Altered grid-like coding in early blind people.

Cognitive maps in the hippocampal-entorhinal system are central for the representation of both spatial and non-spatial relationships. Although this system, especially in humans, heavily relies on vision, the role of visual experience in shaping the development of cognitive maps remains largely unknown. Here, we test sighted and early blind individuals in both imagined navigation in fMRI and real-world navigation. During imagined navigation, the Human Navigation Network, constituted by frontal, medial temporal, and parietal cortices, is reliably activated in both groups, showing resilience to visual deprivation. However, neural geometry analyses highlight crucial differences between groups. A 60° rotational symmetry, characteristic of a hexagonal grid-like coding, emerges in the entorhinal cortex of sighted but not blind people, who instead show a 90° (4-fold) symmetry, indicative of a square grid. Moreover, higher parietal cortex activity during navigation in blind people correlates with the magnitude of 4-fold symmetry. In sum, early blindness can alter the geometry of entorhinal cognitive maps, possibly as a consequence of higher reliance on parietal egocentric coding during navigation.

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.

Anodal transcranial direct current stimulation does not enhance the effects of motor imagery training of a sequential finger-tapping task in young adults.

When applied over the primary motor cortex (M1), anodal transcranial direct current stimulation (a-tDCS) could enhance the effects of a single motor imagery training (MIt) session on the learning of a sequential finger-tapping task (SFTT). This study aimed to investigate the effect of a-tDCS on the learning of an SFTT during multiple MIt sessions. Two groups of 16 healthy young adults participated in three consecutive MIt sessions over 3 days, followed by a retention test 1 week later. They received active or sham a-tDCS during a MIt session in which they mentally rehearsed an eight-item complex finger sequence with their left hand. Before and after each session, and during the retention test, they physically repeated the sequence as quickly and accurately as possible. Both groups (i) improved their performance during the first two sessions, showing online learning; (ii) stabilised the level they reached during all training sessions, reflecting offline consolidation; and (iii) maintained their performance level one week later, showing retention. However, no significant difference was found between the groups, regardless of the MSL stage. These results emphasise the importance of performing several MIt sessions to maximise performance gains, but they do not support the additional effects of a-tDCS.

Beyond imagination: Sorting out and treating psychosis in the context of autism spectrum disorder.

In the last decades, growing caseness for Autism Spectrum Disorder (ASD) has been observed, owing to the diagnostic accretion of low-impairment forms, over and above other possible causes. Unrecognized ASD is likely to be mislabeled as a psychotic disorder (PD), as people in the spectrum may show 'pseudopsychotic' symptoms, resembling both negative and positive symptoms. On the other hand, PDs are likely to be overlooked when they arise in people with ASD, due to the 'diagnostic overshadowing' of new-onset conditions by lifelong core autistic symptoms. The three available metanalyses on the occurrence of psychosis in adults with ASD convergently reported a rate of PDs that is at least ten times higher than in the general population. Therefore, the lack of literature addressing risk factors, outcomes, and treatment options for psychosis in the context of ASD is utterly concerning. The present review aims to summarize up-to-date knowledge of PDs with comorbid ASD in terms of clinical features, course, and treatment.

Ideas of the university.

When intellectual values are no longer paramount, other commitments-say to the professionalized disciplinary pathways that have congealed as the default means of university organization and governance-not only fill the vacuum but seriously limit our imagination.

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.

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.

Investigating the different mechanisms in related neural activities: a focus on auditory perception and imagery.

Neuroimaging studies have shown that the neural representation of imagery is closely related to the perception modality; however, the undeniable different experiences between perception and imagery indicate that there are obvious neural mechanism differences between them, which cannot be explained by the simple theory that imagery is a form of weak perception. Considering the importance of functional integration of brain regions in neural activities, we conducted correlation analysis of neural activity in brain regions jointly activated by auditory imagery and perception, and then brain functional connectivity (FC) networks were obtained with a consistent structure. However, the connection values between the areas in the superior temporal gyrus and the right precentral cortex were significantly higher in auditory perception than in the imagery modality. In addition, the modality decoding based on FC patterns showed that the FC network of auditory imagery and perception can be significantly distinguishable. Subsequently, voxel-level FC analysis further verified the distribution regions of voxels with significant connectivity differences between the 2 modalities. This study complemented the correlation and difference between auditory imagery and perception in terms of brain information interaction, and it provided a new perspective for investigating the neural mechanisms of different modal information representations.

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 Self-Narrative Role in the Diagnosis of Motivation to Achieve Personal Success.

This study aims to investigate the efficacy of self-narrative as a tool for identifying personality traits conducive to motivation for success. The research employs several methodologies, including the "Readiness for Self-Development" test by V.L. Pavlov, the Achievement Motivation Diagnosis test, and the katathym imaginative psychotherapy motive "Mountain" as a form of self-narrative. Psycholinguistic analysis tools such as the verbosity coefficient, embolism coefficient, and correlation coefficient are utilized. Through empirical analysis of self-narratives, criteria for evaluating motivational potential are established. Quantitative and qualitative analyses of respondent narratives reveal distinct patterns. Coefficients derived from psycholinguistic analysis indicate a correlation between self-narratives and motivation for achievement. Respondents demonstrating motivation for success and readiness for self-development exhibit lower verbosity and embolism coefficients. Conversely, those with a tendency to avoid failure and low readiness for self-development tend to employ narratives rich in superficial language elements. The findings suggest that self-narrative analysis can effectively gauge an individual's motivational tendencies and readiness for personal development. This method holds promise as a tool for identifying and nurturing talent within organizations, particularly in the context of forming a vertical personnel reserve. By understanding the motivational drivers revealed through self-narratives, organizations can better tailor their approaches to talent management and development.

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.

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.

TBEEG: A Two-Branch Manifold Domain Enhanced Transformer Algorithm for Learning EEG Decoding.

The electroencephalogram-based (EEG) brain-computer interface (BCI) has garnered significant attention in recent research. However, the practicality of EEG remains constrained by the lack of efficient EEG decoding technology. The challenge lies in effectively translating intricate EEG into meaningful, generalizable information. EEG signal decoding primarily relies on either time domain or frequency domain information. There lacks a method capable of simultaneously and effectively extracting both time and frequency domain features, as well as efficiently fuse these features. Addressing these limitations, a two-branch Manifold Domain enhanced transformer algorithm is designed to holistically capture EEG's spatio-temporal information. Our method projects the time-domain information of EEG signals into the Riemannian spaces to fully decode the time dependence of EEG signals. Using wavelet transform, the time domain information is converted into frequency domain information, and the spatial information contained in the frequency domain information of EEG signal is mined through the spectrogram. The effectiveness of the proposed TBEEG algorithm is validated on BCIC-IV-2a dataset and MAMEM-SSVEP-II datasets.

Peering into the future: Eye movements predict neural repetition effects during episodic simulation.

Imagining future scenarios involves recombining different elements of past experiences into a coherent event, a process broadly supported by the brain's default network. Prior work suggests that distinct brain regions may contribute to the inclusion of different simulation features. Here we examine how activity in these brain regions relates to the vividness of future simulations. Thirty-four healthy young adults imagined future events with familiar people and locations in a two-part study involving a repetition suppression paradigm. First, participants imagined events while their eyes were tracked during a behavioral session. Immediately after, participants imagined events during MRI scanning. The events to be imagined were manipulated such that some were identical to those imagined in the behavioral session while others involved new locations, new people, or both. In this way, we could examine how self-report ratings and eye movements predict brain activity during simulation along with specific simulation features. Vividness ratings were negatively correlated with eye movements, in contrast to an often-observed positive relationship with past recollection. Moreover, fewer eye movements predicted greater involvement of the hippocampus during simulation, an effect specific to location features. Our findings suggest that eye movements may facilitate scene construction for future thinking, lending support to frameworks that spatial information forms the foundation of episodic simulation.

Effects of finger pinch motor imagery on short-latency afferent inhibition and corticospinal excitability.

Motor imagery is a cognitive process involving the simulation of motor actions without actual movements. Despite the reported positive effects of motor imagery training on motor function, the underlying neurophysiological mechanisms have yet to be fully elucidated. Therefore, the purpose of the present study was to investigate how sustained tonic finger-pinching motor imagery modulates sensorimotor integration and corticospinal excitability using short-latency afferent inhibition (SAI) and single-pulse transcranial magnetic stimulation (TMS) assessments, respectively. Able-bodied individuals participated in the study and assessments were conducted under two experimental conditions in a randomized order between participants: (1) participants performed motor imagery of a pinch task while observing a visual image displayed on a monitor (Motor Imagery), and (2) participants remained at rest with their eyes fixed on the monitor displaying a cross mark (Control). For each condition, sensorimotor integration and corticospinal excitability were evaluated during sustained tonic motor imagery in separate sessions. Sensorimotor integration was assessed by SAI responses, representing inhibition of motor-evoked potentials (MEPs) in the first dorsal interosseous muscle elicited by TMS following median nerve stimulation. Corticospinal excitability was assessed by MEP responses elicited by single-pulse TMS. There was no significant difference in the magnitude of SAI responses between motor imagery and Control conditions, while MEP responses were significantly facilitated during the Motor Imagery condition compared to the Control condition. These findings suggest that motor imagery facilitates corticospinal excitability, without altering sensorimotor integration, possibly due to insufficient activation of the somatosensory circuits or lack of afferent feedback during sustained tonic motor 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.

Collectives closer to the self are anticipated to have a brighter future: Self-enhancement in collective cognition.

Collective future thinking is a budding research field concerned with the act of imagining possible events in the future of a collective-typically one's nation. Prior research has shown that people imagine more positive than negative events in the personal future but more negative than positive events in the collective future. This interaction has been interpreted as a valence-based dissociation between collective and personal cognition. We examine if degrees of self-relatedness may account for these effects. In Study 1, participants (N = 299) imagined events in the future of their country and family, rated how central they viewed these collectives to their self and identity and rated the collectives' futures for positive and negative valence. Positive and negative valence of the imagined collective futures was strongly associated with how central the collectives were viewed to the self. In Study 2, participants (N = 306) rated self-centrality, personal agency, and moral decline perceived for their country. All three measures explained independent variance in how positive the future was for their country. In Study 3, participants (N = 310) self-nominated collectives that they viewed as highly versus minimally central to their self and identity. The futures of highly central collectives were rated more positive than negative, whereas such positive bias was absent for the futures of minimally self-central collectives. Overall, the findings indicate that a continuum of different degrees of self-relatedness may explain the Valence × Domain interaction in previous work, and suggest a need to integrate research on collective future thinking with self-serving biases in social cognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Isolating the effects of visual imagery on prospective memory.

Two experiments investigated the role of visual imagery in prospective memory (PM). In experiment 1, 140 participants completed a general knowledge quiz which included a PM task of writing a letter "X" next to any questions that referred to space. Participants either visualised themselves performing this task, verbalised an implementation intention about the task, did both, or did neither. Performance on the PM task was enhanced in both conditions involving visual imagery but not by implementation intentions alone. In experiment 2, 120 participants imagined themselves writing a letter "X" next to questions about space, or in a bizarre imagery condition imagined themselves drawing an alien next to those questions. Relative to the control condition, PM was significantly enhanced when participants imagined writing a letter "X" next to the target questions, but not by the bizarre imagery task. The findings indicate that the robust effects of imagery observed in retrospective memory also extend to PM.

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.