Francys Subiaul

A natural history of the human mind: tracing evolutionary changes in brain and cognition

Since the last common ancestor shared by modern humans, chimpanzees and bonobos, the lineage leading to Homo sapiens has undergone a substantial change in brain size and organization. As a result, modern humans display striking differences from the living apes in the realm of cognition and linguistic expression. In this article, we review the evolutionary changes that occurred in the descent of Homo sapiens by reconstructing the neural and cognitive traits that would have characterized the last common ancestor and comparing these with the modern human condition. The last common ancestor can be reconstructed to have had a brain of approximately 300–400 g that displayed several unique phylogenetic specializations of development, anatomical organization, and biochemical function. These neuroanatomical substrates contributed to the enhancement of behavioral flexibility and social cognition. With this evolutionary history as precursor, the modern human mind may be conceived as a mosaic of traits inherited from a common ancestry with our close relatives, along with the addition of evolutionary specializations within particular domains. These modern human‐specific cognitive and linguistic adaptations appear to be correlated with enlargement of the neocortex and related structures. Accompanying this general neocortical expansion, certain higher‐order unimodal and multimodal cortical areas have grown disproportionately relative to primary cortical areas. Anatomical and molecular changes have also been identified that might relate to the greater metabolic demand and enhanced synaptic plasticity of modern human brains. Finally, the unique brain growth trajectory of modern humans has made a significant contribution to our species’ cognitive and linguistic abilities.

Do chimpanzees learn reputation by observation? Evidence from direct and indirect experience with generous and selfish strangers.

Can chimpanzees learn the reputation of strangers indirectly by observation? Or are such stable behavioral attributions made exclusively by first-person interactions? To address this question, we let seven chimpanzees observe unfamiliar humans either consistently give (generous donor) or refuse to give (selfish donor) food to a familiar human recipient (Experiments 1 and 2) and a conspecific (Experiment 3). While chimpanzees did not initially prefer to beg for food from the generous donor (Experiment 1), after continued opportunities to observe the same behavioral exchanges, four chimpanzees developed a preference for gesturing to the generous donor (Experiment 2), and transferred this preference to novel unfamiliar donor pairs, significantly preferring to beg from the novel generous donors on the first opportunity to do so. In Experiment 3, four chimpanzees observed novel selfish and generous acts directed toward other chimpanzees by human experimenters. During the first half of testing, three chimpanzees exhibited a preference for the novel generous donor on the first trial. These results demonstrate that chimpanzees can infer the reputation of strangers by eavesdropping on third-party interactions.

Social Learning in Humans and Nonhuman Animals: Theoretical and Empirical Dissections

The past decade has seen a resurgent, concerted interest in social learning research comparing human and nonhuman animals. In this special issue, we present a synthesis of work that consolidates what is currently known and provides a platform for future research. Consequently, we include both new empirical studies and novel theoretical proposals describing work with both human children and adults and a range of nonhuman animals. In this introduction, we describe the background of this special issue and provide a context for each of the eight articles it contains. We hope such introduction will not only help the reader synthesize the interdisciplinary views that characterize this broad field, but also stimulate development of new methods, concepts, and data.

Dissecting the imitation faculty: The multiple imitation mechanisms (MIM) hypothesis

Is the imitation faculty one self-contained domain-general mechanism or an amalgamation of multiple content-specific systems? The multiple imitation mechanisms (MIM) hypothesis posits that the imitation faculty consists of distinct content-specific psychological systems that are dissociable both structurally and functionally. This hypothesis is supported by research in the developmental, cognitive, comparative and neural sciences. This body of work suggests that there are dissociable imitation systems that may be distinguished by unique behavioral and neurobiological profiles. The distribution of these different imitation skills in the animal kingdom further suggests a phylogenetic dissociation, whereby some animals specialized in some (but not all possible) imitation types; a reflection of specific selection pressures favoring certain imitation systems. The MIM hypothesis attempts to bring together these different areas of research into one theoretical framework that defines imitation both functionally and structurally.

Cognitive imitation in 2-year-old children (Homo sapiens): a comparison with rhesus monkeys (Macaca mulatta)

Here we compare the performance of 2-year-old human children with that of adult rhesus macaques on a cognitive imitation task. The task was to respond, in a particular order, to arbitrary sets of photographs that were presented simultaneously on a touch sensitive video monitor. Because the spatial position of list items was varied from trial to trial, subjects could not learn this task as a series of specific motor responses. On some lists, subjects with no knowledge of the ordinal position of the items were given the opportunity to learn the order of those items by observing an expert model. Children, like monkeys, learned new lists more rapidly in a social condition where they had the opportunity to observe an experienced model perform the list in question, than under a baseline condition in which they had to learn new lists entirely by trial and error. No differences were observed between the accuracy of each species’ responses to individual items or in the frequencies with which they made different types of errors. These results provide clear evidence that monkeys and humans share the ability to imitate novel cognitive rules (cognitive imitation).

Do chimpanzees know what others can and cannot do? Reasoning about ‘capability’

Much recent comparative work has been devoted to exploring what nonhuman primates understand about physical causality. However, few laboratory experiments have attempted to test what nonhumans understand about what physical acts others are capable of performing. We tested seven chimpanzees’ ability to predict which of two human experimenters could deliver a tray containing a food reward. In the ‘floor’ condition, legs were required to push the tray toward the subject. In the ‘lap’ condition, arms were required to hand the tray to the subject. In Exp. 1, chimpanzees begged (by gesturing) to either an experimenter whose legs were not visible (LNV) or whose arms were not visible (ANV). Rather than flexibly altering their preferences between conditions, the chimpanzees preferred the ANV experimenter regardless of the task. In subsequent experiments, we manipulated various factors that might have controlled the chimpanzees’ preferences, such as (a) distance between experimenter and subject (Experiment 2), (b) amount of occlusion of experimenters’ body (Experiments 2 and 3), (c) contact with the food tray (Experiments 3 and 4) and (d) positioning of barriers that either impeded the movement of the limbs or not (Experiment 5). The chimpanzees’ performance was best explained by attention to cues such as perceived proximity, contact, and maximal occlusion of body that although highly predictive in certain tasks, were irrelevant in others. When the discriminative role of such cues was eliminated, performance fell to chance levels, indicating that chimpanzees do not spontaneously (or after considerable training) use limb visibility as a cue to predict the ability of a human to perform particular physical tasks. Thus, the current findings suggest a possible failure of causal reasoning in the context of reasoning about the use of the limbs to perform physical acts.

Working memory constraints on imitation and emulation.

Does working memory (WM) constrain the amount and type of information children copy from a model? To answer this question, preschool-age children (N=165) were trained and then tested on a touch-screen task that involved touching simultaneously presented pictures. Prior to responding, children saw a model generate two target responses: Order (touching all of the pictures on the screen in a target sequence three consecutive times) and Multi-Tap (consistently touching one of the pictures two times). Childrens accuracy copying Order and Multi-Tap was assessed on two types of sequences: low WM load (2 pictures) and high WM load (3 pictures). Results showed that more children copied both Order and Multi-Tap on 2-picture sequences than on 3-picture sequences. Children who copied only one of the two target responses tended to copy only Order on 2-picture sequences but only Multi-Tap on 3-picture sequences. Instructions to either copy or ignore the Multi-Tap response did not affect this overall pattern of results. In sum, results are consistent with the hypothesis that WM constrains not just the amount but also the type of information children copy from models, potentially modulating whether children imitate or emulate in a given task.

Becoming a High-Fidelity--"Super"--Imitator: What Are the Contributions of Social and Individual Learning?.

In contrast to other primates, human childrens imitation performance goes from low to high fidelity soon after infancy. Are such changes associated with the development of other forms of learning? We addressed this question by testing 215 children (26-59 months) on two social conditions (imitation, emulation) - involving a demonstration - and two asocial conditions (trial-and-error, recall) - involving individual learning - using two touchscreen tasks. The tasks required responding to either three different pictures in a specific picture order (Cognitive: Airplane→Ball→Cow) or three identical pictures in a specific spatial order (Motor-Spatial: Up→Down→Right). There were age-related improvements across all conditions and imitation, emulation and recall performance were significantly better than trial-and-error learning. Generalized linear models demonstrated that motor-spatial imitation fidelity was associated with age and motor-spatial emulation performance, but cognitive imitation fidelity was only associated with age. While this study provides evidence for multiple imitation mechanisms, the development of one of those mechanisms - motor-spatial imitation - may be bootstrapped by the development of another social learning skill - motor-spatial emulation. Together, these findings provide important clues about the development of imitation, which is arguably a distinctive feature of the human species.

The ghosts in the computer: the role of agency and animacy attributions in "ghost controls".

Three studies evaluated the role of 4-year-old childrens agency- and animacy-attributions when learning from a computerized ghost control (GC). In GCs, participants observe events occurring without an apparent agent, as if executed by a “ghost” or unobserved causal forces. Using a touch-screen, children in Experiment 1 responded to three pictures in a specific order under three learning conditions: (i) trial-and-error (Baseline), (ii) imitation and (iii) Ghost Control. Before testing in the GC, children were read one of three scripts that determined agency attributions. Post-test assessments confirmed that all children attributed agency to the computer and learned in all GCs. In Experiment 2, children were not trained on the computer prior to testing, and no scripts were used. Three different GCs, varying in number of agency cues, were used. Children failed to learn in these GCs, yet attributed agency and animacy to the computer. Experiment 3 evaluated whether children could learn from a human model in the absence of training under conditions where the information presented by the model and the computer was either consistent or inconsistent. Children evidenced learning in both of these conditions. Overall, learning in social conditions (Exp. 3) was significantly better than learning in GCs (Exp. 2). These results, together with other published research, suggest that children privilege social over non-social sources of information and are generally more adept at learning novel tasks from a human than from a computer or GC.

Human Cognitive Specializations

What makes the human mind different from the minds of other animals? Here, the cognitive abilities of human and nonhuman primates are compared and contrasted in three general domains: (1) self-awareness, (2) social cognition, and (3) physical cognition. Our analysis of the data is framed in terms of an overarching theory of human cognitive specialization. We postulate that many aspects of the human and the nonhuman primate mind are remarkably conserved. As a result, human and nonhuman primates share many cognitive and behavioral capabilities. However, we will argue that, despite the many similarities between the human and nonhuman mind, one fundamental feature of our species’ psychology is its ability to interpret observable variables in terms of unobservable (causal) forces. Consequently, although animals can develop rules premised on observable causes, humans can reason about both observable and unobservable causes, resulting in the kind of cognitive and behavioral flexibility that characterizes our species.