Bilateral 5 Hz transcranial alternating current stimulation on fronto-temporal areas modulates resting-state EEG

Rhythmic non-invasive brain stimulations are promising tools to modulate brain activity by entraining neural oscillations in specific cortical networks. The aim of the study was to assess the possibility to influence the neural circuits of the wake-sleep transition in awake subjects via a bilateral transcranial alternating current stimulation at 5 Hz (theta-tACS) on fronto-temporal areas. 25 healthy volunteers participated in two within-subject sessions (theta-tACS and sham), one week apart and in counterbalanced order. We assessed the stimulation effects on cortical EEG activity (28 derivations) and self-reported sleepiness (Karolinska Sleepiness Scale). theta-tACS induced significant increases of the theta activity in temporo-parieto-occipital areas and centro-frontal increases in the alpha activity compared to sham but failed to induce any online effect on sleepiness. Since the total energy delivered in the sham condition was much less than in the active theta-tACS, the current data are unable to isolate the specific effect of entrained theta oscillatory activity per se on sleepiness scores. On this basis, we concluded that theta-tACS modulated theta and alpha EEG activity with a topography consistent with high sleep pressure conditions. However, no causal relation can be traced on the basis of the current results between these rhythms and changes on sleepines

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations

Multisensory self-motion processing in humans

Humans obtain and process sensory information from various modalities to ensure successful navigation through the environment. While visual, vestibular, and auditory self-motion perception have been extensively investigated, studies on tac-tile self-motion perception are comparably rare. In my thesis, I have investigated tactile self-motion perception and its interaction with the visual modality. In one of two behavioral studies, I analyzed the influence of a tactile heading stimulus intro-duced as a distractor on visual heading perception. In the second behavioral study, I analyzed visuo-tactile perception of self-motion direction (heading). In both studies, visual self-motion was simulated as forward motion over a 2D ground plane. Tactile self-motion was simulated by airflow towards the subjects’ forehead, mimicking the experience of travel wind, e.g., during a bike ride. In the analysis of the subjects’ perceptual reports, I focused on possible visuo-tactile interactions and applied dif-ferent models to describe the integration of visuo-tactile heading stimuli. Lastly, in a functional magnetic resonance imaging study (fMRI), I investigated neural correlates of visual and tactile perception of traveled distance (path integration) and its modu-lation by prediction and cognitive task demands. In my first behavioral study, subjects indicated perceived heading from uni-modal visual (optic flow), unimodal tactile (tactile flow) or from a combination of stimuli from both modalities, simulating either congruent or incongruent heading (bimodal condition). In the bimodal condition, the subjects’ task was to indicate visually perceived heading. Hence, here tactile stimuli were behaviorally irrelevant. In bimodal trials, I found a significant interaction of stimuli from both modalities. Visually perceived heading was biased towards tactile heading direction for an offset of up to 10° between both heading directions. The relative weighting of stimuli from both modalities in the visuo-tactile in-teraction were examined in my second behavioral study. Subjects indicated per-ceived heading from unimodal visual, unimodal tactile and bimodal trials. Here, in bimodal trials, stimuli form both modalities were presented as behaviorally rele-vant. By varying eye- relative to head position during stimulus presentation, possi-ble influences of different reference frames of the visual and tactile modality were investigated. In different sensory modalities, incoming information is encoded rela-tive to the reference system of the receiving sensory organ (e.g., relative to the reti-na in vision or relative to the skin in somatosensation). In unimodal tactile trials, heading perception was shifted towards eye-position. In bimodal trials, varying head- and eye-position had no significant effect on perceived heading: subjects indicated perceived heading based on both, the vis-ual and tactile stimulus, independently of the behavioral relevance of the tactile stimulus. In sum, results of both studies suggest that the tactile modality plays a greater role in self-motion perception than previously thought. Besides the perception of travel direction (heading), information about trav-eled speed and duration are integrated to achieve a measure of the distance trav-eled (path integration). One previous behavioral study has shown that tactile flow can be used for the reproduction of travel distance (Churan et al., 2017). However, studies on neural correlates of tactile distance encoding in humans are lacking en-tirely. In my third study, subjects solved two path integration tasks from unimodal visual and unimodal tactile self-motion stimuli. Brain activity was measured by means of functional magnetic resonance imaging (fMRI). Both tasks varied in the engagement of cognitive task demands. In the first task, subjects replicated (Active trial) a previously observed traveled distance (Passive trial) (= Reproduction task). In the second task, subjects traveled a self-chosen distance (Active trial) which was then recorded and played back to them (Passive trial) (= Self task). The predictive coding theory postulates an internal model which creates predictions about sensory outcomes-based mismatches between predictions and sensory input which enables the system to sharpen future predictions (Teufel et al., 2018). Recent studies sug-gested a synergistical interaction between prediction and cognitive demands, there-by reversing the attenuating effect of prediction. In my study, this hypothesis was tested by manipulating cognitive demands between both tasks. For both tasks, Ac-tive trials compared to Passive trials showed BOLD enhancement of early sensory cortices and suppression of higher order areas (e.g., the intraparietal lobule (IPL)). For both modalities, enhancement of early sensory areas might facilitate task solv-ing processes at hand, thereby reversing the hypothesized attenuating effect of pre-diction. Suppression of the IPL indicates this area as an amodal comparator of pre-dictions and incoming self-motion signals. In conclusion, I was able to show that tactile self-motion information, i.e., tactile flow, provides significant information for the processing of two key features of self-motion perception: Heading and path integration. Neural correlates of tactile path-integration were investigated by means of fMRI, showing similarities between visual and tactile path integration on early processing stages as well as shared neu-ral substrates in higher order areas located in the IPL. Future studies should further investigate the perception of different self-motion parameters in the tactile modali-ty to extend the understanding of this less researched – but important – modality

Perspectives on the Neuroscience of Cognition and Consciousness

The origin and current use of the concepts of computation, representation and information in Neuroscience are examined and conceptual flaws are identified which vitiate their usefulness for addressing problems of the neural basis of Cognition and Consciousness. In contrast, a convergence of views is presented to support the characterization of the Nervous System as a complex dynamical system operating in the metastable regime, and capable of evolving to configurations and transitions in phase space with potential relevance for Cognition and Consciousness

Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform

Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species

Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease

Objective Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson’s disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia. Methods Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1–3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13–20 Hz) and high (21–30 Hz) beta frequency bands and low (31–60 Hz) and high (61–100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures. Results Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side. Discussion Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes

Neuromodulation of Right Auditory Cortex Selectively Increases Activation in Speech-Related Brain Areas in Brainstem Auditory Agnosia

Auditory agnosia is an inability to make sense of sound that cannot be explained by deficits in low-level hearing. In view of recent promising results in the area of neurorehabilitation of language disorders after stroke, we examined the effect of transcranial direct current stimulation (tDCS) in a young woman with general auditory agnosia caused by traumatic injury to the left inferior colliculus. Specifically, we studied activations to sound embedded in a block design using functional magnetic resonance imaging before and after application of anodal tDCS to the right auditory cortex. Before tDCS, auditory discrimination deficits were associated with abnormally reduced activations of the auditory cortex and bilateral unresponsiveness of the anterior superior temporal sulci and gyri. This session replicated a previous functional scan with the same paradigm a year before the current experiment. We then applied anodal tDCS over right auditory cortex for 20 min-utes and immediately re-scanned the patient. We found increased activation of bilateral auditory cortices and, for speech sounds, selectively increased activation in Broca’s and Wernicke’s areas. Future research might consider the long-term behavioral effects after neurostimulation in auditory agnosia and its potential use in the neurorehabilitation of more general auditory disorders

Global neural rhythm control by local neuromodulation

Neural oscillations are a ubiquitous form of neural activity seen across scales and modalities. These neural rhythms correlate with diverse cognitive functions and brain states. One mechanism for changing the oscillatory dynamics of large neuronal populations is through neuromodulator activity. An intriguing phenomenon explored here is when local neuromodulation of a distinct neuron type within a single brain nucleus exerts a powerful influence on global cortical rhythms. One approach to investigate the impact of local circuits on global rhythms is through optogenetic techniques. My first project involves the statistical analysis of electrophysiological recordings of an optogenetically-mediated Parkinsonian phenotype. Empirical studies demonstrate that Parkinsonian motor deficits correlate with the emergence of exaggerated beta frequency (15-30 Hz) oscillations throughout the cortico-basal ganglia-thalamic network. However, the mechanism of these aberrant oscillatory dynamics is not well understood. A previous modeling study predicted that cholinergic neuromodulation of medium spiny neurons in the striatum of the basal ganglia may mediate the pathologic beta rhythm. Here, this hypothesis was tested using selective optogenetic stimulation of striatal cholinergic interneurons in normal mice; stimulation robustly and reversibly amplified beta oscillations and Parkinsonian motor symptoms. The modulation of global rhythms by local networks was further studied using computational modeling in the context of intrathalamic neuromodulation. While intrathalamic vasoactive intestinal peptide (VIP) is known to cause long-lasting excitation in vitro, its in vivo dynamical effects have not been reported. Here, biophysical computational models were used to elucidate the impact of VIP on thalamocortical dynamics during sleep and propofol general anesthesia. The modeling results suggest that VIP can form robust sleep spindle oscillations and control aspects of sleep architecture through a novel homeostatic mechanism. This homeostatic mechanism would be inhibited by general anesthesia, representing a new mechanism contributing to anesthetic-induced loss of consciousness. While the previous two projects differed in their use of empirical versus theoretical methods, a challenge common to both domains is the difficulty in visualizing and analyzing large multi-dimensional datasets. A tool to mitigate these issues is introduced here: GIMBL-Vis is a Graphical Interactive Multi-dimensional extensiBLe Visualization toolbox for Matlab. This toolbox simplifies the process of exploring multi-dimensional data in Matlab by providing a graphical interface for visualization and analysis. Furthermore, it provides an extensible open platform for distributed development by the community