Social interactions represent a ubiquitous aspect of our everyday life that we acquire by interpreting and responding to visual cues from conspecifics1. However, despite the general acceptance of this view, how visual information is used to guide the decision to cooperate is unknown. Here, we wirelessly recorded the spiking activity of populations of neurons in the visual and prefrontal cortex in conjunction with wireless recordings of oculomotor events while freely moving macaques engaged in social cooperation. As animals learned to cooperate, visual and executive areas refined the representation of social variables, such as the conspecific or reward, by distributing socially relevant information among neurons in each area. Decoding population activity showed that viewing social cues influences the decision to cooperate. Learning social events increased coordinated spiking between visual and prefrontal cortical neurons, which was associated with improved accuracy of neural populations to encode social cues and the decision to cooperate. These results indicate that the visual-frontal cortical network prioritizes relevant sensory information to facilitate learning social interactions while freely moving macaques interact in a naturalistic environment.
Until now, it has been difficult to examine the neural bases of foraging in naturalistic environments because previous approaches have relied on restrained animals performing trial-based foraging tasks. Here we allowed unrestrained monkeys to freely interact with concurrent reward options while we wirelessly recorded population activity in the dorsolateral prefrontal cortex. The animals decided when and where to forage based on whether their prediction of reward was fulfilled or violated. This prediction was not solely based on a history of reward delivery, but also on the understanding that waiting longer improves the chance of reward. The task variables were continuously represented in a subspace of the high-dimensional population activity, and this compressed representation predicted the animal's subsequent choices better than the true task variables and as well as the raw neural activity. Our results indicate that monkeys' foraging strategies are based on a cortical model of reward dynamics as animals freely explore their environment.
Tests of visuospatial memory following short (<1 s) and medium (1 to 30 s) delays have revealed characteristically different patterns of behavior in humans. These data have been interpreted as evidence for different memory systems operating during short (iconic memory) and long delays (working memory). Leising et al. (2019, Behavioural Processes, 169, Article 103957 ) found evidence for both systems in pigeons and humans completing a location change-detection task using a visual mask that disrupted accuracy following a short (100 ms), but not a long (1,000 ms) delay. Another common finding is that adding to-be-remembered items should disrupt accuracy after a long, but not short, delay. Experiments 1a and 1b reported this memory system crossover effect in pigeons and people, respectively, tested on location change detection with delays of 0, 100, and 1,000 ms and displays of two to 16 items. Experiments 2a and 2b reported that the color of the items had little (pigeons) or no (humans) effect on change-detection accuracy. Pigeons tested in Experiment 3 with longer delays (2,000, 4,000, and 8,000 ms) and large set sizes demonstrated the crossover effect with most displays but did not demonstrate an abrupt drop in accuracy characteristic of iconic memory. In Experiment 4, accuracy with novel types of change (color, shape, and size) was better after a 0-ms delay and above-chance levels on color and shape trials. These data demonstrate the memory system crossover effect in both humans and pigeons and expand our knowledge of the properties of memory systems across species.
concept learning, including same/different and matching-to-sample concept learning, provides the basis for many other forms of "higher"cognition. The issue of which species can learn abstract concepts and the extent to which abstract-concept learning is expressed across species is discussed. Definitive answers to this issue are argued to depend on the subjects' learning strategy (e.g., a relational-learning strategy) and the particular procedures used to test for abstract-concept learning. Some critical procedures that we have identified are: How to present the items to-be-compared (e.g., in pairs), a high criterion for claiming abstract-concept learning (e.g., transfer performance equivalent to baseline performance), and systematic manipulation of the training set (e.g., increases in the number of rule exemplars when transfer is less than baseline performance). The research covered in this article on the recent advancements in abstract-concept learning show this basic ability in higher-order cognitive processing is common to many animal species and that "uniqueness"may be limited more to how quickly new abstract concepts are learned rather than to the ability itself.
concepts require individuals to identify relationships between novel stimuli. Previous studies have reported that the ability to learn abstract concepts is found in a wide range of species. In regard to a same/different concept, Clark's nutcrackers (Nucifraga columbiana) and black-billed magpies (Pica hudsonia), two corvid species, were shown to outperform other avian and primate species (Wright et al., 2017). Two additional corvid species, pinyon jays (Gymnorhinus cyanocephalus) and California scrub jays (Aphelocoma californica) chosen as they belong to a different clade than nutcrackers and magpies, were examined using the same set-size expansion procedure of the same/different task (the task used with nutcrackers and magpies) to evaluate whether this trait is common across the Corvidae lineage. During this task, concept learning is assessed with novel images after training. Results from the current study showed that when presented with novel stimuli after training with an 8-image set, discrimination accuracy did not differ significantly from chance for pinyon jays and California scrub jays, unlike the magpies and nutcrackers from previous studies that showed partial transfer at that stage. However, concept learning improved with each set-size expansion, and the jays reached full concept learning with a 128-image set. This performance is similar to the other corvids and monkeys tested, all of which outperform pigeons. Results from the current study show a qualitative similarity in full abstract-concept learning in all species tested with a quantitative difference in the set-size functions, highlighting the shared survival importance of mechanisms supporting abstract-concept learning for corvids and primates. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Same/different abstract-concept learning experiments were conducted with two primate species and three avian species by progressively increasing the size of the training stimulus set of distinctly different pictures from eight to 1,024 pictures. These same/different learning experiments were trained with two pictures presented simultaneously. Transfer tests of same and different learning employed interspersed trials of novel pictures to assess the level of correct performance on the very first time of subjects had seen those pictures. All of the species eventually performed these tests with high accuracy, contradicting the long-accepted notion that nonhuman animals are unable to learn the concept of same/different. Capuchin and rhesus monkeys learned the concept more readily than did pigeons. Clark's nutcrackers and black-billed magpies learned as readily as monkeys, and even showed a slight advantage with the smallest training stimulus sets. Those tests of same/different learning were followed by delay procedures, such that a delay was introduced after the subjects responded to the sample picture and before the test picture. In the sequential same/different task, accuracy was shown to diminish when the stimulus on a previous trial matched the test picture previously shown on a different trial. This effect is known as proactive interference. The pigeons' proactive interference was greater at 10-s delays than 1-s delays, revealing time-based interference. By contrast, time delays had little or no effect on rhesus monkeys' proactive interference, suggesting that rhesus monkeys have better explicit memory of where and when they saw the potential interfering picture, revealing better event-based memory.
Judgements of items viewed less than 100 ms prior are predominantly supported by a sensory, or iconic, memory system. Iconic memory is of high-capacity, but is also volatile and limited in duration. Judgements after longer delays increasingly rely on a working memory system, which is lower in capacity and volatility than sensory memory, but is longer in duration. In four experiments, several factors (e.g., length of delay, number of items, time to view items, presence of a visual mask) were manipulated during a spatial change-detection task conducted with humans and pigeons. Both species were exposed to trials with an array of colored circles (2, 3, and 4 circles in Experiment 1 and 2a; 4, 6, and 8 circles in Experiment 2b) followed by a brief delay (0, 50, and 100 ms in Experiment la; 0, 100, and 1000 ms in Experiments lb and 2), and then were presented with a test display in which the position of one of the items had changed. Pigeons, like humans, were less accurate in selecting the changed item with more items in the display and after longer delays. Pigeons were equally accurate on trials with 0 and 100-ms delays, but worse on trials with a 1000-ms delay; whereas, humans were equally accurate on 100-ms and 1000-ms delays, but better on 0-ms delay trials. Accurate change detection was disrupted in both species when a visual mask was inserted between the sample and test display after a short (100 ms), but not a long (1000 ms) delay. The results support similarity between species in the functional relationships between delay and memory systems, despite time course differences related to sensory memory.
Rats exposed to variable-length, unique-odor lists were tested in distinctive contexts for odors second or forth from list-end. Accurate ability to recall odors backwards from the end of lists points to their ability to manipulate and replay odor-list episodic memories.
This article describes an approach for assessing and comparing complex cognition in rhesus monkeys and pigeons by training them in a sequence of synergistic tasks, each yielding a whole function for enhanced comparisons. These species were trained in similar same/different tasks with expanding training sets (8, 16, 32, 64, 128 … 1024 pictures) followed by novel-stimulus transfer eventually resulting in full abstract-concept learning. Concept-learning functions revealed better rhesus transfer throughout and full concept learning at the 128 set, versus pigeons at the 256 set. They were then tested in delayed same/different tasks for proactive interference by inserting occasional tests within trial-unique sessions where the test stimulus matched a previous sample stimulus (1, 2, 4, 8, 16 trials prior). Proactive-interference functions revealed time-based interference for pigeons (1, 10 s delays), but event-based interference for rhesus (no effect of 1, 10, 20 s delays). They were then tested in list-memory tasks by expanding the sample to four samples in trial-unique sessions (minimizing proactive interference). The four-item, list-memory functions revealed strong recency memory at short delays, gradually changing to strong primacy memory at long delays over 30 s for rhesus, and 10 s for pigeons. Other species comparisons and future directions are discussed.
This article describes an approach for training a variety of species to learn the abstract concept of same/different, which in turn forms the basis for testing proactive interference and list memory. The stimulus set for concept-learning training was progressively doubled from 8, 16, 32, 64, 128 . . . to 1,024 different pictures with novel-stimulus transfer following learning. All species fully learned the same/different abstract concept: capuchin and rhesus monkeys learned more readily than pigeons; nutcrackers and magpies were at least equivalent to monkeys and transferred somewhat better following initial training sets. A similar task using the 1,024-picture set plus delays was used to test proactive interference on occasional trials. Pigeons revealed greater interference with 10-s than with 1-s delays, whereas delay time had no effect on rhesus monkeys, suggesting that the monkeys’ interference was event based. This same single-item same/different task was expanded to a 4-item list memory task to test animal list memory. Humans were tested similarly with lists of kaleidoscope pictures. Delays between the list and test were manipulated, resulting in strong initial recency effects (i.e., strong 4th-item memory) at short delays and changing to a strong primacy effect (i.e., strong 1st-item memory) at long delays (pigeons 0-s to 10-s delays; monkeys 0-s to 30-s delays; humans 0-s to 100-s delays). Results and findings are discussed in terms of these species’ cognition and memory comparisons, evolutionary implications, and future directions for testing other species in these synergistically related tasks.
Corvids (birds of the family Corvidae) display intelligent behavior previously ascribed only to primates, but such feats are not directly comparable across species. To make direct species comparisons, we used a same/different task in the laboratory to assess abstract-concept learning in black-billed magpies ( Pica hudsonia). Concept learning was tested with novel pictures after training. Concept learning improved with training-set size, and test accuracy eventually matched training accuracy-full concept learning-with a 128-picture set; this magpie performance was equivalent to that of Clark's nutcrackers (a species of corvid) and monkeys (rhesus, capuchin) and better than that of pigeons. Even with an initial 8-item picture set, both corvid species showed partial concept learning, outperforming both monkeys and pigeons. Similar corvid performance refutes the hypothesis that nutcrackers' prolific cache-location memory accounts for their superior concept learning, because magpies rely less on caching. That corvids with "primitive" neural architectures evolved to equal primates in full concept learning and even to outperform them on the initial 8-item picture test is a testament to the shared (convergent) survival importance of abstract-concept learning.
relational concepts depend upon relationships between stimuli (e.g., same vs. different) and transcend features of the training stimuli. Recent evidence shows that learning abstract concepts is shared across a variety species including birds. Our recent work with a highly-skilled food-storing bird, Clark's nutcracker, revealed superior same/different abstract-concept learning compared to rhesus monkeys, capuchin monkeys, and pigeons. Here we test a more social, but less reliant on food-storing, corvid species, the Black-billed magpie (Pica hudsonia). We used the same procedures and training exemplars (eight pairs of the same rule, and 56 pairs of the different rule) as were used to test the other species. Magpies (n = 10) showed a level of abstract-concept learning that was equivalent to nutcrackers and greater than the primates and pigeons tested with these same exemplars. These findings suggest that superior initial abstract-concept learning abilities may be shared across corvids generally, rather than confined to those strongly reliant on spatial memory.
Since sensory measurements are noisy, an observer is rarely certain about the identity of a stimulus. In visual perception tasks, observers generally take their uncertainty about a stimulus into account when doing so helps task performance. Whether the same holds in visual working memory tasks is largely unknown. Ten human and two monkey subjects localized a single change in orientation between a sample display containing three ellipses and a test display containing two ellipses. To manipulate uncertainty, we varied the reliability of orientation information by making each ellipse more or less elongated (two levels); reliability was independent across the stimuli. In both species, a variable-precision encoding model equipped with an "uncertainty-indifferent" decision rule, which uses only the noisy memories, fitted the data poorly. In both species, a much better fit was provided by a model in which the observer also takes the levels of reliability-driven uncertainty associated with the memories into account. In particular, a measured change in a low-reliability stimulus was given lower weight than the same change in a high-reliability stimulus. We did not find strong evidence that observers took reliability-independent variations in uncertainty into account. Our results illustrate the importance of studying the decision stage in comparison tasks and provide further evidence for evolutionary continuity of working memory systems between monkeys and humans.
Three rhesus monkeys (Macaca mulatta) were tested in a same/different memory task for proactive interference (PI) from prior trials. PI occurs when a previous sample stimulus appears as a test stimulus on a later trial, does not match the current sample stimulus, and the wrong response “same” is made. Trial-unique pictures (scenes, objects, animals, etc.) were used on most trials, except on trials where the test stimulus matched potentially interfering sample stimulus from a prior trial (1, 2, 4, 8, or 16 trials prior). Greater interference occurred when fewer trials separated interference and test. PI functions showed a continuum of interference. Delays between sample and test stimuli and intertrial intervals were manipulated to test how PI might vary as a function of elapsed time. Contrary to a similar study with pigeons, these time manipulations had no discernable effect on the monkey’s PI, as shown by compete overlap of PI functions with no statistical differences or interactions. These results suggested that interference was strictly based upon the number of intervening events (trials with other pictures) without regard to elapsed time. The monkeys’ apparent event-based interference was further supported by retesting with a novel set of 1,024 pictures. PI from novel pictures 1 or 2 trials prior was greater than from familiar pictures, a familiar set of 1,024 pictures. Moreover, when potentially interfering novel stimuli were 16 trials prior, performance accuracy was actually greater than accuracy on baseline trials (no interference), suggesting that remembering stimuli from 16 trials prior was a cue that this stimulus was not the sample stimulus on the current trial—a somewhat surprising conclusion particularly given monkeys.
Same/Different abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana) was tested with novel stimuli following learning of training set expansion (8, 16, 32, 64, 128, 256, 512, and 1024 picture items). The resulting set-size function was compared to those from rhesus monkeys (Macaca mulatta), capuchin monkeys (Cebus apella), and pigeons (Columba livia). Nutcrackers showed partial concept learning following initial eight-item set learning, unlike the other species (Magnotti, Katz, Wright, & Kelly, 2015). The mean function for the nutcrackers' novel-stimulus transfer increased linearly as a function of the logarithm of training set size, which intersected its baseline function at the 128-item set size. Thus, nutcrackers on average achieved full concept learning (i.e., transfer statistically equivalent to baseline performance) somewhere between set sizes of 64 to 128 items, similar to full concept learning by monkeys. Pigeons required a somewhat larger training set (256 items) for full concept learning, but results from other experiments (initial training and transfer with 32- and 64-item set sizes) suggested carryover effects with smaller set sizes may have artificially prolonged the pigeon's full concept learning. We find it remarkable that these diverse species with very different neural architectures can fully learn this same/different abstract concept, and (at least under some conditions) do so with roughly similar sets sizes (64-128 items) and numbers of training exemplars, despite initial concept learning advantages (nutcrackers), learning disadvantages (pigeons), or increasing baselines (monkeys).
Previous work in discrimination learning has shown that nonmatching (oddity) tasks are learned faster and more accurately than comparable matching tasks. This learning advantage has been coined the oddity preference effect (Wright & Delius in Journal of Experimental Psychology: Animal Behavior Processes, 31 , 425–432. doi: 10.1037/0097-7403.31.4.425 , 2005 ). Pigeons trained in a nonmatching task, following training in a same/different (S/D) task, learned the abstract concept of difference (Daniel et al., in Animal Cognition, 18 (4), 831–837, 2015 ), but they did not show the expected faster acquisition or high levels of transfer from the oddity preference effect. In the present study, experimentally naïve pigeons were trained in an identical nonmatching task to examine whether they would show the oddity preference effect on abstract-concept learning. These experimentally naïve pigeons did show an oddity preference effect; their transfer to novel configurations was above chance with the initial (smallest) set size (3-item set) and was substantially more accurate than novel transfer in similar match-to-sample (MTS) or S/D tasks (Bodily et al., in Journal of Experimental Psychology: Animal Behavior Processes, 34 , 178–184. doi: 10.1037/0097-7403.34.1.178 , 2008 ; Katz & Wright in Journal of Experimental Psychology: Animal Behavior Processes, 32 , 80–86. doi: 10.1037/0097-7403.32.1.80 , 2006 ). As the number exemplars in the training set increased, transfer to novel configurations increased and reached equivalence to trained-stimulus performance with a 24-item set. Despite this transfer being equal to baseline performance with a 24-item set, subsequent transfers following training with larger set sizes declined before eventually rising again to baseline performance. This unusual set-size function (with inflection points at the 24- and 96-set sizes) suggests that these pigeons may have combined item-specific and relational learning strategies with differing emphasis as they acquired the abstract concept.
Many species have demonstrated the capacity to learn abstract concepts. Recent studies have shown that the quantity of stimuli used during training plays a critical role in how subjects learn abstract concepts. As the number of stimuli available in the training set increases, so too does performance on novel combinations. The role of set size has been explored with learning the concept of matching and same/different but not with learning the concept of difference. In the present study, pigeons were trained in a non-matching-to-sample task with an initial training set of three stimuli followed by transfer tests to novel stimuli. The training set was progressively doubled eight times with learning and transfer following each expansion. Transfer performance increased from chance level (50 %) at the smallest set size to a level equivalent to asymptotic training performance at the two largest training set sizes (384, 768). This progressive novel-stimulus transfer function of a non-matching (difference) rule is discussed in comparison with results from a similar experiment where pigeons were trained on a matching rule.