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Probabilistic models of the brain Perception and neural
function Rajesh P. N. Rao Digital Instant Download
Author(s): Rajesh P. N. Rao, Bruno A. Olshausen, Michael S. Lewicki
ISBN(s): 9780585437125, 0585437122
Edition: illustrated edition
File Details: PDF, 3.25 MB
Year: 2002
Language: english

Probabilistic Models of the Brain

Neural Information Processing Series
Michael I. Jordan and Sara A. Solla, editors
Advances in Large Margin Classiﬁers
Alexander J. Smola, Peter L. Bartlett, Bernhard Schölkopf,
and Dale Schuurmans, eds., 2000
Advanced Mean Field Methods: Theory and Practice
Manfred Opper and David Saad, eds., 2001
Probabilistic Models of the Brain: Perception and Neural Function
Rajesh P.N. Rao, Bruno A. Olshausen, and Michael S. Lewicki, eds., 2002

Probabilistic Models of the Brain:
Perception and Neural Function
Edited by
Rajesh P. N. Rao
Bruno A. Olshausen
Michael S. Lewicki
A Bradford Book
The MIT Press
Cambridge, Massachusetts
London, England

c 2002 Massachusetts Institute of Technology
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical
means (including photocopying, recording, or information storage and retrieval) without permission in
writing from the publisher.
Printed and bound in the United States of America
Library of Congress Cataloging-in-Publication Data
Probabilistic models of the brain: perception and neural function / edited by Rajesh P. N.
Rao, Bruno A. Olshausen, Michael S. Lewicki
p. cm. (Neural information processing series)
“A Bradford book.”
Includes bibliographical references and index.
ISBN 0-262-18224-6 (hc.: alk. paper)
1. Brain–Mathematical models. 2. Neurology–Statistical Methods. I. Rao, Rajesh P.
N. II. Olshausen, Bruno A. III. Lewicki, Michael S. IV. Series.
DNLM: 1.Brain Mapping–methods. 2. Models, Neurological. 3. Models, Statistical.
4. Neurons–physiology. 5. Visual Perception–physiology. WL 335 P9615 2002
QP376.P677 2002
612.8’2’011–dc21 2001042806

Contents
Preface ix
Introduction 1
Part I: Perception
1 Bayesian Modelling of Visual Perception 13
Pascal Mamassian, Michael Landy, and Laurence T. Maloney
2 Vision, Psychophysics and Bayes 37
Paul Schrater and Daniel Kersten
3 Visual Cue Integration for Depth Perception 61
Robert A. Jacobs
4 Velocity Likelihoods in Biological and Machine Vision 77
Yair Weiss and David J. Fleet
5 Learning Motion Analysis 97
William Freeman, John Haddon, and Egon Pasztor
6 Information Theoretic Approach to Neural Coding and Parameter
Estimation: A Perspective 117
Jean-Pierre Nadal
7 From Generic to Speciﬁc: An Information Theoretic Perspective
on the Value of High-Level Information 135
A.L. Yuille and James M. Coughlan
8 Sparse Correlation Kernel Reconstruction and Superresolution 155
Constantine P. Papageorgiou, Federico Girosi, and Tomaso Poggio
Part II: Neural Function
9 Natural Image Statistics for Cortical Orientation Map Development 181
Christian Piepenbrock

vi
10 Natural Image Statistics and Divisive Normalization 203
Martin J. Wainwright, Odelia Schwartz, and Eero P. Simoncelli
11 A Probabilistic Network Model of Population Responses 223
Richard S. Zemel and Jonathan Pillow
12 Efﬁcient Coding of Time-Varying Signals Using a Spiking Population
Code 243
Michael S. Lewicki
13 Sparse Codes and Spikes 257
Bruno A. Olshausen
14 Distributed Synchrony: A Probabilistic Model of Neural Signaling 273
Dana H. Ballard, Zuohua Zhang, and Rajesh P. N. Rao
15 Learning to Use Spike Timing in a Restricted Boltzmann Machine 285
Geoffrey E. Hinton and Andrew D. Brown
16 Predictive Coding, Cortical Feedback, and Spike-Timing Dependent
Plasticity 297
Rajesh P. N. Rao and Terrence J. Sejnowski
Contributors 317
Index 321

Series Foreword
The yearly Neural Information Processing Systems (NIPS) workshops bring together
scientists with broadly varying backgrounds in statistics, mathematics, computer sci-
ence, physics, electrical engineering, neuroscience and cognitive science, unified by
a common desire to develop novel computational and statistical strategies for infor-
mation processing, and to understand the mechanisms for information processing
in the brain. As opposed to conferences, these workshops maintain a flexible format
that both allows and encourages the presentation and discussion of work in progress,
and thus serve as an incubator for the development of important new ideas in this
rapidly evolving field.
The Series Editors, in consultation with workshop organizers and members of the
NIPS Foundation Board, select specific workshop topics on the basis of scientific ex-
cellence, intellectual breadth, and technical impact. Collections of papers chosen and
edited by the organizers of specific workshops are built around pedagogical intro-
ductory chapters, while research monographs provide comprehensive descriptions
of workshop-related topics, to create a series of books that provides a timely, author-
ative account of the latest developments in the exciting field of neural computation.
Michael I. Jordan, Sara A. Solla

7KLVSDJHLQWHQWLRQDOOOHIW blank

Preface
A considerable amount of data has been collected over the past several decades on
the cellular, physiological, and anatomical properties of the brain. However, with
the exception of a few notable early efforts, it is only in recent years that concerted
attempts have been made to link the distinctive properties of the brain to concrete
computational principles. In our view, an especially promising computational ap-
proach has been the use of probabilistic principles such as maximum likelihood and
Bayesian inference to derive efficient algorithms for learning and perception. Our
enthusiasm for this approach is based in part on some of its recent demonstrated
successes, for example:
The application of efficient coding algorithms to natural signals has been shown to
generate receptive field properties similar to those observed in the nervous system.
The instantiation of these algorithms in the form of ”analysis-synthesis” loops has
suggested functional models for the reciprocal feedforward-feedback connections
between cortical areas.
The theory of Bayesian belief propagation in probabilistic networks has yielded
robust models for perceptual inference and allowed for a functional interpretation of
several intriguing visual illusions and perceptual phenomena.
This book presents a representative sampling of some of the current probabilis-
tic approaches to understanding perception and brain function. The book originated
from a workshop on Statistical Theories of Cortical Function held in Breckenridge, Col-
orado, as part of the Neural Information Processing Systems (NIPS) conference in De-
cember, 1998. The goal of the workshop was to bring together researchers interested
in exploring the use of well-defined statistical principles in understanding cortical
structure and function. This book contains chapters written by many of the speak-
ers from the NIPS workshop, as well as invited contributions from other leading re-
searchers in the field. The topics include probabilistic and information theoretic mod-
els of perception, theories of neural coding and spike timing, computational models
of lateral and cortico-cortical feedback connections, and the development of receptive
field properties from natural signals.
While books with the words “brain” and “model” (or any of its cognates) in their
title abound, one of the attributes that we feel sets the present book apart from many
of its predecessors is its emphasis on the use of well-established probabilistic princi-
ples in interpreting data and constructing models. A second unique attribute is the

x Preface
attempt to present within a single volume both top-down computational models and
bottom-up neurally-motivated models of brain function. This allows the similarities
between these two types of approaches to be appreciated. To facilitate these connec-
tions, chapters containing related topics have been cross-referenced by the authors
as much as possible. The introductory chapter provides an overview of the field and
summarizes the contents of each chapter. A list of open problems and contentious
issues is included at the end of this chapter to encourage new researchers to join in
the effort and help infuse new ideas and techniques into the field.
We expect the book to be of interest to students and researchers in computational
and cognitive neuroscience, psychology, statistics, information theory, artificial intel-
ligence, and machine learning. Familiarity with elementary probability and statistics,
together with some knowledge of basic neurobiology and vision, should prove suffi-
cient in understanding much of the book.
We would like to thank Sara Solla, Michael Jordan, and Terry Sejnowski for their
encouragement, the reviewers of our book proposal for their comments, and the NIPS
workshops co-chairs for 1998, Rich Zemel and Sue Becker, for their help in organizing
the workshop that was the seed for this book. We are also grateful to Michael Rutter,
formerly of MIT Press, for his role in initiating the project, Bob Prior of MIT Press for
seeing the project through to its completion, and Sergio Lucero for his excellent work
in assembling the chapters in L
A
TEX.

Introduction
Each waking moment, our body’s sensory receptors convey a vast amount of infor-
mation about the surrounding environment to the brain. Visual information, for ex-
ample, is measured by about 10 million cones and 100 million rods in each eye, while
approximately 50 million receptors in the olfactory epithelium at the top of the nasal
cavity signal olfactory information. How does the brain transform this raw sensory
information into a form that is useful for goal-directed behavior? Neurophysiologi-
cal, neuroanatomical, and brain imaging studies in the past few decades have helped
to shed light on this question, revealing bits and pieces of the puzzle of how sensory
information is represented and processed by neurons at various stages within the
brain.
However, a fundamental question that is seldom addressed by these studies is why
the brain chose to use the types of representations it does, and what ecological or
evolutionary advantage these representations confer upon the animal. It is difficult
to address such questions directly via animal experiments. A promising alternative
is to investigate computational models based on efficient coding principles. Such
models take into account the statistical properties of environmental signals, and
attempt to explain the types of representations found in the brain in terms of a
probabilistic model of these signals. Recently, these models have been shown to be
capable of accounting for the response properties of neurons at early stages of the
visual and auditory pathway, providing for the first time a unifying view of sensory
coding across different modalities. There is now growing optimism that probabilistic
models can also be applied successfully to account for the sensory coding strategies
employed in yet other modalities, and eventually to planning and executing goal-
directed actions.
This book surveys some of the current themes, ideas, and techniques dominat-
ing the probabilistic approach to modeling and understanding brain function. The
sixteen chapters that comprise the book demonstrate how ideas from probability
and statistics can be used to interpret a variety of phenomena, ranging from psy-
chophysics to neurophysiology. While most of the examples presented in the chap-
ters focus on vision, this is not meant to imply that these models are applicable only
to this modality. Many of the models and techniques presented in these chapters are
quite general, and therefore are applicable to other modalities as well.

2 Introduction
The probabilistic approach
The probabilistic approach to perception and brain function has its roots in the ad-
vent of information theory, which inspired many psychologists during the 1950’s to
attempt to quantify human perceptual and cognitive abilities using statistical tech-
niques. One of these was Attneave, who attempted to point out the link between the
redundancy inherent in images and certain aspects of visual perception [2]. Barlow
then took this notion a step further, by proposing a self-organizing strategy for sen-
sory nervous systems based on the principle of redundancy reduction [3, 4]—i.e., the
idea that neurons should encode information in such a way as to minimize statistical
dependencies. The alluring aspect of this approach is that it does not require that one
pre-suppose a specific goal for sensory processing, such as “edge-detection” or “con-
tour extraction.” Rather, the emphasis is on formulating a general goal for sensory
processing from which specific coding strategies such as edge detection or contour
integration could be derived.
Despite the elegance of Attneave’s and Barlow’s proposals, their ideas would not
be put seriously to work until much later. 1 Most modeling work in sensory physi-
ology and psychophysics over the past 40 years has instead been dominated by the
practice of attributing specific coding strategies to certain neurons in the brain. This
approach is probably best exemplified by Marr and Hildreth’s classic theory of edge-
detection [11], or the plethora of Gabor-filter based models of visual cortical neurons
that followed [10, 6, 8]. It is also prevalent in the realms of intermediate and high
level vision, for example in schemes such as codons [14], geons [5], and the medial
axis transform [13] for representing object shape. In contrast to the probabilistic ap-
proach, the goal from the outset in such models is to formulate a specific compu-
tational strategy for extracting a set of desired properties from images. Nowhere is
there any form of learning or adaptation to the properties of images. Instead, these
models draw upon informal observations of image structure and they rely heavily
upon mathematical elegance and sophistication to achieve their goal.
Interest in the probabilistic approach was revived in the 1980s, when Simon Laugh-
lin and M.V. Srinivasan began measuring the forms of redundancy present in the nat-
ural visual environment and used this knowledge to make quantitative predictions
about the response properties of neurons in early stages of the visual system [9, 15].
This was followed several years later by the work of Field [7], showing that natu-
ral images exhibit a characteristic power spectrum, and that cortical neurons
are well-adapted for representing natural images in terms of a sparse code (where a
small number of neurons out of the population are active at any given time). Then
drawing upon information theory, as well as considerations of noise and the
power spectrum, Atick [1] and van Hateren [16] formulated efficient coding theories
for the retina in terms of whitening of the power spectrum (hence removing correla-
1. There were some early attempts at implementing these principles in self-organizing net-
works (e.g. [12]), but these fell short of being serious neurobiological models.

Introduction 3
tions from signals sent down the optic nerve) in space and time. This body of work,
accumulated throughout the 1980’s and early 1990’s, began to build a convincing
case that probabilistic models could contribute to our understanding of sensory cod-
ing strategies. Part II of this book contains eight recent contributions to this area of
inquiry.
The probabilistic approach has also been applied beyond the realm of sensory cod-
ing, to problems of perception. In fact, the idea that perception is fundamentally a
problem of inference goes back at least to Hermann von Helmholtz in the nineteenth
century. The main problem of perception is to deduce from the patterns of sensory
stimuli the properties of the external environment. What makes this problem espe-
cially difficult is that there is ambiguity at every stage, resulting from lack of informa-
tion, inherent noise, and the multitude of perceptual interpretations that are consis-
tent with the available sensory data. Even something as simple as the interpretation
of an edge can be complicated: Is it due to a reflectance change on the object? Is it a
shadow that arises from the object’s 3-dimensional structure? Or does it represent an
object boundary? Determining which interpretation is most likely depends on inte-
grating information from the surrounding context and from higher level knowledge
about typical scene structure.
The process of inference is perhaps most compellingly demonstrated by the famous
Dalmatian dog scene (reproduced in Figure 7.1), in which the luminance edges pro-
vide little or no explicit information about the object boundaries. Like a perceptual
puzzle, each part of the image provides clues to the best interpretation of the whole.
The question is how to combine these different sources of information in the face of
a considerable degree of uncertainty. One framework for addressing these problems
in the context of perceptual processing is that of Bayesian Inference (Szeliski, 1989;
Knill and Richards, 1996).
What makes Bayesian inference attractive for modeling perception is that it pro-
vides a general framework for quantifying uncertainty and precisely relating what
one set of information tells us about another. In Bayesian probability theory, uncer-
tainty is represented by probability distribution functions, and Bayes’ rule specifies
the relation between the distributions (and therefore the uncertainties) and the ob-
served data. A discrete distribution might represent uncertainty among a set of dis-
tinct possible interpretations, such as the probability of a word given a sound. A
continuous distribution represents uncertainty of an analog quantity, such as the di-
rection of motion given a time-varying image. By quantitatively characterizing these
distributions for a given perceptual task, it is then possible to make testable predic-
tions about human behavior. As we shall see in the chapters of Part I of this book,
there is now substantial evidence showing that humans are good Bayesian observers.
Contributions of this book
The chapters in this book fall naturally into two categories, based on the type of ap-
proach taken to understand brain function. The first approach is to formulate proba-

4 Introduction
bilistic theories with a predominantly top-down point of view—i.e., with an emphasis
on computational algorithms rather than the details of the underlying neural ma-
chinery. The goal here is to explain certain perceptual phenomena or analyze com-
putational tractability or performance. This has been the predominant approach in
the psychology, cognitive science, and artificial intelligence communities. Part I of
the book, entitled Perception, comprises eight chapters that embody the top-down
approach to constructing probabilistic theories of the brain.
The second approach is the formulate theories of brain function that are moti-
vated by understanding neural substrates and mechanisms. The goal of such the-
ories is twofold: (a) to show how the distinctive properties of neurons and their
specific anatomical connections can implement concrete statistical principles such as
Bayesian inference, and (b) to show how such models can solve interesting problems
such as feature and motion detection. Part II of this book, entitled Neural Function,
presents eight such models.
The first three chapters of Part I present an introduction to modeling visual percep-
tion using the Bayesian framework. Chapter 1 by Mamassian, Landy, and Maloney
serves as an excellent tutorial on Bayesian inference. They review the three basic
components of any Bayesian model: the likelihood function, the prior, and the gain
function. Likelihood functions are used to model how visual sensors encode sen-
sory information, while priors provide a principled way of formulating constraints
on possible scenes to allow unambiguous visual perception. Gain functions are used
to account for task-dependent performance. Mamassian, Landy, and Maloney illus-
trate how Bayesian models can be investigated experimentally, drawing upon a psy-
chophysical task in which the observer is asked to judge 3D surface structure. They
show how the assumptions and biases used by the observer in inferring 3D structure
from images may be modeled in terms of priors. More importantly, their work pro-
vides a compelling demonstration of the utility of the Bayesian approach in designing
and interpreting the results of psychophysical experiments.
This approach is carried further in Chapter 2 by Schrater and Kersten, who ex-
plore the Bayesian approach as a framework within which to develop and test pre-
dictive quantitative theories of human visual behavior. Within this framework, they
distinguish between mechanistic and functional levels in the modeling of human
vision. At the mechanistic level, traditional signal detection theory provides a tool
for inferring the properties of neural mechanisms from psychophysical data. At the
functional level, signal detection theory is essentially extended to pattern inference
theory, where the emphasis is on natural tasks and generative models for images and
scene structure. Drawing upon examples in the domain of motion processing and
color constancy, Schrater and Kersten show how ideal observers can be used to test
theories at both mechanistic and functional levels.
Jacobs then uses the Bayesian approach in Chapter 3 to explore the question
of how observers integrate various visual cues for depth perception. Again, the
emphasis is on evaluating whether or not observers’ cue integration strategies can
be characterized as “optimal” in terms of Bayesian inference, in this case by using an

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The Project Gutenberg eBook of Webster—
Man's Man

This ebook is for the use of anyone anywhere in the United States
and most other parts of the world at no cost and with almost no
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you are located before using this eBook.
Title: Webster—Man's Man
Author: Peter B. Kyne
Illustrator: Dean Cornwell
Release date: May 3, 2016 [eBook #51987]
Most recently updated: October 23, 2024
Language: English
Credits: Produced by David Widger from page images generously
provided by the Internet Archive
*** START OF THE PROJECT GUTENBERG EBOOK WEBSTER—
MAN'S MAN ***

By Peter B. Kyne
Author Of “Cappy Ricks” “The Three Godfathers,” Etc.
Illustrated By Dean Cornwell
New York
Doubleday, Page Company
1917

CONTENTS
WEBSTER—MAN'S MAN
CHAPTER I
CHAPTER II

CHAPTER III
CHAPTER IV
CHAPTER V
CHAPTER VI
CHAPTER VII
CHAPTER VIII
CHAPTER IX
CHAPTER X
CHAPTER XI
CHAPTER XII
CHAPTER XIII
CHAPTER XIV
CHAPTER XV
CHAPTER XVI
CHAPTER XVII
CHAPTER XVIII
CHAPTER XIX
CHAPTER XX
CHAPTER XXI
CHAPTER XXII
CHAPTER XXIII
CHAPTER XXIV

CHAPTER XXV
CHAPTER XXVI
CHAPTER XXVII
CHAPTER XXVIII
CHAPTER XXIX
CHAPTER XXX
WEBSTER—MAN'S MAN

W
CHAPTER I
HEN John Stuart Webster, mining engineer and kicker-up-
of-dust on distant trails, flagged the S. P., L. A. S. L.
Limited at a blistered board station in Death Valley,
California, he had definitely resolved to do certain things. To begin,
he would invade the dining car at the first call to dinner and order
approximately twenty dollars' worth of ham and eggs, which
provender is, as all who know will certify, the pinnacle of epicurean
delight to an old sour-dough coming out of the wilderness with a
healthy bankroll and a healthier appetite; for even as the
hydrophobic dog avoids water, so does the adventurer of the
Webster type avoid the weird concoctions of high-priced French
chefs until he has first satisfied that void which yawns to receive
ham and eggs.
Following the ham and eggs, Mr. Webster planned to saturate
himself from soul to vermiform appendix with nicotine, which he
purposed obtaining from tobacco with nicotine in it. It was a week
since he had smoked anything, and months since he had tasted
anything with an odour even remotely like tobacco, for the August
temperature in Death Valley is no respecter of moisture in any man
or his tobacco. By reason of the fact that he had not always dwelt in
Death Valley, however, John Stuart Webster knew the dining-car
steward would have in the ice chest some wonderful cigars,
wonderfully preserved.
Webster realized that, having sampled civilization thus far, his
debauch would be at an end until he reached Salt Lake City-unless,
indeed, he should find aboard the train something fit to read or
somebody worth talking to. Upon arrival in Salt Lake City, however,
his spree would really begin. Immediately upon leaving the train he
would proceed to a clothing shop and purchase a twenty-five-dollar
ready-to-wear suit, together with the appurtenances thereunto

pertaining or in any wise belonging. These habiliments he would
wear just long enough to shop in respectably and without attracting
the attention of the passing throng; and when later his “tailor-
mades” and sundry other finery should be delivered, he would send
the store clothes to one Ubehebe Henry, a prospector down in the
Mojave country, who would appreciate them and wear them when
he came to town in the fall to get drunk.
Having arranged for the delivery of his temporary attire at the best
hotel in town, Webster designed chartering a taxicab and proceeding
forthwith to that hotel, where he would engage a sunny room with a
bath, fill the bathtub, climb blithely in and soak for two hours at
least, for it was nearly eight months since he had had a regular bath
and he purposed making the most of his opportunity. His long-drawn
ablutions at length over, he would don a silken dressing gown and
slippers, order up a barber, and proceed to part with enough hair
and whiskers to upholster an automobile; and upon the completion
of his tonsorial adventures he would encase his person in a suit of
mauve-coloured silk pajamas, climb into bed and stay there for forty-
eight hours, merely waking long enough to take another bath, order
up periodical consignments of ham and eggs and, incidentally, make
certain that a friendly side-winder or chuck-walla hadn't crawled
under the blankets with him.
So much for John Stuart Webster's plans. Now for the gentleman
himself. No one—not even the Pullman porter, shrewd judge of
mankind that he was—could have discerned in the chrysalis that
flagged the Limited the butterfly of fashion that was to be. As the
ebony George raised the vestibule platform, opened the car door
and looked out, he had no confidence in the lean, sun-baked big
man standing by the train. Plainly the fellow was not a first-class
passenger but a wandering prospector, for he was dog-dirty, a ruin
of rags and hairy as a tarantula. The only clean thing about him was
a heavy-calibred automatic pistol of the army type, swinging at his
hip.
“Day coach an' tourist up in front,” the knight of the whiskbroom
announced in disapproving tones and started to close down the

platform.
“So I perceived,” John Stuart Webster replied blandly. “I also
observed that you failed to employ the title sir when addressing a
white man. Put that platform back and hop out here with your little
stool, you saddle-coloured son of Senegambia, or I'll make you a
hard porter to catch.”
“Yassah, yassah!” the porter sputtered, and obeyed instantly. Mr.
Webster handed him a disreputable-looking suitcase and stepped
aboard in state, only to be informed by the sleeping-car conductor
that there wasn't a vacant first-class berth on the train.
“Yes, I know I'm dirty,” the late arrival announced cheerfully, “but
still, as Bobby Burns once remarked, 'a man's a man for a' that'—and
I'm not unsanitary. I sloshed around some in Furnace Creek the
night before last, and while of course I got the top layer off, still, a
fellow can't accomplish a great deal without hot water, soap, a good
scrubbing-brush and a can of lye.”
“I'm very sorry,” the conductor replied perfunctorily and
endeavoured to pass on, but Webster secured a firm grip on his
lapel and frustrated the escape.
“You're not sorry,” the ragged wanderer declared, “not one little
bit. You're only apprehensive. However, you needn't be. There is no
wild life on me, brother, I assure you. If you can prove it, I'll give
you a thousand-dollar bill for each and every bit of testimony you
can adduce.”
“But I tell you, the train is full up. You'll have to roost in the
daycoach or the tourist. I'm very sorry——”
“So am I, for I know what daycoaches and tourist-cars smell like
in the middle of August, because, as the poet says, I've been there
many a time and oft.' Nevertheless, despite your deep grief,
something tells me you're spoofing, so while I must, of necessity,
accept your suggestion, said acceptance will be but temporary. In
about two hours, young fellow, you're going to make the alarming
discovery that you have bats in your belfry.” And with a whiskery grin

which, under the circumstances, was charming in its absolute
freedom from malice, Mr. Webster departed for the daycoach.
Two hours later the conductor found him in the aforementioned
daycoach, engaged in a mild game of poker with a mule-skinner, a
Chinaman, an aged prospector, and a half-breed Indian, and waited
until Mr. Webster, on a bob-tailed club flush, bluffed the Chinaman
out of a dollar-and-a-half pot.
“Maud, Lily, and Kate!” Webster murmured, as the Celestial laid
down three queens and watched his ragged opponent rake in the
pot. “Had I held those three queens and had you made a two-card
draw as I did, only death could have stopped me from seeing what
you held! Hello! Here's Little Boy Blue again. All right, son. Blow your
horn.”
“Are you Mr. John S. Webster?”
“Your assumption that I am that person is so eminently correct
that it would be a waste of time for me to dispute it,” Webster
replied quizzically. “However, just to prove that you're not the only
clairvoyant on this train, I'm going to tell you something about
yourself. In your pocket you have a telegram; it is from Chicago,
where your pay-check originates; it is a short, sweet, and
comprehensive, containing an order which you are going to obey. It
reads somewhat as follows:
“'My friend, John S. Webster, wires me from Blank that he boarded
train at Blank and was refused first-class accommodation because he
looked like a hobo. Give him the best you have in stock, if you have
to throw somebody off the train to accommodate him. Unless you
see your way clear to heed this suggestion your resignation is not
only in order but has already been accepted.' Signed, 'Sweeney.'
“Do I hit the target?”
The conductor nodded. “You win, Mr. Webster,” he admitted.
“Occasionally I lose, old-timer. Well?”
“Who the devil is Sweeney?”

John Stuart Webster turned to his cosmopolitan comrades of the
national game. “Listen to him,” he entreated them. “He has worked
for the company, lo, these many years, and he doesn't know who
Sweeney is?” He eyed the conductor severely. “Sweeney,” he
declared, “is the man who is responsible for the whichness of the
why-for. Ignorance of the man higher up excuses no sleeping-car
conductor, and if your job is gone when you reach Salt Lake, old-
timer, don't blame it on me, but rather on your distressing propensity
to ask foolish questions. Vamos, amigo, and leave me to my despair.
Can't you see I'm happy here?”
“No offense, Mr. Webster, no offense. I can let you have a
stateroom——”
“That's trading talk. I'll take it.”
The conductor gave him his receipt and led him back to the
stateroom in the observation-car. At the door Webster handed him a
five-dollar bill. “For you, son,” he said gently, “just to take the sting
out of what I'm about to tell you. Now that I possess your receipt
and know that ten men and a boy cannot take it away from me, I'm
going to tell you who Sweeney is.”
“Who is he?” the conductor queried. Already he suspected he had
been outgeneralled.
“Sweeney,” said Mr. Webster, “is the chief clerk in one of Chicago's
most pretentious hotels and a young man who can find all the
angles of a situation without working it out in logarithms. I wired
him the details of my predicament; he heard the Macedonian cry
and kicked in. Neat, is it not?”
The conductor grinned. “I hate to take your money,” he declared.
“Don't. Just at present I'm very flush. Yes, sir, I'm as prosperous
as a yearling burro up to his ears in alfalfa, and the only use I have
ever found for money is to make other people happy with it, thereby
getting some enjoyment out of it myself. Just as soon as I get a little
chunk together, some smarter man than I takes it all away from me
again—so the cleaning process might just as well start here. When
I'm broke I'll make some more.”

“How?”
“By remembering that all a man needs in this world, in order to
excel, is about two per cent, more courage than a jack-rabbit; also
that an ounce of promotion in a world of boobs is worth a ton of
perspiration. Thank you for falling for my bluff.”
And having wotted the which, Mr. Webster retired to his hard-won
sanctuary, where he removed as much alkali and perspiration as he
could, carded his long hair and whiskers, manicured his finger nails
with a jack-knife, changed his shirt, provided five minutes of industry
for George, with his whiskbroom and brush, and set himself patiently
to await the first call to dinner.
The better to hear the dinner call Webster left his stateroom door
open, and presently a pink-jowled, well-curried, flashily dressed big
man, of about Webster's age, passed in the corridor, going toward
the head of the train. An instant later a woman's voice said very
distinctly:
“I do not know you, sir; I do not wish to know you, and it is
loathsome of you to persist in addressing me. If you do not stop
your annoying attentions, I shall call the conductor.”
“Ah! Beauty in distress,” John Stuart Webster soliloquized. “I look
so much like an Angora goat I might as well butt in.” He stepped to
the door of his stateroom. A girl stood in the vestibule, confronting
the man who had just passed Webster's door. Webster bowed.
“Madame, or mademoiselle, as the case may be,” he said, “unlike
this other male biped, my sole purpose in presuming to address you
is to suggest that there is not the slightest necessity for taking this
matter up with the conductor. I am here and very much at your
service.”
The girl turned—and John Stuart Webster's heart flopped twice in
rapid succession, like a trout newly grassed. She was as lovely as a
royal flush. Her starry glance began at his miner's boots, travelled up
his old, soiled, whipcord trousers, over his light blue chambray shirt
and found the man behind the whiskers. She favoured him with a
quick, curious scrutiny and a grave, sweet smile. “Thank you so

much, sir,” she answered, and passed down the corridor to the
observation-car.
“Well, old-timer,” Webster greeted the fellow who had been
annoying her, “how about you? What do you think we ought to do
about this little affair?”
“The sensible thing would be to do—nothing.”
“Nothing?”
“Nothing.”
“Why?”
“You might start something you couldn't finish.”
“That's a dare,” Webster declared brightly, “and wasn't it the
immortal Huckleberry Finn who remarked that anybody that'd take a
dare would suck eggs and steal sheep?” He caressed his beard
meditatively. “They say the good Lord made man to His own image
and likeness. I take it those were only the specifications for the
building complete—the painting and interior decorating, not to
mention the furnishings, being let to a sub-contractor.” He was silent
a few seconds, appraising his man. “I suppose you commenced
operations by moving into her section and asking if she would like to
have the window open and enjoy the fresh air. Of course if she had
wanted the window open, she would have called the porter. She
rebuffed you, but being a persistent devil, you followed her into the
observation-car, and in all probability you ogled her at luncheon and
ruined her appetite. And just now, when you met her in this
vestibule, you doubtless jostled her, begged her pardon and without
waiting to be introduced asked her to have dinner with you this
evening.”
“Well?” the fellow echoed belligerently.
“It's all bad form. You shouldn't try to make a mash on a lady. I
don't know who she is, of course, but she's not common; she's
travelling without a chaperon, I take it, and for the sake of the
mother that bore me I always respect and protect a good woman
and whale hell out of those that do not.”

He reached inside his stateroom and pressed the bell. The porter
arrived on the run.
“George,” said Mr. Webster, “in a few minutes we're due at
Smithville. If my memory serves me aright, we stop five minutes for
water and orders.”
“Yassah.”
“Remain right here and let me off as soon as the train comes to a
stop.”
When the train slid to a grinding halt and the porter opened the
car door, Webster pointed.
“Out!” he said. “This is no nice place to pull off a scrap.”
“See here, neighbour, I don't want to have any trouble with you
——”
“I know it. All the same, you're going to have it—or come with me
to that young lady and beg her pardon.”
There are some things in this world which the most craven of men
will not do—and the vanity of that masher forbade acceptance of
Webster's alternative. He preferred to fight, but—he did not purpose
being thrashed. He resolved on strategy.
“All right. I'll apologize,” he declared, and started forward as if to
pass Webster in the vestibule, on his way to the observation-car,
whither the subject of his annoying attentions had gone. Two steps
brought him within striking distance of his enemy, and before
Webster could dodge, a sizzling righthanded blow landed on his jaw
and set him back on his haunches in the vestibule.
It was almost a knockout—almost, but not quite. As Webster's
body struck the floor the big automatic came out of the holster;
swinging in a weak circle, it covered the other.
“That was a daisy,” Webster mumbled. “If you move before my
head clears, I'll put four bullets into you before you reach the
corridor.”
He waited about a minute; then with the gun he pointed to the
car door, and the masher stepped out. Webster handed the porter

his gun and followed; two minutes later he returned, dragging his
assailant by the collar. Up the steps he jerked the big battered hulk
and tossed it in the corner of the vestibule, just as the girl came
through the car, making for the diner up ahead.
Again she favoured him with that calm, grave, yet vitally
interested gaze, nodded appreciatively, made as if to pass on,
changed her mind, and said very gravely: “You are—a very courtly
gentleman, sir.”
He bowed. There was nothing else to do, nothing that he could
say, under the circumstances; to use his chivalry as a wedge to open
an acquaintance never occurred to him—but his whiskers did occur
to him. Hastily he backed into his stateroom and closed the door;
presently he rose and surveyed himself critically in the small mirror
over the washstand.
“No, Johnny,” he murmured, “we can't go into the diner now.
We're too blamed disreputable. We were bad enough before that big
swine hung the shanty on our right eye, but whatever our physical
and personal feelings, far be it from us to parade our iridescent orb
in public. Besides, one look at that queen is enough to do us for the
remainder of our natural life, and a second look, minus a proper
introduction, would only drive us into a suicide's grave. That's a fair
sample of our luck, Johnny. It rains duck soup—and we're there like
a Chinaman—with chopsticks; and on the only day in the history of
the human race, here I am with a marvellous black eye, a dislocated
thumb, four skinned knuckles, and a grouch, while otherwise looking
like a cross between Rip Van Winkle and a hired man.” He sighed,
rang for the porter and told him to send a waiter for his order, since
he would fain break his fast in the privacy of his stateroom. And
when the waiter came for the order, such was Mr. Webster's mental
perturbation that ham and eggs were furthest from his thoughts. He
ordered a steak with French fried potatoes.

J
CHAPTER II
OHN STUART WEBSTER passed a restless night. Sleep came to
him in hourly installments, from which he would rouse to ask
himself whether it was worth while to continue to go through
the motions of living, or alight at the next station, seek a lonely and
unfrequented spot and there surrender to outrageous fortune. He
had lived every moment of his life; fair fortune and ill had been his
portion so often that he had long since ceased to care which took
precedence over the other; to quote Mr. Kipling, he had schooled
himself to “treat those two impostors both the same”—not a very
difficult task, if one be granted a breathing spell between the arrival
of each impostor! Hitherto, in Webster's experience, there had
always been a decent interval between the two—say a day, a week,
a month or more; whereas in the present instance, two minutes had
sufficed to make the journey from a heaven of contentment to the
dungeons of despair.
It was altogether damnable. In a careless moment, Fate had
accorded him a glimpse of the only woman he had ever met and
desired to meet again—for Webster was essentially a man's man,
and his profession and environment had militated against his
opportunities for meeting extraordinary women; and extraordinary
women were the only kind that could hope to challenge his serious
attention. Had his luck changed there, he might have rested content
with his lot—but it hadn't. Fate had gone farther. She had accorded
him a signal opportunity for knightly combat in the service of this
extraordinary woman; and in the absence of a formal introduction,
what man could desire a finer opportunity for getting acquainted! If
only their meeting had but been delayed two weeks, ten days, a
week! Once free of his ugly cocoon of rags and whiskers, the
butterfly Webster would not have hesitated one brief instant to
inform himself of that young lady's name and address, following his

summary disposal of her tormentor. Trusting to the mingled respect
and confusion in his manner, and to her own womanly intuition to
warn her that no rudeness or brazen familiarity was intended, he
would have presented himself before her and addressed her in these
words:
“A few minutes ago, Miss, you were gracious enough to accord me
the rare pleasure of being of slight service to you. May I presume on
that evidence of your generosity and perfect understanding to risk a
seeming impertinence by presuming to address you?”
Webster pictured her as bowing, favouring him with that grave yet
interested scrutiny and saying: “Certainly, sir.” Whereupon he would
say:
“It has occurred to me—for, like Bimi, the orangoutang, I have
perhaps too much ego in my cosmos—that you might be charitably
moved to admit me to the happy circle of those privileged to call you
by name. Were there a mutual friend on this train whom I could
prevail upon to introduce me formally, I should not be reduced to
the necessity of being unconventional. Under the circumstances,
however, I am daring enough to presume that this misfortune is not
so great that I should permit it to interfere with my respectful
desires. Therefore—have I your permission to present myself, with
the hope that in so doing I may feel freer to be of additional service
to you throughout the remainder of our journey?”
That would be a pretty, a graceful speech—a little ornate,
doubtless, but diplomatic in the extreme. Having been accorded
permission to introduce himself, he would cease thereafter to be
flowery. However, Webster realized that however graceful might be
his speech and bearing, should he essay the great adventure in the
morning, his appearance would render him ridiculous and
presumptuous and perhaps shock and humiliate her; for in all things
there is a limit, and John Stuart Webster's right eye constituted a
deadline beyond which, as a gentleman, he dared not venture; so
with a heavy heart he bowed to the inevitable. Brilliant and
mysterious as a meteorite she had flashed once across his horizon
and was gone.

In the privacy of his stateroom Webster had ham and eggs for
breakfast. He was lighting his second cigar when the porter knocked
and entered with an envelope.
“Lady in the observation-car asked me to deliver this to you, sah,”
he announced importantly.
It 'was a note, freshly written on the train stationery. Webster
read:
The distressed lady desires to thank the gentleman in stateroom A
for his chivalry of yesterday. She quite realizes that the gentleman's
offer to relieve her of the annoyance to which she was being
subjected was such a direct expression of his nature and code, that
to have declined his aid would have been discourteous, despite her
distress at the possible outcome. She is delighted to know that her
confidence in the ability of her champion has been fully justified by a
swift and sweeping victory, but profoundly sorry that in her service
the gentleman in stateroom A was so unfortunate as to acquire a red
eye with blue trimmings.
John Stuart Webster swore his mightiest oath, “By the twelve
apostles, Simon Peter, Andrew, James, John, Philip, Bartholomew,
Matthew, Thomas, James, Jude, and Simon, not omitting Judas
Iscariot, the scaly scoundrel who betrayed his Lord and Master!” He
searched through an old wallet until he discovered a fairly clean
professional card, across the bottom of which he wrote, “Thank you.
J. S.W.” and sent it to the no-longer-distressed lady.
“The most signal adventure of my life is now over,” he soliloquized
and turned to his cigar. “For the sake of my self-respect, I had to let
her know I'm not a hobo! And now to the task of framing up a
scheme for future acquaintance. I must learn her name and
destination; so as a preliminary I'll interview the train conductor.”
He did, and under the ameliorating influence of a five-dollar bill
the conductor bent a respectful ear to the Websterian message.
“In Car Seven,” he began, “there is a young lady. I do not know
what section she occupies; neither do I know her name and
destination. I only know what she looks like.”

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