Sensory-organ-like response determines the magnetism of zigzag-edged honeycomb nanoribbons

We present an analytical effective theory for the magnetic phase diagram for zigzag-edge terminated honeycomb nanoribbons described by a Hubbard model with an interaction parameter U. We show that the edge magnetic moment varies as ln U and uncover its dependence on the width W of the ribbon. The physics of this owes its origin to the sensory-organ-like response of the nanoribbons, demonstrating that considerations beyond the usual Stoner-Landau theory are necessary to understand the magnetism of these systems. A first-order magnetic transition from an antiparallel orientation of the moments on opposite edges to a parallel orientation occurs upon doping with holes or electrons. The critical doping for this transition is shown to depend inversely on the width of the ribbon. Using variational Monte Carlo calculations, we show that magnetism is robust to fluctuations. Additionally, we show that the magnetic phase diagram is generic to zigzag-edge terminated nanostructures such as nanodots. Furthermore, we perform first-principles modeling to show how such magnetic transitions can be realized in substituted graphene nanoribbons. DOI: 10.1103/PhysRevB.87.085412

Sensory cues employed for the acquisition of familiarity-dependent recognition of a shoal of conspecifics by climbing perch (Anabas testudineus Bloch)

In this study we showed that a freshwater fish, the climbing perch (Anabas testudineus) is incapable of using chemical communication but employs visual cues to acquire familiarity and distinguish a familiar group of conspecifics from an unfamiliar one. Moreover, the isolation of olfactory signals from visual cues did not affect the recognition and preference for a familiar shoal in this species.

Deficits in sensory prediction are related to delusional ideation in healthy individuals.

Motor control strongly relies on neural processes that predict the sensory consequences of self-generated actions. Previous research has demonstrated deficits in such sensory-predictive processes in schizophrenic patients and these low-level deficits are thought to contribute to the emergence of delusions of control. Here, we examined the extent to which individual differences in sensory prediction are associated with a tendency towards delusional ideation in healthy participants. We used a force-matching task to quantify sensory-predictive processes, and administered questionnaires to assess schizotypy and delusion-like thinking. Individuals with higher levels of delusional ideation showed more accurate force matching suggesting that such thinking is associated with a reduced tendency to predict and attenuate the sensory consequences of self-generated actions. These results suggest that deficits in sensory prediction in schizophrenia are not simply consequences of the deluded state and are not related to neuroleptic medication. Rather they appear to be stable, trait-like characteristics of an individual, a finding that has important implications for our understanding of the neurocognitive basis of delusions.

Near optimal combination of sensory and motor uncertainty in time during a naturalistic perception-action task.

Most behavioral tasks have time constraints for successful completion, such as catching a ball in flight. Many of these tasks require trading off the time allocated to perception and action, especially when only one of the two is possible at any time. In general, the longer we perceive, the smaller the uncertainty in perceptual estimates. However, a longer perception phase leaves less time for action, which results in less precise movements. Here we examine subjects catching a virtual ball. Critically, as soon as subjects began to move, the ball became invisible. We study how subjects trade-off sensory and movement uncertainty by deciding when to initiate their actions. We formulate this task in a probabilistic framework and show that subjects' decisions when to start moving are statistically near optimal given their individual sensory and motor uncertainties. Moreover, we accurately predict individual subject's task performance. Thus we show that subjects in a natural task are quantitatively aware of how sensory and motor variability depend on time and act so as to minimize overall task variability.