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Insect-level intelligence

Insect-level intelligence

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Insect-level intelligence. Information for performing tasks Learning about home – a routine for acquisition Exploration and the return from newly discovered sites Learning routes – scaffolding Multiple routes and memory retrieval Representation of space: routes not maps. - PowerPoint PPT Presentation

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Page 1: Insect-level intelligence

Insect-level intelligence

Page 2: Insect-level intelligence

Information for performing tasks

Learning about home – a routine for acquisition

Exploration and the return from newly discovered sites

Learning routes – scaffolding

Multiple routes and memory retrieval

Representation of space: routes not maps

Page 3: Insect-level intelligence

Behaviours generally evolve within a specific ecological niche and the strategies and underlying neural systems may only operate effectively in that niche.

Page 4: Insect-level intelligence

Predator avoidance: categorisation using simple features

Zeil and Hemmi, 2006

Page 5: Insect-level intelligence

Crabs live on a flat surface where all objects above the horizon are classified as predators

Zeil and Hemmi 2006

Page 6: Insect-level intelligence

Unexpected sophistication:

Crabs at first run to their burrow whenever they spot movement above the horizon.

But, if objects are presented repeatedly, their escape attempts habituate, unless the object is a dummy bird.

(Hemmi and Zeil)

Page 7: Insect-level intelligence
Page 8: Insect-level intelligence

Behaviour is also guided by complex information

Burrows are a valued resource and fiddler crabs keep their burrow under constant surveillance. They return rapidly to it if an intruder threatens to take it over.

Zeil and Hemmi 2006

Page 9: Insect-level intelligence

A crab starts to rush home when an intruder comes within a set distance of the burrow. How does it gauge this distance when the hole is invisible?

Crab can know the distance of the intruder from retinal elevation and of the burrow from path integration. These egocentric measures must be combined to give the allocentric distance of intruder from burrow.

Page 10: Insect-level intelligence

Ants, social bees and wasps collect food for their nest. Individuals stick to one or few foraging sites and learn fixed routes between these sites and their nest.

Cataglyphis bicolor

Page 11: Insect-level intelligence

Collett, Dillman, Giger and Wehner, 1992

Homeward routes of Cataglyphis bicolor

Page 12: Insect-level intelligence

Behavioural routines for learning

A bumblebee leaving its nest for the first time may be gone for an hour and then return to a small nest hole with a load of pollen.

On departure. the bee performs an elaborate flight that helps acquire landmark information that can guide its return.

The structure of such learning flights reveal efficient strategies for acquiring visual information.

Page 13: Insect-level intelligence

Collett (1995)

10 cm

Learning flight of Vespula vulgaris leaving feeder

10 cm

Page 14: Insect-level intelligence

Two learning flights from one wasp

Moments during six of the wasp’s flights when it faces the feeder (+)

Page 15: Insect-level intelligence

Return flights to feeder

Note consistent body orientation when is close to the goal

Page 16: Insect-level intelligence

Body orientation in learning and return flights

Wasp 1

Wasp 2

Learning flight(when facing feeder)

Return flight(when close to feeder)

Page 17: Insect-level intelligence

Wehner, Meier, Zollikofer (2004)

Route learning in Cataglyphis starts with exploration.

Successive foraging trips of an unsuccessful ant

Page 18: Insect-level intelligence

White numbers show successful trips

Wehner, Meier, Zollikofer (2004)

A luckier ant

Page 19: Insect-level intelligence

Wehner 1982, 1990

Path integration encodes the coordinates of an ant’s current position relative to the nest so providing it with the information to go straight home.

Page 20: Insect-level intelligence

Ants encode the path integration coordinates of a newly discovered feeding site into long term memory and so can return directly to the site through path integration.

Collett, Collett, Wehner, 1999

Page 21: Insect-level intelligence

Such straight routes due to path integration are

modulated by innate visuo-motor responses to objects.

Page 22: Insect-level intelligence

Collett, Collett and Wehner (2000)

Route modulation by barrier

Page 23: Insect-level intelligence

Graham and Collett (2002)

Page 24: Insect-level intelligence

Graham and Collett (2002)

Page 25: Insect-level intelligence

Graham, Fauria, Collett (2003)

Route modulation by beacon

Page 26: Insect-level intelligence

Scaffolding allows route to be acquired simultaneously along the whole sequence.

It also means little chance of learning the wrong thing, so no danger in acquiring routes fast.

Why does the ant bother to learn routes if it can reach its destination through path integration?

Page 27: Insect-level intelligence

Route memories are linked to motivational state

Page 28: Insect-level intelligence

Food-ward and homeward routes overlap

Wehner (2003)

Page 29: Insect-level intelligence

Formica rufa

Page 30: Insect-level intelligence

Harris, Hempel de Ibarra, Graham and Collett (2006)

Page 31: Insect-level intelligence

Harris, Hempel de Ibarra, Graham and Collett (2006)

Page 32: Insect-level intelligence

Wehner et al. (2006)

Food-ward route not recognised by ant in homeward motivational state

Page 33: Insect-level intelligence

Memories primed by panoramic context

Collett, Fauria, Baron, Dale 1997

Page 34: Insect-level intelligence

Honeybees in a 2 compartment maze in one place

Collett, Baron, Sellen,1996

Page 35: Insect-level intelligence

Spatial representation

Ants use visual landmarks in a procedural rather than a map-like way.

They are attracted towards places defined by landmarks or they associate motor commands with landmarks.

But landmarks are not labelled with positional coordinates.

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Independence of PI and landmarks: PI coordinates are not reset by encountering familiar landmarks

Collett et al. 2003

Page 37: Insect-level intelligence

Routes are independent of PI state: repeated homeward routes (red and black) do not differ from normal trajectories (grey).

Kohler and Wehner 2005

But home vector changes. After 1st repetition of homeward route there is no home vector. After 2nd repetition, home vector points away from nest.

Andell and Wehner, 2005

Page 38: Insect-level intelligence

In mammals robust and flexible navigation is ensured by combining path integration and visual information.

Separating the two strategies also gives robustness, one strategy can take over when the other fails, and errors in one strategy do not contaminate the operation of the other.

A possible hallmark of insect intelligence is that it comprises smart, but specific and independent modules.