Ordering effect of Coulomb interaction in ballistic double-ring systems

We study a model of two concentric onedimensional rings with incommensurate areas $A_1$ and $A_2$, in a constant magnetic field. The two rings are coupled by a nonhomogeneous inter-ring tunneling amplitude, which makes the one-particle spectrum chaotic. For noninteracting particles the energy of the many-body ground state and the first excited state exhibit random fluctuations characterized by the Wigner-Dyson statistics. In contrast, we show that the electron-electron interaction orders the magnetic field dependence of these quantities, forcing them to become periodic functions, with period $\propto 1/(A_1 + A_2)$. In such a strongly correlated system the only possible source of disorder comes from charge fluctuations, which can be controlled by a tunable inter-ring gate voltage.Comment: 4 pages, 4 eps figures, revised text and new figures (as published

A dual role for prediction error in associative learning

Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance imaging and dynamic causal modeling (DCM) to furnish neurophysiological evidence that statistical associations are learnt, even when task-irrelevant. Subjects performed an audio-visual target-detection task while being exposed to distractor stimuli. Unknown to them, auditory distractors predicted the presence or absence of subsequent visual distractors. We modeled incidental learning of these associations using a Rescorla--Wagner (RW) model. Activity in primary visual cortex and putamen reflected learning-dependent surprise: these areas responded progressively more to unpredicted, and progressively less to predicted visual stimuli. Critically, this prediction-error response was observed even when the absence of a visual stimulus was surprising. We investigated the underlying mechanism by embedding the RW model into a DCM to show that auditory to visual connectivity changed significantly over time as a function of prediction error. Thus, consistent with predictive coding models of perception, associative learning is mediated by prediction-error dependent changes in connectivity. These results posit a dual role for prediction-error in encoding surprise and driving associative plasticity

Hubble Space Telescope Observations of Comet 9P/Tempel 1 during the Deep Impact Encounter

We report on the Hubble Space Telescope program to observe periodic comet 9P/Tempel 1 in conjunction with NASA's Deep Impact mission. Our objectives were to study the generation and evolution of the coma resulting from the impact and to obtain wide-band images of the visual outburst generated by the impact. Two observing campaigns utilizing a total of 17 HST orbits were carried out: the first occurred on 2005 June 13-14 and fortuitously recorded the appearance of a new, short-lived fan in the sunward direction on June 14. The principal campaign began two days before impact and was followed by contiguous orbits through impact plus several hours and then snapshots one, seven, and twelve days later. All of the observations were made using the Advanced Camera for Surveys (ACS). For imaging, the ACS High Resolution Channel (HRC) provides a spatial resolution of 36 km (16 km/pixel) at the comet at the time of impact. Baseline images of the comet, made prior to impact, photometrically resolved the comet's nucleus. The derived diameter, 6.1 km, is in excellent agreement with the 6.0 +/- 0.2 km diameter derived from the spacecraft imagers. Following the impact, the HRC images illustrate the temporal and spatial evolution of the ejecta cloud and allow for a determination of its expansion velocity distribution. One day after impact the ejecta cloud had passed out of the field-of-view of the HRC.Comment: 15 pages, 14 postscript figures. Accepted for publication in Icarus special issue on Deep Impac

Memory Complaint in a Community Sample Aged 70 and Older

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111116/1/j.1532-5415.2000.tb02634.x.pd

Vaspin inhibits kallikrein 7 by serpin mechanism

The molecular target of the adipokine vaspin (visceral adipose tissue-derived serpin; serpinA12) and its mode of action are unknown. Here, we provide the vaspin crystal structure and identify human kallikrein 7 (hK7) as a first protease target of vaspin inhibited by classical serpin mechanism with high specificity in vitro. We detect vaspin–hK7 complexes in human plasma and find co-expression of both proteins in murine pancreatic β-cells. We further demonstrate that hK7 cleaves human insulin in the A- and B-chain. Vaspin treatment of isolated pancreatic islets leads to increased insulin concentration in the media upon glucose stimulation without influencing insulin secretion. By application of vaspin and generated inactive mutants, we find the significantly improved glucose tolerance in C57BL/6NTac and db/db mice treated with recombinant vaspin fully dependent on the vaspin serpin activity and not related to vaspin-mediated changes in insulin sensitivity as determined by euglycemic-hyperinsulinemic clamp studies. Improved glucose metabolism could be mediated by increased insulin plasma concentrations 150 min after a glucose challenge in db/db mice, supporting the hypothesis that vaspin may inhibit insulin degradation by hK7 in the circulation. In conclusion, we demonstrate the inhibitory serpin nature and the first protease target of the adipose tissue-derived serpin vaspin, and our findings suggest hK7 inhibition by vaspin as an underlying physiological mechanism for its compensatory actions on obesity-induced insulin resistance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00018-013-1258-8) contains supplementary material, which is available to authorized users

An Exact Diagonalization Demonstration of Incommensurability and Rigid Band Filling for N Holes in the t-J Model

We have calculated S(q) and the single particle distribution function for N holes in the t - J model on a non--square sqrt{8} X sqrt{32} 16--site lattice with periodic boundary conditions; we justify the use of this lattice in compariosn to those of having the full square symmetry of the bulk. This new cluster has a high density of vec k points along the diagonal of reciprocal space, viz. along k = (k,k). The results clearly demonstrate that when the single hole problem has a ground state with a system momentum of vec k = (pi/2,pi/2), the resulting ground state for N holes involves a shift of the peak of the system's structure factor away from the antiferromagnetic state. This shift effectively increases continuously with N. When the single hole problem has a ground state with a momentum that is not equal to k = (pi/2,pi/2), then the above--mentioned incommensurability for N holes is not found. The results for the incommensurate ground states can be understood in terms of rigid--band filling: the effective occupation of the single hole k = (pi/2,pi/2) states is demonstrated by the evaluation of the single particle momentum distribution function . Unlike many previous studies, we show that for the many hole ground state the occupied momentum states are indeed k = (+/- pi/2,+/- pi/2) states.Comment: Revtex 3.0; 23 pages, 1 table, and 13 figures, all include

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring

Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker