"Sense of number" refers to the classical idea that we perceive the number of items (numerosity) intuitively. However, whether the brain signals numerosity spontaneously, in the absence of learning, remains unknown; therefore, we recorded from neurons in the ventral intraparietal sulcus and the dorsolateral prefrontal cortex of numerically naive monkeys. Neurons in both brain areas responded maximally to a given number of items, showing tuning to a preferred numerosity. Numerosity was encoded earlier in area ventral intraparietal area, suggesting that numerical information is conveyed from the parietal to the frontal lobe. Visual numerosity is thus spontaneously represented as a perceptual category in a dedicated parietofrontal network. This network may form the biological foundation of a spontaneous number sense, allowing primates to intuitively estimate the number of visual items.association cortices | quantity | single-unit recording T he classical idea of a "sense of number" (1,2) suggests that we and animals are endowed with the faculty to perceive the number of items (i.e., numerosity) intuitively. Numerosity might be a perceptual category provided by hard-wired sensory brain processes, without the need to learn what numerosity refers to. Supporting this hypothesis, numerosity is represented by an approximate nonverbal system that allows wild animals (3,4), prelinguistic infants(5,6), and innumerate humans (7,8) to readily estimate set size. Evidence that the brain is set up to assess visual numerosity spontaneously was recently provided by psychophysical and computational experiments: numerosity-just like color or perceptual categories like faces-in humans is susceptible to adaptation (9,10), and is extracted en passant by computational network models (11).So far, the neuronal foundations of a perceptual number sense were never tested because all experiments done so far were performed in animals that learned to discriminate numerosity (12)(13)(14). Work with behaviorally trained nonhuman primates identified a cortical network with individual neurons in the prefrontal (PFC) and posterior parietal cortex (PPC) selectively responding to the number of items. Such "number neurons" abstractly represent the number of items across space, time, and modalities (15,16,17). Number neurons have also been traced indirectly in the human brain using functional MRI (fMRI) (18,19).However, because neurons can be trained to represent behaviorally meaningful categories (20,21,22), it has been argued (23) that the presence of previously described number neurons in trained animals might be a product of intense learning, rather than a reflection of a spontaneous number sense. For the same reason, the coding scheme for numerosity has been debated (23): Is the spontaneous neuronal code for numerosity a summation code, as evidenced by monotonic discharges as a function of quantity (14,24), or a labeled-line code as witnessed by numerosity-selective neurons tuned to preferred numerosities analogous to those found in monkeys perform...

Humans and animals have a “number sense,” an innate capability to intuitively assess the number of visual items in a set, its numerosity. This capability implies that mechanisms to extract numerosity indwell the brain’s visual system, which is primarily concerned with visual object recognition. Here, we show that network units tuned to abstract numerosity, and therefore reminiscent of real number neurons, spontaneously emerge in a biologically inspired deep neural network that was merely trained on visual object recognition. These numerosity-tuned units underlay the network’s number discrimination performance that showed all the characteristics of human and animal number discriminations as predicted by the Weber-Fechner law. These findings explain the spontaneous emergence of the number sense based on mechanisms inherent to the visual system.

Prefrontal cortex (PFC) and posterior parietal cortex are key brain areas for magnitude representations. Whether active discrimination of numerosity changes neuronal representations is still not known. We simultaneously recorded from the same recording sites in the PFC and ventral intraparietal area (VIP) before and after monkeys learned to actively discriminate the number of items in a set. Only PFC neurons, and not VIP neurons, exhibited heightened representation of number after numerosity training. Increased responsiveness of PFC was evidenced by enhanced differentiation of numerosity by the population of neurons, as well as increased numerosity encoding by individual selective neurons. None of these effects were observed in the VIP, in which neurons responded invariably to numerosity irrespective of behavioral relevance. This suggests elevated PFC participation during numerical task demands and executive control, whereas VIP encodes quantity as a perceptual category regardless of behavioral relevance.

The computational architecture that enables the flexible coupling between otherwise independent eye and hand effector systems is not understood. By using a drift diffusion framework, in which variability of the reaction time (RT) distribution scales with mean RT, we tested the ability of a common stochastic accumulator to explain eye-hand coordination. Using a combination of behavior, computational modeling and electromyography, we show how a single stochastic accumulator to threshold, followed by noisy effector-dependent delays, explains eye-hand RT distributions and their correlation, while an alternate independent, interactive eye and hand accumulator model does not. Interestingly, the common accumulator model did not explain the RT distributions of the same subjects when they made eye and hand movements in isolation. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning.

The question of how the brain recognizes the faces of familiar individuals has been important throughout the history of neuroscience. Cells linking visual processing to person memory have been proposed, but not found. Here we report the discovery of such cells through recordings from an fMRI-identified area in the macaque temporal pole. These cells responded to faces when they were personally familiar. They responded non-linearly to step-wise changes in face visibility and detail, and holistically to face parts, reflecting key signatures of familiar face recognition. They discriminated between familiar identities, as fast as a general face identity area. The discovery of these cells establishes a new pathway for the fast recognition of familiar individuals.