Recovery of the 20Hz Rebound to Tactile and Proprioceptive Stimulation after Stroke

Sensorimotor integration is closely linked to changes in motor-cortical excitability, observable in the modulation of the 20 Hz rhythm. After somatosensory stimulation, the rhythm transiently increases as a rebound that reflects motor-cortex inhibition. Stroke-induced alterations in afferent input likely affect motor-cortex excitability and motor recovery. To study the role of somatosensory afferents in motor-cortex excitability after stroke, we employed magnetoencephalographic recordings (MEG) at 1-7 days, one month, and 12 months in 23 patients with stroke in the middle cerebral artery territory and 22 healthy controls. The modulation of the 20 Hz motor-cortical rhythm was evaluated to two different somatosensory stimuli, tactile stimulation, and passive movement of the index fingers. The rebound strengths to both stimuli were diminished in the acute phase compared to the controls and increased significantly during the first month after stroke. However, only the rebound amplitudes to tactile stimuli fully recovered within the follow-up period. The rebound strengths in the affected hemisphere to both stimuli correlated strongly with the clinical scores across the follow-up. The results show that changes in the 20 Hz rebound to both stimuli behave similarly and occur predominantly during the first month. The 20 Hz rebound is a potential marker for predicting motor recovery after stroke.Peer reviewe

Comparing Features for Classification of MEG Responses to Motor Imagery

Peer reviewe

Expanding the applicability of magnetoencephalography

Magnetoencephalography (MEG) offers a unique way to non-invasively monitor the neural activity in the human brain. MEG is based on measuring the very weak magnetic fields generated by the electric currents in the active neurons. Such measurements allow, with certain limitations, estimating the underlying current distribution and thus the locations and time courses of the neural generators with an excellent temporal resolution. The aim of this Thesis was to advance MEG to certain realms that have been considered difficult or even impossible for it. Specifically, the included studies contributed to the modelling of the neural generators, detection of activity in the deep brain areas, analysis of oscillatory activity, and characterisation of neural states related to bistable perception. Estimating the sources of MEG signals is non-trivial as multiple current constellations can give rise to the same observed magnetic fields. As a new solution to this problem, we introduced an automatic Bayesian tracking algorithm that recovers the locations and time courses of a set of focal neural current sources from MEG data. The majority of MEG experiments have concentrated on brain signals originating in the neocortex due to the rapid decrease of the MEG signals as a function increasing source depth. Here, we demonstrated that neural activity deep in the brainstem can be detected and accurately localised by MEG in favourable conditions. We also explored the utility of stochastic resonance in varying the salience of a cognitive stimulus, and showed that the detection accuracy of visually-presented words correlated better with the amplitudes of the late than early responses. The temporal resolution provided by MEG was exploited in novel ways. We showed that oscillatory 20-Hz signals from the primary and secondary somatosensory cortex were transiently phase-locked in response to a stimulus, possibly signifying functional connectivity. We also introduced a frequency-tagging method employing dynamical noise to separate brain activations elicited by different parts of a visual scene: monitoring these rhythmic signals with MEG enabled us to probe the neural engagement in the early visual brain areas during bistable perception and thus to link subjective perceptual states to brain states

Modulation of the similar to 20-Hz motor-cortex rhythm to passive movement and tactile stimulation

Background: Integration of afferent somatosensory input with motor-cortex output is essential for accurate movements. Prior studies have shown that tactile input modulates motor-cortex excitability, which is reflected in the reactivity of the similar to 20-Hz motor-cortex rhythm. similar to 20-Hz rebound is connected to inhibition or deactivation of motor cortex whereas suppression has been associated with increased motor cortex activity. Although tactile sense carries important information for controlling voluntary actions, proprioception likely provides the most essential feedback for motor control. Methods: To clarify how passive movement modulates motor-cortex excitability, we studied with magnetoencephalography (MEG) the amplitudes and peak latencies of suppression and rebound of the similar to 20-Hz rhythm elicited by tactile stimulation and passive movement of right and left index fingers in 22 healthy volunteers. Results: Passive movement elicited a stronger and more robust similar to 20-Hz rebound than tactile stimulation. In contrast, the suppression amplitudes did not differ between the two stimulus types. Conclusion: Our findings suggest that suppression and rebound represent activity of two functionally distinct neuronal populations. The similar to 20-Hz rebound to passive movement could be a suitable tool to study the functional state of the motor cortex both in healthy subjects and in patients with motor disorders.Peer reviewe

Human Empathy, Personality and Experience Affect the Emotion Ratings of Dog and Human Facial Expressions

Facial expressions are important for humans in communicating emotions to the conspecifics and enhancing interpersonal understanding. Many muscles producing facial expressions in humans are also found in domestic dogs, but little is known about how humans perceive dog facial expressions, and which psychological factors influence people's perceptions. Here, we asked 34 observers to rate the valence, arousal, and the six basic emotions (happiness, sadness, surprise, disgust, fear, and anger/aggressiveness) from images of human and dog faces with Pleasant, Neutral and Threatening expressions. We investigated how the subjects' personality (the Big Five Inventory), empathy (Interpersonal Reactivity Index) and experience of dog behavior affect the ratings of dog and human faces. Ratings of both species followed similar general patterns: human subjects classified dog facial expressions from pleasant to threatening very similarly to human facial expressions. Subjects with higher emotional empathy evaluated Threatening faces of both species as more negative in valence and higher in anger/aggressiveness. More empathetic subjects also rated the happiness of Pleasant humans but not dogs higher, and they were quicker in their valence judgments of Pleasant human, Threatening human and Threatening dog faces. Experience with dogs correlated positively with ratings of Pleasant and Neutral dog faces. Personality also had a minor effect on the ratings of Pleasant and Neutral faces in both species. The results imply that humans perceive human and dog facial expression in a similar manner, and the perception of both species is influenced by psychological factors of the evaluators. Especially empathy affects both the speed and intensity of rating dogs' emotional facial expressions.Peer reviewe

Non-linear dynamical analysis of resting tremor for demand-driven deep brain stimulation.

Parkinson's Disease (PD) is currently the second most common neurodegenerative disease. One of the most characteristic symptoms of PD is resting tremor. Local Field Potentials (LFPs) have been widely studied to investigate deviations from the typical patterns of healthy brain activity. However, the inherent dynamics of the Sub-Thalamic Nucleus (STN) LFPs and their spatiotemporal dynamics have not been well characterized. In this work, we study the non-linear dynamical behaviour of STN-LFPs of Parkinsonian patients using ε -recurrence networks. RNs are a non-linear analysis tool that encodes the geometric information of the underlying system, which can be characterised (for example, using graph theoretical measures) to extract information on the geometric properties of the attractor. Results show that the activity of the STN becomes more non-linear during the tremor episodes and that ε -recurrence network analysis is a suitable method to distinguish the transitions between movement conditions, anticipating the onset of the tremor, with the potential for application in a demand-driven deep brain stimulation system

Prepulse Inhibition of Auditory Cortical Responses in the Caudolateral Superior Temporal Gyrus in Macaca mulatta

Prepulse inhibition (PPI) refers to a decreased response to a startling stimulus when another weaker stimulus precedes it. Most PPI studies have focused on the physiological startle reflex and fewer have reported the PPI of cortical responses. We recorded local field potentials (LFPs) in four monkeys and investigated whether the PPI of auditory cortical responses (alpha, beta, and gamma oscillations and evoked potentials) can be demonstrated in the caudolateral belt of the superior temporal gyrus (STGcb). We also investigated whether the presence of a conspecific, which draws attention away from the auditory stimuli, affects the PPI of auditory cortical responses. The PPI paradigm consisted of Pulse-only and Prepulse + Pulse trials that were presented randomly while the monkey was alone (ALONE) and while another monkey was present in the same room (ACCOMP). The LFPs to the Pulse were significantly suppressed by the Prepulse thus, demonstrating PPI of cortical responses in the STGcb. The PPI-related inhibition of the N1 amplitude of the evoked responses and cortical oscillations to the Pulse were not affected by the presence of a conspecific. In contrast, gamma oscillations and the amplitude of the N1 response to Pulse-only were suppressed in the ACCOMP condition compared to the ALONE condition. These findings demonstrate PPI in the monkey STGcb and suggest that the PPI of auditory cortical responses in the monkey STGcb is a pre-attentive inhibitory process that is independent of attentional modulation.Peer reviewe

Consistency and similarity of MEG- and fMRI-signal time courses during movie viewing

Movie viewing allows human perception and cognition to be studied in complex, real-life-like situations in a brain-imaging laboratory. Previous studies with functional magnetic resonance imaging (fMRI) and with magneto-and electroencephalography (MEG and EEG) have demonstrated consistent temporal dynamics of brain activity across movie viewers. However, little is known about the similarities and differences of fMRI and MEG or EEG dynamics during such naturalistic situations. We thus compared MEG and fMRI responses to the same 15-min black-and-white movie in the same eight subjects who watched the movie twice during both MEG and fMRI recordings. We analyzed intra-and intersubject voxel-wise correlations within each imaging modality as well as the correlation of the MEG envelopes and fMRI signals. The fMRI signals showed voxel-wise within-and between-subjects correlations up to r = 0.66 and r = 0.37, respectively, whereas these correlations were clearly weaker for the envelopes of band-pass filtered (7 frequency bands below 100 Hz) MEG signals (within-subjects correlation r <0.14 and between-subjects r <0.05). Direct MEG-fMRI voxel-wise correlations were unreliable. Notably, applying a spatial-filtering approach to the MEG data uncovered consistent canonical variates that showed considerably stronger (up to r = 0.25) between-subjects correlations than the univariate voxel-wise analysis. Furthermore, the envelopes of the time courses of these variates up to about 10 Hz showed association with fMRI signals in a general linear model. Similarities between envelopes of MEG canonical variates and fMRI voxel time-courses were seen mostly in occipital, but also in temporal and frontal brain regions, whereas intra-and intersubject correlations for MEG and fMRI separately were strongest only in the occipital areas. In contrast to the conventional univariate analysis, the spatial-filtering approach was able to uncover associations between the MEG envelopes and fMRI time courses, shedding light on the similarities of hemodynamic and electromagnetic brain activities during movie viewing.Peer reviewe