bioRxiv ScienceSearch

bioRxiv · 10.1101/2020.10.08.330654

Electrophysiological investigation of reward anticipation and outcome evaluation during slot machine play

Abstract

Slot machines are a popular form of gambling, offering a tractable way to experimentally model reward processes. This study used a 3-reel slot paradigm to assess psychologically distinct phases of reward processing, reflecting anticipation, and early and late-stage outcome processing. EEG measures of winning, nearly missing (a losing outcome revealed at the final, third reel), and "totally" missing (a losing outcome revealed earlier, at the second reel) were collected from healthy adults (n=54). Condition effects were evaluated in: i) event-related potential (ERP) components reflecting anticipatory attention (stimulus preceding negativity, SPN) and outcome processing (reward positivity, RewP and late-positive potential, LPP) and ii) total power and phase synchrony of theta and delta band oscillations. Behaviorally, trial initiation was fastest after a near miss outcome and slowest after a winning outcome. As expected, a significant SPN was observed for possible wins (AA) vs. total misses (AB), consistent with reward anticipation. In addition, significantly larger win (AAA) vs. near miss (AAB) amplitudes were observed for the RewP and LPP to wins and LPP to near misses (vs. total misses) reflecting early and late-stage outcome processing effects. There was an effect of reel position on the RewP, with larger effects in the final reel (AAA-AAB) relative to the 2nd-reel locked difference waves (AA-AB). Across all outcomes, near misses elicited the largest and most phase-synchronized theta responses, while wins elicited larger and more phase-synchronized delta responses than total misses, with near misses not differing from wins or total misses. Phase locking measures contrasting win vs. near miss delta and theta synchronization, within time windows corresponding to ERP measurements, covaried with RewP, but not SPN or LPP, amplitude. Lastly, EEG measures showed differential relationships with age and self-reported consummatory pleasure. In the context of slot machine play, where reward anticipation and attainment place minimal demands on effort and skill, ERP and time-frequency methods capture distinct neurophysiological signatures of reward anticipation and outcome processing.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fryer, S. L., Roach, B. J., Holroyd, C., Paulus, M., Sargent, K., Boos, A., Ford, J., Mathalon, D. H.. 2020-10-08. Electrophysiological investigation of reward anticipation and outcome evaluation during slot machine play. https://doi.org/10.1101/2020.10.08.330654

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience