Slower but more accurate mental rotation performance in aphantasia linked to differences in cognitive strategies.

Mental rotation tasks are frequently used as standard measures of mental imagery. However, aphantasia research has brought such use into question. Here, we assessed a large group of individuals who lack visual imagery (aphantasia) on two mental rotation tasks: a three-dimensional block-shape, and a human manikin rotation task. In both tasks, those with aphantasia had slower, but more accurate responses than controls. Both groups demonstrated classic linear increases in response time and error-rate as functions of angular disparity. In the three-dimensional block-shape rotation task, a within-group speed-accuracy trade-off was found in controls, whereas faster individuals in the aphantasia group were also more accurate. Control participants generally favoured using object-based mental rotation strategies, whereas those with aphantasia favoured analytic strategies. These results suggest that visual imagery is not crucial for successful performance in classical mental rotation tasks, as alternative strategies can be effectively utilised in the absence of holistic mental representations.

Does context matter for memory? Testing the effectiveness of learning by imagining situated interactions with objects.

Mounting evidence supports the efficacy of mental imagery for verbal information retention. Motor imagery, imagining oneself interacting physically with the object to be learned, emerges as an optimal form compared to less physically engaging imagery. Yet, when engaging in mental imagery, it occurs within a specific context that may affect imagined actions and consequently impact the mnemonic benefits of mental imagery. In a first study, participants were given instructions for incidental learning: mental rehearsal, visual imagery, motor imagery or situated motor imagery. The latter, which involved imagining physical interaction with an item within a coherent situation, produced the highest proportion of correct recalls. This highlights memory's role in supporting situated actions and offers the possibility for further developing the mnemonic potential of embodied mental imagery. Furthermore, item-level analysis showed that individuals who engaged in situated motor imagery remembered words primarily due to the sensorimotor characteristics of the words' referent. A second study investigating the role of inter-item distinctiveness in this effect failed to determine the extent to which the situational and motor elements need to be distinctive in order to be considered useful retrieval cues and produce an optimal memory performance.

Fatigue in children using motor imagery and P300 brain-computer interfaces.

BACKGROUND: Brain-computer interface (BCI) technology offers children with quadriplegic cerebral palsy unique opportunities for communication, environmental exploration, learning, and game play. Research in adults demonstrates a negative impact of fatigue on BCI enjoyment, while effects on BCI performance are variable. To date, there have been no pediatric studies of BCI fatigue. The purpose of this study was to assess the effects of two different BCI paradigms, motor imagery and visual P300, on the development of self-reported fatigue and an electroencephalography (EEG) biomarker of fatigue in typically developing children. METHODS: Thirty-seven typically-developing school-aged children were recruited to a prospective, crossover study. Participants attended three sessions: (A) motor imagery-BCI, (B) visual P300-BCI, and (C) video viewing (control). The motor imagery task involved an imagined left- or right-hand squeeze. The P300 task involved attending to one square on a 3 × 3 grid during a random single flash sequence. Each paradigm had respective calibration periods and a similar visual counting game. Primary outcomes were self-reported fatigue and the power of the EEG alpha band both collected during resting-state periods pre- and post-task. Self-reported fatigue was measured using a 10-point visual analog scale. EEG alpha band power was calculated as the integrated power spectral density from 8 to 12 Hz of the EEG spectrum. RESULTS: Thirty-two children completed the protocol (age range 7-16, 63% female). Self-reported fatigue and EEG alpha band power increased across all sessions (F(1,155) = 33.9, p < 0.001; F = 5.0(1,149), p = 0.027 respectively). No differences in fatigue development were observed between session types. There was no correlation between self-reported fatigue and EEG alpha band power change. BCI performance varied between participants and paradigms as expected but was not associated with self-reported fatigue or EEG alpha band power. CONCLUSION: Short periods (30-mintues) of BCI use can increase self-reported fatigue and EEG alpha band power to a similar degree in children performing motor imagery and P300 BCI paradigms. Performance was not associated with our measures of fatigue; the impact of fatigue on useability and enjoyment is unclear. Our results reflect the variability of fatigue and the BCI experience more broadly in children and warrant further investigation.

No clear evidence of a difference between individuals who self-report an absence of auditory imagery and typical imagers on auditory imagery tasks.

Aphantasia is characterised by the inability to create mental images in one's mind. Studies investigating impairments in imagery typically focus on the visual domain. However, it is possible to generate many different forms of imagery including imagined auditory, kinesthetic, tactile, motor, taste and other experiences. Recent studies show that individuals with aphantasia report a lack of imagery in modalities, other than vision, including audition. However, to date, no research has examined whether these reductions in self-reported auditory imagery are associated with decrements in tasks that require auditory imagery. Understanding the extent to which visual and auditory imagery deficits co-occur can help to better characterise the core deficits of aphantasia and provide an alternative perspective on theoretical debates on the extent to which imagery draws on modality-specific or modality-general processes. In the current study, individuals that self-identified as being aphantasic and matched control participants with typical imagery performed two tasks: a musical pitch-based imagery and voice-based categorisation task. The majority of participants with aphantasia self-reported significant deficits in both auditory and visual imagery. However, we did not find a concomitant decrease in performance on tasks which require auditory imagery, either in the full sample or only when considering those participants that reported significant deficits in both domains. These findings are discussed in relation to the mechanisms that might obscure observation of imagery deficits in auditory imagery tasks in people that report reduced auditory imagery.

Aphantasia and involuntary imagery.

Aphantasia is a condition that is often characterized as the impaired ability to create voluntary mental images. Aphantasia is assumed to selectively affect voluntary imagery mainly because even though aphantasics report being unable to visualize something at will, many report having visual dreams. We argue that this common characterization of aphantasia is incorrect. Studies on aphantasia are often not clear about whether they are assessing voluntary or involuntary imagery, but some studies show that several forms of involuntary imagery are also affected in aphantasia (including imagery in dreams). We also raise problems for two attempts to show that involuntary images are preserved in aphantasia. In addition, we report the results of a study about afterimages in aphantasia, which suggest that these tend to be less intense in aphantasics than in controls. Involuntary imagery is often treated as a unitary kind that is either present or absent in aphantasia. We suggest that this approach is mistaken and that we should look at different types of involuntary imagery case by case. Doing so reveals no evidence of preserved involuntary imagery in aphantasia. We suggest that a broader characterization of aphantasia, as a deficit in forming mental imagery, whether voluntary or not, is more appropriate. Characterizing aphantasia as a volitional deficit is likely to lead researchers to give incorrect explanations for aphantasia, and to look for the wrong mechanisms underlying it.

The priming of stimulus-elicited involuntary mental imagery.

Percepts, urges, and even high-level cognitions often enter the conscious field involuntarily. The Reflexive Imagery Task (RIT) was designed to investigate experimentally the nature of such entry into consciousness. In the most basic version of the task, participants are instructed not to subvocalize the names of visual objects. Involuntary subvocalizations arise on the majority of the trials. Can these effects be influenced by priming? In our experiment, participants were exposed to an auditory prime 300 ms before being presented with the RIT stimuli. For example, participants heard the word "FOOD" before seeing two RIT stimuli (e.g., line drawings of BANANA and CAT, with the former being the target of the prime). The short span between prime and target allowed us to assess whether the RIT effect is strategic or automatic. Before each trial, participants were instructed to disregard what they hear, and not to think of the name of any of the objects. On an average of 83% of the trials, the participants thought (involuntarily) of the name of the object associated with the prime. This is the first study to use a priming technique within the context of the RIT. The theoretical implications of these involuntary effects are discussed.

Adaptive Time-Frequency Segment Optimization for Motor Imagery Classification.

Motor imagery (MI)-based brain-computer interface (BCI) has emerged as a crucial method for rehabilitating stroke patients. However, the variability in the time-frequency distribution of MI-electroencephalography (EEG) among individuals limits the generalizability of algorithms that rely on non-customized time-frequency segments. In this study, we propose a novel method for optimizing time-frequency segments of MI-EEG using the sparrow search algorithm (SSA). Additionally, we apply a correlation-based channel selection (CCS) method that considers the correlation coefficient of features between each pair of EEG channels. Subsequently, we utilize a regularized common spatial pattern method to extract effective features. Finally, a support vector machine is employed for signal classification. The results on three BCI datasets confirmed that our algorithm achieved better accuracy (99.11% vs. 94.00% for BCI Competition III Dataset IIIa, 87.70% vs. 81.10% for Chinese Academy of Medical Sciences dataset, and 87.94% vs. 81.97% for BCI Competition IV Dataset 1) compared to algorithms with non-customized time-frequency segments. Our proposed algorithm enables adaptive optimization of EEG time-frequency segments, which is crucial for the development of clinically effective motor rehabilitation.

A matter of precision? Scene imagery in individuals with high-functioning autism spectrum disorder.

The ability to create mental representations of scenes is essential for remembering, predicting, and imagining. In individuals with autism spectrum disorders (ASD) this ability may be impaired. Considering that autistic characteristics such as weak central coherence or reduced communication abilities may disadvantage autistic participants in traditional imagery tasks, this study attempted to use a novel task design to measure the ability of scene imagery. Thirty high-functioning adults with ASD and 27 non-autistic matched control adults were asked to describe imagined fictitious scenes using two types of scene imagery tasks. In a free imagery task, participants were asked to imagine a scene based on a given keyword. In a guided imagery task, participants had to imagine a scene based on a detailed description of the scene. Additionally, narrative abilities were assessed using the Narrative Scoring Scheme. Statistical analyses revealed no group effects in the free and guided imagery of fictional scenes. Participants with ASD performed worse than control participants in the narrative task. Narrative abilities correlated positively with performance in both imagery tasks in the ASD group only. Hence, individuals with ASD seem to show as good imagery abilities as non-autistic individuals. The results are discussed in the light of the differences between imagery and imagination and possible gender differences.

EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding.

The motor imagery brain-computer interface (MI-BCI) based on electroencephalography (EEG) is a widely used human-machine interface paradigm. However, due to the non-stationarity and individual differences among subjects in EEG signals, the decoding accuracy is limited, affecting the application of the MI-BCI. In this paper, we propose the EISATC-Fusion model for MI EEG decoding, consisting of inception block, multi-head self-attention (MSA), temporal convolutional network (TCN), and layer fusion. Specifically, we design a DS Inception block to extract multi-scale frequency band information. And design a new cnnCosMSA module based on CNN and cos attention to solve the attention collapse and improve the interpretability of the model. The TCN module is improved by the depthwise separable convolution to reduces the parameters of the model. The layer fusion consists of feature fusion and decision fusion, fully utilizing the features output by the model and enhances the robustness of the model. We improve the two-stage training strategy for model training. Early stopping is used to prevent model overfitting, and the accuracy and loss of the validation set are used as indicators for early stopping. The proposed model achieves within-subject classification accuracies of 84.57% and 87.58% on BCI Competition IV Datasets 2a and 2b, respectively. And the model achieves cross-subject classification accuracies of 67.42% and 71.23% (by transfer learning) when training the model with two sessions and one session of Dataset 2a, respectively. The interpretability of the model is demonstrated through weight visualization method.

On the relationship between foveal mask interference and mental imagery in peripheral object recognition.

A delayed foveal mask affects perception of peripheral stimuli. The effect is determined by the timing of the mask and by the similarity with the peripheral stimulus. A congruent mask enhances performance, while an incongruent one impairs it. It is hypothesized that foveal masks disrupt a feedback mechanism reaching the foveal cortex. This mechanism could be part of a broader circuit associated with mental imagery, but this hypothesis has not as yet been tested. We investigated the link between mental imagery and foveal feedback. We tested the relationship between performance fluctuations caused by the foveal mask-measured in terms of discriminability (d') and criterion (C)-and the scores from two questionnaires designed to assess mental imagery vividness (VVIQ) and another exploring object imagery, spatial imagery and verbal cognitive styles (OSIVQ). Contrary to our hypotheses, no significant correlations were found between VVIQ and the mask's impact on d' and C. Neither the object nor spatial subscales of OSIVQ correlated with the mask's impact. In conclusion, our findings do not substantiate the existence of a link between foveal feedback and mental imagery. Further investigation is needed to determine whether mask interference might occur with more implicit measures of imagery.

The positive dimension of schizotypy is associated with self-report measures of autobiographical memory and future thinking but not experimenter-scored indices.

ABSTRACTThe ability to remember our past and to imagine the future are critical to our sense of self. Previous research has indicated that they are disrupted in schizophrenia. However, it is unclear (i) whether this is found when examining experimenter-scored indices of content and/or participants' self-report of phenomenological characteristics, and (ii) how these abilities might be related to symptoms. This study sought to address these questions by taking a dimensional approach and measuring positive and negative schizotypal experiences in healthy people (n = 90). Participants were given cue words. For some, they remembered an event from the past and for others they generated an event in the future. No significant relationships were found with any aspect of schizotypy when participants' descriptions were scored by the experimenter according to a standardised episodic content measure. In contrast, several significant positive correlations were observed for past memory and future thinking when examining the positive dimension of schizotypy and participants' ratings, particularly to sensory characteristics of the experience and mental pre- or reliving. These results indicate enhanced subjective experiences of autobiographical memory and future thinking in those who report delusional and hallucinatory-like occurrences, which might be linked to mental imagery or metacognitive alterations.

Demystifying wine expertise through the lens of imagination: Descriptions and imagery vividness across sensory modalities.

For most untrained novices, talking about wine or imagining the smells and flavours of wine is difficult. Wine experts, on the other hand, have been found to have better imagery for wine, and are also more proficient in describing wine. Some scholars have suggested that imagery and language are based on similar underlying processes, but no conclusive evidence has been found regarding mental imagery and language production. In this study, we examined the relationship between imagery and language use in both novices and experts. In an online experiment, wine experts and novices were asked to imagine the colour, smell, taste and mouthfeel of wines in different situations, and were asked to rate the vividness of the imagined experience as well as describe it with words. The results show that experts differ from novices on a number of linguistic measures when describing wine, including the number of words used, the type of words used, the concreteness of those words, and the adjective to noun ratio. Similarly, imagery for wine was more vivid in wine experts compared to novices in the modalities of smell, taste, and mouthfeel, in alignment with previous work. Surprisingly, we found that no single linguistic variable significantly predicted the reported vividness of wine imagery, neither in experts nor in novices. However, the linguistic model predicted imagery vividness better using data from experts compared to novices. Taken together, these findings underscore that imagery and language are different facets of wine cognition.

EEG rhythm separation and time-frequency analysis of fast multivariate empirical mode decomposition for motor imagery BCI.

Motor imagery electroencephalogram (EEG) is widely employed in brain-computer interface (BCI) systems. As a time-frequency analysis method for nonlinear and non-stationary signals, multivariate empirical mode decomposition (MEMD) and its noise-assisted version (NA-MEMD) has been widely used in the preprocessing step of BCI systems for separating EEG rhythms corresponding to specific brain activities. However, when applied to multichannel EEG signals, MEMD or NA-MEMD often demonstrate low robustness to noise and high computational complexity. To address these issues, we have explored the advantages of our recently proposed fast multivariate empirical mode decomposition (FMEMD) and its noise-assisted version (NA-FMEMD) for analyzing motor imagery data. We emphasize that FMEMD enables a more accurate estimation of EEG frequency information and exhibits a more noise-robust decomposition performance with improved computational efficiency. Comparative analysis with MEMD on simulation data and real-world EEG validates the above assertions. The joint average frequency measure is employed to automatically select intrinsic mode functions that correspond to specific frequency bands. Thus, FMEMD-based classification architecture is proposed. Using FMEMD as a preprocessing algorithm instead of MEMD can improve the classification accuracy by 2.3% on the BCI Competition IV dataset. On the Physiobank Motor/Mental Imagery dataset and BCI Competition IV Dataset 2a, FMEMD-based architecture also attained a comparable performance to complex algorithms. The results indicate that FMEMD proficiently extracts feature information from small benchmark datasets while mitigating dimensionality constraints resulting from computational complexity. Hence, FMEMD or NA-FMEMD can be a powerful time-frequency preprocessing method for BCI.

Individual-finger motor imagery classification: a data-driven approach with Shapley-informed augmentation.

Objective. Classifying motor imagery (MI) tasks that involve fine motor control of the individual five fingers presents unique challenges when utilizing electroencephalography (EEG) data. In this paper, we systematically assess the classification of MI functions for the individual five fingers using single-trial time-domain EEG signals. This assessment encompasses both within-subject and cross-subject scenarios, supported by data-driven analysis that provides statistical validation of the neural correlate that could potentially discriminate between the five fingers.Approach. We present Shapley-informed augmentation, an informed approach to enhance within-subject classification accuracy. This method is rooted in insights gained from our data-driven analysis, which revealed inconsistent temporal features encoding the five fingers MI across sessions of the same subject. To evaluate its impact, we compare within-subject classification performance both before and after implementing this augmentation technique.Main results. Both the data-driven approach and the model explainability analysis revealed that the parietal cortex contains neural information that helps discriminate the individual five fingers' MI apart. Shapley-informed augmentation successfully improved classification accuracy in sessions severely affected by inconsistent temporal features. The accuracy for sessions impacted by inconsistency in their temporal features increased by an average of26.3%±6.70, thereby enabling a broader range of subjects to benefit from brain-computer interaction (BCI) applications involving five-fingers MI classification. Conversely, non-impacted sessions experienced only a negligible average accuracy decrease of2.01±5.44%. The average classification accuracy achieved is around 60.0% (within-session), 50.0% (within-subject) and 40.0% (leave-one-subject-out).Significance. This research offers data-driven evidence of neural correlates that could discriminate between the individual five fingers MI and introduces a novel Shapley-informed augmentation method to address temporal variability of features, ultimately contributing to the development of personalized systems.

Health anxiety amplifies fearful responses to illness-related imagery.

Severe health anxiety (HA) is characterized by excessive worry and anxiety about one's health, often accompanied by distressing intrusive imagery of signs of a serious illness or potentially receiving bad news about having a life-threatening disease. However, the emotional responses to these illness-related mental images in relation to HA have not been fully elucidated. Emotional responses to mental imagery of 142 participants were assessed in a well-controlled script-driven imagery task, systematically comparing emotional responses to illness-related imagery with neutral and standard fear imagery. The results revealed that participants reported higher anxiety, aversion, emotional arousal, and a stronger avoidance tendency during imagery of fear and illness-related scenes compared to neutral scenes. Importantly, the emotional modulation varied by the level of HA, indicating that individuals with higher HA experienced stronger emotional responses to illness-related imagery. This association between HA and fearful imagery could not be better accounted for by other psychological factors such as trait anxiety, anxiety sensitivity, somatic symptom severity, or symptoms of depression and anxiety. Fearful responding to standard threat material was not associated with HA. The present findings highlight the importance of considering fear responding to mental imagery in understanding and addressing HA.

Working memory signals in early visual cortex are present in weak and strong imagers.

It has been suggested that visual images are memorized across brief periods of time by vividly imagining them as if they were still there. In line with this, the contents of both working memory and visual imagery are known to be encoded already in early visual cortex. If these signals in early visual areas were indeed to reflect a combined imagery and memory code, one would predict them to be weaker for individuals with reduced visual imagery vividness. Here, we systematically investigated this question in two groups of participants. Strong and weak imagers were asked to remember images across brief delay periods. We were able to reliably reconstruct the memorized stimuli from early visual cortex during the delay. Importantly, in contrast to the prediction, the quality of reconstruction was equally accurate for both strong and weak imagers. The decodable information also closely reflected behavioral precision in both groups, suggesting it could contribute to behavioral performance, even in the extreme case of completely aphantasic individuals. Our data thus suggest that working memory signals in early visual cortex can be present even in the (near) absence of phenomenal imagery.

Association between visuo-spatial working memory and gait motor imagery.

Although motor imagery and working memory (WM) appear to be closely linked, no previous studies have demonstrated direct evidence for the relationship between motor imagery and WM abilities. This study investigated the association between WM and gait motor imagery and focused on the individual differences in young adults. This study included 33 participants (mean age: 22.2 ± 0.9 years). We used two methods to measure the ability of different WM domains: verbal and visuo-spatial WM. Gait motor imagery accuracy was assessed via the mental chronometry paradigm. We measured the times participants took to complete an actual and imagined walk along a 5 m walkway, with three different path widths. The linear mixed effects model analysis revealed that visuo-spatial WM ability was a significant predictor of the accuracy of gait motor imagery, but not of verbal WM ability. Specifically, individuals with lower visuo-spatial WM ability demonstrated more inaccuracies in the difficult path-width conditions. However, gait motor imagery was not as accurate as actual walking even in the easiest path width or in participants with high visuo-spatial WM ability. Further, visuo-spatial WM ability was significantly correlated with mental walking but not with actual walking. These results suggest that visuo-spatial WM is related to motor imagery rather than actual movement.

Revisiting the blind mind: Still no evidence for sensory visual imagery in individuals with aphantasia.

The inability to visualise was given the name aphantasia in 2015 by Zeman and colleagues. In 2018 we published research showing that fifteen individuals who self-identified as having aphantasia also demonstrated a lack of sensory visual imagery when undergoing the binocular rivalry imagery paradigm, suggesting more than just a metacognitive difference. Here we update these findings with over fifty participants with aphantasia and show that there is evidence for a lack of sensory imagery in aphantasia. How the binocular rivalry paradigm scores relate to the vividness of visual imagery questionnaire (VVIQ) and how aphantasia can be confirmed is discussed.

Classification Algorithm for fNIRS-based Brain Signals Using Convolutional Neural Network with Spatiotemporal Feature Extraction Mechanism.

Brain Computer Interface (BCI) is a highly promising human-computer interaction method that can utilize brain signals to control external devices. BCI based on functional near-infrared spectroscopy (fNIRS) is considered a relatively new and promising paradigm. fNIRS is a technique of measuring functional changes in cerebral hemodynamics. It detects changes in the hemodynamic activity of the cerebral cortex by measuring oxyhemoglobin and deoxyhemoglobin (HbR) concentrations and inversely predicts the neural activity of the brain. At the present time, Deep learning (DL) methods have not been widely used in fNIRS decoding, and there are fewer studies considering both spatial and temporal dimensions for fNIRS classification. To solve these problems, we proposed an end-to-end hybrid neural network for feature extraction of fNIRS. The method utilizes a spatial-temporal convolutional layer for automatic extraction of temporally valid information and uses a spatial attention mechanism to extract spatially localized information. A temporal convolutional network (TCN) is used to further utilize the temporal information of fNIRS before the fully connected layer. We validated our approach on a publicly available dataset including 29 subjects, including left-hand and right-hand motor imagery (MI), mental arithmetic (MA), and a baseline task. The results show that the method has few training parameters and high accuracy, providing a meaningful reference for BCI development.

No verbal overshadowing in aphantasia: The role of visual imagery for the verbal overshadowing effect.

The verbal overshadowing effect refers to the phenomenon that the verbal description of a past complex stimulus impairs its subsequent recognition. Theoretical explanations range from interference between different mental representations to the activation of different processing orientations or a provoked shift in the recognition criterion. In our study, 61 participants with aphantasia (= lack of mental imagery) and 70 controls participated in a verbal overshadowing paradigm. The verbal overshadowing effect did not occur in people with aphantasia, although the effect was replicated in controls. We speculate that this is either due to the lack of visual representations in people with aphantasia that verbal descriptions could interfere with, or to the absence of a shift in processing orientation during verbalisation. To rule out criterion-based explanations, further research is needed to distinguish between discriminability and response bias in people with aphantasia. Finally, data indicated that the verbal overshadowing effect may even be reversed in individuals with aphantasia, partly due to a lower memory performance in the no verbalisation condition. Effects of further variables are discussed, such as mental strategies, memory confidence, and difficulty, quantity and quality of verbalisation.