Investigating the neural mechanisms of innate fear, considering oscillatory patterns, presents a promising avenue for future study.
Within the online version, further materials are available; they are located at the URL 101007/s11571-022-09839-6.
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With regard to social memory and encoding information from social experiences, the hippocampal CA2 region is vital. A preceding study of ours demonstrated a specific response of CA2 place cells to social stimuli, as published in Nature Communications by Alexander et al. (2016). An earlier study, appearing in Elife (Alexander, 2018), indicated that hippocampal CA2 activation induces slow gamma rhythmicity, oscillating within the frequency range of 25 to 55 Hz. Considering these results simultaneously, one is led to question whether slow gamma rhythms are involved in the synchronization of CA2 activity during social information processing tasks. The transmission of social memories from the CA2 to CA1 hippocampus could potentially be correlated with slow gamma oscillations, potentially serving to combine information across brain areas or to boost social memory retrieval. Four rats, engaging in a social exploration task, had local field potentials recorded from their hippocampal subregions CA1, CA2, and CA3. Within each subfield, we investigated the activity of theta, slow gamma, and fast gamma rhythms, as well as sharp wave-ripples (SWRs). Our investigation into subfield interactions took place during social exploration sessions, and during subsequent sessions focused on presumed social memory retrieval. CA2 slow gamma rhythms increased in response to social interactions, a change absent during non-social exploration activities. The CA2-CA1 theta-show gamma coupling mechanism exhibited a surge in strength during social exploration. Furthermore, CA1's slow gamma rhythms and sharp wave ripples were associated with the presumed process of recalling social memories. In essence, the results presented here demonstrate a relationship between CA2-CA1 interactions, occurring through slow gamma oscillations, and the process of encoding social memories; CA1 slow gamma activity is further observed to correlate with the retrieval of these social memories.
The online version's supporting materials, which are an integral part of the publication, can be found at 101007/s11571-022-09829-8.
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Parkinson's disease (PD) often presents abnormal beta oscillations (13-30 Hz), frequently linked with the external globus pallidus (GPe), a subcortical nucleus deeply involved within the basal ganglia's indirect pathway. Despite the many proposed mechanisms for the emergence of these beta oscillations, the functional significance of the GPe, especially whether it is capable of generating beta oscillations, continues to be elusive. A well-documented firing rate model of the GPe neural population is used to examine the part the GPe plays in producing beta oscillations. The results of our extensive simulations highlight the significant role of the transmission delay within the GPe-GPe pathway in inducing beta oscillations, and the impact of the time constant and connection strength of the GPe-GPe pathway on the generation of these oscillations is substantial. Beyond this, the firing characteristics of GPe cells are greatly dependent on the time constant of the GPe-GPe pathway's connections, its connection strength, and the transmission delay along this same circuit. Interestingly, the manipulation of transmission delay, whether amplified or diminished, can influence the GPe's firing pattern, shifting it from beta oscillations to alternative patterns, including both oscillatory and non-oscillatory firing. These findings imply that transmission delays within the GPe exceeding 98 milliseconds could generate beta oscillations intrinsically within the GPe neuronal population. This intrinsic generation may also be the source of PD-related beta oscillations, making it a promising therapeutic target for Parkinson's disease.

The communication between neurons, fostered by synaptic plasticity and synchronization, is vital for learning and memory. STDP, or spike-timing-dependent plasticity, is a synaptic modification mechanism whereby the efficacy of connections between neurons is adjusted based on the precision of timing between pre- and post-synaptic action potentials. Simultaneously, STDP forms neuronal activity and synaptic connections through a feedback mechanism in this manner. Physical distance-induced transmission delays undermine 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. The two-neuron motif's activity synchronizes in either in-phase or anti-phase patterns, which are influenced by transmission delay range, and in parallel, its connectivity adopts either symmetric or asymmetric coupling. The coevolutionary interplay between neuronal systems and synaptic weights, influenced by STDP, stabilizes motifs in in-phase/anti-phase synchronization or symmetric/asymmetric coupling regimes based on precise transmission delay. 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.

This study seeks to investigate the impact of acute high-frequency repetitive transcranial magnetic stimulation (hf-rTMS) on the excitability of granule cells within the hippocampal dentate gyrus, along with the underlying intrinsic mechanisms that mediate rTMS's influence on neuronal excitability. Initially, high-frequency single transcranial magnetic stimulation (TMS) was utilized to assess the motor threshold (MT) in mice. Subsequently, acute mouse brain slices received rTMS stimulation at varying intensities: 0 mT (control), 8 mT, and 12 mT. Subsequently, the patch-clamp technique was employed to measure the resting membrane potential and elicited nerve impulses of granule cells, alongside the voltage-gated sodium current (Ina) of voltage-gated sodium channels (VGSCs), the transient outward potassium current (IA) and the delayed rectifier potassium current (IK) of voltage-gated potassium channels (KVs). The findings from hf-rTMS on both the 08 MT and 12 MT groups revealed significant activation of I Na and inhibition of I A and I K channels. This contrasted with the control group and was linked to changes in the dynamic properties of voltage-gated sodium and potassium channels. Acute hf-rTMS intervention led to a significant increase in membrane potential and nerve discharge frequency in both the 08 MT and 12 MT groups. Dynamic modifications to voltage-gated sodium channels (VGSCs) and potassium channels (Kv), combined with activation of the sodium current (I Na) and inhibition of A-type and delayed rectifier potassium currents (I A and I K), are potentially intrinsic mechanisms responsible for rTMS-induced enhancement of neuronal excitability in granular cells. The impact of this regulation increases with the strength of the stimulus.

This paper examines the problem of H-state estimation for quaternion-valued inertial neural networks (QVINNs) experiencing nonuniform time-varying delays. 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. selleck kinase inhibitor By employing a newly designed Lyapunov function incorporating adjustable parameters, readily verifiable algebraic criteria are derived to confirm the asymptotic stability of the error state system, achieving the desired H performance. Additionally, a sophisticated algorithm is used to create the parameters of the estimator. For the purpose of illustrating the feasibility of the state estimator, a numerical example is presented.

Newly discovered data in this study demonstrates a significant link between graph-theoretic global brain connectivity and the ability of healthy adults to regulate and manage 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. immune factor From the public LEMON dataset, individual participants' EEG measurements and psychometric scores were retrieved. The Directed Transfer Function, unaffected by volume conduction, was applied to 62-channel recordings to estimate cortical connectivity across the entire cerebral cortex. Genetic exceptionalism Connectivity estimations, when adhering to a precisely established threshold, are rendered into binary format for application within the Brain Connectivity Toolbox. The groups' comparison relies on both statistical logistic regression models and deep learning models, utilizing frequency band-specific network measures that assess segregation, integration, and modularity. Results from full-band (0.5-45 Hz) EEG analysis show significant classification accuracies of 96.05% (1st vs 2nd) and 89.66% (3rd vs 4th) when considering overall performance. Overall, strategies with a negative impact can disrupt the equilibrium between division and combination. Visually, the data indicates that frequent rumination diminishes the assortativity of the network, thereby impacting its resilience.