Data from: Exponential history integration with diverse temporal scales in retrosplenial cortex supports hyperbolic behavior
Creators
- 1. University of California, San Diego
Description
Animals rely on their experience to guide their next choice. In foraging-type tasks guided by history-dependent value, these experiences are typically integrated such that the weights of past events initially decay quickly over time but show a longer tail than expected by exponential decay. Rather, such integration is better described by a hyperbolic function. Hyperbolic integration affords sensitivity to both recent environmental dynamics and long-term trends, however the mechanism by which the brain implements this hyperbolic integration is unknown. We trained mice on a history-dependent, value-based decision task and found that the mice indeed showed hyperbolic decay on their weighting of past experience. However, the activity of history-encoding cortical neurons showed weighting with exponential decay. In resolving this apparent mismatch, we observed that cortical neurons encode history information heterogeneously across a wide variety of exponential time-constants, with the retrosplenial cortex (RSC) overrepresenting longer time-constants compared to other areas. A model that combines these diverse timescales of exponential history integration can recreate the heavy-tailed, hyperbolic history integration observed in behavior. In particular, time-constants of RSC neurons best matched the behavior, and optogenetic inactivation of RSC uniquely reduced the use of history information. These results indicate that behavior-relevant history information is maintained in neurons across multiple timescales in parallel, and suggest that the neural population in RSC is a critical reservoir of this information guiding decision-making.
Notes
Analysis Code
Code written in Python available in the linked Zenodo repository.
Behavior data
Data was recorded during mouse in vivo imaging or inactivation sessions. Behavior data is saved in Python pickle files in the pandas dataframe format.
a: choice type for each trial (Right choice, Left choice, Alarm, Miss) = (1,2,3,4)
R: reward outcome type for each trial. (Reward delivered, Reward not delivered) = (1,0)
Imaging data
Processed two-photon calcium imaging data, aligned to trial 'ready' period or 'choice' period. Saved as a netcdf file in the xarray dataset format, bundling neural activity for all cells recorded in a session with that session's behavior metrics.
spks: deconvolved estimate spike rate, aligned to ready cue onset. First data point corresponds to 2sec before ready cue onset. Last data point corresponds to 10sec after ready cue onset.
z_spks: zscore normalized spks, each cell zscored over the entire session.
Inactivation data
Behavior data from the inactivation sessions includes variable 'a' and 'R' as well as the inactivation condition 'Opto' and metadata associated with the inactivation parameters.
a: choice type for each trial (Right choice, Left choice, Alarm, Miss) = (1,2,3,4)
R: reward outcome type for each trial. (Reward delivered, Reward not delivered) = (1,0)
Opto: inactivation status for the trial. (cortical inactivation, control inactivation) = (1,0)
Inac Type: trial-aligned timing of inactivation, either aligned to the 'ready-answer' periods, the 'intertrial interval', or the both. String = ('ra', 'iti', '0i1ra')
Area: the area targeted for inactivation in that session
Analysis outputs
All of the outputs associated with the analysis are located in the respective directories. Reference the Jupyter notebook files for the specific analysis performed and the generation of the figures from the output data.
Funding provided by: David and Lucile Packard Foundation
Crossref Funder Registry ID: https://ror.org/032atxq54
Award Number:
Funding provided by: National Institute of Mental Health
Crossref Funder Registry ID: https://ror.org/04xeg9z08
Award Number: R03 MH120426
Funding provided by: National Institute of Mental Health
Crossref Funder Registry ID: https://ror.org/04xeg9z08
Award Number: F31 MH116613
Funding provided by: National Eye Institute
Crossref Funder Registry ID: https://ror.org/03wkg3b53
Award Number: R01 EY025349
Funding provided by: National Eye Institute
Crossref Funder Registry ID: https://ror.org/03wkg3b53
Award Number: P30 EY02259
Funding provided by: National Institute on Deafness and Other Communication Disorders
Crossref Funder Registry ID: https://ror.org/04mhx6838
Award Number: R01 DC018545
Funding provided by: National Institute of Neurological Disorders and Stroke
Crossref Funder Registry ID: https://ror.org/01s5ya894
Award Number: R01 NS091010
Funding provided by: National Institute of Neurological Disorders and Stroke
Crossref Funder Registry ID: https://ror.org/01s5ya894
Award Number: R01 NS125298
Funding provided by: Simons Foundation
Crossref Funder Registry ID: https://ror.org/01cmst727
Award Number:
Funding provided by: Uehara Memorial Foundation
Crossref Funder Registry ID: https://ror.org/00gc20a07
Award Number:
Funding provided by: Achievement Rewards for College Scientists Foundation
Crossref Funder Registry ID: https://ror.org/054awkm93
Award Number:
Methods
This dataset includes the processed data from in vivo two-photon calcium imaging, optogenetic stimulation, and behavioral choices from mice performing a decision-making task. The imaging data is trial-aligned fluorescence and deconvolved activity traces, as well as further analysis products of that data. The optogenetics data includes the stimulus parameters and the trial-by-trial choices made by the mice. Further details for the processing and acquisition can be found in the associated publication.
Files
chr2_optogenetics.zip
Files
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Additional details
Related works
- Is cited by
- 10.1126/sciadv.adj4897 (DOI)
- Is derived from
- 10.5281/zenodo.8152662 (DOI)