Biology subjects

Rogers, D. A.

Publications and source records attributed to Rogers, D. A..

3 recordsLinked to original sources

bioRxiv2025

The absent P3a. Performance monitoring ERPs differentiate trust in humans and autonomous systems.

To address suggestions that human brain responses to autonomous system errors may be used as brain-based measures of trust in automation, the present study asked participants to monitor the performance of either a virtual human or an autonomous system partner performing a novel, complex, real-world image classification task. We predicted visual feedback of partner errors would elicit the feedback-related negativity and P3 ERP components, and that these components would differ between the human and system groups. Behavioural results showed that while participants calibrated their trust in their partner according to our intended manipulation of error rates, no group differences were found. The ERP data, however, revealed FRN and P3 effects for both groups, modulated by accuracy and error rate. An unexpected finding was that the P3 topography differed between groups, with both a frontal P3a and posterior P3b component seen for the human condition, while for the system condition only the posterior P3b was observed and the P3a was completely absent. We suggest that this selective absence of the P3a may reflect reduced frontal attention during system monitoring in passive task conditions potentially resulting from reduced social and emotional processing for the system partner. This study demonstrates the potential for EEG-based measures of trust in automation to surpass the sensitivity of traditional measures of trust, while additionally uncovering a potential neural signature of automation complacency in the absent P3a. This identifies potential boundary conditions under which the application of human correlates of performance monitoring may not apply to the monitoring of an automated system.

neuroscience↗

bioRxiv2023

Functional traits fail to predict long-term responses to climate change

AimEnvironmental conditions strongly affect the distribution and abundance of species via complex forces. Shifts in environmental conditions and differences in the speed and scale of these effects complicate our efforts to infer how species will respond to future environmental change. We test how 18 functional traits affect plant species responses to gradients in environmental conditions and 50-year shifts in climate. LocationWe analyzed 50-year shifts in the distribution and abundance of 153 plant species distributed across 284 sites in Wisconsin, USA. Time period1950s to 2000s. Major taxa studiedVascular plants (much of the flora of NE North America). MethodsWe used random forest and integrated hierarchical mixed models to test how plant abundances (and 50-year changes in abundance) track gradients in overstory, soil, and climatic conditions. ResultsWithin study periods, plant abundances reflect gradients in environmental conditions. Leaf traits affected local abundance (both directly and via trait-environment interactions) in the 1950s and 2000s. Strong soil and temperature effects in the 1950s have weakened while precipitation effects have strengthened. Although we expected these models to also predict how plants would respond to shifts in climate, they did not. Main conclusionsLags in species responses, increases in the stochastic forces affecting community assembly, and other forces limit the ability of models fitted to static data (e.g., space-for-time substitutions) to predict how plant species will respond to long-term shifts in environmental conditions. We must therefore be cautious about applying trait-based species distribution models to predict how climate change will affect species distributions and community structure.

ecology↗

bioRxiv2021

AD Informer Set: Chemical tools to facilitate Alzheimer's disease drug discovery

IntroductionThe portfolio of novel targets to treat Alzheimers disease (AD) has been enriched by the AMP-AD program. MethodsA cheminformatics-driven effort enabled identification of existing small molecule modulators for many protein targets nominated by AMP-AD and suitable positive control compounds to be included in the set. ResultsWe have built an annotated set of 171 small molecule modulators, including mostly inhibitors, targeting 98 unique proteins that have been nominated by AMP-AD consortium members as novel targets for AD treatment. These small molecules vary in their quality and should be considered chemical tools that can be used in efforts to validate therapeutic hypotheses, but which would require further optimization. A physical copy of the AD Informer Set can be ordered via the AD Knowledge Portal. DiscussionSmall molecule tools that enable target validation are important tools for the translation of novel hypotheses into viable therapeutic strategies for AD.

neuroscience↗