ライフサイエンスコーパス: gambling

1 n or neuroadaptive consequences of long-term gambling.

2 , for instance, during foraging, trading, or gambling.

3 risk-seeking behaviors, most pertinently in gambling.

4 utcomes confer vulnerability to pathological gambling.

5 g [F(1,9) = 9.2, P = 0.01] in the context of gambling.

6 show promise in the treatment of disordered gambling.

7 ional human behaviors such as overeating and gambling.

8 ondition marked by excessive and problematic gambling.

9 risk-taking in humans, such as pathological gambling.

10 s are less likely to be risk aversive during gambling.

11 l investments, career and health choices, or gambling.

12 erized by risky choices such as pathological gambling.

13 ncertainty on decision making extends beyond gambling.

14 h as drug abuse, overeating, or pathological gambling.

15 factors have been established for adolescent gambling.

16 in the treatment of adults with pathological gambling.

17 ed about the risks associated with excessive gambling.

18 owledge of the growing problem of adolescent gambling.

19 ficant reduction in severity of pathological gambling.

20 addressed in effective prevention of problem gambling.

21 order extend to those with problem (at-risk) gambling.

22 n-making, such as addiction and pathological gambling.

23 ification of the dangers of products used in gambling.

24 -related effects of neuroscience research on gambling.

25 aborations are needed to reduce the harms of gambling.

26 striatal dopamine synthesis in pathological gambling.

27 th a lifetime history of DSM-IV pathological gambling, 36%-39% did not experience any gambling-relate

28 Gambling addiction constitutes an example.

29 reward anticipation and in individuals with gambling addiction during reward outcome is in line with

30 of task settings affects reward responses in gambling addiction is debated.

31 e ventral striatum, whereas individuals with gambling addiction showed decreased activation in the do

32 across all addictions and for substance and gambling addictions separately.

33 anticipation, individuals with substance and gambling addictions showed decreased striatal activation

34 similar to what is observed in substance and gambling addictions, the neural and behavioral mechanism

35 ween technology addictions and substance and gambling addictions.

36 uncertainty can determine whether they find gambling addictive.

37 terview-based diagnoses of past-year problem gambling and alcohol, cannabis, and nicotine dependence

38 wed by punding, compulsive sexual behaviour, gambling and buying disorder.

39 when food is abundant, and why people enjoy gambling and care about winning.

40 This pattern, also seen in gambling and cocaine use, may reflect a primary deficit

41 r, and even pathological conditions, such as gambling and drug addiction.

42 neural discriminators (including those from gambling and emotion tasks), it suggests the involvement

43 the Human Connectome Project (HCP) study for gambling and emotion tasks.

44 npharmacological treatments for pathological gambling and is based on a review of the literature publ

45 evaluation signals subsequent choices during gambling and is essential for dynamically adjusting deci

46 ve-behavioral therapy (CBT) for pathological gambling and its general principles and provides an exam

47 us of understanding of the neurobiologies of gambling and PG is described.

48 nsula, among others) have been implicated in gambling and PG.

49 pted suicide misestimate expected rewards on gambling and probabilistic learning tasks.OBJECTIVES-To

50 impulse control disorders (eg, pathological gambling and shopping, binge eating, and hypersexuality)

51 important and understudied component of both gambling and substance use disorders.

52 europsychiatric disorders, including problem gambling and suicidal behavior.

53 relationship between diminished control over gambling and the adverse socioeconomic consequences of g

54 d prognostic uses of neuroscience in problem gambling and the provision of novel tools (eg, virtual r

55 The relations between problem gambling and the substance-related addictive disorders (

56 atric disorders such as impulsivity, problem gambling, and addiction suggests that a common mechanism

57 disorder, Tourette's syndrome, pathological gambling, and addictions remain poorly understood, limit

58 luding substance use disorders, pathological gambling, and attention deficit hyperactivity disorder.

59 order, substance use disorders, pathological gambling, and bipolar disorder.

60 range of behaviors including substance use, gambling, and risky sexual practice.

61 while they watched videos depicting cocaine, gambling, and sad scenarios to investigate the neural co

62 Pathological and problem gambling are associated with significant decrements in H

63 trol disorders (ICD), including pathological gambling, are common in Parkinson's disease (PD) and ten

64 oral addiction, with a focus on pathological gambling as the prototypical disorder.

65 Problem gambling at age 21 years was associated with higher scor

66 nd disorders including addiction, compulsive gambling, attention-deficit/hyperactivity disorder, and

67 in Gambling Disorder or in at-risk (problem) gambling: attentional inhibition, motor inhibition, disc

68 Many of the risk factors for gambling behavior can be addressed in effective preventi

69 a from a subset of twin pairs discordant for gambling behavior was used to control for genetic and fa

70 influencing risky choices that may moderate gambling behaviors in humans, particularly in casino and

71 The gambling behaviour of participants (bet increases, slot

72 work connectivity with medication dosage and gambling behaviour.

73 is of connectivity and its relationship with gambling behaviour.

74 ling twins and their problem or pathological gambling brothers, but adjusted co-twin analyses resulte

75 impulsivity may extend to problem (at-risk) gambling, but further studies are needed to confirm such

76 may be associated with the addictiveness of gambling, but little is known about the neurocognitive m

77 ntrol disorders (ICDs), including compulsive gambling, buying, sexual behavior, and eating, can occur

78 expected value had a stronger influence over gambling choices in adolescents relative to adults, an e

79 for addictive disorders such as pathological gambling, cigarette smoking, and drug and alcohol abuse.

80 e Compulsive Scale Modified for Pathological Gambling, compared to the placebo group.

81 sts develop pathological behaviours, such as gambling, compulsive eating, shopping, or disinhibited s

82 omoxetine could improve response inhibition, gambling decisions and reflection impulsivity.

83 y contrast, Bayesian analysis indicated that gambling decisions were better explained by models that

84 version and their respective contribution to gambling decisions.

85 neurobiological markers in individuals with gambling disorder (GD) could reflect transdiagnostic vul

86 Although gambling disorder (GD) has been associated with high imp

87 ed a lifetime history of DSM-IV pathological gambling disorder (N=21 and N=185, respectively).

88 ain opioid receptors are implicated, such as gambling disorder and alcohol use disorder.

89 Neuroscientific explanations of gambling disorder can help people make sense of their ex

90 also not clear whether cognitive deficits in Gambling Disorder extend to those with problem (at-risk)

91 Gambling disorder frequently co-occurs with other condit

92 The prevalence of gambling disorder has been estimated at 0.5% of the adul

93 e-third of the individuals with pathological gambling disorder in these two nationally representative

94 y among individuals with DSM-IV pathological gambling disorder in two large and representative U.S. n

95 Gambling Disorder is a prevalent psychiatric condition o

96 Gambling disorder is characterized by a persistent, recu

97 The aetiology of gambling disorder is complex, with implicated genetic an

98 Individuals with gambling disorder often go unrecognized and untreated, i

99 examining the following cognitive domains in Gambling Disorder or in at-risk (problem) gambling: atte

100 Gambling Disorder was associated with significant impair

101 of impulsivity to neurobiological models of Gambling Disorder, a comprehensive meta-analysis of all

102 Gambling disorder, a form of addiction without the confo

103 has a formal indication for the treatment of gambling disorder, although placebo-controlled trials su

104 Impulse control disorders, including gambling disorder, binge eating disorder, compulsive sex

105 ted dexamphetamine-induced opioid release in gambling disorder, suggesting that this dysregulation in

106 ivity across a range of cognitive domains in Gambling Disorder.

107 Anonymous, are supported in the treatment of gambling disorder.

108 rn the established wisdom about pathological gambling disorder.

109 cal systems of addictive disorders including gambling disorder.

110 tment efforts are needed to help people with gambling disorder.

111 Gambling disorders commonly co-occur with other psychiat

112 th other substance use disorders, and moving gambling disorders to the chapter formerly reserved for

113 en the comorbidity between substance use and gambling disorders, surprisingly little is known about t

114 caudate head was positively correlated with gambling distortions in pathological gamblers.

115 ain anatomy alterations to other (substance, gambling etc.) addictions.

116 f individuals with a history of pathological gambling eventually recover, most without formal treatme

117 eversing a loss-induced effect (causing more gambling for gains than losses and the reverse) while le

118 of no reward, provoked animals to excessive gambling for large rewards.

119 nnabis, opiates, alcohol, nicotine, smokers, gambling, gamblers, gaming, and gamers.

120 ng logs of numerous solely probability-based gambling games and extract the wager and odds distributi

121 Online gambling sites offer many different gambling games.

122 acy of naltrexone treatment for pathological gambling has been replicated in a double-blind, placebo-

123 From the perspective of personality, problem gambling has much in common with the addictive disorders

124 The behaviors include pathological gambling, hypersexuality, compulsive shopping, and compu

125 psychiatric comorbid conditions and problem gambling (i.e. depression).

126 ry were estimated among individuals from the Gambling Impact and Behavior Study (N=2,417) and the Nat

127 There is a clear link between problem gambling in adolescence and pathologic gambling in adult

128 oblem gambling in adolescence and pathologic gambling in adulthood.

129 r amantadine as a treatment for pathological gambling in patients with Parkinson disease (PD).

130 Gambling in the presence of salient cues may therefore r

131 Pathological gambling is a common disorder with severe consequences f

132 Pathological gambling is a disabling disorder experienced by approxim

133 Gambling is a naturalistic example of risky decision-mak

134 Pathological gambling is a psychiatric disorder and the first recogni

135 For many, gambling is a recreational activity that is performed pe

136 Problem gambling is also highly comorbid with substance use diso

137 Pathological gambling is described in DSM-IV as a chronic and persist

138 role in the pathophysiology of pathological gambling is pervasive.

139 increasing overall prevalence of adolescent gambling, it is imperative that pediatricians appreciate

140 In this work we analyse the gambling logs of numerous solely probability-based gambl

141 y environmental effects on HRQoL and problem gambling.Main Outcome Measure Health-related quality of

142 arge epidemiological surveys of pathological gambling may eventually overturn the established wisdom

143 iodically without ill effects, but for some, gambling may interfere with life functioning.

144 Pathological gambling may not always follow a chronic and persisting

145 new pharmacological agents for pathological gambling, N-acetyl cysteine and modafinil, produced sign

146 A commonly reported ICD is pathological gambling of which risk taking is a prominent feature.

147 Gambling on a long shot, whether a horse at the racetrac

148 For problem gambling, only decision-making had sufficient data for m

149 fail, as in mental disorders such as problem gambling or addiction, the results can be disastrous.

150 Fourteen impulse control disorder (problem gambling or compulsive shopping) and 14 matched Parkinso

151 viours, such as hypersexuality, pathological gambling or compulsive shopping.

152 vioral phenotypes (such as in uncontrollable gambling or eating).

153 task-switching, and reward-based tasks like gambling or reversal learning.

154 Pathological behaviors such as problem gambling or shopping are characterized by compulsive cho

155 addictions, that certain activities such as gambling or video-game play may be considered addictive

156 ncertainty when updating their beliefs about gambling outcome and translating these beliefs into acti

157 Cognitive distortions regarding gambling outcomes confer vulnerability to pathological g

158 jects learning to associate masked cues with gambling outcomes to maximize their payoff.

159 ay render them overoptimistic with regard to gambling outcomes.

160 measured behavioral and neural responses to gambling outcomes.

161 ed from clinician-administered tasks and the gambling paradigm, as compared to questionnaire data.

162 than 18 years; recreational substance use or gambling; participants at risk for addictive behaviors;

163 avorable and unfavorable outcomes during the gambling period.

164 ehavioral addiction phenotypes: pathological gambling (PG) and binge eating disorder (BED).

165 ty have both been implicated in pathological gambling (PG) and in reward processing.

166 ause of shared characteristics, pathological gambling (PG) has been variously conceptualized as an ob

167 ll individuals in treatment for pathological gambling (PG), but relatively little is known about the

168 oth cocaine dependence (CD) and pathological gambling (PG), few studies have directly investigated ne

169 A diagnostic entity, pathological gambling (PG), is currently used to define a condition m

170 amygdalar function, and link to pathological gambling (PG).

171 has trouble explaining why, in slot machine gambling, players are motivated by extended play to spen

172 During gambling, players typically display an array of cognitiv

173 e, value-independent) gambling propensity, a gambling preference scaling with the amount/variance, an

174 amounts of money in 15 patients with problem gambling (PRGs) and 16 healthy control subjects (HCs).

175 mperative that pediatricians appreciate that gambling problems can also afflict adolescents.

176 nd the adverse socioeconomic consequences of gambling problems.

177 diction disorders, the cues inherent in many gambling procedures are thought to play an important rol

178 substance use disorder, and many commercial gambling products incorporate salient win-paired cues.

179 mpany reward delivery, similar to commercial gambling products, show greater preference for risky opt

180 tcomes are proximal to the jackpot, increase gambling propensity and may be associated with the addic

181 pended on a baseline (ie, value-independent) gambling propensity, a gambling preference scaling with

182 ncreased just the value-independent baseline gambling propensity, leaving the other components unaffe

183 atings as well as a questionnaire measure of gambling propensity.

184 Disordered gambling refers to the full continuum of gambling-relate

185 generally lacking from these procedures are gambling related cues that may moderate risk preferences

186 changes similar to previous research lacking gambling related cues.

187 Animal models of gambling-related behavior, while capturing dimensions of

188 tudy investigated brain regions underpinning gambling-related cognitive distortions, contrasting pati

189 nal imaging studies of reward processing and gambling-related cognitive distortions.

190 may be further increased by the presence of gambling-related cues in the environment, but the extent

191 at have highlighted the transitory nature of gambling-related problems have called into question whet

192 cal gambling, 36%-39% did not experience any gambling-related problems in the past year, even though

193 red gambling refers to the full continuum of gambling-related problems that includes PG disorder.

194 ilored larger-but-later rewards while visual gambling-related scenes were presented in the background

195 the environment, but the extent to which the gambling relatedness of task settings affects reward res

196 Considerations for future directions in gambling research, with a view towards translating neuro

197 Within each gambling round, the accumulation of gains gradually incr

198 Furthermore, the negative relation between gambling severity and amygdala activation in gain expect

199 hly significant negative correlation between gambling severity scores and right amygdala activation a

200 lamus and caudate correlated negatively with gambling severity.

201 include hypersexuality as well as compulsive gambling, shopping, and eating, and these behaviors are

202 Online gambling sites offer many different gambling games.

203 However, when applied to uncertain gambling situations, there are several areas where this

204 in humans, particularly in casino and other gambling-specific environments.

205 D (17.6% vs 12.4%, p < 0.001) and compulsive gambling specifically (7.4% vs 4.2%, p < 0.001).

206 Moreover, the degree to which gambling strengthened encoding scaled with the reward pr

207 rates of treatment-seeking for pathological gambling suggests that natural recovery might be common.

208 The Iowa gambling task (IGT) is one of the most influential behav

209 rticipants, while they took part in the Iowa Gambling Task (IGT), a monetary decision making task tha

210 ociation with cognition, especially the Iowa Gambling Task (IGT), and with schizophrenic psychopathol

211 sion making can be quantified using the Iowa Gambling Task (IGT), which requires choosing between adv

212 impulsive decision making, we used the Iowa Gambling task (IGT).

213 ith pramipexole or placebo by using the Iowa Gambling Task (IGT).

214 Rats trained to perform a version of the rat gambling task (rGT) in which salient audiovisual cues ac

215 We developed the rat gambling task (rGT) to investigate the neurobiology unde

216 ing win-associated audiovisual cues to a rat gambling task (rGT) would influence decision making.

217 To address this question, we used a gambling task and a model-based analytic approach to mea

218 ng correct decisions in blindsight, the Iowa gambling task and an artificial grammar task.

219 Here we show with a gambling task and functional magnetic resonance imaging

220 onths, who played 60 turns of the Children's Gambling Task and provided regular estimates on their pe

221 loyed a simple two-alternative forced choice gambling task and quantified the frequency at which part

222 reduces risky gambling when the training and gambling task are separated by 24 hours.

223 ormance in specific domains of the Cambridge Gambling Task correlated inversely and specifically with

224 aking over 3 million decisions, who played a gambling task designed to measure the latent causes and

225 bjects played a modified version of the Iowa Gambling Task during MR scanning.

226 ealthy control subjects (n = 23) completed a gambling task featuring a decision between a gamble and

227 elucidate its neural basis, we used a novel gambling task in conjunction with functional magnetic re

228 ication in 18 healthy human subjects using a gambling task in fMRI.

229 e, we investigate human decision-making in a gambling task in which the informational value of each t

230 ty of single neurons in monkeys performing a gambling task in which the reward outcome of each choice

231 and adult participants performed a monetary gambling task in which they chose to accept or reject ga

232 Using functional imaging during a simple gambling task in which we constantly changed risk, we sh

233 high-reward objects shown as primes before a gambling task increased financial risk taking.

234 d dopamine release to conditioned cues and a gambling task on [(11)C]raclopride positron emission tom

235 acquired while the participants performed a gambling task predicting whether they would win or lose

236 ementary eye field (SEF) of monkeys during a gambling task that allowed us to distinguish chosen good

237 (20 males and 20 females) while performing a gambling task that involved monetary loss and gain.

238 al circuits encoding bias, we administered a gambling task to 10 participants implanted with intracer

239 We used the Cambridge Gambling Task to characterize decision-making and risk-t

240 atement: We used a rodent analog of the Iowa Gambling Task to determine whether the addition of audio

241 We combined functional imaging with a simple gambling task to vary expected reward and risk simultane

242 fy time-series for emotion task vs. no-task, gambling task vs. no-task and emotion task vs. gambling

243 imaging (fMRI) data during performance of a gambling task where blocks comprise values drawn from on

244 ices made by two rhesus macaques in a visual gambling task while we varied the delay between trials.

245 ing vmPFC neurons while macaques performed a gambling task with asynchronous offer presentation.

246 Following the two nights, they performed a gambling task with no immediate feedback; for each round

247 e probabilities are ambiguous (e.g. the Iowa Gambling Task).

248 individuals make poor decisions on the Iowa Gambling Task, a reward-related decision-making task tha

249 Indeed, studies with the Iowa Gambling Task, a standard measure of risk-based decision

250 e between the good and bad decks of the Iowa Gambling Task, and that healthy participants even have c

251 We demonstrate this independence in a gambling task, by selectively reversing a loss-induced e

252 Participants played the Iowa Gambling Task, during which only experimental participan

253 Participants completed a gambling task, embedded within an emotional working memo

254 As in the Iowa Gambling Task, favoring options associated with smaller

255 Here, using a simple gambling task, in which the decisions of ostensible prev

256 e risky, disadvantageous options on the Iowa Gambling Task, is associated with greater risk of relaps

257 Here we show, in a gambling task, that human subjects' choices can be chara

258 As in the Iowa Gambling task, the optimal strategy is to avoid choosing

259 s) recorded in humans during a probabilistic gambling task, we show that individuals' behavioral tend

260 ala (BLA) in acquisition of the rGT and Iowa Gambling task, we used a contralateral disconnection les

261 risk-aversion attitudes expressed during the gambling task.

262 hy young individuals engaged in a sequential gambling task.

263 but normal activation levels for a monetary gambling task.

264 rature on expertise acquisition and the Iowa Gambling Task.

265 and healthy controls (6 women) performing a gambling task.

266 cision-making performance on a modified Iowa Gambling Task.

267 es, and performed worse on the modified Iowa Gambling Task.

268 imensional Set Shift Task, and the Cambridge Gambling Task.

269 tive decision making as measured by the Iowa Gambling Task.

270 eted the N-back task of working memory and a gambling task.

271 sonance images of 56 human subjects during a gambling task.

272 garette-smoking subjects performing the Iowa Gambling Task.

273 mentary eye field (SEF) during an oculomotor gambling task.

274 accumbens neurons while subjects performed a gambling task.

275 al response to feedback information during a gambling task.

276 Men outperform women on the Iowa Gambling Task.

277 mbling task vs. no-task and emotion task vs. gambling task.

278 ion making using the rat version of the Iowa gambling task.

279 striatal dopamine release to incentive cues, gambling tasks and reward prediction, and possible inhib

280 to be robustly risk-seeking in computerized gambling tasks typically used for electrophysiology.

281 of sleep restriction affects neither general gambling tendency, nor two of the main predictions of pr

282 erized by a persistent, recurrent pattern of gambling that is associated with substantial distress or

283 se data indicate that near-misses invigorate gambling through the anomalous recruitment of reward cir

284 Gambling to recover losses is a common gaming behavior.

285 own by the recent allocation of pathological gambling to this category in DSM-5.

286 differences existed between the non-problem gambling twins and their problem or pathological gamblin

287 n the neural correlates of drug cravings and gambling urges in CD and PG.

288 videos, and PG participants reporting strong gambling urges to gambling videos.

289 in reversal-learning tasks and more complex 'gambling' variants.

290 vated for cocaine videos in CD participants, gambling videos in PG participants, and sad videos in co

291 ticipants reporting strong gambling urges to gambling videos.

292 G participants showed increased responses to gambling videos.

293 Problem gambling was also associated with Multidimensional Perso

294 Main Outcome Measure Disordered gambling was defined based on lifetime DSM-IV PG symptom

295 ndred seven persons with DSM-IV pathological gambling were randomly assigned to receive nalmefene (25

296 e Compulsive Scale Modified for Pathological Gambling) were analyzed by using a linear mixed-effects

297 ion was phrased in terms of gains and toward gambling when the decision was phrased in terms of losse

298 ng in the stop-signal paradigm reduces risky gambling when the training and gambling task are separat

299 that they are dysfunctional in pathological gambling with poor self-control, we studied gamblers wit

300 therapy, compulsive buying and pathological gambling, with eight patients exhibiting more than one i