New frontiers in cognitive neuroscience research have emerged from investigations that integrate data at different spatial and temporal scales. A wide range of neuroimaging techniques are employed by cognitive neuroscientists for measuring or inferring neural activity, as well as techniques for determining neuroanatomical structure-function relationships (e.g., fMRI, EEG, MEG, TMS). Electrocorticography (ECoG) and experimental interventions in human neural function, including stimulation and manipulation techniques combined with neuroimaging, have advanced the field. Additional recent methodological advances include machine-learning and multivariate analysis methods, resting-state and task-based connectomics and large-scale data analysis used to investigate and infer functional mechanisms, as well as multimodal neuroimaging and model-based approaches, wherein computational cognitive models may directly inform neuroimaging results.
The Cognitive Neuroscience Program seeks highly innovative proposals aimed at advancing a rigorous understanding of the neural mechanisms of human cognition. Central research topics for consideration by the program include attention, learning, memory, decision-making, language, social cognition, and emotions. Proposals with animal models are appropriate only if they include a comparative element with human subjects.
Proposals focused on behavioral, clinical or molecular mechanisms will not be considered for this program. Additionally, proposals directed at understanding low-level sensorimotor processes or restricted to model-based simulations of neural data will not be considered, unless they are embedded in a cognitive question related to one of the central research topics listed above.