Article Topics

The field of bioelectronic medicine combines molecular medicine, bioengineering, and neuroscience to discover and develop nerve stimulating and sensing technologies to regulate biological processes and treat disease.

Work submitted to the journal will cover topics in these disciplines but may also expand to topics in the fields of disease biology, bioinformatics, bioengineering, materials science, nanotechnology, neurosurgery, and device development. Ethical, legal and financial issues related to bioelectronic medicine and device development are welcomed. Significant negative results will be considered. 

The following are examples (not limitations) of topics which may be considered by the journal: basic science, preclinical science, clinical studies, transcranial modulation, telemetry, modeling, model-based control, neural decoding, algorithms, and related tools (i.e. electrodes).

Time Stability and Coherence Analysis of Multiunit, Single-Unit and Local Field Potential Neuronal Signals in Chronically Implanted Brain Electrodes

Gaurav Sharma, Nicholas Annetta, David Friedenberg, Tony Blanco, Daphne Vasconcelos, Ammar Shaikhouni, Ali R Rezai, and Chad Bouton
Introducing neural sensing and decoding to open-loop neurostimulation technologies has the potential to significantly improve the diagnosis and treatment of a wide variety of diseases treated through bioelectronic medicine. Chronically implanted multielectrode arrays (MEA) can be used for such neural sensing and are critical for obtaining data of high spatial and temporal resolution to provide accurate decoding. Signals recorded from these arrays include local field potentials (LFP), and multiunit (MU) and single-unit (SU) activity. LFP offer signal stability over time, but at the expense of decreased spatial resolution. SU activity, on the other hand, offers better spatial resolution, but is considered less stable in chronic applications. MU activity, which represents an aggregate spiking activity of a population of neurons on the order of several hundred microns away from the recording tip, is considered a signal that can offer a compromise between the two signals. Here we used a wavelet decomposition method to extract and characterize the LFP, MU and SU signals obtained from a 96-channel MEA implanted in the motor cortex of a nonhuman primate over a 7.5-month period. We observed that not only are the MU signals more stable over time compared with SU activity, but that they are also significantly less correlated among electrodes compared with LFP over the spatial scale of the implanted array. Histological analysis of tissue sections also revealed a 51% reduction in the number of neuronal cell bodies within a 100-μm radius around the electrode tips of the implanted tissue compared with control tissue. Our results indicate that MU activity offers long-term signal stability with less correlated signals, potentially providing an effective signal for neural sensing in bioelectronic medicine.
Bioelectronic Medicine 2015
Page Range
63 - 71
Date Published
September 9, 2015
Article PDF
15_010_sharma.pdfNew description3173 KB
Supplemental Data
15_010_sharma_suppl.pdfNew description181 KB
Sharma, Annetta, Friedenberg, Blanco, Vasconcelos, neural sensing, open-loop neurostimulation technologies, bioelectronic medicine, neural decoding, chronically implanted multielectrode arrays, MEA, local field potentials, LFP, multiunit activity, MU, single-unit activity, SU, chronic implants
Article Type
Research Article
This is a Current Volume Article
Current Volume