Two new methods for quantifying the rapidity of action potential onset have lower relative standard deviations and better distinguish neuron cell types than current methods. Action potentials (APs) in most central mammalian neurons exhibit sharp onset dynamics. The main views explaining such an abrupt onset differ. Some studies suggest sharp onsets reflect cooperative sodium channels activation, while others suggest they reflect AP backpropagation from the axon initial segment. However, AP onset rapidity is defined subjectively in these studies, often using the slope at an arbitrary value on the phase plot. Thus, we proposed more systematic methods using the membrane potential’s second-time derivative ( V¨m ) peak width. Here, the AP rapidity was measured for four different cortical and hippocampal neuron types using four quantification methods: the inverse of full-width at the half maximum of the V¨m peak (IFWd²), the inverse of half-width at the half maximum of the V¨m peak (IHWd²), the phase plot slope, and the error ratio method. The IFWd²and IHWd²methods show the smallest variation among neurons of the same type. Furthermore, the AP rapidity, using the V¨m peak width methods, significantly differentiates between different types of neurons, indicating that AP rapidity can be used to classify neuron types. The AP rapidity measured using the IFWd²method was able to differentiate between all four neuron types analyzed. Therefore, the V¨m peak width methods provide another sensitive tool to investigate the mechanisms impacting the AP onset dynamics.

Background: Transcranial direct current stimulation (tDCS) has exhibited potential in augmenting motor functions, neuroplasticity, and cognitive abilities within neurological rehabilitation contexts. Despite these promising outcomes, the utilization of tDCS in both research and clinical environments in Saudi Arabia remains relatively unexplored. Objective: This study aims to evaluate the knowledge, attitudes, and motivations of rehabilitation specialists in Saudi Arabia concerning tDCS. Methods: A cross-sectional observational study was conducted through an online questionnaire, involving 112 registered rehabilitation professionals. Results: While 58% of respondents acknowledged tDCS as a therapeutic tool, the overall knowledge level was modest, with a mean score of 3.0 ± 2.7 out of 9. Enhanced levels of knowledge were associated with individuals holding doctoral degrees (p = 0.02) and those with international training exposure (p = 0.03). Despite the limited knowledge base, an overwhelming 94.64% of participants displayed a neutral to positive attitude towards tDCS, with 52.7% recognizing its potential efficacy in neurological recovery. Principal obstacles to implementation included safety-related concerns (21.4%) and the need for specialized training (23.3%). Conclusions: Rehabilitation specialists in Saudi Arabia generally hold a favorable view of tDCS and demonstrate an eagerness to pursue further training. The results underscore the imperative for enhanced educational initiatives and practical training to address knowledge deficiencies and facilitate the seamless integration of tDCS into clinical routines. The implementation of structured training programs could not only reinforce adoption rates but also optimize the role of tDCS within rehabilitation.

Pyramidal neurons and interneurons play critical roles in regulating the neuronal activities in the mammalian cortex, where they exhibit different firing patterns. Pyramidal neurons mainly exhibit regular-spiking firing patterns, while interneurons have fast-spiking firing patterns. Cortical neurons have distinct action potential onset dynamics, in which the evoked action potential is rapid and highly variable. However, it is still unclear how cortical regular-spiking and fast-spiking neurons discriminate between different types of stimuli by changing their action potential onset parameters. Thus, we used intracellular recordings of regular-spiking and fast-spiking neurons, taken from layer 2/3 in the somatosensory cortex of adult mice, to investigate changes in the action potential waveform in response to two distinct stimulation protocols: the conventional step-and-hold and frozen noise. The results show that the frozen noise stimulation paradigm evoked more rapid action potential with lower threshold potential in both neuron types. Nevertheless, the difference in the action potential rapidity in response to different stimuli was significant in regular-spiking pyramidal neurons while insignificant in fast-spiking interneurons. Furthermore, the threshold variation was significantly higher for regular-spiking neurons than for fast-spiking neurons. Our findings demonstrate that different types of cortical neurons exhibit various onset dynamics of the action potentials, implying that different mechanisms govern the initiation of action potentials across cortical neuron subtypes.

Action potentials (AP) are the basic elements of information processing in the nervous system. Understanding AP generation mechanisms is a critical step to understand how neurons encode information. However, an individual neuron might fire APs with various shapes even in response to the same stimulus, and the mechanisms responsible for this variability remain unclear. Therefore, we analyzed four AP attributes including AP rapidity and threshold during consecutive bursts from three neuron types using intracellular electrophysiological recordings. In response to consecutive current steps, the AP attributes in evoked spike trains show two distinctive patterns across different neurons: (1) The first APs from each train always have comparable properties regardless of the stimulus strength; (2) The attributes of the subsequent APs during each pulse monotonically change during the burst, where the magnitude of AP attribute change during each pulse increases with increasing stimulation strength. Various conductance-based models were explored to determine if they replicated the observed AP bursts. The observed patterns could not be replicated using the classical HH-type models, or modified HH model with cooperative Na ⁺ gating. However, adding ion concentration dynamics to the model reproduced the AP attribute variation, and the magnitude of change during a pulse correlated with change in dynamic reversal potential (DRP), but failed to replicate the first AP attributes pattern. Then, the role of cooperative Na ⁺ gating on neuronal firing dynamics was investigated. Inclusion of cooperative gating restored the first APs’ attributes and enhanced the magnitude of modeled variation of some AP attributes to better agree with observed data. We conclude that changes in local ion concentrations could be responsible for the monotonic change in APs attributes during neuronal bursts, and cooperative gating of Na ⁺ channels can enhance the effect. Thus, the two mechanisms could contribute to the observed variability in neuronal response.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that impairs cognitive and psychological performance and adversely impacts daily routines and activities. We hypothesized that Binaural beat stimulation (BBS) enhances psychological performance by increasing connectivity in the θ- and α- bands over the fronto-parietal region. Twenty-five AD patients received either Binaural beat (BBS) or Standard Auditory beat stimulation (SAS) for 12 consecutive days. Psychometric assessments (Blessed Dementia Scale, Depression Anxiety Stress Scale, and Mini-Mental State Examination) and a 38-channel EEG were conducted on Day 1 and Day 14. Independent t-tests (p< 0.05) compared the pre- and post-states of both groups. The neurological analysis was conducted using brain functional connectivity, including imaginary coherence and graph-theory parameters. Two-way ANOVA examined the effects of group and intervention on behavioral and connectivity outcomes, while Pearson’s correlation assessed the relationship between behavioral improvements and graph-theoretical metrics. The findings reveal significant changes in the network dynamics of the BBS group, including increased long-range θ-band connectivity and enhanced local α-band processing. These neural changes corresponded with improved cognitive and daily functioning, reflected by decreased BDS and DASS-21 scores and increased MMSE scores. This highlights the positive impact of BBS on AD patients’ neurological, psychological, and behavioral responses, suggesting a promising intervention for cognitive and psychological advancement in AD.

Surface electromyography (sEMG) is widely used to assess muscle activity in clinical and research settings. However, while conventional wet electrodes have advanced considerably in recent years, they are often limited by disposability, reduced comfort, and limited reusability. Recent advances in additive manufacturing provide opportunities to fabricate customizable, low-cost dry electrodes using conductive filaments. This study aimed to evaluate the feasibility and signal performance of in-house-fabricated 3D-printed sEMG electrodes made from three commercially available conductive filaments, (Fili, Filaflex, and Proto-Pasta) differing in base polymer and resistivity, and compared their performance with standard wet electrodes. Surface electrodes were placed over the biceps brachii muscle, and EMG signals were recorded during concentric–eccentric elbow flexion under three loading conditions (3, 5, and 7 kg). Signal quality was assessed using EMG amplitude, signal-to-noise ratio (SNR), and background noise. The results showed no significant differences in SNR or background noise between the 3D-printed electrodes and standard wet electrodes. Among the tested materials, Proto-Pasta electrodes produced the highest mean EMG amplitudes, while Filaflex electrodes showed slightly lower background noise, although these differences were not statistically significant. Overall, the findings indicate that in-house-fabricated 3D-printed electrodes can provide signal quality comparable to conventional wet electrodes, supporting their potential use as low-cost and customizable alternatives for sEMG applications in research and wearable monitoring systems.