Although transcranial magnetic stimulation (TMS) is widely used in neuromodulation, conventional TMS struggles to achieve both depth and focal specificity. Temporal interference TMS (TI-TMS) offers a promising approach to enhance stimulation depth while reducing the focal area; however, current research remains largely simulation-based, with limited studies on system implementation and experimental validation in rodent deep brain regions. To address this, we developed a TI-TMS system based on a realistic mouse head model using finite element simulation. Electrophysiological recordings of local field potentials (LFPs) in the ventral hippocampal formation (vHPC) were performed to evaluate changes in θ rhythm power spectral density (PSD) and θ-γ phase-amplitude coupling (PAC) following stimulation. The results demonstrated that TI-TMS enhanced θ rhythm power and strengthened θ-γ PAC, indicating effective modulation of deep brain regions. This study establishes a functional TI-TMS system capable of effectively stimulating deep vHPC, providing an experimental basis for its application in precise neuromodulation of subcortical brain areas.
With the widespread use of electrical equipment, cognitive functions such as working memory (WM) could be severely affected when people are exposed to 50 Hz electromagnetic fields (EMF) for long term. However, the effects of EMF exposure on WM and its neural mechanism remain unclear. In the present paper, 15 rats were randomly assigned to three groups, and exposed to an EMF environment at 50 Hz and 2 mT for a different duration: 0 days (control group), 24 days (experimental group I), and 48 days (experimental group II). Then, their WM function was assessed by the T-maze task. Besides, their local field potential (LFP) in the media prefrontal cortex (mPFC) was recorded by the in vivo multichannel electrophysiological recording system to study the power spectral density (PSD) of θ and γ oscillations and the phase-amplitude coupling (PAC) intensity of θ-γ oscillations during the T-maze task. The results showed that the PSD of θ and γ oscillations decreased in experimental groups I and II, and the PAC intensity between θ and high-frequency γ (hγ) decreased significantly compared to the control group. The number of days needed to meet the task criterion was more in experimental groups I and II than that of control group. The results indicate that long-term exposure to EMF could impair WM function. The possible reason may be the impaired communication between different rhythmic oscillations caused by a decrease in θ-hγ PAC intensity. This paper demonstrates the negative effects of EMF on WM and reveals the potential neural mechanisms from the changes of PAC intensity, which provides important support for further investigation of the biological effects of EMF and its mechanisms.
The transmission and interaction of neural information between the hippocampus and the prefrontal cortex play an important role in learning and memory. However, the specific effects of learning memory-related tasks on the connectivity characteristics between these two brain regions remain inadequately understood. This study employed in vivo microelectrode recording to obtain local field potentials (LFPs) from the ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC) in eight rats during the performance of a T-maze task, assessed both before and after task learning. Additionally, dynamic causal modeling (DCM) was utilized to analyze alterations in causal connectivity between the vHPC and the mPFC during memory task execution pre- and post-learning. Results indicated the presence of forward connections from vHPC to mPFC and backward connections from mPFC to vHPC during the T-maze task. Moreover, the forward connection between these brain regions was slightly enhanced after task learning, whereas the backward connection was diminished. These changes in connectivity corresponded with the observed trends when the rats correctly performed the T-maze task. In conclusion, this study may facilitate future investigations into the underlying mechanisms of learning and memory from the perspective of connectivity characteristics between distinct brain regions.