Music can be reconstructed from human auditory cortex activity using nonlinear decoding models.

Music is core to human experience, yet the precise neural dynamics underlying music perception remain unknown. We analyzed a unique intracranial electroencephalography (iEEG) dataset of 29 patients who listened to a Pink Floyd song and applied a stimulus reconstruction approach previously used in the speech domain. We successfully reconstructed a recognizable song from direct neural recordings and quantified the impact of different factors on decoding accuracy. Combining encoding and decoding analyses, we found a right-hemisphere dominance for music perception with a primary role of the superior temporal gyrus (STG), evidenced a new STG subregion tuned to musical rhythm, and defined an anterior-posterior STG organization exhibiting sustained and onset responses to musical elements. Our findings show the feasibility of applying predictive modeling on short datasets acquired in single patients, paving the way for adding musical elements to brain-computer interface (BCI) applications.

Dynamic expectations: Behavioral and electrophysiological evidence of sub-second updates in reward predictions.

Expectations are often dynamic: sports fans know that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here we present behavioral and electrophysiological evidence of sub-second changes in expectations using slot machines as a case study. In Study 1, we demonstrate that EEG signal before the slot machine stops varies based on proximity to winning. Study 2 introduces a behavioral paradigm to measure dynamic expectations via betting, and shows that expectation trajectories vary as a function of winning proximity. Notably, these expectation trajectories parallel Study 1's EEG activity. Studies 3 (EEG) and 4 (behavioral) replicate these findings in the loss domain. These four studies provide compelling evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our research opens promising avenues for understanding the dynamic nature of reward expectations and their impact on cognitive processes.

Electrophysiological signatures of inequity-dependent reward encoding in the human OFC.

Social decision making requires the integration of reward valuation and social cognition systems, both dependent on the orbitofrontal cortex (OFC). How these two OFC functions interact is largely unknown. We recorded intracranial activity from the OFC of ten patients making choices in a social context where reward inequity with a social counterpart varied and could be either advantageous or disadvantageous. We find that OFC high-frequency activity (HFA; 70-150 Hz) encodes self-reward, consistent with previous reports. We also observe encoding of the social counterpart's reward, as well as the type of inequity being experienced. Additionally, we find evidence of inequity-dependent reward encoding: depending on the type of inequity, electrodes rapidly and reversibly switch between different reward-encoding profiles. These results provide direct evidence for encoding of self- and other rewards in the human OFC and highlight the dynamic nature of encoding in the OFC as a function of social context.

Dynamic expectations: Behavioral and electrophysiological evidence of sub-second updates in reward predictions.

Expectations are often dynamic: any sports fan knows that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here, using slot machines as a case study, we provide parallel behavioral and electrophysiological evidence of sub-second moment-to-moment changes in expectations. In Study 1, we show that the dynamics of the EEG signal before the slot machine stopped differed depending on the nature of the outcome, including not only whether the participant won or lost, but also how close they came to winning. In line with our predictions, Near Win Before outcomes (the slot machine stops one item before a match) were similar to Wins, but different than Near Win After (the machine stops one item after a match) and Full Miss (the machine stops two or three items from a match). In Study 2, we designed a novel behavioral paradigm to measure moment-to-moment changes in expectations via dynamic betting. We found that different outcomes also elicited unique expectation trajectories in the deceleration phase. Notably, these behavioral expectation trajectories paralleled Study 1's EEG activity in the last second prior to the machine's stop. In Studies 3 (EEG) and 4 (behavior) we replicated these findings in the loss domain where a match entails a loss. Again, we found a significant correlation between behavioral and EEG results. These four studies provide the first evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our findings open up new avenues for studying the ongoing dynamics of reward expectations and their role in healthy and unhealthy cognition.

Gender bias in academia: A lifetime problem that needs solutions.

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.

Alternative outcomes create biased expectations regarding the received outcome: Evidence from event-related potentials.

After choosing between uncertain options, one might get feedback on both the outcome of the chosen option and the outcome of the unchosen option (the alternative). Behavioral research has shown that in such cases people engage in outcome comparison, and that the alternative outcome influences the way one evaluates his own received outcome. Moreover, this influence differs whether one was responsible or not for the choice made. In two studies, we looked for the electrophysiological correlates of outcome comparison. Subjects chose one of two boxes shown on the screen, each box contained a gain or a loss. The alternative outcome was always revealed first, followed by the received outcome. In half of the trials the software picked one box instead of subjects. We tested whether the feedback-related negativity (FRN) and the P3 elicited by the received reflect outcome comparison. As expected, we found that the FRN and P3 were more positive when the received outcome was a gain (vs. a loss). The FRN and P3 were also sensitive to the value of the alternative outcome, but contrary to our predictions, they were more positive when the alternative outcome was a gain (vs. a loss). As the FRN and P3 are sensitive to expectations, we hypothesized that our findings might result from subjects' biased expectations: subjects might have wrongly believed that a good (bad) alternative outcome signaled a bad (good) received outcome. This hypothesis, coined as the Alternative Omen Effect, was confirmed in parallel in a series of behavioral experiments: people see an illusory negative correlation between the uncorrelated outcomes of choice options (reported in Marciano-Romm et al. (2016)). A challenge for future research will be to disentangle the effects of expectation from those of outcome comparison.

LPS induces the interaction of a transcription factor, LPS-induced TNF-alpha factor, and STAT6(B) with effects on multiple cytokines.

TNF-alpha is a pivotal cytokine whose overproduction can be lethal. Previously, we identified a transcription factor, LPS-induced TNF-alpha factor (LITAF), that regulates TNF-alpha transcription. We now report the discovery and characterization of a regulatory cofactor that we call signal transducer and activator of transcription (STAT) 6(B) because of its considerable homology to STAT6 [here referred to as STAT6(A)]. The STAT6(B) gene expression was found to be activated by LPS. Furthermore, we show that cotransfection of STAT6(B) and LITAF induces an interaction between the two proteins, consequently forming a complex that subsequently translocates into the nucleus and up-regulates the transcription of cytokines. The effect of the complex on a panel of cytokines was tested. In addition, the specific role of LITAF in this complex was established with experiments, including RNA interference technology. Overall, these findings describe roles for LITAF, STAT6(B), and the LITAF-STAT6(B) complex in the regulation of inflammatory cytokines in response to LPS stimulation in mammalian cells.