Decision Making in Mice During an Optimized Touchscreen Spatial Working Memory Task Sensitive to Medial Prefrontal Cortex Inactivation and NMDA Receptor Hypofunction
Bibliographic record
Abstract
Working memory is a fundamental cognitive process for decision-making and is a hallmark impairment in a variety of neuropsychiatric and neurodegenerative diseases. Spatial working memory paradigms are a valuable tool to assess these processes in rodents and dissect the neurobiology underlying working memory. The trial unique non-match to location (TUNL) task is an automated touchscreen paradigm used to study spatial working memory and pattern separation processes in rodents. Here, animals must remember the spatial location of a stimulus presented on the screen over a delay period; and use this representation to respond to the novel location when the two are presented together. Because stimuli can be presented in a variety of spatial configurations, TUNL offers a trial-unique paradigm, which can aid in combating the development of unwanted mediating strategies. Here, we have optimized the TUNL protocol for mice to reduce training time and further reduce the potential development of mediating strategies. As a result, mice are able to accurately perform an enhanced trial-unique paradigm, where the locations of the sample and choice stimuli can be presented in any configuration on the screen during a single session. We also aimed to pharmacologically characterize this updated protocol, by assessing the roles of the medial prefrontal cortex (mPFC) and N-methyl-D-aspartate (NMDA) receptor (NMDAr) functioning during TUNL. Temporary inactivation of the medial prefrontal cortex (mPFC) was accomplished by directly infusing a mixture of GABA agonists muscimol and baclofen into the mPFC. We found that mPFC inactivation significantly impaired TUNL performance in a delay-dependent manner. In addition, mPFC inactivation significantly increased the susceptibility of mice to proactive interference. Mice were then challenged with acute systemic injections of the NMDAr antagonist ketamine, which resulted in a dose-dependent, delay-dependent working memory impairment. Together, we describe an optimized automated touchscreen task of working memory, which is dependent on the intact functioning of the mPFC and sensitive to acute NMDAr hypofunction. With the vast genetic toolbox available for modeling disease and probing neural circuit functioning in mice, the TUNL task offers a valuable paradigm to pair with these technologies to further investigate the processes underlying spatial working memory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".