Decrease in reaction time for volleyball athletes during saccadic eye movement task: A preliminary study with evoked potentials.

AIM: This preliminary study investigated the differences in event-related potential and reaction time under two groups (athletes vs. non-athletes). MATERIAL AND METHODS: The P300 was analyzed for Fz, Cz, and Pz electrodes in thirty-one healthy volunteers divided into two groups (volleyball athletes and non-athletes). In addition, the participants performed a saccadic eye movement task to measure reaction time. RESULTS: The EEG analysis showed that the athletes, in comparison to the no-athletes, have differences in the P300 in the frontal area (p = 0.021). In relation to reaction time, the results show lower reaction time for athletes (p = 0.001). CONCLUSIONS: The volleyball athletes may present a greater allocation of attention during the execution of the inhibition task, since they have a lower reaction time for responses when compared to non-athletes.

Neural coding of space by time.

The intertwining of space and time poses a significant scientific challenge, transcending disciplines from philosophy and physics to neuroscience. Deciphering neural coding, marked by its inherent spatial and temporal dimensions, has proven to be a complex task. In this paper, we present insights into temporal and spatial modes of neural coding and their intricate interplay, drawn from neuroscientific findings. We illustrate the conversion of a purely spatial input into the temporal form of a singular spike train, demonstrating storage, transmission to remote locations, and recall through spike bursts corresponding to Sharp Wave Ripples. Moreover, the converted temporal representation can be transformed back into a spatiotemporal pattern. The principles of the transformation process are illustrated using a simple feed-forward spiking neural network. The frequencies and phases of Subthreshold Membrane potential Oscillations play a pivotal role in this framework. The model offers insights into information multiplexing and phenomena such as stretching or compressing time of spike patterns.

Modern Artificial Neural Networks: Is Evolution Cleverer?

Machine learning tools, particularly artificial neural networks (ANN), have become ubiquitous in many scientific disciplines, and machine learning-based techniques flourish not only because of the expanding computational power and the increasing availability of labeled data sets but also because of the increasingly powerful training algorithms and refined topologies of ANN. Some refined topologies were initially motivated by neuronal network architectures found in the brain, such as convolutional ANN. Later topologies of neuronal networks departed from the biological substrate and began to be developed independently as the biological processing units are not well understood or are not transferable to in silico architectures. In the field of neuroscience, the advent of multichannel recordings has enabled recording the activity of many neurons simultaneously and characterizing complex network activity in biological neural networks (BNN). The unique opportunity to compare large neuronal network topologies, processing, and learning strategies with those that have been developed in state-of-the-art ANN has become a reality. The aim of this review is to introduce certain basic concepts of modern ANN, corresponding training algorithms, and biological counterparts. The selection of these modern ANN is prone to be biased (e.g., spiking neural networks are excluded) but may be sufficient for a concise overview.

Secure data authentication and access control protocol for industrial healthcare system.

Because of recent COVID-19 epidemic, the Internet-of-Medical-Things (IoMT) has acquired a significant impetus to diagnose patients remotely, regulate medical equipment, and track quarantined patients via smart electronic devices installed at the patient's end. Nevertheless, the IoMT confronts various security and privacy issues, such as entity authentication, confidentiality, and integrity of health-related data, among others, rendering this technology vulnerable to different attacks. To address these concerns, a number of security procedures based on traditional cryptographic approaches, such as discrete logarithm and integer factorization problems, have been developed. All of these protocols, however, are vulnerable to quantum attacks. This paper, in this context, presents a data authentication and access control protocol for IoMT systems that can withstand quantum attacks. A comprehensive formal security assessment demonstrates that the proposed algorithm can endure both current and future threats. In terms of data computing, transmission, and key storage overheads, it also surpasses other related techniques.

Open monitoring meditation alters the EEG gamma coherence in experts meditators: The expert practice exhibit greater right intra-hemispheric functional coupling.

AIM: This study investigated the differences in frontoparietal EEG gamma coherence between expert meditators (EM) and naïve meditators (NM). MATERIAL AND METHODS: This is a cross-sectional study with a sample of twenty-one healthy adults divided under two groups (experts meditators vs. naive-meditators), with analyzing the intra-hemispheric coherence of frontoparietal gamma oscillations by electroencephalography during the study steps: EEG resting-state 1, during the open presence meditation practice, and EEG resting-state 2. RESULTS: The findings demonstrated greater frontoparietal EEG coherence in gamma for experts meditators in the Fp1-P3, F4-P4, F8-P4 electrode pairs during rest 1 and rest 2 (p ≤ 0.0083). In addition, we evidenced differences in the frontoparietal EEG coherence for expert meditators in F4-P4, F8-P4 during the meditation (p ≤ 0.0083). CONCLUSION: Our results can support evidence that the connectivity of the right frontoparietal network acts as a biomarker of the enhanced Open monitoring meditation training.

A Model of Pattern Separation by Single Neurons.

For efficient processing, spatiotemporal spike patterns representing similar input must be able to transform into a less similar output. A new computational model with physiologically plausible parameters shows how the neuronal process referred to as "pattern separation" can be very well achieved by single neurons if the temporal qualities of the output patterns are considered. Spike patterns generated by a varying number of neurons firing with fixed different frequencies within a gamma range are used as input. The temporal and spatial summation of dendritic input combined with theta-oscillating excitability in the output neuron by subthreshold membrane potential oscillations (SMOs) lead to high temporal separation by different delays of output spikes of similar input patterns. A Winner Takes All (WTA) mechanism with backward inhibition suffices to transform the spatial overlap of input patterns to much less temporal overlap of the output patterns. The conversion of spatial patterns input into an output with differently delayed spikes enables high separation effects. Incomplete random connectivity spreads the times up to the first spike across a spatially expanded ensemble of output neurons. With the expansion, random connectivity becomes the spatial distribution mechanism of temporal features. Additionally, a "synfire chain" circuit is proposed to reconvert temporal differences into spatial ones.

Bromazepam increases the error of the time interval judgments and modulates the EEG alpha asymmetry during time estimation.

AIM: This study investigated the bromazepam effects in male subjects during the time estimation performance and EEG alpha asymmetry in electrodes associated with the frontal and motor cortex. MATERIAL AND METHODS: This is a double-blind, crossover study with a sample of 32 healthy adults under control (placebo) vs. experimental (bromazepam) during visual time-estimation task in combination with electroencephalographic analysis. RESULTS: The results demonstrated that the bromazepam increased the relative error in the 4 s, 7 s, and 9 s intervals (p = 0.001). In addition, oral bromazepam modulated the EEG alpha asymmetry in cortical areas during the time judgment (p ≤ 0.025). CONCLUSION: The bromazepam decreases the precision of time estimation judgments and modulates the EEG alpha asymmetry, with greater left hemispheric dominance during time perception. Our findings suggest that bromazepam influences internal clock synchronization via the modulation of GABAergic receptors, strongly relating to attention, conscious perception, and behavioral performance.

Non-immersive 3D virtual stimulus alter the time production task performance and increase the EEG theta power in dorsolateral prefrontal cortex.

AIM: The study investigated the cortical activity changes and time production task performance induced by changes in motion speed of a non-immersive 3D virtual stimulus. MATERIAL AND METHODS: Twenty-one individuals were participated in the crossover study with the visual-time reproduction task under three-speed conditions: original, slow and fast virtual stimulus. In addition, the electroencephalographic analysis of the theta band power in the dorsolateral prefrontal cortex was done simultaneously with time production task execution. RESULTS: The results demonstrated that in the slow speed condition, there is an increase in the error in the time production task after virtual reality (p < 0.05). There is also increased EEG theta power in the right dorsolateral prefrontal cortex in all speed conditions (p < 0.05). CONCLUSIONS: We propose that the modulations of speed of virtual stimulus may underlie the accumulation of temporal pulses, which could be responsible for changes in the performance of the production task of the time intervals and a substantial increase in right dorsolateral prefrontal cortex activity related to attention and memory, acting in cognitive domains of supraseconds.

Repetitive transcranial magnetic stimulation changes cognitive/motor tasks performance: An absolute alpha and beta power study.

The voluntary movement demands integration between cognitive and motor functions. During the initial stages of motor learning until mastery of a new motor task, and during a demanding task that is not automatic, cognitive and motor functions can be perceived as independent from each other. Areas used for actually performing motor tasks are essentially the same used by Motor Imagery (MI). The main objective of this study was to investigate inhibition effects on cognitive functions of motor skills induced by low-frequency (1 Hz) Repetitive Transcranial Magnetic Stimulation (rTMS) at the sensory-motor integration site (Cz). In particular, the goal was to examine absolute alpha and beta power changes on frontal regions during Execution, Action observation, and Motor Imagery of finger movement tasks. Eleven healthy, right-handed volunteers of both sexes (5 males, 6 females; mean age 28 ± 5 years), with no history of psychiatric or neurological disorders, participated in the experiment. The execution task consisted of the subject flexing and extending the index finger. The action observation task involved watching a video of the same movement. The motor imagery task was imagining the flexion and extension of the index finger movement. After performing the tasks randomly, subjects were submitted to 15 min of low-frequency rTMS and performed the tasks again. All tasks were executed simultaneously with EEG signals recording. Our results demonstrated a significant interaction between rTMS and the three tasks in almost all analyzed regions showing that rTMS can affect the frontal region regarding Execution, Action observation, and Motor Imagery tasks.

A Model of Memory Linking Time to Space.

The storage of temporally precise spike patterns can be realized by a single neuron. A spiking neural network (SNN) model is utilized to demonstrate the ability to precisely recall a spike pattern after presenting a single input. We show by using a simulation study that the temporal properties of input patterns can be transformed into spatial patterns of local dendritic spikes. The localization of time-points of spikes is facilitated by phase-shift of the subthreshold membrane potential oscillations (SMO) in the dendritic branches, which modifies their excitability. In reference to the points in time of the arriving input, the dendritic spikes are triggered in different branches. To store spatially distributed patterns, two unsupervised learning mechanisms are utilized. Either synaptic weights to the branches, spatial representation of the temporal input pattern, are enhanced by spike-timing-dependent plasticity (STDP) or the oscillation power of SMOs in spiking branches is increased by dendritic spikes. For retrieval, spike bursts activate stored spatiotemporal patterns in dendritic branches, which reactivate the original somatic spike patterns. The simulation of the prototypical model demonstrates the principle, how linking time to space enables the storage of temporal features of an input. Plausibility, advantages, and some variations of the proposed model are also discussed.

Unskilled shooters improve both accuracy and grouping shot having as reference skilled shooters cortical area: An EEG and tDCS study.

Transcranial direct current stimulation (tDCS) has been used as a non-invasive method for enhanced motor and cognitive abilities. However, no previous study has investigated if the tDCS application in unskilled shooters on cortical sites, selected based on the cortical activity of skilled shooters, improves the accuracy and shot grouping. Sixty participants were selected, which included 10 skilled shooters and 50 unskilled shooters. After we identified the right dorsolateral prefrontal cortex (DLPFC) as the area with the highest activity in skilled shooters, we applied anodal tDCS over the right DLPFC in the unskilled shooters under two conditions: sham-tDCS (placebo) and real-tDCS (anodal tDCS). We also analyzed electroencephalography. Our results indicated that anodal tDCS application enhanced the shot accuracy (p = 0.001). Furthermore, the beta power in the EEG recording was higher in the left DLPFC, left and right parietal cortex (p = 0,001) after applying anodal tDCS, while the low-gamma power was higher in the right DLPFC in sham-tDCS (p = 0.001) and right parietal cortex after anodal-tDCS (p = 0.001). Our findings indicate that anodal tDCS can improve accuracy and shot grouping when applied over the unskilled shooters' right DLPFC. Furthermore, beta and low-gamma bands are influenced by anodal tDCS over the right DLPFC, which may be predictive of skill improvement.

Time estimation exposure modifies cognitive aspects and cortical activity of attention deficit hyperactivity disorder adults.

AIM: This study investigated whether time-estimation task exposure influences the severity of Attention Deficit Hyperactivity Disorder (ADHD), as well as theta band activity in the dorsolateral prefrontal cortex and ventrolateral prefrontal cortex. MATERIAL AND METHODS: Twenty-two patients with ADHD participated in a crossover experiment with a visual time-estimation task under control conditions (without exposure to time estimation tasks) and experimental (thirty days exposure to time-estimation tasks) in association with electroencephalographic analysis of theta band. RESULTS: ADHD patients with thirty days of time-estimation task exposure presented a worse performance of the time-estimation task, as revealed by the measurements of the absolute error and relative error (p ≤ 0.05). However, our findings show the improvement of self-reported symptoms of attention, impulsivity, and emotional control in patients after the time-estimation task exposure (p = 0.0001). Moreover, the theta band oscillations in the right dorsolateral prefrontal cortex and in the ventrolateral prefrontal increased with thirty days of time-estimation task exposure (p ≤ 0.05). CONCLUSION: We propose that the decrease in EEG theta power may indicate an efficient accumulation of temporal pulses, which could be responsible for the improvement in the patient cognitive aspects as demonstrated by the current study. Time-estimation task improves ADHD cognitive symptoms, with a substantial increase in cortical areas activity related to attention and memory, suggesting its use as a tool for cognitive timing function management and non-invasive therapeutic aid in ADHD.

The role of low-frequency rTMS in the superior parietal cortex during time estimation.

The low-frequency repetitive transcranial magnetic stimulation (rTMS) application has been associated with changes in cognitive processes embedded during time perception tasks. Although several studies have investigated the influence of neuromodulation on time perception, the effect of the 1-Hz rTMS application on the superior parietal cortex is not clearly understood. This study analyzes the effect of the low-frequency rTMS on time estimation when applied in the parietal medial longitudinal fissure. For the proposed study, 20 subjects were randomly selected for a crossover study with two conditions (sham and 1 Hz). Our findings reveal that participant underestimate 1-s time interval and overestimate 4-s and 9-s time intervals after 1-Hz rTMS (p ≤ 0.05). We conclude that the 1-Hz rTMS in the parietal medial longitudinal fissure delays short interval and speed up long time intervals. This could be due to the effect of parietal inhibition on the attentional level and working memory functions during time estimation.

Methylphenidate modifies activity in the prefrontal and parietal cortex accelerating the time judgment.

Methylphenidate produces its effects via actions on cortical areas involved with attention and working memory, which have a direct role in time estimation judgment tasks. In particular, the prefrontal and parietal cortex has been the target of several studies to understand the effect of methylphenidate on executive functions and time interval perception. However, it has not yet been studied whether acute administration of methylphenidate influences performance in time estimation task and the changes in alpha band absolute power in the prefrontal and parietal cortex. The current study investigates the influence of the acute use of methylphenidate in both performance and judgment in the time estimation interpretation through the alpha band absolute power activity in the prefrontal and parietal cortex. This is a double-blind, crossover study with a sample of 32 subjects under control (placebo) and experimental (methylphenidate) conditions with absolute alpha band power analysis during a time estimation task. We observed that methylphenidate does not influence task performance (p > 0.05), but it increases the time interval underestimation by over 7 s (p < 0.001) with a concomitant decrease in absolute alpha band power in the ventrolateral prefrontal cortex and dorsolateral prefrontal cortex and parietal cortex (p < 0.001). Acute use of methylphenidate increases the time interval underestimation, consistent with reduced accuracy of the internal clock mechanisms. Furthermore, acute use of methylphenidate influences the absolute alpha band power over the dorsolateral prefrontal cortex, ventrolateral prefrontal cortex, and parietal cortex.

Low-frequency rTMS stimulation over superior parietal cortex medially improves time reproduction and increases the right dorsolateral prefrontal cortex predominance.

AIM OF THE STUDY: Previous studies have shown that several cortical regions are involved in temporal tasks in multiple timescales. However, the hemispheric predominance of the dorsolateral prefrontal cortex (DLPFC) during time reproduction after repetitive low-frequency transcranial magnetic stimulation (rTMS) is relatively unexplored. Here, we study the effects of 1 Hz rTMS and sham stimulation applied medially over the superior parietal cortex (SPC) on the DLPFC alpha and beta band asymmetry and on time reproduction. MATERIALS AND METHODS: For this purpose, we have combined rTMS with electroencephalography in 20 healthy subjects who performed the time reproduction task in two conditions (sham and 1 Hz). RESULTS: The worst performance was observed in sham and 1Hz conditions for longer time intervals (p < .05), with the 1Hz condition subjects sub-reproducing the time interval, closer to the target interval (p < .05). The right DLPFC hemispheric predominance was found in both conditions, but after low-frequency rTMS, the right hemisphere predominance increased in the 1Hz condition (p < .05). CONCLUSIONS: Results of this study suggest that rTMS applied over the SPC influences time interval interpretation and the DLPFC functions. Future studies would explore the effects of the rTMS application to other cortical areas, and study how it influences time interval interpretation.

Increase in Mutual Information During Interaction with the Environment Contributes to Perception.

Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with the physical environment are partly accounted for by a reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level, but belonging to different networks. The increase in mutual information is partly accounted for by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta (Front. Neurosci. 2018). We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs' and neural circuits' connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. The increase in mutual information, given the knowledge about environmental sensory stimuli and the type of motor response produced, is responsible for the coupling between action and perception. In addition, the processing of sensory inputs within neural circuits, with no prior knowledge of the occurrence of a sensory stimulus, increases Shannon information. Consequently, the increase in surprise serves to increase the evidence of the sensory model of physical surroundings.