Distributed Cortical Regions for the Recall of People, Places, and Objects.

The human medial parietal cortex (MPC) is recruited during multiple cognitive processes. Previously, we demonstrated regions specific to recall of people or places and proposed that the functional organization of MPC mirrors the category selectivity defining the medial-lateral axis of the ventral-temporal cortex (VTC). However, prior work considered recall of people and places only, and VTC also shows object selectivity sandwiched between face- and scene-selective regions.

A Molecular Engineering Approach to Conformationally Regulated Conductance Dualism in a Molecular Junction.

One key aspect for the development of functional molecular electronic devices is the ability to precisely tune and reversibly switch the conductance of individual molecules in electrode-molecule-electrode junctions in response to external stimuli. In this work, we present a new approach to access molecular switches by deliberately controlling the flexibility in the molecular backbone. We here describe two new conductance switches based on bis(triarylamines) that rely on the reversible toggling between two conformers, each associated with vastly different conductances.

Centering cognitive neuroscience on task demands and generalization.

Cognitive neuroscience seeks generalizable theories explaining the relationship between behavioral, physiological and mental states. In pursuit of such theories, we propose a theoretical and empirical framework that centers on understanding task demands and the mutual constraints they impose on behavior and neural activity. Task demands emerge from the interaction between an agent's sensory impressions, goals and behavior, which jointly shape the activity and structure of the nervous system on multiple spatiotemporal scales.

Exploring the Limitations of Hybrid Adiabatic Quantum Computing for Emission Tomography Reconstruction.

Our study explores the feasibility of quantum computing in emission tomography reconstruction, addressing a noisy ill-conditioned inverse problem. In current clinical practice, this is typically solved by iterative methods minimizing a L2 norm. After reviewing quantum computing principles, we propose the use of a commercially available quantum annealer and employ corresponding hybrid solvers, which combine quantum and classical computing to handle more significant problems.