Differential neural mechanisms for early and late prediction error detection

Graph analysis of cortical reorganization after virtual reality-based rehabilitation following stroke: a pilot randomized study

Introduction

Stroke is the leading cause of functional disability worldwide. With the increase of the global population, motor rehabilitation of stroke survivors is of ever-increasing importance. In the last decade, virtual reality (VR) technologies for rehabilitation have been extensively studied, to be used instead of or together with conventional treatments such as physiotherapy or occupational therapy. The aim of this work was to evaluate the GestureCollection VR-based rehabilitation tool in terms of the brain changes and clinical outcomes of the patients.

Methods

Two groups of chronic patients underwent a rehabilitation treatment with (experimental) or without (control) complementation with GestureCollection. Functional magnetic resonance imaging exams and clinical assessments were performed before and after the treatment. A functional connectivity graph-based analysis was used to assess differences between the connections and in the network parameters strength and clustering coefficient.

Results

Patients in both groups showed improvement in clinical scales, but there were more increases in functional connectivity in the experimental group than in the control group.

Discussion

The experimental group presented changes in the connections between the frontoparietal and the somatomotor networks, associative cerebellum and basal ganglia, which are regions associated with reward-based motor learning. On the other hand, the control group also had results in the somatomotor network, in its ipsilateral connections with the thalamus and with the motor cerebellum, which are regions more related to a purely mechanical activity. Thus, the use of the GestureCollection system was successfully shown to promote neuroplasticity in several motor-related areas.

Revealing robust neural correlates of conscious and unconscious visual processing: activation likelihood estimation meta-analyses

Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex.

Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors

How susceptible a memory is to later modification might depend on how stable the episode has been encoded. This stability was proposed to increase when retrieving information more (vs. less) often and in a spaced (vs. massed) practice. Using fMRI, we examined the effects of these different pre-fMRI retrieval protocols on the subsequent propensity to learn from episodic prediction errors. After encoding a set of different action stories, participants came back for two pre-fMRI retrieval sessions in which they encountered original episodes either 2 or 8 times in either a spaced or a massed retrieval protocol. One week later, we cued episodic retrieval during the fMRI session by using original or modified videos of encoded action stories. Recurrent experience of modified episodes was associated with increasing activity in the episodic memory network including hippocampal and cortical areas, when leading to false memories in a post-fMRI memory test. While this observation clearly demonstrated learning from episodic prediction errors, we found no evidence for a modulatory effect of the different retrieval protocols. As expected, the benefit of retrieving an episode more often was reflected in better memory for originally encoded episodes. In addition, frontal activity increased for episodic prediction errors when episodes had been less frequently retrieved pre-fMRI. A history of spaced versus massed retrieval was associated with increased activation throughout the episodic memory network, with no significant effect on behavioral performance. Our findings show that episodic prediction errors led to false memories. The history of different retrieval protocols was reflected in memory performance and brain responses to episodic prediction errors, but did not interact with the brain's episodic learning response.

Effects of virtual reality-based motor rehabilitation: a systematic review of fMRI studies

BACKGROUND

The use of virtual reality (VR) as a rehabilitation tool has been shown to induce motor and cognitive improvements in different populations. Functional magnetic resonance imaging (fMRI) has been used to investigate neuroplasticity resulting from these treatments. We hypothesize that VR rehabilitation induces functional improvement and brain changes that can be detected by fMRI.

OBJECTIVE

To systematically review the effects of VR intervention on the cortical reorganization measured by fMRI and associated with functional improvement.

METHODS

We performed a systematic review of studies published between 2005 and 2021. Papers were retrieved from six databases using the following keywords: "motor rehabilitation", "fMRI" and "virtual reality". Case studies, pre-post studies, cross-sectional studies, and randomized controlled trials published were included. Manuscripts were assessed by The NIH Study Quality Assessment Tools to determine their quality.

RESULTS

Twenty-three articles met our eligibility criteria: 18 about VR rehabilitation in stroke and five on other clinical conditions (older adults, cerebral palsy, and Parkinson's disease). Changes in neural patterns of activation and reorganization were revealed in both the ipsilesional and the contralesional hemispheres. Results were located mainly in the primary motor cortex, sensorimotor cortex and supplementary motor area in post-stroke patients in the acute, subacute, and chronic rehabilitation phases, and were associated with functional improvement after VR intervention. Similar effects were observed in older adults and in patients with other neurological diseases with improved performance.

CONCLUSION

Most stroke-related studies showed either restoration to normal or increase of activation patterns or relateralization at/to the ipsilesional hemisphere, with some also reporting a decrease in activity or extent of activation after VR therapy. In general, VR intervention demonstrated evidence of efficacy both in neurological rehabilitation and in performance improvement of older adults, accompanied by fMRI evidence of brain reorganization.

Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network

According to the predictive coding (PC) theory, the brain is constantly engaged in predicting its upcoming states and refining these predictions through error signals. Despite extensive research investigating the neural bases of this theory, to date no previous study has systematically attempted to define the neural mechanisms of predictive coding across studies and sensory channels, focussing on functional connectivity. In this study, we employ a coordinate-based meta-analytical approach to address this issue. We first use the Activation Likelihood Estimation (ALE) algorithm to detect spatial convergence across studies, related to prediction error and encoding. Overall, our ALE results suggest the ultimate role of the left inferior frontal gyrus and left insula in both processes. Moreover, we employ a meta-analytic connectivity method (Seed-Voxel Correlations Consensus). This technique reveals a large, bilateral predictive network, which resembles large-scale networks involved in task-driven attention and execution. In sum, we find that: (i) predictive processing seems to occur more in certain brain regions than others, when considering different sensory modalities at a time; (ii) there is no evidence, at the network level, for a distinction between error and prediction processing.

Neural Evidence of Hierarchical Cognitive Control during Haptic Processing: An fMRI Study

Interacting with our immediate surroundings requires constant manipulation of objects. Dexterous manipulation depends on comparison between actual and predicted sensory input, with these predictions calculated by means of lower- and higher-order corollary discharge signals. However, there is still scarce knowledge about the hierarchy in the neural architecture supporting haptic monitoring during manipulation. The present study aimed to assess this issue focusing on the cross talk between lower-order sensory and higher-order associative regions. We used functional magnetic resonance imaging in humans during a haptic discrimination task in which participants had to judge whether a touched shape or texture corresponded to an expected stimulus whose name was previously presented. Specialized haptic regions identified with an independent localizer task did not differ between expected and unexpected conditions, suggesting their lack of involvement in tactile monitoring. When presented stimuli did not match previous expectations, the left supramarginal gyrus (SMG), middle temporal, and medial prefrontal cortices were activated regardless of the nature of the haptic mismatch (shape/texture). The left primary somatosensory area (SI) responded differently to unexpected shapes and textures in line with a specialized detection of haptic mismatch. Importantly, connectivity analyses revealed that the left SMG and SI were more functionally coupled during unexpected trials, emphasizing their interaction. The results point for the first time to a hierarchical organization in the neural substrates underlying haptic monitoring during manipulation with the SMG as a higher-order hub comparing actual and predicted somatosensory input, and SI as a lower-order site involved in the detection of more specialized haptic mismatch.

Dynamic Interactions between Top-Down Expectations and Conscious Awareness

It is well known that top-down expectations affect perceptual processes. Yet, remarkably little is known about the relationship between expectations and conscious awareness. We address three crucial outstanding questions: (1) how do expectations affect the likelihood of conscious stimulus perception?; (2) does the brain register violations of expectations nonconsciously?; and (3) do expectations need to be conscious to influence perceptual decisions? Using human participants, we performed three experiments in which we manipulated stimulus predictability within the attentional blink paradigm, while combining visual psychophysics with electrophysiological recordings. We found that valid stimulus expectations increase the likelihood of conscious access of stimuli. Furthermore, our findings suggest a clear dissociation in the interaction between expectations and consciousness: conscious awareness seems crucial for the implementation of top-down expectations, but not for the generation of bottom-up stimulus-evoked prediction errors. These results constrain and update influential theories about the role of consciousness in the predictive brain.SIGNIFICANCE STATEMENT While the relationship between expectations and conscious awareness plays a major role in many prediction-based theories of brain functioning, thus far few empirical studies have examined this relationship. Here, we address this gap in knowledge in a set of three experiments. Our results suggest that the effect of expectations on conscious awareness varies between different steps of the hierarchy of predictive processing. While the active use of top-down expectations for perceptual decisions requires conscious awareness, prediction errors can be triggered outside of conscious awareness. These results constrain and update influential theories about the role of consciousness in the predictive brain.

Brodmann area 10: Collating, integrating and high level processing of nociception and pain

Multiple frontal cortical brain regions have emerged as being important in pain processing, whether it be integrative, sensory, cognitive, or emotional. One such region, Brodmann Area 10 (BA 10), is the largest frontal brain region that has been shown to be involved in a wide variety of functions including risk and decision making, odor evaluation, reward and conflict, pain, and working memory. BA 10, also known as the anterior prefrontal cortex, frontopolar prefrontal cortex or rostral prefrontal cortex, is comprised of at least two cytoarchitectonic sub-regions, medial and lateral. To date, the explicit role of BA 10 in the processing of pain hasn't been fully elucidated. In this paper, we first review the anatomical pathways and functional connectivity of BA 10. Numerous functional imaging studies of experimental or clinical pain have also reported brain activations and/or deactivations in BA 10 in response to painful events. The evidence suggests that BA 10 may play a critical role in the collation, integration and high-level processing of nociception and pain, but also reveals possible functional distinctions between the subregions of BA 10 in this process.

Synthetic consciousness: the distributed adaptive control perspective

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'.