Contact Points
Plexon Inc 32-contact electrode with 90 degree rotated connector (92078-010), 32-contact electrode with 51 mm pig-tail tether (92078-012).
Salient characteristics:
• Passive electrodes for deep recordings in nonhuman primates
• 32 contact linear electrode arrays
• 100% Plexon V-probe compatible
• Sufficiently robust to tolerate 20 to 40 or more penetrations
• Validated for our application
• 120 mm overall length to reach deep structures
• Omnetics connector wired to match Ripple Nano head stages
• Omnetics connector at 90 degrees (type 1)
• Omnetics connector on 51 mm pig-tail tether (type 2)
The Laboratory of Neuropsychology investigates higher brain functions such as learning, memory and reward related decision making. Electodes are used for recording brain activity associated with motivated behaviors and to study pathways involved in decision making. Linear electrodes are ultrafine wires used to record signal from cells (neurons) in the brain. There are many characteristic requirements that must be met for such systems to work in a study. Once an specific electrode technology is selected, all other equipment, implants and electronics must work in unison with the chosen electrode technology. In this case, the technology has been chosen and the experiment has been started. However, we need two slightly different versions of the electrodes to solve the problem of clustering many (5) electrodes in a tightly packed space. This order is not a continuation of a prior order or contract.
The project is aimed at advancing our understanding of reward-based learning. It combines large-scale neuronal recordings, challenging decision-making tasks by nonhuman primates and advanced computational modeling to better understand the role of dopamine in motivated behaviors. Animals have been trained on multiple decision-making tasks where they win juice rewards of different flavors. Electrodes are being used to record from multiple areas of the brain known to participate in these tasks. Behavior will be modeled using reinforcement learning algorithms, then the activity of simultaneously recorded neurons will be processed through an advanced computational pipeline to test hypotheses about the contribution of each brain area to decision making.
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