Melophorus bagoti Navigational mechanisms Central place foragers
Effective, Robust
Wehner and Wehner 1990; Wehner 2003
Navigational mechanisms
Effective, Robust Relatively simple
Tiny Brain (1mm3) Parsimonious, Efficient Melophorus bagoti Gigantiops destructor The ants’ navigational toolkit
Path Landmark Systematic Integration navigation Search Path Integration
Food item Direction Distance (celestial compass) (odometer)
Cataglyphis fortis Nest Wehner 1982………………………… 2012 Problems of Path Integration Path - Accumulate errors Integration
Food item Direction Distance (celestial compass) (odometer)
Cataglyphis fortis Nest Problems of Path Integration Path - Accumulate errors Integration - Passive displacement
Food item Direction Distance (celestial compass) (odometer)
Cataglyphis fortis Nest
Wehner and Srinivasan 1981. J. comp. phys Problems of Systematic Path Integration Search - Accumulate errors - Passive displacement
Food item
Cataglyphis fortis Nest
Wehner and Räber 1979. Experencia Cartwright and Collett 1983. J. comp. phys Landmark navigation
Food item
Nest Landmark navigation
Food item Landmarks… Our human way of seeing the world
Nest Our human way of seeing the world
Panorama Landmark Our human way of seeing the world
Distal Panorama Landmark Our human way of seeing the world …..and designing experiments Distal panorama
Proximal Landmarks Our human way of seeing the world …..and designing experiments
Panorama (very flat)
Landmarks Our human way of seeing the w orld
Geometry Features (Extended surfaces) Our human way of seeing the w orld …..and designing experiments
Geometry (Extended surfaces) !
Features ?
A little bit more objective… A little bit more objective… 1 pixel / 4 deg
Melophorus bagoti compound eye: Acuity = 4 deg
(Schwarz et al., 2003. Arthr. Struct & Devlop.) 1 pixel / 4 deg
1 pixel / 4 deg
UV 1 pixel / 4 deg
Green A little bit more objective… A little bit more objective…
Do insect segregate landmarks and panorama? (Wystrach and Graham 2012) Quantify the modification of the scenery…
2 days
Training
N
10m
F F (Wystrach et al., 2011) Quantify the modification of the scenery…
Reference pictures Compared pictures Map of mismatch (training condition) (Test conditions)
N N
10m Comparisons
F F Relate image difference / ant behaviour…
Cues widespread on their panoramic view
U turns
Degradation of the matching Zero vector ants (Wystrach et al., 2011) Information available to the animal
Cues widespread on their panoramic view
Landmark navigation Information available to the animal
Cues widespread on their panoramic view
Visual scene navigation Identify the problem in natural environment Visual scene navigation
Cataglyphis velox
Melophorus bagoti Route following
Cataglyphis velox
Melophorus bagoti
Mangan and Webb 2012. Behav. Ecol. Kohler and Wehner 2005, Neurobiol. of Learn. and Mem. Wystrach, Philippides and Graham (in prep). Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest
Current view Current view
Visual scene navigation Modelling: Zeil et al. 2003. J. Opt. Soc. Am. A; Graham et al. 2010. Cur. Biol. Ant experiment: Wystrach et al. 2011. J. Exp. Psych.
Memory
Nest Best match! Current view Current view
Simply move in the most familiar direction
Visual scene navigation Route following model (Baddeley et al., 2012)
Route following No positional knowledge Simply move in the most familiar direction Homing from novel locations
Melophorus bagoti N
Melophorus bagoti Wystrach et al. 2012. J. Exp. Biol Homing from novel locations
(Cartwright and Collett, 1983; Zeil et al., 2003) Homing from novel locations
(Cartwright and Collett, 1983; Zeil et al., 2003) Homing from novel locations
Simply move as to increase the familiarity
(Cartwright and Collett, 1983; Zeil et al., 2003) Visual scene Feeder navigation
Route following No positional knowledge Simply going in the most familiar direction
Familiar terrain
Nest Homing from novel locations No positional knowledge Simply moving so as the familiarity increase The ants’ navigational toolkit
Path Visual scene Systematic Integration navigation Search
Quite simple …
How can it be so robust ? How can it be so robust ?
Kohler and Wehner 2005. Neurobiol. Learn. Mem. Melophorus bagoti
How can it be so robust ?
Nest
Melophorus bagoti Wystrach et al. 2011. JCPA How can it be so robust ?
Wystrach et al. 2011. JCPA How can it be so robust ?
Nest
Melophorus bagoti Wystrach et al. 2011. JCPA How can it be so robust ? Sensory level: using multiple cues How can it be so robust ? Sensory level: using multiple cues
Path Integration
Direction Distance (celestial compass) (odometer) How can it be so robust ? Sensory level: using multiple cues
Path Integration
Direction Distance
Polarized light Proprioception Sun position (Stride, Ascent Chromatic cues and Descent) Light gradient Optic flow Wind direction
Wehner 2008. Myrmec. news Wittlinger et al., 2006. Science Wystrach and Schwarz, in prep Ronacher 2008. Myrmec. News How can it be so robust ? Sensory level: using multiple cues Visual scene navigation
Skyline Centre of mass Edges orientation Optic flow pattern
Wystrach et al., 2011. Front. in Zool. How can it be so robust ? Sensory level: using multiple cues Visual scene navigation
Panoramic views Wystrach et al., 2011. Front. in Zool. Motor routines Knaden et al. 2006. Curr. biol Odor cues Steck et al., 2009. Front. in Zool. Magnetic cue Buehlmann et al., 2012. Plos one
Vibratory cue Cataglyphis noda Buehlmann et al., 2012. Plos one credit: Max Planck Institute for Chemical Ecology/Badeke
How can it be so robust ? Sensory level: using multiple cues Learnt information
Panoramic views Wystrach et al., 2011. Front. in Zool. Motor routines Knaden et al. 2006. Curr. biol Odor cues Steck et al., 2009. Front. in Zool. Magnetic cue Buehlmann et al., 2012. Plos one
Vibratory cue Cataglyphis noda Buehlmann et al., 2012. Plos one credit: Max Planck Institute for Chemical Ecology/Badeke
How can it be so robust ? Sensory level: using multiple cues
Chromatic gradient Panoramic views Proprioception Polarized light Vibratory cue Light gradient Optic flow Odor cues Sun position Motor routines Wind direction Magnetic cues
Path Learnt Systematic Integration information Search
Emergency plan! How can it be so robust ? Output level: combining strategies
Path Learnt Systematic Integration information Search ?
Behavior How can it be so robust ? Output level: combining strategies
Path Learnt Systematic Integration information Search
Map-like representation?
Behavior How can it be so robust ? Output level: combining strategies
Path Learnt Systematic Integration information Search
Learnt views operate independently from PI Map-like representation? (Kohler and Wehner, 2005) PI operate independently from views (Andel and Wehner, 2002)
Behavior N F
X 10 How can it be so robust ? Output level: combining strategies
Path Learnt Systematic Integration information Search
Learnt views operate independently from PI Map-like representation? (Kohler and Wehner, 2005) PI operate independently from views (Andel and Wehner, 2002)
N F How can it be so robust ? Output level: combining strategies
Path Learnt Systematic Integration information Search
How do the different Behavior systems interact?
Wehner 2008, Myrmec. News. How can it be so robust ? Output level: combining strategies
PI Views
Zero vector Nest
Melophorus bagoti Wystrach and Legge, in prep How can it be so robust ? Output level: combining strategies
Zero vector Nest
Full vector
Feeder PI Views
Melophorus bagoti Wystrach and Legge, in prep How can it be so robust ? Output level: combining strategies
PI Views Zero vector Nest
Full vector
Melophorus bagoti Wystrach and Legge, in prep How can it be so robust ? Output level: combining strategies
Zero vector Nest
Full vector
Feeder
PI Views Wystrach and Legge, in prep See also Collett 2012. Curr. biol. How can it be so robust ? Output level: combining strategies
PI Views Zero vector Nest
Full vector
Wystrach and Legge, in prep How can it be so robust ? Output level: combining strategies
Zero vector Nest
Full vector
Feeder
PI Views Wystrach and Legge, in prep How can it be so robust ? Output level: combiningweighting strategies
Zero vector Nest
Full vector
Feeder
Wystrach and Legge, in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Current Familiarity
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Current Familiarity
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity continuous
How are the Behavior strategies weighted?
Wystrach et al. in prep Weighting the different systems
Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity continuous
How are the Behavior strategies weighted?
Wystrach et al. in prep Path Integration
Feeder Vector length
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest unfamiliar Path Integration terrain Feeder Vector length
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest Path Integration
Feeder Vector length
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest Path Integration
Feeder Path Vector length integration
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest Totally Path Integration unfamiliar Feeder Path Vector length integration terrain ? Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest Path Path Path Integration integration integration Feeder Vector length
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous
Nest Systematic Systematic search search What ants do when they are lost ?
Feeder
Nest
Melophorus bagoti
Wystrach et al. in prep What ants do when they are lost ? Distant release points: unfamiliar environment
Feeder
Zero vector ?
Nest Path Visual scene Systematic Integration navigation Search
Vector length Current Familiarity continuous
Behavior Melophorus bagoti
Wystrach et al. in prep What ants do when they are lost ? Distant release points: unfamiliar environment
Feeder
Zero vector
Nest
Melophorus bagoti
Wystrach et al. in prep Distant release points: unfamiliar environment
Zero vector
Nest Zero vector
Feeder
Wystrach et al. in prep Distant release points: unfamiliar environment
Backtracking
Zero vector
Nest Zero vector
Zero-vector ants backtrack towards the feeder Feeder
Wystrach et al. in prep When do ants backtrack ?
Path Backtracking Visual scene Systematic Integration Navigation Search Current Vector length continuous ? Familiarity
Output When do ants backtrack ?
Feeder Feeder
Zero vector Residual PI Nest Nest ants vector
- On unfamiliar terrain… - When PI vector is small…
Wystrach et al. in prep When do ants backtrack ?
Recent view of the nest vicinity!
Feeder Feeder Feeder
Zero vector Zero vector Zero vector Nest Nest Nest ants ants ants
- On unfamiliar terrain… - When PI vector is small… - Recent view of the nest vicinity Wystrach et al. in prep When do ants backtrack ?
Path Backtracking Visual scene Systematic Integration Navigation Search Recent view of Current Vector length the nest vicinity continuous Familiarity
Output - On unfamiliar terrain… - When PI vector is small… - Recent view of the nest vicinity Robust !
Path Path Path Integration integration integration Feeder Vector length
Visual scene navigation Current Familiarity
Systematic Familiar Search terrain continuous Systematic Systematic search search Backtracking
Nest Recent view of the nest vicinity Backtracking Backtracking Robust !
Path Path integration integration Feeder Complex Decision making ?
A distributed system with simple interactions
Path scene Systematic Integration navigation Search Familiar terrain Systematic Systematic search search
No need of a higher Nest representation
Backtracking Backtracking Simple solutions behind apparently complex behaviour
Exploit complex visual information without landmark recognition
Follow complex routes without positional knowledge
Home from novel locations without cognitive map
Path scene Systematic Complex decision making Integration navigation Search without higher representations CONCLUSION Top-Down Human way of seeing the world
(Landmarks) (Cognitive map)
Literature What is their ecological problem ? Hypotheses How do they solve it? Insects use landmarks! Behavioural criterion
Animal’s Umwelt
Result Bottom-up Insects use landmarks! Chittka et al., 2012 Wystrach and Graham, 2012
Sebastian Schwarz Thanks Patrick Schultheiss
Alice Baniel Ken Cheng
Paul Graham The ants you Michael Mangan
Bart Baddeley Andy Philippides