Liujing Zhuang

A novel bioelectronic nose based on brain–machine interface using implanted electrode recording in vivo in olfactory bulb

The mammalian olfactory system has merits of higher sensitivity, selectivity and faster response than current electronic nose system based on chemical sensor array. It is advanced and feasible to detect and discriminate odors by mammalian olfactory system. The purpose of this study is to develop a novel bioelectronic nose based on the brain-machine interface (BMI) technology for odor detection by in vivo electrophysiological measurements of olfactory bulb. In this work, extracellular potentials of mitral/tufted (M/T) cells in olfactory bulb (OB) were recorded by implanted 16-channel microwire electrode arrays. The odor-evoked response signals were analyzed. We found that neural activities of different neurons showed visible different firing patterns both in temporal features and rate features when stimulated by different small molecular odorants. The detection low limit is below 1 ppm for some specific odors. Odors were classified by an algorithm based on population vector similarity and support vector machine (SVM). The results suggested that the novel bioelectonic nose was sensitive to odorant stimuli. The best classifying accuracy was up to 95%. With the development of the BMI and olfactory decoding methods, we believe that this system will represent emerging and promising platforms for wide applications in medical diagnosis and security fields.

Detection and classification of natural odors with an in vivo bioelectronic nose.

The mammalian olfactory system is recognized as one of the most effective chemosensing systems. We thus investigated the potential of utilizing the rats olfactory system to detect odors. By chronically coupling multiple microelectrodes to olfactory bulb of behaving rats, we extract an array of mitral/tufted cells (M/Ts) which could generate odor-specific temporal patterns of neural discharge. We performed multidimensional analysis of recorded M/Ts, finding that natural odors released from different fruit lead to distinct odor response patterns. Thus an array of M/Ts carried sufficient information to discriminate odors. This novel brain-machine interface using rats olfaction presents a promising method for odor detection and discrimination, and it is the first step towards in vivo bioelectronic nose equipped with biological olfaction and artificial devices.

Synchronized electromechanical integration recording of cardiomyocytes

Cardiac issues are always one of major health problems that attract wide attention by the public. It is urgent to explore a preclinical strategy to efficiently prevent the life-threatening arrhythmias by precisely assessing the cardiac excitation-contraction behavior. Conventional label-free asynchronous strategies are difficult to synchronously record and precisely match the excitation and contraction signals in vitro, while label-based strategies generally present pharmacological adverse effects and phototoxicity that significantly interfere the natural excitation and contraction signals. Both types of strategies preclude to exactly understand how cardiac excitation-contraction coupling changes in quantitative and coherent detail when dysfunctions occur. Here, we show a label-free synchronized electromechanical integration detection strategy that can synchronously monitor electrical and mechanical signals of cardiomyocytes over a long period of time by an integrated microelectrode-interdigitated electrode (ME-IDE). ME-IDE can detect subtle changes in electromechanical integration signals induced by drugs that target excitation-contraction coupling. Moreover, electromechanical integration delay is explored to specifically recognize the sodium channel inhibition. Furthermore, biomimetic electronic pacemaker function provides an alternative way to efficiently assess the drug-induced arrhythmia using refractory period of cardiomyocytes.

In vivo bioelectronic nose using transgenic mice for specific odor detection

This study focuses on the odor detection with “in vivo bioelectronic nose”. Still, high specific sensing elements and improved shelf-life are highly desired for the construction of biosensors. So we utilized the Green fluorescent protein (GFP) genetically labeled mouse M72 as sensing components to improve the specificity. In addition, long-term in vivo electrophysiological monitoring from M72 olfactory sensory neurons (OSNs) could be obtained by implanting the Microelectrode arrays (MEAs) probe into behaving mouses olfactory bulb. We first explored its reliability, repeatability, specificity for odor detection. We thus found it possessed high sensitivity for odors which contain benzene ring. Further, we explored its potential in trinitrotoluene (TNT) detection. The results illustrated that it can detect TNT in liquid concentration as low as 10−8M and can discriminate TNT from chemicals with similar structure. It is suggested that the in vivo biomimetic olfactory system could provide novel approaches for promoting the specificity and working-life of olfactory biosensors as well as detecting explosives.

Characterization of in vivo bioelectronic nose with combined manganese-enhanced MRI and brain-computer interface

The sensitivity and specificity of the in vivo bioelectronic nose is substantially enhanced by using mammals own olfactory system. However, where to implant the electrode in the OB are based on the researchers experiences, which results in unsatisfying success rate. This study takes advantage of the paramagnetism and calcium ion similarity of the manganese ion. A small dose of manganese ion is delivered into the right naris of the rat and an odor is delivered to its nose before MRI scanning. With the MRI data, a region in the olfactory bulb activated by the specific odor is identified. Micro-wire electrode is implanted into the region and olfactory signals are recorded. When the rat is stimulated by the specific odor, the LFP and spike signals are found to be responsive. The LODs to isoamyl acetate and n-butyric acid are determined to be 0.033μM and 0.0072μM, respectively.

In Vivo Bioelectronic Nose

Detection of odors has been applied to many real applications, such as quality control of food products, safety and security, environmental monitoring, medical diagnosis, and so on. These natural odors are composed of many different odorant molecules.

Mammalian Odor Information Recognition by Implanted Microsensor Array in vivo

The mammalian olfactory system has an exquisite capacity to rapidly recognize and discriminate thousands of distinct odors in our environment. Our research group focus on reading information from olfactory bulb circuit of anethetized Sprague‐Dawley rat and utilize artificial recognition system for odor discrimination. After being stimulated by three odors with concentration of 10 μM to rat nose, the response of mitral cells in olfactory bulb is recorded by eight channel microwire sensor array. In 20 sessions with 3 animals, we obtained 30 discriminated individual cells recordings. The average firing rates of the cells are Isoamyl acetate 26 Hz, Methoxybenzene 16 Hz, and Rose essential oil 11 Hz. By spike sorting, we detect peaks and analyze the interspike interval distribution. Further more, principal component analysis is applied to reduce the dimensionality of the data sets and classify the response.

ODOR DISCRIMINATION BY MITRAL CELLS IN RAT OLFACTORY BULB USING MICROWIRE ARRAY RECORDING

Response features of mitral cells in the olfactory bulb were examined using principal component analysis to determine whether they contain information about odorant stimuli. Using microwire electrode array to record from the olfactory bulb in freely breathing anesthetized rats, we recorded responses of different mitral cells to saturated vapor of anisole (1 M), carvone (1 M), isobutanol (1 M), citral (1 M) and isoamyl actate (1 M). The responses of single mitral cells to the same odorant varied over time. The response profiles showed similarity during certain amount of period, which indicated that the response was not only depended on odor itself but also associated with context. Furthermore, the responses of single mitral cell to different odorants were observed with difference in firing rate. In order to recognize different odorant stimuli, we apply four cells as a sensing group for classification using principal component analysis. Features of each cells response describing both temporal and frequency characteristics were selected. The results showed that five different single molecular odorants can be distinguished from each other. These data suggest that action potentials of mitral cells may play a role in odor coding.