Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances

Valid population inference for information-based imaging: From the second-level t-test to prevalence inference

In multivariate pattern analysis of neuroimaging data, ‘second-level’ inference is often performed by entering classification accuracies into a t-test vs chance level across subjects. We argue that while the random-effects analysis implemented by the t-test does provide population inference if applied to activation differences, it fails to do so in the case of classification accuracy or other ‘information-like’ measures, because the true value of such measures can never be below chance level. This constraint changes the meaning of the population-level null hypothesis being tested, which becomes equivalent to the global null hypothesis that there is no effect in any subject in the population. Consequently, rejecting it only allows to infer that there are some subjects in which there is an information effect, but not that it generalizes, rendering it effectively equivalent to fixed-effects analysis. This statement is supported by theoretical arguments as well as simulations. We review possible alternative approaches to population inference for information-based imaging, converging on the idea that it should not target the mean, but the prevalence of the effect in the population. One method to do so, ‘permutation-based information prevalence inference using the minimum statistic’, is described in detail and applied to empirical data

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

An examination of the relationship between shame, guilt and self-harm: A systematic review and meta-analysis

Self-harm is a major public health concern associated with suicide risk and significant psychological distress. Theories suggest that aversive emotional states are an important process that drives self-harm. Shame and guilt may , in particular, be important emotions in self-harm. This review therefore sought to provide a systematic review and meta-analysis of the relationship between shame, guilt, and self-harm. A systematic search of electronic databases (PsycINFO; Medline; CINAHL Plus; Web of Science and ProQuest) was undertaken to identify studies measuring shame, guilt and self-harm (including suicidal and non-suicidal behaviour). Meta-analysis was undertaken where papers focused on the same subtype of shame or guilt and shared a common outcome. Thirty studies were identified for inclusion. Most forms of shame were associated with non-suicidal self-injury (NSSI), but research was sparse concerning suicidal behaviour. Fewer studies examined guilt and findings were more varied. Methodological issues included a paucity of longitudinal designs and lack of justification for sample sizes. Results of this review support the link between shame and self-harm, particularly NSSI. The direction of this relationship is yet to be established. Clinically, consideration should be given to the role of shame amongst individuals who present with NSSI. This review was pre-registered on PROSPERO (CRD42017056165)

The US Program in Ground-Based Gravitational Wave Science: Contribution from the LIGO Laboratory

Recent gravitational-wave observations from the LIGO and Virgo observatories have brought a sense of great excitement to scientists and citizens the world over. Since September 2015,10 binary black hole coalescences and one binary neutron star coalescence have been observed. They have provided remarkable, revolutionary insight into the "gravitational Universe" and have greatly extended the field of multi-messenger astronomy. At present, Advanced LIGO can see binary black hole coalescences out to redshift 0.6 and binary neutron star coalescences to redshift 0.05. This probes only a very small fraction of the volume of the observable Universe. However, current technologies can be extended to construct "3rd Generation" (3G) gravitational-wave observatories that would extend our reach to the very edge of the observable Universe. The event rates over such a large volume would be in the hundreds of thousands per year (i.e. tens per hour). Such 3G detectors would have a 10-fold improvement in strain sensitivity over the current generation of instruments, yielding signal-to-noise ratios of 1000 for events like those already seen. Several concepts are being studied for which engineering studies and reliable cost estimates will be developed in the next 5 years

Mechanisms of Age-Related Changes in ER (MARCER)

temporary placeholder for the MARCER projec

Frontoparietal pattern similarity analyses of cognitive control in monozygotic twins

Supplementary materials for "Frontoparietal pattern similarity analyses of cognitive control in monozygotic twins"