Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making.

Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making.

Neurochemical and functional interactions for improved perceptual decisions through training.

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task.

A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study.

Background: The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the forefront as a promising solution for the rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies.

Functional Interactions between Sensory and Memory Networks for Adaptive Behavior.

The brain's capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown.

Fine-scale computations for adaptive processing in the human brain.

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs.

White-Matter Pathways for Statistical Learning of Temporal Structures.

Extracting the statistics of event streams in natural environments is critical for interpreting current events and predicting future ones. The brain is known to rapidly find structure and meaning in unfamiliar streams of sensory experience, often by mere exposure to the environment (i.e.

Functional brain networks for learning predictive statistics.

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e.