Xiaoke Niu, Zhenyang Jiang, Yanyan Peng, Shuman Huang, Zhizhong Wang, Li Shi. 2022: Visual cognition of birds and its underlying neural mechanism: A review. Avian Research, 13(1): 100023. DOI: 10.1016/j.avrs.2022.100023
Citation: Xiaoke Niu, Zhenyang Jiang, Yanyan Peng, Shuman Huang, Zhizhong Wang, Li Shi. 2022: Visual cognition of birds and its underlying neural mechanism: A review. Avian Research, 13(1): 100023. DOI: 10.1016/j.avrs.2022.100023

Visual cognition of birds and its underlying neural mechanism: A review

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  • Corresponding author:

    E-mail address: wzz1982@zzu.edu.cn (Z. Wang)

  • Available Online: 06 Jul 2022
  • Publish Date: 23 Mar 2022
  • Birds have acute vision and many remarkable visual cognition abilities, due to their unique living environment. The underlying neural mechanisms have also attracted interests of researchers in neuroscience. Here, we firstly summarize the visual cognition abilities of birds, and make a comparison with mammals. Secondly, the underlying neural mechanisms are presented, including histological structure of avian brain and visual pathways, typical experimental results and conclusions in electrochemistry and electrophysiology. The latter mainly focuses on several higher brain areas related to visual cognition, including mesopallium ventrolaterale, entopallium, visual Wulst, and nidopallium caudolaterale. Finally, we make a conclusion and provide a suggestion about future studies on revealing the neural mechanisms of avian visual cognition. This review presents a detailed understanding of avian visual cognition and would be helpful in ornithology studies in the field of cognitive neuroscience.

  • Animal personality, as a series of consistent variances in behaviour among conspecifics across time and context, has been widely found in diverse taxa (Sih et al., 2004; Réale et al., 2007, 2010). The inter-individual variations of personality influence the way animals adapt to environment (Wolf and Weissing, 2012), with important ecological consequences (Sih et al., 2012; Wolf and Weissing, 2012). For example, high-exploratory Zebra Finches (Taeniopygia guttata) are less successful in finding food but more likely to adjust their behaviours (David et al., 2011). Since behaviour can be infinitely flexible in theory, how animals exhibit personality becomes a hot topic in behavioural ecology. Animal personality is considered as an adaptive outcome of inter-individual variance in state (Sih et al., 2015). The state of an individual can mean any features affecting the costs and benefits of its behavioural actions (Houston and McNamara, 1999), which includes features of the focal individual and characteristics of its ecological and social environment (Sih et al., 2015).

    Social context could modulate individual behaviour (Webster and Ward, 2011; van den Bos et al., 2013). A growing body of evidence shows that the expression of personality depends on whether individuals are on their own or in the presence of companions (Webster and Ward, 2011). For instance, Java Sparrows (Lonchura oryzivora) are more active in the novel environment and the novel object tests in the presence of social partners (Zhang et al., 2020). In contrast, in a foraging experiment, Zebra Finches are bolder when isolated than in a flock (Kerman et al., 2018). Such modulating effects on animal personality vary across species and contexts, with conformity, facilitation, and inhibition being reported (Webster and Ward, 2011). Besides differences traced across genotypes, high plasticity of brain circuits in early phases of life (e.g., Jumping Spiders Marpissa muscosa, Liedtke et al., 2015; Black Widow Spiders Latrodectus Hesperus, DiRienzo et al., 2019), parts of which seem to retain their plasticity into adulthood, permits behavioural profiles to be shaped by environment during later phases of life (Gross and Hen, 2004; Champagne and Curley, 2005; Sachser et al., 2013).

    While most studies have focused on the real-time effects of social context, empirical evidence on the carryover effects of social experience is relatively rare. Previous social experience in early life has been shown to affect the subsequent behaviour of fish, in that Cichlid Fish (Pelvicachromis taeniatus) reared in 90-day isolation are more aggressive and less willing to shoal than group-reared ones (Hesse and Thünken, 2014). It has been suggested that the more experience an individual has with a particular behaviour, the better it performs that behaviour (Sih et al., 2015). Since social context has been proved to greatly influence adult individuals, here comes the question how social experience would make the subsequent expression of personality be when individuals are alone once again. Jolles et al. (2016) showed that the social conditions two days before tests could obfuscate behaviour of Three-spined Sticklebacks (Gasterosteus aculeatus) in later contexts. While cumulative evidence has been found in fishes (e.g., Zebrafish Danio rerio, Kareklas et al., 2018; Three-spined Sticklebacks, Jolles et al., 2019; Munson et al., 2021), we still know little about the carryover effects of social experience on behaviour of animals from higher taxa, including birds.

    The aim of our study was to investigate how social experience would affect the subsequent expression of personality in Java Sparrows. We randomly arranged birds for a four-week life in solitary or social treatment. Using a series of exploration assays, birds' exploratory behaviours were measured before and after the treatment. As birds might be influenced by conspecifics while in social treatment, we predicted that the social birds might behave differently from their behaviour before the treatment, whereas the solitary birds would be stable in exploration.

    All procedures involving birds were carried out in accordance with the Policy on the Care and Use of Animals, approved by the Ethical Committee, Center of Zoological Evolution and Systematic Zoological Museum of China, School of Life Sciences, Liaoning University (EC-LNU, 20200150). We adhered to the ASAB/ABS Guidelines for the use of animals. Birds' health was checked every day and no injuries were observed.

    Forty Java Sparrows (twenty males and twenty females) were purchased from a registered pet shop in Shenyang, Liaoning Province, China in September 2021. All birds were raised in farms in Dalian, Liaoning Province, and kept in family groups. Once the birds were fledged, they were transported to pet shops and housed singly (in cages measuring 25 × 25 × 25 cm). Subjects for this study were not related with each other and were transported to laboratory at the age of six months, without any prior breeding experience. Birds sexing was based on the sexual dimorphism of Java Sparrows (Soma and Iwama, 2017; Zhang et al., 2020). The birds were housed individually (in cages measuring 30 cm × 25 cm and 35 cm high) in the same laboratory for a month prior to the experiments. Both visual and auditory contacts were allowed, but physical contact was forbidden to ensure no mating. Each cage was equipped with a feeder, a drinker, a perch, and a nest. The birds were provided ad libitum with millets, health sand, fresh fruits, and water. The laboratory had a 12:12 h light cycle and the temperature was maintained at 22–24 ℃.

    After a month of acclimatization in the laboratory, the exploration assays were proceeded twice for all birds with a three-week interval. To verify that the exploratory behaviour can be classified as a personality trait, behavioural consistency was assessed between the two-time trials for exploration tendencies (Réale et al., 2007). Once the second assays were completed, birds were randomly assigned to one of the two treatments: solitary (N = 20) or social (N = 20). Each treatment lasted for four weeks. Solitary birds were individually housed in 24-L cages (30 cm × 20 cm and 40 cm high), whereas the social birds were housed (10 per cage, males in one cage and females in another) in a 240-L cage (100 cm × 60 cm and 40 cm high) (Ros-Simó and Valverde, 2012; Appendix Fig. S1). Such arrangement aimed to maintain similar densities in both treatments (Munson et al., 2021). All cages were separated by opaque partitions to prevent birds from seeing conspecifics in adjacent compartments but acoustic contact was allowed (Apfelbeck and Raess, 2008; King et al., 2015). Enough food and water were provided in both treatments, with one perch and one nest per bird. After the 4-week treatment, all birds' explorations were tested individually for the third time.

    A novel environment test and a novel object test were involved in the exploration assays (Mainwaring et al., 2011). To limit neophobia involving boldness in the novel object test (Greggor et al., 2015), we used objects with which birds did not have any dangerous experience, in a non-threatening situation. Both tests were conducted during 8:00 to 16:00 on each test day. Birds initially encountered the novel environment test on the first day, and then the novel object test on the next two days (Mainwaring et al., 2011). The exploratory behaviour of each bird was recorded by a HP F860 driving recorder mounted on the top of the cage.

    On the first test day, exploratory behaviour in a novel environment was tested in an unfamiliar test cage (60 cm × 43 cm and 40 cm high; Appendix Fig. S2A). Five empty feeders were placed on the floor of the cage, with four at the corners and one in the middle. The focal bird was initially placed in a separated introductory cage, waiting 30 s for the sliding door to open, and could enter the test cage through the door spontaneously (Mainwaring et al., 2011). The whole test lasted for 10 min, and the time that each bird required to visit 4 of the 5 feeders was recorded by an observer (Q.C.) from the video. The time used by each bird was converted to a linear scale of 0–10 (0:00–0:59 = 10, 1:00–1:59 = 9, etc.; Martins et al., 2007). A score of 10 meant that the focal bird reached 4 of the 5 feeders within 1 min, while a score of 0 meant that the focal bird did not reach 4 different feeders within 10 min.

    The novel object test was carried out on the next two test days to evaluate the response of birds to an unfamiliar object placed in the same test cage (Appendix Fig. S2B). The test cage was divided into three parts by two perches with the same size. Two novel objects (a battery measuring 4.5 by 1.5 cm and a carrot toy measuring 13 by 7 cm and 3 cm high; Appendix Fig. S3) were successively fixed on one of the two perches at random (Jha and Kumar, 2017). Birds were introduced to the battery on the second test day and the carrot toy on the third test day (Mainwaring et al., 2011). After 30-s waiting in the separated cage, the focal bird's behaviour was recorded by the driving recorder once upon entry. Each test lasted for 2 min. Following Jha and Kumar (2017), the reactions to both objects were recorded on a scale of 0–5 (0 meant to stay on the floor furthest from the novel object; 1 meant to stay on the floor between the two perches; 2 meant to stay on the floor but be close to the perch with the novel object; 3 meant to hop on the empty perch; 4 meant to hop on the perch with the novel object but not touch it; and 5 meant to hop on the perch with the novel object and touch it). The score was the maximum rating achieved when the bird presented more than one of the five situations above (Mainwaring et al., 2011).

    The exploration score of each bird was calculated as the sum of their performances recorded in the novel environment test and the novel object test (Drent et al., 2003; van Oers et al., 2004). In theory, the lowest score is 0 and the highest score is 20. Actually, few birds reached four empty feeders in the 10-min novel environment test, with only one bird getting a score in the first-time test (similar phenomenon in Java Sparrows see Wang et al., 2022). Thus, the maximum pretreatment score recorded was 10 (Martins et al., 2007).

    We tested the repeatability of all forty birds' explorations across the twice repeated behavioural assays before treatments by calculating average measures intraclass correlation coefficients (ICCs) and 95% confidence intervals (CIs) with two-way random effects model, using SPSS v. 21.0 (IBM, Armonk, NY, U.S.A.).

    To assess whether different social experience could affect birds' exploration, a linear mixed model (LMM) was fitted in the 'nlme' package of R (R Development Core Team, 2019). Treatment (solitary, social), stage (pre, post), sex (male, female), the interaction treatment * stage and the interaction treatment * sex were included as the explanatory variables in our model, while the exploration score (average of the first two replicates as the pretreatment score) was included as the dependent variable. We fitted bird ID as a random factor in model to control for individual differences and repeated observations. Model fit was checked by visual inspection of quantile-quantile plots of model residuals versus the predictor. Differences in exploration scores were compared among the groups in the same stage and across stages, using independent sample t-tests or paired t-tests. Relationship between pre- and post-treatment exploration scores of social birds was investigated using Pearson correlations.

    A significant proportion of observed variation across all the forty birds in the two repeated behavioural assays before treatments could be attributed to inter-individual differences (ICC (CI) = 0.551 (0.295–0.734), F39, 39 = 3.659, P < 0.001).

    We found an interaction between treatment and stage on birds' exploration scores (LMM: estimate ± SE = −5.200 ± 0.720, t = −7.221, P < 0.001; Table 1, Fig. 1). Exploration scores showed no variation between males and females (LMM: estimate ± SE = −0.533 ± 0.685, t = −0.779, P = 0.441; Table 1, Fig. 1), and both sexes showed similar reactions to the treatments (LMM: estimate ± SE = 0.500 ± 0.969, t = 0.516, P = 0.609; Table 1, Fig. 1). For the two treatments, birds showed no significant difference in pretreatment scores (P = 0.401; Fig. 1), but in post-treatment scores (P < 0.001; Fig. 1). Solitary birds did not differ in their pre- and post-treatment exploration scores (t = 0.809, P = 0.428; Fig. 1), whereas social birds showed significantly higher exploration scores after treatment than before (t = −5.407, P < 0.001; Fig. 1), with 18 out of the 20 individuals showing higher exploration scores (Fig. 2). There was no significant correlation between the pre- and post-treatment exploration scores of social birds (rs = 0.224, N = 20, P = 0.341; Fig. 3).

    Table  1.  Results from linear mixed model (LMM) testing the effects of treatment, stage, sex, and their interactions on birds' exploration scores.
    Model and effects df t P
    Intercept 78 5.878 < 0.001
    Treatment (solitary, social) 36 0.138 0.891
    Stage (pre, post) 78 9.917 < 0.001
    Sex (male, female) 36 −0.779 0.441
    Treatment * Stage 78 −7.221 < 0.001
    Treatment * Sex 36 0.516 0.609
     | Show Table
    DownLoad: CSV
    Figure  1.  The exploration scores of birds pre- and post-solitary or social treatment. Box plots show 25th, 50th (median), and 75th percentiles with horizontal lines. The whiskers end at the largest and smallest non-outliers. ***p < 0.001.
    Figure  2.  The pre- and post-treatment exploration scores of the 20 birds in social groups.
    Figure  3.  The relationship between the pre- and post-treatment exploration scores of social birds.

    In this study, we tested whether the experience of social life could affect the subsequent expression of personality. We found that social experience made birds differ in their pre- and post-treatment explorations. While the solitary birds maintained consistent exploratory behaviours, social birds showed higher exploration tendencies after the four-week social life than before. However, the magnitude of increases in the social birds' exploration scores were different, which had no correlation with the starting condition.

    We did not find behavioural consistency across contexts as almost all birds scored 0 in the repeated novel environment tests before treatments. Similar phenomena were observed in Zebra Finches (Martins et al., 2007). The increase in post-treatment scores came from the birds' getting scores in the novel environment test and their higher scoring in the novel object test. However, there was no significant consistency between the post-treatment scores in the novel environment test and the novel object test (ICC (CI) = −0.307 (−0.653–0.145), F39, 39 = 0.530, P = 0.912). It is unclear whether such inconsistency is due to the influence of social experience or the possible different responses of individuals across exploration tasks, as proposed by Miller et al. (2022).

    Our results support the prediction that social experience would have a carryover effect on the subsequent expression of personality in Java Sparrows, which is in line with previous findings (Hsu and Wolf, 1999; Frost et al., 2007; Jolles et al., 2014). We interpreted it as that the solitary birds almost had no need to adjust and conform their behaviour to maintain or reach coherence in any population (e.g., Ioannou and Dall, 2016). They remained their prior expressions of exploration just because they received no impact from conspecifics. There was a general increase in the exploration tendencies of twenty birds with social experience. Social context can offer animals more safety than solitude (Magurran and Pitcher, 1983; Webster and Ward, 2011; Ward, 2012), and thus risk-aversive behaviour may be less facilitated in identical situations (Kareklas et al., 2018). Moreover, resource competition among conspecific individuals could also lead to a higher dispersal tendency (Hauzy et al., 2007). Even when tested alone, the expression of individual's personality could still be affected (Jolles et al., 2016), probably because social experience can carry over from one context to the next (Frost et al., 2007; Gómez-Laplaza, 2009; Jolles et al., 2014).

    Although social experience indeed promoted the general proactive behaviour in two flocks, the uncorrelated relationship between the birds' pre- and post-treatment exploration scores for the social treatment suggested that individual's future expression of personality could not be simply predicted by its initial level. As a key component of dispersal to habitat with higher quality (Bowler and Benton, 2005; Debeffe et al., 2013), exploration would be a means for the individual to obtain fitness benefits limited to the individual's current rank. It is notable that there is a trade-off between such fitness benefits and the potential cost of dispersal (Coates et al., 2019). Despite in the same social context, birds with different personalities may still encounter selective pressures to different extents (Greenberg and Mettke-Hofmann, 2001; Réale et al., 2007). Those variances in pressures probably serve as an explanation for the various ways through which birds adjust their behaviours. Further works should consider the rank of each individual. It is notable that there were significantly higher post-treatment exploration scores of the birds in the social treatment rather than the solitary one. As high exploration could help individuals expand their territories and obtain more resources, such variation might bring advantages to the population.

    In summary, our results indicate that social experience can have a carryover effect on the subsequent expression of personality. We examined such effect respectively in male and female populations, because we have no means to deal with the influence of potential breeding in a mixed group. For the birds with social experience, they showed higher exploration tendencies in general than themselves before. Such social experience could lead to a more proactive average expression of birds flocking than the birds which were not different from the flocks initially but lived alone. Nevertheless, the bird flocking's initial exploration tendencies did not predict the increase in their exploratory behaviours after the social experience. For the need of rearing, we did not control the social living experience in their family groups before the experiment. The same density kept, that in fact allowed the social birds to have much more to explore, might also promote the birds' exploratory behaviour. Further works should be done to address these issues. To understand more about the carryover effects of social experience, we call for more experiments on various group compositions and varying durations of the social experience. The recovery of individual's behavioural expressions may also deserve more attention.

    The ethics standard is provided in the section "2.1. Ethical note" in the main text.

    JY and QC designed the experiment. GC, MS, YW and QC collected the data. JW and QC conducted the analyses. QC and JY wrote the manuscript. All authors read and approved the final manuscript.

    The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

    Authors thank two anonymous reviewers for their constructive comments and suggestions. This work was supported by Department of Science and Technology of Liaoning Province (2019-ZD-0196) and Department of Education of Liaoning Province (LJC202009). All authors declare no conflict of interests.

    Supplementary data to this article can be found online at https://doi.org/10.1016/j.avrs.2023.100087.

  • Anderson, C., Johnston, M., Marrs, E.J., Porter, B., Colombo, M., 2020a. Delay activity in the Wulst of pigeons (Columba livia) represents correlates of both sample and reward information. Neurobiol. Learn. Mem. 171, 107214.
    Anderson, C., Parra, R.S., Chapman, H., Steinemer, A., Porter, B., Colombo, M., 2020b. Pigeon nidopallium caudolaterale, entopallium, and mesopallium ventrolaterale neural responses during categorisation of Monet and Picasso paintings. Sci. Rep. 10, 15971.
    Atoji, Y., Wild, J.M., 2012. Afferent and efferent projections of the mesopallium in the pigeon (Columba livia). J. Comp. Neurol. 520, 717-741.
    Azizi, A.H., Pusch, R., Koenen, C., Klatt, S., Broker, F., Thiele, S., et al., 2019. Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia). Behav. Brain Res. 356, 423-434.
    Bayer, H.M., Glimcher, P.W., 2005. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron 47, 129-141.
    Behroozi, M., Helluy, X., Strockens, F., Gao, M., Pusch, R., Tabrik, S., et al., 2020. Event-related functional MRI of awake behaving pigeons at 7T. Nat. Commun. 18, 4715.
    Behroozi, M., Strockens, F., Stacho, M., Gunturkun, O., 2017. Functional connectivity pattern of the internal hippocampal network in awake pigeons: a resting-state fMRI study. Brain Behav. Evol. 90, 62-72.
    Berg, M.E., Grace, R.C. 2011. Categorization of multidimensional stimuli by pigeons. J. Exp. Anal. Behav. 95, 305-326.
    Burton, R.F., 2008. The scaling of eye size in adult birds: relationship to brain, head and body sizes. Vision Res. 48, 2345-2351.
    Campos, H.C., Debert, P., da Silva Barros, R., McIlvane, W.J., 2011. Relational discrimination by pigeons in a go/no-go procedure with compound stimuli: a methodological note. J. Exp. Anal. Behav. 96, 417-426.
    Castro, L., Wasserman, E.A., 2013. Information-seeking behavior: exploring metacognitive control in pigeons. Anim. Cogn. 16, 241-254.
    Cheng, S., Li, M., Yu, H., Zhao, K., Liu, S., Wan, H., 2020. Decoding pigeon behavior outcomes during goal-directed decision task by WSR functional network analysis. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 38-41.
    Chen, J., Zou, Y., Sun, Y.H., Ten Cate, C., 2019. Problem-solving males become more attractive to female budgerigars. Science 363, 166-167.
    Clark, W.J., Colombo, M., 2020. The functional architecture, receptive field characteristics, and representation of objects in the visual network of the pigeon brain. Prog. Neurobiol. 195, 101781.
    Clark, W.J., Porter, B., Colombo, M., 2019. Searching for face-category representation in the avian visual forebrain. Front. Physiol. 10, 140.
    Clayton, N.S., Emery, N.J., 2015. Avian models for human cognitive aeuroscience: a proposal. Neuron 86, 1330-1342.
    Coello, Y., Danckert, J., Blangero, A., Rossetti, Y., 2007. Do visual illusions probe the visual brain? Illusions in action without a dorsal visual stream. Neuropsychologia 45, 1849-1858.
    Cole, E., Chad, M., Moman, V., Mumby, D.G., 2020. A Go/No-go delayed nonmatching-to-sample procedure to measure object-recognition memory in rats. Behav. Process. 178, 104180.
    Colombo, M., 2017. Prospective processing: behavioural and neural evidence. Jpn. J. Anim. Psychol. 67, 47-61.
    Cook, R.G., 2000. The comparative psychology of avian visual cognition. Curr. Direct. Psychol. Sci. 9, 83-89.
    Cook, R.G., Qadri, M.A.J., Keller, A.M., 2015. The analysis of visual cognition in birds: implications for evolution, mechanism, and representation. Psychol. Learn. Motivat. 63, 173-210.
    Cook, R.G., Wright, A.A., Drachman, E.E., 2013. Categorization of birds, mammals, and chimeras by pigeons. Behav. Process. 93, 98-110.
    Daniel, T.A., Cook, R.G., Katz, J.S., 2015. Temporal dynamics of task switching and abstract-concept learning in pigeons. Front. Psychol. 6, 1334.
    Daniel, T.A., Wright, A.A., Katz, J.S., 2015. Abstract-concept learning of difference in pigeons. Anim. Cogn. 18, 831-837.
    de Brouwer, A.J., Smeets, J.B., Gutteling, T.P., Toni, I., Medendorp, W.P., 2015. The Muller-Lyer illusion affects visuomotor updating in the dorsal visual stream. Neuropsychologia 77, 119-127.
    de Groof, G., Jonckers, E., Gunturkun, O., Denolf, P., Van Auderkerke, J., Van der Linden, A., 2013. Functional MRI and functional connectivity of the visual system of awake pigeons. Behav. Brain Res. 239, 43-50.
    de la Malla, C., Brenner, E., de Haan, E.H.F., Smeets, J.B.J., 2019. A visual illusion that influences perception and action through the dorsal pathway. Commun. Biol. 2, 38.
    Ditz, H.M., Nieder, A., 2015. Neurons selective to the number of visual items in the corvid songbird endbrain. P. Natl. Acad. Sci. U. S. A. 112, 7827-7832.
    Ditz, H.M., Nieder, A., 2016. Numerosity representations in crows obey the Weber-Fechner law. Proc. Biol. Sci. 283, 20160083.
    Dugas-Ford, J., Ragsdale, C. W., 2015. Levels of homology and the problem of neocortex. Annu. Rev. Neurosci. 38, 351-368.
    Emery, N.J., 2005. Cognitive ornithology: the evolution of avian intelligence. Phil. Trans. R. Soc. B. 361, 23-43.
    Fernandez-Juricic, E., 2012. Sensory basis of vigilance behavior in birds: synthesis and future prospects. Behav. Process. 89, 143-152.
    Fields, L., Verhave, T., Fath, S., 1984. Stimulus equivalence and transitive associations: a methodological analysis. J. Exp. Anal. Behav. 42, 143-157.
    Frost, B.J., 2009. Bird head stabilization. Curr. Biol. 19, R315-R316.
    Gadagkar, V., Puzerey, P.A., Chen, R., Baird-Daniel, E., Farhang, A.R., Goldberg, J.H., 2016. Dopamine neurons encode performance error in singing birds. Science 354, 1278-1282.
    Garlick, D., Fountain, S.B., Blaisdell, A.P., 2017. Serial pattern learning in pigeons: Rule-based or associative? J. Exp. Psychol. Anim. Learn. Cogn. 43, 30-47.
    Geers, L., Pesenti, M., Andres, M., 2018. Visual illusions modify object size estimates for prospective action judgements. Neuropsychologia 117, 211-221.
    Guez, D., Audley, C., Hauber, M., 2013. Transitive or not: a critical appraisal of transitive inference in animals. Ethology 119, 703-726. .
    Gunturkun, O., Bugnyar, T., 2016. Cognition without Cortex. Trends. Cogn. Sci. 20, 291-303.
    Gunturkun, O., Koenen, C., Iovine, F., Garland, A., Pusch, R., 2018. The neuroscience of perceptual categorization in pigeons: a mechanistic hypothesis. Learn. Behav. 46, 229-241.
    Gunturkun, O., von Eugen, K., Packheiser, J., Pusch, R., 2021. Avian pallial circuits and cognition: a comparison to mammals. Curr. Opin. Neurobiol. 71, 29-36.
    Hackett, S.J., Kimball, R.T., Reddy, S., Bowie, R.C., Braun, E.L., Braun, M.J., et al., 2008. A phylogenomic study of birds reveals their evolutionary history. Science 320, 1763-1768.
    Hasselmo, M.E., 2006. The role of acetylcholine in learning and memory. Curr. Opin. Neurobiol. 16, 710-715.
    Hedges, S.B., 2002. The origin and evolution of model organisms. Nat. Rev. Genet. 3, 838-849.
    Herbranson, W.T., Karas, E., Hardin, G., 2017. Perception of angle in visual categorization by pigeons (Columba livia). Anim. Behav. Cogn. 4, 286-300.
    Herrnstein, R.J., Loveland, D.H., 1964. Complex visual concept in the pigeon. Science 146, 549-551.
    Hsiao, Y.T., Chen, T.C., Yu, P.H., Huang, D.S., Hu, F.R., Chuong, C.M., et al., 2020. Connectivity between nidopallium caudolateral and visual pathways in color perception of zebra finches. Sci. Rep. 10, 19382.
    Jarvis, E.D., Mirarab, S., Aberer, A.J., Li, B., Houde, P., Li, C., et al., 2014. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320-1331.
    Johnston, M., Anderson, C., Colombo, M., 2017. Neural correlates of sample-coding and reward-coding in the delay activity of neurons in the entopallium and nidopallium caudolaterale of pigeons (Columba livia). Behav. Brain Res. 317, 382-392.
    Karten, H.J., 2015. Vertebrate brains and evolutionary connectomics: on the origins of the mammalian 'neocortex'. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 370, 20150060-20150060.
    Knudsen, E.I., 2018. Neural circuits that mediate selective attention: a comparative perspective. Trends. Neurosci. 41, 789-805.
    Koenen, C., Pusch, R., Broker, F., Thiele, S., Gunturkun, O., 2016. Categories in the pigeon brain: a reverse engineering approach. J. Exp. Anal. Behav. 105, 111-122.
    Krauzlis, R.J., Bogadhi, A.R., Herman, J.P., Bollimunta, A., 2018. Selective attention without a neocortex. Cortex 102, 161-175.
    Krutzfeldt, N.O., Wild, J.M., 2005. Definition and novel connections of the entopallium in the pigeon (Columba livia). J. Comp. Neurol. 490, 40-56.
    Ksepka, D.T., Balanoff, A.M., Smith, N.A., Bever, G.S., Bhullar, B.S., Bourdon, E., et al., 2020. Tempo and pattern of avian brain size evolution. Curr. Biol. 30, e2023.
    Kumar, S., Hedges, S.B., 1998. A molecular timescale for vertebrate evolution. Nature 392, 917-920.
    Lazareva, O.F., Smirnova, A.A., Bagozkaja, M.S., Zorina, Z.A., Rayevsky, V.V., Wasserman, E.A., 2004. Transitive responding in hooded crows requires linearly ordered stimuli. J. Exp. Anal. Behav. 82, 1-19.
    Levenson, R.M., Krupinski, E.A., Navarro, V.M., Wasserman, E.A., 2015. Pigeons (Columba livia) as trainable observers of pathology and radiology breast cancer images. PLoS ONE 10, e0141357.
    Liu, Y., Xin, Y., Xu, N.L., 2021. A cortical circuit mechanism for structural knowledge-based flexible sensorimotor decision-making. Neuron 109, 2009-2024.
    Lombardi, C.M., 2007. Matching and oddity relational learning by pigeons (Columba livia): transfer from color to shape. Anim. Cognit. 11, 67-74.
    Ma, X., Zhang, Y., Wang, L., Li, N., Barkai, E., Zhang, X., et al., 2020. The firing of theta state-related septal cholinergic neurons disrupt hippocampal ripple oscillations via muscarinic receptors. J. Neurosci. 40, 3591-3603.
    Manns, M., Romling, J., 2012. The impact of asymmetrical light input on cerebral hemispheric specialization and interhemispheric cooperation. Nat. Commun. 3, 696.
    Marzluff, J.M., Miyaoka, R., Minoshima, S., Cross, D.J., 2012. Brain imaging reveals neuronal circuitry underlying the crow's perception of human faces. Proc. Natl. Acad. Sci. U. S. A. 109, 15912-15917.
    Mikolasch, S., Kotrschal, K., Schloegl, C., 2013. Transitive inference in jackdaws (Corvus monedula). Behav. Process. 92, 113-117.
    Moll, F.W., Nieder, A., 2015. Cross-modal associative mnemonic signals in crow endbrain neurons. Curr. Biol. 25, 2196-2201.
    Morandi-Raikova, A., Danieli, K., Lorenzi, E., Rosa-Salva, O., Mayer, U., 2021. Anatomical asymmetries in the tectofugal pathway of dark-incubated domestic chicks: Rightwards lateralization of parvalbumin neurons in the entopallium. Laterality 26, 163-185.
    Murphy, M.S., Brooks, D.I., Cook, R.G., 2015. Pigeons use high spatial frequencies when memorizing pictures. J. Exp. Psychol. Anim. Learn. Cogn. 41, 277-285.
    Ng, B.S., Grabska-Barwinska, A., Gunturkun, O., Jancke, D., 2010. Dominant vertical orientation processing without clustered maps: early visual brain dynamics imaged with voltage-sensitive dye in the pigeon visual Wulst. J. Neurosci. 30, 6713-6725.
    Nieder, A., 2020. The adaptive value of numerical competence. Trends. Ecol. Evol. 35, 605-617.
    Nieder, A., Wagener, L., Rinnert, P., 2020. A neural correlate of sensory consciousness in a corvid bird. Science 369, 1626-1629.
    Nomoto, K., Schultz, W., Watanabe, T., Sakagami, M., 2010. Temporally extended dopamine responses to perceptually demanding reward-predictive stimuli. J. Neurosci. 30, 10692-10702.
    Norton, J.W., Corbett, J.J., 2000. Visual perceptual abnormalities: hallucinations and illusions. Semin. Neurol. 20, 111-121.
    Olkowicz, S., Kocourek, M., Lucan, R.K., Portes, M., Fitch, W.T., Herculano-Houzel, S., et al., 2016. Birds have primate-like numbers of neurons in the forebrain. P. Natl. Acad. Sci. U. S. A. 113, 7255-7260.
    Ott, T., Nieder, A., 2019. Dopamine and cognitive control in prefrontal cortex. Trends. Cogn. Sci. 23, 213-234.
    Peissig, J.J., Young, M.E., Wasserman, E.A., Biederman, I., 2005. The role of edges in object recognition by pigeons. Perception 34, 1353-1374.
    Pepperberg, I.M., Nakayama, K., 2016. Robust representation of shape in a Grey parrot (Psittacus erithacus). Cognition 153, 146-160.
    Punsawad, Y., Siribunyaphat, N., Wongsawat, Y., 2021. Exploration of illusory visual motion stimuli: an EEG-based brain-computer interface for practical assistive communication systems. Heliyon 7, e06457.
    Qadri, M.A., Cook, R.G., 2015. Experimental Divergences in the Visual Cognition of Birds and Mammals. Comp. Cogn. Behav. Rev. 10, 73-105.
    Qadri, M.A., Cook, R.G., 2017. Pigeons and humans use action and pose information to categorize complex human behaviors. Vision. Res. 131, 16-25.
    Rinnert, P., Nieder, A., 2021. Neural code of motor planning and execution during goal-directed movements in crows. J. Neurosci. 41, 4060-4072.
    Roberts, W.A., Macpherson, K., Strang, C., 2016. Context controls access to working and reference memory in the pigeon (Columba livia). J. Exp. Anal. Behav. 105, 184-193.
    Rowe, M.P., 2016. 25th Annual Computational Neuroscience Meeting: CNS-2016. B.M.C. Neurosci. 17, 54.
    Scarf, D., Boy, K., Uber Reinert, A., Devine, J., Gunturkun, O., Colombo, M., 2016a. Orthographic processing in pigeons (Columba livia). P. Natl. Acad. Sci. U. S. A. 113, 11272-11276.
    Scarf, D., Stuart, M., Johnston, M., Colombo, M., 2016b. Visual response properties of neurons in four areas of the avian pallium. J. Comp. Physiol. A. Neuroethol. Sens. Neural Behav. Physiol. 202, 235-245.
    Schultz, W., 1998. Predictive reward signal of dopamine neurons. J. Neurophysiol. 80, 1-27.
    Schultz, W., 2016. Dopamine reward prediction-error signalling: a two-component response. Nat. Rev. Neurosci. 17, 183-195.
    Shanahan, M., Bingman, V.P., Shimizu, T., Wild, M., Gunturkun, O., 2013. Large-scale network organization in the avian forebrain: a connectivity matrix and theoretical analysis. Front. Comput. Neurosci. 7, 89.
    Sigala, N., Logothetis, N.K., 2002. Visual categorization shapes feature selectivity in the primate temporal cortex. Nature 415, 318-320.
    Soto, F.A., Wasserman, E.A., 2011. Asymmetrical interactions in the perception of face identity and emotional expression are not unique to the primate visual system. J. Vis. 11, 24.
    Soto, F.A., Wasserman, E.A., 2014. Mechanisms of object recognition: what we have learned from pigeons. Front. Neural Circuits 8, 122.
    Spetch, M.L., Friedman, A., 2006. Pigeons see correspondence between objects and their pictures. Psychol. Sci. 17, 966-972.
    Srihasam, K., Vincent, J.L., Livingstone, M.S., 2014. Novel domain formation reveals proto-architecture in inferotemporal cortex. Nat. Neurosci. 17, 1776-1783.
    Stacho, M., Herold, C., Rook, N., Wagner, H., Axer, M., Amunts, K., et al., 2020. A cortex-like canonical circuit in the avian forebrain. Science 369, 6511.
    Stacho, M., Strockens, F., Xiao, Q., Gunturkun, O., 2016. Functional organization of telencephalic visual association fields in pigeons. Behav. Brain Res. 303, 93-102.
    Strockens, F., Freund, N., Manns, M., Ocklenburg, S., Gunturkun, O., 2013. Visual asymmetries and the ascending thalamofugal pathway in pigeons. Brain Struct. Funct. 218, 1197-1209.
    Tanaka, K., 1996. Inferotemporal cortex and object vision. Annu. Rev. Neurosci. 19, 109-139.
    Teng, Y., Vyazovska, O.V., Wasserman, E.A., 2015. Selective attention and pigeons' multiple necessary cues discrimination learning. Behav. Process. 112, 61-71.
    Van Meir, V., Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., et al., 2005. Spatiotemporal properties of the BOLD response in the songbirds' auditory circuit during a variety of listening tasks. Neuroimage 25, 1242-1255.
    Veit, L., Hartmann, K., Nieder, A., 2017. Spatially tuned neurons in corvid nidopallium caudolaterale signal target position during visual search. Cereb. Cortex 27, 1103-1112.
    Veit, L., Nieder, A., 2013. Abstract rule neurons in the endbrain support intelligent behaviour in corvid songbirds. Nat. Commun. 4, 2878.
    Verhaal, J., Kirsch, J.A., Vlachos, I., Manns, M., Gunturkun, O., 2012. Lateralized reward-related visual discrimination in the avian entopallium. Eur. J. Neurosci. 35, 1337-1343.
    Vorobyev, M., 2003. Coloured oil droplets enhance colour discrimination. Proc. Biol. Sci. 270, 1255-1261.
    Vyazovska, O.V., 2021. The effect of dimensional reinforcement prediction on discrimination of compound visual stimuli by pigeons. Anim. Cogn. 24, 1329-1338.
    Vyazovska, O.V., Navarro, V.M., Wasserman, E.A., 2016. Stagewise multidimensional visual discrimination by pigeons. J. Exp. Anal. Behav. 106, 58-74.
    Vyazovska, O.V., Teng, Y., Wasserman, E.A., 2014. Attentional tradeoffs in the pigeon. J. Exp. Anal. Behav. 101, 337-354.
    Waelti, P., Dickinson, A., Schultz, W., 2001. Dopamine responses comply with basic assumptions of formal learning theory. Nature 412, 38-43.
    Wang, Y.C., Jiang, S., Frost, B.J., 1993. Visual processing in pigeon nucleus rotundus: luminance, color, motion, and looming subdivisions. Vis. Neurosci. 10, 21-30.
    Watanabe, S., 1991. Effects of ectostriatal lesions on natural concept, pseudoconcept, and artificial pattern discrimination in pigeons. Vis. Neurosci. 6, 497-506.
    Wei, C.A., Kamil, A.C., Bond, A.B., 2014. Direct and relational representation during transitive list linking in pinyon jays (Gymnorhinus cyanocephalus). J. Comp. Psychol. 128, 1-10.
    Wilkie, D.M., Summers, R.J., Spetch, M.L., 1981. Effect of delay-interval stimuli on delayed symbolic matching to sample in the pigeon. J. Exp. Anal. Behav. 35, 153-160.
    Wirthlin, M., Lima, N.C.B., Guedes, R.L.M., Soares, A.E.R., Almeida, L.G.P., Cavaleiro, N.P., et al., 2018. Parrot genomes and the evolution of heightened longevity and cognition. Curr. Biol. 28, 4001-4008.
    Wood, S.M., Wood, J.N., 2015. A chicken model for studying the emergence of invariant object recognition. Front. Neural Circuits 9, 7.
    Wright, A.A., Cumming, W.W., 1971. Color-naming functions for the pigeon. J. Exp. Anal. Behav. 15, 7-17.
    Wright, A.A., Delius, J.D., 2005. Learning processes in matching and oddity: the oddity preference effect and sample reinforcement. J. Exp. Psychol. Anim. Behav. Process. 31, 425-432.
    Wylie, D.R., Pakan, J.M., Gutierrez-Ibanez, C., Iwaniuk, A.N., 2008. Expression of calcium-binding proteins in pathways from the nucleus of the basal optic root to the cerebellum in pigeons. Vis. Neurosci. 25, 701-707.
    Xiao, Q., Frost, B.J., 2009. Looming responses of telencephalic neurons in the pigeon are modulated by optic flow. Brain Res. 1305, 40-46.
    Xue, C., Kramer, L.E., Cohen, M.R., 2021. Dynamic task-belief is an integral part of decision-making. BioRxiv .
    Yang, J., Zhang, C., Wang, S.R., 2005. Comparisons of visual properties between tectal and thalamic neurons with overlapping receptive fields in the pigeon. Brain Behav. Evol. 65, 33-39.
    Zentall, T.R., Jackson-Smith, P., Jagielo, J.A., Nallan, G.B., 1986. Categorical shape and color coding by pigeons. J. Exp. Psychol. Anim. Behav. Process. 12, 153-159.
    Zentall, T.R., Singer, R.A., Miller, H.C., 2008. Matching-to-sample by pigeons: the dissociation of comparison choice frequency from the probability of reinforcement. Behav. Process. 78, 185-190.
    Zhao, K., Nie, J., Yang, L., Liu, X., Shang, Z., Wan, H., 2019. Hippocampus-nidopallium caudolaterale interactions exist in the goal-directed behavior of pigeon. Brain Res. Bull. 153, 257-265.
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