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This study is aim 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 CA1 region and medial entorhinal cortex (MEC) of mice. 42 male ICR mice were randomized into control, HIIT, and MICT groups. Electrophysiological recordings were performed pre- and post-intervention to assess neural circuit dynamics and neuronal firing patterns in the CA1-MEC pathway. Both exercise protocols increased LFP coherence, with MICT showing a more pronounced effect on delta and gamma coherences ( P < 0.05). Both modalities reduced delta power spectral density (PSD; HIIT, P < 0.05; MICT, P < 0.01) and elevated theta, beta, and gamma 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), while 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, inter-burst 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 to 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.
This study is aim 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 CA1 region and medial entorhinal cortex (MEC) of mice. 42 male ICR mice were randomized into control, HIIT, and MICT groups. Electrophysiological recordings were performed pre- and post-intervention to assess neural circuit dynamics and neuronal firing patterns in the CA1-MEC pathway. Both exercise protocols increased LFP coherence, with MICT showing a more pronounced effect on delta and gamma coherences ( P < 0.05). Both modalities reduced delta power spectral density (PSD; HIIT, P < 0.05; MICT, P < 0.01) and elevated theta, beta, and gamma 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), while 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, inter-burst 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 to 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.
There is experimental evidence of varying correlation among the elements of the neuromuscular system over the course of the reach-and-grasp task. Several neuromuscular disorders are accompanied by anomalies in muscular coupling during the task. The aim of this study was to investigate if modifications in correlations and clustering can be detected in the Local Field Potential (LFP) recordings of the motor cortex during the task. To this end, we analyzed the LFP recordings from a previously published study on monkeys which performed a reach-and-grasp task for targets with a vertical or horizontal orientation. LFP signals were recorded from the motor and premotor cortex of macaque monkeys as they performed the task. We found very robust changes in the correlations of the multielectrode LFP recordings which corresponded to task epochs. Mean LFP correlation increased significantly during reaching and then decreased during grasp. This pattern was very robust for both left and right arm reaches irrespective of target orientation. A hierarchical cluster analysis supported the same conclusion – a decreased number of clusters during reach followed by an increase for grasp. As most previous LFP studies have focused on the question of LFP amplitude, our study has contributed to the understanding of this signal and its relationship to movement by focusing on correlations. A sliding window computation of the number of clusters was performed to probe the capacities of these LFP clusters for detecting upcoming task events. For a very high percentage of trials (97.89%), there was a downturn in cluster number following the Pellet Drop (GO signal) which reached a minimum preceding the Start of grasp, hence indicating that cluster analyses of LFP signals could add to signaling the increased probability of the Start of grasp.Significance StatementThe creation of muscular groups also called synergies for accomplishing an action is a well known feature of motor control. Since the motor cortex plays an important role in creating motor commands, it is only to be expected that such features might also be seen in this brain area. This study is among the first to show that alterations in local field potential (LFP) correlations as a function of task phase can be observed during the reach-and-grasp task by macaque monkeys. The LFPs recorded using multielectrode arrays in the motor cortex, showed increased correlations during reach, followed by decreased correlations at the start of grasp. This pattern was robust and held irrespective of which arm was employed or hand orientation.
Intracranial potentials are used as functional biomarkers of neural networks. As potentials spread away from the source populations, they become mixed in the recordings. In humans, interindividual differences in the gyral architecture of the cortex pose an additional challenge, as functional areas vary in location and extent. We used source separation techniques to disentangle mixing potentials obtained by exploratory deep arrays implanted in epileptic patients of either sex to gain access to the number, location, relative contribution and dynamics of co-active sources. The unique spatial profiles of separated generators made it possible to discern dozens of independent cortical areas for each patient, whose stability maintained even during seizure, enabling the follow up of activity for days and across states. Through matching these profiles to MRI, we associated each with limited portions of sulci and gyri, and determined the local or remote origin of the corresponding sources. We also plotted source-specific 3D coverage across arrays. In average, individual recording sites are contributed to by 3–5 local and distant generators from areas up to several centimeters apart. During seizure, 13-85 % of generators were involved, and a few appeared anew. Significant bias in location assignment using raw potentials is revealed, including numerous false positives when determining the site of origin of a seizure. This is not amended by bipolar montage, which introduce additional errors of its own. In this way, source disentangling reveals the multisource nature and far intracranial spread of potentials in humans, while efficiently addressing patient-specific anatomofunctional cortical divergence.Significance StatementField potentials are used to better localize zones showing normal and pathological activity. However, as potentials spread throughout the brain volume, they mix with others and make their place of origin uncertain, even when recorded intracranially. We used advanced algorithms to disentangle the activity of each these zones by their unique spatial profiles, which allowed us to determine the 3D outline of normal and epileptic areas and follow their activity for days. Dozens of independent sources per patient can be explored and precisely located. The findings show that standard stereoEEG recordings are contributed by 3-5 populations, which after separation will help to plan clinical intervention to break epileptic networks by more accurately marking epileptic foci and avoiding false positives.
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