Biology subjects

Blankenburg, F.

Publications and source records attributed to Blankenburg, F..

13 recordsLinked to original sources

bioRxiv2026

Remembering touch: Somatosensory cortex supports long-term memory for dynamic vibrotactile patterns.

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.

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bioRxiv2026

Time- and performance-dependent enhancement of tactospatial working memory caused by online anodal tDCS of the posterior parietal cortex

BackgroundSpatial 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. ObjectiveWe 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. MethodsIn 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. ResultsActive 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. ConclusionsThese 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. HighlightsO_LIOnline anodal PPC-tDCS enhances tactile working memory C_LIO_LIBehavioral gains emerge after [~]8 min of stimulation C_LIO_LIActive stimulation improves accuracy by [~]5% versus sham C_LIO_LILower baseline performers show larger stimulation benefits C_LIO_LISliding-window analyses capture dynamic online tDCS effects C_LI

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bioRxiv2026

Decoding Graded Grip-Force Intensity from fMRI Data Reveals a Transformation from Abstract to Effector- and Movement-Specific Codes prior to Execution

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.

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bioRxiv2026

Harmonizing the stimulation dose of focal tDCS across target sites

Non-invasive brain stimulation is an established tool for modulating neural activity that holds promise for advancing both cognitive neuroscience and clinical interventions. Focal transcranial direct current stimulation (tDCS), using center-surround electrode montages, enables more region-specific targeting. Although computational models can simulate individual electric fields, no existing approach enables the prospective individualization of electrode placement while standardizing the dose across targeted brain regions. In the current preparatory methodological study, we present a modeling-based framework that harmonizes the electric field strength between different target regions at the group level, but preserves inter-individual variability. This enables systematic examination of dose-response relationships and their regional differences. Positioning of the center-surround electrode montages is individualized to ensure focusing of the electric field on the target regions. We started by defining brain targets for eight cognitive and motor functions using MRI data from 43 participants. Using field simulations, we then estimated a group-average field strength in the target regions that had led to behavioral and physiological effects in prior tDCS studies (resulting in 0.2 V/m). The radii of the center-surround montages were optimized for each target region to achieve the intended field strength while maximizing focality. Validation in an independent sample (n=53) confirmed that the intended target field strength is achieved on average for new participants. The described computational tools are made available as open-source software, allowing other researchers to apply our individualization framework with parameters (target regions and target field strengths) tailored to their specific research questions; and are currently being implemented in a multi-center study involving approximately 1,000 datasets.

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bioRxiv2025

The P50 predicts conscious perception under tactile but not electrical somatosensory stimulation in human EEG

Past research has not reached consensus about the neural correlates of conscious somatosensory perception. Different studies have identified ERP components at various latencies as predictors of somatosensory detection, but it is still largely unclear which factors are responsible for this variation. Here, for the first time we directly compare the event-related potential correlates of stimulus detection under tactile versus electrical peri-threshold stimulation in a between-groups design, while controlling for task-relevance and post-perceptual processes with a visual-somatosensory matching task. We show that the P50 component predicts conscious perception under tactile, but not electrical stimulation: while electrical stimulation evokes a P50 already for subliminal stimuli, there is no subliminal P50 for tactile stimulation. In contrast, the P100 and N140 components robustly predict conscious detection in both stimulation groups. Tactile stimulation produced a clearly separable N80 component for detected stimuli, that appeared as part of the N140 under electrical stimulation. The P300 predicted conscious detection even though we controlled for post-perceptual processes, suggesting that it partly reflects aspects of subjective experience. Our results demonstrate that the neural correlates of somatosensory detection depend on the type of stimulation used, limiting the scope of previous results achieved using electrical stimulation.

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bioRxiv2024

Decoding Parametric Grip-Force Anticipation from fMRI-Data

Previous functional magnetic resonance imaging (fMRI) studies have shown that activity in premotor and parietal brain-regions covaries with the intensity of upcoming grip-force. However, it remains unclear how information about the intended grip-force intensity is initially represented and subsequently transformed into a motor code before motor-execution. In this fMRI study, we used multivoxel pattern analysis (MVPA) to decode where and when information about grip-force intensities is parametrically coded in the brain. Human participants performed a delayed grip-force task in which one of four cued levels of grip-force intensity had to be maintained in working memory (WM) during a 9-second delay-period preceding motor execution. Using time-resolved MVPA, with a searchlight approach and support vector regression (SVR), we tested which brain regions exhibit multivariate WM codes of anticipated grip-force intensities. During an early delay-period, we observed above-chance decoding in the ventromedial prefrontal cortex (vmPFC). During a late delay-period, we found a network of action-specific brain regions, including the bilateral intraparietal sulcus (IPS), left dorsal premotor cortex (l-PMd) and supplementary motor areas (SMA). Additionally, cross-regression decoding was employed to test for temporal generalization of activation patterns between early and late delay-periods with those during cue presentation and motor execution. Cross-regression decoding indicated temporal generalization to the cue-period in the vmPFC, and to motor-execution in the l-IPS and l-PMd. Together, these findings suggest that the WM representation of grip-force intensities undergoes a transformation where the vmPFC encodes information about the intended grip-force, which is subsequently converted into a motor code in the l-IPS and l-PMd before execution.

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bioRxiv2024

Effector-Specific Neural Representations of Perceptual Decisions Independent of Motor Actions and Sensory Modalities

Neuroscientific research has shown that perceptual decision-making occurs in effector-specific 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 motor actions partly challenge this, indicating abstract representations that might vary across stimulus modalities. However, cross-modal comparisons 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 actions and stimulus sequence. Using Bayesian modelling, we estimated subjective frequency differences based on the time order effect. These values were applied in support vector regression analysis of a multi-voxel pattern whole-brain searchlight approach to identify brain regions containing information on subjective decision values. Furthermore, a conjunction analysis with data from a re-analyzed analogue vibrotactile study was conducted for a cross-modal comparison. Both analyses revealed significant activation patterns in the left dorsal (PMd) and ventral (PMv) premotor cortex as well as in the bilateral 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 PMd and PMv represent an effector-specific, but motor response independent encoding of perceptual decisions that persists across sensory domains.

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bioRxiv2022

EEG mismatch responses in a multi-modal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation and vision.

The human brain is constantly subjected to a multi-modal stream of probabilistic sensory inputs. EEG signatures, such as the mismatch negativity (MMN) and the P3, can give valuable insight into neuronal probabilistic inference. Although reported for different modalities, mismatch responses have largely been studied in isolation, with a strong focus on the auditory MMN. To investigate the extent to which early and late mismatch responses across modalities represent comparable signatures of uni- and cross-modal probabilistic inference in the hierarchically structured cortex, we recorded EEG from 32 participants undergoing a novel tri-modal roving stimulus paradigm. The employed sequences consisted of high and low intensity stimuli in the auditory, somatosensory and visual modalities and were governed by uni-modal transition probabilities and cross-modal conditional dependencies. We found modality specific signatures of MMN ([~]100-200ms) in all three modalities, which were source localized to the respective sensory cortices and shared right lateralized pre-frontal sources. Additionally, we identified a cross-modal signature of mismatch processing in the P3a time range ([~]300-350ms), for which a common network with frontal dominance was found. Across modalities, the mismatch responses showed highly comparable parametric effects of stimulus train length, which were driven by standard and deviant response modulations in opposite directions. Strikingly, the P3a responses across modalities were increased for mispredicted compared to predicted and unpredictable stimuli, suggesting sensitivity to cross-modal predictive information. Finally, model comparisons indicated that the observed single trial dynamics were best captured by Bayesian learning models tracking uni-modal stimulus transitions as well as cross-modal conditional dependencies.

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bioRxiv2021

Differences in working memory coding of biological motion attributed to oneself and others

The question how the brain distinguishes between information about oneself and the rest of the world is of fundamental interest to both philosophy and neuroscience. This question can be approached empirically by investigating how associating stimuli with oneself leads to differences in neurocognitive processing. However, little is known about the brain network involved in forming such self-associations for, specifically, bodily stimuli. In this fMRI study, we sought to distinguish the neural substrates of representing a full-body movement as ones movement and as someone elses movement. Participants performed a delayed match-to-sample working memory task where a retained full-body movement (displayed using point-light walkers) was arbitrarily labelled as ones own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self-association was coded. Movement specific activation patterns was found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain-general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self-associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

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bioRxiv2021

Enhanced processing of aversive stimuli on embodied artificial limbs by the human amygdala

Body perception has been extensively investigated, with one particular focus being the integration of vision and touch within a neuronal body representation. Previous studies have implicated a distributed network comprising the extrastriate body area (EBA), posterior parietal cortex (PPC) and ventral premotor cortex (PMv) during illusory self-attribution of a rubber hand. Here, we set up an fMRI paradigm in virtual reality (VR) to study whether and how threatening (artificial) body parts affects their self-attribution. Participants (N=30) saw a spider (aversive stimulus) or a toy-car (neutral stimulus) moving along a 3D-rendered virtual forearm positioned like their real forearm, while tactile stimulation was applied on the real arm in the same (congruent) or opposite (incongruent) direction. We found that the PPC was more activated during congruent stimulation; higher visual areas and the anterior insula (aIns) showed increased activation during aversive stimulus presentation; and the amygdala was more strongly activated for aversive stimuli when there was stronger multisensory integration of body-related information (interaction of aversiveness and congruency). Together, these findings suggest an enhanced processing of aversive stimuli within the amygdala when they represent a bodily threat.

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bioRxiv2020

Late cortical potentials are not a reliable marker of somatosensory awareness

Two types of scalp-recorded event-related potentials have been proposed as neural correlates of perceptual awareness in humans: an early, modality-specific negativity and a late, modality-independent positivity. However, whether these potentials genuinely reflect perception or result from task demands remains controversial. To address this question, we compared results from a classical somatosensory detection task (direct report task) to a somatosensory-visual matching task, in which overt reports were decorrelated from target detection, equated the behavioural relevance of detected and undetected stimuli, and mitigated the influence of attentional processes. By means of Bayesian model selection, we show that the early N140 component was the first to reflect target detection in both tasks, whereas the late P300 component was task dependent, with strong detection effects in the direct report task that were absent in the matching task. We conclude that the P300 is not a genuine correlate of somatosensory awareness but reflects postperceptual processing.

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bioRxiv2020

Neural surprise in somatosensory Bayesian learning

Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Primary somatosensory cortex is found to encode Bayesian surprise, reflecting model updating, from around 140ms. As such, this dissociation indicates that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its precise mechanisms. Author summaryOur environment features statistical regularities, such as a drop of rain predicting imminent rainfall. Despite the importance for behavior and survival, much remains unknown about how these dependencies are learned, particularly for somatosensation. As surprise signalling about novel observations indicates a mismatch between ones beliefs and the world, it has been hypothesized that surprise computation plays an important role in perceptual learning. By analyzing EEG data from human participants receiving sequences of tactile stimulation, we compare different formulations of surprise and investigate the employed underlying learning model. Our results indicate that the brain estimates transitions between observations. Furthermore, we identified different signatures of surprise computation and thereby provide a dissociation of the neural correlates of belief inadequacy and belief updating. Specifically, early surprise responses from around 70ms were found to signal the need for changes to the model, with encoding of its subsequent updating occurring from around 140ms. These results provide insights into how somatosensory surprise signals may contribute to the learning of environmental statistics.

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bioRxiv2019

Response modality-dependent abstract choice representations for vibrotactile comparisons

Previous electrophysiological studies in monkeys and humans suggest that premotor regions are the primary loci for the encoding of perceptual choices during vibrotactile comparisons. However, these studies employed paradigms wherein choices were inextricably linked with the physical properties of the stimuli and action selection. It raises the question what brain regions represent choices at a more abstract level, independent of the sensorimotor components of the task. To address this question, we used fMRI-MVPA and a variant of the vibrotactile frequency discrimination task which enabled the isolation of choice-related signals from those related to stimulus properties and selection of the manual decision reports. We identified the left, contralateral dorsal premotor cortex (PMd) and intraparietal sulcus (IPS) as carrying information about abstract choices. Notably, our previous work using an oculomotor variant of the task also reported abstract choice representation in intraparietal and premotor regions. However, the informative premotor cluster was centered in the frontal eye fields rather than in the PMd, providing empirical support for a response effector-dependent organization of abstract choice representation in the context of vibrotactile comparisons. Considering our results together with findings from recent studies in animals, we speculate that the premotor region likely serves as a temporary storage site for information necessary for the specification of concrete manual movements, while the IPS might be more directly involved in the computation of choice.

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