How to be a salmon?

This is a depository of material connected to the workshop "What is is like to be an Atlantic salmon?". It is written and maintained by Jarl Giske.

Here is a quite recent version of the ms.

Videos and PDFs of presentations

Unfortunately, the zoom recording of the first day ended abruptly during Knut's talk. The later talks by Magda, Marc and Andy were therefore not recorded. The whole second day is recorded. Sergey has split the whole-day video files into separate files for each talk.

Jarl Giske: To be an Atlantic salmon video PDF
Katja Enberg: The UN perspective video PDF
Knut Wiik Vollset: What senses are used to make life changing decisions video PDF
Magda Dumitru: What is it to be an animal? PDF
Marc Mangel: What Is it like to be (an Atlantic) salmon? PDF
Andy Higginson: A behavioural ecology perspective on what it is to be a salmon. PDF
Steve Railsback: To be a salmon in a river video PDF
Anders Frugård Opdal: How salmon (and its brain) is changed by experiences video PDF
Tore S Kristiansen: The salmon's quality of life .. and the predictive brain video PDF
Ivar Rønnestad: To feed or not to feed - that is my question video PDF
Sergey Budaev: The salmon machine video PDF

Papers mentioned

Nagel 1974: What is it like to be a bat?

Jarl's talk:
Anderson 1972: More is different.
Bubic & al 2010: Prediction, cognition and the brain.
Budaev & al 2018: AHA: A general cognitive architecture for Darwinian agents.
Budaev & al 2019: Decision-making from the animal perspective: Bridging ecology and subjective cognition.
Budaev & al 2020: Computational animal welfare: towards cognitive architecture models of animal sentience, emotion and wellbeing.
Clark 2013: Whatever next? Predictive brains, situated agents, and the future of cognitive science.
FitzGerald & al 2014: Model averaging, optimal inference, and habit formation.
Giske & al 1998: Modelling spatial dynamics of fish.
Grafen 1984: Natural selection, kin selection and group selection.
Hoffmeyer 2008. We do not have this as pdf, but a related text from 2002: Reading Hoffmeyer, rethinking biology.
Jensen & al 2021: Hormonal adjustments to future expectations impact growth and survival in juvenile fish.
Nesse 2013: Tinbergen’s four questions, organized: a response to Bateson and Laland.
Soylu 2016: An embodied approach to understanding: making sense of the world through simulated bodily activity.
Tinbergen 1963: On aims and methods of ethology.
Weidner & al 2020: Hormones as adaptive control systems in juvenile fish.

Magda's talk:
Bshary & Triki 2022: Fish ecology and cognition: insights from studies on wild and wild-caught teleost fishes.
Cleeremans 2011: The radical plasticity thesis: how the brain learns to be conscious.
Cleeremans 2022: Consciousness matters: phenomenal experience has functional value.
Mather & al 2016: Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory.

Marc's talk:
Clark & Mangel 1988: Dynamic Modeling in Behavioral Ecology.
Dobzhansky 1973: Nothing in biology makes sense except in the light of evolution.
Fleming 1998: Pattern and variability in the breeding system of Atlantic salmon (Salmo salar), with comparisons to other salmonids.
Gerhart & Kirschner 1997: Cells, Embryos and Evolution.
Mangel & Clark 2000: Dynamic State Variable Models in Ecology.
Mangel 1994: Climate change and salmonid life history variation.
Nagel 1974: What is it like to be a bat?
Rikardsen & al 2004: Modelling the life-history variation of Arctic charr.
Satterthwaite & al 2009: Steelhead life history on California's Central Coast: Insights from a state-dependent model.
Stearley & Smith 1993: Phylogeny of the Pacific trouts and salmons (Oncorhynchus) and genera of the family Salmonidae.
Thorpe & al 1998: Modelling the proximate basis of salmonid life-history variation, with application to Atlantic salmon, Salmo salar L..

Anders's talk:
Birse 1980: Neuronal increase in various areas of the nervous system of the nervous system of the guppy, Lebistes.
Braithwaite VA & AGV Salvanes 2005. Environmental variability in the early rearing environment generates behaviourally flexible cod: implications for rehabilitating wild populations. Proc R Soc B 272:1107–1113
Braithwaite et al 1996: Can juvenile Atlantic salmon use multiple cue systems in spatial learning?
Brandão et al 2015: Isolation impairs cognition in a social fish.
Bredy & al 2003: Partial reversal of the effect of maternal care on cognitive function through environmental enrichment.
Bshary & al 2014: Social cognition in fishes.
Burns JG & al 2009. Rearing environment affects the brain size of guppies: Lab-reared guppies have smaller brains than wild-caught guppies. Ethology 115:122–133
Dunlap KD 2016. Fish neurogenesis in context: Assessing environmental influences on brain plasticity within a highly labile physiology and morphology. Brain Behav Evol 87:156–166
Ebbesson and Braithwaite 2012: Environmental effects on fish neural plasticity and cognition.
Gonda et al 2009: Habitat dependent and independent plastic responses to social environment in the nine-spined stickleback (Pungitius pungitius) brain.
Gonda A & al 2010: Predation and competition mediated brain plasticity in Rana temporaria tadpoles.
Gonda A & al 2012: Brain development and predation: plastic responses depend on evolutionary history. Biol Lett 8:249-252
Guo & al 2022: Social isolation affects intra specific interaction behaviour and reduces the size of the cerebellar brain region in juvenile Atlantic salmon Salmo salar.
Herzeg & al 2015: Experimental evidence for sex specific plasticity in adult brain.
Joyce and Brown 2019: Rapid plastic changes in brain morphology in response to acute changes in predation pressure in juvenile Atlantic salmon (Salmo salar) and northern redbelly dace (Phoxinus eos).
Kihslinger RL & Nevitt 2006: Early rearing environment impacts cerebellar growth in juvenile salmon.
Kihslinger RL & al 2006. Environmental rearing conditions produce forebrain differences in wild Chinook salmon Oncorhynchus tshawytscha. Comp Biochem Physiol A 145:145–151
Knudsen 2004: Sensitive periods in the development of the brain and behaviour.
Kotrschal 2012: Inside the heads of David and Goliath: environmental effects on brain morphology among wild and growth-enhanced coho salmon Oncorhynchus kisutch.
Kotrschal and Taborsky 2010: Environmental change enhances cognitive abilities in fish.
Kotrschal et al 1998: Fish brains: evolution and environmental relationships.
Kruska 2005: On the evolutionary significance of encephalization in some eutherian mammals: Effects of adaptive radiation, domestication, and feralization.
Larsen et al 2014: Reduced rearing density increases postrelease migration success of Atlantic salmon (Salmo salar) smolts.
Lema et al 2005: Proliferation zones in the salmon telencephalon and evidence for environmental influence on proliferation rate.
Marchetti and Nevitt 2003: Effects of hatchery rearing on brain structures of rainbow trout, Oncorhynchus mykiss.
Maruska et al 2013: Social descent with territory loss causes rapid behavioral endocrine and transcriptional changes in the brain.
Mayer et el 2011: Domestication causes rapid changes in heart and brain morphology in Atlantic cod (Gadus morhua).
Mes D & al 2018. Neurobiology of wild and hatchery-reared Atlantic salmon: How nurture drives neuroplasticity.
Mes D & al 2019. Effects of environmental enrichment on forebrain neural plasticity and survival success of stocked Atlantic salmon. J Exp Biol 222:jeb212258
Näslund J & al 2012: Early enrichment effects on brain development in hatchery reared salmon Salmo salar: No evidence for a critical period.
Näslund J & al 2017: Environment dependent plasticity and ontogenetic changes in the brain of hatchery-reared Atlantic salmon.
Näslund J & al 2019: Fish density, but not environmental enrichment, affects the size of cerebellum in the brain of juvenile hatchery-reared Atlantic salmon. Environ Biol Fish 102:705–712
Park and Bell 2010: Variation of telencephalon morphology of the threespine stickleback (Gasterosteus aculeatus) in relation to inferred ecology.
Salas et al 2003: Evolution of forebrain and spatial cognition in vertebrates: Conservation across diversity.
Salas et al 2006: Neuropsychology of learning and memory in teleost fish.
Salvanes AGV & al 2007. Effects of early experience on group behaviour in fish.
Salvanes AGV & al 2013. Environmental enrichment promotes neural plasticity and cognitive ability in fish. Proc R Soc B 280:20131331
Schmidt-Hieber et al 2004: Enhanced synaptic plasticity in newly generated granule cells in the adult hippocampus.
Sørensen et al 2007: Social regulation of neurogenesis in teleosts.
von Krogh K & al 2010. Forebrain cell proliferation behaviour and physiology of zebrafish kept in enriched or barren environments. Physiol Behav 101:32–39
Zupanc and Sirbulenscu 2011: Adult neurogenesis and neuronal regeneration in the central nervous system of teleost fish.
Zupanc GHK 2006: Neurogenesis and neuronal regeneration in the adult fish brain. J Comp Physiol A 192:649–670

Tore's talk:
Conant & Ashby 1970: Every good regulator of a system must be a model of that system.
Korte & al 2007: A new animal welfare concept based on allostasis.
Perathoner & al 2016: Potential of zebrafish as a model for exploring the role of the amygdala in emotional memory and motivational behavior.
Sterling 2012: Allostasis: a model of predictive regulation.
Williams & al 2013: The function of fin rays as proprioceptive sensors in fish.

Sergey's talk:
Bossaerts & Murawski 2017: Computational complexity and human decision-making.
Bowers & Davis 2012: Bayesian just-so stories in psychology and neuroscience.
Bubic & al 2010: Prediction, cognition and the brain.
Budaev & al 2020: Computational animal welfare: towards cognitive architecture models of animal sentience, emotion and wellbeing.
Føre & al 2018: Precision fish farming: A new framework to improve production in aquaculture.
Giske & al 2013: Effects of the emotion system on adaptive behavior.
Hesslow 2016: The current status of the simulation theory of cognition.
Higginson & al 2018: Trust your gut: using physiological states as a source of information is almost as effective as optimal Bayesian learning.
Soylu 2016: An embodied approach to understanding: making sense of the world through simulated bodily activity.
Trotsos 1993: The role of computational complexity in perceptual theory.

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