Blake Scott Porter

Inferential reasoning is a vital cognitive ability that enables animals to navigate novel situations by leveraging existing relational knowledge of memory schema, with hypothesized roles of prefrontal cortical-hippocampal circuits. Transitive inference (TI) tasks test the ability of subjects to infer relationships within a value hierarchy (e.g., A > B > C > D > E) after being trained only on adjacent premise pairs (e.g., A-B, B-C, etc.). In rodents, current TI paradigms are primarily based on odor-cues and have several limitations that preclude investigation of physiological mechanisms underlying schemas and inference-based choice. To address these challenges, we developed a novel, automated spatial TI task for rats using a radial maze with maze arms as premise elements and a dedicated deliberation zone. Most rats successfully learned the premise pairs over training. Further, animals demonstrated rapid, successful inference (test pair B > D and control pair A > E) within a single test session, with higher initial accuracy than comparable premise pairs, indicating the use of schema-based inference. We also investigated vicarious trial-and-error's (VTE), a behavioral correlate of spatial deliberation. VTE behavior was elevated on choice trajectories early in learning, when novel premise pairs were introduced, and generally for incorrect trials, corresponding to the hypothesized association of VTE's with uncertainty. Further, rats also exhibited elevated VTE behavior with high variability during inference testing, with individual variability suggestive of varying strengths of schema usage. Our findings demonstrate the feasibility of a rodent spatial TI task that provides new insights into the behavioral correlates of schemas and inference-based choices. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Inferential reasoning is a vital cognitive ability that enables animals to navigate novel situations by leveraging existing relational knowledge of memory schema, with hypothesized roles of prefrontal cortical – hippocampal circuits. Transitive inference (TI) tasks test the ability of subjects to infer relationships within a value hierarchy (e.g., A>B>C>D>E) after being trained only on adjacent premise pairs (e.g., A-B, B-C, etc.). In rodents, current TI paradigms are primarily based on odor-cues and have several limitations that preclude investigation of physiological mechanisms underlying schemas and deliberation. To address these challenges, we developed a novel, automated spatial TI task for rats using a radial maze with maze arms as premise elements and a dedicated deliberation zone. Most rats successfully learned the premise pairs over training. Further, animals demonstrated rapid, successful inference (test pair B>D and control pair A>E) within a single test session, with higher initial accuracy than comparable premise pairs, indicating the use of schema-based inference. We also investigated vicarious trial and error’s (VTE), a behavioral correlate of spatial deliberation. VTE behavior was elevated on choice trajectories early in learning, when novel premise pairs were introduced, and generally for incorrect trials, corresponding to the hypothesized association of VTE’s with uncertainty. Further, rats also exhibited elevated VTE behavior with high variability during inference testing, with individual variability suggestive of varying strengths of schema usage. Our findings demonstrate the feasibility of a rodent spatial TI task that provides new insights into the behavioral correlates of schemas and deliberation for inferential reasoning.

Mazes are a fundamental and widespread tool in behavior and systems neuroscience research in rodents, especially in spatial navigation and spatial memory investigations in freely behaving animals. However, their form and inflexibility often restrict potential experimental paradigms that involve multiple or adaptive maze designs. Unique layouts often lead to elevated costs, whether financially or in terms of time investment from scientists. To alleviate these issues, we have developed an automated, modular maze system that is flexible and scalable. This open source Adapt-A-Maze (AAM) system will allow for experiments with multiple track configurations in rapid succession. Additionally, the flexibility can expedite prototyping of behavioral paradigms. Automation ensures less variability in experimental parameters and higher throughput. Finally, the standardized componentry enhances experimental repeatability within labs and replicability across labs. Our maze was successfully used across labs, in multiple experimental designs, with and without extracellular or optical recordings, in rats. The AAM system presents multiple advantages over current maze options and can facilitate novel behavior and systems neuroscience research. Significance statement We have developed an open source, modular maze system (the Adapt-A-Maze, AAM) that enables any lab interested in rodent behavior and cognition to create standard and unique mazes for their research. The AAM uses modular track pieces that can be combined to create a wide array of maze types. The AAM system also included reward wells with lick detection and pneumatic barriers. All aspects of the maze can be controlled via TTL signals to automate tasks and improve repeatability of experiments. The AAM system is expected to help labs quickly and inexpensively set up recordable experiments to advance our understanding of the neurophysiology underlying behavior and cognition.

When carrying out a physically demanding task, animals must continually assess whether to persist or quit. In this study, we recorded neurons in the dorsomedial prefrontal cortex (dmPFC) of rats as they carried out a challenging weightlifting task, up to the point of quitting. We demonstrate that dmPFC neurons form a representation of the task that is modified, via a decrease in firing rate, by the decreasing the utility of the task that may signal quitting.

Mazes are a fundamental and widespread tool in behavior and systems neuroscience research in rodents. However, their form and inflexibility often restrict potential experimental paradigms that involve multiple or adaptive maze designs. Unique layouts often cost substantial engineering and time investments from trainee scientists. To alleviate these issues, we have developed an automated modular maze system that is flexible and scalable. This system will allow for experiments with multiple track configurations in rapid succession. Additionally, the flexibility can expedite prototyping of behaviors. Finally, the standardized componentry enhances experimental reproducibility and repeatability. This maze system presents advantages over current maze options and can facilitate novel behavior and systems neuroscience research. Highlights Modular maze system enables same-day behavior recordings from multiple flexibly-configured maze environments. High degree of experimental reproducibility and repeatability. Automated lick-detection, liquid reward delivery, and movable barriers. Electronics interface with SpikeGadgets hardware for plug-and-play automated control. Flexibility enables rapid experimental piloting.

When performing a physically demanding behavior, sometimes the optimal choice is to quit the behavior rather than persist in order to minimize energy expenditure for the benefits gained. The dorsomedial prefrontal cortex (dmPFC), consisting of the anterior cingulate cortex and secondary motor area, likely contributes towards such utility assessments. Here, we examined how male rat dmPFC single unit and ensemble level activity corresponded to changes in task utility and quitting in an effortful weight lifting task. Rats carried out two task paradigms: one that became progressively more physically demanding over time and a second fixed effort version. Rats could quit the task at any time. Dorsomedial PFC neurons were highly responsive to each behavioral stage of the task, consisting of rope pulling, reward retrieval, and reward area leaving. Activity was highest early in sessions, commensurate with the highest relative task utility, then decreased until the point of quitting. Neural ensembles consistently represented the sequential behavioral phases of the task. However, these representations were modified over time and became more distinct over the course of the session. These results suggest that dmPFC neurons represent behavioral states that are dynamically modified as behaviors lose their utility, culminating in task quitting. New & Noteworthy: When carrying out a physically demanding task animals must continually assess whether to persist or quit. In this study we recorded neurons in the dorsomedial prefrontal cortex (dmPFC) of rats as they carried out a challenging weightlifting task, up to the point of quitting. We demonstrate that dmPFC neurons form a representation of the task that is modified, via a decrease in firing rate, by the decreasing utility of the task that may signal quitting.

As animals carry out behaviors, particularly costly ones, they must constantly assess whether or not to persist in the behavior or quit. The anterior cingulate cortex (ACC) has been shown to assess the value of behaviors and to be especially sensitive to physical effort costs. Complimentary to these functions, the insula is thought to represent the internal state of the animal including factors such as hunger, thirst, and fatigue. Using a novel weight-lifting task for rats, we characterized the local field potential (LFP) activity of the ACC and anterior insula (AI) during effort expenditure. In the task, male rats are challenged to work for sucrose reward, which costs progressively more effort over time to obtain. Rats are able to quit the task at any point. We found modest shifts in LFP theta (7–9 Hz) activity as the task got progressively more difficult in terms of absolute effort expenditure. However, when the LFP data were analyzed based on the relative progress of the rat toward quitting the task, substantial shifts in LFP power in the theta and gamma (55–100 Hz) frequency bands were observed in ACC and AI. Both ACC and AI theta power decreased as the rats got closer to quitting, while ACC and AI gamma power increased. Furthermore, coherency between ACC and AI in the delta (2–4 Hz) range shifted alongside the performance state of the rat. Overall, we show that ACC and AI LFP activity changes correlate to the relative performance state of rats in an effort-based task.

As animals carry out behaviors, particularly costly ones, they must constantly assess whether or not to persist in the behavior or quit. The anterior cingulate cortex (ACC) has been shown to assess the value of behaviors and to be especially sensitive to physical effort costs. Complimentary to these functions, the insula is thought to represent the internal state of the animal including factors such as hunger, thirst, and fatigue. Utilizing a novel weight lifting task for rats, we characterized the local field potential (LFP) activity of the ACC and anterior insula (AI) during effort expenditure. In the task male rats are challenged to work for sucrose reward, which costs progressively more effort over time to obtain. Rats are able to quit the task at any point. We found modest shifts in LFP theta (7-9 Hz) activity as the task got progressively more difficult in terms of absolute effort expenditure. However, when the LFP data were analyzed based on the rat’s relative progress towards quitting the task, or performance state, substantial shifts in LFP power in the theta and gamma (55-100 Hz) frequency bands were observed in ACC and AI. Both ACC and AI theta power decreased as the rats got closer to quitting, while ACC and AI gamma power increased. Furthermore, coherency between ACC and AI in the delta (2-4 Hz) range shifted alongside the rat’s performance state. Overall we show that ACC and AI LFP activity changes correlate to the rats’ relative performance state in an effort-based task. Significance Statement: Animals need to assess whether or not a behavior is worth pursuing based on their internal states (e.g., hunger, fatigue) and the costs and benefits of the behavior. However, internal states often change as behaviors are carried out, such as becoming fatigued, necessitating constant reassessment as to whether to continue the behavior or quit. We characterized brain activity in the anterior cingulate cortex and insula, brain regions involved in cost-benefit decision making and internal state representations, respectively, as rats carried out a challenging physical-effort task. Both brain regions showed significant shifts in activity as the rats approached their quitting point. Our study provides one of the first characterizations of neural activity as an animal decides to quit an effortful task.