Neurons in the Endbrain of Numerically Naive Crows Spontaneously Encode Visual Numerosity

Wagener, Lysann; Loconsole, Maria; Ditz, Helen M.; Nieder, Andreas

doi:10.1016/j.cub.2018.02.023

Cited by 56 publications

(51 citation statements)

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“…adapter. This channel-based hypothesis is in line with numerosity-tuned neural populations (Harvey & Dumoulin, 2017;Harvey et al, 2015;Harvey et al, 2013;Nieder, Freedman, & Miller, 2002;Nieder & Miller, 2004;Viswanathan & Nieder, 2013;Wagener, Loconsole, Ditz, & Nieder, 2018) and duration-tuned neural populations (Aubie, Sayegh, & Faure, 2012;Becker & Rasmussen, 2007;Duysens et al, 1996;Hawken, Shapley, & Grosof, 1996;Heron et al, 2012;Leon & Shadlen, 2003;Maarseveen et al, 2019;Mita, Mushiake, Shima, Matsuzaka, & Tanji, 2009), with our results implying either that onset/offset duration channels also encode numerosity or that there is neuronal communication between duration-selective and numerosity-selective channels (duration/numerosity channels).…”

Section: Theoretical Implicationssupporting

confidence: 89%

Distinct temporal mechanisms modulate numerosity perception

et al. 2019

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Our ability to process numerical and temporal information is an evolutionary skill thought to originate from a common magnitude system. In line with a common magnitude system, we have previously shown that adaptation to duration alters numerosity perception. Here, we investigate two hypotheses on how duration influences numerosity perception. A channelbased hypothesis predicts that numerosity perception is influenced by adaptation of onset/offset duration channels which also encode numerosity or wire together with numerosity channels (duration/numerosity channels). Hence, the onset/offset duration of the adapter is driving the effect regardless of the total duration of adaptation. A strength-of-adaptation hypothesis predicts that the effect of duration on numerosity perception is driven by the adaptation of numerosity channels only, with the total duration of adaptation driving the effect regardless of the onset/ offset duration of the adapter. We performed two experiments where we manipulated the onset/offset duration of the adapter, the adapter's total presentation time, and the total duration of the adaptation trial. The first experiment tested the effect of adaptation to duration on numerosity discrimination, whereas the second experiment tested the effect of adaptation to numerosity and duration on numerosity discrimination. We found that the effect of adaptation to duration on numerosity perception is primarily driven by adapting duration/numerosity channels, supporting the channel-based hypothesis. In contrast, the effect of adaptation to numerosity on numerosity perception appears to be driven by the total duration of the adaptation trial, supporting the strength-of-adaptation hypothesis. Thus, we show that adaptation of at least two temporal mechanisms influences numerosity perception.

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Section: Theoretical Implicationssupporting

confidence: 89%

Distinct temporal mechanisms modulate numerosity perception

et al. 2019

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“…Despite these controls, a significant portion of network units in the topmost layers of our model spontaneously developed numerosity encoding that was virtually identical to the encoding observed in real neurons. Just like neurons in the brains of numerically naïve animals, about 10% of the network units exhibited numerosity selectivity ( 9 , 10 ). Moreover, and in agreement with real number neurons, the network units were tuned to preferred numerosities, exhibited approximate tuning that decreased in precision with increasing numbers, and were best described on a logarithmically compressed number line.…”

Section: Discussionmentioning

confidence: 99%

“…Human psychophysics ( 5 , 6 ), brain imaging studies in humans ( 7 , 8 ), and single-neuron recordings in animals support the direct and automatic assessment of numerosity in the brain. In animals that had not been trained to judge number, single neurons spontaneously responded to numerosity and were tuned to preferred numerosities ( 9 , 10 ). These “number neurons” that also exist in the human brain ( 11 ) are regarded as the neuronal foundation of numerical information processing ( 12 ).…”

Section: Introductionmentioning

confidence: 99%

Number detectors spontaneously emerge in a deep neural network designed for visual object recognition

2019

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Humans and animals have a “number sense,” an innate capability to intuitively assess the number of visual items in a set, its numerosity. This capability implies that mechanisms to extract numerosity indwell the brain’s visual system, which is primarily concerned with visual object recognition. Here, we show that network units tuned to abstract numerosity, and therefore reminiscent of real number neurons, spontaneously emerge in a biologically inspired deep neural network that was merely trained on visual object recognition. These numerosity-tuned units underlay the network’s number discrimination performance that showed all the characteristics of human and animal number discriminations as predicted by the Weber-Fechner law. These findings explain the spontaneous emergence of the number sense based on mechanisms inherent to the visual system.

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“…In humans, as well as non-human primates, evidence suggests that parietal cortex is the primary locus of this capacity [9, 10], although other cortical regions have also been implicated in this function [11, 12]. Recent work with birds, for example, suggests neural encoding of numerical information is localized in the endbrain of crows [13]. Given crows’ early divergence in phylogenetic history, it is not clear what the endbrain might be analogous to in mammals, or whether parietal mechanisms support numerical abilities in non-primates.…”

Section: Introductionmentioning

confidence: 99%

Canine sense of quantity: evidence for numerical ratio-dependent activation in parietotemporal cortex

Aulet

Chiu

Prichard

et al. 2019

Preprint

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47The approximate number system, which supports the rapid estimation of quantity, emerges early 48 in human development and is widespread across species. Neural evidence from both human and 49 non-human primates suggests the parietal cortex as a primary locus of numerical estimation, but 50 it is unclear whether the numerical competencies observed across non-primate species are 51 subserved by similar neural mechanisms. Moreover, because studies with non-human animals 52 typically involve extensive training, little is known about the spontaneous numerical capacities 53 of non-human animals. To address these questions, we examined the neural underpinnings of 54 number perception using awake canine functional magnetic resonance imaging. Dogs passively 55 viewed dot arrays that varied in ratio and, critically, received no task-relevant training or 56 exposure prior to testing. We found evidence of ratio-dependent activation, which is a key 57 feature of the approximate number system, in canine parietotemporal cortex in the majority of 58 dogs tested. This finding is suggestive of a neural mechanism for quantity perception that has 59 been conserved across mammalian evolution. 60 61 Keywords: approximate number system; canine cognition; quantity discrimination; fMRI; 62 parietal cortex 63 93 of cortex for representing non-symbolic numerical quantity, then activation in this region should 94 increase as the ratio between alternating dot arrays increases, despite constant cumulative surface 95 area and variable element size [17]. That is, a number-sensitive region of cortex will exhibit 96 greater activation when the numerical values of the stimuli presented are more dissimilar (e.g., 2 97 vs. 10 dots) than when numerical value is constant (e.g., 6 vs. 6 dots), consistent with Weber's 98 law [18]. 99 100 Methods 101 Participants 102 103 Eleven awake, unrestrained dogs (see Table 1 for demographic information), were 104 scanned in a Siemens 3T Trio MRI scanner. Prior to testing, all dogs completed a training 105 program to be desensitized to the scanner environment through behavior shaping and positive 106 reinforcement [19]. All dogs had previously participated in fMRI studies while viewing stimuli 107 on a projection screen but had no prior training on numerical discrimination. 108 109 Table 1. Dogs' demographic information Stimuli were 75 dot arrays comprised of light gray dots on a black background (800 x 130 800 px). For each numerosity used (2, 4, 6, 8, and 10), stimuli varied in cumulative area (i.e., the 131 total gray on each image). For each numerosity, cumulative area was either 10, 20, or 30% of the 132 total stimulus. For each numerosity, 15 unique stimuli were used (5 stimuli per cumulative area 133 value). In each stimulus, individual dot size varied up to 30%. Dot location varied randomly. 134Critically, these controls minimize the influence of non-numerical properties, in order to ensure 135 that the results can be attributed to changes in numerical value [20, 21]. In accordance with 136 current esti...

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Neurons in the Endbrain of Numerically Naive Crows Spontaneously Encode Visual Numerosity

Cited by 56 publications

References 40 publications

Distinct temporal mechanisms modulate numerosity perception

Distinct temporal mechanisms modulate numerosity perception

Number detectors spontaneously emerge in a deep neural network designed for visual object recognition

Canine sense of quantity: evidence for numerical ratio-dependent activation in parietotemporal cortex

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