Hardware tools for optogenetic neuroscience experimentation

  • Ruaridh Francis Winstanley

Student thesis: Doctoral Thesis

Abstract

Optogenetics confers the ability to precisely control the activity of neural populations with cell type specificity in response to illumination, providing a distinct advantage over the indiscriminate action of electrical stimulation. This added specificity offers considerable potential for advancement of experimental neuroscience, with applications ranging from improved understandings of neural circuits to the development of novel neuroprosthesis. The work presented here focuses on the development of hardware tools for optogeneticexperimentation; divided between the development of micro-LED neural probes, and electronic hardware for stimulation/recording control. The development of neural probes with both optical stimulation and electrical recording sites (commonly known as optrodes), capable of providing illumination up to 100 mW/mm2 is illustrated. A hybrid fabrication technique integrating micro-LEDs withmonolithic probes was demonstrated; offering an attractive technique for the development of neural probes with multi-spectral stimulation capabilities. To utilise such optoelectronic neural probes, a lightweight (sub 3g), low form factor (≈18x15x10mm) wireless stimulation system was realised; offering individual control of up to 16 µLED channels. Microprocessor control enables flexible control of intensity, pulse width and repetition rate with a temporal resolution of 0.1ms; facilitating creation of diverse optical stimulation patterns. IR communication allows user selection of pre-uploaded stimulation protocols or direct uploading of stimulation protocols to the system’s memory. A bi-directional neural stimulation/recording system was created to harness the ability of optrode probes, allowing electrical/optical stimulation combined with recording of up to 16 channels at a sampling rate of 20kHz. These features were translated to a prototype wireless SD card based logger (permitting recording at 1kHz). Exemplar closed loop algorithms based on threshold crossing events were implemented on these systems.
Date of Award5 May 2022
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsEPSRC (Engineering and Physical Sciences Research Council)
SupervisorKeith Mathieson (Supervisor) & Shuzo Sakata (Supervisor)

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