Visual categories and concepts in the avian brain

Innate face-selectivity in the brain of young domestic chicks

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.

Transcriptomic changes in the posterior pallium of male zebra finches associated with social niche conformance

Animals plastically adjust their physiological and behavioural phenotypes to conform to their social environment-social niche conformance. The degree of sexual competition is a critical part of the social environment to which animals adjust their phenotypes, but the underlying genetic mechanisms are poorly understood. We conducted a study to investigate how differences in sperm competition risk affect the gene expression profiles of the testes and two brain areas (posterior pallium and optic tectum) in breeding male zebra finches (Taeniopygia castanotis). In this pre-registered study, we investigated a large sample of 59 individual transcriptomes. We compared two experimental groups: males held in single breeding pairs (low sexual competition) versus those held in two pairs (elevated sexual competition) per breeding cage. Using weighted gene co-expression network analysis (WGCNA), we observed significant effects of the social treatment in all three tissues. However, only the treatment effects found in the pallium were confirmed by an additional randomisation test for statistical robustness. Likewise, the differential gene expression analysis revealed treatment effects only in the posterior pallium (ten genes) and optic tectum (six genes). No treatment effects were found in the testis at the single gene level. Thus, our experiments do not provide strong evidence for transcriptomic adjustment specific to manipulated sperm competition risk. However, we did observe transcriptomic adjustments to the manipulated social environment in the posterior pallium. These effects were polygenic rather than based on few individual genes with strong effects. Our findings are discussed in relation to an accompanying paper using the same animals, which reports behavioural results consistent with the results presented here.

Toward viewing behavior for aerial scene categorization

Previous work has demonstrated similarities and differences between aerial and terrestrial image viewing. Aerial scene categorization, a pivotal visual processing task for gathering geoinformation, heavily depends on rotation-invariant information. Aerial image-centered research has revealed effects of low-level features on performance of various aerial image interpretation tasks. However, there are fewer studies of viewing behavior for aerial scene categorization and of higher-level factors that might influence that categorization. In this paper, experienced subjects' eye movements were recorded while they were asked to categorize aerial scenes. A typical viewing center bias was observed. Eye movement patterns varied among categories. We explored the relationship of nine image statistics to observers' eye movements. Results showed that if the images were less homogeneous, and/or if they contained fewer or no salient diagnostic objects, viewing behavior became more exploratory. Higher- and object-level image statistics were predictive at both the image and scene category levels. Scanpaths were generally organized and small differences in scanpath randomness could be roughly captured by critical object saliency. Participants tended to fixate on critical objects. Image statistics included in this study showed rotational invariance. The results supported our hypothesis that the availability of diagnostic objects strongly influences eye movements in this task. In addition, this study provides supporting evidence for Loschky et al.'s (Journal of Vision, 15(6), 11, 2015) speculation that aerial scenes are categorized on the basis of image parts and individual objects. The findings were discussed in relation to theories of scene perception and their implications for automation development.

Responses in the left and right entopallium are differently affected by light stimulation in embryo

Sensory stimulation during the prenatal period has been argued to be a main factor in establishing asymmetry in the vertebrate brain. However, though largely studied in behavior and neuroanatomy, nothing is known on the effects of light stimulation in embryo on the activities of single neurons. We performed single-unit recordings from the left and right entopallium of dark- and light-incubated chicks, following ipsi-, contra-, and bilateral visual stimulation. Light incubation increased the general responsiveness of visual neurons in both the left and the right entopallium. Entopallial responses were clearly lateralized in dark-incubated chicks, which showed a general right-hemispheric dominance. This could be suppressed or inverted after light incubation, revealing the presence of both spontaneous and light-dependent asymmetries. These results suggest that asymmetry in single-neuron activity is present at the onset and can be modulated by environmental stimuli such as light exposure in embryos.

Causal Influence of Linguistic Learning on Perceptual and Conceptual Processing: A Brain-Constrained Deep Neural Network Study of Proper Names and Category Terms

Language influences cognitive and conceptual processing, but the mechanisms through which such causal effects are realized in the human brain remain unknown. Here, we use a brain-constrained deep neural network model of category formation and symbol learning and analyze the emergent model's internal mechanisms at the neural circuit level. In one set of simulations, the network was presented with similar patterns of neural activity indexing instances of objects and actions belonging to the same categories. Biologically realistic Hebbian learning led to the formation of instance-specific neurons distributed across multiple areas of the network, and, in addition, to cell assembly circuits of "shared" neurons responding to all category instances-the network correlates of conceptual categories. In two separate sets of simulations, the network learned the same patterns together with symbols for individual instances ["proper names" (PN)] or symbols related to classes of instances sharing common features ["category terms" (CT)]. Learning CT remarkably increased the number of shared neurons in the network, thereby making category representations more robust while reducing the number of neurons of instance-specific ones. In contrast, proper name learning prevented a substantial reduction of instance-specific neurons and blocked the overgrowth of category general cells. Representational similarity analysis further confirmed that the neural activity patterns of category instances became more similar to each other after category-term learning, relative to both learning with PN and without any symbols. These network-based mechanisms for concepts, PN, and CT explain why and how symbol learning changes object perception and memory, as revealed by experimental studies.

The Pigeon as a Model of Complex Visual Processing and Category Learning

Over the past 30 years, behavioral, computational, and neuroscientific investigations have yielded fresh insights into how pigeons adapt to the diverse complexities of their visual world. A prime area of interest has been how pigeons categorize the innumerable individual stimuli they encounter. Most studies involve either photorealistic representations of actual objects thus affording the virtue of being naturalistic, or highly artificial stimuli thus affording the virtue of being experimentally manipulable. Together those studies have revealed the pigeon to be a prodigious classifier of both naturalistic and artificial visual stimuli. In each case, new computational models suggest that elementary associative learning lies at the root of the pigeon's category learning and generalization. In addition, ongoing computational and neuroscientific investigations suggest how naturalistic and artificial stimuli may be processed along the pigeon's visual pathway. Given the pigeon's availability and affordability, there are compelling reasons for this animal model to gain increasing prominence in contemporary neuroscientific research.

Convergent Circuit Computation for Categorization in the Brains of Primates and Songbirds

Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.

Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks

Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles.

The pigeon as a machine: Complex category structures can be acquired by a simple associative model

Never known for its smarts, the pigeon has proven to be a prodigious classifier of complex visual stimuli. What explains its surprising success? Does it possess elaborate executive functions akin to those deployed by humans? Or does it effectively deploy an unheralded, but powerful associative learning mechanism? In a series of experiments, we first confirm that pigeons can learn a variety of category structures - some devised to foil the use of advanced cognitive processes. We then contrive a simple associative learning model to see how effectively the model learns the same tasks given to pigeons. The close fit of the associative model to pigeons' categorization behavior provides unprecedented support for associative learning as a viable mechanism for mastering complex category structures and for the pigeon's using this mechanism to adapt to a rich visual world. This model will help guide future neuroscientific research into the biological substrates of visual cognition.

Categorical representation of abstract spatial magnitudes in the executive telencephalon of crows

The ability to group abstract continuous magnitudes into meaningful categories is cognitively demanding but key to intelligent behavior. To explore its neuronal mechanisms, we trained carrion crows to categorize lines of variable lengths into arbitrary "short" and "long" categories. Single-neuron activity in the nidopallium caudolaterale (NCL) of behaving crows reflected the learned length categories of visual stimuli. The length categories could be reliably decoded from neuronal population activity to predict the crows' conceptual decisions. NCL activity changed with learning when a crow was retrained with the same stimuli assigned to more categories with new boundaries ("short", "medium," and "long"). Categorical neuronal representations emerged dynamically so that sensory length information at the beginning of the trial was transformed into behaviorally relevant categorical representations shortly before the crows' decision making. Our data show malleable categorization capabilities for abstract spatial magnitudes mediated by the flexible networks of the crow NCL.

Unfolding a sequence of sensory influences and interactions in the development of functional brain laterality

Evidence of sensory experience influencing the development of lateralized brain and behavior is reviewed. The epigenetic role of light exposure during two specific stages of embryonic development of precocial avian species is a particular focus of the research discussed. Two specific periods of light sensitivity (in early versus late incubation), each depending on different subcellular and cellular processes, affect lateralized behavior after hatching. Auditory and olfactory stimulation during embryonic development is also discussed with consideration of interactions with light-generated visual lateralization.