Previously, we developed a novel model for anxiety during motivated behavior by training rats to perform a task where actions executed to obtain a reward were probabilistically punished and observed that after learning, neuronal activity in the ventral tegmental area (VTA) and dorsomedial prefrontal cortex (dmPFC) represent the relationship between action and punishment risk (Park & Moghaddam, 2017). Here we used male and female rats to expand on the previous work by focusing on neural changes in the dmPFC and VTA that were associated with the learning of probabilistic punishment, and anxiolytic treatment with diazepam after learning. We find that adaptive neural responses of dmPFC and VTA during the learning of anxiogenic contingencies are independent from the punisher experience and occur primarily during the peri-action and reward period. Our results also identify peri-action ramping of VTA neural calcium activity, and VTA-dmPFC correlated activity, as potential markers for the anxiolytic properties of diazepam.

No abstract

Extracting single-unit activity from in vivo extracellular neural electrophysiology data requires sorting spikes from background noise and action potentials from multiple cells in order to identify the activity of individual neurons. Typically this has been achieved by algorithms that employ principal component analyses followed by manual allocation of spikes to individual clusters based on visual inspection of the waveform shape. This method of manual sorting can give varying results between human operators and is highly time-consuming, especially in recordings with higher levels of background noise. To address these problems, automatic sorting algorithms have begun to gain popularity as viable methods for sorting electrophysiological data, although little is known about the use of these algorithms with neural data from midbrain recordings. KiloSort is a relatively new algorithm that automatically clusters raw data which can then be manually curated. In this report, we compare results of manually-sorted and KiloSort-processed recordings from the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). Sorting with KiloSort required substantially less time to complete, while yielding comparable and consistent results. We conclude that the use of KiloSort to identify single units from multi-channel recording in the VTA and SNc is accurate and efficient.

No abstract

Previously, we developed a novel model for anxiety during motivated behavior by training rats to perform a task where actions executed to obtain a reward were probabilistically punished and observed that after learning, neuronal activity in the ventral tegmental area (VTA) and dorsomedial prefrontal cortex (dmPFC) encode the relationship between action and punishment risk (Park & Moghaddam, 2017). Here we used male and female rats to expand on the previous work by focusing on neural changes in the dmPFC and VTA that were associated with the learning of probabilistic punishment, and with anxiolytic treatment with diazepam after learning. We find that adaptive neural responses of dmPFC and VTA during the learning of anxiogenic contingencies are independent from the punishment experience and occur primarily during the peri-action period. Our results further identify peri-action ramping of VTA neural activity, and VTA-dmPFC correlated activity, as potential markers for the anxiolytic properties of diazepam.