Bird intelligence: Difference between revisions

From Wikipedia, the free encyclopedia
Content deleted Content added
No edit summary
Ann8206 (talk | contribs)
Added information in the Associative learning section
Line 13: Line 13:


Many birds are also able to detect changes in the number of eggs in their nest and brood. [[Brood parasite|Parasitic cuckoos]] are often known to remove one of the host eggs before laying their own.
Many birds are also able to detect changes in the number of eggs in their nest and brood. [[Brood parasite|Parasitic cuckoos]] are often known to remove one of the host eggs before laying their own.

===Associative learning===
===Associative learning===
Visual or auditory signals and their association with food and other rewards have been well studied, and birds have been trained to recognize and distinguish complex shapes.<ref>{{Cite journal|last=Mattison|first=Sara|year=2012|title=Training Birds and Small Mammals for Medical Behaviors|journal=Veterinary Clinics of North America: Exotic Animal Practice
Visual or auditory signals and their association with food and other rewards have been well studied, and birds have been trained to recognize and distinguish complex shapes.<ref>{{Cite journal|last=Mattison|first=Sara|year=2012|title=Training Birds and Small Mammals for Medical Behaviors|journal=Veterinary Clinics of North America: Exotic Animal Practice|volume=15|issue=3|pages=487–499|doi=10.1016/j.cvex.2012.06.012|pmid=22998964}}</ref> This is probably an important ability that aids their survival.{{Clarify|date=July 2011}}.<ref>{{cite journal|last1=Carter|first1=D. E.|last2=Eckerman|first2=D. A.|year=1975|title=Symbolic matching by pigeons: rate of learning complex discriminations predicted from simple discriminations|url=|journal=Science|volume=187|issue=4177|pages=662–664|doi=10.1126/science.1114318|pmid=1114318}}</ref>

|pmid=22998964|volume=15|issue=3|pages=487–499|doi=10.1016/j.cvex.2012.06.012}}</ref> This is probably an important ability that aids their survival.{{Clarify|date= July 2011}}.<ref>{{cite journal | last1 = Carter | first1 = D. E. | last2 = Eckerman | first2 = D. A. | year = 1975 | title = Symbolic matching by pigeons: rate of learning complex discriminations predicted from simple discriminations | url = | journal = Science | volume = 187 | issue = 4177| pages = 662–664 | doi=10.1126/science.1114318| pmid = 1114318 }}</ref>
[[Associative learning]] is a method often used on animals to assess [[Animal cognition|cognitive abilities]].<ref name=":02">{{Cite journal|last=Dickinson|first=Anthony|date=2012-10-05|title=Associative learning and animal cognition|url=https://royalsocietypublishing.org/doi/10.1098/rstb.2012.0220|journal=Philosophical Transactions of the Royal Society B: Biological Sciences|language=en|volume=367|issue=1603|pages=2733–2742|doi=10.1098/rstb.2012.0220|issn=0962-8436|pmc=PMC3427555|pmid=22927572}}</ref> Bebus et al. define associative learning as<blockquote>acquiring knowledge of a predictive or causal relationship (association) between two stimuli, responses or events.<ref name=":1">{{Cite journal|last=Bebus|first=Sara E.|last2=Small|first2=Thomas W.|last3=Jones|first3=Blake C.|last4=Elderbrock|first4=Emily K.|last5=Schoech|first5=Stephan J.|date=2016|title=Associative learning is inversely related to reversal learning and varies with nestling corticosterone exposure|url=https://linkinghub.elsevier.com/retrieve/pii/S0003347215003991|journal=Animal Behaviour|language=en|volume=111|pages=251–260|doi=10.1016/j.anbehav.2015.10.027|via=}}</ref></blockquote>A classic example of associative learning is [[Classical conditioning|Pavlovian conditioning]]. In avian research, performance on simple associative learning tasks can be used to assess how cognitive abilities vary with experimental measures.

==== Associative learning vs. Reversal learning ====
In this first study, Bebus et al. demonstrated that associative learning in [[Florida scrub jay|Florida scrub-jays]] correlated with reversal learning, personality and baseline hormone levels.<ref name=":1" /> To measure associative learning abilities, their method consisted of associating coloured rings to food rewards. To test reversal learning, the researchers simply reversed the rewarding and non-rewarding colours to see how quickly the scrub-jays would adapt to the new association. Their results suggest that associative learning is negatively correlated to reversal learning.<ref name=":1" /> In other words, birds that learned the first association quickly were slower to learn the new association upon reversal. The authors conclude that there must be a trade-off between learning an association and adapting to a new association.<ref name=":1" />

==== Neophobia ====
Bebus et al. also showed that reversal learning was correlated with [[neophobia]]: birds that were afraid of a novel environment previously set up by the researchers were faster at reversal learning.<ref name=":1" /> The researchers also found an inverse correlation, where less neophobic birds performed better on the associative learning task, although this correlation was not statistically significant. Opposite results were found by Guido et al.<ref name=":4">{{Cite journal|last=Guido|first=Jorgelina María|last2=Biondi|first2=Laura Marina|last3=Vasallo|first3=Aldo Ivan|last4=Muzio|first4=Rubén Nestor|date=2017|title=Neophobia is negatively related to reversal learning ability in females of a generalist bird of prey, the Chimango Caracara, Milvago chimango|url=http://link.springer.com/10.1007/s10071-017-1083-9|journal=Animal Cognition|language=en|volume=20|issue=4|pages=591–602|doi=10.1007/s10071-017-1083-9|issn=1435-9448|via=}}</ref> In their research, Guido et al. showed that neophobia in the ''[[Chimango caracara|M. chimango]]'' bird of prey negatively correlated to reversal learning.<ref name=":4" /> In other words, neophobic birds were slower at reversal learning. The researchers suggested a modern explanation for this discrepancy: since birds living near urban areas benefit from being less neophobic to feed on human resources (such as detritus), but also benefit from being flexible learners (since human activity fluctuates), perhaps low neophobia coevolved with high reversal learning ability.<ref name=":4" /> Therefore, personality alone might be insufficient to predict associative learning due to contextual differences.

==== Hormones ====
Bebus et al. found a correlation between baseline hormone levels and associative learning. According to their study, low baseline levels of [[corticosterone]] (CORT), a hormone involved in stress response, predicted better associative learning.<ref name=":1" /> In contrast, high baseline levels of CORT predicted better reversal learning.<ref name=":1" /> In summary, Bebus et al. found that low neophobia (not statistically significant) and low baseline CORT levels predicted better associative learning abilities. Inversely, high neophobia and high baseline CORT levels predicted better reversal learning abilities.<ref name=":1" />

==== Diet ====
In addition to reversal learning, personality and hormone levels, further research suggests that diet may also correlate with associative learning performance. In this next study, Bonaparte et al. demonstrated that high-protein diets in [[Zebra finch|zebra finches]] correlated with better associative learning.<ref name=":2">{{Cite journal|last=Bonaparte|first=Kristina M.|last2=Riffle-Yokoi|first2=Christina|last3=Burley|first3=Nancy Tyler|date=2011-09-19|editor-last=Iwaniuk|editor-first=Andrew|title=Getting a Head Start: Diet, Sub-Adult Growth, and Associative Learning in a Seed-Eating Passerine|url=http://dx.plos.org/10.1371/journal.pone.0023775|journal=PLoS ONE|language=en|volume=6|issue=9|pages=e23775|doi=10.1371/journal.pone.0023775|issn=1932-6203|pmc=PMC3176201|pmid=21949684}}</ref> The researchers showed that high-diet treatment was associated with larger head width, [[Tarsus (skeleton)|tarsus]] length and body mass in the treated males.<ref name=":2" /> In the subsequent testing, researchers show that high-diet and larger head-to-tarsus ratio correlated with better performance on an associative learning task.<ref name=":2" /> The researchers used associative learning as a correlate of cognition to support that nutritional stress during development can negatively impact cognitive development which in turn may reduce reproductive success.<ref name=":2" /> One such way that poor diet may affect reproductive success is through song learning. According to the developmental stress hypothesis, zebra finches learn songs during a stressful period of development and their ability to learn complex songs reflects their adequate development.<ref>{{Cite journal|last=Spencer|first=K.A|last2=Buchanan|first2=K.L|last3=Goldsmith|first3=A.R|last4=Catchpole|first4=C.K|date=2003|title=Song as an honest signal of developmental stress in the zebra finch (Taeniopygia guttata)|url=http://dx.doi.org/10.1016/s0018-506x(03)00124-7|journal=Hormones and Behavior|volume=44|issue=2|pages=132–139|doi=10.1016/s0018-506x(03)00124-7|issn=0018-506X|via=}}</ref>

Contradicting results were found by Kriengwatana et al.<ref name=":5">{{Cite journal|last=Kriengwatana|first=Buddhamas|last2=Farrell|first2=Tara M.|last3=Aitken|first3=Sean D.T.|last4=Garcia|first4=Laura|last5=MacDougall-Shackleton|first5=Scott A.|date=2015|title=Early-life nutritional stress affects associative learning and spatial memory but not performance on a novel object test|url=https://brill.com/view/journals/beh/152/2/article-p195_5.xml|journal=Behaviour|volume=152|issue=2|pages=195–218|doi=10.1163/1568539X-00003239|issn=0005-7959}}</ref> In this study, the researchers found that low food diet in zebra finches (before nutritional independence, that is, before the birds are able to feed themselves) enhanced spatial associative learning, impaired memory and had no effect on neophobia. They also failed to find a correlation between physiological growth and associative learning.<ref name=":5" /> Though Bonaparte et al. focused on protein content whereas Kriengwatana et al. focused on quantity of food, the results seem contradictory. Further research should be conducted to clarify the relationship between diet and associative learning.

==== Ecology ====
Associative learning may vary across species depending on their ecology. According to Clayton and Krebs, there are differences in associative learning and memory between food-storing and non-storing birds.<ref name=":3">{{Cite journal|last=Clayton|first=Nicky S.|last2=Krebs|first2=John R.|date=1994|title=One-trial associative memory: comparison of food-storing and nonstoring species of birds|url=http://dx.doi.org/10.3758/bf03209155|journal=Animal Learning & Behavior|volume=22|issue=4|pages=366–372|doi=10.3758/bf03209155|issn=0090-4996|via=}}</ref> In their experiment, food-storing [[Eurasian jay|jays]] and [[Marsh tit|marsh tits]] and non-storing [[Western jackdaw|jackdaws]] and [[Eurasian blue tit|blue tits]] were introduced to seven sites, one of which contained a food reward. For the first phase of the experiment, the bird randomly searched for the reward between the seven sites, until it found it and was allowed to partially consume the food item. All species performed equally well in the first phase of the experiment. For the second phase of the experiment, the sites were hidden again and the birds had to return to the previously rewarding site to obtain the remainder of food item. The researchers found that food-storing birds performed better on phase 2 than non-storing birds.<ref name=":3" /> While food-storing birds preferentially returned to the rewarding sites, non-storing birds preferentially returned to previously visited sites, regardless of the presence of reward.<ref name=":3" /> If the food reward was visible in phase 1, there was no difference in performance between storers and non-storers.<ref name=":3" /> Therefore, the results show that memory following associative learning, rather than the learning itself, can vary with ecological lifestyle.

==== Age ====
Associative learning correlates with age in [[Australian magpie]] according to Mirville et al.<ref name=":6">{{Cite journal|last=Mirville|first=Melanie O.|last2=Kelley|first2=Jennifer L.|last3=Ridley|first3=Amanda R.|date=2016|title=Group size and associative learning in the Australian magpie (Cracticus tibicen dorsalis)|url=http://link.springer.com/10.1007/s00265-016-2062-x|journal=Behavioral Ecology and Sociobiology|language=en|volume=70|issue=3|pages=417–427|doi=10.1007/s00265-016-2062-x|issn=0340-5443|via=}}</ref> In their study, the researchers initially wanted to study the effect of group size on learning. However, they found that group size correlated with the likelihood of interaction with the task, but not with associative learning itself. Instead, they found that age played a role on performance: adults were more successful at completing the associative learning task, but less likely to approach the task initially. Inversely, juveniles were less successful at completing the task, but more likely to approach it. Therefore, adults in larger groups were the most likely individuals to complete the task due to their increased likelihood to both approach and succeed on the task.<ref name=":6" />

==== Weight ====
Though it may seem universally beneficial to be a fast learner, Madden et al. suggested that the weight of individuals affected whether or not associative learning was adaptive.<ref name=":7">{{Cite journal|last=Madden|first=Joah R.|last2=Langley|first2=Ellis J. G.|last3=Whiteside|first3=Mark A.|last4=Beardsworth|first4=Christine E.|last5=van Horik|first5=Jayden O.|date=2018-09-26|title=The quick are the dead: pheasants that are slow to reverse a learned association survive for longer in the wild|url=https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0297|journal=Philosophical Transactions of the Royal Society B: Biological Sciences|language=en|volume=373|issue=1756|pages=20170297|doi=10.1098/rstb.2017.0297|issn=0962-8436|pmc=PMC6107567|pmid=30104439}}</ref> The researchers studied [[Common pheasant|common pheasants]] and showed that heavy birds that performed well on associative tasks had an increased probability of survival to 4 months old after being released into the wild, whereas light birds that performed well on associative tasks were less likely to survive.<ref name=":7" /> The researchers provide two explanations for the effect of weight on the results: perhaps larger individuals are more dominant and benefit from novel resources more than smaller individuals or they simply have a higher survival rate compared to smaller individuals due to bigger food reserves, difficulty for predators to kill them, increased motility, etc.<ref name=":7" /> Alternatively, ecological pressures may affect smaller individuals differently. Associative learning might be more costly on smaller individuals, thus reducing their fitness and leading to maladaptive behaviours.<ref name=":7" /> Additionally, Madden et al. found that slow reversal learning in both groups correlated with low survival rate.<ref name=":7" /> The researchers suggested a trade-off hypothesis where the cost of reversal learning would inhibit the development of other cognitive abilities. According to Bebus et al., there is a negative correlation between associative learning and reversal learning.<ref name=":1" /> Perhaps low reversal learning correlates to better survival due to enhanced associative learning. Madden et al. also suggested this hypothesis but note their skepticism since they could not show the same negative correlation between associative and reversal learning found by Bebus et al.

==== Neural representations ====
In their research, Veit et al. show that associative learning modified [[Avian pallium|NCL]] (nidopallium caudolaterale) neuronal activity in [[Carrion crow|crows]].<ref name=":8">{{Cite journal|last=Veit|first=Lena|last2=Pidpruzhnykova|first2=Galyna|last3=Nieder|first3=Andreas|date=2015-12-08|title=Associative learning rapidly establishes neuronal representations of upcoming behavioral choices in crows|url=http://www.pnas.org/lookup/doi/10.1073/pnas.1509760112|journal=Proceedings of the National Academy of Sciences|language=en|volume=112|issue=49|pages=15208–15213|doi=10.1073/pnas.1509760112|issn=0027-8424|pmc=PMC4679020|pmid=26598669}}</ref> To test this, visual cues were presented on a screen for 600ms, followed by a 1000ms delay. After the delay, a red stimulus and a blue stimulus were presented simultaneously and the crows had to choose the correct one. Choosing the correct stimulus was rewarded with a food item. As the crows learned the associations through trial and error, NCL neurons showed increased selective activity for the rewarding stimulus. In other words, a given NCL neuron that fired when the correct stimulus was the red one increased its firing rate selectively when the crow had to choose the red stimulus. This increased firing was observed during the delay period during which the crow was presumably thinking about which stimulus to choose. Additionally, increased NCL activity reflected the crow's increased performance. The researchers suggest that NCL neurons are involved in learning associations as well as making the subsequent behavioural choice for the rewarding stimulus.<ref name=":8" />

==== Olfactory associative learning ====
Though most research is concerned with visual associative learning, Slater and Hauber showed that [[Bird of prey|birds of prey]] are also able to learn associations using olfactory cues.<ref>{{Cite journal|last=Nelson Slater|first=Melissa|last2=Hauber|first2=Mark E.|date=2017|title=Olfactory enrichment and scent cue associative learning in captive birds of prey|url=http://doi.wiley.com/10.1002/zoo.21353|journal=Zoo Biology|language=en|volume=36|issue=2|pages=120–126|doi=10.1002/zoo.21353|via=}}</ref> In their study, nine individuals from five species of birds of prey learned to pair a neutral olfactory cue to a food reward.


===Spatial and temporal abilities===
===Spatial and temporal abilities===

Revision as of 01:30, 31 January 2020

Kea are known for their intelligence and curiosity, both vital traits for survival in the harsh mountain environment that is their home. Kea can solve logical puzzles, such as pushing and pulling things in a certain order to get to food, and will work together to achieve a certain objective.

Bird intelligence deals with the definition of intelligence and its measurement as it applies to birds. The difficulty of defining or measuring intelligence in non-human animals makes the subject difficult for scientific study. Anatomically, birds (the 10,000 species of which are theropod dinosaurs) have relatively large brains compared to their head size. The visual and auditory senses are well developed in most species, while the tactile and olfactory senses are well realized only in a few groups. Birds communicate using visual signals as well as through the use of calls and song. The testing of intelligence is therefore based on studying the responses to sensory stimuli.

Studies

Cormorants used by fishermen in Southeast Asia may be able to count

Bird intelligence has been studied through several attributes and abilities. Many of these studies have been on birds such as quail, domestic fowl and pigeons kept under captive conditions. It has, however, been noted that field studies have been limited, unlike those of the apes. Birds in the crow family (corvids), and parrots (psittacines) have been shown to live socially, have long developmental periods, and possess large forebrains, and these may be expected to allow for greater cognitive abilities.[1]

Counting has been considered an ability that shows intelligence. Anecdotal evidence from the 1960s has suggested that crows may count up to 3.[2] Researchers however need to be cautious and ensure that birds are not merely demonstrating the ability to subitize, or count a small number of items quickly.[3][4] Some studies have suggested that crows may indeed have a true numerical ability.[5] It has been shown that parrots can count up to 6,.[6][7] and crows can count up to 8.

Cormorants used by Chinese fishermen that were given every eighth fish as a reward were found to be able to keep count up to seven. E.H. Hoh wrote in Natural History magazine:

In the 1970s, on the Li River, Pamela Egremont observed fishermen who allowed the birds to eat every eighth fish they caught. Writing in the Biological Journal of the Linnean Society, she reported that, once their quota of seven fish was filled, the birds "stubbornly refuse to move again until their neck ring is loosened. They ignore an order to dive and even resist a rough push or a knock, sitting glum and motionless on their perches." Meanwhile, other birds that had not filled their quotas continued to catch fish as usual. "One is forced to conclude that these highly intelligent birds can count up to seven," she wrote.[8]

Many birds are also able to detect changes in the number of eggs in their nest and brood. Parasitic cuckoos are often known to remove one of the host eggs before laying their own.

Associative learning

Visual or auditory signals and their association with food and other rewards have been well studied, and birds have been trained to recognize and distinguish complex shapes.[9] This is probably an important ability that aids their survival.[clarification needed].[10]

Associative learning is a method often used on animals to assess cognitive abilities.[11] Bebus et al. define associative learning as

acquiring knowledge of a predictive or causal relationship (association) between two stimuli, responses or events.[12]

A classic example of associative learning is Pavlovian conditioning. In avian research, performance on simple associative learning tasks can be used to assess how cognitive abilities vary with experimental measures.

Associative learning vs. Reversal learning

In this first study, Bebus et al. demonstrated that associative learning in Florida scrub-jays correlated with reversal learning, personality and baseline hormone levels.[12] To measure associative learning abilities, their method consisted of associating coloured rings to food rewards. To test reversal learning, the researchers simply reversed the rewarding and non-rewarding colours to see how quickly the scrub-jays would adapt to the new association. Their results suggest that associative learning is negatively correlated to reversal learning.[12] In other words, birds that learned the first association quickly were slower to learn the new association upon reversal. The authors conclude that there must be a trade-off between learning an association and adapting to a new association.[12]

Neophobia

Bebus et al. also showed that reversal learning was correlated with neophobia: birds that were afraid of a novel environment previously set up by the researchers were faster at reversal learning.[12] The researchers also found an inverse correlation, where less neophobic birds performed better on the associative learning task, although this correlation was not statistically significant. Opposite results were found by Guido et al.[13] In their research, Guido et al. showed that neophobia in the M. chimango bird of prey negatively correlated to reversal learning.[13] In other words, neophobic birds were slower at reversal learning. The researchers suggested a modern explanation for this discrepancy: since birds living near urban areas benefit from being less neophobic to feed on human resources (such as detritus), but also benefit from being flexible learners (since human activity fluctuates), perhaps low neophobia coevolved with high reversal learning ability.[13] Therefore, personality alone might be insufficient to predict associative learning due to contextual differences.

Hormones

Bebus et al. found a correlation between baseline hormone levels and associative learning. According to their study, low baseline levels of corticosterone (CORT), a hormone involved in stress response, predicted better associative learning.[12] In contrast, high baseline levels of CORT predicted better reversal learning.[12] In summary, Bebus et al. found that low neophobia (not statistically significant) and low baseline CORT levels predicted better associative learning abilities. Inversely, high neophobia and high baseline CORT levels predicted better reversal learning abilities.[12]

Diet

In addition to reversal learning, personality and hormone levels, further research suggests that diet may also correlate with associative learning performance. In this next study, Bonaparte et al. demonstrated that high-protein diets in zebra finches correlated with better associative learning.[14] The researchers showed that high-diet treatment was associated with larger head width, tarsus length and body mass in the treated males.[14] In the subsequent testing, researchers show that high-diet and larger head-to-tarsus ratio correlated with better performance on an associative learning task.[14] The researchers used associative learning as a correlate of cognition to support that nutritional stress during development can negatively impact cognitive development which in turn may reduce reproductive success.[14] One such way that poor diet may affect reproductive success is through song learning. According to the developmental stress hypothesis, zebra finches learn songs during a stressful period of development and their ability to learn complex songs reflects their adequate development.[15]

Contradicting results were found by Kriengwatana et al.[16] In this study, the researchers found that low food diet in zebra finches (before nutritional independence, that is, before the birds are able to feed themselves) enhanced spatial associative learning, impaired memory and had no effect on neophobia. They also failed to find a correlation between physiological growth and associative learning.[16] Though Bonaparte et al. focused on protein content whereas Kriengwatana et al. focused on quantity of food, the results seem contradictory. Further research should be conducted to clarify the relationship between diet and associative learning.

Ecology

Associative learning may vary across species depending on their ecology. According to Clayton and Krebs, there are differences in associative learning and memory between food-storing and non-storing birds.[17] In their experiment, food-storing jays and marsh tits and non-storing jackdaws and blue tits were introduced to seven sites, one of which contained a food reward. For the first phase of the experiment, the bird randomly searched for the reward between the seven sites, until it found it and was allowed to partially consume the food item. All species performed equally well in the first phase of the experiment. For the second phase of the experiment, the sites were hidden again and the birds had to return to the previously rewarding site to obtain the remainder of food item. The researchers found that food-storing birds performed better on phase 2 than non-storing birds.[17] While food-storing birds preferentially returned to the rewarding sites, non-storing birds preferentially returned to previously visited sites, regardless of the presence of reward.[17] If the food reward was visible in phase 1, there was no difference in performance between storers and non-storers.[17] Therefore, the results show that memory following associative learning, rather than the learning itself, can vary with ecological lifestyle.

Age

Associative learning correlates with age in Australian magpie according to Mirville et al.[18] In their study, the researchers initially wanted to study the effect of group size on learning. However, they found that group size correlated with the likelihood of interaction with the task, but not with associative learning itself. Instead, they found that age played a role on performance: adults were more successful at completing the associative learning task, but less likely to approach the task initially. Inversely, juveniles were less successful at completing the task, but more likely to approach it. Therefore, adults in larger groups were the most likely individuals to complete the task due to their increased likelihood to both approach and succeed on the task.[18]

Weight

Though it may seem universally beneficial to be a fast learner, Madden et al. suggested that the weight of individuals affected whether or not associative learning was adaptive.[19] The researchers studied common pheasants and showed that heavy birds that performed well on associative tasks had an increased probability of survival to 4 months old after being released into the wild, whereas light birds that performed well on associative tasks were less likely to survive.[19] The researchers provide two explanations for the effect of weight on the results: perhaps larger individuals are more dominant and benefit from novel resources more than smaller individuals or they simply have a higher survival rate compared to smaller individuals due to bigger food reserves, difficulty for predators to kill them, increased motility, etc.[19] Alternatively, ecological pressures may affect smaller individuals differently. Associative learning might be more costly on smaller individuals, thus reducing their fitness and leading to maladaptive behaviours.[19] Additionally, Madden et al. found that slow reversal learning in both groups correlated with low survival rate.[19] The researchers suggested a trade-off hypothesis where the cost of reversal learning would inhibit the development of other cognitive abilities. According to Bebus et al., there is a negative correlation between associative learning and reversal learning.[12] Perhaps low reversal learning correlates to better survival due to enhanced associative learning. Madden et al. also suggested this hypothesis but note their skepticism since they could not show the same negative correlation between associative and reversal learning found by Bebus et al.

Neural representations

In their research, Veit et al. show that associative learning modified NCL (nidopallium caudolaterale) neuronal activity in crows.[20] To test this, visual cues were presented on a screen for 600ms, followed by a 1000ms delay. After the delay, a red stimulus and a blue stimulus were presented simultaneously and the crows had to choose the correct one. Choosing the correct stimulus was rewarded with a food item. As the crows learned the associations through trial and error, NCL neurons showed increased selective activity for the rewarding stimulus. In other words, a given NCL neuron that fired when the correct stimulus was the red one increased its firing rate selectively when the crow had to choose the red stimulus. This increased firing was observed during the delay period during which the crow was presumably thinking about which stimulus to choose. Additionally, increased NCL activity reflected the crow's increased performance. The researchers suggest that NCL neurons are involved in learning associations as well as making the subsequent behavioural choice for the rewarding stimulus.[20]

Olfactory associative learning

Though most research is concerned with visual associative learning, Slater and Hauber showed that birds of prey are also able to learn associations using olfactory cues.[21] In their study, nine individuals from five species of birds of prey learned to pair a neutral olfactory cue to a food reward.

Spatial and temporal abilities

A common test of intelligence is the detour test, where a glass barrier between the bird and an item such as food is used in the setup. Most mammals discover that the objective is reached by first going away from the target. Whereas domestic fowl fail on this test, many within the crow family are able to readily solve the problem.[22]

Large fruit-eating birds in tropical forests depend on trees which bear fruit at different times of the year. Many species, such as pigeons and hornbills, have been shown to be able to decide upon foraging areas according to the time of the year. Birds that show food hoarding behavior have also shown the ability to recollect the locations of food caches.[23][24] Nectarivorous birds such as hummingbirds also optimize their foraging by keeping track of the locations of good and bad flowers.[25] Studies of western scrub jays also suggest that birds may be able to plan ahead. They cache food according to future needs and risk of not being able to find the food on subsequent days.[26]

Many birds follow strict time schedules in their activities. These are often dependent upon environmental cues. Birds also are sensitive to day length, and this awareness is especially important as a cue for migratory species. The ability to orient themselves during migrations is attributed to birds' superior sensory abilities, rather than to intelligence.

Beat induction

Research published in 2008 that was conducted with an Eleonora cockatoo named Snowball has shown that birds can identify the beat of man-made music, an ability known as beat induction.[27]

Self awareness

The mirror test allows scientists to determine whether birds are conscious of themselves and able to distinguish themselves from other animals by determining whether they possess or lack the ability to recognize themselves in their own reflections. Mirror self-recognition has been demonstrated in European magpies,[28] making them one of only a few species to possess this capability.[29] However, in 1981, Epstein, Lanza and Skinner published a paper in the journal Science in which they argued that pigeons also pass the mirror test. A pigeon was trained to look in a mirror to find a response key behind it which it then turned to peck—food was the consequence of a correct choice (i.e., the pigeon learned to use a mirror to find critical elements of its environment). Next, the bird was trained to peck at dots placed on its feathers; food was, again, the consequence of touching the dot. This was done without a mirror. Then a small bib was placed on the pigeon—enough to cover a dot placed on its lower belly. A control period without the mirror yielded no pecking at the dot. But when the mirror was shown, the pigeon became active, looked into it and then tried to peck on the dot under the bib.

Untrained pigeons have never been able to pass the mirror test. However, pigeons do not normally have access to mirrors and do not have the necessary experiences to use them. Giving a pigeon this experience in no way guaranteed it would pass the mirror test, since the pigeon never pecked dots on its own body in the presence of the mirror (until the final test).

Despite this, pigeons are not classified as being able to recognize their reflection, because those that did were trained to do so and the animal must be able to do this without human assistance: it must also be shown that the birds are able to do this in the wild with no experience, just on their own intelligence. But even when an animal is trained to do this, it is still unknown if they are self-aware, or are just repeating the same movements and commands that they were taught so that they may receive a treat as a reward after they have correctly completed their task.[citation needed]

Some studies have suggested that birds—separated from mammals by over 300 million years of independent evolution—have developed brains capable of primate-like consciousness through a process of convergent evolution.[30][31] Although avian brains are structurally very different from the brains of cognitively-advanced mammals, each has the neural circuitry associated with higher-level consciousness, according to a 2006 analysis of the neuroanatomy of consciousness in birds and mammals.[31] The study acknowledges that similar neural circuitry does not by itself prove consciousness, but notes its consistency with suggestive evidence from experiments on birds’ working and episodic memory, sense of object permanence, and theory of mind (both covered below).[31]

Tool use

The woodpecker finch using a stick to impale a grub, with a second image showing it had successfully captured it.

Many birds have been shown capable of using tools. The definition of a tool has been debated. One proposed definition of tool use has been defined by T. B. Jones and A. C. Kamil in 1973 as

the use of physical objects other than the animal's own body or appendages as a means to extend the physical influence realized by the animal[32]

By this definition, a bearded vulture (lammergeier) dropping a bone on a rock would not be using a tool since the rock cannot be seen as an extension of the body. However the use of a rock manipulated using the beak to crack an ostrich egg would qualify the Egyptian vulture as a tool user. Many other species, including parrots, corvids and a range of passerines, have been noted as tool users.[1]

New Caledonian crows have been observed in the wild to use sticks with their beaks to extract insects from logs. While young birds in the wild normally learn this technique from elders, a laboratory crow named "Betty" improvised a hooked tool from a wire with no prior experience, the only known species other than humans to do so.[33][34] In 2014, a New Caledonian crow named "007" by researchers from the University of Auckland in New Zealand solved an eight-step puzzle to get to some food. The crows also fashion their own tools, the only bird that does so, out of the leaves of pandanus trees.[34] The woodpecker finch from the Galapagos Islands also uses simple stick tools to assist it in obtaining food. In captivity, a young Española cactus finch learned to imitate this behavior by watching a woodpecker finch in an adjacent cage.[35][36][37][38]

Crows in urban Japan and the United States have innovated a technique to crack hard-shelled nuts by dropping them onto crosswalks and letting them be run over and cracked by cars. They then retrieve the cracked nuts when the cars are stopped at the red light.[39] Macaws have been shown to utilize rope to fetch items that would normally be difficult to reach.[40][41] Striated herons (Butorides striatus) use bait to catch fish.

Observational learning

Using rewards to reinforce responses is often used in laboratories to test intelligence. However, the ability of animals to learn by observation and imitation is considered more significant. Crows have been noted for their ability to learn from each other.[42]

Brain anatomy

At the beginning of the 20th century, scientists argued that the birds had hyper-developed basal ganglia, with tiny mammalian-like telencephalon structures.[43] Modern studies have refuted this view.[44] The basal ganglia only occupy a small part of the avian brain. Instead, it seems that birds use a different part of their brain, the medio-rostral neostriatum/hyperstriatum ventrale (see also nidopallium), as the seat of their intelligence, and the brain-to-body size ratio of psittacines (parrots) and corvines (birds of the crow family) is actually comparable to that of higher primates.[45]

Studies with captive birds have given insight into which birds are the most intelligent. While parrots have the distinction of being able to mimic human speech, studies with the grey parrot have shown that some are able to associate words with their meanings and form simple sentences (see Alex). Parrots and the corvid family of crows, ravens, and jays are considered the most intelligent of birds. Not surprisingly, research has shown that these species tend to have the largest HVCs. Dr. Harvey J. Karten, a neuroscientist at UCSD who has studied the physiology of birds, has discovered that the lower parts of avian brains are similar to those of humans.[citation needed]

Social behavior

Social life has been considered to be a driving force for the evolution of intelligence. Many birds have social organizations, and loose aggregations are common. Many corvid species separate into small family groups (or "clans") for activities such as nesting and territorial defense. The birds then congregate in massive flocks made up of several different species for migratory purposes. Some birds use teamwork while hunting. Predatory birds hunting in pairs have been observed using a "bait and switch" technique, whereby one bird will distract the prey while the other swoops in for the kill.

Social behavior requires individual identification, and most birds appear to be capable of recognizing mates, siblings and young. Other behaviors such as play and cooperative breeding are also considered indicators of intelligence.

Crows appear to be able to remember who observed them catching food. They also steal food caught by others.[46]

In some fairy-wrens such as the superb and red-backed, males pick flower petals in colors contrasting with their bright nuptial plumage and present them to others of their species that will acknowledge, inspect and sometimes manipulate the petals. This function seems not linked to sexual or aggressive activity in the short and medium term thereafter, though its function is apparently not aggressive and quite possibly sexual.[47]

Communication

Birds communicate with their flockmates through song, calls, and body language. Studies have shown that the intricate territorial songs of some birds must be learned at an early age, and that the memory of the song will serve the bird for the rest of its life. Some bird species are able to communicate in several regional varieties of their songs. For example, the New Zealand saddleback will learn the different song "dialects" of clans of its own species, much as human beings might acquire diverse regional dialects. When a territory-owning male of the species dies, a young male will immediately take his place, singing to prospective mates in the dialect appropriate to the territory he is in.[48] Similarly, around 300 tui songs have been recorded.[49] The greater the competition in the area, it has been suggested, the more likely the birds are to actually create or make their song more complex.[50]

Recent studies indicate that some birds may have an ability to memorize "syntactic" patterns of sounds, and that they can be taught to reject the ones determined to be incorrect by the human trainers. These experiments were carried out by combining whistles, rattles, warbles, and high-frequency motifs.[51]

Conceptual abilities

Evidence that birds can form abstract concepts such as same v. different has been provided by Alex, the grey parrot. Alex was trained by animal psychologist Irene Pepperberg to vocally label more than 100 objects of different colors and shapes and which are made from different materials. Alex could also request or refuse these objects ('I want X') and quantify numbers of them.[52]

Macaws have been demonstrated to comprehend the concept of "left" and "right." [53][54]

Object permanence

Macaws as well as carrion crows have been demonstrated to fully comprehend the concept of object permanence at a young age.[55][56] Macaws will even refute the "A-not-B error". If they are shown an item, especially one with whose purpose they are familiar—they will search logically for where it could be feasibly placed. One test for was done as follows: A macaw was shown an item; the item was then hidden behind the back of the trainer and placed into a container. The container it was placed in without the macaw seeing, along with another container and multiple objects, were spread upon a table simultaneously. The specific container that the item was stored in out of the macaws' sight was one that the macaw had never observed before. The macaw searched this some, then another container, then returning to open the correct container to demonstrate knowledge of and the ability to search for the item.[57]

Theory of mind

A study on the little green bee-eater suggests that these birds may be able to see from the point of view of a predator.[58] The brown-necked raven has been observed hunting lizards in complex cooperation with other ravens, demonstrating an apparent understanding of prey behavior.[59] The California scrub jay hides caches of food and will later re-hide food if it was watched by another bird the first time, but only if the bird hiding the food has itself stolen food before from a cache.[60] A male Eurasian jay takes into account which food his bonded partner prefers to eat when feeding her during courtship feeding rituals.[61] Such an ability to see from the point of view of another individual and to attribute motivations and desires had previously been attributed only to the great apes and elephants.

See also

References

  1. ^ a b Nathan J. Emery (2006) Cognitive ornithology: the evolution of avian intelligence. Phil. Trans. R. Soc. B (2006) 361, 23–43, princeton.edu
  2. ^ Rand, Ayn 1967. Introduction to Objectivist Epistemology. New York: The Objectivist.
  3. ^ Hurford, James (2007). The Origins of Meaning: Language in the Light of Evolution. New York: Oxford University Press. ISBN 978-0-19-920785-5.
  4. ^ Miller, D. J. (1993). Do animals subitize? In S. T. Boysen & E. J. Capaldi (Eds.), The development of numerical competence: Animal and human models (pp. 149–169). Hillsdale, NJ: Erlbaum.
  5. ^ Smirnova, AA, OF Lazareva and ZA Zorina (2000) Use of number by crows: investigation by matching and oddity learning. J. Experimental analysis of Behaviour 73:163–176 PDF Archived 17 December 2008 at the Wayback Machine, seab.envmed.rochester.edu
  6. ^ Pepperberg, IM (2006). "Grey parrot numerical competence: a review". Animal Cognition. 9 (4): 377–391. doi:10.1007/s10071-006-0034-7. PMID 16909236.
  7. ^ Cook, Robert (2001). Avian Visual Cognition. http://pigeon.psy.tufts.edu/avc/: Department of Psychology, Tufts University, Comparative Cognition Press. pp. Birds' Judgments of Number and Quality. {{cite book}}: External link in |location= (help)
  8. ^ Hoh, Erling Hoh (1988) Flying fishes of Wucheng – fisherman in China use cormorants to catch fish. Natural History. October, 1988
  9. ^ Mattison, Sara (2012). "Training Birds and Small Mammals for Medical Behaviors". Veterinary Clinics of North America: Exotic Animal Practice. 15 (3): 487–499. doi:10.1016/j.cvex.2012.06.012. PMID 22998964.
  10. ^ Carter, D. E.; Eckerman, D. A. (1975). "Symbolic matching by pigeons: rate of learning complex discriminations predicted from simple discriminations". Science. 187 (4177): 662–664. doi:10.1126/science.1114318. PMID 1114318.
  11. ^ Dickinson, Anthony (5 October 2012). "Associative learning and animal cognition". Philosophical Transactions of the Royal Society B: Biological Sciences. 367 (1603): 2733–2742. doi:10.1098/rstb.2012.0220. ISSN 0962-8436. PMC 3427555. PMID 22927572.{{cite journal}}: CS1 maint: PMC format (link)
  12. ^ a b c d e f g h i Bebus, Sara E.; Small, Thomas W.; Jones, Blake C.; Elderbrock, Emily K.; Schoech, Stephan J. (2016). "Associative learning is inversely related to reversal learning and varies with nestling corticosterone exposure". Animal Behaviour. 111: 251–260. doi:10.1016/j.anbehav.2015.10.027.
  13. ^ a b c Guido, Jorgelina María; Biondi, Laura Marina; Vasallo, Aldo Ivan; Muzio, Rubén Nestor (2017). "Neophobia is negatively related to reversal learning ability in females of a generalist bird of prey, the Chimango Caracara, Milvago chimango". Animal Cognition. 20 (4): 591–602. doi:10.1007/s10071-017-1083-9. ISSN 1435-9448.
  14. ^ a b c d Bonaparte, Kristina M.; Riffle-Yokoi, Christina; Burley, Nancy Tyler (19 September 2011). Iwaniuk, Andrew (ed.). "Getting a Head Start: Diet, Sub-Adult Growth, and Associative Learning in a Seed-Eating Passerine". PLoS ONE. 6 (9): e23775. doi:10.1371/journal.pone.0023775. ISSN 1932-6203. PMC 3176201. PMID 21949684.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  15. ^ Spencer, K.A; Buchanan, K.L; Goldsmith, A.R; Catchpole, C.K (2003). "Song as an honest signal of developmental stress in the zebra finch (Taeniopygia guttata)". Hormones and Behavior. 44 (2): 132–139. doi:10.1016/s0018-506x(03)00124-7. ISSN 0018-506X.
  16. ^ a b Kriengwatana, Buddhamas; Farrell, Tara M.; Aitken, Sean D.T.; Garcia, Laura; MacDougall-Shackleton, Scott A. (2015). "Early-life nutritional stress affects associative learning and spatial memory but not performance on a novel object test". Behaviour. 152 (2): 195–218. doi:10.1163/1568539X-00003239. ISSN 0005-7959. {{cite journal}}: no-break space character in |first2= at position 5 (help); no-break space character in |first3= at position 5 (help); no-break space character in |first5= at position 6 (help)
  17. ^ a b c d Clayton, Nicky S.; Krebs, John R. (1994). "One-trial associative memory: comparison of food-storing and nonstoring species of birds". Animal Learning & Behavior. 22 (4): 366–372. doi:10.3758/bf03209155. ISSN 0090-4996.
  18. ^ a b Mirville, Melanie O.; Kelley, Jennifer L.; Ridley, Amanda R. (2016). "Group size and associative learning in the Australian magpie (Cracticus tibicen dorsalis)". Behavioral Ecology and Sociobiology. 70 (3): 417–427. doi:10.1007/s00265-016-2062-x. ISSN 0340-5443.
  19. ^ a b c d e Madden, Joah R.; Langley, Ellis J. G.; Whiteside, Mark A.; Beardsworth, Christine E.; van Horik, Jayden O. (26 September 2018). "The quick are the dead: pheasants that are slow to reverse a learned association survive for longer in the wild". Philosophical Transactions of the Royal Society B: Biological Sciences. 373 (1756): 20170297. doi:10.1098/rstb.2017.0297. ISSN 0962-8436. PMC 6107567. PMID 30104439.{{cite journal}}: CS1 maint: PMC format (link)
  20. ^ a b Veit, Lena; Pidpruzhnykova, Galyna; Nieder, Andreas (8 December 2015). "Associative learning rapidly establishes neuronal representations of upcoming behavioral choices in crows". Proceedings of the National Academy of Sciences. 112 (49): 15208–15213. doi:10.1073/pnas.1509760112. ISSN 0027-8424. PMC 4679020. PMID 26598669.{{cite journal}}: CS1 maint: PMC format (link)
  21. ^ Nelson Slater, Melissa; Hauber, Mark E. (2017). "Olfactory enrichment and scent cue associative learning in captive birds of prey". Zoo Biology. 36 (2): 120–126. doi:10.1002/zoo.21353.
  22. ^ Scott, John P. 1972. Animal Behavior. Univ. of Chicago Press. Chicago, Ill. p. 193.
  23. ^ Kamil, A.; Balda, R. (1985). "Cache recovery and spatial memory in Clark's nutcrackers (Nucifraga columbiana)". Journal of Experimental Psychology: Animal Behavior Processes. 11: 95–111. doi:10.1037/0097-7403.11.1.95.
  24. ^ Bennett, A. T. D. (1993). "Spatial memory in a food storing corvid. I. Near tall landmarks are primarily used". J. Comp. Physiol. A. 173 (2): 193–207. doi:10.1007/BF00192978.
  25. ^ Healy, S. D. & Hurly, T. A. 1995 Spatial memory in rufous hummingbirds (Selasphorus rufus): a field test. Anim. Learn. Behav. 23, 63–68.
  26. ^ C. R. Raby, D. M. Alexis, A. Dickinson and N. S. Clayton 2007. Planning for the future by western scrub-jays. Nature 445, 919–921 doi:10.1038/nature05575 PMID 17314979 PDF, bec.ucla.edu
  27. ^ Patel, Aniruddh D.; Iversen, John R.; Bregman, Micah R.; Schulz, Irena & Schulz, Charles (2008–2008), "Investigating the human-specificity of synchronization to music", Proceedings of the 10th Intl. Conf. on Music Perception and Cognition (Adelaide: Causal Productions)
  28. ^ Güntürkün, Onur; Schwarz, Ariane; Prior, Helmut (19 August 2008). "Mirror-Induced Behavior in the Magpie (Pica pica): Evidence of Self-Recognition". PLOS Biology. 6 (8): e202. doi:10.1371/journal.pbio.0060202. ISSN 1545-7885. PMC 2517622. PMID 18715117.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  29. ^ Prior, H.; Schwarz, A.; Güntürkün, O. (2008). "Mirror-induced behavior in the Magpie (Pica pica): evidence of self-recognition". PLoS Biology. 6 (8): e202. doi:10.1371/journal.pbio.0060202. PMC 2517622. PMID 18715117.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  30. ^ Butler, Ann B.; Manger, Paul R.; Lindahl, B.I.B.; Århem, Peter (2005). "Evolution of the neural basis of consciousness: a bird–mammal comparison". BioEssays. 27 (9): 923–936. doi:10.1002/bies.20280. PMID 16108067.
  31. ^ a b c Butler, Ann B.; Cotterill, Rodney M.J. (2006). "Mamillian and avian neuroanatomy and the question of consciousness in birds". The Biological Bulletin. no. 2 (2): 106–127. doi:10.2307/4134586. JSTOR 4134586. PMID 17062871. {{cite journal}}: |volume= has extra text (help)
  32. ^ Jones, T. B.; Kamil, A. C. (1973). "Tool-making and tool-using in the northern blue jay". Science. 180 (4090): 1076–1078. doi:10.1126/science.180.4090.1076. PMID 17806587.
  33. ^ Crow making tools, news.nationalgeographic.com
  34. ^ a b Ackerman, J (2016). The Genius of Birds. New York, NY: Penguin Books. pp. 65, 72. ISBN 9781594205217.
  35. ^ Robert Burton; Jane Burton; Kim Taylor (1985). Bird behavior. Knopf. p. 58. ISBN 978-0-394-53957-7.
  36. ^ Millikan, G. C. & Bowman, R. I. (1967). Observations on Galapagos tool-using finches in captivity. Living Bird, 6, 23-41
  37. ^ Pacific Discovery. Vol. 46 or 47. California Academy of Sciences. 1993. p. 10.
  38. ^ Davis-Merlen, Gayle; Merlen, Godfrey (2000). "WHISH: More than a tool-using finch" (PDF). Notícias de Galápagos. 61: 3.
  39. ^ "Attenborough – Crows in the City". YouTube.com. 12 February 2007. Retrieved 21 February 2018.
  40. ^ "Gizzard uses a rope to retrieve a submerged gift, 10 second retrieval from noticing the rope". YouTube. 20 June 2011. Retrieved 10 December 2013.
  41. ^ "Hyacinth Macaw-Cincinnati Zoo". YouTube. Retrieved 10 December 2013.
  42. ^ Bugnyar, T. & Kotrschal, K. 2002 Observational learning and the raiding of food caches in ravens, Corvus corax: is it 'tactical' deception? Anim. Behav. 64, 185–195. doi:10.1006/anbe.2002.3056
  43. ^ Edinger, L (1908). "The relations of comparative anatomy to comparative psychology". Journal of Comparative Neurology and Psychology. 18 (5): 437–457. doi:10.1002/cne.920180502. hdl:2027/hvd.32044106448244.
  44. ^ Reiner, A. et al., (2005) Organization and Evolution of the Avian Forebrain, The Anatomical Record Part A 287A:1080–1102
  45. ^ Iwaniuk, A.N.; Nelson, J.E. (2003). "Developmental differences are correlated with relative brain size in birds: A comparative analysis". Canadian Journal of Zoology. 81 (12): 1913–1928. doi:10.1139/z03-190.
  46. ^ Emery, N.J.; Clayton, N.S. (2004). "The mentality of crows: convergent evolution of intelligence in corvids and apes". Science. 306 (5703): 1903–1907. CiteSeerX 10.1.1.299.6596. doi:10.1126/science.1098410. PMID 15591194.
  47. ^ Karubian, Jordan & Alvarado, Allison (2003): Testing the function of petal-carrying in the Red-backed Fairy-wren (Malurus melanocephalus). Emu 103(1):87–92 HTML abstract, publish.csiro.au
  48. ^ Environews: Saddleback Dialects, Radio live (2011) http://www.radiolive.co.nz/Environews-Saddleback-Dialects/tabid/506/articleID/20318/Default.aspx
  49. ^ The language of love, Auckland Now http://www.stuff.co.nz/auckland/local-news/6740119/The-language-of-love
  50. ^ Tui one of world's most intelligent birds, 3 News (2012) http://www.3news.co.nz/Tui-one-of-worlds-most-intelligent-birds/tabid/1160/articleID/254369/Default.aspx Archived 1 February 2014 at the Wayback Machine
  51. ^ Gentner, Timothy Q.; Fenn, Kimberly M.; Margoliash, Daniel; Nusbaum, Howard C. (2006). "Recursive syntactic pattern learning by songbirds". Nature. 440 (7088): 1204–1207. doi:10.1038/nature04675. PMC 2653278. PMID 16641998.
  52. ^ Pepperberg, I. M. 1999 The Alex studies: cognitive and communicative abilities of Grey parrots. Cambridge, MA: Harvard University Press.
  53. ^ "Left and right progress Sept 27th, 2011". YouTube. 27 September 2011. Retrieved 10 December 2013.
  54. ^ "Left and right shake progress Dec 18, 2011". YouTube. 18 December 2011. Retrieved 10 December 2013.
  55. ^ "Object permanence demonstration 2". YouTube. 18 December 2011. Retrieved 10 December 2013.
  56. ^ Hoffmann, Almut; Rüttler, Vanessa; Nieder, Andreas (1 August 2011). "Ontogeny of object permanence and object tracking in the carrion crow, Corvus corone". Animal Behaviour. 82 (2): 359–367. doi:10.1016/j.anbehav.2011.05.012. ISSN 0003-3472.
  57. ^ "Object permanance for our macaws- video documentation". YouTube. 23 June 2011. Retrieved 10 December 2013.
  58. ^ Watve, Milind; Thakar, Juilee; Kale, Abhijit; Puntambekar, S; Shaikh, I; Vaze, K; Jog, M; Paranjape, S; et al. (December 2002). "Bee-eaters (Merops orientalis) respond to what a predator can see". Animal Cognition. 5 (4): 253–259. doi:10.1007/s10071-002-0155-6. PMID 12461603.
  59. ^ Yosef, Reuven; Yosef, Nufar (May 2010). "Cooperative hunting in Brown-Necked Raven (Corvus rufficollis) on Egyptian Mastigure (Uromastyx aegyptius)". Journal of Ethnology. 28 (2): 385–388. doi:10.1007/s10164-009-0191-7.
  60. ^ Clayton, Nichola S.; Joanna M Dally; Nathan J Emery (29 April 2007). "Social cognition by food-caching corvids. The western scrub-jay as a natural psychologist". Phil. Trans. R. Soc. B. 362 (1480): 507–522. doi:10.1098/rstb.2006.1992. PMC 2346514. PMID 17309867.
  61. ^ Ostojic, L.; Shaw, R. C.; Cheke, L. G.; Clayton, N. S. (4 February 2013). "Evidence suggesting that desire-state attribution may govern food sharing in Eurasian jays". Proceedings of the National Academy of Sciences. 110 (10): 4123–4128. doi:10.1073/pnas.1209926110. ISSN 0027-8424. PMC 3593841. PMID 23382187.

External links