Neural Prediction Errors Reveal a Risk-Sensitive Reinforcement-Learning Process in the Human Brain

Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric–psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms

Simulating Responses of Gravitational-Wave Instrumentation

Synthetic LISA is a computer program for simulating the responses of the instrumentation of the NASA/ESA Laser Interferometer Space Antenna (LISA) mission, the purpose of which is to detect and study gravitational waves. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the time-delay-interferometry (TDI) observables. (TDI is a method of canceling phase noise in temporally varying unequal-arm interferometers.) Synthetic LISA provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI (including the motion of the LISA array and the temporal and directional dependence of the arm lengths). Synthetic LISA is written in the C++ programming language as a modular package that accommodates the addition of code for specific gravitational wave sources or for new noise models. In addition, time series for waves and noises can be easily loaded from disk storage or electronic memory. The package includes a Python-language interface for easy, interactive steering and scripting. Through Python, Synthetic LISA can read and write data files in Flexible Image Transport System (FITS), which is a commonly used astronomical data format

Perceptions and understanding of research situations as a function of consent form characteristics and experimenter instructions

Two studies examined how research methodology affected participant behaviors. Study 1 tested (a) consent form perspective (1st, 2nd, or 3rd person) and (b) information on participants’ right to sue upon perceptions of coercion, ability to recall consent information, and performance on experimental tasks. Unexpectedly, participants who received instructions without the right to sue information had significantly better recall of their research rights. Study 2 manipulated (a) consent form complexity (presence or absence of jargon) and (b) the detail of verbal instructions (simple, elaborate); participants who received a consent form with simpler language spent more time on a difficult task, and participants in the elaborate instruction condition recalled more details. Together, these studies suggest (a) explaining the right to sue may actually be counterproductive; (b) providing a more detailed explanation may help participants remember procedural details; and (c) using jargon may decrease task performance

Sex Differences in Jealousy in Response to Actual Infidelity

The present studies address two criticisms of the theory of evolved sex differences in jealousy: (a) that the sex difference in jealousy emerges only in response to hypothetical infidelity scenarios, and (b) that the sex difference emerges only using forced-choice measures. In two separate studies, one a paper-and-pencil survey with a student sample and the other a web-based survey targeting a non-student sample, men and women showed significant sex differences in jealousy in response to actual infidelity experiences; men experienced more jealousy in response to the sexual aspects of an actual infidelity, whereas women experienced more jealousy in response to the emotional aspects of the infidelity. Sex differences emerged using both continuous measures of jealousy as well as the traditional forced-choice measure. Overall, our results demonstrate that sex differences in jealousy are not limited to responses to hypothetical infidelity scenarios; they also emerge in response to actual infidelity experiences