Watching an instructional video has become a common way to learn a new task. However, we have but a sparse understanding of the neural processes involved during observational learning in naturalistic settings. Recently developed data driven methods for analyzing brain activity provide an opportunity for further investigation. Here, we evaluate intersubject synchrony during fMRI to understand common brain processes during naturalistic observational learning. Participants solitarily watched an instructional video and learned how to fold a paper figure. Three learning runs were sufficient to successfully solve the task. To assess interbrain synchrony, we extended previous principal component (PCA)-based methods to an intersubject principal component analysis (PCA), which offers multiple measures for additional insights into the nature of the synchrony. Using the different metrics of this method, we show a robust synchronous involvement of the action observation execution network (AOEN) in observational learning, between subjects as well as within subjects, regardless of the task or video content. Importantly, additional areas such as the cerebellum, primary motor cortex, control, and sensory integration areas also showed robust synchrony in observational learning. Complimentary to this robust general synchrony, individual regions of the AOEN exhibited task-related differences. Synchrony decreased during the learning process, likely reflecting task state and individual learning strategies. To test the stimulus as a possible source of synchrony, we quantified the temporal structure as the optic flow of the instructional video. Optic flow was strongly related to common activation of the somatomotor areas of the AOEN well beyond visual areas, but could not completely explain synchrony. Thus, although visual motion provides a proxy for meaningful hand actions, our results suggest that intersubject synchrony reflects common cognitive processing during observa- tional learning beyond sensory input.
Perception of magnitudes such as duration or distance is often found to be systematically biased.
The biases, which result from incorporating prior knowledge in the perceptual process, can vary considerably between individuals. The variations are commonly attributed to differences in sensory precision and reliance on priors. However, another factor not considered so far is the implicit belief about how successive sensory stimuli are generated: independently from each other or with certain temporal continuity. The main types of explanatory models proposed so far—static or iterative—mirror this distinction but cannot adequately explain individual biases. Here we propose a new unifying model that explains individual variation as combination of sensory precision and beliefs about temporal continuity and predicts the experimentally found changes in biases when altering temporal continuity. Thus, according to the model, individual differences in perception depend on beliefs about how stimuli are generated in the world.
The angular vestibulo-ocular reflex (aVOR) stabilizes retinal images by counter-rotating the eyes during head rotations. Perfect compensatory movements would thus rotate the eyes exactly opposite to the head, that is, eyes vs. head would exhibit a unity gain. However, in many species, but also in elderly humans or patients with a history of vestibular damage, the aVOR is far from compensatory with gains that are in part considerably lower than unity. The reason for this apparent suboptimality is unknown. Here, we propose that low VOR gain values reflect an optimal adaptation to sensory and motor signal variability. According to this hypothesis, gaze stabilization mechanisms that aim at minimizing the overall retinal image slip must consider the effects of (1) sensory and motor noise and (2) dynamic constraints of peripheral and central nervous processing. We demonstrate that a computational model for optimizing retinal image slip in the presence of such constraints of signal processing in fact predicts gain values smaller than unity. We further show specifically for tadpoles of the clawed toad, Xenopus laevis with particularly low gain values that previously reported VOR gains quantitatively correspond to the observed variability of eye movements and thus constitute an optimal adaptation mechanism. We thus hypothesize that lower VOR gain values in elderly human subjects or recovered patients with a history of vestibular damage may be the sign of an optimization given higher noise levels rather than a direct consequence of the damage, such as an inability of executing fast compensatory eye movements.
Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional magnetic resonance imaging, we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a “Response” trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individual’s sequential bias following active
reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages.
Introduction: Functional disorders are prevalent in all medical fields and pose a tremendous public health problem, with pain being one of the most common functional symptoms. Understanding the underlying, potentially unifying mechanism in functional (pain) disorders is instrumental in facilitating timely diagnosis, stigma reduction, and adequate treatment options. Neuroscientific models of perception suggest that functional symptoms arise due to dysregulated sensorimotor processing in the central nervous system, with brain-based predictions dominating the eventual percept. Experimental evidence for this transdiagnostic mechanism has been established in various functional symptoms. The goal of the current study was to investigate whether erroneous sensorimotor processing is an underlying transdiagnostic mechanism in chronic (functional) pain.
Method: A total of 13 patients with chronic (functional) pain [three patients with chronic (functional) pain disorder, F45.40, ICD-10; 10 patients with chronic pain disorder with somatic and psychological factors, F45.41, ICD-10]; and 15 healthy controls performed large combined eye-head gaze shifts toward visual targets, naturally and with increased head moment of inertia. We simultaneously measured participants’ eye and head movements to assess head oscillations at the end of the gaze shift, which are an established indicator of (transdiagnostic) sensorimotor processing deficits of head control.
Results: Using a Bayesian analysis protocol, we found that patients with chronic (functional) pain and control participants stabilized their heads equally well (Bayes Factor 01 = 3.7, Bayes Factor exclusion = 5.23; corresponding to substantial evidence) during all sessions of the experiment.
Conclusion: Our results suggest that patients with chronic (functional) pain do not show measurable symptom-unspecific sensorimotor processing deficits.