Selective attention in rat visual category learning

Abstract

A prominent theory of category learning, COVIS, posits that new categories are learned with either a declarative or procedural system, depending on the task. The declarative system uses the prefrontal cortex (PFC) to learn rule-based (RB) category tasks in which there is one relevant sensory dimension that can be used to establish a rule for solving the task, whereas the procedural system uses corticostriatal circuits for information integration (II) tasks in which there are multiple relevant dimensions, precluding use of explicit rules. Previous studies have found faster learning of RB versus II tasks in humans and monkeys but not in pigeons. The absence of a learning rate difference in pigeons has been attributed to their lacking a PFC. A major gap in this comparative analysis, however, is the lack of data from a nonprimate mammalian species, such as rats, that have a PFC but a less differentiated PFC than primates. Here, we investigated RB and II category learning in rats. Similar to pigeons, RB and II tasks were learned at the same rate. After reaching a learning criterion, wider distributions of stimuli were presented to examine generalization. A second experiment found equivalent RB and II learning with wider category distributions. Computational modeling revealed that rats extract and selectively attend to category-relevant information but do not consistently use rules to solve the RB task. These findings suggest rats are on a continuum of PFC function between birds and primates, with selective attention but limited ability to utilize rules relative to primates.

Category learning in rodents using touchscreen‐based tasks

“…The typical trial sequence contains four phases, a Star phase, Cue phase, Choice phase and Reward phase (Figure 1A). 37,38 Importantly, this trial sequence separates categorization (Cue phase) from decision execution (Choice phase) and feedback processing (Reward phase), a feature that is favorable for neuroscientific approaches like optogenetics and neurophysiological recording. The trial sequence is self‐paced, which ensures the rat is attending to the screen and has adequate time to (a) observe the category stimulus and (b) make a category decision.…”

“…Rodents are well suited for determining the neural mechanisms underlying cognitive functions, and although the study of categorization in non‐human animals has heavily relied on pigeons, 28‐34 rats are capable of category learning 35‐42 . We have developed category learning tasks for rats using touchscreens as a foundation for a systematic analysis of the neural mechanisms underlying categorization.…”

Memory Traces Diminished by Exercise Affect New Learning as Proactive Facilitation

“…Human studies have shown the benefits of long-term memory for learning new information with similar principle (Gerven et al, 2017;Oberauer et al, 2017;Wang et al, 2017). In addition, rule-based learning (combined cues with an abstract principle) has been reported during associative learning both in human and animal studies (Racht-Delatour and Massioui, 1999;Wills et al, 2011;Maes et al, 2017;Broschard et al, 2019). Compared with remembering only separate cues, rule-based learning is more stable with the passing of time and can adjust to various contexts (Hoffmann et al, 2018).…”

Critical mass: The rise of a touchscreen technology community for rodent cognitive testing

“…The rise in popularity of touchscreen technology for cognitive behavioral testing in rodent neuroscience research suggests that accumulating knowledge and collaborating through an annual or biennial symposium, twice‐yearly hands‐on training course and through our virtual community on https://touchscreencognition.org/ ensures that common issues can be addressed which can further improve standardized testing. Some of these issues involve optimizing touchscreen systems such as the hardware, 47 and development of new touchscreen tasks which is easily achievable because of the flexibility of the touchscreen systems 15,48,49 . For example, Piantadosi et al 48 have developed a novel multichoice task for assessing cognitive flexibility.…”