Jackdaws form categorical prototypes based on experience with category exemplars.

Categorization represents one cognitive ability fundamental to animal behavior. Grouping of elements based on perceptual or semantic features helps to reduce processing resources and facilitates appropriate behavior. Corvids master complex categorization, yet the detailed categorization learning strategies are less well understood. We trained two jackdaws on a delayed match to category paradigm using a novel, artificial stimulus type, RUBubbles. Both birds learned to differentiate between two session-unique categories following two distinct learning protocols. Categories were either introduced via central category prototypes (low variability approach) or using a subset of diverse category exemplars from which diagnostic features had to be identified (high variability approach). In both versions, the stimulus similarity relative to a central category prototype explained categorization performance best. Jackdaws consistently used a central prototype to judge category membership, regardless of whether this prototype was used to introduce distinct categories or had to be inferred from multiple exemplars. Reliance on a category prototype occurred already after experiencing only a few trials with different category exemplars. High stimulus set variability prolonged initial learning but showed no consistent beneficial effect on later generalization performance. High numbers of stimuli, their perceptual similarity, and coherent category structure resulted in a prototype-based strategy, reflecting the most adaptive, efficient, and parsimonious way to represent RUBubble categories. Thus, our birds represent a valuable comparative animal model that permits further study of category representations throughout learning in different regions of a brain producing highly cognitive behavior.

Executive Control of Sequence Behavior in Pigeons Involves Two Distinct Brain Regions.

Executive functions arise from multiple regions of the brain acting in concert. To facilitate such cross-regional computations, the brain is organized into distinct executive networks, like the frontoparietal network. Despite similar cognitive abilities across many domains, little is known about such executive networks in birds. Recent advances in avian fMRI have shown a possible subset of regions, including the nidopallium caudolaterale (NCL) and the lateral part of medial intermediate nidopallium (NIML), that may contribute to complex cognition, forming an action control system of pigeons. We investigated the neuronal activity of NCL and NIML. Single-cell recordings were obtained during the execution of a complex sequential motor task that required executive control to stop executing one behavior and continue with a different one. We compared the neuronal activity of NIML to NCL and found that both regions fully processed the ongoing sequential execution of the task. Differences arose from how behavioral outcome was processed. Our results indicate that NCL takes on a role in evaluating outcome, while NIML is more tightly associated with ongoing sequential steps. Importantly, both regions seem to contribute to overall behavioral output as parts of a possible avian executive network, crucial for behavioral flexibility and decision-making.

Oscillations without cortex: Working memory modulates brainwaves in the endbrain of crows.

Complex cognition requires coordinated neuronal activity at the network level. In mammals, this coordination results in distinct dynamics of local field potentials (LFP) central to many models of higher cognition. These models often implicitly assume a cortical organization. Higher associative regions of the brains of birds do not have cortical layering, yet single-cell correlates of higher cognition are very similar to those found in mammals. We recorded LFP in the avian equivalent of prefrontal cortex while crows performed a highly controlled and cognitively demanding working memory task. We found signatures in local field potentials, modulated by working memory. Frequencies of a narrow gamma and the beta band contained information about the location of target items and were modulated by working memory load. This indicates a critical involvement of these bands in ongoing cognitive processing. We also observed bursts in the beta and gamma frequencies, similar to those that play a vital part in 'activity silent' models of working memory. Thus, despite the lack of a cortical organization the avian associative pallium can create LFP signatures reminiscent of those observed in primates. This points towards a critical cognitive function of oscillatory dynamics evolved through convergence in species capable of complex cognition.

Working memory capacity of crows and monkeys arises from similar neuronal computations.

Complex cognition relies on flexible working memory, which is severely limited in its capacity. The neuronal computations underlying these capacity limits have been extensively studied in humans and in monkeys, resulting in competing theoretical models. We probed the working memory capacity of crows (Corvus corone) in a change detection task, developed for monkeys (Macaca mulatta), while we performed extracellular recordings of the prefrontal-like area nidopallium caudolaterale. We found that neuronal encoding and maintenance of information were affected by item load, in a way that is virtually identical to results obtained from monkey prefrontal cortex. Contemporary neurophysiological models of working memory employ divisive normalization as an important mechanism that may result in the capacity limitation. As these models are usually conceptualized and tested in an exclusively mammalian context, it remains unclear if they fully capture a general concept of working memory or if they are restricted to the mammalian neocortex. Here, we report that carrion crows and macaque monkeys share divisive normalization as a neuronal computation that is in line with mammalian models. This indicates that computational models of working memory developed in the mammalian cortex can also apply to non-cortical associative brain regions of birds.

Working memory is the brain's ability to temporarily hold and manipulate information. It is essential for carrying out complex cognitive tasks, such as reasoning, planning, following instructions or solving problems. Unlike long-term memory, information is not stored and recalled, but held in an accessible state for brief periods. However, the capacity of working memory is very limited. Humans, for example, can only hold around four items of information simultaneously. There are various competing theories about how this limitation arises from the network of neurons in the brain. These models are based on studies of humans and other primates. But memory limitations are not exclusive to mammals. Indeed, the working memory of some birds, such as crows, has a similar capacity to humans despite the architecture of their brains being very different to mammals. So, how do brains with such distinct structural differences produce working memories with similar capacities? To investigate, Hahn et al. probed the working memory of carrion crows in a change detection task developed for macaque monkeys. Crows were trained to memorize varying numbers of colored squares and indicate which square had changed after a one second delay when the screen went blank. While the crows performed the task, Hahn et al. measured the activity of neurons in an area of the brain equivalent to the prefrontal cortex, the central hub of cognition in mammals. The experiments showed that neurons in the crow brain responded to the changing colors virtually the same way as neurons in monkeys. Hahn et al. also noticed that increasing the number of items the crows had to remember affected individual neurons in a similar fashion as had previously been observed in monkeys. This suggests that birds and monkeys share the same central mechanisms of, and limits to, working memory despite differences in brain architecture. The similarities across distantly related species also validates core ideas about the limits of working memory developed from studies of mammals.

Working Memory as an Indicator for Comparative Cognition - Detecting Qualitative and Quantitative Differences.

Working memory (WM), the representation of information held accessible for manipulation over time, is an essential component of all higher cognitive abilities. It allows for complex behaviors that go beyond simple stimulus-response associations and inflexible behavioral patterns. WM capacity determines how many different pieces of information (items) can be used for these cognitive processes, and in humans, it correlates with fluid intelligence. As such, WM might be a useful tool for comparison of cognition across species. WM can be tested using comparatively simple behavioral protocols, based on operant conditioning, in a multitude of different species. Species-specific contextual variables that influence an animal's performance on a non-cognitive level are controlled by adapting the WM paradigm. The neuronal mechanisms by which WM emerges in the brain, as sustained neuronal activity, are comparable between the different species studied (mammals and birds), as are the areas of the brain in which WM activity can be measured. Thus WM is comparable between vastly different species within their respective niches, accounting for specific contextual variables and unique adaptations. By approaching the question of "general cognitive abilities" or "intelligence" within the animal kingdom from the perspective of WM, the complexity of the core question at hand is reduced to a fundamental memory system required to allow for complex cognitive abilities. This article argues that measuring WM can be a suitable addition to the toolkit of comparative cognition. By measuring WM on a behavioral level and going beyond behavior to the underlying physiological processes, qualitative and quantitative differences in cognition between different animal species can be identified, free of contextual restraints.