ライフサイエンスコーパス: prediction error

1 nternal prediction cannot account for (i.e., prediction error).

2 ected and received rewards (i.e., the reward prediction error).

3 modulation was consistent with an appetitive prediction error.

4 In both cases the terminals encoded a reward prediction error.

5 stimuli, and so cannot arise as this sort of prediction error.

6 n +/-1.00 D of targeted refractive IOL power prediction error.

7 tic plasticity and learning is instructed by prediction error.

8 n +/-1.00 D of targeted refractive IOL power prediction error.

9 formation of subjective expected reward and prediction error.

10 uctive signal known as a temporal difference prediction error.

11 activity, probably reflecting differences in prediction error.

12 ack, and 8 studies (314 patients) for reward prediction error.

13 t it did not act independently as a negative prediction error.

14 nables memory re-evaluation driven by reward-prediction error.

15 resentations and signal their deviation as a prediction error.

16 s, while VS dopamine reliably encodes reward prediction error.

17 the discontinuation of reinforcement through prediction errors.

18 eflect belief updating by precision-weighted prediction errors.

19 s received a reward, yielding trial-by-trial prediction errors.

20 rly brief pauses can substitute for negative prediction errors.

21 s received a reward, yielding trial-by-trial prediction errors.

22 and scales with the magnitude of experienced prediction errors.

23 oices by encoding temporal-difference reward prediction errors.

24 Dopamine neurons signal reward prediction errors.

25 ng as disturbed weighting of predictions and prediction errors.

26 to mimic the effects of endogenous negative prediction errors.

27 s a longer-term estimate (or expectation) of prediction errors.

28 ve updating of predictive models with larger prediction errors.

29 ention and were specific to value and reward prediction errors.

30 ty to key decision variables, such as reward prediction errors.

31 Associative learning is driven by prediction errors.

32 adjusting action values according to reward prediction errors.

33 d were more driven by recent negative reward prediction errors.

34 ntially from positive, relative to negative, prediction errors.

35 neutral cues, neutral outcomes, and neutral prediction errors.

36 terfering with its key computation of reward prediction errors.

37 nd from signals of expected reward or reward prediction errors.

38 ning models that incorporate negative reward prediction errors.

39 o account positive, as compared to negative, prediction errors.

40 the only significant factor that influenced prediction error (a = -0.32; P = .001).

41 Heightened prediction error activity in brain reward regions may re

42 Prediction error (adjusted for using both eyes) at 7 yea

43 influence on the client, and relative merit prediction error affects activity in medial-prefrontal c

44 w that the same signal that codes for reward prediction errors also codes the animal's certainty abou

45 n, this paper presents an extension based on prediction errors' analysis to statistically define the

46 This restoration of prediction error and fear learning was specific to the i

47 ximal ESN performance, expressed in terms of prediction error and memory capacity.

48 RI observations were uniquely simulated by a Prediction Error and not a Sharpened Signal model.

49 an be used to distinguish representations of Prediction Error and Sharpened Signals in other perceptu

50 pothesis that gamma-band power is related to prediction error and that this might underlie perceptual

51 Prediction error and unexpected reward omission response

52 e ventral tegmental area (VTA) encode reward prediction errors and can drive reinforcement learning t

53 correlate with positive and negative reward prediction errors and can mimic their effects [3-15].

54 ider the effect of cycloplegia on refractive prediction errors and IOL power calculations determined

55 esponses in the striatum to value and reward prediction errors and reduced the impact of both on smok

56 gmental area (VTA) to striatum encode reward prediction errors and reinforce specific actions; howeve

57 etween nonrewarding events is also driven by prediction errors and that, contrary to existing canon,

58 ined by differences in learning from outcome prediction errors and were associated with distinct form

59 uroimaging signals coding the learning rate, prediction error, and acquired value follow the multipli

60 tive or ineffective phase III conclusion, by prediction error, and by concordance index (c-index).

61 oceptive signals, the precision-weighting of prediction errors, and the "affective tuning" of neurona

62 are activated by both positive and negative prediction errors, and thus report signals similar to th

63 zy models proven the best results with small prediction errors, and variability lower than 10%.

64 t neurons specialize in different aspects of prediction error; another is that each neuron calculates

65 Prediction errors are critical for associative learning

66 lly, we show that these subjectively defined prediction errors are informative of the riskiness of th

67 hat unexpected features of the speech input (Prediction Errors) are processed further.

68 he models were ranked using root mean square prediction error as a percentage of the average observed

69 resence of a deafferentation-based bottom-up prediction error as a result of a top-down prediction.

70 opamine neurons have been proposed to signal prediction errors as defined in model-free reinforcement

71 neurons have been proposed to signal reward prediction errors as defined in temporal difference (TD)

72 The main outcome measure was prediction error at 7 years of age.

73 ritic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of

74 ean and confidence interval of drug response prediction errors based on ensemble approaches with vari

75 o evaluated systems and (2) the low relative prediction errors, below 7% in all cases, indicating goo

76 ther limbic regions for rewards and positive prediction errors; blunted activation of the ventral str

77 ug (DREADD) in dmPFC and isolated actions of prediction error by using an associative blocking design

78 reward is expected, causally contributing to prediction-error calculations.

79 show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects

80 of advance information arises because reward prediction errors carried by such information can boost

81 ct of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subje

82 Adaptive prediction error coding was paralleled by behavioral ada

83 paminergic function is critical for adaptive prediction error coding, a key property of the brain tho

84 It has been suggested that social prediction errors-coding discrepancies between the predi

85 modelling, we provide evidence in favour of Prediction Error computations.

86 a prosocial context and signals a prosocial prediction error conforming to classical principles of r

87 ard value as a numeric, quantitative utility prediction error, consistent with formal concepts of eco

88 Brain function was tested using the reward prediction error construct, a computational model for re

89 Using functional MRI, we show these social prediction errors correlate with activity in ventral str

90 modulated learning signals (value and reward prediction error) defined by a computational model of me

91 process that learns invariantly from sensory prediction error detected by proprioception and a visual

92 le to learn a new gait pattern using sensory prediction errors detected by proprioceptive feedback.

93 is instead responsible for fast but general prediction error detection.

94 nce), with incongruence between these termed prediction error (deviation from prediction) or surprise

95 s for the learning rate, expected value, and prediction error did not differ between the groups.

96 ward expectancy (expected outcome value) and prediction error- (discrepancy between expected and actu

97 s prior fear conditioning of CSA reduced the prediction error during stage II to block fear learning

98 This cerebellar region also responded to prediction error during the outcome of the trial.

99 ational simulations of Sharpened Signals and Prediction Errors during speech perception could both ex

100 m Schultz provides an introduction of reward prediction error, exploring the signal of dopamine neuro

101 seem to modulate the precision attributed to prediction errors, favoring the selective updating of pr

102 Barrett Universal II formula had the lowest prediction error for the 2 IOL models studied.

103 Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes w

104 Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compa

105 n phasic dopamine, acting as a reinforcement prediction error, gates plasticity at cortico-striatal s

106 whereas mispredicted stimuli may induce both prediction error generated by prediction that is not per

107 ated by prediction that is not perceived and prediction error generated by sensory input that is not

108 Therefore, the consequences of prediction error go beyond memory weakening.

109 Consistent with the "prediction error" hypothesis, activation was significant

110 ue is decreased because of a negative reward prediction error (i.e., the animal receives less than ex

111 This is thought to be mediated by prediction errors (i.e., the difference between expectat

112 er neural responses associated with Bayesian prediction errors, i.e. the difference between actual an

113 tive values correspond to precision-weighted prediction errors, (iii) and contextual information unfo

114 ying true models and reducing estimation and prediction error in a number of simulation studies.

115 ting pain were consistent with an appetitive prediction error in both groups.

116 ated in a manner consistent with an aversive prediction error in individuals who learned predominantl

117 x are best accounted for by a model in which prediction error in one object feature spreads to other

118 li and food outcomes and computes a negative prediction error in Pavlovian conditioning.

119 view that the LHb promotes a negative reward prediction error in Pavlovian conditioning.SIGNIFICANCE

120 rror; another is that each neuron calculates prediction error in the same way.

121 ral signals of both learning rate and reward prediction error in the ventral striatum, and the signal

122 we find a relative predominance of expected prediction errors in dACC, instantaneous prediction erro

123 ls in the ventromedial prefrontal cortex and prediction errors in the striatum were similarly biased

124 ted prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice sig

125 that the PFC can suppress the expression of prediction errors in the VS.

126 e anterior cingulate cortex signalled social prediction errors in typically developing individuals, t

127 member elicits a classical learning signal (prediction error) in the anterior insular cortex.

128 or the SN60WF, the standard deviation of the prediction error, in order of lowest to highest, was the

129 e learning and memory, including motivation, prediction error, incentive salience, memory consolidati

130 ggered, it is likely that different kinds of prediction errors (including interoceptive/affective) ne

131 three independent cohorts by calculating the prediction error (integrated Brier score), and concordan

132 hanism by which the brain transforms sensory prediction errors into corrective motor commands is the

133 associated with a reduced reward expectancy-prediction error inverse relationship, even after contro

134 om high-dimensional biological data with low prediction error is an important challenge of statistica

135 This suggests that the valence of prediction error is more important than the valence of t

136 However, this effect of prediction error is only observed during late processing

137 Moreover, the precision of prediction errors is thought to be modulated by attentio

138 to quantify explore-exploit strategy use and prediction error magnitude.

139 ng rate, and formally mediated the effect of prediction-error magnitude on learning rate.

140 as neuronal enhancement and the unpredicted prediction error manifested as neuronal attenuation on t

141 ative to predicted stimuli, the mispredicted prediction error manifested as neuronal enhancement and

142 individual cases and singular sectors, high prediction errors may occur.

143 orts and show that the mesolimbic confidence prediction error modulation derived through the model pr

144 Mean prediction error (MPE) and root mean squared prediction

145 N/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smalle

146 -validation resulted in a R(2) of 0.57 and a prediction error of 4.4 mg TOC L(-1).

147 the independent data set, with a mean As RBA prediction error of 5.4%.

148 ic brain areas encoded both anticipation and prediction error of confidence-in remarkable similarity

149 rnal neural activation pattern may reflect a prediction error of the brain, where rewards at unexpect

150 nectomes that provide better cross-validated prediction error of the diffusion MRI data than optimize

151 Prediction error of the implanted IOL was <1.00 diopter

152 variety of contexts; however, the inevitable prediction errors of GRNs hinder optimal data mining of

153 hese results suggest that precision-weighted prediction errors of stimulus locations and motor respon

154 el calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median fo

155 and compare the framework's cross-validated prediction error on historical data to that of a variety

156 ltivars at both growing sites) gave relative prediction errors on anthocyanin content less than 14.1%

157 Thus, although neurons carrying sensory prediction error or feedback signals show attenuated mod

158 othetical rewards, which may reflect greater prediction error or regret emotion after real monetary l

159 Currently only the average prediction error or the ratio of performance to deviatio

160 nce decision-making, either by gating reward prediction errors or by modifying an implicit representa

161 opamine neurons are thought to signal reward prediction error, or the difference between actual and p

162 ns facilitate learning by calculating reward prediction error, or the difference between expected and

163 whether the representation of reinforcement prediction error (PE) (the difference between received a

164 del and then used trial-by-trial S-C and S-R prediction error (PE) estimates in model-based behaviora

165 For example, prediction error (PE) models suggest a role of learning,

166 The IOL prediction error (PE) was obtained by subtracting the pr

167 comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs.

168 ithms in artificial intelligence: the reward prediction error (PE)-the difference between how rewardi

169 states, such as pain, cognitive control, and prediction error (PE).

170 the internal and external validations as the prediction errors (%PE) for Cmax and AUC were less than

171 nt of prediction error's extent more than by prediction error per se.

172 d less by predictions themselves and more by prediction errors per se, and this relationship scales w

173 Here we show that prediction errors (PEs) coded by the striatum support co

174 Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable

175 show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, w

176 outcomes are better than predicted (positive prediction errors [PEs]) and decreased for worse than pr

177 he predicted and actual outcomes of actions (prediction errors [PEs]).

178 t this is associated with the suppression of prediction error processing in the ventral striatum by t

179 tal conceptual processes, which can suppress prediction error processing in the VS and lead to reduce

180 that this is mediated by the suppression of prediction error processing through the prefrontal corte

181 dopamine neurons themselves calculate reward prediction error, rather than inherit it passively from

182 ctivation for aversive outcomes and aversive prediction errors; reduced willingness to expend effort

183 roup exhibited greater brain response 1) for prediction error regression within the caudate, ventral

184 behavioral benefit was related to heightened prediction error-related BOLD activity in the hippocampu

185 The normal reward expectancy and prediction error-related ventral striatal reactivity inv

186 aptation of the learning rate, and coding of prediction errors relative to reward variability.

187 ptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD

188 Prediction error response could be a neurobiological mar

189 Greater caudate prediction error response when underweight was associate

190 y correlated positively with ventral caudate prediction error response.

191 Vulnerability modulated the expression of prediction error responses in anterior insula and insula

192 pants during an auditory paradigm identified prediction error responses in bilateral primary auditory

193 antity known to be substantially affected by prediction errors resulting from the outcomes of risky c

194 ver a restricted spectral range gave a lower prediction error (RMSEC=0.86% vs 1.06%, for HgCdTe and I

195 prediction error (MPE) and root mean squared prediction error (RMSPE) for daily predictions are 1.78

196 Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 mug/m(3).

197 The resulted prediction errors (root mean square error of cross-valid

198 centration are considered to encode a reward prediction error (RPE) in reinforcement learning tasks.

199 as well as Q-learning, an established reward-prediction error (RPE) model.

200 forcement learning mechanisms using a reward prediction error (RPE) signal (the difference between ac

201 second laboratory stress paradigm on reward prediction error (RPE) signaling in the ventral striatum

202 e (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in assoc

203 Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward.

204 tween actual and predicted reward, or reward prediction error (RPE).

205 es to test whether both decisions and reward prediction errors (RPE) in the absence of choice violate

206 e, signaled via dopaminergic positive reward prediction error (+RPE) and negative reward-prediction e

207 prediction error (+RPE) and negative reward-prediction error (-RPE) signals, respectively.

208 ates how incorrect a prediction was ("reward prediction error," RPE).

209 ine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual

210 eled as a monolithic process in which reward prediction errors (RPEs) are used to update expected val

211 ociated with deficits in representing reward prediction errors (RPEs), which are the difference betwe

212 encoding of teaching signals such as reward prediction errors (RPEs).

213 ant stimuli is elicited by the assessment of prediction error's extent more than by prediction error

214 scent group, encoding of own preferences and prediction errors scaled with parent-reported social tra

215 st models of RL assume that the dopaminergic prediction error signal drives plasticity in frontal-str

216 pathy-related insula responses by the neural prediction error signal was mediated by an establishment

217 e actually experience, our brains generate a prediction error signal, so that we can map stimuli to r

218 h dopamine neuron to contribute fully to the prediction error signal.

219 ce errors independently of a negative reward prediction error signal.

220 prediction signal shapes the dopamine reward prediction error signal.

221 demonstrate a causal link between disrupted prediction error signaling and inefficient learning in s

222 gs to establish a causal link between faulty prediction error signaling and learning deficits in schi

223 The results describe a novel mode of prediction error signaling by ACC neurons that is associ

224 ror-related negativity), a putative index of prediction error signaling in the brain.

225 Theories of schizophrenia implicate abnormal prediction error signaling in the cognitive deficits of

226 ing rate, as well as the neural signature of prediction error signaling, in patients to a level quant

227 sic changes in dopamine activity with reward prediction error signaling.

228 how this plasticity is driven by a striatal "prediction error," signaling the discrepancy between the

229 Punishment prediction error signalling in offenders with antisocial

230 Importantly, the degree to which social prediction error signalling was aberrant correlated with

231 y supported a model that assumes a mixing of prediction error signals across features: surprise in on

232 appears to be involved in generating reward-prediction error signals and inhibition of motivated beh

233 maging analyses to identify neural coding of prediction error signals driving motivational learning.

234 tly learned and that this is associated with prediction error signals in the ventral striatum (VS) in

235 y, we observed significantly stronger neural prediction error signals in the VS in the stimulus conte

236 , we found preliminary evidence that sensory prediction error signals may be positively signed for st

237 Amplifying ascending sensory prediction error signals may optimize stimulus detection

238 ision variables and was inversely related to prediction error signals thought to underlie model-free

239 Whereas model-free prediction error signals were preserved, alcohol-depende

240 test whether the coordination of VTA reward prediction error signals with these replayed spatial seq

241 neurons serve as full-fledged bidirectional prediction error signals.

242 Prediction-error signals consistent with formal models o

243 To test for the presence of these prediction-error signals in the brain, we scanned human

244 reward are dissociable and that dopaminergic prediction-error signals rely on the ventral striatum fo

245 presentations of subjective value, such that prediction errors simultaneously update multiple agents'

246 l cortex code for perceptual predictions and prediction errors, supporting predictive coding theories

247 udicate between three possible ways in which prediction error (surprise) in the processing of one fea

248 Successful predictions remain implicit; only prediction errors ("surprises") attract consciousness.

249 The state-value-prediction error (SVPE), which is independent of actions

250 The median of prediction errors (symmetric mean absolute percent error

251 This expected reward is used to form a prediction error that correlates with the trial-by-trial

252 s sent backward from higher levels result in prediction errors that are fed forward from lower levels

253 ell established role in reporting appetitive prediction errors that are widely considered in terms of

254 timized to dissociate the subtypes of reward-prediction errors that function as the key computational

255 es fluctuations in self-esteem engendered by prediction errors that quantify the difference between e

256 h sensory afferent inputs to compute sensory prediction errors that then modify locomotor circuits to

257 ught to encode novelty in addition to reward prediction error (the discrepancy between actual and pre

258 e an integration of RPEs with counterfactual prediction errors, the latter defined by how much better

259 In this theory, prediction errors-the difference between a predicted and

260 been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed

261 brief increases can substitute for positive prediction errors, there is no comparable evidence that

262 control with aperiodic sampling triggered by prediction error thresholds (IC).

263 istically by aperiodic sampling triggered by prediction error thresholds.

264 interactions modulate conscious detection of prediction error through top-down processes for the anal

265 nterval duration, and doesn't reflect reward prediction error, timing, or value as single factors alo

266 tamatergic neurons prevented use of negative prediction error to reduce fear learning, leading to sig

267 f BLA glutamatergic neurons disrupted use of prediction error to regulate fear learning.

268 mple fear learning is unaffected, the use of prediction error to regulate this learning is profoundly

269 ror-driven learning benefits from scaling of prediction errors to reward variability.

270 Reward prediction errors underlie learning of values in reinfor

271 Using sensory preconditioning, we show that prediction errors underlying stimulus-stimulus learning

272 nger than predicted in RPLC exhibit negative prediction errors using an additive HILIC model.

273 The prediction errors using partial least squares discrimina

274 However, whether or not the prediction error valence also affects counterfactual lea

275 putational model that was adapted to test if prediction error valence influences learning.

276 with wakefulness, a specific peak reflecting prediction error vanished during sleep.

277 acid (GABA)ergic neurons that mediate reward prediction error via inhibition of dopaminergic activity

278 ward contexts, dopamine neurons signal value prediction errors (VPEs) integrating information about b

279 Biometry prediction error was 1.11 diopters (D) for MFS and 1.33

280 Prediction error was defined as refractive error minus e

281 The prediction error was defined as the difference between t

282 A prediction error was generated on incongruent trials as

283 However, variability in model bias and prediction error was observed with significantly lower (

284 m spectrum disorder, the magnitude of social prediction errors was driven by input from the ventromed

285 To determine how dopamine neurons calculate prediction error, we combined optogenetic manipulations

286 Three PLS-discriminant models with low prediction errors were constructed.

287 tructure, encompassing the region where pain prediction errors were expressed, predicted participants

288 n the VTA of rats performing a task in which prediction errors were induced by shifting reward timing

289 the opposite valence-induced bias: negative prediction errors were preferentially taken into account

290 arning signals-the learned associability and prediction error-were correlated with fMRI brain respons

291 ve value corresponds to a precision-weighted prediction error, where predictions are based upon expec

292 with learning-based theories (such as reward prediction error) whereas in the shell, dopamine is cons

293 attribute this finding to a positive reward prediction error, whereby the animal perceives they rece

294 e that increasing attunement or reduction of prediction errors, which implies increasing validation o

295 should be strongly correlated and reflect a 'prediction error' while the spikes themselves are uncorr

296 itute of Health Stroke Scale alone regarding prediction error (Wilcoxon signed rank test, p < 0.001)

297 Main outcome measures were mean prediction errors with Hoffer Q, Holladay 1, Holladay 2,

298 t daily reward response represents a type of prediction error, with neural reward activation relative

299 There were frequent GFT prediction errors, with correlation ranging from r = -0.

300 ral representations of reward and punishment prediction errors within the ventral striatum and anteri