ライフサイエンスコーパス: choice behavior

1 question of causal factors underlying human choice behavior.

2 site ways with the baseline stochasticity of choice behavior.

3 ssion-like effects, can alter effort-related choice behavior.

4 racterize our model of individual and social choice behavior.

5 rcuits govern the ability to learn and shift choice behavior.

6 ge to future actions is crucial for adaptive choice behavior.

7 e neural mechanisms mediating this important choice behavior.

8 ing success through adjustments in nest site choice behavior.

9 and result in more impulsive social-economic choice behavior.

10 ulsivity, whereas valproate had no effect on choice behavior.

11 ompeting valuation systems in the control of choice behavior.

12 ained monkeys can serve as a model for human choice behavior.

13 the inability of rats to maintain reinforced choice behavior.

14 yses to identify regions involved in biasing choice behavior.

15 ferentially engaged in effort and cue-guided choice behavior.

16 oportions matching those that best explained choice behavior.

17 ce of conceptual knowledge and its effect on choice behavior.

18 3 receptor agonist, 7-OH-DPAT, did not alter choice behavior.

19 effort can be used to assess effort-related choice behavior.

20 perience to the contrary, instructions drove choice behavior.

21 hat value, risk, and risk aversion influence choice behavior.

22 ing an overall metric of value used to guide choice behavior.

23 aptic plasticity is able to produce adaptive choice behavior.

24 choice outcome, novelty nevertheless drives choice behavior.

25 he two sets of brain regions predicts actual choice behavior.

26 e-exposed rats displayed increased impulsive choice behavior.

27 experience and can exert strong influence on choice behavior.

28 einforcement learning model of the patient's choice behavior.

29 ositive and negative outcomes to guide their choice behavior.

30 that governs the time course of learning and choice behavior.

31 aying an important role in optimizing future choice behavior.

32 of the molecular mechanisms underlying food choice behavior.

33 al dynamics of value coding and psychometric choice behavior.

34 e opposing predictions in experimental human choice behavior.

35 ess differentially impacts context-dependent choice behavior.

36 rough which mood fluctuations may bias human choice behavior.

37 e developed in economics to model individual choice behavior.

38 e cognitive representations that drive human choice behavior.

39 bjective value of available options to guide choice behavior.

40 plete model of the environment could explain choice behavior.

41 , exhibiting biases and distortions in their choice behavior.

42 prefrontal cortex and midbrain but not with choice behavior.

43 also predicted the amount of variability in choice behavior.

44 nforcement learning model fitted on monkeys' choice behavior.

45 es and used these models to fit individuals' choice behavior.

46 humans and an analog framework for flexible choice behavior.

47 nce of the active role of motor processes in choice behavior.

48 c neurons within the OFC and utilized during choice behavior.

49 nlinearities, shape attribute processing and choice behavior.

50 ncorporate them in computations that mediate choice behavior.

51 sk and constructed network models to capture choice behavior.

52 affective experience and impacts subsequent choice behavior.

53 g lastingly influences female perception and choice behavior.

54 other measures that describe the underlying choice behavior.

55 performs other learning models in predicting choice behavior.

56 ypes of physicians' information on patients' choice behavior.

57 icate that these factors can directly impact choice behavior.

58 ter self-control and improved predictions of choice behavior.

59 romedial prefrontal cortex (vmPFC) predicted choice behavior.

60 avioral mechanism by which MA rigidly biases choice behavior.

61 significant component of the variability of choice behavior.

62 to motor actions, thereby enabling adaptive choice behavior.

63 pulations of value are sufficient to mediate choice behavior.

64 renicline on probabilistic reversal learning choice behavior.

65 processes, which in turn leads to irrational choice behavior.

66 rgets, ensuring that total reward was due to choice behavior.

67 e influencing RTs and errors, did not affect choice behavior.

68 the evolution of qualitative aspects of its choice behavior.

69 ed individual differences in satiety-related choice behavior.

70 ortance of the law of diminishing returns in choice behavior.

71 que to modulate dopamine activity and monkey choice behavior.

72 not use prospective regret signals to guide choice behavior.

73 volved in Pavlovian processes that influence choice behavior.

74 phasic dopamine release that may drive risky choice behavior.

75 formation and use of prior beliefs to guide choice behavior.

76 ous reward, and are predictive of subsequent choice behavior.

77 animals integrate prior knowledge into their choice behavior.

78 ognized as a ubiquitous aspect of real-world choice behavior.

79 y contribute differently to value coding and choice behaviors.

80 animal's nervous system during naturalistic choice behaviors.

81 ole for cingulate-motor circuits in adaptive choice behaviors.

82 srupts mPFC-HPC oscillatory interactions and choice behaviors.

83 rong candidate genes for mate and host plant choice behaviors.

84 e of the selection pressures associated with choice behaviors.

85 Strikingly, computational modeling of choice behavior [7] revealed that tolcapone exerted sele

86 issors game, rhesus monkeys can adjust their choice behaviors according to both actual and hypothetic

87 Models of choice behavior account for this bias by weighting decis

88 but could be dynamically engaged to control choice behavior across early and extended training.

89 By simulating choice behavior across various network models, we found

90 commissurotomy, were unable to adjust their choice behavior after a change in the outcome (here, a r

91 thyltransferase gene predicts both impulsive choice behavior and activity levels in the dPFC and PPC

92 l substrates of such mechanisms by comparing choice behavior and blood oxygen level-dependent (BOLD)

93 executive cognitive function could influence choice behavior and brain responses.

94 oblem was assessed by monitoring accuracy of choice behavior and by measuring latency to respond for

95 vity forecast stock price movement even when choice behavior and conventional stock indicators did no

96 d acute stress exposure affect participants' choice behavior and decision speed in a two-stage sequen

97 ly reproduced the co-variability in animals' choice behavior and dopaminergic activity.

98 of purely economic motivations in explaining choice behavior and instead emphasize the importance of

99 Choice behavior and its neural correlates have been inte

100 ulation of reward- but not punishment-guided choice behavior and learning, driven by increased explor

101 unts, we find that goal congruency dominates choice behavior and neural activity.

102 alue coding critically influences stochastic choice behavior and provide a generalizable quantitative

103 We measured choice behavior and recorded dLight signals that reflect

104 estigate amino acid-specific effects on food-choice behavior and report that folic acid from the micr

105 rovide a model-free tool to predict adaptive choice behavior and reveal underlying neural mechanisms.

106 sing multiple approaches, we found that both choice behavior and reward probabilities estimated by pa

107 provides evidence for OFC's role in guiding choice behavior and shows that this is dissociable from

108 key role of orbitofrontal cortex activity in choice behavior and shows that this is dissociable from

109 eostasis, yet whether AgRP neurons influence choice behavior and temporal discounting is unknown.

110 periences, or recent events, influence risky choice behavior and the underlying processes.

111 se reversibly modulated the subjects' visual choice behavior and was specific to the targeted region

112 s were screened for aggressive and impulsive choice behaviors and categorized into Low-Aggression (L-

113 There is no difference in their choice behavior, and both groups depart substantially fr

114 njunctions should be attended to and control choice behavior, and how subsequent attentional modulati

115 -dependent fear conditioning, lever-pressing choice behavior, and social interaction behaviors.

116 Here we present a mouse model of economic choice behavior, and we show that the lateral orbital (L

117 period would impair working memory, disrupt choice behaviors, and alter mPFC-HPC oscillatory synchro

118 olistic perspective on the interplay between choice, behavior, and their neural underpinnings.

119 nstrates that the two dominant frameworks of choice behavior are linked through the law of diminishin

120 ls assume that the parameters giving rise to choice behavior are stable, yet emerging research sugges

121 making, but the effects of normalization on choice behavior are unknown.

122 Mate choice behaviors are among the most important reproducti

123 er, the signaling mechanisms underlying food-choice behaviors are poorly understood.

124 Studies 3 and 4 (n = 918) introduced choice behavior as outcome variables, revealing that sad

125 tion and explains both classically described choice behavior as well as behavioral patterns not predi

126 ng how marketing actions can affect consumer choice behavior as well as for how environmental cues ca

127 he effects of a scarcity mindset on consumer choice behavior, as well as its underlying neural mechan

128 Characters involved in choice behavior at reproduction appear based on quantita

129 ce that enhanced cognitive control can shift choice behavior away from immediate and risky rewards, w

130 mplicated dopamine as a modulating factor in choice behavior based on effort.

131 e has an impact on monkeys' ability to guide choice behavior based on reward value but does not impac

132 magination can be used to accurately predict choice behavior both between and within individuals.

133 Such choice behavior can be assessed from an optimal foraging

134 We propose that choice behavior can be more accurately accounted for by

135 ce, and show that the contribution of BLA to choice behavior changes across the lifespan.

136 e rhesus macaque monkeys, showing that their choice behavior complied with the existence of a numeric

137 re can cause enduring increases in impulsive choice behavior, consistent with observations in human s

138 del-based and model-free influences on human choice behavior could be distinguished.

139 This pattern of choice behavior could be explained by a causal role for

140 We explored whether this kind of choice behavior could be seen in other primates.

141 uggested that tasks measuring effort-related choice behavior could be used as animal models of the mo

142 We show that choice behavior depended on a baseline (ie, value-indepe

143 trials and reinforcer intake, but effects on choice behavior did not depend on these motivational cha

144 g on WM can benefit the rapid acquisition of choice behavior during learning but impairs retention.SI

145 s and humans) on latent processes supporting choice behavior during probabilistic reversal learning,

146 ve payoffs and primary rewards, the animal's choice behavior during this task was nearly optimal.

147 Human choice behaviors during social interactions often deviat

148 d positively with state impulsivity (riskier choice behavior) during gambling.

149 Economic choice behavior entails the computation and comparison o

150 ity during context encoding is necessary for choice behavior, even while that choice behavior is robu

151 Is human choice behavior evolutionarily adaptive or is it an inef

152 Human choice behavior exhibits many paradoxical and challengin

153 Here, we combined computational modeling of choice behavior, experimentally induced inflammation, an

154 any of the puzzling inconsistencies of human choice behavior, explaining why these inconsistencies ar

155 udy the neurophysiological signals governing choice behavior fall under one of two major theoretical

156 a key prediction of this hypothesis, we fit choice behavior from a dynamic foraging task with reinfo

157 Choice behaviors, from hard-wired to experience-dependen

158 ssumption in the behavioral sciences is that choice behavior generalizes enough across individuals th

159 This inflection in risky choice behavior has been attributed to a neurobiological

160 possible role of the SC in voluntary visual choice behaviors has not been established.

161 ision making reliably predicts intertemporal choice behavior have not been identified.

162 lude that previous exposure to cocaine makes choice behavior hypersensitive to differences in the tim

163 in 34 brain regions during thirst-motivated choice behavior in 21 mice as they consumed water and be

164 also the case in rodents, we examined rat's choice behavior in a binary choice task in which variabl

165 hat treatment with dopaminergic drugs alters choice behavior in a manner consistent with the theory.

166 nhibition of the BLA has opposite effects on choice behavior in a rat model of risky decision making,

167 provide the first evidence that value-based choice behavior in a reversal-learning task improves dur

168 llodynia with that of cognitively controlled choice behavior in a two-arm maze, adapted from Hayashid

169 d duration resulted in normal alterations in choice behavior in AcbC-lesioned rats.

170 oral protocol for rapidly assessing adaptive choice behavior in adolescent rats with a reversal-learn

171 However, context-dependent choice behavior in both animals and humans violates this

172 ask domains and further predicted subsequent choice behavior in both.

173 rotocol for the rapid assessment of adaptive choice behavior in dynamic environments in rats as young

174 logy to investigate the architecture of mate choice behavior in Heliconius cydno butterflies, a clade

175 s one of the clearest examples of irrational choice behavior in humans.

176 by supporting striatal plasticity in shaping choice behavior in humans.

177 igate this function, we studied instrumental choice behavior in mice lacking GPR88, a striatum-enrich

178 tion of low- and high-level processes shapes choice behavior in more naturalistic settings, modulates

179 To do so, we quantified Now/Later choice behavior in naturally cycling adult females (n =

180 ing and particularly how it shapes nest site choice behavior in nature.

181 We provide the first evidence that choice behavior in rats is influenced by model-free and

182 social experience, which were necessary for choice behavior in social and nonsocial contexts alike.

183 Mathematical models that describe choice behavior in specific contexts have provided impor

184 e importance of the SC for visual perceptual choice behavior in the mouse.

185 t fixed but collapse over time, facilitating choice behavior in the presence of low-quality evidence.

186 Computational modeling of choice behavior in the reversal phase indicated that [(1

187 in, serves as a major determinant to predict choice behavior in the task.

188 The animals' choice behavior in this task followed the molar matching

189 Here we comprehensively modeled choice behavior in this task, including the trial-to-tri

190 enter, the activity of which predicates this choice behavior in zebrafish.

191 The new research has focussed on choice behaviors in the context of habitat and resource

192 uggest that the genetic architecture of mate choice behavior, in this case, is more complex than QTL

193 s indicate that the influence of dopamine on choice behavior involves a specific modulation of the at

194 Choice behavior is characterized by temporal discounting

195 The ability to use prior knowledge to adapt choice behavior is critical for flexible decision making

196 ggesting that information relevant for risky choice behavior is encoded in coarse global patterns of

197 ence of monetary loss on decision making and choice behavior is extensively studied.

198 cessary for choice behavior, even while that choice behavior is robust to inactivations during choice

199 lly in these neurons contribute to impulsive choice behavior is unknown.

200 nfluence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pat

201 This neural pattern, as well as subjects' choice behavior, is consistent with a teaching signal fo

202 ns, as well as the performance of cue-guided choice behavior, is thought to involve dopamine D1 and D

203 ight/half-dark visual image evokes an innate choice behavior, light avoidance.

204 These findings suggest that inconsistent choice behavior may arise from multiple cognitive proces

205 However, age differences in choice behavior may be reduced if older adults can recru

206 that emotional associations have on survival choice behaviors may lead to better treatments for menta

207 Findings indicate that choice behaviors mediated by cocaine conditioning are re

208 han gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision

209 those of cocaine as evidenced by a change in choice behaviors motivated by drug reward.

210 After OFC lesions, animals' choice behavior no longer reflected the history of preci

211 rient-specific components to account for the choice behavior observed in the monkeys.

212 erent task representations to trial-by-trial choice behavior of individual rats performing this task,

213 ral consistency across people, even when the choice behavior of the sample does not match the aggrega

214 netic resonance imaging, we examined how the choice behavior of treatment-engaged male and female par

215 Human choice behavior often reflects a competition between inf

216 also makes testable predictions about human choice behavior on a simple decision-making task.

217 that deficits specifically in reward-guided choice behavior on the probabilistic reversal learning t

218 video games for measures of brain activity, choice behavior, or cognitive performance.SIGNIFICANCE S

219 struggled with the irrationalities of human choice behavior; people consistently make choices that a

220 gs across disciplines suggests that observed choice behavior reflects a precise optimization of the t

221 n decision-making experiments and found that choice behavior relies on an interplay among multiple in

222 A model of choice behavior revealed that the rate of sensory eviden

223 It is believed that choice behavior reveals the underlying value of goods.

224 estigate the molecular and cellular basis of choice behavior, reward and associative learning.

225 matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Baye

226 Computational models of choice behavior showed that citalopram increased harm av

227 e influence of information on variability in choice behavior.SIGNIFICANCE STATEMENT Many animals seek

228 ds and reveal a novel circuit that determine choice behavior.SIGNIFICANCE STATEMENT Temporal discount

229 r the normal performance of voluntary visual choice behaviors.SIGNIFICANCE STATEMENT The mouse superi

230 cruitment of pre-SMA may contribute to risky choice behavior (state impulsivity) during sequential ga

231 (trait impulsivity) were reflected in their choice behavior (state impulsivity) when involved in a s

232 model predicts both PRC-intact and -lesioned choice behaviors, suggesting that a linear readout of th

233 Human choice behavior takes account of internal decision costs

234 8-091) by using two different effort-related choice behavior tasks in male Sprague-Dawley rats.

235 pre-feeding resulted in divergent changes in choice behavior that depended on the rats' prior prefere

236 behaving in a dynamic foraging task exhibit choice behavior that varied as a function of two forms o

237 ovement initiation produced a robust bias in choice behavior, this bias was substantially diminished

238 tes female odor perception and expression of choice behavior through a dopamine-gated learning circui

239 w motor neurons may help shape threat-reward choice behaviors through interacting with other neurons.

240 tions to explain valuation and choice, or on choice behavior to derive value functions.

241 retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions

242 shroom body to explain each fly's sequential choice behavior using a family of biologically realistic

243 mpete with those of cocaine for control over choice behavior using a place conditioning task.

244 The modulation of choice behavior using microstimulation was best modeled

245 ns between genetic risk for obesity and food choice behaviors using objectively assessed workplace fo

246 ngle, unified decision process that mediates choice behavior via a common neural currency for outcome

247 nd suggest how reward can influence adaptive choice behavior via prefrontal dopamine.

248 Participant choice behavior was analyzed using both a standard reinf

249 Choice behavior was best predicted by a model including

250 We found that choice behavior was better described by a learning model

251 Subjects rarely fixated both options, yet choice behavior was better explained by assuming the val

252 design allowed us to test whether subjects' choice behavior was guided by policy-based methods, whic

253 The animal's choice behavior was relatively close to the optimal stra

254 Using computational modeling of choice behavior we find that fatiguing exertions cause p

255 plore the neural basis of such intertemporal choice behavior, we devised a novel two-alternative choi

256 s causally related to specific components of choice behavior, we employed selective optogenetic stimu

257 in D. melanogaster and mediate critical host-choice behavior, were deleted or pseudogenized in the ge

258 e effort model better explains out-of-sample choice behavior when compared with parabolic and exponen

259 Notably, OFC inactivation did not affect choice behavior when it was guided by innate taste avers

260 The AcbC-lesioned rats produced appropriate choice behavior when the reward magnitude was equal.

261 I improved prediction of variability in ally-choice behavior, whereas variability from the pgACC did

262 Our results show that context-dependent choice behavior, which is commonly perceived as an irrat

263 representations are used directly to adjust choice behavior, which thus likely requires integration

264 negative outcomes and increased exploitatory choice behaviors while preserving learning for positive

265 ble to produce a bidirectional modulation of choice behavior, while drugs that act on D3 receptors we

266 tance and polarization-dependent female mate choice behavior with no polarization-dependent courtship

267 rative data indicate that context influences choice behavior, with the strongest effect seen in marmo

268 Reversal of choice behavior within each block is driven by a combina