Rhythmic Oscillations Research Articles

Oscillatory Resonance and Dynamic Manifolds in Cortical Networks With Time Delay and Multiple External Stimuli.

Rhythmic oscillation is crucial for information transmission and neural communication among different brain areas. Stochastic resonance (SR) can evoke different patterns of neural oscillation. However, the characteristics of network resonance and underlying dynamical mechanisms are still unclear. In this paper, a biological model of cortical network is established and its dynamical response to external periodic stimulation is investigated. We explore the oscillatory resonance of excitatory and inhibitory populations in cortical network. It is found that the intrinsic parameters of neural populations determine the extent of resonant activity, indicating that the firing rate exhibits coherent oscillation when the frequency of external stimulation is close to intrinsic frequency of neural population. In addition, the nonlinear dynamics of cortical network in oscillatory resonance can be represented by helical manifolds in low-dimensional state space. The geometry of neural manifolds reveals the periodic dynamics and state transition in oscillatory resonance. Moreover, time delay in chemical synapses can induce multiple resonances, which appear intermittently at integer multiples of the period of input signal. The dynamical response of neural population achieves maximal periodically, due to the transition of network states induced by time delay. Furthermore, mean-field theory is applied to analyze theoretical dynamic of cortical networks with time delay and demonstrate the effective transmission of stimulation information via oscillatory resonance in the brain. Consequently, the obtained results contribute to the improvement of neuromodulation for neurological disease from the viewpoint of the neural basis.

The Rhythmicity of Life: A Review of the Circadian Clocks.

Physiology of the mammalian body has been adapted to diurnal cycles of around 24 h, an evolutionary situation that affects a wide spectrum of biological events including sleep-to-wake transitions, feeding/fasting, body temperature, and hormonal regulations. The patterns of the diurnal cycle occur due to rhythmic oscillations that arise from the suprachiasmatic nucleus of hypothalamus, which also can be defined as the pacemaker of the system. The clock can be defined as a molecular machinery driven by the core clock genes that encode clock proteins in a rhythmic oscillatory fashion maintained by the light/dark cycles of the environment. Although the well-established knowledge refers to the function of the circadian rhythm as maintenance of the normal physiology, growing evidence shows that disruptions in the system usually caused by genetic and/or epigenetic misregulations may have a direct effect to lead major pathological conditions, such as carcinogenesis. This review outlines the main molecular aspects of circadian physiology, and reveals the reasons for and results of the circadian disruptions at different levels. In spite of the fact that more proof is needed for a direct correlation between circadian disruptions and oncogenesis and other pathological events, data obtained from current research supports the role of circadian rhythms in malfunctioning of the normal cellular metabolism.

Transcranial Alternating Current Stimulation (Tacs) Alters Auditory Steady-State Oscillatory Rhythms and Their Cross-Frequency Couplings

Transcranial Alternating Current Stimulation (Tacs) Alters Auditory Steady-State Oscillatory Rhythms and Their Cross-Frequency Couplings

Processing and model design of the gamma oscillation activity based on FitzHugh-Nagumo model and its interaction with slow rhythms in the brain

The brain is processing information 24 hours a day. There are millions of processes proceeding in it accompanied by various spectra of rhythms. This paper tests the hypothesis that the slow delta rhythm excites the gamma rhythm oscillations. Unlike other papers, we determine the slow rhythm spectrum not at the hypothesis stage but during the experiment. We design algorithms of filtering, envelope extraction, and correlation coefficient calculation for signal processing. Moreover, we examine the data on all electroencephalogram channels, which allows us to make a more reasonable conclusion. We confirm that a slow delta rhythm excites a fast gamma rhythm with an amplitude-phase type of interaction and calculate a delay between these two signals equal to about half a second.

Data Augmentation for Deep Neural Networks Model in EEG Classification Task: A Review.

Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems (BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.

Corticothalamic Projections Gate Alpha Rhythms in the Pulvinar.

Two types of corticothalamic (CT) terminals reach the pulvinar nucleus of the thalamus, and their distribution varies according to the hierarchical level of the cortical area they originate from. While type 2 terminals are more abundant at lower hierarchical levels, terminals from higher cortical areas mostly exhibit type 1 axons. Such terminals also evoke different excitatory postsynaptic potential dynamic profiles, presenting facilitation for type 1 and depression for type 2. As the pulvinar is involved in the oscillatory regulation between intercortical areas, fundamental questions about the role of these different terminal types in the neuronal communication throughout the cortical hierarchy are yielded. Our theoretical results support that the co-action of the two types of terminals produces different oscillatory rhythms in pulvinar neurons. More precisely, terminal types 1 and 2 produce alpha-band oscillations at a specific range of connectivity weights. Such oscillatory activity is generated by an unstable transition of the balanced state network’s properties that it is found between the quiescent state and the stable asynchronous spike response state. While CT projections from areas 17 and 21a are arranged in the model as the empirical proportion of terminal types 1 and 2, the actions of these two cortical connections are antagonistic. As area 17 generates low-band oscillatory activity, cortical area 21a shifts pulvinar responses to stable asynchronous spiking activity and vice versa when area 17 produces an asynchronous state. To further investigate such oscillatory effects through corticothalamo-cortical projections, the transthalamic pathway, we created a cortical feedforward network of two cortical areas, 17 and 21a, with CT connections to a pulvinar-like network with two cortico-recipient compartments. With this model, the transthalamic pathway propagates alpha waves from the pulvinar to area 21a. This oscillatory transfer ceases when reciprocal connections from area 21a reach the pulvinar, closing the CT loop. Taken together, results of our model suggest that the pulvinar shows a bi-stable spiking activity, oscillatory or regular asynchronous spiking, whose responses are gated by the different activation of cortico-pulvinar projections from lower to higher-order areas such as areas 17 and 21a.

PRIME uncovers circadian oscillation patterns and links with Alzheimer’s disease in untimed genome‐wide gene expression data across multiple regions of human brain

AbstractBackgroundThe disruption of brain circadian rhythm is a major symptom of AD patients. Recent studies and accumulating clinic evidence have suggested that this symptom usually occurs in the early phase of AD and probably precedes cognitive impairment development; however, the full circadian rhythm orchestration of gene expression in the human brain and its inherent associations with AD currently remain unknown. The main barrier to studying circadian rhythmic patterns of the whole‐genome gene expression is the requirement of time labels of brain tissues, which is hard to obtain or inaccurate. Indeed, current existing circadian rhythm analyses rely on the timestamps of samples.MethodThis study aims to explore the relationships between circadian rhythms of brain regions and AD with untimed genome‐wide gene expression data. To this end, we developed and presented an innovative, comprehensive, unsupervised machine‐learning based approach based on principal component analysis (PCA) and matrix factorization (MF), called PRIME, to detect and analyze oscillation patterns in untimed high‐dimensional data across multiple brain regions. PRIME captures oscillatory patterns in the latent space underlying the gene expression data without requiring time stamps of brain tissue samples.ResultTo demonstrate PRIME’s utility, firstly, we validated it by a time course expression dataset from mouse liver (Figs. 1‐2) as a cross‐species and cross‐organ validation, because this dataset has systematically recorded time labels. Then, we applied it to studying oscillation patterns in genome‐wide gene expression from 19 human brain regions of controls and AD patients. Our experiments showed that there exist clear synchronized oscillation patterns in 15 union brain regions of normal controls (Fig. 3). In sharp contrast, the synchronized oscillation patterns became either disappear or weakened for AD‐affected brains (Fig. 4). Additionally, we provided necessary rules to infer AD’s impacts on human brain regions (Table 1).ConclusionWe developed a novel comprehensive approach, called PRIME, to detect and analyze rhythmic oscillation patterns in untimed high‐dimensional gene expression data across multiple datasets. It is worth noting that our approach discovered the circadian rhythmic patterns without the need for the sample’s timestamps.

Circadian Alterations Increase with Progression in a Patient-Derived Cell Culture Model of Breast Cancer.

Circadian rhythm disruption can elicit the development of various diseases, including breast cancer. While studies have used cell lines to study correlations between altered circadian rhythms and cancer, these models have different genetic backgrounds and do not mirror the changes that occur with disease development. Isogenic cell models can recapitulate changes across cancer progression. Hence, in this study, a patient-derived breast cancer model, the 21T series, was used to evaluate changes to circadian oscillations of core clock protein transcription as cells progress from normal to malignant states. Three cell lines were used: H16N2 (normal breast epithelium), 21PT (atypical ductal hyperplasia), and 21MT-1 (invasive metastatic carcinoma). The cancerous cells are both HER2+. We assessed the transcriptional profiles of two core clock proteins, BMAL1 and PER2, which represent a positive and negative component of the molecular oscillator. In the normal H16N2 cells, both genes possessed rhythmic mRNA oscillations with close to standard periods and phases. However, in the cancerous cells, consistent changes were observed: both genes had periods that deviated farther from normal and did not have an anti-phase relationship. In the future, mechanistic studies should be undertaken to determine the oncogenic changes responsible for the circadian alterations found.

Phase Analysis of Ultradian Rhythms of Body Temperature in Laboratory Mice Maintained under Constant Illumination at Different Longitudinal Locations.

The study examined the rhythmic oscillations of body temperature with the period ranging 100-400 min in three groups of laboratory mice maintained under persistent artificial illumination in Moscow and Ulyanovsk. The difference in the moments of sunrise or sunset in these towns is about 1 h. The greatest rhythmic oscillations of body temperature in examined mice had the periods of 100-400 min. The phase analysis of 100-200-min rhythms revealed their synchronicity with local but not universal time despite the mice had no photic signs indicating alternation of day and night. Of them, the most pronounced were the rhythms with the periods of 121, 143, 151, and 186 min. The present data suggest existence of an external environmental synchronizer of body temperature ultradian rhythms related to local solar time.

Instantaneous EEG Signal Analysis Based on Empirical Mode Decomposition Applied to Burst-Suppression in Propofol Anaesthesia

The human electroencephalogram (EEG) constitutes a nonstationary, nonlinear electrophysiological signal resulting from synchronous firing of neurons in thalamocortical structures of the brain. Due to the complexity of the brain's physiological structures and its rhythmic oscillations, analysis of EEG often utilises spectral analysis methods.Aim: to improve clinical monitoring of neurophysiological signals and to further explain basic principles of functional mechanisms in the brain during anaesthesia.Material and methods. In this paper we used Empirical Mode decomposition (EMD), a novel spectral analysis method especially suited for nonstationary and nonlinear signals. EMD and the related Hilbert-Huang Transform (HHT) decompose signal into constituent Intrinsic Mode Functions (IMFs). In this study we applied EMD to analyse burst-suppression (BS) in the human EEG during induction of general anaesthesia (GA) with propofol. BS is a state characterised by cyclic changes between significant depression of brain activity and hyper-active bursts with variable duration, amplitude, and waveform shape. BS arises after induction into deep general anaesthesia after an intravenous bolus of general anaesthetics. Here we studied the behaviour of BS using the burst-suppression ratio (BSR).Results. Comparing correlations between EEG and IMF BSRs, we determined BSR was driven mainly by alpha activity. BSRs for different spectral components (IMFs 1-4) showed differing rates of return to baseline after the end of BS in EEG, indicating BS might differentially impair neural generators of low-frequency EEG oscillations and thalamocortical functional connectivity.Conclusion. Studying BS using EMD represents a novel form of analysis with the potential to elucidate neurophysiological mechanisms of this state and its impact on post-operative patient prognosis.

A cluster based model for brain activity data staging

Brain signals allow a fundamental understanding of the mechanisms underpinning behavioral changes. Currently, standard signal staging of brain electrical activity relies on supervised processes. In this work, we propose an unsupervised data segmentation method based on time series complexity and in the cluster-weighted representation. Receiver operating characteristic curves for predicting transitions on simulated and biological datasets suggest that our model distinguishes accordingly between true and false positive transitions. The advantages revealed were as follows: our method was suited for short-length signals; it was adapted to detect changes of rhythmic oscillations; and it showed no restrictive modeling conditions. Moreover, considering a calibration procedure, this method proved to be suitable for different data samples with a single threshold. This hybrid approach saves time and increases the reliability of post data analysis.

Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.

Mechanism for the Generation of Robust Circadian Oscillations through Ultransensitivity and Differential Binding Affinity.

Biochemical circadian rhythm oscillations play an important role in many signaling mechanisms. In this work, we explore some of the biophysical mechanisms responsible for sustaining robust oscillations by constructing a minimal but analytically tractable model of the circadian oscillations in the KaiABC protein system found in the cyanobacteria S. elongatus. In particular, our minimal model explicitly accounts for two experimentally characterized biophysical features of the KaiABC protein system, namely, a differential binding affinity and an ultrasensitive response. Our analytical work shows how these mechanisms might be crucial for promoting robust oscillations even in suboptimal nutrient conditions. Our analytical and numerical work also identifies mechanisms by which biological clocks can stably maintain a constant time period under a variety of nutrient conditions. Finally, our work also explores the thermodynamic costs associated with the generation of robust sustained oscillations and shows that the net rate of entropy production alone might not be a good figure of merit to asses the quality of oscillations.

Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons

Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be differentially involved in many cognitive functions. These cell types also show different relationships with the power and phase of oscillations in local field potentials. The mechanisms that underlie the emergence of different oscillatory rhythms in neural circuits with more than one interneuron subtype, and the roles specific interneurons play in those mechanisms, are not fully understood. Here, we present a comprehensive analysis of all possible circuit motifs and input regimes that can be achieved in circuits comprised of excitatory cells, PV-like fast-spiking interneurons and SOM-like low-threshold spiking interneurons. We identify 18 unique motifs and simulate their dynamics over a range of input strengths. Using several characteristics, such as oscillation frequency, firing rates, phase of firing and burst fraction, we cluster the resulting circuit dynamics across motifs in order to identify patterns of activity and compare these patterns to behaviors that were generated in circuits with one interneuron type. In addition to the well-known PING and ING gamma oscillations and an asynchronous state, our analysis identified three oscillatory behaviors that were generated by the three-cell-type motifs only: theta-nested gamma oscillations, stable beta oscillations and theta-locked bursting behavior, which have also been observed in experiments. Our characterization provides a map to interpret experimental activity patterns and suggests pharmacological manipulations or optogenetics approaches to validate these conclusions.

Possible External Factors Determining Ultradian (4-20-min) Rhythms of Body Temperature.

The study examined the effect of passive magnetic shielding on the magnitude of rhythmic oscillations of body temperature (BT) with 4-20 min periods in mice and their correlation with similar oscillations in unshielded control group. A magnetic permalloy screen that 35-fold attenuates the total geomagnetic field and decreased the undulations of magnetic field with the periods of few minutes by 5 times, produced no effect on the mean amplitude of BT oscillations within the same period range, their spectral power, and the cross-spectral density of examined rhythms in comparison with the control (unshielded) mice. Thus, either the mice possess a very sensitive magnetic sensory system or there exists an external non-magnetic factor affecting rhythmicity of BT. The study advanced intensity of thermal neutron radiation near the Earth's surface known to reflect the flow of accelerated particles generated by the secondary cosmic rays as the external factor, which strongly correlates with BT rhythms revealed by cross-spectrum analysis.

Tracking transient changes in the intrinsic neural frequency architecture: Oxytocin facilitates non-harmonic relationships between alpha and theta rhythms in the resting brain

Shifts in the peak frequencies of oscillatory neural rhythms have been put forward as a principal mechanism by which cross-frequency coupling and decoupling is implemented in the brain. This notion is based on the mathematical reality that neural oscillations can only fully synchronize when their peak frequencies form harmonic 2:1 relationships (e.g., f2=f1/2). Non-harmonic cross-frequency relationships, on the other hand (based on the irrational golden mean 1.618.:1), provide the highest physiologically possible desynchronized state (reducing the occurrence of spurious, noisy, background coupling), and are therefore anticipated to characterize the resting state of the brain, in which no selective information processing takes place. The present study sought to assess whether the transient occurrence of 1.6:1 non-harmonic and 2:1 harmonic relationships between peak frequencies in the alpha (8–14 Hz) and theta (4–8 Hz) bands – respectively facilitating states of decoupling or coupling between oscillatory rhythms – are impacted by the intranasal administration of a single-dose of oxytocin (OT) or placebo. To do so, continuous resting-state electroencephalography (5 min eyes open, 19 electrodes) was obtained from 96 healthy adult men before and after nasal spray administration. The transient formation of non-harmonic cross-frequency configurations between alpha and theta peak frequencies was significantly increased after OT nasal spray administration, indicating an effect of OT on reducing the intrinsic occurrence of spurious (noisy) background phase synchronizations during resting-state. As a group, the OT group also showed a significant parallel increase in high-frequency and decrease in low-frequency heart rate variability, confirming a homeostatic role of OT in balancing parasympathetic drive. Overall, non-harmonic cross-frequency configurations have been put forward to lay the ground for a healthy neural network allowing the opportunity for an efficient transition from resting state to activity. The observed effects of OT on cross-frequency dynamics are therefore interpreted to reflect a homeostatic role of OT in increasing the signal-to-noise properties of the intrinsic EEG neural frequency architecture, i.e., by precluding the occurrence of ‘noisy’, unwanted, spurious couplings among neural rhythms in the resting brain.

Functional protection in J20/VLW mice: a model of non-demented with Alzheimer's disease neuropathology.

Alzheimer's disease comprises amyloid-β and hyperphosphorylated Tau accumulation, imbalanced neuronal activity, aberrant oscillatory rhythms and cognitive deficits. Non-demented with Alzheimer's disease neuropathology defines a novel clinical entity with amyloid-β and Tau pathologies but preserved cognition. The mechanisms underlying such neuroprotection remain undetermined and animal models of non-demented with Alzheimer's disease neuropathology are currently unavailable. We demonstrate that J20/VLW mice (accumulating amyloid-β and hyperphosphorylated Tau) exhibit preserved hippocampal rhythmic activity and cognition, as opposed to J20 and VLW animals, which show significant alterations. Furthermore, we show that the overexpression of mutant human Tau in coexistence with amyloid-β accumulation renders a particular hyperphosphorylated Tau signature in hippocampal interneurons. The GABAergic septohippocampal pathway, responsible for hippocampal rhythmic activity, is preserved in J20/VLW mice, in contrast to single mutants. Our data highlight J20/VLW mice as a suitable animal model in which to explore the mechanisms driving cognitive preservation in non-demented with Alzheimer's disease neuropathology. Moreover, they suggest that a differential Tau phosphorylation pattern in hippocampal interneurons prevents the loss of GABAergic septohippocampal innervation and alterations in local field potentials, thereby avoiding cognitive deficits.

SWCNTs/PEDOT:PSS-Modified Microelectrode Arrays for Dual-Mode Detection of Electrophysiological Signals and Dopamine Concentration in the Striatum under Isoflurane Anesthesia.

Accurate detection of the degree of isoflurane anesthesia during a surgery is important to avoid the risk of overdose isoflurane anesthesia timely. To address this challenge, a four-shank implantable microelectrode array (MEA) was fabricated for the synchronous real-time detection of dual-mode signals [electrophysiological signal and dopamine (DA) concentration] in rat striatum. The SWCNTs/PEDOT:PSS nanocomposites were modified onto the MEAs, which significantly improved the electrical and electrochemical performances of the MEAs. The electrical performance of the modified MEAs with a low impedance (16.20 ± 1.68 kΩ) and a small phase delay (-27.76 ± 0.82°) enabled the MEAs to detect spike firing with a high signal-to-noise ratio (> 3). The electrochemical performance of the modified MEAs with a low oxidation potential (160 mV), a low detection limit (10 nM), high sensitivity (217 pA/μM), and a wide linear range (10 nM-72 μM) met the specific requirements for DA detection in vivo. The anesthetic effect of isoflurane was mediated by inhibiting the spike firing of D2_SPNs (spiny projection neurons expressing the D2-type DA receptor) and the broadband oscillation rhythm of the local field potential (LFP). Therefore, the spike firing rate of D2_SPNs and the power of LFP could reflect the degree of isoflurane anesthesia together. During the isoflurane anesthesia-induced death procedure, we found that electrophysiological activities and DA release were strongly inhibited, and changes in the DA concentration provided more details regarding this procedure. The dual-mode recording MEA provided a detection method for the degree of isoflurane anesthesia and a prediction method for fatal overdose isoflurane anesthesia.

Exploring the effects of large-area dorsal skin irradiation on locomotor activity and plasm melatonin level in C3H/He mice

ABSTRACT As the largest organ exposed to the outside of mammals, skin has direct photosensitivity. Recent studies have even shown that cutaneous irradiation played a role in local circadian systems. However, whether it can further affect the central clock system is controversial. Here, plasm melatonin rhythm of melatonin-proficient C3H/He mice was assessed, and on this basis, a well-designed segmented lighting method was used to investigate the effects of dorsal skin irradiation on locomotor activity and plasm melatonin content in male C3H/He mice. In brief, mice were separately exposed to cutaneous irradiation, intraocular irradiation or darkness for 60 min at specific moments. The results showed that neither blue nor red cutaneous exposure had obvious effect on central rhythm oscillation while intraocular irradiation could significantly change the central clock of mice, and the effect of blue light was more forceful than red light. It suggests that intraocular nonvisual channels still play a dominant role in rhythmic regulation, which has not been challenged by the discovery of local light entrainment in exposed peripheral tissues.

Ambient fine particulate matter exposure disrupts circadian rhythm and oscillation of the HPA axis in a mouse model

Emerging evidence supports that exposure to ambient fine particulate matter (PM2.5) is associated with the metabolic syndrome. As the main neuroendocrine axis in mammals, the hypothalamic-pituitary-adrenal (HPA) axis's circadian rhythm (CR) plays an essential role in regulating metabolic homeostasis. Our previous studies found that ambient PM2.5 exposure caused CR disorder of the critical enzymes involved in lipid metabolism in mouse liver and adipose tissues. However, the impact of ambient PM2.5 exposure on the HPA axis is not fully illustrated yet. Male C57BL/6 mice were randomly exposed to ambient PM2.5 or filtered air for ten weeks via a whole-body exposure system. Rhythmic oscillations of clock genes in the hypothalamus and adrenal gland were characterized. The effects of ambient PM2.5 exposure on clock gene expression and rhythmic expression of molecules related to glucocorticoid synthesis were also examined. Firstly, a more robust CR of clock genes was demonstrated in the adrenal gland than that in the hypothalamus. Secondly, PM2.5 exposure significantly inhibited the expression of Clock at ZT8 in the hypothalamus. However, both circadian oscillation and expression levels of Bmal1, Cry1, Cry2, and Rorα were increased significantly by ambient PM2.5 exposure in the adrenal gland. Moreover, abnormal rhythmic oscillation patterns of corticotropin-releasing hormone and adrenocorticotropic hormone were observed after ambient PM2.5 exposure, with no change at the expression levels. Finally, the expression of Cyp11b1 was markedly decreased at ZT0 in the adrenal gland of PM2.5 exposed mice. Our findings provide new insights into the ambient PM2.5 exposure-induced metabolic syndrome from the perspective of CR disturbances.