A noteworthy in the dynamic field of neuroscience is the study of extracellular neural responses in live insect neurons, triggered by volatile organic compounds (VOCs). Biological olfaction has shown remarkable sensitivity in detecting low concentrations of VOCs, ranging from parts per billion (ppb) to parts per trillion (ppt) range, and minute changes in the compositions of gas mixtures. This scenario has inspired a novel concept for early lung cancer diagnosis, wherein odors exhaled by humans are channeled to insect sensory organs, like locust antennae. To effectively implement this scheme, efficient neural activity recording tools and robust analysis methods are essential. Tetrodes are commonly used in insect neural recordings, but are limited by their design, having only four electrodes that are widely spaced, rendering them relatively inefficient for detailed neural signals. Microelectrode arrays (MEAs) present a more promising alternative. Yet, in the specific context of insect brain neurology, there is a growing need for flexible, multi-channel, or even high-density MEAs(HDMEAs). Flexible MEAs, particularly those with high-density configurations, offer significant advantages over traditional rigid systems, including reduced tissue damage, better long-term stability, and higher resolution in both electrophysiological recording and biosensing applications. This dissertation presents the development and validation of advanced biosensing platforms for neurophysiological recording, emphasizing the integration of flexible dual-sided MEAs with locust olfactory systems to detect lung cancer biomarkers from VOCs. Through a multidisciplinary approach combining materials science, electronic engineering, and neurobiology, we explore the capabilities of HDMEAs and traditional MEAs to enhance the spatial and temporal resolution of neural recordings in both experimental and clinical settings. Chapter 1 begins with a foundational understanding of physiological signals and the techniques used to record them, followed by an in-depth discussion of MEAs, their principles, and their historical development. Special attention is given to the importance of flexibility and high channel density, which have transformed the design and performance of MEAs. Through an analysis of current flexible high-density MEAs, their fabrication, and the challenges they face, the chapter highlights the innovations that have propelled these tools into cutting-edge bioelectronic applications. Finally, strategies and future directions for next-generation flexible HDMEAs are outlined, setting the stage for their continued role in advanced sensing and neural interfacing technologies. Chapter 2 explores the development of dual-sided MEAs designed to enhance the recording capabilities and mechanical reliability necessary for in vivo insects’ applications. The innovative folding-annealing technique used in this research allows for a substantial increase in the density of recording sites without expanding the MEAs' physical footprint. Chapter 3 expands on the application of these technologies, detailing the development of a flexible, dual-sided microelectrode array optimized for capturing the complex neural dynamics of the locust olfactory system. This novel biosensing platform leverages the locust's acute sensory detection capabilities to identify cancer-related VOCs, offering a promising alternative to traditional diagnostic methods like gas chromatography-mass spectrometry (GC-MS). Chapter 4 provides a comprehensive outlook and delineates ongoing work and conclusions from this research. Overall, this dissertation demonstrates the potential of merging biological systems with electronic sensing technologies to create sensitive and non-invasive diagnostic tools for human lung cancer. This work not only contributes to the field of biomedical engineering but also opens avenues for future research into bioelectronic interfaces and their applications in medical diagnostics.
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