Modulation Of Neural Activity Research Articles

Modulation of neural activity in response to dance training in Parkinson’s: A case study

Modulation of neural activity in response to dance training in Parkinson’s: A case study

Modulatory Effects on Laminar Neural Activity Induced by Near-Infrared Light Stimulation with a Continuous Waveform to the Mouse Inferior Colliculus In Vivo.

Infrared neural stimulation (INS) is a promising area of interest for the clinical application of a neuromodulation method. This is in part because of its low invasiveness, whereby INS modulates the activity of the neural tissue mainly through temperature changes. Additionally, INS may provide localized brain stimulation with less tissue damage. The inferior colliculus (IC) is a crucial auditory relay nucleus and a potential target for clinical application of INS to treat auditory diseases and develop artificial hearing devices. Here, using continuous INS with low to high-power density, we demonstrate the laminar modulation of neural activity in the mouse IC in the presence and absence of sound. We investigated stimulation parameters of INS to effectively modulate the neural activity in a facilitatory or inhibitory manner. A mathematical model of INS-driven brain tissue was first simulated, temperature distributions were numerically estimated, and stimulus parameters were selected from the simulation results. Subsequently, INS was administered to the IC of anesthetized mice, and the modulation effect on the neural activity was measured using an electrophysiological approach. We found that the modulatory effect of INS on the spontaneous neural activity was bidirectional between facilitatory and inhibitory effects. The modulatory effect on sound-evoked responses produced only an inhibitory effect to all examined stimulus intensities. Thus, this study provides important physiological evidence on the response properties of IC neurons to INS. Overall, INS can be used for the development of new therapies for neurological disorders and functional support devices for auditory central processing.

Stress increases hepatic release of lipocalin 2 which contributes to anxiety-like behavior in mice.

Chronic stress induces anxiety disorders via both neural pathways and circulating factors. Although many studies have elucidated the neural circuits involved in stress-coping behaviors, the origin and regulatory mechanism of peripheral cytokines in behavioural regulation under stress conditions are not fully understood. Here, we identified a serum cytokine, lipocalin 2 (LCN2), that was upregulated in participants with anxiety disorders. Using a mouse model of chronic restraint stress (CRS), circulating LCN2 was found to be related to stress-induced anxiety-like behaviour via modulation of neural activity in the medial prefrontal cortex (mPFC). These results suggest that stress increases hepatic LCN2 via a neural pathway, leading to disrupted cortical functions and behaviour.

Modulatory effects of low-intensity retinal ultrasound stimulation on rapid and non-rapid eye movement sleep.

Prior investigations have established that the manipulation of neural activity has the potential to influence both rapid eye movement and non-rapid eye movement sleep. Low-intensity retinal ultrasound stimulation has shown effectiveness in the modulation of neural activity. Nevertheless, the specific effects of retinal ultrasound stimulation on rapid eye movement and non-rapid eye movement sleep, as well as its potential to enhance overall sleep quality, remain to be elucidated. Here, we found that: In healthy mice, retinal ultrasound stimulation: (i) reduced total sleep time and non-rapid eye movement sleep ratio; (ii) changed relative power and sample entropy of the delta (0.5-4Hz) in non-rapid eye movement sleep; and (iii) enhanced relative power of the theta (4-8Hz) and reduced theta-gamma coupling strength in rapid eye movement sleep. In Alzheimer's disease mice with sleep disturbances, retinal ultrasound stimulation: (i) reduced the total sleep time; (ii) altered the relative power of the gamma band during rapid eye movement sleep; and (iii) enhanced the coupling strength of delta-gamma in non-rapid eye movement sleep and weakened the coupling strength of theta-fast gamma. The results indicate that retinal ultrasound stimulation can modulate rapid eye movement and non-rapid eye movement-related neural activity; however, it is not beneficial to the sleep quality of healthy and Alzheimer's disease mice.

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and of the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.

Development and application of implantable electrical neural electrodes

Implantable nerve electrodes are a crucial neuro-engineering device that can play a pivotal role in the treatment of various neurological disorders. As the fundamental unit of the nervous system, neurons possess the capability to generate electrical signals, which serve as the primary means of information transmission. Implantable neural electrodes have the capacity to intercept and record these electrical signals, thereby providing invaluable insights into understanding nervous system functionality. Furthermore, these electrodes enable precise modulation of neural activity through targeted delivery of pulses to neurons. Surgical implantation of these electrodes within the nervous system allows for simulation or inhibition of neural signals with therapeutic objectives in mind. This article comprehensively reviews the significance and application of implantable neural electrodes in neuro-engineering while highlighting their immense potential in enhancing patients quality of life across diverse neurological conditions With further research and technological improvements, we can expect implantable neural electrodes to play an even greater role in improving the quality of life of patients, treating neurological diseases, and advancing neuroscience.

Bursting activity in the reduced mean-field model of neuron-glial interaction

The study of neural activity synchronization in the brain is a central focus of modern neurobiology and neurodynamics. In a healthy brain, cognitive functions necessitate the accurate integration of neural activity at specific spatiotemporal scales. Some neurological and psychiatric disorders exhibit observable variations in patterns of synchronous population activity. One of the most significant and compelling synchronous population activity patterns is the bursting activity that participates in various informational and physiological processes, including epilepsy. Several mathematical models have been proposed to explain the mechanisms of formation of the bursting activity. The most intriguing and scientifically sound models enable incorporation of astrocytic modulation of neural activity [1]. In this paper, we present a novel phenomenological model for accurately replicating the bursting neural population activity. Our model builds upon the Tsodyks-Markram [2] model and incorporates vital aspects of neuron-glial interaction through a tripartite synapse. The presented model is a simplified version of the previously proposed model [3]. During astrocyte activity (which lasts seconds), we can set the probability of neurotransmitter release, u, which is determined in fractions of a second. This enables the proposed model to be written in the following manner: r=–E+α ln(1+exp((Ju(Y)xE+I0)/α)), =(1–x)/τD–u(Y)xE, =–y/τY+βσy(X). Here, E(t) represents the average neuronal activity of the excitatory population, while x(t) denotes the quantity of available neurotransmitter. Additionally, y(t) describes the concentration of gliotransmitters, which are released as a result of biochemical reactions during neuron-astrocyte interactions. The function describes the alteration in the likelihood of neurotransmitter release when gliotransmitters are present u(y)=u0+(∆u0)/(1+exp(–50(y–ythr)). Here u0 represents the probability of neurotransmitter release without astrocytic influence; ∆u0 indicates the change in the probability of neurotransmitter release caused by the interaction of the gliotransmitter with the presynaptic terminal, and ythr represents the threshold value that determines the change in the probability of neurotransmitter release due to the effect of a gliotransmitter. The function describes the influence of neurotransmitter on the concentration of the gliotransmitter σy(x)=1/(1+exp(–20(x–xthr)), where xthr is the astrocyte activation threshold. Note that the proposed model does not account for synaptic depression’s mechanism. Therefore, various dynamical regimes’ formation in the model is solely controlled by astrocytic dynamics. In the study, control parameters I0 and u0 were selected while the remaining parameters were held constant. Specifically, τ=0.013, τD=0.08, α=1.58, J=3.07. Changes in the concentration of neurotransmitters and gliotransmitters were characterized by parameters ∆u0=0.305, τν=3.3, β=0.3, xxthr=0.75, ythr=0.4. The research was conducted using computer modeling and numerical methods in nonlinear dynamics. The proposed model exhibits a diverse range of population activity patterns, such as spiking and bursting regular and chaotic activity. Chaotic dynamics zones are identified in the control parameter plane. An account is given of the mechanisms behind the emergence of these activity patterns through bifurcation analysis. It is shown that the occurrence of chaotic activity in the system can be associated both with the cascade of period doubling bifurcations and with the further development of chaos, as a result of which a homoclinic attractor appears in the system according to the Shilnikov scenario. It was also shown that multistability is observed in the system in a certain range of parameters. Note that the emergence of multistability and bursting activity in the model is independent of the intricacy of neuron and glial cell dynamics. These dynamics are instead influenced by the feedback loop between the presynaptic neuron and the glial cell. The effects of neuron-like dynamics and neural-glial interaction demonstrated are generally applicable, without specifying particular characteristics of neural-glial interaction, network architecture, or single-cell neuron dynamics. It should be noted that our proposed model solely concerns the potentiation of synaptic transmission by astrocytes. In summary, the proposed phenomenological model for population activity can replicate various patterns of neuron activity found in a wide range of dynamic memory and information processing studies. This research can potentially lead to the development of new, effective treatment methods for neurological diseases that involve neuron-glial interaction. Another potential application for these results is in the development of an optimized live chip that has preset functions. This requires a deeper understanding of rhythmogenesis in neural networks and brain function.

Research Progress on Effects of Ginsenoside Rg2 and Rh1 on Nervous System and Related Mechanisms

Neurological-related disorders are diseases that affect the body’s neurons or peripheral nerve tissue, such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). The development of neurological disorders can cause serious harm to the quality of life and functioning of the patient. The use of traditional therapeutic agents such as dopamine-promoting drugs, anticholinergic drugs, cholinesterase inhibitors, and NMDA receptor antagonists is often accompanied by a series of side effects such as drug resistance, cardiac arrhythmia, liver function abnormalities, and blurred vision. Therefore, there is an urgent need to find a therapeutic drug with a high safety profile and few side effects. Herbal medicines are rich in active ingredients that are natural macromolecules. Ginsenoside is the main active ingredient of ginseng, which has a variety of pharmacological effects and is considered to have potential value in the treatment of human diseases. Modern pharmacological studies have shown that ginsenosides Rg2 and Rh1 have strong pharmacological activities in the nervous system, with protective effects on nerve cells, improved resistance to neuronal injury, modulation of neural activity, resistance to cerebral ischemia/reperfusion injury, improvement of brain damage after eclampsia hemorrhage, improvement of memory and cognitive deficits, treatment of AD and vascular dementia, alleviation of anxiety, pain, and inhibition of ionic-like behavior. In this article, we searched the pharmacological research literature of Rg2 and Rh1 in the field of neurological diseases, summarized the latest research progress of the two ginsenosides, and reviewed the pharmacological effects and mechanisms of Rg2 and Rh1, which provided a new way of thinking for the research of the active ingredients in ginseng anti-neurological diseases and the development of new drugs.

Functional Magnetic Resonance Imaging Signatures of Pavlovian and Instrumental Valuation Systems during a Modified Orthogonalized Go/No-go Task.

Motivational (i.e., Pavlovian) values interfere with instrumental responding and can lead to suboptimal decision-making. In humans, task-based neuroimaging studies have only recently started illuminating the functional neuroanatomy of Pavlovian biasing of instrumental control. To provide a mechanistic understanding of the neural dynamics underlying the Pavlovian and instrumental valuation systems, analysis of neuroimaging data has been informed by computational modeling of conditioned behavior. Nonetheless, because of collinearities in Pavlovian and instrumental predictions, previous research failed to tease out hemodynamic activity that is parametrically and dynamically modulated by coexistent Pavlovian and instrumental value expectations. Moreover, neural correlates of Pavlovian to instrumental transfer effects have so far only been identified in extinction (i.e., in the absence of learning). In this study, we devised a modified version of the orthogonalized go/no-go paradigm, which introduced Pavlovian-only catch trials to better disambiguate trial-by-trial Pavlovian and instrumental predictions in both sexes. We found that hemodynamic activity in the ventromedial pFC covaried uniquely with the model-derived Pavlovian value expectations. Notably, modulation of neural activity encoding for instrumental predictions in the supplementary motor cortex was linked to successful action selection in conflict conditions. Furthermore, hemodynamic activity in regions pertaining to the limbic system and medial pFC was correlated with synergistic Pavlovian and instrumental predictions and improved conditioned behavior during congruent trials. Altogether, our results provide new insights into the functional neuroanatomy of decision-making and corroborate the validity of our variant of the orthogonalized go/no-go task as a behavioral assay of the Pavlovian and instrumental valuation systems.

Closed‐Loop Optogenetic Modulation of Neural Activities in Freely Moving Mice with Multimodal Fibers

AbstractThe precise manipulation of neural activity is of great significance to reveal the function of complex neural circuits in brain, especially the mechanism of neurological disorders such as epilepsy, Parkinson's, and Alzheimer's disease. In the past decades, optogenetics has become a powerful tool to investigate the function of neural circuits due to its unique advantages of cell specificity and high spatiotemporal resolution. However, to date, most optogenetic manipulation has been conducted in an open‐loop fashion. The closed‐loop neural modulation is still an important task. Here, a closed‐loop optogenetic modulation system is developed for ultra‐fast, ‐accurate, and ‐stable manipulation of neural activities in behaving mice. Specifically, this system is mediated by a functional fiber probe with excellent low optical loss (0.052 dB cm−1 at 589 nm) and electrical impedance (5.40 MΩ µm−2 at 1 kHz). In vivo electrophysiology and behavioral experiments demonstrated that the system can be successfully applied for the identification and intervention of seizures in epilepsy mice with high efficiency. It is envision that the closed‐loop manipulation system has promising applications in brain science, neuroscience, and neuromodulation therapies.

Editorial: 90th anniversary of the Sherrington and Adrian Nobel Prize: brain rhythms and oscillations in neural activity modulation, brain function and dysfunction

Editorial: 90th anniversary of the Sherrington and Adrian Nobel Prize: brain rhythms and oscillations in neural activity modulation, brain function and dysfunction

Computational assessment of visual coding across mouse brain areas and behavioural states.

Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions. To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks. Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states. Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states.

A Versatile Strategy for Genetic Manipulation of Cajal-Retzius Cells in the Adult Mouse Hippocampus.

Cajal-Retzius (CR) cells are transient neurons with long-lasting effects on the architecture and circuitry of the neocortex and hippocampus. Contrary to the prevailing assumption that CR cells completely disappear in rodents shortly after birth, a substantial portion of these cells persist in the hippocampus throughout adulthood. The role of these surviving CR cells in the adult hippocampus is largely unknown, partly because of the paucity of suitable tools to dissect their functions in the adult versus the embryonic brain. Here, we show that genetic crosses of the ΔNp73-Cre mouse line, widely used to target CR cells, to reporter mice induce reporter expression not only in CR cells, but also progressively in postnatal dentate gyrus granule neurons. Such a lack of specificity may confound studies of CR cell function in the adult hippocampus. To overcome this, we devise a method that not only leverages the temporary CR cell-targeting specificity of the ΔNp73-Cre mice before the first postnatal week, but also capitalizes on the simplicity and effectiveness of freehand neonatal intracerebroventricular injection of adeno-associated virus. We achieve robust Cre-mediated recombination that remains largely restricted to hippocampal CR cells from early postnatal age to adulthood. We further demonstrate the utility of this method to manipulate neuronal activity of CR cells in the adult hippocampus. This versatile and scalable strategy will facilitate experiments of CR cell-specific gene knockdown and/or overexpression, lineage tracing, and neural activity modulation in the postnatal and adult brain.

Flexible, Transparent, and Cytocompatible Nanostructured Indium Tin Oxide Thin Films for Bio-optoelectronic Applications.

Electrical stimulation has been used successfully for several decades for the treatment of neurodegenerative disorders, including motor disorders, pain, and psychiatric disorders. These technologies typically rely on the modulation of neural activity through the focused delivery of electrical pulses. Recent research, however, has shown that electrically triggered neuromodulation can be further enhanced when coupled with optical stimulation, an approach that can benefit from the development of novel electrode materials that combine transparency with excellent electrochemical and biological performance. In this study, we describe an electrochemically modified, nanostructured indium tin oxide/poly(ethylene terephthalate) (ITO/PET) surface as a flexible, transparent, and cytocompatible electrode material. Electrochemical oxidation and reduction of ITO/PET electrodes in the presence of an ionic liquid based on d-glucopyranoside and bistriflamide units were performed, and the electrochemical behavior, conductivity, capacitance, charge transport processes, surface morphology, optical properties, and cytocompatibility were assessed in vitro. It has been shown that under selected conditions, electrochemically modified ITO/PET films remained transparent and highly conductive and were able to enhance neural cell survival and neurite outgrowth. Consequently, electrochemical modification of ITO/PET electrodes in the presence of an ionic liquid is introduced as an effective approach for tailoring the properties of ITO for advanced bio-optoelectronic applications.

Regulation of mouse exploratory behaviour by irradiance and cone-opponent signals

BackgroundAnimal survival depends on the ability to adjust behaviour according to environmental conditions. The circadian system plays a key role in this capability, with diel changes in the quantity (irradiance) and spectral content (‘colour’) of ambient illumination providing signals of time-of-day that regulate the timing of rest and activity. Light also exerts much more immediate effects on behaviour, however, that are equally important in shaping daily activity patterns. Hence, nocturnal mammals will actively avoid light and dramatically reduce their activity when light cannot be avoided. The sensory mechanisms underlying these acute effects of light are incompletely understood, particularly the importance of colour.ResultsTo define sensory mechanisms controlling mouse behaviour, we used photoreceptor-isolating stimuli and mice with altered cone spectral sensitivity (Opn1mwR), lacking melanopsin (Opn1mwR; Opn4−/−) or cone phototransduction (Cnga3−/−) in assays of light-avoidance and activity suppression. In addition to roles for melanopsin-dependent irradiance signals, we find a major influence of spectral content in both cases. Hence, remarkably, selective increases in S-cone irradiance (producing a blue-shift in spectrum replicating twilight) drive light-seeking behaviour and promote activity. These effects are opposed by signals from longer-wavelength sensitive cones, indicating a true spectrally-opponent mechanism. Using c-Fos-mapping and multielectrode electrophysiology, we further show these effects are associated with a selective cone-opponent modulation of neural activity in the key brain site implicated in acute effects of light on behaviour, the subparaventricular zone.ConclusionsCollectively, these data reveal a mechanism whereby blue-shifts in the spectrum of environmental illumination, such as during twilight, promote mouse exploratory behaviour.

Spontaneous dyadic behavior predicts the emergence of interpersonal neural synchrony

Synchronization of neural activity across brains – Interpersonal Neural Synchrony (INS) – is emerging as a powerful marker of social interaction that predicts success of multi-person coordination, communication, and cooperation. As the origins of INS are poorly understood, we tested whether and how INS might emerge from spontaneous dyadic behavior. We recorded neural activity (EEG) and human behavior (full-body kinematics, eye movements, and facial expressions) while dyads of participants were instructed to look at each other without speaking or making co-verbal gestures. We made four fundamental observations. First, despite the absence of a structured social task, INS emerged spontaneously only when participants were able to see each other. Second, we show that such spontaneous INS, comprising specific spectral and topographic profiles, did not merely reflect intra-personal modulations of neural activity, but it rather reflected real-time and dyad-specific coupling of neural activities. Third, using state-of-art video-image processing and deep learning, we extracted the temporal unfolding of three notable social behavioral cues – body movement, eye contact, and smiling – and demonstrated that these behaviors also spontaneously synchronized within dyads. Fourth, we probed the correlates of INS in such synchronized social behaviors. Using cross-correlation and Granger causality analyses, we show that synchronized social behaviors anticipate and in fact Granger cause INS. These results provide proof-of-concept evidence for studying interpersonal neural and behavioral synchrony under natural and unconstrained conditions. Most importantly, the results suggest that INS could be conceptualized as an emergent property of two coupled neural systems: an entrainment phenomenon, promoted by real-time dyadic behavior.

Advancements in the Clinical Outcomes of Functional Neurosurgery With Deep Brain Stimulation for Movement Disorders: A Literature Review.

This literature review explores recent advancements in deep brain stimulation (DBS) surgery for movement disorders. It highlights notable improvements, including closed-loop stimulation techniques, optogenetics, and improved surgical targeting. Positive clinical outcomes with low complication rates and improved motor symptoms are consistently reported. The review emphasizes the importance of minimizing risks through meticulous surgical practices and discussespotentialcomplications associated with DBS surgery. Future prospects focus on enhancing technology, refining surgical techniques, and conducting further research. Closed-loop stimulation optimizes DBS efficacy by tailoring stimulation parameters to individual patient needs. Optogenetics offers precise modulation of neural activity with light-sensitive proteins, enabling more targeted treatments. Cybersecurity measures are essential due to the integration of wireless and digital technologies in DBS systems. DBS surgery has significantly improved the management of movement disorders with its safety and effectiveness. Ongoing research in closed-loop stimulation, optogenetics, and cybersecurity is expected to further enhance DBS technology and outcomes, benefiting patients with treatment-resistant movement disorders.

Cortico-ocular coupling in the service of episodic memory formation

Encoding of visual information is a necessary requirement for most types of episodic memories. In search for a neural signature of memory formation, amplitude modulation of neural activity has been repeatedly shown to correlate with and suggested to be functionally involved in successful memory encoding. We here report a complementary view on why and how brain activity relates to memory, indicating a functional role of cortico-ocular interactions for episodic memory formation. Recording simultaneous magnetoencephalography and eye tracking in 35 human participants, we demonstrate that gaze variability and amplitude modulations of alpha/beta oscillations (10–20 Hz) in visual cortex covary and predict subsequent memory performance between and within participants. Amplitude variation during pre-stimulus baseline was associated with gaze direction variability, echoing the co-variation observed during scene encoding. We conclude that encoding of visual information engages unison coupling between oculomotor and visual areas in the service of memory formation.

Are single-peaked tuning curves tuned for speed rather than accuracy?

According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment, given some biophysical constraints. In early visual areas, stimulus-induced modulations of neural activity (or tunings) are predominantly single-peaked. However, periodic tuning, as exhibited by grid cells, has been linked to a significant increase in decoding performance. Does this imply that the tuning curves in early visual areas are sub-optimal? We argue that the time scale at which neurons encode information is imperative to understanding the advantages of single-peaked and periodic tuning curves. Here, we show that the possibility of catastrophic (large) errors creates a trade-off between decoding time and decoding ability. We investigate how decoding time and stimulus dimensionality affect the optimal shape of tuning curves for removing catastrophic errors. In particular, we focus on the spatial periods of the tuning curves for a class of circular tuning curves. We show an overall trend for minimal decoding time to increase with increasing Fisher information, implying a trade-off between accuracy and speed. This trade-off is reinforced whenever the stimulus dimensionality is high, or there is ongoing activity. Thus, given constraints on processing speed, we present normative arguments for the existence of the single-peaked tuning organization observed in early visual areas.

Effect of lower limb exoskeleton on the modulation of neural activity and gait classification.

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (RAGT) with a brain-machine interface (BMI) represents an important step in this direction but requires better elucidation of the effect of RAGT on the user's neural modulation. Here, we investigated how different exoskeleton walking modes modify brain and muscular activity during exoskeleton assisted gait. We recorded electroencephalographic (EEG) and electromyographic (EMG) activity from ten able-bodied volunteers walking with an exoskeleton with three modes of user assistance (i.e., transparent, adaptive and full assistance) and during free overground gait. Results identified that exoskeleton walking (irrespective of the exoskeleton mode) induces a stronger modulation of central mid-line mu (8-13 Hz) and low-beta (14-20 Hz) rhythms compared to free overground walking. These modifications are accompanied by a significant re-organization of the EMG patterns in exoskeleton walking. On the other hand, we observed no significant differences in neural activity during exoskeleton walking with the different assistance levels. We subsequently implemented four gait classifiers based on deep neural networks trained on the EEG data during the different walking conditions. Our hypothesis was that exoskeleton modes could impact the creation of a BMI-driven RAGT. We demonstrated that all classifiers achieved an average accuracy of 84.13 ± 3.49% in classifying swing and stance phases on their respective datasets. In addition, we demonstrated that the classifier trained on the transparent mode exoskeleton data can classify gait phases during adaptive and full modes with an accuracy of 78.3 ± 4.8%, while the classifier trained on free overground walking data fails to classify the gait during exoskeleton walking (accuracy of 59.4 ± 11.8%). These findings provide important insights into the effect of robotic training on neural activity and contribute to the advancement of BMI technology for improving robotic gait rehabilitation therapy.