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How the brain generates conscious experiences remains profoundly mysterious. Pharmacological interventions that alter the state of consciousness have been proposed as a tool to investigate the neural mechanisms of consciousness. However, we have recently demonstrated that the sedative Propofol influences both conscious and unconscious neural processing. Altered arousal, and other pharmacological effects, therefore cannot be assumed a priori to provide information specifically on conscious neural processes. Instead, effects on both conscious and unconscious processes need to be considered. Here we investigated the role of noradrenergic activity in conscious and unconscious visuospatial processing. In Study 1 we used Dexmedetomidine, a sedative that specifically targets α2A noradrenergic receptors. In Study 2, we used sleep deprivation as a natural state of altered arousal, which exerts partially overlapping effects on noradrenaline levels. Unlike Propofol, both Dexmedetomidine and sleep deprivation selectively altered brain activity (fMRI BOLD signal change) during conscious processing. However, the two methods produced distinct effects on visuospatial bias during low arousal: while Dexmedetomidine reduced leftward bias, sleep deprivation increased leftward bias. These differential effects on spatial bias were explained by an unexpected increase in sympathetic drive, as indexed by increased activity in the central autonomic network and in heart rate, from sleep deprivation, that indicate increased rather than decreased noradrenaline levels during task performance. Together, these findings emphasize noradrenergic activity as a target for pharmacological manipulations of consciousness, which could open a window to its neurophysiological underpinnings.

In vivo proton magnetic resonance spectroscopy is a non-invasive technique used to measure biochemical molecules such as choline, glutamate, glutamine, and γ-Aminobutyric acid (GABA), many of which are relevant to anxiety and pain. However, the relationship between these neurotransmitters/metabolites and their implications for anxiety and subjective experience of pain is not yet fully understood. The objective of this cross-sectional study was to investigate the association between anxiety and pain ratings with levels of total choline, glutamate and GABA in brain regions known to be involved in anxiety and emotional experience of pain, specifically pregenual anterior cingulate cortex (pgACC) and dorsal anterior cingulate cortex (dACC). The levels of the neurotransmitters/metabolites were measured using GABA-edited Mescher–Garwood PRESS for GABA measurements, with the OFF-sequence measurements for total choline (tCho) and Glx (combined glutamate + glutamine). The total choline (tCho) signal in our analysis included glycerophosphocholine (GPC) and phosphocholine (PC), which is consistent with standard practices in MRS studies. This approach ensures a robust estimation of tCho concentrations across participants. The study collected data from 38 participants (17 males and 21 females). The analysis revealed a significant correlation between anxiety ratings before a standardized pain provocation and the rated pain unpleasantness during the pain provocation. tCho correlated negatively with these parameters in pgACC. A linear regression analysis indicated that tCho levels in pgACC have a significant negative association with anxiety and perceived pain when controlling for age, depressive symptoms, and alcohol and tobacco intake. We also found that sex significantly moderates the relationship between pgACC choline levels and pain unpleasantness. The study suggests that levels of choline, an essential precursor of acetylcholine, are associated with anxiety and perceived pain. These levels may influence how Glx and GABA contribute to affective pain experiences by modulating the balance between excitatory and inhibitory signals. However, future research is needed to identify the mechanisms involved. Furthermore, the study indicates that sex is a significant factor in this relationship, with lower choline levels being associated with higher pain ratings in females but not in males. This highlights the significance of addressing sex as a biological factor in pain research to better understand the different responses to treatments and to facilitate the development of more effective interventions in the future.

A key process for successful working memory is to prioritize task-relevant information over distraction, i.e., to control attentional deployment. Here we investigate to what extent attentional control during a delayed match-to-sample task can be achieved when to-be-remembered items were presented unconsciously together with distracting information and with a prestimulus cue that indicated whether the target was likely to appear on the left or right side of the screen. This expectation was sometimes violated (20% of trials), requiring reorienting of attention to successfully solve the task. Moreover, the cue was uninformative of the exact location of the target, which could appear on the top, middle, or bottom part of the screen. Participants performed better than chance on unconscious trials only when the cue correctly indicated target side, suggesting an inability to reorient attention when the cues were invalid. Neural activity (fMRI BOLD signal change) in medial and lateral prefrontal cortex was significant for unconscious valid-cue trials and remained significant for invalid-cue trials only in the lateral prefrontal cortex, although neither region was significantly modulated by cue validity. Parietal regions did not show significant activation for valid or invalid unconscious stimuli. Thus, even though activity in brain regions associated with cognitive control reached significant levels for unconscious stimuli, there was no evidence for adaptive deployment of selective attention based on unconscious information, which was the case for conscious stimuli. The ability to control attentional deployment appears to differ between conscious and unconscious working memory.

Inner speech, or covert speech, refers to the internal generation of language without overt articulation. Decoding inner speech has significant implications for brain-computer interfaces (BCIs), particularly for assistive communication in individuals with speech and motor impairments. To facilitate research in this area, we introduce a publicly available dataset comprising simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data during inner speech production.

Data were collected from three healthy, right-handed participants performing an inner speech task. The task involved silent repetition of visually presented words belonging to either a social or numerical category. The experiment consisted of 40 trials per word, with eight unique words and starts with a fixation period of two seconds. Stimuli were displayed for two seconds at the beginning of each session, followed by a 12-second rest period to allow hemodynamic responses to return to baseline. Participants were instructed to remain still and avoid movements to minimize artifacts. EEG was recorded using a 64-channel MR-compatible cap (BrainCap MR, EasyCap GmbH) at a 5 kHz sampling rate. Electrocardiogram (ECG) signals were simultaneously acquired using an additional electrode placed on the trapezius muscle to facilitate cardioballistic artifact correction. Gradient and cardioballistic artifacts were corrected using BrainVision Analyzer software.

Functional MRI data were acquired using a 3T scanner with a 48-channel headcoil, and an echo-planar imaging (EPI) sequence optimized for whole-brain coverage. The repetition time (TR) was 2 s. High-resolution anatomical T1-weighted images were also acquired for structural reference. The dataset is publicly available in the OpenNeuro repository. The aim of this dataset is to provide a resource for studying inner speech processing, multimodal neuroimaging, EEG-fMRI fusion techniques, and BCI-driven speech prosthesis development.

While the effectiveness of deep brain stimulation in alleviating essential tremor is well-established, the underlying mechanisms of the treatment are unclear. Essential tremor, as characterized by tremor during action, is proposed to be driven by a dysfunction in the cerebello-thalamo-cerebral circuit that is evident not only during motor actions but also during rest. Stimulation effects on resting-state functional connectivity were investigated by functional MRI in 16 essential tremor patients with fully implanted deep brain stimulation in the caudal zona incerta during On-and-Off therapeutic stimulation, in a counterbalanced design. Functional connectivity was calculated between different constellations of sensorimotor as well as non-sensorimotor regions (as derived from seed-based and data-driven approaches), and compared between On and Off stimulation. We found that deep brain stimulation did not modulate resting-state functional connectivity. The lack of modulation by deep brain stimulation during resting-state, in combination with previously demonstrated effects on the cerebello-thalamo-cerebral circuit during motor tasks, suggests an action-dependent modulation of the stimulation in essential tremor.

After resective glioma surgery in the Supplementary Motor Area (SMA), patients often experience a transient disturbance of the ability to initiate speech and voluntary motor actions, known as the SMA syndrome (SMAS). It has been proposed that enhanced interhemispheric functional connectivity (FC) within the sensorimotor system may serve as a potential mechanism for recovery, enabling the non-resected SMA to assume the function of the resected region. The purpose of the present study was to investigate the extent to which changes in FC can be observed in patients after resolution of the SMAS.

Eight patients underwent resection of left SMA due to suspected gliomas, resulting in various levels of the SMA syndrome. Resting-state functional MR images were acquired prior to the surgery and after resolution of the syndrome.

At the group level we found an increased connectivity between the unaffected (right) SMA and the primary motor cortex on the same side following surgery. However, no significant increase in interhemispheric connectivity was observed.

These findings challenge the prevailing notion that increased interhemispheric FC serves as the only mechanism underlying recovery from SMA syndrome and suggest the presence of one or more alternative mechanisms.

Decoding inner speech from the brain via the hybridisation of fMRI and EEG data is explored to investigate the performance benefits over unimodal models. Two different fusion approaches are examined: concatenation of probability vectors from unimodal fMRI and EEG machine learning models, and data fusion with feature engineering. Same-task inner speech data are recorded from four participants, and different processing strategies are compared and contrasted to previously-employed hybridisation efforts. Data across participants are discovered to encode different underlying structures, which correlates to decoding performances between subject-dependent fusion models. For all participants, the performance of inner speech decoding models is shown to improve when pursuing bimodal fMRI-EEG fusion strategies, with an average increase of 6.025% accuracy on an 8-word classification task across two semantic categories.

The recognition of inner speech, which could give a ‘voice’ to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

Essential tremor (ET) is characterized by bilateral upper limb postural and/or kinetic tremor, but also cognitive deficits. Tremor in ET, as well as aspects of cognitive deficits associated with ET, have been suggested to be linked to dysfunction in the cerebello-thalamo-cerebral circuit. In ET patients with disabling and medically intractable motor symptoms, Deep Brain Stimulation (DBS) is effective in reducing tremor. DBS in the caudal Zona incerta (cZi) has been shown to modulate the activity of the sensorimotor cerebello-cerebral circuit during motor tasks. Whether the activity in the cerebello-cerebral circuit is modulated by DBS during tasks involving working memory is unknown. The present study therefore aimed to investigate the possible effects of cZi DBS on working-memory processing in ET patients by means of task-based blood oxygen level-dependent (BOLD) fMRI.

Thirteen ET patients completed a working-memory task during DBS OFF and ON conditions. The task involved three conditions: maintenance, manipulation, and control. Behaviorally, there was no significant effect from DBS on accuracy, but a marginally significant Task x DBS interaction was detected for response times (RTs). However, post hoc comparisons for each condition failed to reach statistical significance. FMRI analyses revealed that DBS did not alter BOLD signal in regions of interest (lateral prefrontal cortex, parietal cortex, and the cerebellum), or in a complementary whole-brain analysis.

The present study indicates that DBS in the cZi in patients with ET has at most marginal effects on working memory, which is consistent with the results of pre- and post-DBS neuropsychological assessment showing minimal cognitive effects of surgery.

Background and objective: We recently reported improvements of working memory across 10 years post stroke among middle-aged individuals. However, the mechanisms underlying working-memory recovery are largely unknown. This study investigated the associations between long-term improvement of working memory and resting-state functional connectivity in two frontoparietal networks: the frontoparietal network and the dorsal attention network.

Methods: Working memory was repeatedly assessed by the Digit Span Backwards task in 21 persons, within 1 year after stroke onset and again 10 years post stroke onset. Brain functional connectivity was examined by resting state functional magnetic resonance imaging at the 10-year follow-up.

Results: A significant improvement of working memory was found among 21 persons after stroke (median age = 64) at the 10-year follow-up compared to the within-one-year assessment. The magnitude of performance improvement on the Digit Span Backwards task was significantly positively correlated with stronger brain connectivity in the frontoparietal network (r = 0.51, p = 0.018) measured at the 10-year follow-up only. A similar association was observed in the dorsal attention network (r = 0.43, p = 0.052) but not in a visual network (r = -0.17, p = 0.46) that served as a control network. The association between functional connectivity within the above-mentioned networks and Digit Span Backwards scores at 10-year after stroke was in the same direction but did not reach significance.

Conclusions: The present work relate stronger long-term performance improvement on the Digit Span Backwards task with higher integrity of frontoparietal network connectivity.