A helpful avenue for future research on innate fear might be a deeper investigation of its underlying neural mechanisms, taking an oscillatory viewpoint into account.
Supplementary materials for the online version are accessible at 101007/s11571-022-09839-6.
The online version's supplementary material is linked through the URL 101007/s11571-022-09839-6.
The encoding of social experience information and the support of social memory are functions of the hippocampal CA2 area. In our prior investigation, CA2 place cells exhibited a selective reaction to social cues, as detailed in the publication by Alexander et al. (2016) in Nature Communications. Previously reported in Elife (Alexander, 2018), a study indicated that activation of CA2 within the hippocampus led to the emergence of slow gamma rhythms, with frequencies between 25 and 55 hertz. In light of these findings, a crucial question emerges: do slow gamma rhythms influence the coordinated activity of CA2 neurons during social information processing? Our prediction is that slow gamma activity will be associated with the transmission of social memories from the CA2 region to the CA1 region, likely to promote the integration of information across brain regions or to support the retrieval of social memories. Local field potentials were recorded from the hippocampal subfields CA1, CA2, and CA3 in 4 rats undergoing a social exploration task. The activity of theta, slow gamma, and fast gamma rhythms and sharp wave-ripples (SWRs) was characterized within each subfield. We studied subfield interactions in social exploration sessions and during the subsequent phase of presumed social memory retrieval. While social interactions resulted in elevated CA2 slow gamma rhythms, non-social exploration did not produce any such increase. Enhanced CA2-CA1 theta-show gamma coupling was observed in conjunction with social exploration activity. Besides this, slow gamma activity in CA1, combined with sharp wave ripples, was thought to be related to the recovery of social memories. To conclude, the obtained results suggest a critical role for CA2-CA1 interactions facilitated by slow gamma oscillations during the formation of social memories, and an association between CA1 slow gamma activity and the retrieval of social memories.
The online version's supplemental materials are detailed and accessible at 101007/s11571-022-09829-8.
Supplementary materials for the online version are located at the following URL: 101007/s11571-022-09829-8.
Parkinson's disease (PD) often exhibits abnormal beta oscillations (13-30 Hz), which are strongly correlated with the external globus pallidus (GPe), a subcortical nucleus integral to the basal ganglia's indirect pathway. Even with the various mechanisms put forward to explain these beta oscillations, the functional contribution of the GPe, and specifically its inherent capacity for generating beta oscillations, remains unclear. To understand the role of the GPe in beta oscillations, we use a well-described firing rate model for the GPe neural population. Extensive simulations reveal that the transmission delay along the GPe-GPe pathway is a substantial contributor to the generation of beta oscillations, and the influence of the time constant and connection strength within this pathway on beta oscillation generation is also significant. In addition, the temporal characteristics of GPe's firing activity are considerably modified by the time constant and connection strength of the GPe-GPe circuit, along with the transmission latency of signals within this circuit. Remarkably, adjustments to transmission delay, whether upward or downward, can shift the GPe's firing pattern from beta oscillations to diverse firing patterns, encompassing both oscillatory and non-oscillatory activity. Research suggests that GPe transmission delays of at least 98 milliseconds can initiate beta oscillations within the GPe neuronal population. This intrinsic origin of beta oscillations may also be a root cause in Parkinson's disease, making the GPe a potentially impactful treatment target for PD.
The key to learning and memory lies in synchronization, supporting the communication between neurons, and fueled by synaptic plasticity. Synaptic plasticity, known as spike-timing-dependent plasticity (STDP), fine-tunes the strength of connections between neurons, regulated by the simultaneous occurrence of pre- and postsynaptic action potentials. Thus, STDP simultaneously shapes the dynamics of neuronal activity and synaptic connectivity in a feedback loop. Despite the proximity of neurons, the physical distance still causes transmission delays, impacting neuronal synchronization and the symmetry of synaptic coupling. To determine how transmission delays and spike-timing-dependent plasticity (STDP) jointly influence the emergence of pairwise activity-connectivity patterns, we analyzed the phase synchronization properties and coupling symmetry of two bidirectionally coupled neurons, using phase oscillator and conductance-based neuron models. We demonstrate that the transmission delay range influences the two-neuron motif's ability to achieve in-phase or anti-phase synchronization, while its connectivity transitions between symmetric and asymmetric coupling patterns. Stable motifs in neuronal systems, co-evolving with synaptic weights regulated by STDP, are achieved via transitions between in-phase/anti-phase synchronization and symmetric/asymmetric coupling regimes at specific transmission delays. Despite the substantial influence of neuron phase response curves (PRCs) on these transitions, they prove remarkably resilient to disparities in transmission delays and the STDP profile's imbalance between potentiation and depression.
By applying acute high-frequency repetitive transcranial magnetic stimulation (hf-rTMS), this study will explore how it affects granule cell excitability in the hippocampus' dentate gyrus, and will also determine the inherent mechanisms through which it affects neuronal excitability. The motor threshold (MT) of mice was measured by using high-frequency single transcranial magnetic stimulation (TMS). Acute mouse brain tissue slices then underwent rTMS treatments, with intensities ranging from 0 mT (control) to 8 mT and 12 mT. Utilizing the patch-clamp method, the resting membrane potential and evoked nerve discharges of granule cells were recorded, along with the voltage-gated sodium current (I Na) of voltage-gated sodium channels (VGSCs), the transient outward potassium current (I A), and the delayed rectifier potassium current (I K) of voltage-gated potassium channels (Kv). The observed activation of I Na and inhibition of I A and I K channels in the 08 MT and 12 MT groups after acute hf-rTMS treatment clearly contrasted with the control group. These changes are directly attributable to shifts in the dynamic properties of voltage-gated sodium channels (VGSCs) and potassium channels (Kv). Significant increases in membrane potential and nerve discharge frequency were observed following acute hf-rTMS treatment in the 08 MT and 12 MT groups. Consequently, modifications to the dynamic properties of voltage-gated sodium channels (VGSCs) and potassium channels (Kv), alongside the activation of sodium current (I Na) and the inhibition of both the A-type potassium current (I A) and the delayed rectifier potassium current (I K), could represent an intrinsic mechanism underlying the enhancement of neuronal excitability in granular cells by repetitive transcranial magnetic stimulation (rTMS). This regulatory influence intensifies with rising stimulus strength.
H-state estimation in quaternion-valued inertial neural networks (QVINNs) with non-identical time-varying delay is the subject of this paper. A non-reduced-order technique is employed to analyze the given QVINNs, diverging from the common practice of converting the initial second-order system into two first-order systems, as adopted in many existing references. parasitic co-infection Through the construction of a new Lyapunov functional with tunable parameters, verifiable algebraic criteria are established, ensuring the asymptotic stability of the error state system, thereby attaining the desired H performance. On top of that, an effective algorithm is furnished to construct the estimator's parameter values. Subsequently, a numerical example is offered to show the practicality of the state estimator.
Recent research reveals a strong connection between global brain connectivity, as measured using graph theory, and healthy adults' capacity for managing and regulating negative emotions. EEG recordings from resting states, with subjects' eyes open and closed, were used to gauge functional brain connectivity patterns across four groups differentiated by their emotion regulation strategies (ERS). The first group encompassed 20 participants who frequently engaged in contrasting strategies, such as rumination and cognitive distraction. Conversely, the second group comprised 20 participants who did not deploy these cognitive strategies. In the third and fourth groups, there are individuals who frequently employ both Expressive Suppression and Cognitive Reappraisal strategies in tandem, and others who never utilize either strategy. LNG451 Data concerning EEG measurements and psychometric scores for individuals were downloaded from the public LEMON repository. The Directed Transfer Function's immunity to volume conduction enabled its application to 62-channel recordings for the purpose of assessing cortical connectivity throughout the entire cortical structure. Fumed silica Employing a well-defined threshold, connectivity estimations were reformatted into binary representations for the Brain Connectivity Toolbox's operational use. Utilizing frequency band-specific network measures of segregation, integration, and modularity, the groups are compared via both statistical logistic regression and deep learning models. A full-band (0.5-45 Hz) EEG analysis shows a significant achievement in classification accuracy, achieving 96.05% (1st vs 2nd) and 89.66% (3rd vs 4th) according to overall results. In the final analysis, approaches that are unfavorable may throw off the equilibrium between isolation and unification. Specifically, visual results reveal that often ruminating reduces network resilience, as observed through a decrease in assortativity.