Alpha-band EEG activity in perceptual learning

Perceptual Expectations Are Reflected by Early Alpha Power Reduction

The predictability of a stimulus can be characterized by its transitional probability. Perceptual expectations derived from the transitional probability of the stimulus were found to modulate the early alpha oscillations in the sensory regions of the brain when neural responses to expected versus unexpected stimuli were compared. The objective of our study was to find out the extent to which this low-frequency oscillation reflects stimulus predictability. We aimed to detect the alpha-power difference with smaller differences in transitional probabilities by comparing expected stimuli with neutral ones. We studied the effect of expectation on perception by applying an unsupervised visual statistical learning paradigm with expected and neutral stimuli embedded in an image sequence while recording EEG. Time-frequency analysis showed that expected stimuli elicit lower alpha power in the window of 8-12 Hz and 0-400 msec after stimulus presentation, appearing in the centroparietal region. Comparing previous findings of expectancy-based alpha-band modulation with our results suggests that early alpha oscillation shows an inverse relationship with stimulus predictability. Although current data are insufficient to determine the origin of the alpha power reduction, this could be a potential sign of expectation suppression in cortical oscillatory activity.

Neural correlates tracking different aspects of the emerging representation of novel visual categories

Current studies investigating electroencephalogram correlates associated with categorization of sensory stimuli (P300 event-related potential, alpha event-related desynchronization, theta event-related synchronization) typically use an oddball paradigm with few, familiar, highly distinct stimuli providing limited insight about the aspects of categorization (e.g. difficulty, membership, uncertainty) that the correlates are linked to. Using a more complex task, we investigated whether such more specific links could be established between correlates and learning and how these links change during the emergence of new categories. In our study, participants learned to categorize novel stimuli varying continuously on multiple integral feature dimensions, while electroencephalogram was recorded from the beginning of the learning process. While there was no significant P300 event-related potential modulation, both alpha event-related desynchronization and theta event-related synchronization followed a characteristic trajectory in proportion with the gradual acquisition of the two categories. Moreover, the two correlates were modulated by different aspects of categorization, alpha event-related desynchronization by the difficulty of the task, whereas the magnitude of theta -related synchronization by the identity and possibly the strength of category membership. Thus, neural signals commonly related to categorization are appropriate for tracking both the dynamic emergence of internal representation of categories, and different meaningful aspects of the categorization process.

Assessing the pattern electroretinogram as a proxy measure for dopamine in the context of iron deficiency

OBJECTIVES

Animal studies have suggested that dietary iron deficiency (ID) negatively affects dopamine (DA) synthesis and re-uptake, which in turn negatively affects memory and cognition. This study was intended to assess whether the pattern electroretinogram (pattern ERG) could be used as an indirect measure of DA in college-age women with and without ID by determining the extent to which features of the ERG were sensitive to iron status and were related to other indirect measures of DA.

METHODS

The pattern ERG was measured in 21 iron deficient non-anemic (IDNA) and 21 iron sufficient (IS) women, who also performed a contrast detection and probabilistic selection task, both with concurrent electroencephalography (EEG). Both spontaneous and task-related blink rates were also measured.

RESULTS

The implicit times of the A- and B-waves were significantly longer for the IDNA than for the IS women. Both the amplitudes and implicit times of the A- and B-waves were significantly correlated with levels of serum ferritin (sFt). Only the amplitude of the A-wave was correlated with spontaneous blink rate. It was possible to accurately identify a woman's iron status solely on the basis of the implicit time of the B-wave. Finally, the implicit times of the ERG features mediated the relationship between iron levels and accuracy in the probabilistic selection task.

CONCLUSIONS

Results suggest the utility of the pattern ERG in testing the hypothesis that iron deficiency affects DA levels in humans and that this may be one of the mechanisms by which iron deficiency negatively affects cognition.

Enhancing visual perceptual learning using transcranial electrical stimulation: Transcranial alternating current stimulation outperforms both transcranial direct current and random noise stimulation

Diverse strategies can be employed to enhance visual skills, including visual perceptual learning (VPL) and transcranial electrical stimulation (tES). Combining VPL and tES is a popular method that holds promise for producing significant improvements in visual acuity within a short time frame. However, there is still a lack of comprehensive evaluation regarding the effects of combining different types of tES and VPL on enhancing visual function, especially with a larger sample size. In the present study, we recruited four groups of subjects (26 subjects each) to learn an orientation discrimination task with five daily training sessions. During training, the occipital region of each subject was stimulated by one type of tES-anodal transcranial direct current stimulation (tDCS), alternating current stimulation (tACS) at 10 Hz, high-frequency random noise stimulation (tRNS), and sham tACS-while the subject performed the training task. We found that, compared with the sham stimulation, both the high-frequency tRNS and the 10-Hz tACS facilitated VPL efficiently in terms of learning rate and performance improvement, but there was little modulatory effect in the anodal tDCS condition. Remarkably, the 10-Hz tACS condition exhibited superior modulatory effects compared with the tRNS condition, demonstrating the strongest modulation among the most commonly used tES types for further enhancing vision when combined with VPL. Our results suggest that alpha oscillations play a vital role in VPL. Our study provides a practical guide for vision rehabilitation.

Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability

Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.

Cortical excitability in human somatosensory and visual cortex: implications for plasticity and learning - a minireview

The balance of excitation and inhibition plays a key role in plasticity and learning. A frequently used, reliable approach to assess intracortical inhibition relies on measuring paired-pulse behavior. Moreover, recent developments of magnetic resonance spectroscopy allows measuring GABA and glutamate concentrations. We give an overview about approaches employed to obtain information about excitatory states in human participants and discuss their putative relation. We summarize paired-pulse techniques and basic findings characterizing paired-pulse suppression in somatosensory (SI) and (VI) visual areas. Paired-pulse suppression describes the effect of paired sensory stimulation at short interstimulus intervals where the cortical response to the second stimulus is significantly suppressed. Simultaneous assessments of paired-pulse suppression in SI and VI indicated that cortical excitability is not a global phenomenon, but instead reflects the properties of local sensory processing. We review studies using non-invasive brain stimulation and perceptual learning experiments that assessed both perceptual changes and accompanying changes of cortical excitability in parallel. Independent of the nature of the excitation/inhibition marker used these data imply a close relationship between altered excitability and altered performance. These results suggest a framework where increased or decreased excitability is linked with improved or impaired perceptual performance. Recent findings have expanded the potential role of cortical excitability by demonstrating that inhibition markers such as GABA concentrations, paired-pulse suppression or alpha power predict to a substantial degree subsequent perceptual learning outcome. This opens the door for a targeted intervention where subsequent plasticity and learning processes are enhanced by altering prior baseline states of excitability.

Using occipital ⍺-bursts to modulate behavior in real-time

Pre-stimulus endogenous neural activity can influence the processing of upcoming sensory input and subsequent behavioral reactions. Despite it is known that spontaneous oscillatory activity mostly appears in stochastic bursts, typical approaches based on trial averaging fail to capture this. We aimed at relating spontaneous oscillatory bursts in the alpha band (8-13 Hz) to visual detection behavior, via an electroencephalography-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time. According to alpha theories, we hypothesized that visual targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts (low alpha activity) should lead to faster responses and higher false alarm rates. Our findings support the role of bursts of alpha oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioral theories.

Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions

Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.

Multi-band oscillations emerge from a simple spiking network

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.

Human visual processing during walking: Dissociable pre- and post-stimulus influences

Walking influences visual processing but the underlying mechanism remains poorly understood. In this study, we investigated the influence of walking on pre-stimulus and stimulus-induced visual neural activity and behavioural performance in a discrimination task while participants were standing or freely walking. The results showed dissociable pre- and post-stimulus influences by the movement state. Walking was associated with a reduced pre-stimulus alpha power, which predicted enhanced N1 and decreased P3 components during walking. This pre-stimulus alpha activity was additionally modulated by time on the task, which was paralleled by a similar behavioural modulation. In contrast, the post-stimulus alpha power was reduced in its modulation due to stimulus onset during walking but showed no evidence of modulation by time on the task. Additionally, stimulus parameters (eccentricity, laterality, distractor presence significantly influenced post-stimulus alpha power, whereas the visually evoked components showed no evidence of such an influence. There was further no evidence of a correlation between pre-stimulus and post stimulus alpha power. We conclude that walking has two dissociable influences on visual processing: while the walking induced reduction in alpha power suggests an attentional state change that relates to visual awareness, the post-stimulus influence on alpha power modulation indicates changed spatial visual processing during walking.

Expectance of low contrast retro-cues does not modulate anticipatory alpha power

It has been proposed that alpha oscillations reflect the endogenous modulation of visual cortex excitability. In particular, alpha power increases during the maintenance period in Working Memory (WM) tasks have been interpreted as a mechanism to avoid potential interference of incoming stimuli. In this study we tested whether alpha power was modulated during the maintenance of WM to enhance the processing of relevant incoming perceptual stimuli. To this aim, we manipulated the contrast of a stimulus presented during the maintenance period of a WM task. The to-be-detected stimulus could indicate which of the encoded representations was going to be probed after the delay (spatial retro-cue) or could signal that all the representations had equal probability to be tested (neutral retro-cue). Time-frequency analysis revealed that alpha power preceding retro-cue presentation was not differently modulated by the two different contrast conditions. This is, participants did not endogenously modulate alpha oscillations upon low perceptual contrast stimuli incoming. These results suggest that alpha delay activity is not a goal directed mechanism to control the inflow of information during WM maintenance. Instead, current data suggest that alpha delayed activity might be an index of increased allocation of attentional resources to the processing of the WM representations.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

Perspective on Vision Science-Informed Interventions for Central Vision Loss

Pathologies affecting central vision, and macular degeneration (MD) in particular, represent a growing health concern worldwide, and the leading cause of blindness in the Western World. To cope with the loss of central vision, MD patients often develop compensatory strategies, such as the adoption of a Preferred Retinal Locus (PRL), which they use as a substitute fovea. However, visual acuity and fixation stability in the visual periphery are poorer, leaving many MD patients struggling with tasks such as reading and recognizing faces. Current non-invasive rehabilitative interventions are usually of two types: oculomotor, aiming at training eye movements or teaching patients to use or develop a PRL, or perceptual, with the goal of improving visual abilities in the PRL. These training protocols are usually tested over a series of outcome assessments mainly measuring low-level visual abilities (visual acuity, contrast sensitivity) and reading. However, extant approaches lead to mixed success, and in general have exhibited large individual differences. Recent breakthroughs in vision science have shown that loss of central vision affects not only low-level visual abilities and oculomotor mechanisms, but also higher-level attentional and cognitive processes. We suggest that effective interventions for rehabilitation after central vision loss should then not only integrate low-level vision and oculomotor training, but also take into account higher level attentional and cognitive mechanisms.

The effects of virtual reality training on clinical indices and brain mapping of women with patellofemoral pain: a randomized clinical trial

Background

Virtual reality training (VRT) is a new method for the rehabilitation of musculoskeletal impairments. However, the clinical and central effects of VRT have not been investigated in patients with patellofemoral pain (PFP). To comprehensively assess the effects of VRT on clinical indices and brain function, we used a randomized clinical trial based on clinical and brain mapping assessment.

Methods

Twenty-six women with PFP for more than 6 months were randomly allocated to 2 groups: intervention and control. The intervention consisted of lifestyle education + 8 weeks VRT, in 24 sessions each lasting 40 min of training, whereas the control group just received lifestyle education. The balance was the primary outcome and was measured by the modified star excursion balance test. Secondary outcomes included pain, function, quality of life, and brain function which were assessed by visual analogue scale, step down test and Kujala questionnaire, SF-36, and EEG, respectively. Pre-intervention, post-intervention and follow-up (1 month after the end of the intervention) measurements were taken for all outcome measures except EEG, which was evaluated only at pre-intervention and post-intervention). Analyses of variance was used to compare the clinical outcomes between the two groups. The independent t-test also was used for between group EEG analyses.

Results

Balance score (P < 0.001), function (P < 0.001), and quality of life (P = 0.001) improved significantly at post-intervention and 1 month follow-up in the VRT group compared with the control group. VRT group showed a significantly decreased pain score (P = 0.004). Alpha (P < 0.05) and theta (P = 0.01) power activity also increased in the brain of the VRT group.

Conclusion

This study demonstrated that long term VRT was capable of improving both clinical impairments and brain function in patients with PFP. Therefore, therapists and clinicians can use this method as a more holistic approach in the rehabilitation of PFP.

Trial registration

IRCT, IRCT20090831002391N40. Registered 23 / 10 / 2019.

Performance prediction in a visuo-motor task: the contribution of EEG analysis

Brain state in the time preceding the task affects motor performance at single trial level. Aim of the study was to investigate, through a single trial analysis of the Power Spectral Density (PSD) of the cortical sources of EEG rhythms, whether there are EEG markers, which can predict trial-by-trial the subject's performance as measured by the reaction time (RT). 20 healthy adult volunteers performed a specific visuomotor task while continuously recorded with a 64 electrodes EEG. For each single trial, the PSD of the cortical sources of EEG rhythms was obtained from EEG data to cortical current density time series in 12 regions of interest at Brodmann areas level. Results showed a statistically significant increase of posterior and limbic alpha 1 and of frontal beta 2 power, and a reduction of frontal and limbic delta and of temporal alpha 1 power, during triggering stimulus presentation for better performance, namely faster responses. At single trial level, correlation analyses between RTs and significant PSD, revealed positive correlations in frontal delta, temporal alpha 1, and limbic delta bands, and negative ones in frontal beta 2, parietal alpha 1, and occipital alpha 1 bands. Furthermore, the subject's faster responses have been found as correlated with the similarity between the PSD values in parietal and occipital alpha 1. Predicting individual's performance at single trial level, might be extremely useful in the clinical context, since it could allow to launch rehabilitative therapies in the most efficient brain state, avoiding useless interventions.

The Effects of Useful Field of View Training on Brain Activity and Connectivity

OBJECTIVES

Useful Field of View training (UFOVt) is an adaptive computerized cognitive intervention that improves visual attention and transfers to maintained health and everyday functioning in older adults. Although its efficacy is well established, the neural mechanisms underlying this intervention are unknown. This pilot study used functional MRI (fMRI) to explore neural changes following UFOVt.

METHOD

Task-driven and resting-state fMRI were used to examine changes in brain activity and connectivity in healthy older adults randomized to 10 hr of UFOVt (n = 13), 10 hr of cognitively stimulating activities (CSA; n = 11), or a no-contact control (NC; n = 10).

RESULTS

UFOVt resulted in reduced task-driven activity in the majority of regions of interest (ROIs) associated with task performance, CSA resulted in reduced activity in one ROI, and there were no changes within the NC group. Relative to NC, UFOVt reduced activity in ROIs involved in effortful information processing. There were no other significant between-group task-based differences. Resting-state functional connectivity between ROIs involved in executive function and visual attention was strengthened following UFOVt compared with CSA and NC.

DISCUSSION

UFOVt enhances connections needed for visual attention. Together with prior work, this study provides evidence that improvement of the brain's visual attention efficiency is one mechanism underlying UFOVt.

Spontaneous Brain Oscillations and Perceptual Decision-Making

Making rapid decisions on the basis of sensory information is essential to everyday behaviors. Why, then, are perceptual decisions so variable despite unchanging inputs? Spontaneous neural oscillations have emerged as a key predictor of trial-to-trial perceptual variability. New work casting these effects in the framework of models of perceptual decision-making has driven novel insight into how the amplitude of spontaneous oscillations impact decision-making. This synthesis reveals that the amplitude of ongoing low-frequency oscillations (<30 Hz), particularly in the alpha-band (8-13 Hz), bias sensory responses and change conscious perception but not, surprisingly, the underlying sensitivity of perception. A key model-based insight is that various decision thresholds do not adapt to alpha-related changes in sensory activity, demonstrating a seeming suboptimality of decision mechanisms in tracking endogenous changes in sensory responses.

Moderating effects of visual attention and action video game play on perceptual learning with the texture discrimination task

There is currently substantial controversy regarding the reliability of observed patterns of perceptual learning. Contributing to this controversy are a lack of accounting for individual differences and how variations in training can give rise to different patterns of learning. Here we sought to investigate the impact of individual differences in attention, as measured with the Useful Field of View (UFOV) task, and action video game use on perceptual learning in a large sample of subjects trained on a Texture Discrimination Task (TDT). We examined baseline performance on the TDT, learning on the initially trained TDT stimuli and transfer to a subsequently trained background orientation. We find that participants showing better performance on the UFOV task performed better on the TDT, and also showed greater learning and transfer to an untrained background orientation. On the other hand, self-report of action video game play only inconsistently related performance, learning or transfer on the TDT. Further, we failed to replicate previous findings that training with different backgrounds gives rise to interference on the TDT. Together these results suggest that, while differences between individuals and differences in task structure play a role in perceptual learning, previous findings on the impact of action video game use and interference between training stimuli in perceptual learning may be idiosyncratic.

Beauty in mind: Aesthetic appreciation correlates with perceptual facilitation and attentional amplification

Neuroaesthetic research suggests that aesthetic appreciation results from the interaction between the object perceptual features and the perceiver's sensory processing dynamics. In the present study, we investigated the relationship between aesthetic appreciation and attentional modulation at a behavioural and psychophysiological level. In a first experiment, fifty-eight healthy participants performed a visual search task with abstract stimuli containing more or less natural spatial frequencies and subsequently were asked to give an aesthetic evaluation of the images. The results evidenced that response times were faster for more appreciated stimuli. In a second experiment, we recorded visual evoked potentials (VEPs) during exposure to the same stimuli. The results showed, only for more appreciated images, an enhancement in C1 and N1, P3 and N4 VEP components. Moreover, we found increased attention-related occipital alpha desynchronization for more appreciated images. We interpret these data as indicative of the existence of a correlation between aesthetic appreciation and perceptual processing enhancement, both at a behavioural and at a neurophysiological level.

Visual perceptual learning modulates decision network in the human brain: The evidence from psychophysics, modeling, and functional magnetic resonance imaging

Perceptual learning refers to improved perceptual performance after intensive training and was initially suggested to reflect long-term plasticity in early visual cortex. Recent behavioral and neurophysiological evidence further suggested that the plasticity in brain regions related to decision making could also contribute to the observed training effects. However, how perceptual learning modulates the responses of decision-related regions in the human brain remains largely unknown. In the present study, we combined psychophysics and functional magnetic resonance imaging (fMRI), and adopted a model-based approach to investigate this issue. We trained participants on a motion direction discrimination task and fitted their behavioral data using the linear ballistic accumulator model. The results from model fitting showed that behavioral improvement could be well explained by a specific improvement in sensory information accumulation. A critical model parameter, the drift rate of the information accumulation, was correlated with the fMRI responses derived from three spatial independent components: ventral premotor cortex (PMv), supplementary eye field (SEF), and the fronto-parietal network, including intraparietal sulcus (IPS) and frontal eye field (FEF). In this decision network, we found that the behavioral training effects were accompanied by signal enhancement specific to trained direction in PMv and FEF. Further, we also found direction-specific signal reduction in sensory areas (V3A and MT+), as well as the strengthened effective connectivity from V3A to PMv and from IPS to FEF. These findings provide evidence for the learning-induced decision refinement after perceptual learning and the brain regions that are involved in this process.

Somatosensory alpha oscillations gate perceptual learning efficiency

Cognition and perception are closely coupled to alpha power, but whether there is a link between alpha power and perceptual learning efficacy is unknown. Here we show that somatosensory alpha power can be successfully up- and down-regulated with short-term neurofeedback training, which in turn controls subsequent tactile perceptual learning. We find that neurofeedback-induced increases in alpha power lead to enhanced learning, whereas reductions in alpha power impede learning. As a consequence, interindividual learning variability is substantially reduced. No comparable impact is observed for oscillatory power in theta, beta, and lower gamma frequency bands. Our results demonstrate that high pre-learning alpha levels are a requirement for reaching high learning efficiency. These data provide further evidence that alpha oscillations shape the functional architecture of the brain network by gating neural resources and thereby modulating levels of preparedness for upcoming processing.

Moment-to-Moment Fluctuations in Neuronal Excitability Bias Subjective Perception Rather than Strategic Decision-Making

Perceiving an external stimulus depends not only on the physical features of the stimulus, but also fundamentally on the current state of neuronal excitability, indexed by the power of ongoing alpha-band and beta-band oscillations (8-30 Hz). Recent studies suggest that heightened excitability does not improve perceptual precision, but biases observers to report the presence of a stimulus regardless of its physical presence. It is unknown whether this bias is due to changes in observers' subjective perceptual experience (perceptual bias) or their perception-independent decision-making strategy (decision bias). We tested these alternative interpretations in an EEG experiment in which male and female human participants performed two-interval forced choice (2IFC) detection and discrimination. According to signal detection theory, perceptual bias only affects 2IFC detection, but not discrimination, while interval decision bias should be task independent. We found that correct detection was more likely when excitability before the stimulus-present interval exceeded that before the stimulus-absent interval (i.e., 8-17 Hz power was weaker before the stimulus-present interval), consistent with an effect of excitability on perceptual bias. By contrast, discrimination accuracy was unaffected by excitability fluctuations between intervals, ruling out an effect on interval decision bias. We conclude that the current state of neuronal excitability biases the perceptual experience itself, rather than the decision process.

Deep Neural Networks for Modeling Visual Perceptual Learning

Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. Although existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings. Here, we show that a well -known instance of deep neural network (DNN), whereas not designed specifically for VPL, provides a computational model of VPL with enough complexity to be studied at many levels of analyses. After learning a Gabor orientation discrimination task, the DNN model reproduced key behavioral results, including increasing specificity with higher task precision, and also suggested that learning precise discriminations could transfer asymmetrically to coarse discriminations when the stimulus conditions varied. Consistent with the behavioral findings, the distribution of plasticity moved toward lower layers when task precision increased and this distribution was also modulated by tasks with different stimulus types. Furthermore, learning in the network units demonstrated close resemblance to extant electrophysiological recordings in monkey visual areas. Altogether, the DNN fulfilled predictions of existing theories regarding specificity and plasticity and reproduced findings of tuning changes in neurons of the primate visual areas. Although the comparisons were mostly qualitative, the DNN provides a new method of studying VPL, can serve as a test bed for theories, and assists in generating predictions for physiological investigations.SIGNIFICANCE STATEMENT Visual perceptual learning (VPL) has been found to cause changes at multiple stages of the visual hierarchy. We found that training a deep neural network (DNN) on an orientation discrimination task produced behavioral and physiological patterns similar to those found in human and monkey experiments. Unlike existing VPL models, the DNN was pre-trained on natural images to reach high performance in object recognition, but was not designed specifically for VPL; however, it fulfilled predictions of existing theories regarding specificity and plasticity and reproduced findings of tuning changes in neurons of the primate visual areas. When used with care, this unbiased and deep-hierarchical model can provide new ways of studying VPL from behavior to physiology.

Towards a whole brain model of Perceptual Learning

A hallmark of modern Perceptual Learning (PL) is the extent to which learning is specific to the trained stimuli. Such specificity to orientation, spatial location and even eye of training has been used as psychophysical evidence of the neural basis of learning. This argument that specificity of PL implies regionalization of brain plasticity implicitly assumes that examination of a singular locus of PL is an appropriate approach to understand learning. However, recent research shows that learning effects once thought to be specific depend on subtleties of the training paradigm and that within even a simple training procedure there are multiple aspects of the task and stimuli that are learned simultaneously. Here, we suggest that learning on any task involves a broad network of brain regions undergoing changes in representations, read-out weights, decision rules, attention and feedback processes as well as oculomotor changes. However, importantly, the distribution of learning across the neural system depends upon the details of the training procedure and the characterstics of the individual being trained. We propose that to advance our understanding of PL, the field must move towards understanding how distributed brain processes jointly contribute to behavioral learning effects.

Proprioceptive neuromuscular facilitation increases alpha absolute power in the dorsolateral prefrontal cortex and superior parietal cortex

The physiotherapist's clinical practice includes proprioceptive neuromuscular facilitation (PNF), which is a treatment concept that accelerates the response of neuromuscular mechanisms through spiral and diagonal movements. The adaptations that occur in the nervous system following PNF are still poorly described in the literature. Thus, this study had a goal to investigate the electrophysiological changes in the fronto-parietal circuit during PNF and movement in sagittal and diagonal patterns. This study included 30 female participants, who were divided into three groups (control, PNF, and flexion groups). Electroencephalogram measurements were determined before and after tasks were performed by each group. For the statistical analysis, a two-way ANOVA was performed for the factors group and time. Interactions between the two factors were investigated using a one-way ANOVA. A value of p < 0.004 was considered significant. The results showed an increase in alpha absolute power in the left dorsolateral prefrontal cortex and upper left parietal cortex of the PNF group, suggesting these areas work together to execute a motor action. The PNF group showed a greater alpha absolute power compared with the other groups, indicating a specific cortical demand for planning and attention, reinforcing its use for the rehabilitation of individuals.

Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance

Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations.NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of events.

Spontaneous Neural Oscillations Bias Perception by Modulating Baseline Excitability

The brain exhibits organized fluctuations of neural activity, even in the absence of tasks or sensory input. A prominent type of such spontaneous activity is the alpha rhythm, which influences perception and interacts with other ongoing neural activity. It is currently hypothesized that states of decreased prestimulus α oscillations indicate enhanced neural excitability, resulting in improved perceptual acuity. Nevertheless, it remains debated how changes in excitability manifest at the behavioral level in perceptual tasks. We addressed this issue by comparing two alternative models describing the effect of spontaneous α power on signal detection. The first model assumes that decreased α power increases baseline excitability, amplifying the response to both signal and noise, predicting a liberal detection criterion with no effect on sensitivity. The second model predicts that decreased α power increases the trial-by-trial precision of the sensory response, resulting in improved sensitivity. We tested these models in two EEG experiments in humans where we analyzed the effects of prestimulus α power on visual detection and discrimination using a signal detection framework. Both experiments provide strong evidence that decreased α power reflects a more liberal detection criterion, rather than improved sensitivity, consistent with the baseline model. In other words, when the task requires detecting stimulus presence versus absence, reduced α oscillations make observers more likely to report the stimulus regardless of actual stimulus presence. Contrary to previous interpretations, these results suggest that states of decreased α oscillations increase the global baseline excitability of sensory systems without affecting perceptual acuity.

SIGNIFICANCE STATEMENT

Spontaneous fluctuations of brain activity explain why a faint sensory stimulus is sometimes perceived and sometimes not. The prevailing view is that heightened neural excitability, indexed by decreased α oscillations, promotes better perceptual performance. Here, we provide evidence that heightened neural excitability instead reflects a state of biased perception, during which a person is more likely to see a stimulus, whether or not it is actually present. Therefore, we propose that changes in neural excitability leave the precision of sensory processing unaffected. These results establish the link between spontaneous brain activity and the variability in human perception.

Exploring the unknown: electrophysiological and behavioural measures of visuospatial learning

Visuospatial memory describes our ability to temporarily store and manipulate visual and spatial information and is employed for a wide variety of complex cognitive tasks. Here, a visuospatial learning task requiring fine motor control is employed to investigate visuospatial learning in a group of typically developing adults. Electrophysiological and behavioural data are collected during a target location task under two experimental conditions: Target Learning and Target Cued. Movement times (MTs) are employed as a behavioural metric of performance, while dynamic P3b amplitudes and power in the alpha band (approximately 10 Hz) are explored as electrophysiological metrics during visuospatial learning. Results demonstrate that task performance, as measured by MT, is highly correlated with P3b amplitude and alpha power at a consecutive trial level (trials 1-30). The current set of results, in conjunction with the existing literature, suggests that changes in P3b amplitude and alpha power could correspond to different aspects of the learning process. Here it is hypothesized that changes in P3b correspond to a diminishing inter-stimulus interval and reduced stimulus relevance, while the corresponding changes in alpha power represent an automation of response as habituation occurs in participants. The novel analysis presented in the current study demonstrates how gradual electrophysiological changes can be tracked during the visuospatial learning process under the current paradigm.