Big ideas for small brains: what can psychiatry learn from worms, flies, bees and fish?

Abstract

While the research community has accepted the value of rodent models as informative research platforms, there is less awareness of the utility of other small vertebrate and invertebrate animal models. Neuroscience is increasingly turning to smaller, non-rodent models to understand mechanisms related to neuropsychiatric disorders. Although they can never replace clinical research, there is much to be learnt from 'small brains'. In particular, these species can offer flexible genetic 'tool kits' that can be used to explore the expression and function of candidate genes in different brain regions. Very small animals also offer efficiencies with respect to high-throughput screening programs. This review provides a concise overview of the utility of models based on worm, fruit fly, honeybee and zebrafish. Although these species may have small brains, they offer the neuropsychiatric research community opportunities to explore some of the most important research questions in our field.

Towards a Comprehensive Catalog of Zebrafish Behavior 1.0 and Beyond

“…[18][19][20][21] Zebrafish breed in large numbers, are inexpensive, small and easy to manipulate genetically or pharmacologically. [22][23][24][25][26][27] Zebrafish behavioral responses are robust, appear to be evolutionarily conserved, and resemble those of mammalian species. [28][29][30][31][32][33] Finally, they have significant potential for high-throughput screening due to powerful video-tracking tools developed for both larval and adult zebrafish.…”

Zebrafish embryos and larvae: A new generation of disease models and drug screens

“…This is because zebrafish share extensive homologies to other vertebrate species (including rodents and humans) in terms of their genome, brain patterning, and the structure and function of several neural and physiological systems, including the stress-regulating axis (Postlethwait et al, 2000;Rodriguez et al, 2002;Tropepe and Sive, 2003;Guo, 2004;Sison et al, 2006;Lieschke and Currie, 2007;Schaaf et al, 2008;Veldman and Lin, 2008;Guo, 2009;Morris, 2009;Pogoda and Hammerschmidt, 2009;Steenbergen et al, 2010;Burne et al, 2011).…”

Framework for integrating animal welfare into life cycle sustainability assessment

“…Wild aquatic animals usually die from suffocation, which takes some minutes. The operation before that, for example trawling with a net, can take several hours (Braithwaite 2010). Only shrimps are concerned by wild catch in our study, and we assumed a slaughter duration of 1 h. In aquaculture, in our case for salmon production, we assumed fish is killed by a gill cut or by stunning with carbon dioxide followed by a gill cut, which takes, on average, 5-6 min until brain function is lost (van de Vis et al 2003).…”

“…It is restricted to space allowance and freedom of movement, whereas many more conditions determine an animal's welfare. The (Azevedo et al 2009, Herculano-Houzel 2009 b (Herculano-Houzel 2016) c The number only refers to neocortical neurons (Jelsing et al 2006); hence, it underestimates the cortical neurons d (Olkowicz et al 2016) e The body mass of a salmon was assumed to equal 4.5 kg (FRS Marine Laboratory 2006), while the brain:body mass ratio was assumed to equal that of a shark-1:2496 (Serendip 2016) f (Lobster Institute 2016) g (Burne et al 2011;Shulman and Bostrom 2012) h The factor difference between an adult insect and the larva (a mealworm is the larva of the mealworm beetle) was assumed to equal that of a zebrafish, which is a factor of 10: a larval zebrafish has 100,000 neurons (Naumann et al 2010), while an adult zebrafish has 1 million neurons (Alivisatos et al 2012) (Bartussek 1995a(Bartussek , 1995b(Bartussek , 1996 and the Welfare Quality® Consortium (Welfare Quality® 2009aQuality® , 2009bQuality® , 2009c can, however, not be applied at large scale due to data scarcity. Therefore, a balance must be found between scalability and indicator complexity.…”