Pigeons on Par with Primates in Numerical Competence

Self Cite

Learning to read involves the acquisition of letter-sound relationships (i.e., decoding skills) and the ability to visually recognize words (i.e., orthographic knowledge). Although decoding skills are clearly human-unique, given they are seated in language, recent research and theory suggest that orthographic processing may derive from the exaptation or recycling of visual circuits that evolved to recognize everyday objects and shapes in our natural environment. An open question is whether orthographic processing is limited to visual circuits that are similar to our own or a product of plasticity common to many vertebrate visual systems. Here we show that pigeons, organisms that separated from humans more than 300 million y ago, process words orthographically. Specifically, we demonstrate that pigeons trained to discriminate words from nonwords picked up on the orthographic properties that define words and used this knowledge to identify words they had never seen before. In addition, the pigeons were sensitive to the bigram frequencies of words (i.e., the common co-occurrence of certain letter pairs), the edit distance between nonwords and words, and the internal structure of words. Our findings demonstrate that visual systems organizationally distinct from the primate visual system can also be exapted or recycled to process the visual word form.O n the surface, the human brain seems to have evolved for reading (1). Across individuals and cultures (2), reading activates an identical area in the left lateral occipitotemporal sulcus known as the visual word form area (VWFA) (3). This activation occurs no matter the case or font of the script (4), it increases in the transition from being illiterate to literate (5), and it increases with improvements in reading fluency (6). However, the presence of a VWFA is difficult to assimilate with the fact that writing was invented merely ∼5,400 y ago, and only became widespread very recently in human history, making it impossible that an area of the human brain evolved specifically for reading (7). Without the time to evolve, how can we explain the presence of the VWFA? One intriguing possibility is that the VWFA is the product of neuronal recycling, with its neurons learning to code visual stimuli (i.e., words) that greatly differ from the visual objects it initially evolved to code (8, 9).Anatomically, the VWFA lies just downstream of the ventral visual (i.e., what) pathway, a hierarchy of areas critical to visual object and face recognition in human and nonhuman primates. Dehaene et al. (10) argue that this hierarchy of areas can be tuned to the visual word form, with areas lower in the hierarchy simply encoding letter identities, and areas in the upper echelons of the hierarchy, specifically the VWFA, tuned to the co-occurrence of letter pairs (i.e., bigrams) and letter strings. At the present time, there are no neurophysiological studies that have investigated whether neurons in the nonhuman primate temporal lobe can learn to code anything beyond individual alphabetic ...

Section: Resultssupporting

confidence: 49%

Orthographic processing in pigeons ( Columba livia )

Scarf

Boy

Reinert

et al. 2016

Self Cite

“…A recent study by Scarf et al (29) showed that pigeons can compare numerical values, and in doing so they represent an abstract numerical rule that can be applied to novel numerical values. Pigeons' accuracy on that ordinal numerical task is comparable to that of monkeys tested on an identical task (21).…”

Section: For Review)mentioning

confidence: 99%

Math, monkeys, and the developing brain

Cantlon

2012

101

Thirty thousand years ago, humans kept track of numerical quantities by carving slashes on fragments of bone. It took approximately 25,000 y for the first iconic written numerals to emerge among human cultures (e.g., Sumerian cuneiform). Now, children acquire the meanings of verbal counting words, Arabic numerals, written number words, and the procedures of basic arithmetic operations, such as addition and subtraction, in just 6 y (between ages 2 and 8). What cognitive abilities enabled our ancestors to record tallies in the first place? Additionally, what cognitive abilities allow children to rapidly acquire the formal mathematics knowledge that took our ancestors many millennia to invent? Current research aims to discover the origins and organization of numerical information in humans using clues from child development, the organization of the human brain, and animal cognition.analog magnitude | functional MRI | mathematics education | numerical cognition | numerosity T his review traces the origins of numerical processing from "primitive" quantitative abilities to math intelligence quotient (IQ). "Primitive" quantitative abilities are those that many animals use to estimate the value of an object or event, for instance its distance, length, duration, number, amplitude, saturation, or luminance (among others). The constraints on how human and animal minds process these different quantities are similar (1). For example, all of these quantities show cognitive processing limitations that can be predicted by Weber's law. Weber's law states that quantity discrimination is determined by the objective ratio between their values. This ratio-based psychological and neural signature of quantity processing indicates that many quantities are represented in an analog format, akin to the way in which a machine represents intensities in currents or voltages (1). I discuss the types of constraints that influence quantity discrimination, using "number" as the initial example, and then consider the psychological and neural relationship between "number" and other quantitative dimensions. Similar constraints on processing across different quantities have been interpreted as evidence that they have a common evolutionary and/or developmental origin and a common foundation in the mind and brain (2-11). The resolution of these issues is important for understanding the inherent organization of our most basic conceptual faculties. The issue is also important for understanding how our formal mathematical abilities originated.Primitive quantitative abilities play a role in how modern humans learn culture-specific, formal mathematical concepts (1). Preverbal children and nonhuman animals possess a primitive ability to appreciate quantities, such as the approximate number of objects in a set, without counting them verbally. Instead of counting, children and animals can mentally represent quantities approximately, in an analog format. Studies from our group and others have shown that human adults, children, and nonhuman primates share cogni...

“…single-cell recordings | crow | nidopallium caudolaterale | quantity B irds show elaborate quantification skills (1)(2)(3) that are of adaptive value in naturalistic situations like nest parasitism (4), food caching (5), or communication (6). The neuronal correlates of numerosity representations have only been explored in humans (7)(8)(9) and primates (10)(11)(12)(13)(14)(15)(16)(17)(18), and they have been found to reside in the prefrontal and posterior parietal neocortices.…”

mentioning

confidence: 99%

Neurons selective to the number of visual items in the corvid songbird endbrain

Ditz

Nieder

2015

150

187

It is unknown whether anatomical specializations in the endbrains of different vertebrates determine the neuronal code to represent numerical quantity. Therefore, we recorded single-neuron activity from the endbrain of crows trained to judge the number of items in displays. Many neurons were tuned for numerosities irrespective of the physical appearance of the items, and their activity correlated with performance outcome. Comparison of both behavioral and neuronal representations of numerosity revealed that the data are best described by a logarithmically compressed scaling of numerical information, as postulated by the WeberFechner law. The behavioral and neuronal numerosity representations in the crow reflect surprisingly well those found in the primate association cortex. This finding suggests that distantly related vertebrates with independently developed endbrains adopted similar neuronal solutions to process quantity.single-cell recordings | crow | nidopallium caudolaterale | quantity B irds show elaborate quantification skills (1-3) that are of adaptive value in naturalistic situations like nest parasitism (4), food caching (5), or communication (6). The neuronal correlates of numerosity representations have only been explored in humans (7-9) and primates (10-18), and they have been found to reside in the prefrontal and posterior parietal neocortices. In contrast to primates, birds lack a six-layered neocortex. The birds' lineage diverged from mammals 300 Mya (19), at a time when the neocortex had not yet developed from the pallium of the endbrain. Instead, birds developed different pallial parts as dominant endbrain structures (20, 21) based on convergent evolution, with the nidopallium caudolaterale (NCL) as a highlevel association area (22-26). Where and how numerosity is encoded in vertebrates lacking a neocortex is unknown. Here, we show that neurons in the telencephalic NCL of corvid songbirds respond to numerosity and show a specific code for numerical information. ResultsCrows were trained in a delayed matching-to-sample task to match the number of (one to five) dots presented on touch-sensitive computer displays ( Fig. 1 A and B). Crows watched two displays (first sample, then test) separated by a 1-s delay. They were trained to peck at the displays on the screen if the test displays contained the same number of items as the sample. We varied the exact physical appearance of the displays by randomly placing dots in arbitrary locations, and by randomly choosing dot size.The crows performed the task proficiently (73.8 ± 0.4% and 77.5 ± 0.5% correct over all recording sessions for crow A and crow J, respectively; Fig. 1C). Average performance of both crows was significantly better than chance (50%) for all sample numerosities relative to the numerically most distant nonmatches (Binomial test, P < 0.01). Better performance for sample numerosities at the low (one) and high (five) numerosity range (Fig. 1D) are most likely due to "endeffects," because one and five items had to be discriminated only fro...