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Abstract We are not only passively immersed in a sensorial world, but we are active agents that directly produce stimulations. Understanding what is unique about sensory consequences can give valuable insight into the action-perception-cycle. Sensory attenuation is the phenomenon that self-produced stimulations are perceived as less intense compared to externally-generated ones. Studying this phenomenon, however, requires considering a plethora of factors that could otherwise interfere with its interpretation, such as differences in stimulus properties, attentional resources, or temporal predictability. We therefore developed a novel Virtual Reality (VR) setup which allows control over several of these confounding factors. Furthermore, we modulated the expectation of receiving a somatosensory stimulation across self-production and passive perception through a simple probabilistic learning task, allowing us to test to what extent the electrophysiological correlates of sensory attenuation are impacted by stimulus expectation. Therefore, the aim of the present study was twofold: first we aimed validating a novel VR paradigm during electroencephalography (EEG) recoding to investigate sensory attenuation in a highly controlled setup; second, we tested whether electrophysiological differences between self- and externally-generated sensations could be better explained by stimulus predictability factors, corroborating the validity of sensory attenuation. Results of 26 participants indicate that early (P100), mid-latency (P200) and later negative contralateral potentials were significantly attenuated by self-generated sensations, independent of the stimulus expectation. Moreover, a component around 200 ms post-stimulus at frontal sites was found to be enhanced for self-produced stimuli. The P300 was influenced by stimulus expectation, regardless of whether the stimulation was actively produced or passively attended. Together, our results demonstrate that VR opens up new possibilities to study sensory attenuation in more ecological valid yet well-controlled paradigms, and that sensory attenuation is not significantly modulated by stimulus predictability, suggesting that sensory attenuation relies on motor-specific predictions about their sensory outcomes. This not only supports the phenomenon of sensory attenuation, but is also consistent with previous research and the concept that action actually plays a crucial role in perception.

Transcranial direct current stimulation (tDCS) has been studied extensively for its potential to enhance human cognitive functions in healthy individuals and to treat cognitive impairment in various clinical populations. However, little is known about how tDCS modulates the neural networks supporting cognition and the complex interplay with mediating factors that may explain the frequently observed variability of stimulation effects within and between studies. Moreover, research in this field has been characterized by substantial methodological variability, frequent lack of rigorous experimental control and small sample sizes, thereby limiting the generalizability of findings and translational potential of tDCS. The present manuscript aims to delineate how these important issues can be addressed within a neuroimaging context, to reveal the neural underpinnings, predictors and mediators of tDCS-induced behavioral modulation. We will focus on functional magnetic resonance imaging (fMRI), because it allows the investigation of tDCS effects with excellent spatial precision and sufficient temporal resolution across the entire brain. Moreover, high resolution structural imaging data can be acquired for precise localization of stimulation effects, verification of electrode positions on the scalp and realistic current modeling based on individual head and brain anatomy. However, the general principles outlined in this review will also be applicable to other imaging modalities. Following an introduction to the overall state-of-the-art in this field, we will discuss in more detail the underlying causes of variability in previous tDCS studies. Moreover, we will elaborate on design considerations for tDCS-fMRI studies, optimization of tDCS and imaging protocols and how to assure high-level experimental control. Two additional sections address the pressing need for more systematic investigation of tDCS effects across the healthy human lifespan and implications for tDCS studies in age-associated disease, and potential benefits of establishing large-scale, multidisciplinary consortia for more coordinated tDCS research in the future. We hope that this review will contribute to more coordinated, methodologically sound, transparent and reproducible research in this field. Ultimately, our aim is to facilitate a better understanding of the underlying mechanisms by which tDCS modulates human cognitive functions and more effective and individually tailored translational and clinical applications of this technique in the future.

Abstract Sequential decision problems distill important challenges frequently faced by humans. Through repeated interactions with an uncertain world, unknown statistics need to be learned while balancing exploration and exploitation. Reinforcement learning is a prominent method for modeling such behaviour, with a prevalent application being the two-step task. However, recent studies indicate that the standard reinforcement learning model sometimes describes features of human task behaviour inaccurately and incompletely. We investigated whether active inference, a framework proposing a trade-off to the exploration-exploitation dilemma, could better describe human behaviour. Therefore, we re-analysed four publicly available datasets of the two-step task, performed Bayesian model selection, and compared behavioural model predictions. Two datasets, which revealed more model-based inference and behaviour indicative of directed exploration, were better described by active inference, while the models scored similarly for the remaining datasets. Learning using probability distributions appears to contribute to the improved model fits. Further, approximately half of all participants showed sensitivity to information gain as formulated under active inference, although behavioural exploration effects were not fully captured. These results contribute to the empirical validation of active inference as a model of human behaviour and the study of alternative models for the influential two-step task.

Abstract 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 the self-attribution of (artificial) body parts is altered if these body parts are somehow threatened. 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.

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. Indications of Bayesian surprise encoding, reflecting model updating, are found in primary somatosensory cortex from around 140ms. This dissociation is compatible with the idea 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 underlying mechanisms.

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 stimulus order and selection of manual movements. It remains largely unknown how vibrotactile choices are represented when they are decoupled from these 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 order and selection of the manual decision reports. We identified the left contralateral dorsal premotor cortex (PMd) and intraparietal sulcus (IPS) as carrying information about vibrotactile choices. Our finding provides empirical evidence for an involvement of the PMd and IPS in vibrotactile decisions that goes above and beyond the coding of stimulus order and specific action selection. Considering 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. Moreover, this finding replicates results from our previous work using an oculomotor variant of the task, with the important difference that the informative premotor cluster identified in the previous work was centered in the bilateral frontal eye fields rather than in the PMd. Evidence from these two studies indicates that categorical choices in human vibrotactile comparisons are represented in a response modality-dependent manner.

Working memory (WM) representations are generally known to be influenced by task demands, but it is not clear whether this extends to the somatosensory domain. One way to investigate the influence of task demands is with categorization paradigms, wherein either a single stimulus or an associated category is maintained in WM. In the somatosensory modality, category representations have been identified in the premotor cortex (PMC) and the intraparietal sulcus (IPS). In this study we used multivariate-pattern-analysis with human fMRI data to investigate whether the WM representations in the PMC, IPS or other regions are influenced by changing task demands. We ensured the task-dependent, categorical WM information was decorrelated from stimulus features by (1) teaching participants arbitrary, non-rule based stimulus groupings and (2) contrasting identical pairs of stimuli across experimental conditions, where either a single stimulus or the associated group was maintained in WM. Importantly, we also decoupled the decision and motor output from the WM representations. With these experimental manipulations, we were able to pinpoint stimulus-specific WM information to the left frontal and parietal cortices and context-dependent, group-specific WM information to the left IPS. By showing that grouped stimuli are represented more similarly in the Group condition than in the Stimulus condition, free from stimulus and motor output confounds, we provide novel evidence for the adaptive nature of somatosensory WM representations in the IPS with changing task-demands.

Maladaptive risk taking can have severe individual and societal consequences; thus, individual differences are prominent targets for intervention and prevention. Although brain activation has been shown to be associated with individual differences in risk taking, the directionality of the reported brain–behavior associations is less clear. Here, we argue that one aspect contributing to the mixed results is the low convergence between risk-taking measures, especially between the behavioral tasks used to elicit neural functional markers. To address this question, we analyzed within-participant neuroimaging data for two widely used risk-taking tasks collected from the imaging subsample of the Basel–Berlin Risk Study (N = 116 young human adults). Focusing on core brain regions implicated in risk taking (nucleus accumbens, anterior insula, and anterior cingulate cortex), for the two tasks, we examined group-level activation for risky versus safe choices, as well as associations between local functional markers and various risk-related outcomes, including psychometrically derived risk preference factors. While we observed common group-level activation in the two tasks (notably increased nucleus accumbens activation), individual differences analyses support the idea that the presence and directionality of associations between brain activation and risk taking varies as a function of the risk-taking measures used to capture individual differences. Our results have methodological implications for the use of brain markers for intervention or prevention.

Research on somatosensory awareness has yielded highly diverse findings with putative neural correlates ranging from activity within somatosensory cortex to activation of widely distributed frontoparietal networks. Divergent results from previous studies may reside in cognitive processes that often coincide with stimulus awareness in experimental settings. To scrutinise the specific relevance of regions implied in the target detection network, we used functional magnetic resonance imaging (n = 27) on a novel somatosensory detection task that explicitly controls for stimulus uncertainty, behavioural relevance, overt reports, and motor responses. Using Bayesian Model Selection, we show that responses reflecting target detection are restricted to secondary somatosensory cortex, whereas activity in insular, cingulate, and motor regions is best explained in terms of stimulus uncertainty and overt reports. Our results emphasise the role of sensory-specific cortex for the emergence of perceptual awareness and dissect the contribution of the frontoparietal network to classical detection tasks.

To what degree mental imagery (MI) bears on the same neuronal processes as perception has been a central question in the neurophysiological study of imagery. Sensory-recruitment models suggest that imagery of sensory material heavily relies on the involvement of sensory cortices. Empirical evidence mainly stems from the study of visual imagery and suggests that it depends on the mentally imagined material whether hierarchically lower regions are recruited. However, evidence from other modalities is necessary to infer generalized principles. In this fMRI study we used the somatotopic organization of the primary somatosensory cortex (SI) to test in how far MI of tactile sensations activates topographically sensory brain areas. Participants (N = 19) either perceived or imagined vibrotactile stimuli on their left or right thumbs or big toes. The direct comparison to a corresponding perception condition revealed that SI was somatotopically recruited during imagery. While stimulus driven bottom-up processing induced activity throughout all SI subareas, i.e., BA1, BA3a, BA3b, and BA2 defined by probabilistic cytoarchitectonic maps, top-down recruitment during imagery was limited to the hierarchically highest subarea BA2.

Spatially and temporally congruent visuotactile stimulation of a fake hand together with one’s real hand may result in an illusory self-attribution of the fake hand. Although this illusion relies on a representation of the two touched body parts in external space, there is tentative evidence that, for the illusion to occur, the seen and felt touches also need to be congruent in an anatomical reference frame. We used functional magnetic resonance imaging and a somatotopical, virtual reality-based setup to isolate the neuronal basis of such a comparison. Participants’ index or little finger was synchronously touched with the index or little finger of a virtual hand, under congruent or incongruent orientations of the real and virtual hands. The left ventral premotor cortex responded significantly more strongly to visuotactile co-stimulation of the same versus different fingers of the virtual and real hand. Conversely, the left anterior intraparietal sulcus responded significantly more strongly to co-stimulation of different versus same fingers. Both responses were independent of hand orientation congruence and of spatial congruence of the visuotactile stimuli. Our results suggest that fronto-parietal areas previously associated with multisensory processing within peripersonal space and with tactile remapping evaluate the congruence of visuotactile stimulation on the body according to an anatomical reference frame.

Schizophrenia is associated with a number of cognitive impairments such as deficient sensory encoding or working memory processing. However, it is largely unclear how dysfunctions on these various levels of cortical processing contribute to alterations of stimulus-specific information representation. To test this, we used a well-established sequential frequency comparison paradigm, in which sensory encoding of vibrotactile stimuli can be assessed via frequency-specific steady-state evoked potentials (SSEPs) over primary somatosensory cortex (S1). Further, we investigated the maintenance of frequency information in working memory (WM) in terms of parametric power modulations of induced beta-band EEG oscillations. In the present study schizophrenic patients showed significantly less pronounced SSEPs during vibrotactile stimulation than healthy controls. In particular, inter-trial phase coherence was reduced. While maintaining vibrotactile frequencies in WM, patients showed a significantly weaker prefrontal beta-power modulation compared to healthy controls. Crucially, patients exhibited no general disturbances in attention, as inferred from a behavioral test and from alpha-band event-related synchronization. Together, our results provide novel evidence that patients with schizophrenia show altered neural correlates of stimulus-specific sensory encoding and WM maintenance, suggesting an early somatosensory impairment as well as alterations in the formation of abstract representations of task-relevant stimulus information.

Ample evidence suggests that oscillations in the beta band represent quantitative information about somatosensory features during stimulus retention. Visual and auditory working memory (WM) research, on the other hand, has indicated a predominant role of gamma oscillations for active WM processing. Here we reconciled these findings by recording whole-head magnetoencephalography during a vibrotactile frequency comparison task. A Braille stimulator presented healthy subjects with a vibration to the left fingertip that was retained in WM for comparison with a second stimulus presented after a short delay. During this retention interval spectral power in the beta band from the right intraparietal sulcus and inferior frontal gyrus (IFG) monotonically increased with the to-be-remembered vibrotactile frequency. In contrast, induced gamma power showed the inverse of this pattern and decreased with higher stimulus frequency in the right IFG. Together, these results expand the previously established role of beta oscillations for somatosensory WM to the gamma band and give further evidence that quantitative information may be processed in a fronto-parietal network.

Processing of motion and pattern has been extensively studied in the visual domain, but much less in the somatosensory system. Here, we used ultra-high-field functional magnetic resonance imaging (fMRI) at 7 Tesla to investigate the neuronal correlates of tactile motion and pattern processing in humans under tightly controlled stimulation conditions. Different types of dynamic stimuli created the sensation of moving or stationary bar patterns during passive touch. Activity in somatosensory cortex was increased during both motion and pattern processing and modulated by motion directionality in primary and secondary somatosensory cortices (SI and SII) as well as by pattern orientation in the anterior intraparietal sulcus. Furthermore, tactile motion and pattern processing induced activity in the middle temporal cortex (hMT+/V5) and in the inferior parietal cortex (IPC), involving parts of the supramarginal und angular gyri. These responses covaried with subjects' individual perceptual performance, suggesting that hMT+/V5 and IPC contribute to conscious perception of specific tactile stimulus features. In addition, an analysis of effective connectivity using psychophysiological interactions (PPI) revealed increased functional coupling between SI and hMT+/V5 during motion processing, as well as between SI and IPC during pattern processing. This connectivity pattern provides evidence for the direct engagement of these specialized cortical areas in tactile processing during somesthesis.

UNLABELLED:Reward-related dopaminergic influences on learning and overt behaviour are well established, but any influence on sensory decision-making is largely unknown. We used functional magnetic resonance imaging (fMRI) while participants judged electric somatosensory stimuli on one hand or other, before being rewarded for correct performance at trial end via a visual signal, at one of four anticipated financial levels. Prior to the procedure, participants received either placebo (saline), a dopamine agonist (levodopa), or an antagonist (haloperidol). PRINCIPAL FINDINGS:higher anticipated reward improved tactile decisions. Visually signalled reward reactivated primary somatosensory cortex for the judged hand, more strongly for higher reward. After receiving a higher reward on one trial, somatosensory activations and decisions were enhanced on the next trial. These behavioural and neural effects were all enhanced by levodopa and attenuated by haloperidol, indicating dopaminergic dependency. Dopaminergic reward-related influences extend even to early somatosensory cortex and sensory decision-making.

We used functional magnetic resonance imaging (fMRI) to study neural correlates of a robust somatosensory illusion that can dissociate tactile perception from physical stimulation. Repeated rapid stimulation at the wrist, then near the elbow, can create the illusion of touches at intervening locations along the arm, as if a rabbit hopped along it. We examined brain activity in humans using fMRI, with improved spatial resolution, during this version of the classic cutaneous rabbit illusion. As compared with control stimulation at the same skin sites (but in a different order that did not induce the illusion), illusory sequences activated contralateral primary somatosensory cortex, at a somatotopic location corresponding to the filled-in illusory perception on the forearm. Moreover, the amplitude of this somatosensory activation was comparable to that for veridical stimulation including the intervening position on the arm. The illusion additionally activated areas of premotor and prefrontal cortex. These results provide direct evidence that illusory somatosensory percepts can affect primary somatosensory cortex in a manner that corresponds somatotopically to the illusory percept.