稳态视觉诱发电位神经网络间的相互作用

稳态视觉诱发电位(steady-state visual evoked potential,SSVEP)不同于瞬态视觉诱发电位,有其独特的产生机理。当用两种不同频率的闪光同时刺激时,每种频率闪光诱发的SSVEP之间是否会相互影响?它们与对应单一频率闪光刺激时产生的SSVEP的关系怎样?作者用!波段频率8.3Hz与"波段频率20Hz的闪光分别及同时刺激10个被试的双眼,发现在同时刺激时,每种频率闪光的SSVEP比对应单频刺激时的SSVEP略小,但位置分布无明显变化。这说明不同频率SSVEP的产生网络是彼此独立的,在被同时激活时,每个网络产生的信号并不相互影响。     

用稳态视觉诱发电位研究注意的选择机制

众所周知,注意是一种心理活动,是对外界刺激的一种选择,对人的其它认知活动有一定的调节作用。关于注意的选择机制,有两种不同的理论,一种是早期选择机制,另一种是晚期选择机制。稳态视觉诱发电位是视觉通路对外界刺激的一种物理反应,它的产生过程处于认知的早期阶段,如果它能受到注意的调节,这就支持了注意的早期选择机制。在现有的利用闪光稳态诱发电位对注意的研究中,注意的对象是认知任务,而不是闪光。该实验用两种不同频率的闪光分别做诱发源,对在注意与不注意闪光两种情况下(都没有认知任务)的稳态视觉诱发电位进行研究,发现其明显地受注意调节,而且对不同频率光刺激的调节大小不一样。因此,该实验结果支持了注意的早期选择机制。     

Amplitude modulation of steady-state visual evoked potentials by event-related potentials in a working memory task

Previous studies have shown that the amplitude and phase of the steady-state visual-evoked potential (SSVEP) can be influenced by a cognitive task, yet the mechanism of this influence has not been understood. As the event-related potential (ERP) is the direct neural electric response to a cognitive task, studying the relationship between the SSVEP and ERP would be meaningful in understanding this underlying mechanism. In this work, the traditional average method was applied to extract the ERP directly, following the stimulus of a working memory task, while a technique named steady-state probe topography was utilized to estimate the SSVEP under the simultaneous stimulus of an 8.3-Hz flicker and a working memory task; a comparison between the ERP and SSVEP was completed. The results show that the ERP can modulate the SSVEP amplitude, and for regions where both SSVEP and ERP are strong, the modulation depth is large.     

The graph theoretical analysis of the SSVEP harmonic response networks

Steady-state visually evoked potentials (SSVEP) have been widely used in the neural engineering and cognitive neuroscience researches. Previous studies have indicated that the SSVEP fundamental frequency responses are correlated with the topological properties of the functional networks entrained by the periodic stimuli. Given the different spatial and functional roles of the fundamental frequency and harmonic responses, in this study we further investigated the relation between the harmonic responses and the corresponding functional networks, using the graph theoretical analysis. We found that the second harmonic responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while negatively correlated with the characteristic path lengths of the corresponding networks. In addition, similar pattern occurred with the lowest stimulus frequency (6.25 Hz) at the third harmonic responses. These findings demonstrate that more efficient brain networks are related to larger SSVEP responses. Furthermore, we showed that the main connection pattern of the SSVEP harmonic response networks originates from the interactions between the frontal and parietal–occipital regions. Overall, this study may bring new insights into the understanding of the brain mechanisms underlying SSVEP.     

共情脑机制的研究现状与展望

作为社会交往中的重要因素,共情是指理解并体验他人的情感和知觉感受的能力。目前的研究认为共情依赖于直接的投射机制而非逻辑推理。即观察到他人的情绪状态会涉及一部分处理自我情感的大脑结构的激活,该过程同时还会受到社会认知因素的调节。由于理解和间接体验他人痛觉的能力是维系社会纽带必不可少的,目前研究者越来越多地通过对痛觉共情的研究来揭示关于共情的普遍的神经机制。此外共情的动物模型、镜像神经元系统与共情的产生以及共情的调节等方向也将是研究的重点。     

Investigating the Effect of Flickering Frequency Pair and Mother Wavelet Selection in Steady-State Visually-Evoked Potentials on Two-Command Brain-Computer Interfaces

IntroductionSteady-state visually evoked potentials (SSVEPs) have become popular in brain-computer interface (BCI) applications in addition to many other applications on clinical neuroscience (neurodegenerative disorders, schizophrenia, epilepsy, etc.), cognitive (visual attention, working memory, brain rhythms, etc.), and use of engineering researches. Among available methods to measure brain activities, SSVEPs have advantages like higher information transfer rate, simplicity in structure, and short training time. SSVEP-based BCIs use flickering stimuli at different frequencies to discriminate distinct commands in real life. Some features are extracted from the SSVEP signals before these commands are classified. The wavelet transform (WT) has attracted researchers among feature extraction methods since it utilizes the non-stationary signals well. In the WT, a sample function (named mother wavelet) represents the SSVEP signal in both time and frequency domains. Unfortunately, there is no universal mother wavelet function that fits all the signals. Therefore, choosing an appropriate mother wavelet function may be a challenge in WT-related studies. Although there are such studies in three- and seven-command SSVEP-based studies, there is no study for two-command systems in our knowledge.Materials and MethodsIn this study, two user commands flickered at the combinations of seven different frequencies were tested to determine which frequency pairs give the highest performance. For this purpose, three well-known wavelet features (energy, entropy, and variance) were calculated for each of derived EEG frequency bands from the discrete WT coefficients of SSVEP signals. The WT was repeated for six different mother wavelet functions (Haar, Db4, Sym4, Coif1, Bior3.5, and Rbior2.8). Then, four feature sets (every three features, and all together) were applied to seven commonly-used machine learning algorithms (Decision Tree, Discriminant Analysis, Logistic Regression, Naive Bayes, Support Vector Machines, Nearest Neighbors, and Ensemble Classifiers).Results and DiscussionWe achieved 100% accuracies among these 3,528 runs (7 classifiers x 4 feature sets x 6 mother wavelets x 21 flickering frequency pairs) using the mother wavelet function of Haar and the Ensemble Learner classifier. The highest classifier performances are 100% when two commands have the flickering frequency pairs of (6.0 and 10 Hz), (6.5 and 8.2 Hz), or (6.5 and 10.0 Hz).ConclusionWe obtained three main outcomes from this study. First, the most representative mother wavelet function was Haar, while the worst one was Symlet 4. Second, the Ensemble Learner classifier gave the maximum classifier performance in a two-command SSVEP-based BCI system. Besides, two user commands from SSVEP should be one of the frequency pairs of (6.0 and 10.0 Hz), (6.5 and 8.2 Hz), and (6.5 and 10.0 Hz) to achieve the maximum accuracy.     

Temporal Dynamics of Visual Attention Measured with Event-Related Potentials

How attentional modulation on brain activities determines behavioral performance has been one of the most important issues in cognitive neuroscience. This issue has been addressed by comparing the temporal relationship between attentional modulations on neural activities and behavior. Our previous study measured the time course of attention with amplitude and phase coherence of steady-state visual evoked potential (SSVEP) and found that the modulation latency of phase coherence rather than that of amplitude was consistent with the latency of behavioral performance. In this study, as a complementary report, we compared the time course of visual attention shift measured by event-related potentials (ERPs) with that by target detection task. We developed a novel technique to compare ERPs with behavioral results and analyzed the EEG data in our previous study. Two sets of flickering stimulus at different frequencies were presented in the left and right visual hemifields, and a target or distracter pattern was presented randomly at various moments after an attention-cue presentation. The observers were asked to detect targets on the attended stimulus after the cue. We found that two ERP components, P300 and N2pc, were elicited by the target presented at the attended location. Time-course analyses revealed that attentional modulation of the P300 and N2pc amplitudes increased gradually until reaching a maximum and lasted at least 1.5 s after the cue onset, which is similar to the temporal dynamics of behavioral performance. However, attentional modulation of these ERP components started later than that of behavioral performance. Rather, the time course of attentional modulation of behavioral performance was more closely associated with that of the concurrently recorded SSVEPs analyzed. These results suggest that neural activities reflected not by either the P300 or N2pc, but by the SSVEPs, are the source of attentional modulation of behavioral performance.     

On the synchrony of steady state visual evoked potentials and oscillatory burst events

In this paper, we investigate the large-scale synchrony of EEG oscillatory bursts, during stimulation by a flickering square of light. Whereas most studies focus on averaged raw EEG responses, this study considers oscillatory events within EEG of single trials, which leads to various new insights. We recorded EEG signals before, during and after stimulation by a flickering square of light in medium (16 Hz) and high frequency (32 Hz) ranges. Similar oscillatory bursts, to those observed in spontaneous EEG, can be found in single-trial synchrony of steady state visual evoked potentials (SSVEP). These bursts are extracted from the EEG of single trials using bump modeling. Stochastic event synchrony method is applied to those events, which quantifies synchronies of oscillatory bursts on a large-scale basis. Those oscillatory patterns have a significantly higher degree of co-occurrence during SSVEP, uncorrelated with ongoing signal synchrony. It means that EEG oscillatory patterns are presumably an outcome of brain activity, rather than a mere side effect of ongoing EEG. They undergo a consistent reorganization during visual stimulation, preferentially along the visual pathway, depending on magno or parvo stimulations. Flickering stimuli may induce some cognitive side-effects depending on the stimulation frequency.

The influence of social affiliation on individual vocal signatures of northern resident killer whales (Orcinus orca)

Northern resident killer whales (Orcinus orca) live in highly stable groups and use group-specific vocal signals, but individual variation in calls has not been described previously. A towed beam-forming array was used to ascribe stereotyped pulsed calls with two independently modulated frequency contours to visually identified individual killer whales in Johnstone Strait, British Columbia. Overall, call similarity determined using neural networks differed significantly between different affiliation levels for both frequency components of all the call types analysed. This method distinguished calls from individuals within the same matriline better than different calls produced by a single individual and better than by chance. The calls of individuals from different matrilines were more distinctive than those within the same matriline, confirming previous studies based on group recordings. These results show that frequency contours of stereotyped calls differ among the individuals that are constantly associated with each other and use group-specific vocalizations, though across-group differences were substantially more pronounced.     

Influence of Stimuli Spatial Proximity on a SSVEP-Based BCI Performance

Objective: Steady-State Visual Evoked Potentials based Brain-Computer Interfaces (SSVEP-based BCIs) systems have been shown as promising technology due to their short response time and ease of use. SSVEP-based BCIs use brain responses to a flickering visual stimulus as an input command to an external application or device, and it can be influenced by stimulus properties, signal recording, and signal processing. We aim to investigate the system performance varying the stimuli spatial proximity (a stimulus property).Material and methods: We performed a comparative analysis of two visual interface designs (named cross and square) for an SSVEP-based BCI. The power spectrum density (PSD) was used as feature extraction and the Support Machine Vector (SVM) as classification method. We also analyzed the effects of five flickering frequencies (6.67, 8.57, 10, 12 e 15 Hz) between and within interfaces.Results: We found higher accuracy rates for the flickering frequencies of 10, 12, and 15 Hz. The stimulus of 10 Hz presented the highest SSVEP amplitude response for both interfaces. The system presented the best performance (highest classification accuracy and information transfer rate) using the cross interface (lower visual angle).Conclusion: Our findings suggest that the system has the highest performance in the spatial proximity range from 4° to 13° (visual angle). In addition, we conclude that as the stimulus spatial proximity increases, the interference from other stimuli reduces, and the SSVEP amplitude response decreases, which reduces system accuracy. The inter-stimulus distance is a visual interface parameter that must be chosen carefully to increase the efficiency of an SSVEP-based BCI.     

Single neurons in posterior parietal cortex of monkeys encode cognitive set

The primate posterior parietal cortex (PPC), part of the dorsal visual pathway, is best known for its role in encoding salient spatial information. Yet there are indications that neural activity in the PPC can also be modulated by nonspatial task-related information. In this study, we tested whether neurons in the PPC encode signals related to cognitive set, that is, the preparation to perform a particular task. Cognitive set has previously been associated with the frontal cortex but not the PPC. In this study, monkeys performed a cognitive set shifting paradigm in which they were cued in advance to apply one of two different task rules to the subsequent stimulus on every trial. Here we show that a subset of neurons in the PPC, concentrated in the lateral bank of the intraparietal sulcus and on the angular gyrus, responds selectively to cues for different task rules.     

Neural hierarchical models of ecological populations

Neural networks are increasingly being used in science to infer hidden dynamics of natural systems from noisy observations, a task typically handled by hierarchical models in ecology. This article describes a class of hierarchical models parameterised by neural networks – neural hierarchical models. The derivation of such models analogises the relationship between regression and neural networks. A case study is developed for a neural dynamic occupancy model of North American bird populations, trained on millions of detection/non‐detection time series for hundreds of species, providing insights into colonisation and extinction at a continental scale. Flexible models are increasingly needed that scale to large data and represent ecological processes. Neural hierarchical models satisfy this need, providing a bridge between deep learning and ecological modelling that combines the function representation power of neural networks with the inferential capacity of hierarchical models.     

Effect of steady-state response versus excitatory/inhibitory balance on spiking synchronization in neural networks with log-normal synaptic weight distribution

Synchronization of neural activity, especially at the gamma band, contributes to perceptual functions. In several psychiatric disorders, deficits of perceptual functions are reflected in synchronization abnormalities. Plausible cause of this impairment is an alteration in the balance between excitation and inhibition (E/I balance); a disruption in the E/I balance leads to abnormal neural interactions reminiscent of pathological states. Moreover, the local lateral excitatory-excitatory synaptic connections in the cortex exhibit excitatory postsynaptic potentials (EPSPs) that follow a log-normal amplitude distribution. This long-tailed distribution is considered an important factor for the emergence of spatiotemporal neural activity. In this context, we hypothesized that manipulating the EPSP distribution under abnormal E/I balance conditions would provide insights into psychiatric disorders characterized by deficits in perceptual functions, potentially revealing the mechanisms underlying pathological neural behaviors. In this study, we evaluated the synchronization of neural activity with external periodic stimuli in spiking neural networks in cases of both E/I balance and imbalance with or without a long-tailed EPSP amplitude distribution. The results showed that external stimuli of a high frequency lead to a decrease in the degree of synchronization with an increasing ratio of excitatory to inhibitory neurons in the presence, but not in the absence, of high-amplitude EPSPs. This monotonic reduction can be interpreted as an autonomous, strong-EPSP-dependent spiking activity selectively interfering with the responses to external stimuli. This observation is consistent with pathological findings. Thus, our modeling approach has potential to improve the understanding of the steady-state response in both healthy and pathological states.     

Evaluation of cognitive performance in the heat by functional brain imaging and psychometric testing

Military operations in tropical environments have imposed a significant challenge to the Australian Defence Forces (ADF). The hot and humid conditions are known to cause debilitating effects on soldiers deployed to northern regions of Australia, with the consequence that the effectiveness and efficiency of operations are severely compromised. While the adverse effects of thermal stress on soldiers' physiological capability are well established, this has not been confirmed for cognitive performance. A select range of psychometric tests were administered and functional brain electrical activity imaging was performed to investigate the impact of thermal stress on cognitive performance. The brain electrical activity of subjects was measured while undertaking a range of cognitive tasks. Steady State Probe Topography (SSPT), a novel brain imaging technology, was employed to monitor the changes in regional brain activity and neural processing speed of subjects under thermal stress. The psychometric test batteries included the following tasks; Rey Auditory Verbal Learning Test; Inspection Time; Digit Span test; a spatial working memory task; and the AX-continuous performance task. These tasks measure a range of cognitive processes including attention, memory, verbal learning, information processing and concentration. The functional brain imaging provided topographical information, which showed changes in electrical activity in response to thermal stress during cognitive performance. These changes in brain electrical activity and neural speed induced by thermal stress may help to identify the type of cognitive functions that are likely to be impaired under operational conditions. Results indicated that subjects experienced increasing cardiovascular strain through thermally neutral to thermally straining conditions. The results from the psychometric test battery showed some promising effects given the small sample size including deficits in working memory, in information retention and in information processing. There was also marked differences in the electrical responses of the brain when subjects were thermally strained. The Steady-State Visual Evoked Potential recordings showed an increase in amplitude and a decrease in latency, suggesting an increase in the utilisation of neural resources or effort by subjects to maintain the same level of performance as under thermally neutral conditions. The data are suggestive of the high sensitivity of brain imaging techniques with high temporal resolution to identify important decrements in cognitive performance in hostile environments.     

Electroencephalography as implicit communication channel for proximal interaction between humans and robot swarms

Search and rescue, autonomous construction, and many other semi-autonomous multirobot applications can benefit from proximal interactions between an operator and a swarm of robots. Most research on proximal interaction is based on explicit communication techniques such as gesture and speech. This study proposes a new implicit proximal communication technique to approach the problem of robot selection. We use electroencephalography (EEG) signals to select the robot at which the operator is looking. This is achieved using steady-state visually evoked potential (SSVEP), a repeatable neural response to a regularly blinking visual stimulus that varies predictively based on the blinking frequency. In our experiments, each robot was equipped with LEDs blinking at a different frequency, and the operator’s SSVEP neural response was extracted from the EEG signal to detect and select the robot without requiring any conscious action by the user. This study systematically investigates several parameters affecting the SSVEP neural response: blinking frequency of the LED, distance between the robot and the operator, and color of the LED. Based on these parameters, we study two signal processing approaches and critically analyze their performance on 10 subjects controlling a set of physical robots. Our results show that despite numerous artifacts, it is possible to achieve a recognition rate higher than 85 % on some subjects, while the average over the ten subjects was 75 %.     

Odor Valence Linearly Modulates Attractiveness,but Not Age Assessment,of Invariant Facial Features in a Memory-Based Rating Task

Scented cosmetic products are used across cultures as a way to favorably influence one''s appearance. While crossmodal effects of odor valence on perceived attractiveness of facial features have been demonstrated experimentally, it is unknown whether they represent a phenomenon specific to affective processing. In this experiment, we presented odors in the context of a face battery with systematic feature manipulations during a speeded response task. Modulatory effects of linear increases of odor valence were investigated by juxtaposing subsequent memory-based ratings tasks – one predominantly affective (attractiveness) and a second, cognitive (age). The linear modulation pattern observed for attractiveness was consistent with additive effects of face and odor appraisal. Effects of odor valence on age perception were not linearly modulated and may be the result of cognitive interference. Affective and cognitive processing of faces thus appear to differ in their susceptibility to modulation by odors, likely as a result of privileged access of olfactory stimuli to affective brain networks. These results are critically discussed with respect to potential biases introduced by the preceding speeded response task.     

Adaptation supports short-term memory in a visual change detection task

The maintenance of short-term memories is critical for survival in a dynamically changing world. Previous studies suggest that this memory can be stored in the form of persistent neural activity or using a synaptic mechanism, such as with short-term plasticity. Here, we compare the predictions of these two mechanisms to neural and behavioral measurements in a visual change detection task. Mice were trained to respond to changes in a repeated sequence of natural images while neural activity was recorded using two-photon calcium imaging. We also trained two types of artificial neural networks on the same change detection task as the mice. Following fixed pre-processing using a pretrained convolutional neural network, either a recurrent neural network (RNN) or a feedforward neural network with short-term synaptic depression (STPNet) was trained to the same level of performance as the mice. While both networks are able to learn the task, the STPNet model contains units whose activity are more similar to the in vivo data and produces errors which are more similar to the mice. When images are omitted, an unexpected perturbation which was absent during training, mice often do not respond to the omission but are more likely to respond to the subsequent image. Unlike the RNN model, STPNet produces a similar pattern of behavior. These results suggest that simple neural adaptation mechanisms may serve as an important bottom-up memory signal in this task, which can be used by downstream areas in the decision-making process.     

Social experience organizes parallel networks in sensory and limbic forebrain

Successful social behavior can directly influence an individual's reproductive success. Therefore, many organisms readily modify social behavior based on past experience. The neural changes induced by social experience, however, remain to be fully elucidated. We hypothesize that social modulation of neural systems not only occurs at the level of individual nuclei, but also of functional networks, and their relationships with behavior. We used the green anole lizard (Anolis carolinensis), which displays stereotyped, visually triggered social behaviors particularly suitable for comparisons of multiple functional networks in a social context, to test whether repeated aggressive interactions modify behavior and metabolic activity in limbic-hypothalamic and sensory forebrain regions, assessed by quantitative cytochrome oxidase (a slowly accumulating endogenous metabolic marker) histochemistry. We found that aggressive interactions potentiate aggressive behavior, induce changes in activities of individual nuclei, and organize context-specific functional neural networks. Surprisingly, this experiential effect is not only present in a limbic-hypothalamic network, but also extends to a sensory forebrain network directly relevant to the behavioral expression. Our results suggest that social experience modulates organisms' social behavior via modifying sensory and limbic neural systems in parallel both at the levels of individual regions and networks, potentially biasing perceptual as well as limbic processing.     

Neural regulation of bone remodeling: Identifying novel neural molecules and pathways between brain and bone

The metabolism and homeostasis of the skeletal system have historically been considered to be associated with the endocrine system. However, this view has been expanded with the recognition of several neural pathways playing important roles in the regulation of bone metabolism via central relays. In particular, bone metabolism and homeostasis have been reported to be precisely modulated by the central neural signaling. Initiated by the finding of leptin, the axis of neural regulation on bone expands rapidly. The semaphorin–plexin system plays an important role in the cross-talk between osteoclasts and osteoblasts; a complex system has also been identified and includes neuropeptide Y and cannabinoids. These findings facilitate our understanding of the central neuropeptides and neural factors in the modulation of bone metabolism and homeostasis, and these neuronal pathways also represent an area of research scenario that identifies the novel regulation between brain and bone. These regulatory mechanisms correlate with other homeostatic networks and demonstrate a more intricate and synergetic bone biology than previously envisioned. As such, this review summarizes the current knowledge of the neural regulation of bone metabolism and homeostasis, as well as its role in skeletal diseases and discusses the emerging challenges presented in this field.     

Transcranial Electrical Stimulation over Dorsolateral Prefrontal Cortex Modulates Processing of Social Cognitive and Affective Information

Recent neurofunctional studies suggested that lateral prefrontal cortex is a domain-general cognitive control area modulating computation of social information. Neuropsychological evidence reported dissociations between cognitive and affective components of social cognition. Here, we tested whether performance on social cognitive and affective tasks can be modulated by transcranial direct current stimulation (tDCS) over dorsolateral prefrontal cortex (DLPFC). To this aim, we compared the effects of tDCS on explicit recognition of emotional facial expressions (affective task), and on one cognitive task assessing the ability to adopt another person’s visual perspective. In a randomized, cross-over design, male and female healthy participants performed the two experimental tasks after bi-hemispheric tDCS (sham, left anodal/right cathodal, and right anodal/left cathodal) applied over DLPFC. Results showed that only in male participants explicit recognition of fearful facial expressions was significantly faster after anodal right/cathodal left stimulation with respect to anodal left/cathodal right and sham stimulations. In the visual perspective taking task, instead, anodal right/cathodal left stimulation negatively affected both male and female participants’ tendency to adopt another’s point of view. These findings demonstrated that concurrent facilitation of right and inhibition of left lateral prefrontal cortex can speed-up males’ responses to threatening faces whereas it interferes with the ability to adopt another’s viewpoint independently from gender. Thus, stimulation of cognitive control areas can lead to different effects on social cognitive skills depending on the affective vs. cognitive nature of the task, and on the gender-related differences in neural organization of emotion processing.