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Birtalan, E.

Publications and source records attributed to Birtalan, E..

2 recordsLinked to original sources

In Vivo Localization of Deep Brain Implants in Mice

Electrophysiology provides a direct readout of neuronal activity at a temporal precision only limited by the sampling rate. However, interrogating deep brain structures, implanting multiple targets or aiming at unusual angles still poses significant challenges even for expert operators, and errors are only discovered by post-hoc histological reconstruction. Here, we propose a method combining the high-resolution information about bone landmarks provided by micro-CT scanning with the soft tissue contrast of the MRI, which allowed us to precisely localize electrodes and optic fibers in mice in vivo. This enables arbitrating the success of implantation directly after surgery with a precision comparable to the gold standard histological reconstruction. Adjustment of the recording depth with electrode microdrives or early termination of unsuccessful experiments saves many working hours, while fast 3-dimensional feedback helps surgeons to avoid systematic errors. Increased aiming precision will allow more precise targeting of small or deep brain nuclei and multiple targeting of specific cortical layers.

neuroscience

Rapid learning of the 5-choice serial reaction time task in an automated rodent training system

Experiments aiming to understand sensory-motor systems, cognition and behavior often require animals trained to perform complex tasks. Traditional training protocols require lab personnel to move the animals between home cages and training chambers, to start and end training sessions, and in some cases, to hand-control each training trial. Human labor not only limits the amount of training per day, but also introduces several sources of variability and may increase animal stress. Here we present an automated training system for the 5-choice serial reaction time task (5CSRTT), a classic rodent task often used to test sensory detection, sustained attention and impulsivity. We found that fully automated training without human intervention greatly increased the speed and efficiency of learning, and decreased stress as measured by corticosterone levels. Introducing training breaks did not cancel these beneficial effects of automated training, and mice readily generalized across training systems when transferred from automated to manual protocols. Additionally, we validated our automated training system with mice implanted with wireless optogenetic stimulators, expanding the breadth of experimental needs our system may fulfill. Our automated 5CSRTT system can serve as a prototype for fully automated behavioral training, with methods and principles transferrable to a range of rodent tasks.

neuroscience