Development of a model to study visual categorization learning in chickens (Gallus gallus domesticus)

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Abstract

Categorization is a cognitive process that enables individuals to recognize similar yet distinct stimuli as equivalent [1–3]. To categorize an object, agents must identify key features of the new object by applying what they have learned from previous interactions with objects in that category [4]. Thus, categorization eliminates the need for the agent to repeatedly investigate each new object, thereby significantly expanding its adaptive capabilities. However, the nervous mechanisms that regulate this process are still not well understood. The primary aim of the present study is to establish an experimental behavioral model that will facilitate the investigation of the neurobiological mechanisms underlying visual categorization learning.

Chickens (Gallus gallus domesticus) were selected as a visual learning model. The study of categorization used the chickens’ innate tendency to peck at new small objects and remember their characteristics. For this purpose, a chick was placed in a cage that resembled a house cage with beads affixed to the floor. The “bead floor” consisted of more than 100 beads of different colors and food scattered throughout [5]. In the developed model, pecking solely on the beads was deemed inaccurate as opposed to pecking on the food. For training purposes, the chick was given 80 peckings and evaluated based on how many nibbles it used to create categories for “beads” vs. “food”. If the chick did not make at least 5 cues or was unable to make 80 cues within 10 minutes during the training session, it was excluded from the study.

First, the study investigated the effect of simultaneously presenting two new categories of “food” and “beads” on chicks’ behavior. The group that formed both “beads” and “new food” categories made more errors during the learning period, but performed as well as the group that only formed the “bead” category during the subsequent test. The study analyzed whether chicks could categorize objects (beads) of different sizes into a unified group. The chicks were trained with a floor of small beads and later tested with a different floor of larger beads. Results revealed that the chicks did not transfer their categorization ability from small to large beads. In the opposite scenario, where the chicks were presented with large beads during their training, and then offered small beads during the test, they refrained from pecking the smaller ones.

In the next stage, we examined how the object’s color affected the development of a novel category. The results showed that when the chicks were presented with the floor containing an additional color of beads, specifically yellow, they made the majority of errors while pecking the “new type of beads”. Then, the study evaluated whether the chicks could transition the classification of “beads” between color set № 1 (blue, pink, green, yellow, and black silver) and color set № 2 (light green, beige, blue, red, gold, and white), and vice versa. The findings indicate that the chickens do form the categories of “beads” in both versions of the task, and after training, do not peck at beads of the new color. Chickens are capable of categorizing “beads” and “food”, and can generalize within these categories.

Thus, this experimental study established the formation of categories in chickens during fast learning. Future application of the model will enable the investigation of the underlying neurobiological mechanisms in categorization learning.

Full Text

Categorization is a cognitive process that enables individuals to recognize similar yet distinct stimuli as equivalent [1–3]. To categorize an object, agents must identify key features of the new object by applying what they have learned from previous interactions with objects in that category [4]. Thus, categorization eliminates the need for the agent to repeatedly investigate each new object, thereby significantly expanding its adaptive capabilities. However, the nervous mechanisms that regulate this process are still not well understood. The primary aim of the present study is to establish an experimental behavioral model that will facilitate the investigation of the neurobiological mechanisms underlying visual categorization learning.

Chickens (Gallus gallus domesticus) were selected as a visual learning model. The study of categorization used the chickens’ innate tendency to peck at new small objects and remember their characteristics. For this purpose, a chick was placed in a cage that resembled a house cage with beads affixed to the floor. The “bead floor” consisted of more than 100 beads of different colors and food scattered throughout [5]. In the developed model, pecking solely on the beads was deemed inaccurate as opposed to pecking on the food. For training purposes, the chick was given 80 peckings and evaluated based on how many nibbles it used to create categories for “beads” vs. “food”. If the chick did not make at least 5 cues or was unable to make 80 cues within 10 minutes during the training session, it was excluded from the study.

First, the study investigated the effect of simultaneously presenting two new categories of “food” and “beads” on chicks’ behavior. The group that formed both “beads” and “new food” categories made more errors during the learning period, but performed as well as the group that only formed the “bead” category during the subsequent test. The study analyzed whether chicks could categorize objects (beads) of different sizes into a unified group. The chicks were trained with a floor of small beads and later tested with a different floor of larger beads. Results revealed that the chicks did not transfer their categorization ability from small to large beads. In the opposite scenario, where the chicks were presented with large beads during their training, and then offered small beads during the test, they refrained from pecking the smaller ones.

In the next stage, we examined how the object’s color affected the development of a novel category. The results showed that when the chicks were presented with the floor containing an additional color of beads, specifically yellow, they made the majority of errors while pecking the “new type of beads”. Then, the study evaluated whether the chicks could transition the classification of “beads” between color set № 1 (blue, pink, green, yellow, and black silver) and color set № 2 (light green, beige, blue, red, gold, and white), and vice versa. The findings indicate that the chickens do form the categories of “beads” in both versions of the task, and after training, do not peck at beads of the new color. Chickens are capable of categorizing “beads” and “food”, and can generalize within these categories.

Thus, this experimental study established the formation of categories in chickens during fast learning. Future application of the model will enable the investigation of the underlying neurobiological mechanisms in categorization learning.

ADDITIONAL INFORMATION

Funding sources. The research was funded by a grant from the Non-commercial Foundation for the Advancement of Science and Education “Intellect”, with the support of the Lomonosov Moscow State University Interdisciplinary Scientific and Educational School “Brain, Cognitive Systems, Artificial Intelligence”.

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About the authors

E. A. Diffine

Lomonosov Moscow State University

Author for correspondence.
Email: diffinenok@gmail.com
Russian Federation, Moscow

A. A. Tiunova

Institute of Normal Physiology named after P.K. Anokhin

Email: diffinenok@gmail.com
Russian Federation, Moscow

K. V. Anokhin

Lomonosov Moscow State University; Institute of Normal Physiology named after P.K. Anokhin

Email: diffinenok@gmail.com
Russian Federation, Moscow; Moscow

References

  1. Edelman GM. Neural Darwinism: The Theory of Neuronal Group Selection. New York: BasicBooks; 1978:23–43. doi: 10.1126/science.240.4860.1802
  2. Herrnstein RJ. Levels of categorization. In Signal and sense. Local and global order in perceptual maps. New York: John Wiley and Sons Inc.; 1990:365–413.
  3. Huber L, Aust U. Mechanisms of perceptual categorization in birds. In: ten Cate C, Healy S, editors. Avian cognition. Cambridge University Press.; 2017:208–228. doi: 10.1017/9781316135976.012
  4. Medin DL. Concepts and conceptual structure. American Psychologist. 1989;44(12):1469–1481. doi: 10.1037/0003-066x.44.12.1469
  5. Tiunova AA, Anokhin KV, Rose SP. Two critical periods of protein and glycoprotein synthesis in memory consolidation for visual categorization learning in chicks. Learning & Memory. 1998;4(5):401–410. doi: 10.1101/lm.4.5.401

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