The importance of surface-based cues for face discrimination in non-human primates

Understanding how individual identity is processed from faces remains a complex problem. Contrast reversal, showing faces in photographic negative, impairs face recognition in humans and demonstrates the importance of surface-based information (shading and pigmentation) in face recognition. We tested the importance of contrast information for face encoding in chimpanzees and rhesus monkeys using a computerized face-matching task. Results showed that contrast reversal (positive to negative) selectively impaired face processing in these two species, although the impairment was greater for chimpanzees. Unlike chimpanzees, however, monkeys performed just as well matching negative to positive faces, suggesting that they retained some ability to extract identity information from negative faces. A control task showed that chimpanzees, but not rhesus monkeys, performed significantly better matching face parts compared with whole faces after a contrast reversal, suggesting that contrast reversal acts selectively on face processing, rather than general visual-processing mechanisms. These results confirm the importance of surface-based cues for face processing in chimpanzees and humans, while the results were less salient for rhesus monkeys. These findings make a significant contribution to understanding the evolution of cognitive specializations for face processing among primates, and suggest potential differences between monkeys and apes.     

Human face recognition in sheep: lack of configurational coding and right hemisphere advantage

Face recognition in sheep is qualitatively similar to that in humans in terms of its left visual field bias, and the effects of expertise and configural coding. The current study was designed to determine whether such effects are species specific by investigating the case of sheep recognising humans. It was found that the sheep could identify human faces and while they showed a small inversion-induced decline in discriminatory performance, this was significantly less than seen with sheep faces. In other aspects, there were qualitative differences with human face recognition compared with conspecific recognition. In contrast with sheep faces there was no left visual field advantage in the recognition of human faces and the internal features were not used at all as visual cues. The data suggest that these sheep, whilst being extensively exposed to interactions with humans, were unable to identify them with all the same 'expert' methods as were used to discriminate other sheep. This suggests that different neural systems may, to some extent, be used for recognition of sheep as opposed to human faces. The relative contribution to differential neural processing of the faces of the different species and the role of expertise are discussed.     

The evolution of face processing in primates

The ability to recognize faces is an important socio-cognitive skill that is associated with a number of cognitive specializations in humans. While numerous studies have examined the presence of these specializations in non-human primates, species where face recognition would confer distinct advantages in social situations, results have been mixed. The majority of studies in chimpanzees support homologous face-processing mechanisms with humans, but results from monkey studies appear largely dependent on the type of testing methods used. Studies that employ passive viewing paradigms, like the visual paired comparison task, report evidence of similarities between monkeys and humans, but tasks that use more stringent, operant response tasks, like the matching-to-sample task, often report species differences. Moreover, the data suggest that monkeys may be less sensitive than chimpanzees and humans to the precise spacing of facial features, in addition to the surface-based cues reflected in those features, information that is critical for the representation of individual identity. The aim of this paper is to provide a comprehensive review of the available data from face-processing tasks in non-human primates with the goal of understanding the evolution of this complex cognitive skill.     

Dissecting neural circuits for multisensory integration and crossmodal processing

We rely on rich and complex sensory information to perceive and understand our environment. Our multisensory experience of the world depends on the brain''s remarkable ability to combine signals across sensory systems. Behavioural, neurophysiological and neuroimaging experiments have established principles of multisensory integration and candidate neural mechanisms. Here we review how targeted manipulation of neural activity using invasive and non-invasive neuromodulation techniques have advanced our understanding of multisensory processing. Neuromodulation studies have provided detailed characterizations of brain networks causally involved in multisensory integration. Despite substantial progress, important questions regarding multisensory networks remain unanswered. Critically, experimental approaches will need to be combined with theory in order to understand how distributed activity across multisensory networks collectively supports perception.     

Voice cells in the primate temporal lobe

Communication signals are important for social interactions and survival and are thought to receive specialized processing in the visual and auditory systems. Whereas the neural processing of faces by face clusters and face cells has been repeatedly studied [1-5], less is known about the neural representation of voice content. Recent functional magnetic resonance imaging (fMRI) studies have localized voice-preferring regions in the primate temporal lobe [6, 7], but the hemodynamic response cannot directly assess neurophysiological properties. We investigated the responses of neurons in an fMRI-identified voice cluster in awake monkeys, and here we provide the first systematic evidence for voice cells. "Voice cells" were identified, in analogy to "face cells," as neurons responding at least 2-fold stronger to conspecific voices than to "nonvoice" sounds or heterospecific voices. Importantly, whereas face clusters are thought to contain high proportions of face cells [4] responding broadly to many faces [1, 2, 4, 5, 8-10], we found that voice clusters contain moderate proportions of voice cells. Furthermore, individual voice cells exhibit high stimulus selectivity. The results reveal the neurophysiological bases for fMRI-defined voice clusters in the primate brain and highlight potential differences in how the auditory and?visual systems generate selective representations of communication signals.     

The neurobiology of visual attention: finding sources

The profusion of progress during the past twenty years in identifying neural correlates of selective attention within the visual system has left open the question of how visual representations are biased to favor target stimuli. Studies aimed at specifying the mechanisms that can be causally implicated in the control of visual selective attention have only recently begun in earnest. Employing both the psychophysical and the neuroanatomical data, recent neurophysiological experiments in monkeys and neuroimaging studies in humans are converging on the neural circuits that provide the source of at least some forms of attentional control signals.     

Communication and the primate brain: insights from neuroimaging studies in humans, chimpanzees and macaques

Considerable knowledge is available on the neural substrates for speech and language from brain-imaging studies in humans, but until recently there was a lack of data for comparison from other animal species on the evolutionarily conserved brain regions that process species-specific communication signals. To obtain new insights into the relationship of the substrates for communication in primates, we compared the results from several neuroimaging studies in humans with those that have recently been obtained from macaque monkeys and chimpanzees. The recent work in humans challenges the longstanding notion of highly localized speech areas. As a result, the brain regions that have been identified in humans for speech and nonlinguistic voice processing show a striking general correspondence to how the brains of other primates analyze species-specific vocalizations or information in the voice, such as voice identity. The comparative neuroimaging work has begun to clarify evolutionary relationships in brain function, supporting the notion that the brain regions that process communication signals in the human brain arose from a precursor network of regions that is present in nonhuman primates and is used for processing species-specific vocalizations. We conclude by considering how the stage now seems to be set for comparative neurobiology to characterize the ancestral state of the network that evolved in humans to support language.     

Our Faces in the Dog's Brain: Functional Imaging Reveals Temporal Cortex Activation during Perception of Human Faces

Dogs have a rich social relationship with humans. One fundamental aspect of it is how dogs pay close attention to human faces in order to guide their behavior, for example, by recognizing their owner and his/her emotional state using visual cues. It is well known that humans have specific brain regions for the processing of other human faces, yet it is unclear how dogs’ brains process human faces. For this reason, our study focuses on describing the brain correlates of perception of human faces in dogs using functional magnetic resonance imaging (fMRI). We trained seven domestic dogs to remain awake, still and unrestrained inside an MRI scanner. We used a visual stimulation paradigm with block design to compare activity elicited by human faces against everyday objects. Brain activity related to the perception of faces changed significantly in several brain regions, but mainly in the bilateral temporal cortex. The opposite contrast (i.e., everyday objects against human faces) showed no significant brain activity change. The temporal cortex is part of the ventral visual pathway, and our results are consistent with reports in other species like primates and sheep, that suggest a high degree of evolutionary conservation of this pathway for face processing. This study introduces the temporal cortex as candidate to process human faces, a pillar of social cognition in dogs.     

Perception of shape-from-motion in macaque monkeys and humans

Motion is one of the most efficient cues for shape perception. We conducted behavioral experiments to examine how monkeys perceive shapes defined by motion cues and whether they perceive them as humans do. We trained monkeys to perform a shape discrimination task in which shapes were defined by the motion of random dots. Effects of dot density and dot speed on the shape perception of monkeys were examined. Human subjects were also tested using the same paradigm and the test results were compared with those of monkeys. In both monkeys and humans, correct performance rates declined when density or speed of random dots was reduced. Both of them tended to confuse the same combinations of shapes frequently. These results suggest that monkeys and humans perceive shapes defined by motion cues in a similar manner and probably have common neural mechanisms to perceive them. Electronic Publication     

Imagine Jane and identify John: face identity aftereffects induced by imagined faces

It is not known whether prolonged exposure to perceived and imagined complex visual images produces similar shifts in subsequent perception through selective adaptation. This question is important because a positive finding would suggest that perception and imagery of visual stimuli are mediated by shared neural networks. In this study, we used a selective adaptation procedure designed to induce high-level face-identity aftereffects--a phenomenon in which extended exposure to a particular face facilitates recognition of subsequent faces with opposite features while impairing recognition of all other faces. We report here that adaptation to either real or imagined faces produces a similar shift in perception and that identity boundaries represented in real and imagined faces are equivalent. Together, our results show that identity information contained in imagined and real faces produce similar behavioral outcomes. Our findings of high-level visual aftereffects induced by imagined stimuli can be taken as evidence for the involvement of shared neural networks that mediate perception and imagery of complex visual stimuli.     

Monkeys and humans share a common computation for face/voice integration

Speech production involves the movement of the mouth and other regions of the face resulting in visual motion cues. These visual cues enhance intelligibility and detection of auditory speech. As such, face-to-face speech is fundamentally a multisensory phenomenon. If speech is fundamentally multisensory, it should be reflected in the evolution of vocal communication: similar behavioral effects should be observed in other primates. Old World monkeys share with humans vocal production biomechanics and communicate face-to-face with vocalizations. It is unknown, however, if they, too, combine faces and voices to enhance their perception of vocalizations. We show that they do: monkeys combine faces and voices in noisy environments to enhance their detection of vocalizations. Their behavior parallels that of humans performing an identical task. We explored what common computational mechanism(s) could explain the pattern of results we observed across species. Standard explanations or models such as the principle of inverse effectiveness and a "race" model failed to account for their behavior patterns. Conversely, a "superposition model", positing the linear summation of activity patterns in response to visual and auditory components of vocalizations, served as a straightforward but powerful explanatory mechanism for the observed behaviors in both species. As such, it represents a putative homologous mechanism for integrating faces and voices across primates.     

Mother-infant bonding and the evolution of mammalian social relationships

A wide variety of maternal, social and sexual bonding strategies have been described across mammalian species, including humans. Many of the neural and hormonal mechanisms that underpin the formation and maintenance of these bonds demonstrate a considerable degree of evolutionary conservation across a representative range of these species. However, there is also a considerable degree of diversity in both the way these mechanisms are activated and in the behavioural responses that result. In the majority of small-brained mammals (including rodents), the formation of a maternal or partner preference bond requires individual recognition by olfactory cues, activation of neural mechanisms concerned with social reward by these cues and gender-specific hormonal priming for behavioural output. With the evolutionary increase of neocortex seen in monkeys and apes, there has been a corresponding increase in the complexity of social relationships and bonding strategies together with a significant redundancy in hormonal priming for motivated behaviour. Olfactory recognition and olfactory inputs to areas of the brain concerned with social reward are downregulated and recognition is based on integration of multimodal sensory cues requiring an expanded neocortex, particularly the association cortex. This emancipation from olfactory and hormonal determinants of bonding has been succeeded by the increased importance of social learning that is necessitated by living in a complex social world and, especially in humans, a world that is dominated by cultural inheritance.     

Neurobiological basis of human recognition of facial emotion

In the review of modern data and ideas concerning the neurophysiological mechanisms and morphological foundations of the most essential communicative function of humans and monkeys, that of recognition of faces and their emotional expressions, the attention is focussed on its dynamic realization and structural provision. On the basis of literature data about hemodynamic and metabolic mapping of the brain the author analyses the role of different zones of the ventral and dorsal visual cortical pathway, the frontal neocortex and amigdala in the facial features processing, as well as the specificity of this processing at each level. Special attention is given to the module principle of the facial processing in the temporal cortex. The dynamic characteristics of facial recognition are discussed according to the electrical evoked response data in healthy and disease humans and monkeys. Modern evidences on the role of different brain structures in the generation of successive evoked response waves in connection with successive stages of facial processing are analyzed. The similarity and differences between mechanisms of recognition of faces and their emotional expression are also considered.     

Human face processing is tuned to sexual age preferences

Human faces can motivate nurturing behaviour or sexual behaviour when adults see a child or an adult face, respectively. This suggests that face processing is tuned to detecting age cues of sexual maturity to stimulate the appropriate reproductive behaviour: either caretaking or mating. In paedophilia, sexual attraction is directed to sexually immature children. Therefore, we hypothesized that brain networks that normally are tuned to mature faces of the preferred gender show an abnormal tuning to sexual immature faces in paedophilia. Here, we use functional magnetic resonance imaging (fMRI) to test directly for the existence of a network which is tuned to face cues of sexual maturity. During fMRI, participants sexually attracted to either adults or children were exposed to various face images. In individuals attracted to adults, adult faces activated several brain regions significantly more than child faces. These brain regions comprised areas known to be implicated in face processing, and sexual processing, including occipital areas, the ventrolateral prefrontal cortex and, subcortically, the putamen and nucleus caudatus. The same regions were activated in paedophiles, but with a reversed preferential response pattern.     

Neural basis for spatial memory in animals: what do hippocampal neurons tell us?

Recent studies relying on the recording of neuronal unit activity in freely moving rats show the existence of two populations of neurons signalling the animal's location or head direction: place cells found primarily in the hippocampus and head direction cells found in brain areas anatomically and functionally related to the hippocampus. The properties of these two neuronal populations suggest that their activity strongly depends upon information cues stemming from the spatial environment, and also suggest their involvement in spatial memory. Place cells and head direction cells would jointly participate in a neural network allowing the animal to orient in space and to store spatial locations in memory. This network would also be operating in humans, in particular for encoding specific events in episodic memory.     

Macaque Monkeys Perceive the Flash Lag Illusion

Transmission of neural signals in the brain takes time due to the slow biological mechanisms that mediate it. During such delays, the position of moving objects can change substantially. The brain could use statistical regularities in the natural world to compensate neural delays and represent moving stimuli closer to real time. This possibility has been explored in the context of the flash lag illusion, where a briefly flashed stimulus in alignment with a moving one appears to lag behind the moving stimulus. Despite numerous psychophysical studies, the neural mechanisms underlying the flash lag illusion remain poorly understood, partly because it has never been studied electrophysiologically in behaving animals. Macaques are a prime model for such studies, but it is unknown if they perceive the illusion. By training monkeys to report their percepts unbiased by reward, we show that they indeed perceive the illusion qualitatively similar to humans. Importantly, the magnitude of the illusion is smaller in monkeys than in humans, but it increases linearly with the speed of the moving stimulus in both species. These results provide further evidence for the similarity of sensory information processing in macaques and humans and pave the way for detailed neurophysiological investigations of the flash lag illusion in behaving macaques.     

Neurophysiological mechanisms underlying face processing within and beyond the temporal cortical visual areas.

The ways in which information about faces is represented and stored in the temporal lobe visual areas of primates, as shown by recordings from single neurons in macaques, are considered. Some neurons that respond primarily to faces are found in the cortex in the anterior part of the superior temporal sulcus (in which neurons are especially likely to be tuned to facial expression and to face movement involved in gesture), and in the TE areas more ventrally forming the inferior temporal gyrus (in which neurons are more likely to have responses related to the identity of faces). Quantitative studies of the responses of the neurons that respond differently to the faces of different individuals show that information about the identity of the individual is represented by the responses of a population of neurons, that is, ensemble encoding rather than 'grandmother cell' encoding is used. It is argued that this type of tuning is a delicate compromise between very fine tuning, which has the advantage of low interference in neuronal network operations but the disadvantage of losing the useful properties (such as generalization, completion and graceful degradation) of storage in neuronal networks, and broad tuning, which has the advantage of allowing these properties of neuronal networks to be realized but the disadvantage of leading to interference between the different memories stored in an associative network. There is evidence that the responses of some of these neurons are altered by experience so that new stimuli become incorporated in the network. It is shown that the representation that is built in temporal cortical areas shows considerable invariance for size, contrast, spatial frequency and translation. Thus the representation is in a form which is particularly useful for storage and as an output from the visual system. It is also shown that one of the representations that is built is object based, which is suitable for recognition and as an input to associative memory, and that another is viewer centred, which is appropriate for conveying information about gesture. Ways are considered in which such cortical representations might be built by competitive self-organization aided by back projections in the multi-stage cortical processing hierarchy which has convergence from stage to stage.     

Beetles, boxes and brain cells: neural mechanisms underlying valuation and learning

Sensory cues in the environment can predict the availability of reward. Through experience, humans and animals learn these predictions and use them to guide their actions. For example, we can learn to discriminate chanterelles from ordinary champignons through experience. Assuming the development of a taste for the complex and lingering flavors of chanterelles, we therefore learn to value the same action--picking mushrooms--differentially depending upon the appearance of a mushroom. One major goal of cognitive neuroscience is to understand the neural mechanisms that underlie this sort of learning. Because the acquisition of rewards motivates much behavior, recent efforts have focused on describing the neural signals related to learning the value of stimuli and actions. Neurons in the basal ganglia, in midbrain dopamine areas, in frontal and parietal cortices and in other brain areas, all modulate their activity in relation to aspects of learning. By training monkeys on various behavioral tasks, recent studies have begun to characterize how neural signals represent distinct processes, such as the timing of events, motivation, absolute (objective) and relative (subjective) valuation, and the formation of associative links between stimuli and potential actions. In addition, a number of studies have either further characterized dopamine signals or sought to determine how such signaling might interact with target structures, such as the striatum and rhinal cortex, to underlie learning.     

The neuroscience of primate intellectual evolution: natural selection and passive and intentional niche construction

We trained Japanese macaque monkeys to use tools, an advanced cognitive function monkeys do not exhibit in the wild, and then examined their brains for signs of modification. Following tool-use training, we observed neurophysiological, molecular genetic and morphological changes within the monkey brain. Despite being 'artificially' induced, these novel behaviours and neural connectivity patterns reveal overlap with those of humans. Thus, they may provide us with a novel experimental platform for studying the mechanisms of human intelligence, for revealing the evolutionary path that created these mechanisms from the 'raw material' of the non-human primate brain, and for deepening our understanding of what cognitive abilities are and of those that are not uniquely human. On these bases, we propose a theory of 'intentional niche construction' as an extension of natural selection in order to reveal the evolutionary mechanisms that forged the uniquely intelligent human brain.     

Flutter discrimination: neural codes,perception, memory and decision making

Recent studies combining psychophysical and neurophysiological experiments in behaving monkeys have provided new insights into how several cortical areas integrate efforts to solve a vibrotactile discrimination task. In particular, these studies have addressed how neural codes are related to perception, working memory and decision making in this model. The primary somatosensory cortex drives higher cortical areas where past and current sensory information are combined, such that a comparison of the two evolves into a behavioural decision. These and other observations in visual tasks indicate that decisions emerge from highly-distributed processes in which the details of a scheduled motor plan are gradually specified by sensory information.