Dorsal striatum coding for the timely execution of action sequences
Cite this dataset
Martinez, Maria Cecilia; Belluscio, Mariano (2022). Dorsal striatum coding for the timely execution of action sequences [Dataset]. Dryad. https://doi.org/10.5061/dryad.8kprr4xpv
The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals' subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore-exploit balance.
Data were collected from several experiments that took place between 2013-09 to 2018-10 and 2022-01. Experiments were done with one male Long Evans rat at a time, and behavioral and electrophysiological data were collected in parallel during training sessions using commercially available hardware and software (sampling rate 32.5 kHz, Cheetah, Neuralynx). Neurophysiological and behavioral data were explored using NeuroScope (http://neuroscope.sourceforge.net; Hazan et al., 2006). Spike sorting was performed automatically, using KlustaKwik (http://klustawik.sourceforge.net), followed by a manual adjustment of the clusters (using “Klusters” software package; http://klusters.sourceforge.net, Hazan, et al., 2006). After the spike sorting procedure, all data were analyzed with MATLAB software using custom-built scripts and “FMAtoolbox” (http://fmatoolbox.sourceforge.net/).
An additional group of animals was included in the revised version of the manuscript. These were part of behavior-only experiments, trained in the same chamber as the others and only behavioral data were collected.
Custom-built software was written in English and documented in Spanish. All behavioral data is described in English.
The dataset .mat files are used with MATLAB. Additionally, there are spreadsheets containing behavioral data and mean normalized firing rates for all the registered units.
University of Buenos Aires, Award: 2018-2020 305BA
Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación, Award: PICT 2016-0396
Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación, Award: PICT 2017-0520
Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación, Award: PICT 2017-2465