Minimal self-models and the free energy principle

The term “minimal phenomenal selfhood” (MPS) describes the basic, pre-reflective experience of being a self (Blanke and Metzinger, 2009). Theoretical accounts of the minimal self have long recognized the importance and the ambivalence of the body as both part of the physical world, and the enabling condition for being in this world (Gallagher, 2005a; Grafton, 2009). A recent account of MPS (Metzinger, 2004a) centers on the consideration that minimal selfhood emerges as the result of basic self-modeling mechanisms, thereby being founded on pre-reflective bodily processes. The free energy principle (FEP; Friston, 2010) is a novel unified theory of cortical function built upon the imperative that self-organizing systems entail hierarchical generative models of the causes of their sensory input, which are optimized by minimizing free energy as an approximation of the log-likelihood of the model. The implementation of the FEP via predictive coding mechanisms and in particular the active inference principle emphasizes the role of embodiment for predictive self-modeling, which has been appreciated in recent publications. In this review, we provide an overview of these conceptions and illustrate thereby the potential power of the FEP in explaining the mechanisms underlying minimal selfhood and its key constituents, multisensory integration, interoception, agency, perspective, and the experience of mineness. We conclude that the conceptualization of MPS can be well mapped onto a hierarchical generative model furnished by the FEP and may constitute the basis for higher-level, cognitive forms of self-referral, as well as the understanding of other minds.Peer Reviewe

Parametric Representation of Tactile Numerosity in Working Memory

Estimated numerosity perception is processed in an approximate number system (ANS) that resembles the perception of a continuous magnitude. The ANS consists of a right lateralized frontoparietal network comprising the lateral prefrontal cortex (LPFC) and the intraparietal sulcus. Although the ANS has been extensively investigated, only a few studies have focused on the mental representation of retained numerosity estimates. Specifically, the underlying mechanisms of estimated numerosity working memory (WM) is unclear. Besides numerosities, as another form of abstract quantity, vibrotactile WM studies provide initial evidence that the right LPFC takes a central role in maintaining magnitudes. In the present fMRI multivariate pattern analysis study, we designed a delayed match-to-numerosity paradigm to test what brain regions retain approximate numerosity memoranda. In line with parametric WM results, our study found numerosity-specific WM representations in the right LPFC as well as in the supplementary motor area and the left premotor cortex extending into the superior frontal gyrus, thus bridging the gap in abstract quantity WM literature

Neuronal correlates of continuous manual tracking under varying visual movement feedback in a virtual reality environment

To accurately guide one's actions online, the brain predicts sensory action feedback ahead of time based on internal models, which can be updated by sensory prediction errors. The underlying operations can be experimentally investigated in sensorimotor adaptation tasks, in which moving under perturbed sensory action feedback requires internal model updates. Here we altered healthy participants’ visual hand movement feedback in a virtual reality setup, while assessing brain activity with functional magnetic resonance imaging (fMRI). Participants tracked a continually moving virtual target object with a photorealistic, three-dimensional (3D) virtual hand controlled online via a data glove. During the continuous tracking task, the virtual hand's movements (i.e., visual movement feedback) were repeatedly periodically delayed, which participants had to compensate for to maintain accurate tracking. This realistic task design allowed us to simultaneously investigate processes likely operating at several levels of the brain's motor control hierarchy. FMRI revealed that the length of visual feedback delay was parametrically reflected by activity in the inferior parietal cortex and posterior temporal cortex. Unpredicted changes in visuomotor mapping (at transitions from synchronous to delayed visual feedback periods or vice versa) activated biological motion-sensitive regions in the lateral occipitotemporal cortex (LOTC). Activity in the posterior parietal cortex (PPC), focused on the contralateral anterior intraparietal sulcus (aIPS), correlated with tracking error, whereby this correlation was stronger in participants with higher tracking performance. Our results are in line with recent proposals of a wide- spread cortical motor control hierarchy, where temporoparietal regions seem to evaluate visuomotor congruence and thus possibly ground a self-attribution of movements, the LOTC likely processes early visual prediction errors, and the aIPS computes action goal errors and possibly corresponding motor corrections

Response-Modality-Specific Encoding of Human Choices in Upper Beta Band Oscillations during Vibrotactile Comparisons

Perceptual decisions based on the comparison of two vibrotactile frequencies have been extensively studied in non-human primates. Recently, we obtained corresponding findings from human oscillatory electroencephalography (EEG) activity in the form of choice-selective modulations of upper beta band amplitude in medial premotor areas. However, the research in non-human primates as well as its human counterpart was so far limited to decisions reported by button presses. Thus, here we investigated whether the observed human beta band modulation is specific to the response modality. We recorded EEG activity from participants who compared two sequentially presented vibrotactile frequencies (f1 and f2), and decided whether f2 > f1 or f2 < f1, by performing a horizontal saccade to either side of a computer screen. Contrasting time-frequency transformed EEG data between both choices revealed that upper beta band amplitude (∼24–32 Hz) was modulated by participants’ choices before actual responses were given. In particular, “f2 > f1” choices were always associated with higher beta band amplitude than “f2 < f1” choices, irrespective of whether the choice was correct or not, and independent of the specific association between saccade direction and choice. The observed pattern of beta band modulation was virtually identical to our previous results when participants responded with button presses. In line with an intentional framework of decision making, the most likely sources of the beta band modulation were now, however, located in lateral as compared to medial premotor areas including the frontal eye fields. Hence, we could show that the choice-selective modulation of upper beta band amplitude is on the one hand consistent across different response modalities (i.e., same modulation pattern in similar frequency band), and on the other hand effector specific (i.e., modulation originating from areas involved in planning and executing saccades)

Active inference and the two-step task

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

Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports

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

A multimodal cortical network of sensory expectation violation revealed by fMRI

The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities

New approaches to the study of human brain networks underlying spatial attention and related processes

Cognitive processes, such as spatial attention, are thought to rely on extended networks in the human brain. Both clinical data from lesioned patients and fMRI data acquired when healthy subjects perform particular cognitive tasks typically implicate a wide expanse of potentially contributing areas, rather than just a single brain area. Conversely, evidence from more targeted interventions, such as transcranial magnetic stimulation (TMS) or invasive microstimulation of the brain, or selective study of patients with highly focal brain damage, can sometimes indicate that a single brain area may make a key contribution to a particular cognitive process. But this in turn raises questions about how such a brain area may interface with other interconnected areas within a more extended network to support cognitive processes. Here, we provide a brief overview of new approaches that seek to characterise the causal role of particular brain areas within networks of several interacting areas, by measuring the effects of manipulations for a targeted area on function in remote interconnected areas. In human participants, these approaches include concurrent TMS-fMRI and TMS-EEG, as well as combination of the focal lesion method in selected patients with fMRI and/or EEG measures of the functional impact from the lesion on interconnected intact brain areas. Such approaches shed new light on how frontal cortex and parietal cortex modulate sensory areas in the service of attention and cognition, for the normal and damaged human brai

Response modality-dependent categorical 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 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

EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision

The human brain is constantly subjected to a multimodal stream of probabilistic sensory inputs. Electroencephalography (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 unimodal transition probabilities and cross-modal conditional dependencies. We found modality specific signatures of MMN (~100–200 ms) in all three modalities, which were source localized to the respective sensory cortices and shared right lateralized prefrontal sources. Additionally, we identified a cross-modal signature of mismatch processing in the P3a time range (~300–350 ms), 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, P3a responses across modalities were increased for mispredicted stimuli with low cross-modal conditional probability, suggesting sensitivity to multimodal (global) predictive sequence properties. Finally, model comparisons indicated that the observed single trial dynamics were best captured by Bayesian learning models tracking unimodal stimulus transitions as well as cross-modal conditional dependencies