Article

Wireless Instantaneous Neurotransmitter Concentration System: electrochemical monitoring of serotonin using fast-scan cyclic voltammetry--a proof-of-principle study.

Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota 55905, USA.
Journal of Neurosurgery (Impact Factor: 3.15). 04/2010; 113(3):656-65. DOI: 10.3171/2010.3.JNS091627
Source: PubMed

ABSTRACT The authors previously reported the development of the Wireless Instantaneous Neurotransmitter Concentration System (WINCS) for measuring dopamine and suggested that this technology may be useful for evaluating deep brain stimulation-related neuromodulatory effects on neurotransmitter systems. The WINCS supports fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode (CFM) for real-time, spatially resolved neurotransmitter measurements. The FSCV parameters used to establish WINCS dopamine measurements are not suitable for serotonin, a neurotransmitter implicated in depression, because they lead to CFM fouling and a loss of sensitivity. Here, the authors incorporate into WINCS a previously described N-shaped waveform applied at a high scan rate to establish wireless serotonin monitoring.
Optimized for the detection of serotonin, FSCV consisted of an N-shaped waveform scanned linearly from a resting potential of +0.2 to +1.0 V, then to -0.1 V and back to +0.2 V, at a rate of 1000 V/second. Proof-of-principle tests included flow injection analysis and electrically evoked serotonin release in the dorsal raphe nucleus of rat brain slices.
Flow cell injection analysis demonstrated that the N waveform, applied at a scan rate of 1000 V/second, significantly reduced serotonin fouling of the CFM, relative to that observed with FSCV parameters for dopamine. In brain slices, WINCS reliably detected subsecond serotonin release in the dorsal raphe nucleus evoked by local high-frequency stimulation.
The authors found that WINCS supported high-fidelity wireless serotonin monitoring by FSCV at a CFM. In the future such measurements of serotonin in large animal models and in humans may help to establish the mechanism of deep brain stimulation for psychiatric disease.

0 Bookmarks
 · 
112 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: The distribution and density of neurons within the brain poses many challenges when making quantitative measurements of neurotransmission in the extracellular space. A volume neurotransmitter is released into the synapse during chemical communication and must diffuse through the extracellular space to an implanted sensor for real-time in situ detection. Fast-scan cyclic voltammetry is an excellent technique for measuring biologically relevant concentration changes in vivo; however, the sensitivity is limited by mass-transport-limited adsorption. Due to the resistance to mass transfer in the brain, the response time of voltammetric sensors is increased, which decreases the sensitivity and the temporal fidelity of the measurement. Here, experimental results reveal how the tortuosity of the extracellular space affects the response of the electrode. Additionally, a model of mass-transport-limited adsorption is utilized to account for both the strength of adsorption and the magnitude of the diffusion coefficient to calculate the response time of the electrode. The response time is then used to determine the concentration of dopamine released in response to salient stimuli. We present the method of kinetic calibration of in vivo voltammetric data and apply the method to discern changes in the KM for the murine dopamine transporter. The KM increased from 0.32 ± 0.08 μM (n = 3 animals) prior to drug administration to 2.72 ± 0.37 μM (n = 3 animals) after treatment with GBR-12909.
    ACS Chemical Neuroscience 07/2014; DOI:10.1021/cn500020s · 4.21 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Movement is planned and coordinated by the brain and carried out by contracting muscles acting on specific joints. Motor commands initiated in the brain travel through descending pathways in the spinal cord to effector motor neurons before reaching target muscles. Damage to these pathways by spinal cord injury (SCI) can result in paralysis below the injury level. However, the planning and coordination centers of the brain, as well as peripheral nerves and the muscles that they act upon, remain functional. Neuroprosthetic devices can restore motor function following SCI by direct electrical stimulation of the neuromuscular system. Unfortunately, conventional neuroprosthetic techniques are limited by a myriad of factors that include, but are not limited to, a lack of characterization of non-linear input/output system dynamics, mechanical coupling, limited number of degrees of freedom, high power consumption, large device size, and rapid onset of muscle fatigue. Wireless multi-channel closed-loop neuroprostheses that integrate command signals from the brain with sensor-based feedback from the environment and the system's state offer the possibility of increasing device performance, ultimately improving quality of life for people with SCI. In this manuscript, we review neuroprosthetic technology for improving functional restoration following SCI and describe brain-machine interfaces suitable for control of neuroprosthetic systems with multiple degrees of freedom. Additionally, we discuss novel stimulation paradigms that can improve synergy with higher planning centers and improve fatigue-resistant activation of paralyzed muscles. In the near future, integration of these technologies will provide SCI survivors with versatile closed-loop neuroprosthetic systems for restoring function to paralyzed muscles.
    Frontiers in Neuroscience 09/2014; 8:296. DOI:10.3389/fnins.2014.00296
  • [Show abstract] [Hide abstract]
    ABSTRACT: Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.
    Australasian physical & engineering sciences in medicine / supported by the Australasian College of Physical Scientists in Medicine and the Australasian Association of Physical Sciences in Medicine 09/2014; DOI:10.1007/s13246-014-0297-2 · 0.85 Impact Factor

Full-text (2 Sources)

Download
22 Downloads
Available from
May 19, 2014