Dynamic noise estimation: A generalized method for modeling noise fluctuations in decision-making.

Computational cognitive modeling is an important tool for understanding the processes supporting human and animal decision-making. Choice data in decision-making tasks are inherently noisy, and separating noise from signal can improve the quality of computational modeling. Common approaches to model decision noise often assume constant levels of noise or exploration throughout learning (e.

Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart.

Macaques preferentially attend to intermediately surprising information.

Normative learning theories dictate that we should preferentially attend to informative sources, but only up to the point that our limited learning systems can process their content. Humans, including infants, show this predicted strategic deployment of attention. Here, we demonstrate that rhesus monkeys, much like humans, attend to events of moderate surprisingness over both more and less surprising events.

Coevolution of motor cortex and behavioral specializations associated with flight and echolocation in bats.

Bats have evolved behavioral specializations that are unique among mammals, including self-propelled flight and echolocation. However, areas of motor cortex that are critical in the generation and fine control of these unique behaviors have never been fully characterized in any bat species, despite the fact that bats compose ∼25% of extant mammalian species. Using intracortical microstimulation, we examined the organization of motor cortex in Egyptian fruit bats (Rousettus aegyptiacus), a species that has evolved a novel form of tongue-based echolocation.

Sulcal depth in prefrontal cortex: a novel predictor of working memory performance.

The neuroanatomical changes that underpin cognitive development are of major interest in neuroscience. Of the many aspects of neuroanatomy to consider, tertiary sulci are particularly attractive as they emerge last in gestation, show a protracted development after birth, and are either human- or hominoid-specific. Thus, they are ideal targets for exploring morphological-cognitive relationships with cognitive skills that also show protracted development such as working memory (WM).

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal.

During adolescence, youth venture out, explore the wider world, and are challenged to learn how to navigate novel and uncertain environments. We investigated how performance changes across adolescent development in a stochastic, volatile reversal-learning task that uniquely taxes the balance of persistence and flexibility. In a sample of 291 participants aged 8-30, we found that in the mid-teen years, adolescents outperformed both younger and older participants.

What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and Neuroscience.

Reinforcement learning (RL) is a concept that has been invaluable to fields including machine learning, neuroscience, and cognitive science. However, what RL entails differs between fields, leading to difficulties when interpreting and translating findings. After laying out these differences, this paper focuses on cognitive (neuro)science to discuss how we as a field might over-interpret RL modeling results.

Ultradian rhythms in heart rate variability and distal body temperature anticipate onset of the luteinizing hormone surge.

The menstrual cycle is characterized by predictable patterns of physiological change across timescales. Although patterns of reproductive hormones across the menstrual cycle, particularly ultradian rhythms, are well described, monitoring these measures repeatedly to predict the preovulatory luteinizing hormone (LH) surge is not practical. In the present study, we explored whether non-invasive measures coupled to the reproductive system: high frequency distal body temperature (DBT), sleeping heart rate (HR), sleeping heart rate variability (HRV), and sleep timing, could be used to anticipate the preovulatory LH surge in women.

The effect of social rank feedback on risk taking and associated reward processes in adolescent girls.

The onset of adolescence is associated with an increased tendency to engage in risky behaviors and a developmental shift toward peers that contributes to increased prioritization for learning about and achieving social status. There is relatively little understanding about the specific links between these adolescent-typical phenomena, particularly regarding their neural underpinnings. Based on existing models that suggest the role of puberty in promoting adolescent status-seeking and risk-taking tendencies, we investigated the relation of pubertal hormones with behavioral and neural responses to status-relevant social information in the context of risk taking.

Risky decision-making in adolescent girls: The role of pubertal hormones and reward circuitry.

Adolescence is a developmental period characterized by a greater tendency to take risks. While the adult literature has shown that sex steroids influence reward-related brain functioning and risk taking, research on the role of these hormones during puberty is limited. In this study, we examined the relation between pubertal hormones and adolescent risk taking using a probabilistic decision-making task.

Alpha phase dynamics predict age-related visual working memory decline.

Alpha oscillations (7-14Hz) are modulated in response to visual temporal and spatial cues. However, the neural response to alerting cues is less explored, as is how this response is affected by healthy aging. Using scalp EEG, we examined how visual cortical alpha activity relates to working memory performance.

Suspected non-Alzheimer disease pathophysiology--concept and controversy.

Suspected non-Alzheimer disease pathophysiology (SNAP) is a biomarker-based concept that applies to individuals with normal levels of amyloid-β biomarkers in the brain, but in whom biomarkers of neurodegeneration are abnormal. The term SNAP has been applied to clinically normal individuals (who do not meet criteria for either mild cognitive impairment or dementia) and to individuals with mild cognitive impairment, but is applicable to any amyloid-negative, neurodegeneration-positive individual regardless of clinical status, except when the pathology underlying neurodegeneration can be reliably inferred from the clinical presentation. SNAP is present in ∼23% of clinically normal individuals aged >65 years and in ∼25% of mildly cognitively impaired individuals.

Dopamine modulates egalitarian behavior in humans.

Egalitarian motives form a powerful force in promoting prosocial behavior and enabling large-scale cooperation in the human species [1]. At the neural level, there is substantial, albeit correlational, evidence suggesting a link between dopamine and such behavior [2, 3]. However, important questions remain about the specific role of dopamine in setting or modulating behavioral sensitivity to prosocial concerns.