Local synchronization of resting-state dynamics encodes Gray's trait Anxiety

The Behavioral Inhibition System (BIS) as defined within the Reinforcement Sensitivity Theory (RST) modulates reactions to stimuli indicating aversive events. Gray’s trait Anxiety determines the extent to which stimuli activate the BIS. While studies have identified the amygdala-septo-hippocampal circuit as the key-neural substrate of this system in recent years and measures of resting-state dynamics such as randomness and local synchronization of spontaneous BOLD fluctuations have recently been linked to personality traits, the relation between resting-state dynamics and the BIS remains unexplored. In the present study, we thus examined the local synchronization of spontaneous fMRI BOLD fluctuations as measured by Regional Homogeneity (ReHo) in the hippocampus and the amygdala in twenty-seven healthy subjects. Correlation analyses showed that Gray’s trait Anxiety was significantly associated with mean ReHo in both the amygdala and the hippocampus. Specifically, Gray’s trait Anxiety explained 23% and 17% of resting-state ReHo variance in the left amygdala and the left hippocampus, respectively. In summary, we found individual differences in Gray’s trait Anxiety to be associated with ReHo in areas previously associated with BIS functioning. Specifically, higher ReHo in resting-state neural dynamics corresponded to lower sensitivity to punishment scores both in the amygdala and the hippocampus. These findings corroborate and extend recent findings relating resting-state dynamics and personality while providing first evidence linking properties of resting-state fluctuations to Gray’s BIS

The neural basis of unwanted thoughts during resting state.

Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectivity of a seed region. More unwanted thoughts (state) were associated with lower ReHo in right dorsolateral prefrontal cortex (DLPFC) and higher ReHo in left striatum (putamen). Additional seed-based analysis revealed higher functional connectivity of the left striatum with left inferior frontal gyrus (IFG) in participants reporting more unwanted thoughts. The state-dependent higher connectivty in left striatum was positively correlated with rumination assessed with a dedicated questionnaire focussing on trait aspects. Unwanted thoughts are associated with activity in the fronto-striatal brain circuitry. The reduction of local connectivity in DLPFC could reflect deficiencies in thought suppression processes, whereas the hightened activity in left striatum could imply an imbalance of gating mechanisms housed in basal ganglia. Its functional connectivity to left IFG is discussed as the result of thought-related speech processes

DTER: Schedule Optimal RF Energy Request and Harvest for Internet of Things

We propose a new energy harvesting strategy that uses a dedicated energy source (ES) to optimally replenish energy for radio frequency (RF) energy harvesting powered Internet of Things. Specifically, we develop a two-step dual tunnel energy requesting (DTER) strategy that minimizes the energy consumption on both the energy harvesting device and the ES. Besides the causality and capacity constraints that are investigated in the existing approaches, DTER also takes into account the overhead issue and the nonlinear charge characteristics of an energy storage component to make the proposed strategy practical. Both offline and online scenarios are considered in the second step of DTER. To solve the nonlinear optimization problem of the offline scenario, we convert the design of offline optimal energy requesting problem into a classic shortest path problem and thus a global optimal solution can be obtained through dynamic programming (DP) algorithms. The online suboptimal transmission strategy is developed as well. Simulation study verifies that the online strategy can achieve almost the same energy efficiency as the global optimal solution in the long term

Formation and relaxation of RbHe exciplexes on He nanodroplets studied by femtosecond pump and picosecond probe spectroscopy

Vibrationally resolved photoionization spectra of RbHe exciplexes forming on He nanodroplets are recorded using femtosecond pump-probe spectroscopy with amplitude-shaped probe pulses. The time-evolution of the spectra reveals an exciplex formation time ~10ps followed by vibrational relaxation extending up to >1ns. This points to an indirect, time-delayed desorption process of RbHe off the He surface

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders

Wave packet dynamics of potassium dimers attached to helium nanodroplets

The dynamics of vibrational wave packets excited in K$_2$ dimers attached to superfluid helium nanodroplets is investigated by means of femtosecond pump-probe spectroscopy. The employed resonant three-photon-ionization scheme is studied in a wide wavelength range and different pathways leading to K$^+_2$-formation are identified. While the wave packet dynamics of the electronic ground state is not influenced by the helium environment, perturbations of the electronically excited states are observed. The latter reveal a strong time dependence on the timescale 3-8 ps which directly reflects the dynamics of desorption of K$_2$ off the helium droplets

Frequency Dependent Alterations in Regional Homogeneity of Baseline Brain Activity in Schizophrenia

Low frequency oscillations are essential in cognitive function impairment in schizophrenia. While functional connectivity can reveal the synchronization between distant brain regions, the regional abnormalities in task-independent baseline brain activity are less clear, especially in specific frequency bands. Here, we used a regional homogeneity (ReHo) method combined with resting-state functional magnetic resonance imaging to investigate low frequency spontaneous neural activity in the three different frequency bands (slow-5:0.01–0.027 Hz; slow-4:0.027–0.08 Hz; and typical band: 0.01–0.08 Hz) in 69 patients with schizophrenia and 62 healthy controls. Compared with controls, schizophrenia patients exhibited decreased ReHo in the precentral gyrus, middle occipital gyrus, and posterior insula, whereas increased ReHo in the medial prefrontal cortex and anterior insula. Significant differences in ReHo between the two bands were found in fusiform gyrus and superior frontal gyrus (slow-4> slow-5), and in basal ganglia, parahippocampus, and dorsal middle prefrontal gyrus (slow-5> slow-4). Importantly, we identified significant interaction between frequency bands and groups in the inferior occipital gyrus and caudate body. This study demonstrates that ReHo changes in schizophrenia are widespread and frequency dependent

Detailed study of dissipative quantum dynamics of K-2 attached to helium nanodroplets

We thoroughly investigate vibrational quantum dynamics of dimers attached to He droplets motivated by recent measurements with K-2 [1]. For those femtosecond pump-probe experiments, crucial observed features are not reproduced by gas phase calculations but agreement is found using a description based on dissipative quantum dynamics, as briefly shown in [2]. Here we present a detailed study of the influence of possible effects induced by the droplet. The helium droplet causes electronic decoherence, shifts of potential surfaces, and relaxation of wave packets in attached dimers. Moreover, a realistic description of (stochastic) desorption of dimers off the droplet needs to be taken into account. Step by step we include and study the importance of these effects in our full quantum calculation. This allows us to reproduce and explain all major experimental findings. We find that desorption is fast and occurs already within 2-10 ps after electronic excitation. A further finding is that slow vibrational motion in the ground state can be considered frictionless.Comment: 17 pages, 5 figure

Tau deposition is associated with functional isolation of the hippocampus in aging.

The tau protein aggregates in aging and Alzheimer disease and may lead to memory loss through disruption of medial temporal lobe (MTL)-dependent memory systems. Here, we investigated tau-mediated mechanisms of hippocampal dysfunction that underlie the expression of episodic memory decline using fMRI measures of hippocampal local coherence (regional homogeneity; ReHo), distant functional connectivity and tau-PET. We show that age and tau pathology are related to higher hippocampal ReHo. Functional disconnection between the hippocampus and other components of the MTL memory system, particularly an anterior-temporal network specialized for object memory, is also associated with higher hippocampal ReHo and greater tau burden in anterior-temporal regions. These associations are not observed in the posteromedial network, specialized for context/spatial information. Higher hippocampal ReHo predicts worse memory performance. These findings suggest that tau pathology plays a role in disconnecting the hippocampus from specific MTL memory systems leading to increased local coherence and memory decline