Inferring occluded projectile motion changes connectivity within a visuo-fronto-parietal network.

Anticipating the behaviour of moving objects in the physical environment is essential for a wide range of daily actions. This ability is thought to rely on mental simulations and has been shown to involve frontoparietal and early visual areas. Yet, the connectivity patterns between these regions during intuitive physical inference remain largely unknown. In this study, participants underwent fMRI while performing a task requiring them to infer the parabolic trajectory of an occluded ball falling under Newtonian physics, and a control task. Building on our previous research showing that when solving the physical inference task, early visual areas encode task-specific and perception-like information about the inferred trajectory, the present study aimed to (i) identify regions that are functionally coupled with early visual areas during the physical inference task, and (ii) investigate changes in effective connectivity within this network of regions. We found that early visual areas are functionally connected to a set of parietal and premotor regions when inferring occluded trajectories. Using dynamic causal modelling, we show that predicting occluded trajectories is associated with changes in effective connectivity within a parieto-premotor network, which may drive internally generated early visual activity in a top-down fashion. These findings offer new insights into the interaction between early visual and frontoparietal regions during physical inference, contributing to our understanding of the neural mechanisms underlying the ability to predict physical outcomes.

Self-regulating arousal via pupil-based biofeedback.

The brain's arousal state is controlled by several neuromodulatory nuclei known to substantially influence cognition and mental well-being. Here we investigate whether human participants can gain volitional control of their arousal state using a pupil-based biofeedback approach. Our approach inverts a mechanism suggested by previous literature that links activity of the locus coeruleus, one of the key regulators of central arousal and pupil dynamics. We show that pupil-based biofeedback enables participants to acquire volitional control of pupil size. Applying pupil self-regulation systematically modulates activity of the locus coeruleus and other brainstem structures involved in arousal control. Furthermore, it modulates cardiovascular measures such as heart rate, and behavioural and psychophysiological responses during an oddball task. We provide evidence that pupil-based biofeedback makes the brain's arousal system accessible to volitional control, a finding that has tremendous potential for translation to behavioural and clinical applications across various domains, including stress-related and anxiety disorders.

How and when EEG reflects changes in neuronal connectivity due to time awake.

Being awake means forming new memories, primarily by strengthening neuronal synapses. The increase in synaptic strength results in increasing neuronal synchronicity, which should result in higher amplitude electroencephalography (EEG) oscillations. This is observed for slow waves during sleep but has not been found for wake oscillations. We hypothesized that this was due to a limitation of spectral power analysis, which does not distinguish between changes in amplitudes from changes in number of occurrences of oscillations. By using cycle-by-cycle analysis instead, we found that theta and alpha oscillation amplitudes increase as much as 30% following 24 h of extended wake. These increases were interrupted during the wake maintenance zone (WMZ), a window just before bedtime when it is difficult to fall asleep. We found that pupil diameter increased during this window, suggesting the ascending arousal system is responsible. In conclusion, wake oscillation amplitudes reflect increased synaptic strength, except during the WMZ.

Physical inference of falling objects involves simulation of occluded trajectories in early visual areas.

Humans possess an intuitive understanding of the environment's physical properties and dynamics, which allows them to predict the outcomes of physical scenarios and successfully interact with the physical world. This predictive ability is thought to rely on mental simulations and has been shown to involve frontoparietal areas. Here, we investigate whether such mental simulations may be accompanied by visual imagery of the predicted physical scene. We designed an intuitive physical inference task requiring participants to infer the parabolic trajectory of an occluded ball falling in accordance with Newtonian physics. Participants underwent fMRI while (i) performing the physical inference task alternately with a visually matched control task, and (ii) passively observing falling balls depicting the trajectories that had to be inferred during the physical inference task. We found that performing the physical inference task activates early visual areas together with a frontoparietal network when compared with the control task. Using multivariate pattern analysis, we show that these regions contain information specific to the trajectory of the occluded ball (i.e., fall direction), despite the absence of visual inputs. Using a cross-classification approach, we further show that in early visual areas, trajectory-specific activity patterns evoked by the physical inference task resemble those evoked by the passive observation of falling balls. Together, our findings suggest that participants simulated the ball trajectory when solving the task, and that the outcome of these simulations may be represented in form of the perceivable sensory consequences in early visual areas.

Pre-stimulus beta power modulation during motor sequence learning is reduced in 'Parkinson's disease.

Beta oscillations within motor-cortical areas have been linked to sensorimotor function. In line with this, pathologically altered beta activity in cortico-basal ganglia pathways has been suggested to contribute to the pathophysiology of Parkinson's disease (PD), a neurodegenerative disorder primarily characterized by motor impairment. Although its precise function is still discussed, beta activity might subserve an anticipatory role in preparation of future actions. By reanalyzing previously published data, we aimed at investigating the role of pre-stimulus motor-cortical beta power modulation in motor sequence learning and its alteration in PD. 20 PD patients and 20 healthy controls (HC) performed a serial reaction time task (SRTT) in which reaction time gain presumably reflects the ability to anticipate subsequent sequence items. Randomly varying patterns served as control trials. Neuromagnetic activity was recorded using magnetoencephalography (MEG) and data was reanalyzed with respect to task stimuli onset. Assuming that pre-stimulus beta power modulation is functionally related to motor sequence learning, reaction time gain due to training on the SRTT should vary depending on the amount of beta power suppression prior to stimulus onset. We hypothesized to find less pre-stimulus beta power suppression in PD patients as compared to HC associated with reduced motor sequence learning in patients. Behavioral analyses revealed that PD patients exhibited smaller reaction time gain in sequence relative to random control trials than HC indicating reduced learning in PD. This finding was indeed paralleled by reduced pre-stimulus beta power suppression in PD patients. Further strengthening its functional relevance, the amount of pre-stimulus beta power suppression during sequence training significantly predicted subsequent reaction time advantage in sequence relative to random trials in patients. In conclusion, the present data provide first evidence for the contribution of pre-stimulus motor-cortical beta power suppression to motor sequence learning and support the hypothesis that beta oscillations may subserve an anticipatory, predictive function, possibly compromised in PD.

The significance of brain oscillations in motor sequence learning: Insights from Parkinson's disease.

Motor sequence learning plays a pivotal role in various everyday activities. Motor-cortical beta oscillations have been suggested to be involved in this type of learning. In Parkinson's disease (PD), oscillatory activity within cortico-basal-ganglia circuits is altered. Pathologically increased beta oscillations have received particular attention as they may be associated with motor symptoms such as akinesia. In the present magnetoencephalography (MEG) study, we investigated PD patients and healthy controls (HC) during implicit motor sequence learning with the aim to shed light on the relation between changes of cortical brain oscillations and motor learning in PD with a particular focus on beta power. To this end, 20 PD patients (ON medication) and 20 age- and sex-matched HC were trained on a serial reaction time task while neuromagnetic activity was recorded using a 306-channel whole-head MEG system. PD patients showed reduced motor sequence acquisition and were more susceptible to interference by random trials after training on the task as compared to HC. Behavioral differences were paralleled by changes at the neurophysiological level. Diminished sequence acquisition was paralleled by less training-related beta power suppression in motor-cortical areas in PD patients as compared to HC. In addition, PD patients exhibited reduced training-related theta activity in motor-cortical areas paralleling susceptibility to interference. The results support the hypothesis that the acquisition of a new motor sequence relies on suppression of motor-cortical beta oscillations, while motor-cortical theta activity might be related to stabilization of the learned sequence as indicated by reduced susceptibility to interference. Both processes appear to be impaired in PD.

Facilitating effects of deep brain stimulation on feedback learning in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) provides an effective treatment for Parkinson's disease (PD) motor symptoms. However, findings of effects on cognitive function such as feedback learning remain controversial and rare. The aim of the present study was to gain a better understanding of cognitive alterations associated with STN-DBS. Therefore, we investigated effects of STN-DBS on active and observational feedback learning in PD. 18 PD patients with STN-DBS and 18 matched healthy controls completed active and observational feedback learning tasks. Patients were investigated ON and OFF STN-DBS. Tasks consisted of learning (with feedback) and test phases (without feedback). STN-DBS improved active learning during feedback trials and PD patients ON (but not OFF) STN-DBS showed comparable performance patterns as healthy controls. No STN-DBS effect was found when assessing performance during active test trials without feedback. In this case, however, STN-DBS effects were found to depend on symptom severity. While more impaired patients benefited from STN-DBS, stimulation had no facilitating effect on patients with less severe symptoms. Along similar lines, the severity of motor symptoms tended to be significantly correlated with differences in active test performance due to STN-DBS. For observational feedback learning, there was a tendency for a positive STN-DBS effect with patients reaching the performance level of healthy controls only ON STN-DBS. The present data suggest that STN-DBS facilitates active feedback learning in PD patients. Furthermore, they provide first evidence that STN-DBS might not only affect learning from own but also from observed actions and outcomes.

Implicit Motor Sequence Learning and Working Memory Performance Changes Across the Adult Life Span.

Although implicit motor sequence learning is rather well understood in young adults, effects of aging on this kind of learning are controversial. There is first evidence that working memory (WM) might play a role in implicit motor sequence learning in young adults as well as in adults above the age of 65. However, the knowledge about the development of these processes across the adult life span is rather limited. As the average age of our population continues to rise, a better understanding of age-related changes in motor sequence learning and potentially mediating cognitive processes takes on increasing significance. Therefore, we investigated aging effects on implicit motor sequence learning and WM. Sixty adults (18-71 years) completed verbal and visuospatial n-back tasks and were trained on a serial reaction time task (SRTT). Randomly varying trials served as control condition. To further assess consolidation indicated by off-line improvement and reduced susceptibility to interference, reaction times (RTs) were determined 1 h after initial learning. Young and older but not middle-aged adults showed motor sequence learning. Nine out of 20 older adults (compared to one young/one middle-aged) exhibited some evidence of sequence awareness. After 1 h, young and middle-aged adults showed off-line improvement. However, RT facilitation was not specific to sequence trials. Importantly, susceptibility to interference was reduced in young and older adults indicating the occurrence of consolidation. Although WM performance declined in older participants when load was high, it was not significantly related to sequence learning. The data reveal a decline in motor sequence learning in middle-aged but not in older adults. The use of explicit learning strategies in older adults might account for the latter result.