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The nativist approach to infant cognitive development proposes that infants are born with inherent knowledge structures that allow them to interpret the world almost immediately. This perspective contrasts with earlier developmental theories, such as those proposed by Jean Piaget, which emphasized a more gradual acquisition of cognitive abilities through interaction with the environment. One key concept in this approach is object permanence — the understanding that objects continue to...
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Related Experiment Video

Updated: Jul 8, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

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Temporal origin of nestedness in interaction networks.

Phillip P A Staniczenko1, Debabrata Panja2,3

  • 1Department of Biology, Brooklyn College, City University of New York, Brooklyn, NY 11210, USA.

PNAS Nexus
|December 11, 2023
PubMed
Summary
This summary is machine-generated.

A new model shows that the timing of interactions (phenology) can generate nested network structures. This phenology model successfully predicted many interactions in fish market and plant-pollinator networks.

Keywords:
complex systemsinteraction networksnestedness

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Area of Science:

  • Ecology
  • Network Science
  • Mathematical Biology

Background:

  • Nestedness is a prevalent property in various complex systems, including ecological networks.
  • High nestedness implies that less connected nodes interact with subsets of partners connected to more connected nodes.
  • Understanding the mechanisms generating nestedness is crucial for linking system processes to network structures.

Purpose of the Study:

  • To investigate the mechanisms underlying nestedness in complex networks.
  • To develop and test a probabilistic model for generating nested network structures.
  • To connect phenological timing to network nestedness and interaction predictability.

Main Methods:

  • Developed a probabilistic model based on phenology (timing of interactions).
  • Applied the model to empirical data from fish market and plant-pollinator networks.
  • Assessed the model's ability to predict network interactions.

Main Results:

  • The phenology-based model successfully generated nested structures.
  • The model predicted approximately two-thirds of interactions in fish market networks.
  • The model predicted about one-third of interactions in plant-pollinator networks.

Conclusions:

  • Phenological timing is a key mechanism driving nestedness in interaction networks.
  • Frequent co-occurrences due to phenology form a core structure of nested interactions.
  • Opportunistic interactions and partner preferences explain remaining network links.