The Happiness of Pursuit: What Neuroscience Can Teach Us About the Good Life (27 page)

BOOK: The Happiness of Pursuit: What Neuroscience Can Teach Us About the Good Life
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7
The discussion regarding “WHOSOEVER IS WISE?” is found in the Bavli Talmud (Mishna, Seder Kodashim, Masekhet Tamid 32:1).
8
The head-banging habits of MOLE RATS have been reported by Kimchi, Reshef, and Terkel (2005).
9
An informed, insightful, and engaging treatment of the EVOLVABIL-ITY OF FORESIGHT is offered by Daniel Dennett (2003a) in his book
Freedom Evolves
. For a review of the relationship between brains, innovation, and evolution in birds and primates, see, for instance, Lefebvre, Reader, and Sol (2004) and Lefebvre and Sol (2008).
10
The BAYESIAN approach to understanding the mind is the subject of numerous books (for example, Glymour 2001; Knill and Richards 1996) and scholarly articles (see Chater, Tenenbaum, and Yuille 2006; Tenenbaum and Griffiths 2001). Colin Howson and Peter Urbach (1991) explain why Bayesian reasoning is indispensable in science.
11
Let me stress again, as I did earlier, that to replicate precisely the mind generated by a particular brain one must reproduce the TRAJECTORY DYNAMICS of that brain’s states as they unfold over time (Chalmers 1994), including, crucially, the intrinsic categorical structure of the space of possible trajectories (Fekete and Edelman 2011). As the great American philosopher Charles Sanders Peirce (1868, p. 149) noted, “At no one instant in my state of mind is there cognition or representation, but in the relation of my states of mind at different instants there is.”
NOTES TO CHAPTER 3
 
1
Francis Crick’s (1994) quip, “You are nothing but a pack of neurons,” which is a paraphrase of an exclamation from
Alice’s Adventures in Wonderland
, has been updated recently to: “You are nothing but a pack of COMPUTATIONS” (Edelman 2008a, p. 500).
2
According to Philip K. Dick’s theory of LIFE ORIGINS, “eons ago, in the remote past, a bit of inanimate matter had become so irritated by something that it crawled away, moved by indignation” (Dick 1954/1993).
3
In processing PHEROMONE GRADIENTS, yeast cells perform close to the absolute physical limit of detection (Endres and Wingreen 2008).
4
The FIGHT SCENE is from Shakespeare’s
Romeo and Juliet
, act III, scene I.
5
The no. 1 tool, which reveals computation that is in the nature of things, makes you a bit like Neo in
The Matrix
, who can perceive the flowing numbers that make up reality. The no. 2 tool is akin to what Daniel Dennett (1987) calls the intentional stance in cognitive science. The no. 3 tool is related to Herbert Simon’s (1973) formulation of hierarchical abstraction as an explanatory move and to the multiple levels of analysis of information-processing systems introduced by David Marr and Tomaso Poggio (1977).
6
Some general DESIGN CONSIDERATIONS for cognitive systems can be found in Sloman (1989) and Sloman, Chrisley, and Scheutz (2005).
7
For an intriguing treatment of SUPER POWERS, see Saunders (2008).
8
Overcoming clinical depression, whose symptoms can include a persistent and general LACK OF MOTIVATION, may require professional help.
9
I follow Minsky (2006) in holding that “EMOTIONS are different Ways to Think” (cf. Sloman et al. 2005).
10
Our first encounter with Hume’s
A Treatise of Human Nature
(1740) was in the note on CAUSATION in Chapter 2 (note 5). The passage comparing the soul to a republic is in book I, part IV, section VI, paragraph 19.
11
My own favorite example of the importance of INFORMATION PROCESSING IN A WAR EFFORT, from the days before military intelligence was branded as a contradiction in terms, is the Bletchley Park operation. Bletchley Park is a country estate in Buckinghamshire, England, which during World War II housed the cryptanalysis section of the British military intelligence. If it were not for the daily successes of the code-breaking effort carried out at Bletchley Park by an illustrious team that included Alan Turing and I. J. Good, you would not be reading this note. The historical-causal chain in this case is exceptionally clear. Had the radio communications between the German submarine fleet in the Atlantic and its headquarters not been deciphered, the Allied fleet would have been unable to hunt down the submarines; the shipments of vital war supplies from the United States to Britain would have been disrupted; the Battle of Britain, which for many months hung in the balance, would have been won by Germany; the newly freed resources would have given the German army a critical boost on the eastern front; and my Russian-Jewish parents would not have survived the war, let alone met, fallen in love, and had a son with a predilection for historical digressions. Yet the present digression is not entirely gratuitous; for a connection between Bletchley Park and computational neuroscience, see Gold and Shadlen (2002).
12
Note that Jeremiah’s observation on FOOLISH PEOPLE (5:21) applies recursively to constituents of minds.
13
The discovery of STRUCTURE IN INFORMATION gathered by its senses is a developing mind’s first step toward learning the world (O’Regan and Noë 2001; Philipona et al. 2004).
14
One wonders whether Romeo might not have been better off in the long run by KILLING BENVOLIO instead of Tybalt.
15
The literature on FACE RECOGNITION is vast. Here are a few useful entry points into its main subdivisions: psychophysical (Diamond and Carey 1986; Moses, Ullman, and Edelman 1996; O’Toole, Edelman, and Bülthoff 1998), neural (Eifuku et al. 2004; Haxby et al. 2001; Rolls et al. 1989; Young and Yamane 1992), and computational (Edelman 1998; Edelman, Reisfeld, and Yeshurun 1992; Lando and Edelman 1995; O’Toole and Edelman 1996).
16
Individual neurons in sheep’s brains that are tuned to SHEEP FACES have been reported by Kendrick et al. (1996) and Kendrick and Baldwin (1987).
17
For an integrated treatment of the problem of OBJECT RECOGNITION, see Edelman (1999).
18
This VIRTUAL LINEUP method was implemented by Jungman, Levi, Aperman, and Edelman (1994).
19
In general, GRADED-SIMILARITY COMPUTATION works very well with neurons. The array of numbers that form a snapshot of a face (or of any other object) in a biological visual system is, very straightforwardly, a pattern of activity of some neurons (specifically, the activities of those neurons that respond to a face
are
the coordinates of the face-space point that represents it). This array of numbers can be represented collectively, in a very compact form, by another neuron, to which their outputs are fed. For each stimulus category, the brain only needs to store a few snapshots or exemplars; others can then be estimated by interpolation (Edelman 1999), which can be implemented as Bayesian regression (Bishop 2006)—the normative approach to learning from experience.
20
The actual lines are:
But, soft! what light through yonder window breaks?
It is the east, and Juliet is the sun. (act II, scene II, lines 2–3)
 
21
A discussion of ANALOGY AS THE CORE OF COGNITION can be found in Hofstadter (2001). For an application to vision, see Edelman and Duvdevani-Bar (1997).
22
For a computational analysis of the predicament of a mind that does not trust REALITY, see Edelman (2011b).
23
In vertebrates, a functional equivalent of the GRAND MAP is found in the superior colliculus, a midbrain structure (Merker 2007).
24
The concept of AFFORDANCES was introduced by J. J. Gibson (1979); discussed recently by Alva Noë (2004, p. 105), who wrote: “To perceive . . . is to perceive structure in sensorimotor contingencies”; and reviewed in Edelman (2006). Regarding basilisk lizards, see Glasheen and McMahon (1996).
25
Konrad Körding and Daniel Wolpert (2006) describe DYNAMIC SIMULATION in the context of Bayesian motor control.
26
Computational aspects of BEAUTY have been discussed in Edelman (2008a, ch. 5) and Schmidhuber (2008).
27
Empirical studies of SCENIC BEAUTY are rare (Daniel 1990). Recent work suggests that physical factors (such as complexity, openness, and water features) do a better job of accounting for judgments of scenic beauty than biome category. Still, Ke-Tsung Han (2007, p. 551) concludes: “It appears that no single current theory alone can sufficiently explain the causal processes responsible for any consistently favorable reaction to natural settings in general and to biomes in particular.”
28
Tolkien (1954), p. 54.
29
Morris (1971), p. 138.
30
As Robert A. Wilson (1981) expresses it in
Masks of the Illuminati
, “To the puer, all things are puella.” The influence of BODILY STATES such as thirst on perception has been documented, for example, by Melissa Ferguson and John Bargh (2004).
31
For an overview of NEUROECONOMICS, see Glimcher et al. (2008).
32
Shakespeare,
Romeo and Juliet
, act I, scene II.
33
The quote is from Tennyson’s poem
ULYSSES
(1842), line 51.
34
For a natural history of PARADISE, see Manuel and Manuel (1972). Björn Merker’s “Vehicles of Hope” (1993) offers a book-length treatment of related issues. The preponderance of belief in “heaven” (shared by three-quarters of the population of the United States) is reported by Greeley and Hout (1999). Interestingly, there seems to be no correlation between this belief and education or socioeconomic status (Flannelly et al. 2006).
35
For a science-fictional treatment of the possibility for a person to reach in and adjust his or her mind for PERMANENT CONTENTMENT with an ongoing activity, see Greg Egan’s
Permutation City
(1994). The resulting creature may be happy, but it is no longer human.
36
Gay Watson’s “Buddhism Meets Western Science” (in
Religion and the Brain
19, 2001 ) is an extremely brief introduction to the PSYCHOLOGY OF BUDDHISM. On a humanist reading, the Buddhist philosophy of mind, ethics, and enlightenment (Gier 2002, 2007; Gier and Kjellberg 2004; Siderits 2007) suggests that “awakening does not free one
from
the world; it frees one
for
the world” (Garfield and Priest 2009, p. 76).
37
The original quote reads:

m
m
∂cm

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