Memory Retrieval from First Principles.

The dilemma that neurotheorists face is that (1) detailed biophysical models that can be constrained by direct measurements, while being of great importance, offer no immediate insights into cognitive processes in the brain, and (2) high-level abstract cognitive models, on the other hand, while relevant for understanding behavior, are largely detached from neuronal processes and typically have many free, experimentally unconstrained parameters that have to be tuned to a particular data set and, hence, cannot be readily generalized to other experimental paradigms. In this contribution, we propose a set of "first principles" for neurally inspired cognitive modeling of memory retrieval that has no biologically unconstrained parameters and can be analyzed mathematically both at neuronal and cognitive levels. We apply this framework to the classical cognitive paradigm of free recall. We show that the resulting model accounts well for puzzling behavioral data on human participants and makes predictions that could potentially be tested with neurophysiological recording techniques.

A backside fluorine-functionalized graphene layer for ammonia detection.

Graphene is a remarkable material with the best surface to volume ratio as a result of its 2D nature, which implies that every atom can be considered as a surface one. These features make graphene attractive for use as a sensing material; however, the limiting factor is the chemical inertness of pristine graphene. Here we propose a method to create reactive centers by removal of fluorine atoms from the outer surface of fluorinated graphene while preserving the backside fluorination. Such partially recovered graphene layers were produced by the action of hydrazine-hydrate vapor on initially non-conducting fluorinated graphite. The reduction degree of the material and its electrical response revealed upon ammonia exposure were controlled by measuring the surface conductivity. We showed experimentally that the sensing properties depend on the reduction degree and found the correlation of the adsorption energy of ammonia with the number of residual fluorine atoms by the use of quantum-chemical calculations.

Temporal scaling of neural responses to compressed and dilated natural speech.

Different brain areas integrate information over different timescales, and this capacity to accumulate information increases from early sensory areas to higher order perceptual and cognitive areas. It is currently unknown whether the timescale capacity of each brain area is fixed or whether it adaptively rescales depending on the rate at which information arrives from the world. Here, using functional MRI, we measured brain responses to an auditory narrative presented at different rates. We asked whether neural responses to slowed (speeded) versions of the narrative could be compressed (stretched) to match neural responses to the original narrative. Temporal rescaling was observed in early auditory regions (which accumulate information over short timescales) as well as linguistic and extra-linguistic brain areas (which can accumulate information over long timescales). The temporal rescaling phenomenon started to break down for stimuli presented at double speed, and intelligibility was also impaired for these stimuli. These data suggest that 1) the rate of neural information processing can be rescaled according to the rate of incoming information, both in early sensory regions as well as in higher order cortexes, and 2) the rescaling of neural dynamics is confined to a range of rates that match the range of behavioral performance.