectrode probe to record single-unit activities and neurochemical release in real time.25 In our work, a 7-mm-long and 250-μm-wide microelectrode array (MEA) was fabricated to allow real-time monitoring of DA release and neural spike firings in the caudate putamen (CPU). In addition, we placed platinum nanoparticles and reduced graphene oxide nanocomposites (Pt/rGO) onto the recording microelectrodes to increase the ability of electron transmission.

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MATERIALS AND METHODS

Reagents. DA was purchased from Acros Organics (Belgium). Saline (0.9% NaCl) was purchased from the ShuangHe Corporation (China). Urethane powder, lead acetate, and chloroplatinic acid were purchased from Sinopharm Chemical Reagent company (China). Graphene oxide nanocomposites (GO) solution (2 mg/mL) was purchased from Xianfeng Corporation (China). Nafion solution (20%) was purchased from Sigma-Aldrich (USA). B

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Figure 3. Implantation pathways (marked with red fluorochrome in the brain slices of the experimental rat) compared with stereotaxic coordinates. (a) Two obvious MEA pathways to the CPU in the brain tissue slice. (b) Bilateral CPU shown on a map of stereotaxic coordinates for rat brain. (c) Unilateral pathway of the stimulation electrode to GPi. (d) Position of the GPi. (e) Enlargement of the GPi location undergoing stimulation. Apparatus. Electrochemical signals were recorded on a multichannel potentiostat (BioLogic VMP3, France) driven by EC-lab software. Electrical signals were recorded on a 128-channel neural data recording system (Blackrock Microsystems, USA). A micropositioner (model 2662, David KOPF instrument, USA) was used to implant the MEA sensor and record the depth of implantation. MEA Fabrication. The MEA sensor was mass fabricated by photolithographic methods in a superclean laboratory.25 The fabrication process is shown in Figure 1. Multiple electrodes were patterned onto a single silicon-on-insulator (SOI) substrate (30 μm Si; 1.5 μm SiO2; 650 μm Si). Initially, three microelectrode photographic masks were designed. The first mask included arrays of nine recording microelectrodes, connecting lines and bonding pads. The second mask helped to define the insulator areas; this ensured that the recording sites and bonding pads were active but the connecting lines were not. The third mask helped to define the shape of the individual sensor. Three steps of photolithography were applied on the SOI wafer and individual electrode was released by wet etching back silicon. Modification of Pt/rGO Nanocomposites. Prior to the modification process, the sensors were thoroughly cleaned using the O2 reactive ion etching (RIE). To prepare the plating solution, 19.2 mM of chloroplatinic acid, 1.68 mM of lead acetate, and 2 mg/mL of GO solution were mixed in the ratio of 1:1:2 and ultrasonicated for 2 h. A three-electrode configuration was created using a Pt counter electrode, an Ag|AgCl reference electrode and an MEA sensor recording site working electrode. Then, Pt black and GO nanocomposites were electroplated onto the surface of the recording sites surface by amperometry (−1.0 V, 50 s). Using the same three-electrode set, the sensor was transferred into 10 mL saline solution in order for GO to be reduced by cyclic voltammetry (CV, 50 mV/s, 10 cycles) with a potential range of 0.1 V to −1.6 V. Finally, 5 μL of Nafion (0.5% in ethanol) was dropped onto the DA channel, and then dried for 20 min at 100 °C. MEA Characterization and Testing. The sensitive microelectrodes were characterized by microscopy, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). As shown in Figure 2a, the electrodes were designed so that Ch1−Ch8 were for electrophysiological detection and Ch9 was for DA detection. A Pt counter electrode was integrated for three-electrode configuration. The ability of the MEA to detect single neural spike firing in vivo was due to the specific design of the MEA: (i) The microelectrodes designed on the tip of the electrode matched the size and distribution density of the neurons (20 μm electrode diameter and 50 μm spacing); (ii) the small size of the probe (7 mm long; 250 μm wide) could help to significantly reduce the risk of damage to the brain tissue; (iii) modifying the Pt/rGO on the microelectrode surface significantly reduced the impedance. As shown in Figure 2b, Pt nanoparticles were distributed on the wrinkled surface of rGO and therefore enhanced both surface area and current response. The design of the MEA, and its

modifications, resulted in a low level of background noise and improved signal-to-noise ratio. The XPS image shows the specific “F” (Nafion) existing on DA site surface (Figure 2d,e). For DA recording, it was necessary to calibrate the DA-sensitive microelectrode to equate the variation in DA oxidation current to a proportional variation of DA concentration. A three-electrode configuration was used including a Pt counter electrode, an Ag|AgCl reference electrode, and an MEA sensor working electrode. The calibration was performed on the BioLogic VMP3 potentiostat. First, CV was carried out in standard PBS and DA solution (50 μM, 100 μM, and 200 μM) to understand the DA reaction. Then, in order to evaluate the selectivity of the microelectrode, we used the amperometry method and applied common test interference, including glutamate (Glu), ascorbic acid (AA), serotonin (5-HT), 3,4-dihydroxyphenylacetic acid (DOPAC), and uric acid (UA) in 10 mL of PBS. All of these test substances were applied in the same concentration (20 μM). Then, different concentrations of DA (50 nM, 50 nM, 50 nM, 150 nM, and 2 μM each 8 times) were added into 10 mL of PBS for calibration. Protocol for Recording in the Brain of PD Rats. Male Sprague− Dawley rats (250 g, n = 4) were supplied by Peking University. All animal experiments were performed with permission from the Ethical Committee of Peking University. All efforts were made to minimize the number of animals used and their suffering. A rat model of PD was established by injecting 6-hydroxydopamine (6-OHDA) into the substantia nigra pars compacta (SNc: AP: 5.2 mm; ML: 2.1 mm; DV: −8.0 mm) and ventral tegmental area (VTA: AP: 6.8 mm; ML: 0.6 mm; DV: −8.6 mm). Four weeks after injection, apomorphine was injected into the neck muscles in order to observe the rotation behavior to confirm the PD model.26 Then, the PD rats were anesthetized and fixed onto a stereotaxic frame. As shown in Figure 2c, MEAs were inserted into the bilateral CPU (AP: 1.08 mm, ML: ± 2.4 mm, DV: −4.2 mm), and a commercial bipolar stimulation electrode was inserted into the GPi (AP: −2.45 mm, ML: 3 mm, DV: −7.8 mm). The stimulation brain side was defined as the side injured by 6-OHDA. Another two sites were also located: one for skull nail placement (AP: 2 mm, ML: −3.5 mm, DV: −0.5 mm) and the other for placement of the Ag|AgCl reference electrode (AP: −2 mm, ML: −3.5 mm, DV: −0.8 mm). Ch1−Ch8 recorded the electrophysiological signals by Blackrock Microsystems at a sampling rate of 30 kHz. A high pass filter (500 Hz) was used to obtain spike firings, while a low pass filter (100 Hz) was applied to obtain LFPs. Ch9 recorded the DA oxidation current using a BioLogic VMP3 potentiostat. A three-electrode configuration was used for DA recording. All experiments used the following stimulation parameters: a frequency of 100 Hz,27 a duration of 10 s,28,29 a pulse width of 60 μs,27 and an intensity of 300 μA.30 The stimulation square waveform was stable and consistent with those routinely used in the PD modes. The MEAs and stimulation electrode were coated with red fluorochrome to track their pathway. After in vivo experiments, C

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Figure 4. Typical calibration process for the DA channel. (a) Cyclic voltammetry in standard PBS, 50 μM, 100 μM, 200 μM DA solution. (b) Selectivity test curve created by adding 20 μM of DA, DA, Glu, AA, 5-HT, DOPAC, UA, and DA. (c) DA current−time curve created by adding 2 μM of DA at each step. The red rectangle represents the low concentration response. (d) Low concentration calibration created by adding 50 nM, 50 nM, 50 nM, and 150 nM DA. (e) Linear fitting curve of DA current to concentration in the range of 50 nM to 16.3 μM. (f) Enlarged linear fitting curve of DA response at low concentration (50−300 nM). perfusion surgery was carried out to identify and obtain the brain tissue of interest. The pathways of the sensors were clear in the bilateral CPU (Figure 3a) compared with the rat brain in stereotaxic coordinates (Figure 3b).31 The pathway of the stimulation electrode (Figure 3c) and the enlarged region of the GPi target (Figure 3e) were consistent with the GPi region in a brain map (Figure 3d).

The performance of the DA channel therefore met the requirements for in vivo detection, as it was associated with high sensitivity and selectivity. Synchronous Variation of DA and Electrophysiology in PD Rats under GPi-DBS. In the PD rats, we recorded the DA and electrophysiological response in the bilateral CPU simultaneously, as shown in Figure 5. Figure 5a,b shows the typical response of DA in the ipsilateral and contralateral CPU during GPi-DBS. GPi stimulation lasted for 10 s. DA increased transiently for 30 s and then rapidly decreased thereafter to baseline levels during GPi-DBS. The DA concentration increased by 10.06 μM in the ipsilateral CPU compared to 3.37 μM in the contralateral CPU. This implies that GPi-DBS increased the release of DA in the bilateral CPU and had more significant effects on the ipsilateral CPU in comparison to the contralateral CPU. GPi-DBS is widely used as a therapeutic option in the clinic and also has the ability to recover DA concentration in a rat model of PD. The real-time corresponding neural spike response is shown in Figure 5c (ipsilateral) and d (contralateral). Eight neural spike responses from Ch1−Ch8 are shown over a period of 100 s, including 20 s before stimulation, 10 s during stimulation, and 70 s after stimulation. The firing rate and spike amplitude were all decreased in the bilateral CPU. Prior to GPi stimulation, the clusters of spikes over the eight channels oscillated synchronously at 0.54 Hz (Figure 5c,d). The phenomenon of

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RESULTS Characterization of the MEA. MEA performance is shown in Figure 4. The CV curve shows an oxidation peak potential of 0.134 V (Figure 4a) used as a constant voltage in the amperometry method for DA detection. The selectivity test curve is shown in Figure 4b. The DA channel (Ch9) did not respond to Glu, AA, 5-HT, DOPAC, or UA. Consequently, our technique effectively excluded common sources of interference. Figure 4c shows a typical calibration curve of the DA channel within a concentration range of 50 nM to 16.3 μM. The red dashed rectangle represents the low concentration response shown in Figure 4d. The limit of detection (LOD) was 50 nM, and the signal-to-noise ratio was 3 (S/N = 3). This was sufficient enough to distinguish the lowest DA concentration in vivo. Figure 4e shows the fitting results and clearly illustrates the linearity of the current−concentration response; the lowconcentration fitting curve is shown in Figure 4f. The sensitivity was 8.514 pA/μM and the linearity was 0.999. The mean sensitivity of the DA channel (n = 4) was 8.251 ± 0.643 pA/μM. D

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Figure 5. Dynamic variation of DA concentration, spike firing, and LFP response in the ipsilateral (left) and contralateral (right) CPU during GPi stimulation. (a) Variation of DA concentration in the ipsilateral CPU during GPi-DBS. (b) Variation of DA concentration in the contralateral CPU. (c) Spike firing response in the ipsilateral CPU. (d) Spike firing response in the contralateral CPU. (e) LFPs response in the ipsilateral CPU. (f) LFPs response in the contralateral CPU. The duration of GPi-DBS on and off was 10 s.

MEA reflected the cell response and thus helps us to elucidate the mechanisms involved. Analysis of DA Level, Spike Firing, and LFP before and after GPi-DBS. We also analyzed the mean variation (n = 4) of DA concentration and electrophysiological signals before and after GPi-DBS. The variation in DA concentration is shown in Figure 6a. In the ipsilateral CPU, the DA increased from 0.54 ± 0.23 μM to 7.87 ± 0.76 μM after GPi-DBS. In the contralateral CPU, DA increased from 0.93 ± 0.34 μM to 4.26 ± 0.36 μM. Unilateral GPi stimulation evoked an increase in DA in the bilateral GPi. However, the increase in DA content seen in the ipsilateral CPU was higher than that in the contralateral CPU. The mean increment in the ipsilateral DA was 7.33 μM, which was 2.2 times higher than the increment observed on the contralateral side. Figure 6b shows the mean spike waveform sorted from the spike signal before and after stimulation in the bilateral CPU. As shown in Figure 6c, the amplitude of the spike decreased by 21% from 169 ± 21 μV to 134 ± 24 μV in the ipsilateral CPU. In the contralateral CPU, it decreased by 10% from 155 ± 25 μV to 140 ± 15 μV. As shown in Figure 6d, the spike firing rate decreased by 65% from 13.02 ± 2.56 Hz to 4.49 ± 2.17 Hz in the ipsilateral CPU and decreased by 51% from 8.14 ± 3.79 Hz to 4.00 ± 1.34 Hz in the contralateral CPU. Figure 7 shows the mean power spectral density (PSD) of LFPs in the 0−30 Hz frequency band. Prior to GPi-DBS, the

synchronous oscillation was disturbed by GPi-DBS; specifically, spikes recovered to a normal firing mode. GPi-DBS can therefore treat PD by modulating the spike firing mode to decrease the symptoms of synchronous discharge and thus relieve patient tremor. The LFP response in the ipsilateral and contralateral CPU is shown in Figure 5e,f. In the ipsilateral CPU, the LFP fluctuations were significantly suppressed after stimulation. Note that the mean amplitude of the LFP significantly reduced from 0.705 mV to 0.292 mV. The LFP fluctuation became assuasive. It then returned to the prefluctuation status after DBS for 30 s. In the contralateral CPU, the mean amplitude of LFP decreased from 0.535 mV to 0.254 mV and the periodic oscillatory state was disturbed by GPi-DBS. Neurochemical and electrophysiology are crucial signals that can be used to reflect neural activities. Many neurogenic diseases occur because of abnormal neural activity. Note that as DA increased, the amplitude and fluctuation frequency of LFP decreased. The spike firing frequency and amplitude also decreased. As DA decreased from its peak value, the LFP signal gradually approached a relatively higher amplitude and frequency, as it was prior to stimulation. Using GPi-DBS, neurochemical and electrophysiology can be modulated simultaneously to treat PD. At the neuronal level, the typical characterization of PD-like abnormal synchronous discharge and cell tremor can be relieved. Using dual mode signals, the E

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Figure 6. Changes of mean DA concentration and spike patterns in the bilateral CPU before (red) and after (blue) DBS. (a) Mean concentration of DA in the ipsilateral and contralateral CPU before and after GPi-DBS. (b) Mean spike waveform (derived from 12 354 spikes before stimulation and 4118 spikes after stimulation) in the ipsilateral CPU (solid line), and from 7331 spikes before stimulation and 3607 spikes after stimulation in the contralateral CPU (dashed line). (c) Mean amplitude (peak to peak) of the spikes in the bilateral CPU before and after stimulation. (d) Mean firing rate of the spikes in the bilateral CPU before and after stimulation.

Figure 7. Mean power spectral density of LFPs in the 0−30 Hz frequency band before stimulation (red) and after stimulation (blue). (a) Power spectral density in the ipsilateral CPU. (b) Power spectral density in the contralateral CPU. (c) Comparison of LFP power before and after DBS in the bilateral CPU. The amplitude of LFP was calculated at the μV level.

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bigger than the threshold value is needed to form a neural spike. This characteristic of a spike induces an “all or none” pulse signal. When a relatively high concentration of DA was released, the electrophysiology changed obviously with the increase of DA. For the LFP signals, it was obvious that the power spectrum was able to sustain consistent changes. The neural spikes produced must achieve the membrane threshold. Therefore, these spikes are more difficult to evoke than neurotransmitters. The DBS-generated electrical field interacts with the brain in complex ways. Several variables could influence the DBSinduced biophysical and clinical effects. The unilateral GPi-DBS affects the DA and electrophysiology response in the ipsilateral and contralateral CPU to different degrees. GPi-DBS can modulate the output of basal ganglia and results in the modulation of behavior. GPi-DBS tonically reduced neural activities by 89% and also reduced spike firing rate.46 Over the last few decades, the basal ganglia circuit was believed to integrate information from the cortex and project this information, via the thalamus, to the motor cortex and supplementary motor area.47,48 A significant body of research has addressed this target circuit and provided us with various new insights and perspectives on the mechanisms of many basal ganglia disorders. However, neuroelectricity and neurotransmitters represent the major communication method with which to transport cellular information through various neural networks. The mechanism underlying the use of electrical stimulation to alleviate the symptoms of movement disorders was believed to involve changes in the release of neurotransmitters. Furthermore, alterations in firing pattern can be used to treat neurological disorders. Herein, we verified that a basal ganglia circuit exists between the GPi and CPU in the bilateral cerebrum. DA and electrophysiological responses changed with GPi-DBS. GPi-DBS and STN-DBS represent two main clinical targets and have been compared in many experiments.49−51 We plan to use our MEA technology to compare changes at the neuronal level in order to confirm which will be the preferred target for DBS. Compared Amperometry and Fast-Scan Cyclic Voltammetry. Fast-scan cyclic voltammetry (FSCV) method also provides good temporal−spatial resolution and chemical resolution which is widely used in in vivo DA detection.52,53 In the FSCV detection method, the DA molecules adjacent to the electrode surface could be oxidized or reduced when potential is linearly applied. DA variation in the subsecond was recorded with high sensitivity and selectivity. We compared amperometry and FSCV method by testing our microelectrode arrays (MEA). In this part, autolab PGSTAT302N electrochemical workstation (Autolab, Switzerland) was used. The MEA at the temporal resolution of 0.01 s was tested as shown in Figure S1. The DA electrode responds to different DA concentration (Figure S1a) and shows a linear relationship between DA concentration and current. The selectivity to 5-HT, AA, UA, Dopac, and Glu was tested and shown in Figure S2. The selectivity is higher than 90% demonstrating that the MEA have the ability to block the common interferences. In the FSCV method, a typical triangle waveform is applied as Figure S3 with scan rate of 300 V/s. As shown in Figure S4, the DA current respond to the linear potential in the bare and DA solution (Figure S4b). The background-subtracted cyclic voltammetry shows a current peak of DA (Figure S4). It allows DA measurement with high temporal resolution and detection limitation. The MEA can respond to different DA concentration (Figure S5) and block the common interferences in the brain

PSD of LFPs in the ipsilateral CPU has a relatively peak value in the 10−18 Hz frequency band (Figure 7a). A relatively peak value of PSD in the 8−18 Hz band was also found in the contralateral CPU (Figure 7b). In the bilateral CPU, the PSD decreased significantly after DBS. As shown in Figure 7c, the power decreased from 2.06 ± 0.76 mW to 1.12 ± 0.53 mW (with a reduction of 940 μW) in the ipsilateral CPU. However, in the contralateral CPU, the power decreased from 1.42 ± 0.43 mW to 0.89 ± 0.49 mW (with a reduction of 530 μW).

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DISCUSSION GPi-DBS Regenerates DA in the Brain. The changes of DA concentration in different brain regions after DBS is shown in Table S1. Note that different stimulation parameters and different brain areas would induce different DA concentration increase. The DA level in the CPU of PD rats was significantly increased after unilateral GPi-DBS. PD is considered a typical movement disorder, which results from a reduction in the number of dopaminergic neurons in the motor portions of the putamen.32 L-dopa, a precursor of DA, is approved as an effective clinical therapeutic with which to alleviate the symptoms of PD.33,34 It is well-known that L-dopa can be transformed into DA to modulate the levels of DA in the brain. Compared with the results of increasing DA after L-dopa treatment, GPi-DBS also increased DA levels, in a similar way to L-dopa, representing a means of treating PD. Unilateral GPiDBS has therefore been considered as a potential therapy, which can reduce the L-dopa-induced respiratory dyskinesia in patients.35,36 Given the regenerated DA, GPi-DBS provides the possibility of reducing dopaminergic medication and druginduced dyskinesia. GPi-DBS is safe, and GPi combined with Ldopa would be a better option than STN-DBS.37 DBS has the potential to treat PD and alleviate the symptoms arising from DA-induced features.38 In many clinical therapies, bilateral stimulation has been shown to have greater significance than unilateral stimulation.39,40 Furthermore, Peppe’s team suggested that bilateral stimulation of the entire GPi is the most effective method to reduce abnormal movements in PD.41 Unilateral GPi-DBS evoked DA levels in both the ipsilateral and contralateral CPU. We infer that bilateral stimulation treatment may produce more DA than unilateral stimulation, at least in part. GPi-DBS Disturbs the Synchronous Discharge of Neurons. Many researchers have studied DBS in PD patients but only considered behavior, reaction time, symptom cognition, and mood with which to demonstrate therapeutic effect.7,42 We verified the effect upon neurotransmitters and neural discharge at the level of the neurons. DBS influenced the release of neurotransmitters and spike firing characteristics, in CPU based on the basal ganglia circuit (BG).43,44 GPi-DBS modulates dual mode signals in the CPU via the BG along with the neuronal activities of the nuclei involved in this BG circuit.14 From the above analyses, the pathway from the GPi to the ipsilateral and contralateral CPU was clearly different. The ipsilateral LFP signals were more sensitive to stimulation than the contralateral signals. LFP was sensitive to nearby neurons and recorded information from thousands of neurons.45 Therefore, in the ipsilateral CPU, the stimulation effects can be transported easily and sensitively. Moreover, stimulation would elicit variations in DA, spike activities, and LFP. Note that DA concentration responds to stimulation immediately while the spike signals begin to respond a little bit later than DA response for about 2 s (Figure 5a,c). Overvoltage that should be G

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ACKNOWLEDGMENTS This work was sponsored by NSFC (No. 61527815, No. 61601435), the National Key R&D Program of Nano Science and Technology of China (2017YFA0205902), and the Key Research Programs (QYZDJ-SSW-SYS015, XDA16020902) of Frontier Sciences, CAS.

(Figure S6). The sensitivity, linearity, and selectivity enable detection of DA concentration in vivo. We analyzed the correlation of current response between amperometry method and FSCV method (Figure S7). Those two methods show similar response trends during DA detection with a correlation coefficient of 0.990. In the future, we will combine the neuron activities information with animal behavior by using FSCV method in the freely moving animals to confirm our amperometry results.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors.9b00182. Additional text comparing the DA concentration after deep brain stimulation using different detection methods and the sensitivity and selectivity difference between amperometry method and FSCV method (PDF)

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REFERENCES

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CONCLUSIONS In this study, we fabricated a 7-mm-long and 250-μm-wide implantable MEA to simultaneously detect DA, spike firing, and LFP in a rat model of PD. The calibration results demonstrated the ability of our MEA to selectively respond to DA after modification with Pt/rGO nanoparticles. Low background current and impedance are the basis for low electrical detection in vivo. The in vivo recording results demonstrated that DA concentration increased significantly during GPi-DBS in the bilateral CPU and had a similar function as L-dopa in terms of clinical therapy. In addition, the abnormal synchronous spike discharges in the eight channels were disturbed and controlled. Specifically, the dual mode signal response in the ipsilateral CPU was much stronger than in the contralateral CPU during GPiDBS. First, DA concentration changed, then electrophysiological signals changed; this was because of the spike’s “all or none” principle. The use of MEA technology for in vivo detection would enhance our understanding of the GPi-DBS mechanism at the microscopic level. Understanding the mechanism underlying the beneficial effects of DBS would greatly improve the efficacy of this therapy by combining behavioral effects and neural activities. Our new technology provides an effective platform with which to record several types of neurotransmitters and the single unit spike.

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Article

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (X. Cai). ORCID

Hongyan Zhao: 0000-0002-5454-2759 Xinxia Cai: 0000-0001-5997-7252 Author Contributions

G. Xiao and X. Cai designed the research plan and experiments. G. Xiao and Y. Song designed and fabricated the probe. G. Xiao, Y. Zhang, Y. Xing, and F. Gao carried out the experiments including animal surgery and data recording. M. Wang and S. Xu analyzed the recording signals. H. Zhao and G. Xing established the rat model of PD. G. Xiao wrote the manuscript. All authors read and approved the final manuscript. Notes

The authors declare no competing financial interest. H

DOI: 10.1021/acssensors.9b00182 ACS Sens. XXXX, XXX, XXX−XXX

Article

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DOI: 10.1021/acssensors.9b00182 ACS Sens. XXXX, XXX, XXX−XXX