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Human Culture
Published in Shamim I. Ahmad, Aging: Exploring a Complex Phenomenon, 2017
Snell-Rood and Wick (2013) tested the hypothesis that since the urban ecosystem represented a novel environment, it would select for increased behavioral plasticity. They used small mammals such as voles, bats, mice, shrew, gophers, and squirrels as test subjects and rural and urban areas in Minnesota as the test sites. In this state, about 75% of the population lives in one urban area, Minneapolis-Saint Paul. They used cognition (measured as cranial capacity) as a proxy for behavioral plasticity. Of the 10 species measured, two showed a significant difference in mean cranial capacity between urban and rural populations of each of the species with the urban population having a larger mean size. When relative differences in cranial capacity between rural and urban populations were calculated, all 10 species displayed a significant trend for the urban population of a species to have a relatively larger cranial capacity than the rural population of the same species. Fertility as measured by litter size showed a positive correlation with percentage increase in cranial capacity for urban over rural populations.
Measurement of Brain Age: Conceptual Issues and Neurobiological Indices
Published in Richard C. Adelman, George S. Roth, Endocrine and Neuroendocrine Mechanisms of Aging, 2017
Thus, the measurement of behavioral plasticity during aging requires that considerable attention be given to experimental design. Many alternative interpretations can be controlled for, however, if it can be shown that the aged animals can perform the task normally and are only impaired if certain specific conditions are introduced (e.g., a delay in testing, a reversal procedure, etc.). There are, of course, similarly extensive control problems that must be considered in the assessment of other complex functional measures.
Theories of aging and adaptation
Published in Peter G. Coleman, Ann O’Hanlon, Aging and Development, 2017
Peter G. Coleman, Ann O’Hanlon
Optimisation in contrast involves ongoing effort or rehearsal to acquire or improve performance towards those selected goals. Optimisation is linked to behavioural plasticity and the ability of the individual to modify the environment both to create more favourable or desired outcomes for the self and to meet the continual challenges and changes being experienced. Examples of optimising outcomes can be understood at an age-graded level (e.g. maturation and the accumulation of experience), or at a history-graded level (e.g. improvements in healthcare and education) (Marsiske et al., 1995). Optimisation strategies can also be understood at physical, psychological and social levels. An example within the physical sector would be a person who is overweight, and whose health therefore is in danger. Optimisation in this case would be to keep to a strict diet or to exercise more or to avoid situations that elicit eating behaviour.
The Drosophila melanogaster foraging gene affects social networks
Published in Journal of Neurogenetics, 2021
Nawar Alwash, Aaron M. Allen, Marla B. Sokolowski, Joel D. Levine
Adult rover-sitter heterozygotes are known to exhibit intermediate behavioral phenotypes to rover and sitter [e.g. adult foraging behavior (Pereira & Sokolowski, 1993); sucrose consumption in a foraging arena (Anreiter et al., 2017)]. A pattern of intermediate dominance was also found for most of the behavioral elements and social network measures that exhibited rover-sitter differences (see Figure 2). Interestingly, there appeared to be a larger spread in the sitter compared to the rover and rover-sitter heterozygotes for some of the measures suggesting that sitter group measures may be more plastic in response to the environment. Differences in behavioral plasticity have been reported for behavioral and physiological phenotypes influences by for (reviewed in (Anreiter & Sokolowski, 2019)).
What can a worm learn in a bacteria-rich habitat?
Published in Journal of Neurogenetics, 2020
In addition to non-associative learning, previous studies have shown that olfactory responses can be respectively enhanced or weakened by paring odorant exposure with the presence or absence of food, which presumably represents an appetitive or aversive environment (Figure 1). Various neuronal circuits and molecular pathways have been characterized in regulating these associative learning behaviors [(Alcedo & Zhang, 2013; de Bono & Maricq, 2005) and the references therein]. C. elegans also remembers the salt concentration under its cultivation condition and seeks this concentration when tested in a salt gradient after the training. However, if the worm is kept at a salt concentration in the absence of food, it avoids the concentration during the post-training rest (Kunitomo et al., 2013; Luo et al., 2014; Saeki, Yamamoto, & Iino, 2001; Tomioka et al., 2006). As a critical condition, the cultivation temperature significantly modulates the navigation of the worm in a temperature gradient (Aoki & Mori, 2015; Biron et al., 2006; Goodman et al., 2014; Goodman & Sengupta, 2019; Hedgecock & Russell, 1975; Mori & Ohshima, 1995). Some of these forms of behavioral plasticity resemble associative learning identified in vertebrate animals and in fruit flies. While a one-time massed training in these paradigms often generates a memory for a couple hours, spaced training can generate a long-term memory that lasts for 16 h (Kauffman, Ashraf, Corces-Zimmerman, Landis, & Murphy, 2010).
But can they learn? My accidental discovery of learning and memory in C. elegans
Published in Journal of Neurogenetics, 2020
In retrospect, these accounts embody the ethos of C. elegans research: challenging old assumptions and proving the impossible possible. From these serendipitous beginnings, with the help and support of the C. elegans community, the field of learning and memory in C. elegans began. Since then the field has grown rapidly, and many researchers have expanded our knowledge about the types of learning and memory C. elegans can show and identified genetic mechanisms for many of them. It is quite astounding that the worm shows so much behavioral plasticity and can learn so many different things. The take-home message from this research on a microscopic worm with only ∼300 neurons, that lives about 2 weeks is that it is highly adaptive for organisms to learn from their experience and to use that experience to guide their behavior. The breadth of the abilities of C. elegans to change its behavior as a result of experience is a testament to the importance of behavioral plasticity and learning in survival.