Debates have arisen as to whether non-human animals actually can learn abstract non-symbolic numerousness or whether they always rely on some continuous physical aspect of the stimuli, covarying with number. Here, we investigated archerfish (Toxotes jaculatrix) non-symbolic numerical discrimination with accurate control for covarying continuous physical stimulus attributes. Archerfish were trained to select one of two groups of black dots (Exp. 1: 3 vs 6 elements; Exp. 2: 2 vs 3 elements); these were controlled for several combinations of physical variables (elements’ size, overall area, overall perimeter, density, and sparsity), ensuring that only numerical information was available. Generalization tests with novel numerical comparisons (2 vs 3, 5 vs 8, and 6 vs 9 in Exp. 1; 3 vs 4, 3 vs 6 in Exp. 2) revealed choice for the largest or smallest numerical group according to the relative number that was rewarded at training. None of the continuous physical variables, including spatial frequency, were affecting archerfish performance. Results provide evidence that archerfish spontaneously use abstract relative numerical information for both small and large numbers when only numerical cues are available.

Odorants are coded in the primary olfactory processing centers by spatially and temporally distributed patterns of glomerular activity. Whereas the spatial distribution of odorant-induced responses is known to be conserved across individuals, the universality of its temporal structure is still debated. Via fast two-photon calcium imaging, we analyzed the early phase of neuronal responses in the form of the activity onset latencies in the antennal lobe projection neurons of honeybee foragers. We show that each odorant evokes a stimulus-specific response latency pattern across the glomerular coding space. Moreover, we investigate these early response features for the first time across animals, revealing that the order of glomerular firing onsets is conserved across individuals and allows them to reliably predict odorant identity, but not concentration. These results suggest that the neuronal response latencies provide the first available code for fast odor identification.SIGNIFICANCE STATEMENTHere, we studied early temporal coding in the primary olfactory processing centers of the honeybee brain by fast imaging of glomerular responses to different odorants across glomeruli and across individuals. Regarding the elusive role of rapid response dynamics in olfactory coding, we were able to clarify the following aspects: (1) the rank of glomerular activation is conserved across individuals, (2) its stimulus prediction accuracy is equal to that of the response amplitude code, and (3) it contains complementary information. Our findings suggest a substantial role of response latencies in odor identification, anticipating the static response amplitude code.

Several studies have suggested that vertebrate and invertebrate species may possess a number sense, i.e. an ability to process in a non-symbolic and non-verbal way the numerousness of a set of items. However, this hypothesis has been challenged by the presence of other non-numerical continuous physical variables, which vary along with numerosity (i.e., any change in the number of visual physical elements in a set naturally involves a related change in visual features such as area, density, contour length and convex hull of the stimulus). It is therefore necessary to control and manipulate the continuous physical information when investigating the ability of humans and other animals to perceive numerousness. During decades of research, different methods have been implemented in order to address this issue, which has implications for experiment replicability and inter-species comparisons, since no general standardized procedure is currently being used. Here we present the ‘Generation of Numerical Elements Images Software’ (GeNEsIS) for the creation of non-symbolic numerical arrays in a standardized and user-friendly environment. The main aim of this tool is to provide researchers in the field of numerical cognition a manageable and precise instrument to produce visual numerical arrays controlled for all the continuous variables. Additionally, we implemented the ability to actively guide stimuli presentation during habituation/dishabituation and dual-choice comparison tasks used in human and comparative research.

Soon after birth, naïve animals and newborn babies show spontaneous attraction towards faces and face-like stimuli with three dark features representing eyes and a mouth/beak. While neurons selectively responding to faces have been found in the inferotemporal cortex of adult primates, face-selective domains in the brains of young monkeys seem to develop only later in life after exposure to faces. This has fueled a debate on the role of experience in the development of face-detector mechanisms, since face preferences are well documented in naïve animals, such as domestic chicks reared without exposure to faces. Here we demonstrate that neurons in a cortex-homologue area of one-week-old face-naïve domestic chicks selectively respond to a face-like configuration. Our single-cell recordings show that these face detectors do not respond to alternative configurations or isolated facial features. Moreover, the population activity of face-selective neurons accurately encoded the face-like stimulus as a unique category. Thus, our findings show that face detectors are present in the brains of very young animals without pre-existing experience.

Despite their young age, zebrafish larvae have a well-developed visual system and can distinguish between different visual stimuli. First, we investigated if the first visual surroundings the larvae experience during the first days after hatching shape their habitat preference. Indeed, these animals seem to “imprint” on the first surroundings they see and select visual stimuli accordingly at 7 days post fertilization (dpf). In particular, if zebrafish larvae experience a bar background just after hatching, they later on prefer bars over white stimuli, and vice versa. We then used this acquired preference for bars to investigate innate numerical abilities. We wanted to specifically test if the zebrafish larvae show real numerical abilities or if they rely on a lower-level mechanism—i.e. spatial frequency—to discriminate between two different numerosities. When we matched the spatial frequency in stimuli with different numbers of bars, the larvae reliably selected the higher numerosity. A previous study has ruled out that 7 dpf zebrafish larvae use convex hull, cumulative surface area and density to choose between two numerosities. Therefore, our results indicate that zebrafish larvae rely on real numerical abilities rather than other cues, including spatial frequency, when spontaneously comparing two sets with different numbers of bars.

Shortly after birth, both naïve animals and newborn babies exhibit a spontaneous attraction to faces and face-like stimuli. While neurons selectively responding to faces have been found in the inferotemporal cortex of adult primates, face-selective domains in the brains of young monkeys seem to develop only later in life after exposure to faces. This has fueled a debate on the role of experience in the development of face-detector mechanisms, since face preferences are well documented in naïve animals, such as domestic chicks reared without exposure to faces. Here, we demonstrate that neurons in a higher-order processing brain area of one-week-old face-naïve domestic chicks selectively respond to a face-like configuration. Our single-cell recordings show that these neurons do not respond to alternative configurations or isolated facial features. Moreover, the population activity of face-selective neurons accurately encoded the face-like stimulus as a unique category. Thus, our findings show that face selectivity is present in the brains of very young animals without preexisting experience.