Timo Torsten Schmidt

Motor planning entails a progressive transformation of neural representations ‐ from abstract motor goals, which represent intended action‐outcomes independent of any particular effector (i.e., the body part executing the action), to effector‐specific movement plans. Functional MRI (fMRI) studies have shown that parametric variations in parietal activity patterns reflect the encoding of intended force‐intensities in effector‐specific regions, even before detailed movement parameters are specified. However, how these intended force‐intensities are initially represented in an abstract, effector‐independent format and subsequently transformed into effector‐ and movement‐specific plans remains unclear. To address this, human‐participants performed a delayed grip‐force task during fMRI. They first prepared two of four possible force‐intensities, then received a cue indicating which hand should apply which force, and finally executed both grips simultaneously. Using time‐resolved support vector regression (SVR) combined with a searchlight approach, we identified brain‐regions that parametrically code grip‐force intensities across two 6‐s delay periods. During the first delay, above‐chance decoding was observed in a medial section of the posterior parietal cortex spanning the precuneus and superior parietal lobule (PCu/SPL), whereas during the second delay it emerged in effector‐specific regions, including the contralateral intraparietal sulcus (pIPS/aIPS), primary somatosensory cortex (S1), dorsal premotor cortex (PMd), and supplementary motor area (SMA). Cross‐decoding confirmed effector‐independent coding in the PCu/SPL, while cross‐temporal generalization revealed stable representations in the contralateral IPS and PMd from the second delay through execution. Together, these findings indicate a progressive transformation from abstract representations of intended force‐intensity in the PCu/SPL to effector‐ and movement‐specific plans in the IPS and PMd.

The neural substrates of tactile long-term memory (LTM) in humans remain poorly understood, as relatively few neuroimaging studies have addressed this question. Here, we asked whether retrieval of tactile stimulation engages modality-specific representations in the primary and secondary somatosensory cortices (S1 and S2), alongside domain-general retrieval networks. Participants learned 16 tactile trajectories, each presented for 1.2 s on the left thumb through sequential activation of 10 vibrating dots on a Braille-like display. Three learning sessions within one week were followed by a recognition test during functional magnetic resonance imaging (fMRI). In the final sample (n = 26), we contrasted BOLD responses during successful recognition of learned stimuli with those during correct rejection of novel stimuli. Successful recognition was associated with increased activity in contralateral S1 and S2, alongside activation in the hippocampus as well as frontal and parietal regions implicated in memory retrieval. A psychophysiological interaction analysis (PPI) further revealed increased task-dependent connectivity between the hippocampus and contralateral S1 and S2 during successful recognition. Together, these findings suggest that tactile long-term memory retrieval relies on coordinated hippocampal-somatosensory interactions and may engage long-term memory representations in somatosensory cortex.

Background: Spatial working memory (WM) relies on posterior parietal cortex (PPC) within a distributed fronto-parietal network, yet whether online anodal transcranial direct current stimulation (tDCS) of PPC modulates tactile WM, and how behavioral effects unfold over time, remains unclear. Objective: We tested whether online anodal tDCS over left PPC modulates performance in a tactospatial WM task and whether stimulation effects vary over time and as a function of baseline performance. Methods: In a double-blind, sham-controlled, within-subject crossover design, 32 healthy adults completed two counterbalanced sessions (Active, Sham). Each session comprised baseline, stimulation, and post-stimulation phases while participants performed a retro-cued delayed match-to-sample task with vibrotactile patterns delivered to the left index finger. During the stimulation phase, participants received either 2 mA anodal or sham tDCS over left PPC for 15 min, depending on session. Behavioral accuracy was analyzed using a sliding-window approach combined with cluster-based permutation testing. Results: Active stimulation induced a significant, gradual improvement in WM accuracy relative to sham, emerging approximately eight minutes after stimulation onset and corresponding to a ∼5% performance increase (Hedges’ g = 0.43). Stimulation effects were baseline-dependent, with individuals showing lower initial WM performance exhibiting larger behavioral gains, whereas high performers showed minimal benefits. Conclusions: These findings show that online anodal stimulation of left PPC can modulate tactile WM performance in a time- and baseline-dependent manner. More broadly, the results suggest that behavioral effects of parietal tDCS emerge gradually during ongoing stimulation and depend on initial cognitive state. Highlights: Online anodal PPC-tDCS enhances tactile working memory Behavioral gains emerge after ∼8 min of stimulation Active stimulation improves accuracy by ∼5% versus sham Lower baseline performers show larger stimulation benefits Sliding-window analyses capture dynamic online tDCS effects

Motor planning entails a progressive transformation of neural representations - from abstract motor goals, which represent intended action-outcomes independent of any particular effector (i.e., the body part executing the action), to effector-specific movement plans. Functional MRI (fMRI) studies have shown that parametric variations in parietal activity patterns reflect the encoding of intended force intensities in effector-specific regions, even before detailed movement parameters are specified. However, how these intended force intensities are initially represented in an abstract, effector-independent format and subsequently transformed into effector- and movement-specific plans remains unclear. To address this, human participants performed a delayed grip-force task during fMRI. They first prepared two of four possible force intensities, then received a cue indicating which hand should apply which force, and finally executed both grips simultaneously. Using time-resolved support vector regression (SVR) combined with a searchlight approach, we identified brain regions that parametrically code grip-force intensities across two 6-second delay periods. During the first delay, above-chance decoding was observed in the precuneus (PCu), whereas during the second delay it emerged in effector-specific regions, including the contralateral intraparietal sulcus (pIPS/aIPS), primary somatosensory cortex (S1), dorsal premotor cortex (PMd), and supplementary motor area (SMA). Cross-decoding confirmed effector-independent coding in the PCu, while cross-temporal generalization revealed stable representations in the contralateral IPS and PMd from the second delay through execution. Together, these findings indicate a progressive transformation from abstract representations of intended force intensity in the PCu to effector- and movement-specific plans in the IPS and PMd.

The Open Data initiative Altered States Database (ASDB) collects psychometric questionnaire data on the subjective experiences of pharmacologically and non-pharmacologically induced altered states of consciousness. The ASDB is updated annually and can be utilized by both researchers and non-scientists to access information or conduct further analyses. The current update adds data published in the year 2025, sourced from a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. A total of 578 items were screened, resulting in 32 included journal articles, of which nineteen report on the Mystical Experience Questionnaire (MEQ30), eighteen on the 11-Altered States of Consciousness Rating Scale (11-ASC), fourteen on the 5D-ASC, two on the Phenomenology of Consciousness Inventory (PCI), and one on the Hallucinogen Rating Scale (HRS). In total, the ASDB now encompasses data from 36 pharmacological and 18 non‑pharmacological consciousness modifying techniques (CMT) (plus control substances/techniques), incorporating 289 journal articles and 836 single datasets from 29.287 participants across datasets. The ASDB can be accessed on https://asdb.info and data tables can be downloaded from Open Science Framework (OSF; https://osf.io/8mbru).

Planning motor‐actions involves the neuronal representation of key parameters such as force and timing prior to execution. Functional magnetic resonance imaging (fMRI) studies have shown that activity in premotor and parietal areas covaries with these parameters during motor‐preparation. While previous research has demonstrated that parametric codes reflect graded grip‐force intensities before and after their transformation into motor‐codes, it remains unclear whether these representations are encoded in effector‐specific brain‐regions. To address this, we conducted an fMRI‐study using a delayed grip‐force task in which participants prepared one of four force‐intensities with either their right or left cued‐hand, with the hand to‐be‐used being switched in 50% of the trials midway through the delay. Using time‐resolved multivoxel pattern analysis (MVPA) with a searchlight approach, we identified brain‐regions encoding anticipated grip‐force intensities of the cued‐hand across the two 6‐s delay‐periods. In addition, cross‐decoding analyses tested whether force‐intensities were represented in an effector‐specific or effector‐independent format. We found above‐chance decoding in two lateralized networks: the contralateral intraparietal sulcus (r−/l‐IPS), as well as the lateral occipitotemporal cortex (r−/l‐LOTC) during the first, and the contralateral primary motor cortices (r−/l‐M1) during the second delay. These results indicate effector‐specific coding of anticipated grip‐force intensities, which is revealed by systematic lateralization of decoding‐accuracy depending on the hand to‐be‐used. Cross‐decoding corroborated effector‐specific representation in these regions. Together, our results show that contralateral IPS and LOTCs encode effector‐specific parametric information prior to M1s, likely reflecting a transformation process in which the intended grip‐force intensity is selected, maintained, and then converted into detailed movement‐plans.

Stroboscopic light stimulation (SLS) on closed eyes reliably evokes vivid geometric visual phenomena, and in some contexts, altered-state experiences, leading to its increasing use across research, public installations, recreational use, and exploratory clinical contexts. The main clinical risk for SLS is a photosensitive epileptic response. In contrast, non-epileptic sensitivities (e.g., migraine/photophobia, anxiety, autism/ADHD, psychosis) typically induce discomfort or distress rather than convulsive events. Here, we integrate a multi-laboratory safety survey of 1,070 participants, operational data from two commercial SLS providers, and a focused review of SLS and sensory-intolerance evidence. This synthesis was used to refine safety screening and to characterise adverse events. Across laboratory studies, 20 minor side effects (e.g., early withdrawal due to discomfort; ∼18.7 per 1,000) were reported, with no severe incidents requiring medical attention. From two commercial datasets (∼4.2 million closed-eye SLS sessions), 14 major adverse events requiring medical attention were documented (∼3.3 per million); minor reactions were not systematically captured. Synthesising these strands, we developed the evidence-based Sussex Strobe Safety Screening Questionnaire (4SQ), which uses non-specialist language to identify known sensitivities to SLS, alongside practical recommendations for risk mitigation across research, clinical, commercial, and public contexts. Together, these findings suggest that the absolute risk under SLS is low but non-zero. Screening tools can help exclude pre-existing conditions, while graded exposure (e.g., a short ’taster’ session, after which participants may opt out) and trained staff can mitigate the risk of first-episode events. Nonetheless, such events should be anticipated and minimised through clear screening pathways and managed through rehearsed on-site response plans.

Neuroscientific research has shown that perceptual decision-making occurs in brain regions that are associated with the required motor response. Recent functional magnetic resonance imaging (fMRI) studies that dissociated decisions from coinciding processes, such as the motor response, partly challenge this, indicating that perceptual decisions are represented in an abstract or sensory-specific manner that might vary across sensory modalities. However, comparisons across sensory modalities have been difficult since most task designs differ not only in modality but also in effectors, motor response, and level of abstraction. Here, we describe an fMRI experiment where participants compared frequencies of two sequentially presented visual flicker stimuli in a delayed match-to-comparison task, which controlled for motor responses and stimulus sequence. A whole-brain searchlight support vector machine analysis of multi voxel patterns was used to identify brain regions containing information on perceptual decisions. Furthermore, a conjunction analysis with data from an analogue vibrotactile study was conducted for a comparison between visual and tactile decision-making processes. Both analyses revealed above-chance decoding accuracies in the left dorsal premotor cortex (PMd) as well as in the left intraparietal sulcus (IPS). While previous primate and human imaging research have implicated these regions in transforming sensory information into action, our findings indicate that the IPS processes abstract decision signals while the PMd represents an effector-dependent, but motor response independent encoding of perceptual decisions that is similar across sensory domains.