Surprise response as a probe for compressed memory states

The Impact of Spectral and Temporal Degradation on Vocoded Speech Recognition in Early-Blind Individuals

This study compared the impact of spectral and temporal degradation on vocoded speech recognition between early-blind and sighted subjects. The participants included 25 early-blind subjects (30.32 ± 4.88 years; male:female, 14:11) and 25 age- and sex-matched sighted subjects. Tests included monosyllable recognition in noise at various signal-to-noise ratios (-18 to -4 dB), matrix sentence-in-noise recognition, and vocoded speech recognition with different numbers of channels (4, 8, 16, and 32) and temporal envelope cutoff frequencies (50 vs 500 Hz). Cortical-evoked potentials (N2 and P3b) were measured in response to spectrally and temporally degraded stimuli. The early-blind subjects displayed superior monosyllable and sentence recognition than sighted subjects (all p < 0.01). In the vocoded speech recognition test, a three-way repeated-measure analysis of variance (two groups × four channels × two cutoff frequencies) revealed significant main effects of group, channel, and cutoff frequency (all p < 0.001). Early-blind subjects showed increased sensitivity to spectral degradation for speech recognition, evident in the significant interaction between group and channel (p = 0.007). N2 responses in early-blind subjects exhibited shorter latency and greater amplitude in the 8-channel (p = 0.022 and 0.034, respectively) and shorter latency in the 16-channel (p = 0.049) compared with sighted subjects. In conclusion, early-blind subjects demonstrated speech recognition advantages over sighted subjects, even in the presence of spectral and temporal degradation. Spectral degradation had a greater impact on speech recognition in early-blind subjects, while the effect of temporal degradation was similar in both groups.

Enhanced electrophysiological responses to explicitly predicted and pre-imagined inputs, with confirmation from online decoding with neuro-feedback

Neural responses to sensory inputs can scale with the likelihood of encountering the input. This is consistent with the predictive coding framework, in that the human brain is expected to be less responsive to predicted inputs. Typically, however, prediction is not explicitly measured. It is inferred from the probability of encountering an event. When an input is explicitly predicted, responses to predicted inputs can be enhanced. Here, we ask if this effect can be ascribed to a generic priming effect, from pre-cogitating about one of two possible inputs. Consistent with this, we find that P300s (a relatively late event-related potential measured with electroencephalography) are greater for explicitly predicted audio and visual inputs, and that this effect cannot be distinguished from a priming effect from pre-imagining audio or visual presentations. Evidence indicates that participants engaged in pre-imagining presentations, as we were able to decode online what type of presentation (audio or visual) they were imagining with a high success rate (approx. 73%), and we encouraged compliance with neuro-feedback regarding this success rate. Our data confirm that human cortex can be more responsive to inputs that have been subject to pre-cogitation-including explicit predictions. This highlights that while anticipatory processes can reduce responding to likely inputs, they can also enhance responding to explicitly predicted inputs.

Event Probabilities Have a Different Impact on Early and Late Electroencephalographic Measures Regarded as Metrics of Prediction

The oddball protocol has been used to study the neural and perceptual consequences of implicit predictions in the human brain. The protocol involves presenting a sequence of identical repeated events that are eventually broken by a novel "oddball" presentation. Oddball presentations have been linked to increased neural responding and to an exaggeration of perceived duration relative to repeated events. Because the number of repeated events in such protocols is circumscribed, as more repeats are encountered, the conditional probability of a further repeat decreases-whereas the conditional probability of an oddball increases. These facts have not been appreciated in many analyses of oddballs; repeats and oddballs have rather been treated as binary event categories. Here, we show that the human brain is sensitive to conditional event probabilities in an active, visual oddball paradigm. P300 responses (a relatively late component of visually evoked potentials measured with EEG) tended to be greater for less likely oddballs and repeats. By contrast, P1 responses (an earlier component) increased for repeats as a goal-relevant target presentation neared, but this effect occurred even when repeat probabilities were held constant, and oddball P1 responses were invariant. We also found that later, more likely oddballs seemed to last longer, and this effect was largely independent of the number of preceding repeats. These findings speak against a repetition suppression account of the temporal oddball effect. Overall, our data highlight an impact of event probability on later, rather than earlier, electroencephalographic measures previously related to predictive processes-and the importance of considering conditional probabilities in sequential presentation paradigms.

Prefrontal event-related potential markers in association with mild cognitive impairment

Background

Alzheimer's disease (AD) is among the leading contributors of dementia globally with approximately 60-70% of its cases. Current research is focused on the mild cognitive impairment (MCI), which is associated with cognitive decline but does not disrupt routine activities. Event-related potential (ERP) research is essential in screening patients with MCI. Low-density channel electroencephalography (EEG) is frequently used due to its convenience, portability, and affordability, making it suitable for resource-constrained environments. Despite extensive research on neural biomarkers for cognitive impairment, there is a considerable gap in understanding the effects on early stages of cognitive processes, particularly when combining physiological and cognitive markers using portable devices. The present study aimed to examine cognitive shortfalls and behavioral changes in patients with MCI using prefrontal selective attention ERP recorded from a prefrontal two-channel EEG device.

Methods

We assessed cognitive decline using the Mini-Mental State Examination (MMSE) and the Seoul Neuropsychological Screening Battery (SNSB). We administered auditory selective attention tasks to 598 elderly participants, including those with MCI (160) and cognitively normal (CN) individuals (407). We conducted statistical analyses such as independent t-tests, Pearson's correlations, and univariate and multiple logistic regression analyses to assess group differences and associations between neuropsychological tests, ERP measures, behavioral measures, and MCI prevalence.

Results

Our findings revealed that patients with MCI demonstrated slower information-processing abilities, and exhibited poorer task execution, characterized by reduced accuracy, increased errors, and higher variability in response time, compared to CN adults. Multiple logistic regression analyses confirmed the association between some ERP and behavioral measures with MCI prevalence, independent of demographic and neuropsychological factors. A relationship was observed between neuropsychological scores, ERP, and behavioral measures.

Discussion

The slower information processing abilities, and poor task execution in the MCI group compared to the CN individuals suggests flawed neurological changes and reduced attentional maintenance during cognitive processing, respectively. Hence, the utilization of portable EEG devices to capture prefrontal selective attention ERPs, in combination with behavioral assessments, holds promise for the identification of mild cognitive deficits and neural alterations in individuals with MCI. This approach could potentially augment the traditional neuropsychological tests during clinical screening for MCI.

Inhibitory control effectiveness can be improved: The role of arousal, subjective significance and origin of words in modified Emotional Stroop Test

The interference control measured in the Emotional Stroop Task is the phenomenon that gives us an insight into mechanisms of emotion-cognition interactions. Especially the role of dimensions of affect can be easily studied with this paradigm. In the current study, we were interested in the role of the complexity of emotional stimuli (origin). We also aimed at searching for activation-like factors that impair (arousal) or improve (subjective significance) the effectiveness of cognitive control. We have used an orthogonal manipulation of all the above dimensions in words. We expected to find the contrastive effects of arousal and subjective significance on reaction times and Event Related Potential’s amplitudes. On a behavioural level, we observed the reduction of reaction times with increasing subjective significance of stimuli and reflective origin. We also found a correlation between subjective significance and reduction of amplitude polarisation in the N450 component associated with cognitive control execution effort. This experiment shows that subjective significance has an improving role for cognitive control effectiveness, even when valence, arousal and origin levels are controlled. This guides us to conclude that external stimuli may drive not only disruption of control but also its improvement.

Neural prediction errors depend on how an expectation was formed

When a visual event is unexpected, because it violates a train of repeated events, it excites a greater positive electrical potential at sensors positioned above occipital-parietal human brain regions (the P300). Such events can also seem to have an increased duration relative to repeated (implicitly expected) events. However, recent behavioural evidence suggests that when events are unexpected because they violate a declared prediction-a guess-there is an opposite impact on duration perception. The neural consequences of incorrect declared predictions have not been examined. We replicated the finding whereby repetition violating events elicit a larger P300 response. However, we found that events that violated a declared prediction entrained an opposite pattern of response-a smaller P300. These data suggest that the neural consequences of a violated prediction are not uniform but depend on how the prediction was formed.

A Review of Possible EEG Markers of Abstraction, Attentiveness, and Memorisation in Cyber-Physical Systems for Special Education

Cyber-physical systems (CPSs) for special education rely on effective mental and brain processing during the lesson, performed with the assistance of humanoid robots. The improved diagnostic ability of the CPS is a prerogative of the system for efficient technological support of the pedagogical process. The article focuses on the available knowledge of possible EEG markers of abstraction, attentiveness, and memorisation (in some cases combined with eye tracking) related to predicting effective mental and brain processing during the lesson. The role of processing abstraction is emphasised as the learning mechanism, which is given priority over the other mechanisms by the cognitive system. The main markers in focus are P1, N170, Novelty P3, RewP, N400, and P600. The description of the effects is accompanied by the analysis of some implications for the design of novel educational scenarios in inclusive classes.

Neurophysiological correlates of purchase decision-making

Economic decisions are characterized by their uncertainty and the lack of explicit feedback that indicates the correctness of decisions at the time they are made. Nevertheless, very little is known about the neural mechanisms involved in this process. Our study sought to identify the neurophysiological correlates of purchase decision-making in situations where the optimal purchase time is not known. EEG was recorded in 24 healthy subjects while they were performing a new experimental paradigm that simulates real economic decisions. At the time of price presentation, we found an increase in the P3 Event-Related Potential and induced theta and alpha oscillatory activity when participants chose to buy compared to when they decided to wait for a better price. These results reflect the engagement of attention and executive function in purchase decision-making and might help in the understanding of brain mechanisms underlying economic decisions in uncertain scenarios.

The value-complexity trade-off for reinforcement learning based brain-computer interfaces

OBJECTIVE

One of the recent developments in the field of brain-computer interfaces (BCI) is the reinforcement learning (RL) based BCI paradigm, which uses neural error responses as the reward feedback on the agent's action. While having several advantages over motor imagery based BCI, the reliability of RL-BCI is critically dependent on the decoding accuracy of noisy neural error signals. A principled method is needed to optimally handle this inherent noise under general conditions.

APPROACH

By determining a trade-off between the expected value and the informational cost of policies, the info-RL (IRL) algorithm provides optimal low-complexity policies, which are robust under noisy reward conditions and achieve the maximal obtainable value. In this work we utilize the IRL algorithm to characterize the maximal obtainable value under different noise levels, which in turn is used to extract the optimal robust policy for each noise level.

MAIN RESULTS

Our simulation results of a setting with Gaussian noise show that the complexity level of the optimal policy is dependent on the reward magnitude but not on the reward variance, whereas the variance determines whether a lower complexity solution is favorable or not. We show how this analysis can be utilized to select optimal robust policies for an RL-BCI and demonstrate its use on EEG data.

SIGNIFICANCE

We propose here a principled method to determine the optimal policy complexity of an RL problem with a noisy reward, which we argue is particularly useful for RL-based BCI paradigms. This framework may be used to minimize initial training time and allow for a more dynamic and robust shared control between the agent and the operator under different conditions.

Physiological and Medico-Social Research Trends of the Wave P300 and More Late Components of Visual Event-Related Potentials

To extend the application of the late waves of the event-related potentials (ERPs) to multiple modalities, devices and software the underlying physiological mechanisms and responses of the brain for a particular sensory system and mental function must be carefully examined. The objective of this study was aimed to study the sensory processes of the “human-computer interaction” model when classifying visual images with an incomplete set of signs based on the analysis of early, middle, late and slow ERPs components. 26 healthy subjects (men) aged 20–26 years were investigated. ERPs in 19 monopolar sites according to the 10/20 system were recorded. Discriminant and factor analyzes (BMDP Statistical Software) were applied. The component N₄₅₀ is the most specialized indicator of the perception of unrecognizable (oddball) visual images. The amplitude of the ultra-late components N₇₅₀ and N₉₀₀ is also higher under conditions of presentation of the oddball image, regardless of the location of the registration points. In brain pathology along with the pronounced asymmetry of the wave distribution, reduction of the N₁₅₀ wave and lengthening of its peak latency, a line of regularities were noted. These include–a pronounced reduction in peak latency P₂₅₀ and N₃₅₀, an increased amplitude of N₃₅₀ in the frontal and central points of registration, a decrease in the amplitude of N₄₅₀ in the left frontal cortex and its increase in the occipital registration points, activation of the occipital cortex at a time interval of 400–500 ms, as well as fusion later waves. We called such phenomena of the development of cognitive ERP in brain pathology “the incongruence of ERP components”. The results of the research are discussed in the light of the paradigm of the P₃₀₀ wave application in brain-computer interface systems, as well as with the peculiarities in brain pathology.