Early life stress (ELS) has been widely recognized as a major risk factor for the development of depression and anxiety in humans. While clinical studies have established this association, the underlying neural mechanisms remain elusive. To address this gap, rodent models such as maternal separation have been employed to mimic ELS and to explore its long-term effects on the brain and behavior. Environmental enrichment (EE) has further been proposed as a potential intervention to counteract the detrimental consequences of ELS, but its efficacy and underlying mechanisms remain insufficiently characterized. In this study, we utilized multi-parametric magnetic resonance imaging combined with behavioral tests to systematically evaluate the long-term effects of ELS exposure and subsequent EE intervention on brain signatures and behavioral changes in adult male and female ELS mice. ELS mice exhibited depressive- and anxiety-like behaviors, along with increased brain activity in the striatum. These behavioral changes were accompanied by reductions in gray matter volume, white matter integrity and metabolite ratios in the striatum. Importantly, EE intervention effectively reversed the behavioral impairments by restoring the alterations in brain function, structure, and metabolism, especially in the striatum. This study provides comprehensive insights into the detrimental effects of early life stress on brain and behavioral outcomes and reveals that these negative effects can be mitigated by EE intervention. Our findings identify the striatum as a critical region involved in these processes.

Cortical traveling waves coordinate communication among distributed neural ensembles to modulate brain function and dysfunction through distinct spatiotemporal propagation patterns. However, the brain-wide propagation dynamics of traveling waves from different origins and their roles in regulating behavior remain unclear. Using optogenetics alongside whole-brain fMRI in mice, it is demonstrated that optogenetic activation of the medial prefrontal cortex and primary somatosensory area induces cortical spreading depression (CSD)-like traveling waves. These waves propagate beyond the ipsilateral cortex to the contralateral cortex and midbrain, reaching subcortical structures along cortico-amygdala-striatal pathways, ultimately terminating in the striatum ≈4 min after induction. The propagation directions in the cortex, speed, duration, and region involvement vary with wave origins. Furthermore, these CSD-like traveling waves induce anxiety-like behaviors and increase dendritic spine density. The findings elucidate the complete process from induction to termination of traveling waves across the whole brain and reveal their previously undiscovered role in driving anxiety.

In photoacoustic tomography (PAT), acoustic inversion aims to recover the spatial distribution of light energy deposition within the imaging object from the signals captured by detectors. To achieve quantitative imaging, optical inversion is further employed to derive absorption coefficient (AC) images. However, limitations such as restricted detection angles and inherent noise lead to substantial artifacts and degradation in the quality of PAT images, consequently affecting the accuracy of optical inversion results. In this study, we propose a directional total variation constrained optical inversion model to reconstruct the AC image. By incorporating anatomy prior information into the optical inversion process, our method can effectively suppress artifacts in AC images while maintaining structural integrity. Simulation, phantom, and in vivo experimental results demonstrate that our method significantly improves the reconstructed AC image quality. Our method provides a reliable foundation for achieving high-quality quantitative PAT imaging.

Major depressive disorder (MDD) is a globally prevalent and highly disabling disease characterized by dysfunction of large-scale brain networks. Previous studies have found that static functional connectivity is not sufficient to reflect the complicated and time-varying properties of the brain. The underlying dynamic interactions between brain functional networks of MDD remain largely unknown, and it is also unclear whether neuroimaging-based dynamic properties are sufficiently robust to discriminate individuals with MDD from healthy controls since the diagnosis of MDD mainly depends on symptom-based criteria evaluated by clinical observation. Resting-state functional magnetic resonance imaging (fMRI) data of 221 MDD patients and 215 healthy controls were shared by REST-meta-MDD consortium. We investigated the spatial-temporal dynamics of MDD using co-activation pattern analysis and made individual diagnoses using support vector machine (SVM). We found that MDD patients exhibited aberrant dynamic properties (such as dwell time, occurrence rate, transition probability, and entropy of Markov trajectories) in some transient networks including subcortical network (SCN), activated default mode network (DMN), de-activated SCN-cerebellum network, a joint network, activated attention network (ATN), and de-activated DMN-ATN, where some dynamic properties were indicative of depressive symptoms. The trajectories of other networks to deactivated DMN-ATN were more accessible in MDD patients. Subgroup analyses also showed subtle dynamic changes in first-episode drug-naïve (FEDN) MDD patients. Finally, SVM achieved preferable accuracies of 84.69%, 76.77%, and 88.10% in discriminating patients with MDD, FEDN MDD, and recurrent MDD from healthy controls with their dynamic metrics. Our findings reveal that MDD is characterized by aberrant dynamic fluctuations of brain network and the feasibility of discriminating MDD patients using dynamic properties, which provide novel insights into the neural mechanism of MDD.

Magnetic resonance imaging (MRI) and photoacoustic tomography (PAT) offer two distinct image contrasts. To integrate these two modalities, we present a comprehensive hardware-software solution for the successive acquisition and co-registration of PAT and MRI images in in vivo animal studies. Based on commercial PAT and MRI scanners, our solution includes a 3D-printed dual-modality imaging bed, a 3-D spatial image co-registration algorithm with dual-modality markers, and a robust modality switching protocol for in vivo imaging studies. Using the proposed solution, we successfully demonstrated co-registered hybrid-contrast PAT-MRI imaging that simultaneously displays multi-scale anatomical, functional and molecular characteristics on healthy and cancerous living mice. Week-long longitudinal dual-modality imaging of tumor development reveals information on size, border, vascular pattern, blood oxygenation, and molecular probe metabolism of the tumor micro-environment at the same time. The proposed methodology holds promise for a wide range of pre-clinical research applications that benefit from the PAT-MRI dual-modality image contrast.

The cortical distribution and functional role of cholecystokinin (CCK) are largely unknown. Here, a CCK receptor antagonist challenge paradigm was developed to assess functional connectivity and neuronal responses. Structural-functional magnetic resonance imaging and calcium imaging were undertaken in environmental enrichment (EE) and standard environment (SE) groups (naïve adult male mice, n = 59, C57BL/B6J, P = 60). Functional connectivity network-based statistics and pseudo-demarcation Voronoi tessellations to cluster calcium signals were used to derive region of interest metrics based on calcium transients, firing rate, and location. The CCK challenge elicited robust changes to structural-functional networks, decreased neuronal calcium transients, and max firing rate (5 s) of dorsal hippocampus in SE mice. However, the functional changes were not observed in EE mice, while the decreased neuronal calcium transients and max firing rate (5 s) were similar to SE mice. Decreased gray matter alterations were observed in multiple brain regions in the SE group due to CCK challenge, while no effect was observed in the EE group. The networks most affected by CCK challenge in SE included within isocortex, isocortex to olfactory, isocortex to striatum, olfactory to midbrain, and olfactory to thalamus. The EE group did not experience network changes in functional connectivity due to CCK challenge. Interestingly, calcium imaging revealed a significant decrease in transients and max firing rate (5 s) in the dorsal CA1 hippocampus subregion after CCK challenge in EE. Overall, CCK receptor antagonists affected brain-wide structural-functional connectivity within the isocortex, in addition to eliciting decreased neuronal calcium transients and max firing rate (5 s) in CA1 of the hippocampus. Future studies should investigate the CCK functional networks and how these processes affect isocortex modulation. Significance Statement  Cholecystokinin is a neuropeptide predominately found in the gastrointestinal system. Albeit abundantly expressed in neurons, the role and distribution of cholecystokinin are largely unknown. Here, we demonstrate cholecystokinin affects brain-wide structural-functional networks within the isocortex. In the hippocampus, the cholecystokinin receptor antagonist challenge decreases neuronal calcium transients and max firing rate (5 s) in CA1. We further demonstrate that mice in environmental enrichment do not experience functional network changes to the CCK receptor antagonist challenge. Environmental enrichment may afford protection to the alterations observed in control mice due to CCK. Our results suggest that cholecystokinin is distributed throughout the brain, interacts in the isocortex, and demonstrates an unexpected functional network stability for enriched mice.

Skull stripping is an initial and critical step in the pipeline of mouse fMRI analysis. Manual labeling of the brain usually suffers from intra- and inter-rater variability and is highly time-consuming. Hence, an automatic and efficient skull-stripping method is in high demand for mouse fMRI studies. In this study, we investigated a 3D U-Net based method for automatic brain extraction in mouse fMRI studies. Two U-Net models were separately trained on T2-weighted anatomical images and T2*-weighted functional images. The trained models were tested on both interior and exterior datasets. The 3D U-Net models yielded a higher accuracy in brain extraction from both T2-weighted images (Dice > 0.984, Jaccard index > 0.968 and Hausdorff distance < 7.7) and T2*-weighted images (Dice > 0.964, Jaccard index > 0.931 and Hausdorff distance < 3.3), compared with the two widely used mouse skull-stripping methods (RATS and SHERM). The resting-state fMRI results using automatic segmentation with the 3D U-Net models are highly consistent with those obtained by manual segmentation for both the seed-based and group independent component analysis. These results demonstrate that the 3D U-Net based method can replace manual brain extraction in mouse fMRI analysis.

Major depressive disorder (MDD) is a devastating mental disorder that affects up to 17% of the population worldwide. Although brain-wide network-level abnormalities in MDD patients via resting-state functional magnetic resonance imaging (rsfMRI) exist, the mechanisms underlying these network changes are unknown, despite their immense potential for depression diagnosis and management. Here, we show that the astrocytic calcium-deficient mice, inositol 1,4,5-trisphosphate-type-2 receptor knockout mice ( Itpr2 −/− mice), display abnormal rsfMRI functional connectivity (rsFC) in depression-related networks, especially decreased rsFC in medial prefrontal cortex (mPFC)–related pathways. We further uncover rsFC decreases in MDD patients highly consistent with those of Itpr2 −/− mice, especially in mPFC-related pathways. Optogenetic activation of mPFC astrocytes partially enhances rsFC in depression-related networks in both Itpr2 −/− and wild-type mice. Optogenetic activation of the mPFC neurons or mPFC-striatum pathway rescues disrupted rsFC and depressive-like behaviors in Itpr2 −/− mice. Our results identify the previously unknown role of astrocyte dysfunction in driving rsFC abnormalities in depression.

As an emerging molecular imaging modality, Photoacoustic Tomography (PAT) is capable of mapping tissue physiological metabolism and exogenous contrast agent information with high specificity. Due to its ultrasonic detection mechanism, the precise localization of targeted lesions has long been a challenge for PAT imaging. The poor soft-tissue contrast of the PAT image makes this process difficult and inaccurate. To meet this challenge, in this study, we first make use of the rich and clear structural information brought about by another advanced imaging modality, Magnetic Resonance Imaging (MRI), to assist organ segmentation and correct for the light fluence attenuation of PAT. We demonstrate improved feature visibility and enhanced localization of endogenous and exogenous agents in the fluence corrected PAT images. Compared with PAT-based methods, the contrast-to-noise ratio (CNR) of our MRI-assisted method increases by 29.1% in live animal experiments. Furthermore, we show that the co-registered MRI image can also be incorporated into PAT image restoration, and achieves improved anatomical landscape and soft-tissue contrast (CNR increased by 25.36%) while preserving similar spatial resolution. This PAT-MRI combination provides excellent structural, functional and molecular images of the subject, and may enable more comprehensive analysis of various preclinical research applications.

In Photoacoustic Tomography (PAT), the acquired image represents a light energy deposition map of the imaging object. For quantitative imaging, the PAT image is converted into an absorption coefficient ( μa ) map by dividing the light fluence (LF). Previous methods usually assume a uniform tissue μa distribution, and consequently degrade the LF correction results. Here, we propose a simple method to reconstruct the pixel-wise μa map. Our method is based on a non-segmentation-based iterative algorithm, which alternately optimizes the LF distribution and the μa map. Using simulation data, as well as phantom and animal data, we implemented our algorithm and compared it to segmentation-based correction methods. The results show that our method can obtain accurate estimation of the LF distribution and therefore improve the image quality and feature visibility of the μa map. Our method may facilitate efficient calculation of the concentration distributions of endogenous and exogenous agents in vivo.

Environmental enrichment is known to induce neuronal changes; however, the underlying structural and functional factors involved are not fully known and remain an active area of study. To investigate these factors, we assessed enriched environment (EE) and standard environment (SE) control mice over 30 days using structural and functional MRI methods. Naïve adult male mice (n = 30, ≈20 g, C57BL/B6J, postnatal day 60 initial scan) were divided into SE and EE groups and scanned before and after 30 days. Structural analyses included volumetry based on manual segmentation as well as diffusion tensor imaging (DTI). Functional analyses included seed-based analysis (SBA), independent component analysis (ICA), the amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF). Structural results indicated that environmental enrichment led to an increase in the volumes of cornu ammonis 1 (CA1) and dentate gyrus. Structural results indicated changes in radial diffusivity and mean diffusivity in the visual cortex and secondary somatosensory cortex after EE. Furthermore, SBA and ICA indicated an increase in resting-state functional MRI (rsfMRI) functional connectivity in the hippocampus. Using parallel structural and functional analyses, we have demonstrated coexistent structural and functional changes in the hippocampal subdivision CA1. Future research should map alterations temporally during environmental enrichment to investigate the initiation of these structural and functional changes.

Environmental enrichment induces widespread neuronal changes, but the initiation of the cascade is unknown. We ascertained the critical period of divergence between environmental enriched (EE) and standard environment (SE) mice using continuous infrared (IR) videography, functional magnetic resonance imaging (fMRI), and neuron level calcium imaging. Naïve adult male mice (n = 285, C57BL/6J, postnatal day 60) were divided into SE and EE groups. We assessed the linear time-series of motion activity using a novel structural break test which examined the dataset for change in circadian and day-by-day motion activity. fMRI was used to map brain-wide response using a functional connectome analysis pipeline. Awake calcium imaging was performed on the dorsal CA1 pyramidal layer. We found the preeminent behavioral feature in EE was a forward shift in the circadian rhythm, prolongation of activity in the dark photoperiod, and overall decreased motion activity. The crepuscular period of dusk was seen as the critical period of divergence between EE and SE mice. The functional processes at dusk in EE included increased functional connectivity in the visual cortex, motor cortex, retrosplenial granular cortex, and cingulate cortex using seed-based analysis. Network based statistics found a modulated functional connectome in EE concentrated in two hubs: the hippocampal formation and isocortical network. These hubs experienced a higher node degree and significant enhanced edge connectivity. Calcium imaging revealed increased spikes per second and maximum firing rate in the dorsal CA1 pyramidal layer, in addition to location (anterior-posterior and medial-lateral) effect size differences between EE and SE. The emergence of functional-neuronal changes due to enrichment consisted of enhanced hippocampal-isocortex functional connectivity and CA1 neuronal increased spiking linked to a circadian shift during the dusk period. Future studies should explore the molecular consequences of enrichment inducing shifts in the circadian period.

One of the advantages of photoacoustic imaging (PAI) is that its image contrast may come from exogenous agents. Such advantage leads to the development of a great number of exogenous probes. However, the biosafety of most of these contrast agents has not yet been confirmed, thus hindering their clinical translation. In this work, we report on the utilization of a clinically commonly used nutritional medicine, the Intralipid, as a new contrast agent for photoacoustic imaging. Intralipid consists of soybean oil, lecithin and glycerin and has long been adapted in clinical practices, mainly as a parenteral nutrition. In our study, we found that with Intralipid, the imaging sensitivity of PAI can be effectively enhanced, as demonstrated in in vivo imaging of different organs of nude mice. Further imaging studies on cancerous mice showed not only a twofold PA signal enhancement, but also a strong and long-lasting signal aggregation in the tumor region. Our result revealed the potential of Intralipid to be used in clinical PAI applications, since it is clinically safe, and can be easily prepared at very low cost.