Theta dominates cross-frequency coupling in hippocampal-medial entorhinal circuit during awake-behavior in rats

Effects of high-intensity interval training and moderate-intensity continuous training on neural dynamics and firing in the CA1-MEC region of mice

The aim of this study is to investigate the differential impacts of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on neural circuit dynamics and neuronal firing in the hippocampal CA1 subregion (CA1) region and medial entorhinal cortex (MEC) of mice. Forty-two male ICR mice were randomized into control, HIIT, and MICT groups. Electrophysiological recordings were performed pre- and postintervention to assess neural circuit dynamics and neuronal firing patterns in the CA1-MEC pathway. Both exercise protocols increased local field potential (LFP) coherence, with MICT showing a more pronounced effect on δ and γ coherences (P < 0.05). Both modalities reduced δ power spectral density (PSD) (HIIT, P < 0.05; MICT, P < 0.01) and elevated θ, β, and γ PSDs. Neuronal firing frequency improved in both CA1 and MEC following HIIT and MICT (P < 0.05). HIIT enhanced firing regularity in CA1 (P < 0.05), whereas MICT improved regularity in both regions (P < 0.05). Both protocols reduced firing latency (HIIT, P < 0.05; MICT, P < 0.01) and enhanced burst firing ratio, interburst interval (IBI), burst duration (BD), and LFP phase locking (P < 0.05 or P < 0.01). Notably, MICT significantly improved spatial working memory and novel recognition abilities, as evidenced by increased novel arm time, entries, and preference index (P < 0.01). This study reveals that both HIIT and MICT positively impact neural processing and information integration in the CA1-MEC network of mice. Notably, MICT exhibits a more pronounced impact on neural functional connectivity and cognitive function compared with HIIT. These findings, coupled with the similarities in hippocampal electrophysiological characteristics between rodents and humans, suggest potential exercise-mediated neural plasticity and cognitive benefits in humans.NEW & NOTEWORTHY This study is the first to investigate HIIT and MICT's effects on neural activity in the mouse CA1-MEC circuit, demonstrating that exercise modulates processing, enhances integration, and boosts cognitive performance. Due to similar hippocampal electrophysiology in rodents and humans during movement and navigation, our findings suggest implications for human brain neural changes, advancing the understanding of neurophysiological mechanisms underlying exercise-cognition interactions and informing exercise recommendations for cognitive health.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine

AIMS

Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats.

METHODS

The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD.

RESULTS

Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79).

CONCLUSION

This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

Transcranial ultrasound stimulation at the peak-phase of theta-cycles in the hippocampus improve memory performance

The present study aimed to investigate the effectiveness of closed-loop transcranial ultrasound stimulation (closed-loop TUS) as a non-invasive, high temporal-spatial resolution method for modulating brain function to enhance memory. For this purpose, we applied closed-loop TUS to the CA1 region of the rat hippocampus for 7 consecutive days at different phases of theta cycles. Following the intervention, we evaluated memory performance through behavioral testing and recorded the neural activity. Our results indicated that closed-loop TUS applied at the peak phase of theta cycles significantly improves the memory performance in rats, as evidenced by behavioral testing. Furthermore, we observed that closed-loop TUS modifies the power and cross-frequency coupling strength of local field potentials (LFPs) during memory task, as well as modulates neuronal activity patterns and synaptic transmission, depending on phase of stimulation relative to theta rhythm. We demonstrated that closed-loop TUS can modulate neural activity and memory performance in a phase-dependent manner. Specifically, we observed that effectiveness of closed-loop TUS in regulating neural activity and memory is dependent on the timing of stimulation in relation to different theta phase. The findings implied that closed-loop TUS may have the capability to alter neural activity and memory performance in a phase-sensitive manner, and suggested that the efficacy of closed-loop TUS in modifying neural activity and memory was contingent on timing of stimulation with respect to the theta rhythm. Moreover, the improvement in memory performance after closed-loop TUS was found to be persistent.

Linking temporal coordination of hippocampal activity to memory function

Oscillations in neural activity are widespread throughout the brain and can be observed at the population level through the local field potential. These rhythmic patterns are associated with cycles of excitability and are thought to coordinate networks of neurons, in turn facilitating effective communication both within local circuits and across brain regions. In the hippocampus, theta rhythms (4-12 Hz) could contribute to several key physiological mechanisms including long-range synchrony, plasticity, and at the behavioral scale, support memory encoding and retrieval. While neurons in the hippocampus appear to be temporally coordinated by theta oscillations, they also tend to fire in sequences that are developmentally preconfigured. Although loss of theta rhythmicity impairs memory, these sequences of spatiotemporal representations persist in conditions of altered hippocampal oscillations. The focus of this review is to disentangle the relative contribution of hippocampal oscillations from single-neuron activity in learning and memory. We first review cellular, anatomical, and physiological mechanisms underlying the generation and maintenance of hippocampal rhythms and how they contribute to memory function. We propose candidate hypotheses for how septohippocampal oscillations could support memory function while not contributing directly to hippocampal sequences. In particular, we explore how theta rhythms could coordinate the integration of upstream signals in the hippocampus to form future decisions, the relevance of such integration to downstream regions, as well as setting the stage for behavioral timescale synaptic plasticity. Finally, we leverage stimulation-based treatment in Alzheimer's disease conditions as an opportunity to assess the sufficiency of hippocampal oscillations for memory function.

Dissecting cell-type-specific pathways in medial entorhinal cortical-hippocampal network for episodic memory

Episodic memory, which refers to our ability to encode and recall past events, is essential to our daily lives. Previous research has established that both the entorhinal cortex (EC) and hippocampus (HPC) play a crucial role in the formation and retrieval of episodic memories. However, to understand neural circuit mechanisms behind these processes, it has become necessary to monitor and manipulate the neural activity in a cell-type-specific manner with high temporal precision during memory formation, consolidation, and retrieval in the EC-HPC networks. Recent studies using cell-type-specific labeling, monitoring, and manipulation have demonstrated that medial EC (MEC) contains multiple excitatory neurons that have differential molecular markers, physiological properties, and anatomical features. In this review, we will comprehensively examine the complementary roles of superficial layers of neurons (II and III) and the roles of deeper layers (V and VI) in episodic memory formation and recall based on these recent findings.

PainVision-based evaluation of brain potentials: a novel approach for quantitative pain assessment

Introduction: The complex and multidimensional nature of pain poses a major challenge in clinical pain assessments. In this study, we aimed to evaluate a novel approach combining quantitative sensory testing (QST) with event-related potential measurements for assessment of experimental pain in healthy individuals. Methods: QST was performed with a commercial device (PainVision, PS-2100), and numeric rating scale (NRS) scores after exposure to different sensory stimuli were reported by the participants. Resting-state electroencephalography (EEG) was simultaneously performed to capture the cortical responses to peripheral stimulation. Results: Pain scores increased with the intensity of stimuli, with mean NRS scores of 2.7 ± 1.0 after mild stimuli and 5.6 ± 1.0 after moderate stimuli. A reproducible, significant P2-N2 complex was evoked by both mild and moderately painful stimuli, but not by non-painful stimuli. The latency of pain-related potentials was not significantly different between stimuli. The amplitudes of both P2 and N2 components significantly increased when intense nociception was applied, and the increments mainly originated from theta oscillations. Conclusion: The combination of QST with EEG was feasible for subjective and objective pain assessment. Distinct patterns of brain potentials were associated with the phenotype of the peripheral stimuli (e.g., noxious versus. innoxious, high versus. low pain intensity).

Visual cortical LFP in relation to the hippocampal theta rhythm in track running rats

Theta oscillations in the primary visual cortex (VC) have been observed during running tasks, but the mechanism behind their generation is not well understood. Some studies have suggested that theta in the VC is locally generated, while others have proposed that it is volume conducted from the hippocampus. The present study aimed to investigate the relationship between hippocampal and VC LFP dynamics. Analysis of power spectral density revealed that LFP in the VC was similar to that in the hippocampus, but with lower overall magnitude. As running velocity increased, both the power and frequency of theta and its harmonics increased in the VC, similarly to what is observed in the hippocampus. Current source density analysis triggered to theta did not identify distinct current sources and sinks in the VC, supporting the idea that theta in the VC is conducted from the adjacent hippocampus. Phase coupling between theta, its harmonics, and gamma is a notable feature in the hippocampus, particularly in the lacunosum moleculare. While some evidence of coupling between theta and its harmonics in the VC was found, bicoherence estimates did not reveal significant phase coupling between theta and gamma. Similar results were seen in the cross-region bicoherence analysis, where theta showed strong coupling with its harmonics with increasing velocity. Thus, theta oscillations observed in the VC during running tasks are likely due to volume conduction from the hippocampus.

Nonlinear Theta-Gamma Coupling between the Anterior Thalamus and Hippocampus Increases as a Function of Running Speed

The hippocampal theta rhythm strongly correlates to awake behavior leading to theories that it represents a cognitive state of the brain. As theta has been observed in other regions of the Papez circuit, it has been theorized that activity propagates in a reentrant manner. These observations complement the energy cascade hypothesis in which large-amplitude, slow-frequency oscillations reflect activity propagating across a large population of neurons. Higher frequency oscillations, such as gamma, are related to the speed with which inhibitory and excitatory neurons interact and distribute activity on the local level. The energy cascade hypothesis suggests that the larger anatomic loops, maintaining theta, drive the smaller loops. As hippocampal theta increases in power with running speed, so does the power and frequency of the gamma rhythm. If theta is propagated through the circuit, it stands to reason that the local field potential (LFP) recorded in other regions would be coupled to the hippocampal theta, with the coupling increasing with running speed. We explored this hypothesis using open-source simultaneous recorded data from the CA1 region of the hippocampus and the anterior dorsal and anterior ventral thalamus. Cross-regional theta coupling increased with running speed. Although the power of the gamma rhythm was lower in the anterior thalamus, there was an increase in the coupling of hippocampal theta to anterior thalamic gamma. Broadly, the data support models of how activity moves across the nervous system, suggesting that the brain uses large-scale volleys of activity to support higher cognitive processes.