Animal Behaviors and Animal Communications

2011 ◽  
pp. 1-1
Keyword(s):  
Animal Behaviors

James’s Animal Encounters

2017 ◽  
Author(s):  
Benjamin Bateman
Keyword(s):  
Progressive Era ◽  
Environmental Impacts ◽  
War Zone ◽  
Animal Behaviors

Henry James’s story “The Beast in the Jungle” is read as a response to the “nature fakers” controversy of the Progressive era. As Teddy Roosevelt and others insisted that nature is a war zone in which animals clash violently, James’s tale probes less aggressive animal behaviors and suggests that social Darwinist ideologies encourage the competitive practices they claim to merely describe. Instructing John Marcher in the pleasures to be found in making himself available to a beast he has been trained to fear, May Bartram functions as an early feminist ecologist who deploys a critique of species exceptionalism and its environmental impacts to undermine patriarchal ambition and to promote a vulnerable version of survival.

Social Olfaction: A Review of the Role of Olfaction in a Variety of Animal Behaviors

1971 ◽  
Vol 29 (1) ◽  
pp. 195-243 ◽  
Author(s):  
Mary Lou Cheal ◽  
Richard L. Sprott
Keyword(s):  
Social Behavior ◽  
Experimental Evidence ◽  
Behavioral Effects ◽  
Behavioral Data ◽  
Olfactory Acuity ◽  
Animal Behaviors ◽  
The Social ◽  
History Of ◽  
Social Behavior Of Animals

Behavioral olfactory experiments were reviewed, relating the behavioral effects of pheromones to the psychophysical work in olfaction. Short descriptions of various experiments were used to show the importance of olfaction to the social behavior of animals by tracing the history of the experimental evidence and viewing the behavioral data pertaining to the discharge of pheromones and their effects and to look at the psychophysical evidence for olfactory acuity and the behavioral implications for the role of the physiological structures in olfaction.

Religious Behavior in Animals and Man: Drug-Induced Effects

1977 ◽  
Vol 7 (3) ◽  
pp. 219-236 ◽  
Author(s):  
Ronald K. Siegel
Keyword(s):  
Animal Model ◽  
Experimental Analysis ◽  
Operant Behavior ◽  
Religious Behavior ◽  
Religious Activities ◽  
Drug Induced ◽  
The Third ◽  
Animal Behaviors

This paper attempts to develop an experimental analysis of drug-induced religious behavior. The first part discusses drugs and religious behavior in man and includes sections on anthropological, contemporary, and experimental perspectives. The second part reviews analogous natural and drug-induced animal behaviors which are seen to be structurally similar to human religious activities. The functional similarities are examined in the third section which analyses religion in terms of operant behavior concepts and findings. It is concluded that the behavioral, albeit not necessarily the experiential, aspects of drug-induced religious behavior can be studied in the animal model.

scholarly journals The Origin of a Symbol in Animal Behaviors.

2002 ◽  
Vol 42 (1) ◽  
pp. 14-19
Author(s):  
Yukio-Pegio GUNJI ◽  
Etsuo MIZUKAMI ◽  
Nobuhide KITABAYASHI
Keyword(s):  
Animal Behaviors

scholarly journals Selfee: Self-supervised Features Extraction of animal behaviors

2021 ◽  
Author(s):  
Yinjun Jia ◽  
Shuai-shuai Li ◽  
Xuan Guo ◽  
Junqiang Hu ◽  
Xiao-Hong Xu ◽  
...  
Keyword(s):  
Animal Behavior ◽  
Temporal Dynamics ◽  
Video Recordings ◽  
Animal Behaviors ◽  
Video Frames ◽  
Neuroscience Research ◽  
Depth Analysis ◽  
Time Series Analyses ◽  
Supervised Feature Extraction

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in the laboratories for behavior analysis. However, it has not been achieved to use a fully unsupervised method to extract comprehensive and discriminative features directly from raw behavior video frames for annotation and analysis purposes. Here, we report a self supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end to end way. Visualization and classification of the extracted features (Meta representations) validate that Selfee processes animal behaviors in a comparable way of human understanding. We demonstrate that Meta representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in depth analysis. Furthermore, time series analyses of Meta representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.

scholarly journals Long-range sequential dependencies precede complex syntactic production in language acquisition

2020 ◽  
Author(s):  
Tim Sainburg ◽  
Anna Mai ◽  
Timothy Q Gentner
Keyword(s):  
Long Range ◽  
Power Law ◽  
Language Production ◽  
Language Evolution ◽  
Developmental Time ◽  
Hierarchical Organization ◽  
Cognitive Capacity ◽  
Human Language ◽  
Animal Behaviors ◽  
Linguistic Behavior

AbstractTo convey meaning, human language relies on hierarchically organized, long-range relationships spanning words, phrases, sentences, and discourse. The strength of the relationships between sequentially ordered elements of language (e.g., phonemes, characters, words) decays following a power law as a function of sequential distance. To understand the origins of these relationships, we examined long-range statistical structure in the speech of human children at multiple developmental time points, along with non-linguistic behaviors in humans and phylogenetically distant species. Here we show that adult-like power-law statistical dependencies precede the production of hierarchically-organized linguistic structures, and thus cannot be driven solely by these structures. Moreover, we show that similar long-range relationships occur in diverse non-linguistic behaviors across species. We propose that the hierarchical organization of human language evolved to exploit pre-existing long-range structure present in much larger classes of non-linguistic behavior, and that the cognitive capacity to model long-range hierarchical relationships preceded language evolution. We call this the Statistical Scaffolding Hypothesis for language evolution.1Significance StatementHuman language is uniquely characterized by semantically meaningful hierarchical organization, conveying information over long timescales. At the same time, many non-linguistic human and animal behaviors are also often characterized by richly hierarchical organization. Here, we compare the long-timescale statistical dependencies present in language to those present in non-linguistic human and animal behaviors as well as language production throughout childhood. We find adult-like, long-timescale relationships early in language development, before syntax or complex semantics emerge, and we find similar relationships in non-linguistic behaviors like cooking and even housefly movement. These parallels demonstrate that long-range statistical dependencies are not unique to language and suggest a possible evolutionary substrate for the long-range hierarchical structure present in human language.

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