organization of motivational–emotional systems 67 Aigner, T. G., & Balster, R. L. (1978). Choice behavior in rhesus monkeys: Cocaine versus food. Science, 201, 534–535. Bainton, R. J., Tsai, L. T., Singh, C. M., Moore, M. S., Neckameyer, W. S., & Heberlein, U. (2000). Dopamine modulates acute responses to cocaine, nicotine and ethanol in Drosophila. Current Biology, 10, 187–194. Baldwin, A. E., Sadeghian, K., & Kelley, A. E. (2002). Appetitive instrumental learning requires coincident activation of NMDA and dopamine D 1 receptors within <strong>the</strong> medial prefrontal cortex. Journal of Neuroscience, 22, 1063–1071. Bassareo, V., & Di Chiara, G. (1999). Modulation of feeding-induced activation of mesolimbic dopamine transmission by appetitive stimuli and its relation to motivational state. European Journal of Neuroscience, 11, 4389–4397. Becker, J. B., Rudick, C. N., & Jenkins, W. J. (2001). <strong>The</strong> role of dopamine in <strong>the</strong> nucleus accumbens and striatum during sexual behavior in <strong>the</strong> female rat. Journal of Neuroscience, 21, 3236–3241. Berridge, K. C. (2001). Reward learning. In <strong>The</strong> psychology of learning and motivation (pp. 223–277). New York: Academic Press. Berridge, K. C., & Robinson, T. E. (1998). What is <strong>the</strong> role of dopamine in reward: Hedonic impact, reward learning, or incentive salience? <strong>Brain</strong> Research Reviews, 28, 309–369. Bindra, D. (1978). How adaptive behavior is produced: A perceptual–motivational alternative to response-reinforcement. Behavioral and <strong>Brain</strong> Sciences, 1, 41– 91. Blackburn, J. R., Phillips, A. G., Jakubovic, A., & Fibiger, H. C. (1989). Dopamine and preparatory behavior: II. A neurochemical analysis. Behavioral Neuroscience, 103, 15–23. Blair, H. T., Cho, J., & Sharp, P. E. (1998). Role of <strong>the</strong> lateral mammillary nucleus in <strong>the</strong> rat head direction circuit: A combined single unit recording and lesion study. Neuron, 21, 1387–1397. Blenau, W., & Baumann, A. (2001). Molecular and pharmacological properties of insect biogenic amine receptors: Lessons from Drosophila melanogaster and Apis mellifera. Archives of Insect Biochemistry and Physiology, 48, 13–38. Bolles, R. C. (1972). Reinforcement, expectancy and learning. Psychological Review, 79, 394–409. Bolles, R. C., & Fanselow, M. S. (1980). A perceptual–defensive–recuperative model of fear and pain. Behavioral and <strong>Brain</strong> Sciences, 3, 291–301. Bolles, R. C., & Fanselow, M. S. (1982). Endorphins and behavior. Annual Review of Psychology, 33, 87–101. Brembs, B., Lorenzetti, F. D., Reyes, F. D., Baxter, D. A., & Byrne, J. H. (2002). Operant reward learning in Aplysia: Neuronal correlates and mechanisms. Science, 296, 1706–1709. Buck, R. (1999). <strong>The</strong> biological affects: A typology. Psychological Review, 106, 301– 336. Cardinal, R. N., Parkinson, J. A., Hall, J., & Everitt, B. J. (2002). Emotion and motivation: <strong>The</strong> role of <strong>the</strong> amygdala, ventral striatum, and prefrontal cortex. Neuroscience and Biobehavioral Reviews, 26, 321–352.
68 brains Cardinaud, B., Gilbert, J. M., Liu, F., Sugamori, K. S., Vincent, J. D., Niznik, H. B., & Vernier, P. (1998). Evolution and origin of <strong>the</strong> diversity of dopamine receptors in vertebrates. Advances in Pharmacology, 42, 936–940. Changeux, J. P., Bertrand, D., Corringer, P. J., Dehaene, S., Edelstein, S., Lena, C., Le Novere, N., Marubio, L., Picciotto, M., & Zoli, M. (1998). <strong>Brain</strong> nicotinic receptors: Structure and regulation, role in learning and reinforcement. <strong>Brain</strong> Research Reviews, 26, 198–216. Childress, A. R., Mozley, P. D., McElgin, W., Fitzgerald, J., Reivich, M., & O’Brien, C. P. (1999). Limbic activation during cue-induced cocaine craving. American Journal of Psychiatry, 156, 11–18. Coccaro, E. F., Siever, L. J., Klar, H. M., Maurer, G., Cochrane, K., Cooper, T. B., Mohs, R. C., & Davis, K. L. (1989). Serotonergic studies in patients with affective and personality disorders. Correlates with suicidal and impulsive aggressive behavior. Archives of General Psychiatry, 46, 587–599. Cofer, C. N., & Appley, M. H. (1964). Motivation: <strong>The</strong>ory and research. New York: Wiley. Cooper, S. J., & Kirkham, T. C. (1993). Opioid mechanisms in <strong>the</strong> control of food consumption and taste preferences. In A. Herz (Ed.), Handbook of experimental pharmacology (pp. 239–262). Berlin: Springer-Verlag. Coss, R. G., & Owings, D. H. (1989). Rattler battlers. Natural History, 48, 30–35. Damasio, A. R. (1996). <strong>The</strong> somatic marker hypo<strong>the</strong>sis and <strong>the</strong> possible functions of <strong>the</strong> prefrontal cortex. Philosophical Transactions of <strong>the</strong> Royal Society of London. Series B: Biological Sciences, 351, 1413–1420. Darlison, M. G., & Richter, D. (1999). Multiple genes for neuropeptides and <strong>the</strong>ir receptors: Co-evolution and physiology. Trends in Neurosciences, 22: 81–88. de Bono, M., & Bargmann, C. I. (1998). Natural variation in a neuropeptide Y receptor homolog modifies social behavior and food response in C. elegans. Cell, 94, 679–689. Delfs, J. M., Kong, H., Mestek, A., Chen, Y., Yu, L., Reisine, T., & Chesselet, M. F. (1994). Expression of mu opioid receptor mRNA in rat brain: An in situ hybridization study at <strong>the</strong> single cell level. Journal of Comparative Neurology, 345, 46–68. Diaz-Rios, M., Oyola, E., & Miller, M. W. (2002). Colocalization of gammaaminobutyric acid-like immunoreactivity and catecholamines in <strong>the</strong> feeding network of Aplysia californica. Journal of Comparative Neurology, 445, 29–46. Di Chiara, G. (1998). A motivational learning hypo<strong>the</strong>sis of <strong>the</strong> role of mesolimbic dopamine in compulsive drug use. Journal of Psychopharmacology, 12, 54–67. Dickinson, A., & Balleine, B. (1994). Motivational control of goal-directed action. Animal Learning Behavior, 22, 1–18. Doudet, D., Hommer, D., Higley, J. D., Andreason, P. J., Moneman, R., Suomi, S. J., & Linnoila, M. (1995). Cerebral glucose metabolism, CSF 5-HIAA levels, and aggressive behavior in rhesus monkeys. American Journal of Psychiatry, 152, 1782–1787. Drewnowski, A., Krahn, D. D., Demitrack, M. A., Nairn, K., & Gosnell, B. A. (1992).
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TLFeBOOK Who Needs Emotions? The Br
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The Nature of Emotion: Fundamental
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3 Oxford University Press, Inc., pu
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vi preface want their computer prog
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viii preface is required because th
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x preface prefer to read Part III b
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xii contents PART III: ROBOTS 7 Aff
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xiv contributors Jean-Marc Fellous
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4 perspectives RUSSELL: I confess t
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6 perspectives EDISON: Tinkering! Y
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10 perspectives HOW COULD WE TELL I
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12 perspectives This, of course, ra
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14 perspectives of a stimulus (e.g.
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- Page 47 and 48: 30 brains specificity and flexibili
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- Page 93 and 94: 76 brains trained monkeys: Agonist
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118 brains and flexible in the orbi
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120 brains Pleasure Rage Anger Frus
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122 brains of the eliciting stimulu
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124 brains or a right turn to obtai
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126 brains cortex and basal ganglia
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128 brains tex of recent (episodic)
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130 brains the right value in the c
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132 brains by the process of condit
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134 brains memories to be held in p
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136 brains However, it may be expec
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138 brains Figure 5.4. Some of the
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140 brains acting through the ventr
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142 brains (cutting white matter) w
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144 brains References Alexander, R.
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146 brains Rolls, E. T. (1999a). Th
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148 brains directed to us or when t
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150 brains Specific methods, partly
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152 brains Movements performed by l
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154 brains processing of invariant
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156 brains more about them, their r
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158 brains see Zajonc, 1985), the i
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160 brains The question now arises
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162 brains situations where they ha
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164 brains Estimation of social con
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166 brains Davies, M., & Stone, T.
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168 brains Lhermitte, F. (1983). Ut
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174 robots perform unanticipated ta
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176 Table 7.1. Principal Organism F
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178 robots and cognitive domains. A
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180 robots that they are better tho
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182 robots irregularities or discon
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184 robots 3. A (positive) feeling
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186 robots We consider the well-est
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188 robots disturbed by the approac
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190 robots processing. We view para
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192 robots independent, a value on
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194 robots Implications of the Proc
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196 robots current affective state
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198 robots primitive fear at the ro
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200 robots Gray, J. A. (1990). Brai
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202 robots cesses underlying approa
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204 robots case of CogAff, conjectu
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206 robots some cases and in other
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208 robots DIRECT AND MEDIATED CONT
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210 robots Toward a Useful Ontology
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212 robots different varieties of m
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214 robots Primitive sensors provid
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216 robots Being in a state P of a
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218 robots terms of the ability to
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220 robots Varieties of Affective S
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222 robots Central Perception Actio
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224 robots control, where all the l
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226 robots layer (e.g., observing p
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228 robots are sometimes unclear, i
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230 robots for such a fast-acting s
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232 robots from mental processes ot
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234 robots The majority view in thi
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236 robots Will it be a long-term f
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238 robots or implicitly adopted de
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240 robots some undesirable emotion
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242 robots References Albus, J. S.,
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244 robots Sloman, A. (2001b). Evol
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246 robots state variables such as
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248 robots In order to make robots
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250 robots motivational state also
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252 robots Prey acquisition: This b
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254 robots Figure 9.3. Top photos:
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256 robots especially when young. E
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258 robots Object of Attachment Saf
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260 robots Mean distance to attachm
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262 robots 2003), but the intent is
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264 robots Affective State Emotion
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266 robots Motivational/emotional m
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268 robots Brooks, R. (1986). A rob
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272 robots responsible for perceivi
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274 robots species considered to be
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276 robots This endeavor does not i
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278 robots For example, the person
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280 robots mental states (i.e., int
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282 robots Expression of Affective
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284 robots Negative valence High ar
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286 robots and emotion-related proc
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288 robots For instance, the visual
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290 robots Undesired stimulus Rejec
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292 robots intensity: seek or acqui
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294 robots Table 10.2. Summary of t
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296 robots it up (Breazeal, 2002b).
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298 robots pitch, f o (kHz) pitch,
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300 robots Table 10.3. Overall Clas
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302 robots Each emotion gateway pro
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304 robots Biasing Attention Kismet
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306 robots be to vocalize to the pe
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308 robots References Ackerman, B.,
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310 robots Center for the Study of
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312 robots When team members align
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314 robots effects that the agent h
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316 robots double arrow), which imp
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318 robots that of “robot as avat
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320 robots terms of specific apprai
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322 robots their own self-survival
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324 robots explicit, intended commu
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326 robots Although, the emotion
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328 robots planning. In Proceedings
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334 conclusions handout and pleased
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336 conclusions emotion. How can we
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338 conclusions Presumably, the fac
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340 conclusions Absence of N and N
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342 conclusions Thus, evolution yie
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344 conclusions different from such
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346 conclusions approach to the soc
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348 conclusions at the much higher
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350 conclusions mediated by distrib
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352 conclusions to the prefrontal c
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354 conclusions pathway of much mor
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356 conclusions The Motivated Toad
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358 conclusions explicitly formal r
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360 conclusions directly and by pro
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362 conclusions striatum pallidum d
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364 conclusions (A) Auditory stimul
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366 conclusions from the primary ta
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368 conclusions by an interest in u
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370 conclusions he sees as the stat
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372 conclusions to detect possible
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374 conclusions much of my behavior
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376 conclusions Consider a robot th
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378 conclusions 3. As already noted
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380 conclusions Fellous, J.-M., & S
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382 conclusions Localization of gra
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386 index amygdala back projection,
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388 index cognition (continued) evo
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390 index emotion research (continu
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392 index fear conditioning (contin
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394 index limbic system theory, 80-
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396 index prefrontal cortex and the
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398 index schema theory and Jackson