Distinct ACC Neural Mechanisms Underlie Authentic and Transmitted Anxiety Induced by Maternal Separation in Mice.

It is known that humans and rodents are capable of transmitting stress to their naive partners via social interaction. However, a comprehensive understanding of transmitted stress, which may differ from authentic stress, thus revealing unique neural mechanisms of social interaction resulting from transmitted stress and the associated anxiety, is missing. We used, in the present study, maternal separation (MS) as a stress model to investigate whether MS causes abnormal behavior in adolescence. A key concern in the analysis of stress transmission is whether the littermates of MS mice who only witness MS stress ("Partners") exhibit behavioral abnormalities similar to those of MS mice themselves. Of special interest is the establishment of the neural mechanisms underlying transmitted stress and authentic stress. The results show that Partners, similar to MS mice, exhibit anxiety-like behavior and hyperalgesia after witnessing littermates being subjected to early-life repetitive MS. Electrophysiological analysis revealed that mice subjected to MS demonstrate a reduction in both the excitatory and inhibitory synaptic activities of parvalbumin interneurons (PVINs) in the anterior cingulate cortex (ACC). However, Partners differed from MS mice in showing an increase in the number and excitability of GABAergic PVINs in the ACC and in the ability of chemogenetic PVIN inactivation to eliminate abnormal behavior. Furthermore, the social transfer of anxiety-like behavior required intact olfactory, but not visual, perception. This study suggests a functional involvement of ACC PVINs in mediating the distinct neural basis of transmitted anxiety.SIGNIFICANCE STATEMENT The anterior cingulate cortex (ACC) is a critical brain area in physical and social pain and contributes to the exhibition of abnormal behavior. ACC glutamatergic neurons have been shown to encode transmitted stress, but it remains unclear whether inhibitory ACC neurons also play a role. We evaluate, in this study, ACC neuronal, synaptic and network activities and uncover a critical role of parvalbumin interneurons (PVINs) in the expression of transmitted stress in adolescent mice who had witnessed MS of littermates in infancy. Furthermore, inactivation of ACC PVINs blocks transmitted stress. The results suggest that emotional contagion has a severe effect on brain function, and identify a potential target for the treatment of transmitted anxiety.

Altered corticostriatal synchronization associated with compulsive-like behavior in APP/PS1 mice.

Mild behavioral impairment (MBI), which can include compulsive behavior, is an early sign of Alzheimer's disease (AD), but its underlying neural mechanisms remain unclear. Here, we show that 3-5-month-old APP/PS1 mice display obsessive-compulsive disorder (OCD)-like behavior. The number of parvalbumin-positive (PV) interneurons and level of high gamma (γhigh) oscillation are significantly decreased in the striatum of AD mice. This is accompanied by enhanced ß-γhigh coupling and firing rates of putative striatal projection neurons (SPNs), indicating decorrelation between PV interneurons and SPNs. Local field potentials (LFPs) simultaneously recorded in prefrontal cortex (PFC) and striatum (Str) demonstrate a decrease in γhigh-band coherent activity and spike-field coherence in corticostriatal circuits of APP/PS1 mice. Furthermore, levels of GABAB receptor (GABABR), but not GABAA receptor (GABAAR), and glutamatergic receptors, were markedly reduced, in line with presymptomatic AD-related behavioral changes. These findings suggest that MBI occurs as early as 3-5 months in APP/PS1 mice and that altered corticostriatal synchronization may play a role in mediating the behavioral phenotypes observed.

Pelvic Pain Alters Functional Connectivity Between Anterior Cingulate Cortex and Hippocampus in Both Humans and a Rat Model.

The anterior cingulate cortex (ACC) and hippocampus (HIPP) are two key brain regions associated with pain and pain-related affective processing. However, whether and how pelvic pain alters the neural activity and connectivity of the ACC and HIPP under baseline and during social pain, and the underlying cellular and molecular mechanisms, remain unclear. Using functional magnetic resonance imaging (fMRI) combined with electrophysiology and biochemistry, we show that pelvic pain, particularly, primary dysmenorrhea (PDM), causes an increase in the functional connectivity between ACC and HIPP in resting-state fMRI, and a smaller reduction in connectivity during social exclusion in PDM females with periovulatory phase. Similarly, model rats demonstrate significantly increased ACC-HIPP synchronization in the gamma band, associating with reduced modulation by ACC-theta on HIPP-gamma and increased levels of receptor proteins and excitation. This study brings together human fMRI and animal research and enables improved therapeutic strategies for ameliorating pain and pain-related affective processing.

Reweighted low-rank matrix recovery and its application in image restoration.

In this paper, we propose a reweighted low-rank matrix recovery method and demonstrate its application for robust image restoration. In the literature, principal component pursuit solves low-rank matrix recovery problem via a convex program of mixed nuclear norm and l1 norm. Inspired by reweighted l1 minimization for sparsity enhancement, we propose reweighting singular values to enhance low rank of a matrix. An efficient iterative reweighting scheme is proposed for enhancing low rank and sparsity simultaneously and the performance of low-rank matrix recovery is prompted greatly. We demonstrate the utility of the proposed method both on numerical simulations and real images/videos restoration, including single image restoration, hyperspectral image restoration, and background modeling from corrupted observations. All of these experiments give empirical evidence on significant improvements of the proposed algorithm over previous work on low-rank matrix recovery.

RASL: robust alignment by sparse and low-rank decomposition for linearly correlated images.

This paper studies the problem of simultaneously aligning a batch of linearly correlated images despite gross corruption (such as occlusion). Our method seeks an optimal set of image domain transformations such that the matrix of transformed images can be decomposed as the sum of a sparse matrix of errors and a low-rank matrix of recovered aligned images. We reduce this extremely challenging optimization problem to a sequence of convex programs that minimize the sum of l1-norm and nuclear norm of the two component matrices, which can be efficiently solved by scalable convex optimization techniques. We verify the efficacy of the proposed robust alignment algorithm with extensive experiments on both controlled and uncontrolled real data, demonstrating higher accuracy and efficiency than existing methods over a wide range of realistic misalignments and corruptions.