merkel cells and the individuality of friction ridge skin
TRANSCRIPT
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AGENT-BASED MODEL FOR FRICTION RIDGE
PATTERNS
Merkel cells and the individuality of friction ridge skin
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Agent-Based Model
Introduction Biological Background Model Results Conclusions
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Introduction
Main goal of the paperTo model friction ridge skin (FRS)
FRS once attracted much attentionPatterns of heredityDiagnosing congenital diseases
Most significant papers on FRS embryology are from the early 20th century
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Introduction
No consensus as to how the pattern is formed
Idea—a complex interaction of:Mechanical stressTrophic factorsMerkel cells
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Biological Background
FRS is formed during the 10th week Basal layer of epidermis becomes
undulated, forming primary ridges Pattern appears:
1. Core & Nail Furrow
2. Proximal Phalangeal Crease
3. Fills in and reaches the deltas last
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Biological Background
Volar pads determine overall patternLarge volar pads: whorlsMedium volar pads: loopsSmall volar pads: arches
They create compressive stress on the fingertips
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Biological Background Differential growth forces are responsible for the patterns
The ridges follow the lines of smallest stress
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Merkel Cells
Cells in the epidermis
Slowly
adapting
mechano-
sensors
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Merkel Cells
Appear randomly in the volar skin at week 7
Multiply and cover the volar pads
During the 10th week, they organize along the primary ridges
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Ridge Formation – 3 Phases1. Growth forces
2. Merkel cell rearrangement
3. Establishment of pattern
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Model Agent-based model where the Merkel Cells
are the agents Each agent is characterized by its position Begin with a random distribution of agents
on a rectangular domain On this domain, a tensor field represents
the stress distribution Merkel cells align with lines of smallest
stress
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Model: Movement of Cells Two cells interacts with each other in two
ways: : repulsion force : attraction force
Movement of the Merkel cell at position
Where
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Repulsion Force
Aligned so that force at cell i from cell j points away from cell j
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Attraction Force
- unit vector pointing in the direction of smallest compression in stress tensor field T
- unit vector pointing in the direction of largest compression in stress tensor field T
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Attraction Force – cont.
Where χ is a parameter
between 0 to 1
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Meaning of χ
χ = 0: attraction occurs along line of largest stress
χ = 1: attraction occurs along line of smallest stress
0 < χ < 1: attraction between Merkel cells is generally toward each other, but biased along the lines of largest stress
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Values of Parameters
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General Cell Forces
Fa & Fr → 0 as r →∞
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Simulation Concerns Initially, only repelling forces are present
across the entire rectangular domain Attraction forces are incrementally added to
the simulation. First in areas with large compression stress (core of whorls, the outer limits of the domain) and working out towards areas with decreasing degrees of stress
Note: spring forces are added to the boundary to resist the movement of cells out of the domain.
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Simulation Concerns – cont. Number of cells in simulation: 105
Number of possible interactions: 1010
Rectangular domain is subdivided into rectangular boxes and interactions for cells in adjoining boxes are only used
Slow moving cells – those in areas where the pattern is already established – are updated every 10 steps
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Tensor Field Either derived from simulation (see Kucken &
Newell 2004, 2005) or from actual fingerprints The paper choose the latter Construct tensor field that will give the same
ridge direction & choose magnitudes so that the formation occurs in the correct order
Information about the direction of the ridges was extracted using the NBIS package from the NIST (see http://www.nist.gov/itl/iad/ig/nbis.cfm)
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Results – Constant Tensor Field
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Results – Constant Tensor Field
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Results – Constant Tensor Field
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Results – Constant Tensor Field
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Results - Whorl
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Results - Whorl
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Results - Whorl
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Results - Whorl
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Results
A shift in initial Merkel cell placement changes minutiae placement
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Results
A shift in a single Merkel cell results in different minutiae placement
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Small Displacements
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Results
Too many bifurcations compared to ridge endings—usually a 1:2 ratio
Too many minutiae surrounding deltas Occurrence of open fields (minutiae-less
spots) is too frequent Minutiae combinations (double
bifurcations) are too frequent
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Conclusions
There are other models, why this one?
Creates a pattern using Merkel cell alignment
Fits well with old literature
Builds on the theory that direction ridges are determined by stress fields, but the FRS arises from the Merkel cells
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Conclusions
What makes fingerprints unique?Geometry of volar padsTiming of ridge initiationBuildup of compression stressThe initial random configuration of
Merkel cells