The somatosensory cortex receives information about motor output

Similar neural states, but dissimilar decoding patterns for motor control in parietal cortex

Discrete neural states are associated with reaching movements across the fronto-parietal network. Here, the Hidden Markov Model (HMM) applied to spiking activity of the somato-motor parietal area PE revealed a sequence of states similar to those of the contiguous visuomotor areas PEc and V6A. Using a coupled clustering and decoding approach, we proved that these neural states carried spatiotemporal information regarding behaviour in all three posterior parietal areas. However, comparing decoding accuracy, PE was less informative than V6A and PEc. In addition, V6A outperformed PEc in target inference, indicating functional differences among the parietal areas. To check the consistency of these differences, we used both a supervised and an unsupervised variant of the HMM, and compared its performance with two more common classifiers, Support Vector Machine and Long-Short Term Memory. The differences in decoding between areas were invariant to the algorithm used, still showing the dissimilarities found with HMM, thus indicating that these dissimilarities are intrinsic in the information encoded by parietal neurons. These results highlight that, when decoding from the parietal cortex, for example, in brain machine interface implementations, attention should be paid in selecting the most suitable source of neural signals, given the great heterogeneity of this cortical sector.

The speech neuroprosthesis

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Primary somatosensory cortex organization for engineering artificial somatosensation

Somatosensory deficits from stroke, spinal cord injury, or other neurologic damage can lead to a significant degree of functional impairment. The primary (SI) and secondary (SII) somatosensory cortices encode information in a medial to lateral organization. SI is generally organized topographically, with more discrete cortical representations of specific body regions. SII regions corresponding to anatomical areas are less discrete and may represent a more functional rather than topographic organization. Human somatosensory research continues to map cortical areas of sensory processing with efforts primarily focused on hand and upper extremity information in SI. However, research into SII and other body regions is lacking. In this review, we synthesize the current state of knowledge regarding the cortical organization of human somatosensation and discuss potential applications for brain computer interface. In addition to accurate individualized mapping of cortical somatosensation, further research is required to uncover the neurophysiological mechanisms of how somatosensory information is encoded in the cortex.

Relationships between balance performance and connectivity of motor cortex with primary somatosensory cortex and cerebellum in middle aged and older adults

Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.

Predicting lever press in a vibrotactile yes/no detection task from S1 cortex of freely behaving rats by µECoG arrays

AIM OF THE STUDY

Brain-computer interfaces (BCIs) may help patients with severe neurological deficits communicate with the external world. Based on microelectrocorticography (µECoG) data recorded from the primary somatosensory cortex (S1) of unrestrained behaving rats, this study attempts to decode lever presses in a psychophysical detection task by using machine learning algorithms.

MATERIALS AND METHODS

16-channel Pt-Ir microelectrode arrays were implanted on the S1 of two rats, and µECoG was recorded during a vibrotactile yes/no detection task. For this task, the rats were trained to press the right lever when they detected the vibrotactile stimulus and the left lever when they did not. The multichannel µECoG data was analysed offline by time-frequency methods and its features were used for binary classification of the lever press at each trial. Several machine learning algorithms were tested as such.

RESULTS

The psychophysical sensitivities (A') were similar and low for both rats (0.58). Rat 2 (B'': -0.11) had higher bias for the right lever than Rat 1 (B'': - 0.01). The lever presses could be predicted with accuracies over 66% with all the tested algorithms, and the highest average accuracy (78%) was with the support vector machine.

CONCLUSION

According to the recent studies, sensory feedback increases the benefit of the BCIs. The current proof-of-concept study shows that lever presses can be decoded from the S1; therefore, this area may be utilised for a bidirectional BCI in the future.

Subthalamic Nucleus Deep Brain Stimulation Restores Motor and Sensorimotor Cortical Neuronal Oscillatory Activity in the Free-Moving 6-Hydroxydopamine Lesion Rat Parkinson Model

OBJECTIVES

Enhanced beta oscillations in cortical-basal ganglia (BG) thalamic circuitries have been linked to clinical symptoms of Parkinson's disease. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces beta band activity in BG regions, whereas little is known about activity in cortical regions. In this study, we investigated the effect of STN DBS on the spectral power of oscillatory activity in the motor cortex (MCtx) and sensorimotor cortex (SMCtx) by recording via an electrocorticogram (ECoG) array in free-moving 6-hydroxydopamine (6-OHDA) lesioned rats and sham-lesioned controls.

MATERIALS AND METHODS

Male Sprague-Dawley rats (250-350 g) were injected either with 6-OHDA or with saline in the right medial forebrain bundle, under general anesthesia. A stimulation electrode was then implanted in the ipsilateral STN, and an ECoG array was placed subdurally above the MCtx and SMCtx areas. Six days after the second surgery, the free-moving rats were individually recorded in three conditions: 1) basal activity, 2) during STN DBS, and 3) directly after STN DBS.

RESULTS

In 6-OHDA-lesioned rats (N = 8), the relative power of theta band activity was reduced, whereas activity of broad-range beta band (12-30 Hz) along with two different subbeta bands, that is, low (12-30 Hz) and high (20-30 Hz) beta band and gamma band, was higher in MCtx and SMCtx than in sham-lesioned controls (N = 7). This was, to some extent, reverted toward control level by STN DBS during and after stimulation. No major differences were found between contacts of the electrode grid or between MCtx and SMCtx.

CONCLUSION

Loss of nigrostriatal dopamine leads to abnormal oscillatory activity in both MCtx and SMCtx, which is compensated by STN stimulation, suggesting that parkinsonism-related oscillations in the cortex and BG are linked through their anatomic connections.

Task-driven neural network models predict neural dynamics of proprioception

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging

Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential features of deep learning decoders in brain activity. In this study, we examine the performance of deep learning to classify mouse behavioral states from mesoscopic cortex-wide calcium imaging data. Our convolutional neural network (CNN)-based end-to-end decoder combined with recurrent neural network (RNN) classifies the behavioral states with high accuracy and robustness to individual differences on temporal scales of sub-seconds. Using the CNN-RNN decoder, we identify that the forelimb and hindlimb areas in the somatosensory cortex significantly contribute to behavioral classification. Our findings imply that the end-to-end approach has the potential to be an interpretable deep learning method with unbiased visualization of critical brain regions.

Modulation of Motor Cortical Inhibition and Facilitation by Touch Sensation from the Glabrous Skin of the Human Hand

Touch sensation from the glabrous skin of the hand is essential for precisely controlling dexterous movements, yet the neural mechanisms by which tactile inputs influence motor circuits remain largely unexplored. By pairing air-puff tactile stimulation on the hand's glabrous skin with transcranial magnetic stimulation (TMS) over the primary motor cortex (M1), we examined the effects of tactile stimuli from single or multiple fingers on corticospinal excitability and M1's intracortical circuits. Our results showed that when we targeted the hand's first dorsal interosseous (FDI) muscle with TMS, homotopic (index finger) tactile stimulation, regardless of its point (fingertip or base), reduced corticospinal excitability. Conversely, heterotopic (ring finger) tactile stimulation had no such effect. Notably, stimulating all five fingers simultaneously led to a more pronounced decrease in corticospinal excitability than stimulating individual fingers. Furthermore, tactile stimulation significantly increased intracortical facilitation (ICF) and decreased long-interval intracortical inhibition (LICI) but did not affect short-interval intracortical inhibition (SICI). Considering the significant role of the primary somatosensory cortex (S1) in tactile processing, we also examined the effects of downregulating S1 excitability via continuous theta burst stimulation (cTBS) on tactile-motor interactions. Following cTBS, the inhibitory influence of tactile inputs on corticospinal excitability was diminished. Our findings highlight the spatial specificity of tactile inputs in influencing corticospinal excitability. Moreover, we suggest that tactile inputs distinctly modulate M1's excitatory and inhibitory pathways, with S1 being crucial in facilitating tactile-motor integration.

Reduced Cerebellar Brain Inhibition and Vibrotactile Perception in Response to Mechanical Hand Stimulation at Flutter Frequency

The cerebellum is traditionally considered a movement control structure because of its established afferent and efferent anatomical and functional connections with the motor cortex. In the last decade, studies also proposed its involvement in perception, particularly somatosensory acquisition and prediction of the sensory consequences of movement. However, compared to its role in motor control, the cerebellum's specific role or modulatory influence on other brain areas involved in sensory perception, specifically the primary sensorimotor cortex, is less clear. In the present study, we explored whether peripherally applied vibrotactile stimuli at flutter frequency affect functional cerebello-cortical connections. In 17 healthy volunteers, changes in cerebellar brain inhibition (CBI) and vibration perception threshold (VPT) were measured before and after a 20-min right hand mechanical stimulation at 25 Hz. 5 Hz mechanical stimulation of the right foot served as an active control condition. Performance in a Grooved Pegboard test (GPT) was also measured to assess stimulation's impact on motor performance. Hand stimulation caused a reduction in CBI (13.16%) and increased VPT but had no specific effect on GPT performance, while foot stimulation had no significant effect on all measures. The result added evidence to the functional connections between the cerebellum and primary motor cortex, as shown by CBI reduction. Meanwhile, the parallel increase in VPT indirectly suggests that the cerebellum influences the processing of vibrotactile stimulus through motor-sensory interactions.

Memory consolidation of sequence learning and dynamic adaptation during wakefulness

Motor learning involves acquiring new movement sequences and adapting motor commands to novel conditions. Labile motor memories, acquired through sequence learning and dynamic adaptation, undergo a consolidation process during wakefulness after initial training. This process stabilizes the new memories, leading to long-term memory formation. However, it remains unclear if the consolidation processes underlying sequence learning and dynamic adaptation are independent and if distinct neural regions underpin memory consolidation associated with sequence learning and dynamic adaptation. Here, we first demonstrated that the initially labile memories formed during sequence learning and dynamic adaptation were stabilized against interference through time-dependent consolidation processes occurring during wakefulness. Furthermore, we found that sequence learning memory was not disrupted when immediately followed by dynamic adaptation and vice versa, indicating distinct mechanisms for sequence learning and dynamic adaptation consolidation. Finally, by applying patterned transcranial magnetic stimulation to selectively disrupt the activity in the primary motor (M1) or sensory (S1) cortices immediately after sequence learning or dynamic adaptation, we found that sequence learning consolidation depended on M1 but not S1, while dynamic adaptation consolidation relied on S1 but not M1. For the first time in a single experimental framework, this study revealed distinct neural underpinnings for sequence learning and dynamic adaptation consolidation during wakefulness, with significant implications for motor skill enhancement and rehabilitation.

Decoding hand kinetics and kinematics using somatosensory cortex activity in active and passive movement

Area 2 of the primary somatosensory cortex (S1), encodes proprioceptive information of limbs. Several studies investigated the encoding of movement parameters in this area. However, the single-trial decoding of these parameters, which can provide additional knowledge about the amount of information available in sub-regions of this area about instantaneous limb movement, has not been well investigated. We decoded kinematic and kinetic parameters of active and passive hand movement during center-out task using conventional and state-based decoders. Our results show that this area can be used to accurately decode position, velocity, force, moment, and joint angles of hand. Kinematics had higher accuracies compared to kinetics and active trials were decoded more accurately than passive trials. Although the state-based decoder outperformed the conventional decoder in the active task, it was the opposite in the passive task. These results can be used in intracortical micro-stimulation procedures to provide proprioceptive feedback to BCI subjects.

Rat movements reflect internal decision dynamics in an evidence accumulation task

Perceptual decision-making involves multiple cognitive processes, including accumulation of sensory evidence, planning, and executing a motor action. How these processes are intertwined is unclear; some models assume that decision-related processes precede motor execution, whereas others propose that movements reflecting on-going decision processes occur before commitment to a choice. Here we develop and apply two complementary methods to study the relationship between decision processes and the movements leading up to a choice. The first is a free response pulse-based evidence accumulation task, in which stimuli continue until choice is reported. The second is a motion-based drift diffusion model (mDDM), in which movement variables from video pose estimation constrain decision parameters on a trial-by-trial basis. We find the mDDM provides a better model fit to rats' decisions in the free response accumulation task than traditional DDM models. Interestingly, on each trial we observed a period of time, prior to choice, that was characterized by head immobility. The length of this period was positively correlated with the rats' decision bounds and stimuli presented during this period had the greatest impact on choice. Together these results support a model in which internal decision dynamics are reflected in movements and demonstrate that inclusion of movement parameters improves the performance of diffusion-to-bound decision models.

Testing cognitive theories with multivariate pattern analysis of neuroimaging data

Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the 'how' of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions.

A high-performance neuroprosthesis for speech decoding and avatar control

Speech neuroprostheses have the potential to restore communication to people living with paralysis, but naturalistic speed and expressivity are elusive1. Here we use high-density surface recordings of the speech cortex in a clinical-trial participant with severe limb and vocal paralysis to achieve high-performance real-time decoding across three complementary speech-related output modalities: text, speech audio and facial-avatar animation. We trained and evaluated deep-learning models using neural data collected as the participant attempted to silently speak sentences. For text, we demonstrate accurate and rapid large-vocabulary decoding with a median rate of 78 words per minute and median word error rate of 25%. For speech audio, we demonstrate intelligible and rapid speech synthesis and personalization to the participant's pre-injury voice. For facial-avatar animation, we demonstrate the control of virtual orofacial movements for speech and non-speech communicative gestures. The decoders reached high performance with less than two weeks of training. Our findings introduce a multimodal speech-neuroprosthetic approach that has substantial promise to restore full, embodied communication to people living with severe paralysis.

Attenuated post-movement beta rebound reflects psychomotor alterations in major depressive disorder during a simple visuomotor task: a MEG study

BACKGROUND

Psychomotor alterations are a common symptom in patients with major depressive disorder (MDD). The primary motor cortex (M1) plays a vital role in the mechanism of psychomotor alterations. Post-movement beta rebound (PMBR) in the sensorimotor cortex is abnormal in patients with motor abnormalities. However, the changes in M1 beta rebound in patients with MDD remain unclear. This study aimed to primarily explore the relationship between psychomotor alterations and PMBR in MDD.

METHODS

One hundred thirty-two subjects were enrolled in the study, comprising 65 healthy controls (HCs) and 67 MDD patients. All participants performed a simple right-hand visuomotor task during MEG scanning. PMBR was measured in the left M1 at the source reconstruction level with the time-frequency analysis method. Retardation factor scores and neurocognitive test performance, including the Digit Symbol Substitution Test (DSST), the Making Test Part A (TMT-A), and the Verbal Fluency Test (VFT), were used to measure psychomotor functions. Pearson correlation analyses were used to assess relationships between PMBR and psychomotor alterations in MDD.

RESULTS

The MDD group showed worse neurocognitive performance than the HC group in all three neurocognitive tests. The PMBR was diminished in patients with MDD compared to HCs. In a group of MDD patients, the reduced PMBR was negatively correlated with retardation factor scores. Further, there was a positive correlation between the PMBR and DSST scores. PMBR is negatively associated with the TMT-A scores.

CONCLUSION

Our findings suggested that the attenuated PMBR in M1 could illustrate the psychomotor disturbance in MDD, possibly contributing to clinical psychomotor symptoms and deficits of cognitive functions.

Structural brain connectivity predicts early acute pain after mild traumatic brain injury

ABSTRACT

Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site-namely, conditioned pain modulation and magnitude of suprathreshold pain-and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

How the conception of control influences our understanding of actions

Wilful movement requires neural control. Commonly, neural computations are thought to generate motor commands that bring the musculoskeletal system - that is, the plant - from its current physical state into a desired physical state. The current state can be estimated from past motor commands and from sensory information. Modelling movement on the basis of this concept of plant control strives to explain behaviour by identifying the computational principles for control signals that can reproduce the observed features of movements. From an alternative perspective, movements emerge in a dynamically coupled agent-environment system from the pursuit of subjective perceptual goals. Modelling movement on the basis of this concept of perceptual control aims to identify the controlled percepts and their coupling rules that can give rise to the observed characteristics of behaviour. In this Perspective, we discuss a broad spectrum of approaches to modelling human motor control and their notions of control signals, internal models, handling of sensory feedback delays and learning. We focus on the influence that the plant control and the perceptual control perspective may have on decisions when modelling empirical data, which may in turn shape our understanding of actions.

Engaging distributed cortical and cerebellar networks through motor execution, observation, and imagery

When we interact with the environment around us, we are sometimes active participants, making directed physical motor movements and other times only mentally engaging with our environment, taking in sensory information and internally planning our next move without directed physical movement. Traditionally, cortical motor regions and key subcortical structures such as the cerebellum have been tightly linked to motor initiation, coordination, and directed motor behavior. However, recent neuroimaging studies have noted the activation of the cerebellum and wider cortical networks specifically during various forms of motor processing, including the observations of actions and mental rehearsal of movements through motor imagery. This phenomenon of cognitive engagement of traditional motor networks raises the question of how these brain regions are involved in the initiation of movement without physical motor output. Here, we will review evidence for distributed brain network activation during motor execution, observation, and imagery in human neuroimaging studies as well as the potential for cerebellar involvement specifically in motor-related cognition. Converging evidence suggests that a common global brain network is involved in both movement execution and motor observation or imagery, with specific task-dependent shifts in these global activation patterns. We will further discuss underlying cross-species anatomical support for these cognitive motor-related functions as well as the role of cerebrocerebellar communication during action observation and motor imagery.

Temporal dynamics of the sensorimotor convergence underlying voluntary limb movement

Descending motor drive and somatosensory feedback play important roles in modulating muscle activity. Numerous studies have characterized the organization of neuronal connectivity in which descending motor pathways and somatosensory afferents converge on spinal motor neurons as a final common pathway. However, how inputs from these two pathways are integrated into spinal motor neurons to generate muscle activity during actual motor behavior is unknown. Here, we simultaneously recorded activity in the motor cortices (MCx), somatosensory afferent neurons, and forelimb muscles in monkeys performing reaching and grasping movements. We constructed a linear model to explain the instantaneous muscle activity using the activity of MCx (descending input) and peripheral afferents (afferent input). Decomposition of the reconstructed muscle activity into each subcomponent indicated that muscle activity before movement onset could first be explained by descending input from mainly the primary motor cortex and muscle activity after movement onset by both descending and afferent inputs. Descending input had a facilitative effect on all muscles, whereas afferent input had a facilitative or suppressive effect on each muscle. Such antagonistic effects of afferent input can be explained by reciprocal effects of the spinal reflex. These results suggest that descending input contributes to the initiation of limb movement, and this initial movement subsequently affects muscle activity via the spinal reflex in conjunction with the continuous descending input. Thus, spinal motor neurons are subjected to temporally organized modulation by direct activation through the descending pathway and the lagged action of the spinal reflex during voluntary limb movement.

Manipulation-specific cortical activity as mice handle food

Food handling offers unique yet largely unexplored opportunities to investigate how cortical activity relates to forelimb movements in a natural, ethologically essential, and kinematically rich form of manual dexterity. To determine these relationships, we recorded high-speed (1,000 fps) video and multi-channel electrophysiological cortical spiking activity while mice handled food. The high temporal resolution of the video allowed us to decompose active manipulation ("oromanual") events into characteristic submovements, enabling event-aligned analysis of cortical activity. Activity in forelimb M1 was strongly modulated during food handling, generally higher during oromanual events and lower during holding intervals. Optogenetic silencing and stimulation of forelimb M1 neurons partially affected food-handling movements, exerting suppressive and activating effects, respectively. We also extended the analysis to forelimb S1 and lateral M1, finding broadly similar oromanual-related activity across all three areas. However, each area's activity displayed a distinct timing and phasic/tonic temporal profile, which was further analyzed by non-negative matrix factorization and demonstrated to be attributable to area-specific composition of activity classes. Current or future forelimb position could be accurately predicted from activity in all three regions, indicating that the cortical activity in these areas contains high information content about forelimb movements during food handling. These results thus establish that cortical activity during food handling is manipulation specific, distributed, and broadly similar across multiple sensorimotor areas while also exhibiting area- and submovement-specific relationships with the fast kinematic hallmarks of this natural form of complex free-object-handling manual dexterity.

Anodal transcranial direct current stimulation sustainably increases EEG alpha activity in patients with schizophrenia

Aims

Transcranial direct current stimulation (tDCS) applied to the prefrontal cortex has been frequently used to elicit behavioral changes in patients with schizophrenia. However, the interaction between prefrontal tDCS and electrophysiological changes remains largely uncharted. The present study aimed to investigate cortical electrophysiological changes induced by tDCS in frontal areas by means of repeated electroencephalography (EEG) in patients with schizophrenia.

Methods

In total, 20 patients with schizophrenia received 13 minutes of anodal tDCS (1 mA) applied to the left dorsolateral prefrontal cortex (DLPFC). Repeated resting EEG was recorded before (once) and following (at five follow‐up time‐bins) tDCS to trace post‐tDCS effects. We used sLORETA for source reconstruction to preserve the localization of brain signals with a low variance and to analyze frequency changes.

Results

We observed significant changes after the stimulation in areas highly connected with the stimulated DLPFC areas. The alpha 1 (8.5‐10.0 Hz) activity showed a highly significant, long‐lasting, increase for up to 1 hour after the stimulation in the postcentral gyrus (Brodmann area 2, 3, and 40). Significant yet unstable changes were also seen in the alpha‐2 frequency band precentral at 10 minutes, in the beta‐1 frequency band occipital at 20 minutes, and in the beta‐3 frequency band temporal at 40 minutes.

Conclusion

We were able to show that anodal tDCS can induce stable EEG changes in patients with schizophrenia. The results underline the potential of tDCS to induce long‐lasting neurophysiological changes in patients with schizophrenia showing the possibility to induce brain excitability changes in this population.

Sensorimotor Integration and Pain Perception: Mechanisms Integrating Nociceptive Processing. A Systematic Review and ALE-Meta Analysis

Pain treatment services and clinical indicators of pain chronicity focus on afferent nociceptive projections and psychological markers of pain perception with little focus on motor processes. Research supports a strong role for the motor system both in terms of pain related disability and in descending pain modulation. However, there is little understanding of the neurological regions implicated in pain-motor interactions and how the motor and sensory systems interact under conditions of pain. We performed an ALE meta-analysis on two clinical cohorts with atypical sensory and motor processes under conditions of pain and no pain. Persons with sensory altered processing (SAP) and no pain presented with greater activity in the precentral and supplementary motor area relative to persons with self-reported pain. In persons with motor altered processing (MAP), there appeared to be a suppression of activity in key pain regions such as the insula, thalamus, and postcentral gyrus. As such, activation within the motor system may play a critical role in dampening pain symptoms in persons with SAP, and in suppressing activity in key pain regions of the brain in persons with MAP. Future research endeavors should focus on understanding how sensory and motor processes interact both to understand disability and discover new treatment avenues.

Reduced asymmetry of the hand knob area and decreased sensorimotor u-fiber connectivity in middle-aged adults with autism

Individuals with autism spectrum disorder (ASD) frequently present with impairments in motor skills (e.g., limb coordination, handwriting and balance), which are observed across the lifespan but remain largely untreated. Many adults with ASD may thus experience adverse motor outcomes in aging, when physical decline naturally occurs. The 'hand knob' of the sensorimotor cortex is an area that is critical for motor control of the fingers and hands. However, this region has received little attention in ASD research, especially in adults after midlife. The hand knob area of the precentral (PrC_hand) and postcentral (PoC_hand) gyri was semi-manually delineated in 49 right-handed adults (25 ASD, 24 typical comparison [TC] participants, aged 41-70 years). Using multimodal (T1-weighted, diffusion-weighted, and resting-state functional) MRI, we examined the morphology, ipsilateral connectivity and laterality of these regions. We also explored correlations between hand knob measures with motor skills and autism symptoms, and between structural and functional connectivity measures. Bayesian analyses indicated moderate evidence of group effects with greater right PrC_hand volume and reduced leftward laterality of PrC_hand and PoC_hand volume in the ASD relative to TC group. Furthermore, the right PoC-PrC_hand u-fibers showed increased mean diffusivity in the ASD group. In the ASD group, right u-fiber volume positively correlated with corresponding functional connectivity but did not survive multiple comparisons correction. Correlations of hand knob measures and behavior were observed in the ASD group but did not survive multiple comparisons correction. Our findings suggest that morphological laterality and u-fiber connectivity of the sensorimotor network, putatively involved in hand motor/premotor function, may be diminished in middle-aged adults with ASD, perhaps rendering them more vulnerable to motor decline in old age. The altered morphology may relate to atypical functional motor asymmetries found in ASD earlier in life, possibly reflecting altered functional asymmetries over time.

Tactile perception of right middle fingertip suppresses excitability of motor cortex supplying right first dorsal interosseous muscle

The present study examined whether tactile perception of the fingertip modulates excitability of the motor cortex supplying the intrinsic hand muscle and whether this modulation is specific to the fingertip stimulated and the muscle and hand tested. Tactile stimulation was given to one of the five fingertips in the left or right hand, and transcranial magnetic stimulation eliciting motor evoked potential in the first dorsal interosseous muscle (FDI) or abductor digiti minimi was given 200 ms after the onset of tactile stimulation. The corticospinal excitability of the FDI at rest was suppressed by the tactile stimulation of the right middle fingertip, but such suppression was absent for the other fingers stimulated and for the other muscle or hand tested. The persistence and amplitude of the F-wave was not significantly influenced by tactile stimulation of the fingertip in the right hand. These findings indicate that tactile perception of the right middle fingertip suppresses excitability of the motor cortex supplying the right FDI at rest. The suppression of corticospinal excitability was absent during tonic contraction of the right FDI, indicating that the motor execution process interrupts the tactile perception-induced suppression of motor cortical excitability supplying the right FDI. These findings are in line with a view that the tactile perception of the right middle finger induces surround inhibition of the motor cortex supplying the prime mover of the finger neighboring the stimulated finger.

Somatosensory Cortex Repetitive Transcranial Magnetic Stimulation and Associative Sensory Stimulation of Peripheral Nerves Could Assist Motor and Sensory Recovery After Stroke

Background

We investigated whether transcranial magnetic stimulation (rTMS) over the primary somatosensory cortex (S1) and sensory stimulation (SS) could promote upper limb recovery in participants with subacute stroke.

Methods

Participants were randomized into four groups: rTMS/Sham SS, Sham rTMS/SS, rTMS/SS, and control group (Sham rTMS/Sham SS). Participants underwent ten sessions of sham or active rTMS over S1 (10 Hz, 1,500 pulses, 120% of resting motor threshold, 20 min), followed by sham or active SS. The SS involved active sensory training (exploring features of objects and graphesthesia, proprioception exercises), mirror therapy, and Transcutaneous electrical nerve stimulation (TENS) in the region of the median nerve in the wrist (stimulation intensity as the minimum intensity at which the participants reported paresthesia; five electrical pulses of 1 ms duration each at 10 Hz were delivered every second over 45 min). Sham stimulations occurred as follows: Sham rTMS, coil was held while disconnected from the stimulator, and rTMS noise was presented with computer loudspeakers with recorded sound from a real stimulation. The Sham SS received therapy in the unaffected upper limb, did not use the mirror and received TENS stimulation for only 60 seconds. The primary outcome was the Body Structure/Function: Fugl-Meyer Assessment (FMA) and Nottingham Sensory Assessment (NSA); the secondary outcome was the Activity/Participation domains, assessed with Box and Block Test, Motor Activity Log scale, Jebsen-Taylor Test, and Functional Independence Measure.

Results

Forty participants with stroke ischemic (n = 38) and hemorrhagic (n = 2), men (n = 19) and women (n = 21), in the subacute stage (10.6 ± 6 weeks) had a mean age of 62.2 ± 9.6 years, were equally divided into four groups (10 participants in each group). Significant somatosensory improvements were found in participants receiving active rTMS and active SS, compared with those in the control group (sham rTMS with sham SS). Motor function improved only in participants who received active rTMS, with greater effects when active rTMS was combined with active SS.

Conclusion

The combined use of SS with rTMS over S1 represents a more effective therapy for increasing sensory and motor recovery, as well as functional independence, in participants with subacute stroke.

Clinical Trial Registration

[clinicaltrials.gov], identifier [NCT03329807].

Ca2+ imaging with two-photon microscopy to detect the disruption of brain function in mice administered neonicotinoid insecticides

Neonicotinoid pesticides are a class of insecticides that reportedly have harmful effects on bees and dragonflies, causing a reduction in their numbers. Neonicotinoids act as neuroreceptor modulators, and some studies have reported their association with neurodevelopmental disorders. However, the precise effect of neonicotinoids on the central nervous system has not yet been identified. Herein, we conducted in vivo Ca²⁺ imaging using a two-photon microscope to detect the abnormal activity of neuronal circuits in the brain after neonicotinoid application. The oral administration of acetamiprid (ACE) (20 mg/kg body weight (BW) in mature mice with a quantity less than the no-observed-adverse-effect level (NOAEL) and a tenth or half of the median lethal dose (LD₅₀) of nicotine (0.33 or 1.65 mg/kg BW, respectively), as a typical nicotinic acetylcholine receptor (nAChR) agonist, increased anxiety-like behavior associated with altered activities of the neuronal population in the somatosensory cortex. Furthermore, we detected ACE and its metabolites in the brain, 1 h after ACE administration. The results suggested that in vivo Ca²⁺ imaging using a two-photon microscope enabled the highly sensitive detection of neurotoxicant-mediated brain disturbance of nerves.

Motor planning brings human primary somatosensory cortex into action-specific preparatory states

Motor planning plays a critical role in producing fast and accurate movement. Yet, the neural processes that occur in human primary motor and somatosensory cortex during planning, and how they relate to those during movement execution, remain poorly understood. Here, we used 7T functional magnetic resonance imaging and a delayed movement paradigm to study single finger movement planning and execution. The inclusion of no-go trials and variable delays allowed us to separate what are typically overlapping planning and execution brain responses. Although our univariate results show widespread deactivation during finger planning, multivariate pattern analysis revealed finger-specific activity patterns in contralateral primary somatosensory cortex (S1), which predicted the planned finger action. Surprisingly, these activity patterns were as informative as those found in contralateral primary motor cortex (M1). Control analyses ruled out the possibility that the detected information was an artifact of subthreshold movements during the preparatory delay. Furthermore, we observed that finger-specific activity patterns during planning were highly correlated to those during execution. These findings reveal that motor planning activates the specific S1 and M1 circuits that are engaged during the execution of a finger press, while activity in both regions is overall suppressed. We propose that preparatory states in S1 may improve movement control through changes in sensory processing or via direct influence of spinal motor neurons.

Quantitative characterization of the human retinotopic map based on quasiconformal mapping

The retinotopic map depicts the cortical neurons' response to visual stimuli on the retina and has contributed significantly to our understanding of human visual system. Although recent advances in high field functional magnetic resonance imaging (fMRI) have made it possible to generate the in vivo retinotopic map with great detail, quantifying the map remains challenging. Existing quantification methods do not preserve surface topology and often introduce large geometric distortions to the map. In this study, we developed a new framework based on computational conformal geometry and quasiconformal Teichmüller theory to quantify the retinotopic map. Specifically, we introduced a general pipeline, consisting of cortical surface conformal parameterization, surface-spline-based cortical activation signal smoothing, and vertex-wise Beltrami coefficient-based map description. After correcting most of the violations of the topological conditions, the result was a "Beltrami coefficient map" (BCM) that rigorously and completely characterizes the retinotopic map by quantifying the local quasiconformal mapping distortion at each visual field location. The BCM provided topological and fully reconstructable retinotopic maps. We successfully applied the new framework to analyze the V1 retinotopic maps from the Human Connectome Project (n=181), the largest state of the art retinotopy dataset currently available. With unprecedented precision, we found that the V1 retinotopic map was quasiconformal and the local mapping distortions were similar across observers. The new framework can be applied to other visual areas and retinotopic maps of individuals with and without eye diseases, and improve our understanding of visual cortical organization in normal and clinical populations.

Sensory Circuit Remodeling and Movement Recovery After Spinal Cord Injury

Restoring sensory circuit function after spinal cord injury (SCI) is essential for recovery of movement, yet current interventions predominantly target motor pathways. Integrated cortical sensorimotor networks, disrupted by SCI, are critical for perceiving, shaping, and executing movement. Corticocortical connections between primary sensory (S1) and motor (M1) cortices are critical loci of functional plasticity in response to learning and injury. Following SCI, in the motor cortex, corticocortical circuits undergo dynamic remodeling; however, it remains unknown how rehabilitation shapes the plasticity of S1-M1 networks or how these changes may impact recovery of movement.

Motor impairment evoked by direct electrical stimulation of human parietal cortex during object manipulation

In primates, the parietal cortex plays a crucial role in hand-object manipulation. However, its involvement in object manipulation and related hand-muscle control has never been investigated in humans with a direct and focal electrophysiological approach. To this aim, during awake surgery for brain tumors, we studied the impact of direct electrical stimulation (DES) of parietal lobe on hand-muscles during a hand-manipulation task (HMt). Results showed that DES applied to fingers-representation of postcentral gyrus (PCG) and anterior intraparietal cortex (aIPC) impaired HMt execution. Different types of EMG-interference patterns were observed ranging from a partial (task-clumsy) or complete (task-arrest) impairment of muscles activity. Within PCG both patterns coexisted along a medio (arrest)-lateral (clumsy) distribution, while aIPC hosted preferentially the task-arrest. The interference patterns were mainly associated to muscles suppression, more pronounced in aIPC with respect to PCG. Moreover, within PCG were observed patterns with different level of muscle recruitment, not reported in the aIPC. Overall, EMG-interference patterns and their probabilistic distribution suggested the presence of different functional parietal sectors, possibly playing different roles in hand-muscle control during manipulation. We hypothesized that task-arrest, compared to clumsy patterns, might suggest the existence of parietal sectors more closely implicated in shaping the motor output.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

Convergence of forepaw somatosensory and motor cortical projections in the striatum, claustrum, thalamus, and pontine nuclei of cats

The basal ganglia and pontocerebellar systems regulate somesthetic-guided motor behaviors and receive prominent inputs from sensorimotor cortex. In addition, the claustrum and thalamus are forebrain subcortical structures that have connections with somatosensory and motor cortices. Our previous studies in rats have shown that primary and secondary somatosensory cortex (S1 and S2) send overlapping projections to the neostriatum and pontine nuclei, whereas, overlap of primary motor cortex (M1) and S1 was much weaker. In addition, we have shown that M1, but not S1, projects to the claustrum in rats. The goal of the current study was to compare these rodent projection patterns with connections in cats, a mammalian species that evolved in a separate phylogenetic superorder. Three different anterograde tracers were injected into the physiologically identified forepaw representations of M1, S1, and S2 in cats. Labeled fibers terminated throughout the ipsilateral striatum (caudate and putamen), claustrum, thalamus, and pontine nuclei. Digital reconstructions of tracer labeling allowed us to quantify both the normalized distribution of labeling in each subcortical area from each tracer injection, as well as the amount of tracer overlap. Surprisingly, in contrast to our previous findings in rodents, we observed M1 and S1 projections converging prominently in striatum and pons, whereas, S1 and S2 overlap was much weaker. Furthermore, whereas, rat S1 does not project to claustrum, we confirmed dense claustral inputs from S1 in cats. These findings suggest that the basal ganglia, claustrum, and pontocerebellar systems in rat and cat have evolved distinct patterns of sensorimotor cortical convergence.

Articulatory Gain Predicts Motor Cortex and Subthalamic Nucleus Activity During Speech

Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson's disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.

A pilot behavioural and neuroimaging investigation on photothrombotic stroke models in rhesus monkeys

BACKGROUND

Ischemic stroke leads to a long-term disability in humans and no efficient clinical therapy exists to date. The middle cerebral artery occlusion (MCAO) model in non-human primates has shown to be of value for translational stroke research. New method In the current study, a photothrombotic (PT) stroke model was established in rhesus monkeys with either a proximal or distal segment of middle cerebral artery (MCA) thrombosis. This study is the first that compares the two approaches of PT stroke in monkeys using behavioral and physiological measurements and MRI scans.

RESULTS

The experiment found that infarct occurred in the MCA target regions, with all monkeys having impaired behavior reflected by deficits in neurologic function, and motor and cognition in object retrieval detour (ORD) task. The monkeys with distal MCA thrombosis developed with sequential photo-irritations of the Sylvian fissure zone, adjacent central anterior gyrus and central posterior gyrus, had similar impairments with respect to behavior and showed a tendency of a small edema volume with proximal MCA thrombosis at days 4 and 7 post PT stroke.

COMPARISON WITH EXISTING METHODS

The distal MCA thrombosis developed with sequential photo-irritations might provide a consistent and well-tolerated focal ischemia in rhesus monkeys, compared with other PT stroke models which usually were singly conducted on the animal's motor cortex and had a temporal effect.

CONCLUSIONS

The sequentially photo-irritated PT stroke model is a promising ischemic stroke model in rhesus monkey for studying human stroke pathology and physiology and for new therapies development.

Human Somatosensory Cortex Is Modulated during Motor Planning

Recent data and motor control theory argues that movement planning involves preparing the neural state of primary motor cortex (M1) for forthcoming action execution. Theories related to internal models, feedback control, and predictive coding also emphasize the importance of sensory prediction (and processing) before (and during) the movement itself, explaining why motor-related deficits can arise from damage to primary somatosensory cortex (S1). Motivated by this work, here we examined whether motor planning, in addition to changing the neural state of M1, changes the neural state of S1, preparing it for the sensory feedback that arises during action. We tested this idea in two human functional MRI studies (N = 31, 16 females) involving delayed object manipulation tasks, focusing our analysis on premovement activity patterns in M1 and S1. We found that the motor effector to be used in the upcoming action could be decoded, well before movement, from neural activity in M1 in both studies. Critically, we found that this effector information was also present, well before movement, in S1. In particular, we found that the encoding of effector information in area 3b (S1 proper) was linked to the contralateral hand, similarly to that found in M1, whereas in areas 1 and 2 this encoding was present in both the contralateral and ipsilateral hemispheres. Together, these findings suggest that motor planning not only prepares the motor system for movement but also changes the neural state of the somatosensory system, presumably allowing it to anticipate the sensory information received during movement.SIGNIFICANCE STATEMENT Whereas recent work on motor cortex has emphasized the critical role of movement planning in preparing neural activity for movement generation, it has not investigated the extent to which planning also modulates the activity in the adjacent primary somatosensory cortex. This reflects a key gap in knowledge, given that recent motor control theories emphasize the importance of sensory feedback processing in effective movement generation. Here, we find through a convergence of experiments and analyses, that the planning of object manipulation tasks, in addition to modulating the activity in the motor cortex, changes the state of neural activity in different subfields of the human S1. We suggest that this modulation prepares the S1 for the sensory information it will receive during action execution.

A novel rat robot controlled by electrical stimulation of the nigrostriatal pathway

OBJECTIVE

Artificial manipulation of animal movement could offer interesting advantages and potential applications using the animal's inherited superior sensation and mobility. Although several behavior control models have been introduced, they generally epitomize virtual reward-based training models. In this model, rats are trained multiple times so they can recall the relationship between cues and rewards. It is well known that activation of one side of the nigrostriatal pathway (NSP) in the rat induces immediate turning toward the contralateral side. However, this NSP stimulation-induced directional movement has not been used for the purpose of animal-robot navigation. In this study, the authors aimed to electrically stimulate the NSP of conscious rats to build a command-prompt rat robot.

METHODS

Repetitive NSP stimulation at 1-second intervals was applied via implanted electrodes to induce immediate contraversive turning movements in 7 rats in open field tests in the absence of any sensory cues or rewards. The rats were manipulated to navigate from the start arm to a target zone in either the left or right arm of a T-maze. A leftward trial was followed by a rightward trial, and each rat completed a total of 10 trials. In the control group, 7 rats were tested in the same way without NSP stimulation. The time taken to navigate the maze was compared between experimental and control groups.

RESULTS

All rats in the experimental group successfully reached the target area for all 70 trials in a short period of time with a short interstimulus interval (< 0.7 seconds), but only 41% of rats in the control group reached the target area and required a longer period of time to do so. The experimental group made correct directional turning movements at the intersection zone of the T-maze, taking significantly less time than the control group. No significant difference in navigation duration for the forward movements on the start and goal arms was observed between the two groups. However, the experimental group showed quick and accurate movement at the intersection zone, which made the difference in the success rate and elapsed time of tasks.

CONCLUSIONS

The results of this study clearly indicate that a rat-robot model based on NSP stimulation can be a practical alternative to previously reported models controlled by virtual sensory cues and rewards.

A novel somatosensory spatial navigation system outside the hippocampal formation

Spatially selective firing of place cells, grid cells, boundary vector/border cells and head direction cells constitutes the basic building blocks of a canonical spatial navigation system centered on the hippocampal-entorhinal complex. While head direction cells can be found throughout the brain, spatial tuning outside the hippocampal formation is often non-specific or conjunctive to other representations such as a reward. Although the precise mechanism of spatially selective firing activity is not understood, various studies show sensory inputs, particularly vision, heavily modulate spatial representation in the hippocampal-entorhinal circuit. To better understand the contribution of other sensory inputs in shaping spatial representation in the brain, we performed recording from the primary somatosensory cortex in foraging rats. To our surprise, we were able to detect the full complement of spatially selective firing patterns similar to that reported in the hippocampal-entorhinal network, namely, place cells, head direction cells, boundary vector/border cells, grid cells and conjunctive cells, in the somatosensory cortex. These newly identified somatosensory spatial cells form a spatial map outside the hippocampal formation and support the hypothesis that location information modulates body representation in the somatosensory cortex. Our findings provide transformative insights into our understanding of how spatial information is processed and integrated in the brain, as well as functional operations of the somatosensory cortex in the context of rehabilitation with brain-machine interfaces.

Cerebellar Purkinje cells can differentially modulate coherence between sensory and motor cortex depending on region and behavior

Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1-M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1-M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior.

Parallel and Serial Sensory Processing in Developing Primary Somatosensory and Motor Cortex

It is generally supposed that primary motor cortex (M1) receives somatosensory input predominantly via primary somatosensory cortex (S1). However, a growing body of evidence indicates that M1 also receives direct sensory input from the thalamus, independent of S1; such direct input is particularly evident at early ages before M1 contributes to motor control. Here, recording extracellularly from the forelimb regions of S1 and M1 in unanesthetized rats at postnatal day (P)8 and P12, we compared S1 and M1 responses to self-generated (i.e., reafferent) forelimb movements during active sleep and wake, and to other-generated (i.e., exafferent) forelimb movements. At both ages, reafferent responses were processed in parallel by S1 and M1; in contrast, exafferent responses were processed in parallel at P8 but serially, from S1 to M1, at P12. To further assess this developmental difference in processing, we compared exafferent responses to proprioceptive and tactile stimulation. At both P8 and P12, proprioceptive stimulation evoked parallel responses in S1 and M1, whereas tactile stimulation evoked parallel responses at P8 and serial responses at P12. Independent of the submodality of exafferent stimulation, pairs of S1-M1 units exhibited greater coactivation during active sleep than wake. These results indicate that S1 and M1 independently develop somatotopy before establishing the interactive relationship that typifies their functionality in adults.SIGNIFICANCE STATEMENT Learning any new motor task depends on the ability to use sensory information to update motor outflow. Thus, to understand motor learning, we must also understand how animals process sensory input. Primary somatosensory cortex (S1) and primary motor cortex (M1) are two interdependent structures that process sensory input throughout life. In adults, the functional relationship between S1 and M1 is well established; however, little is known about how S1 and M1 begin to transmit or process sensory information in early life. In this study, we investigate the early development of S1 and M1 as a sensory processing unit. Our findings provide new insights into the fundamental principles of sensory processing and the development of functional connectivity between these important sensorimotor structures.

Prenatal methadone exposure disrupts behavioral development and alters motor neuron intrinsic properties and local circuitry

Despite the rising prevalence of methadone treatment in pregnant women with opioid use disorder, the effects of methadone on neurobehavioral development remain unclear. We developed a translational mouse model of prenatal methadone exposure (PME) that resembles the typical pattern of opioid use by pregnant women who first use oxycodone then switch to methadone maintenance pharmacotherapy, and subsequently become pregnant while maintained on methadone. We investigated the effects of PME on physical development, sensorimotor behavior, and motor neuron properties using a multidisciplinary approach of physical, biochemical, and behavioral assessments along with brain slice electrophysiology and in vivo magnetic resonance imaging. Methadone accumulated in the placenta and fetal brain, but methadone levels in offspring dropped rapidly at birth which was associated with symptoms and behaviors consistent with neonatal opioid withdrawal. PME produced substantial impairments in offspring physical growth, activity in an open field, and sensorimotor milestone acquisition. Furthermore, these behavioral alterations were associated with reduced neuronal density in the motor cortex and a disruption in motor neuron intrinsic properties and local circuit connectivity. The present study adds to the limited body of work examining PME by providing a comprehensive, translationally relevant characterization of how PME disrupts offspring physical and neurobehavioral development.

Cortical Thickness Alterations in Patients With Tinnitus Before and After Sound Therapy: A Surface-Based Morphometry Study

This study aimed to explore brain surface-based morphometry cortical thickness changes in patients with idiopathic tinnitus before and after 24 weeks of sound therapy. In this prospective observational study, we recruited 33 tinnitus patients who had undergone 24 weeks of sound therapy and 26 matched healthy controls. For the two groups of subjects, a 3D-BRAVO pulse sequence was acquired both at baseline and at the 24th week. Structural image data preprocessing was performed using the DPABISurf toolbox. The Tinnitus Handicap Inventory (THI) score was assessed to determine the severity of tinnitus before and after treatment. Two-way mixed-model analysis of variance (ANOVA) and Pearson’s correlation analysis were used in the statistical analysis. Student–Newman–Keuls (SNK) tests were used in the post hoc analysis. Significantly lower cortical thickness was found in the left somatosensory and motor cortex (SMC), left posterior cingulate cortex (PCC), and right orbital and polar frontal cortex (OPFC) of the participants in the tinnitus group at baseline than in the participants in the HC group at baseline and after 24 weeks; in the tinnitus group, significantly higher cortical thickness was found after the 24 weeks sound therapy in comparison to the baseline in the left SMC, bilateral superior parietal cortex (SPC), left inferior parietal cortex (IPC), left PCC, and right OPFC. In the HC group, no statistically significant difference in cortical thickness was found after the 24 weeks treatment in comparison to the baseline in the bilateral SMC, bilateral SPC, left IPC, left PCC, or right OPFC. The changes in cortical thickness before and after sound therapy can provide certain reference values for clinical tinnitus treatment. These brain regions could serve as potential targets for neuroimaging.

Different activation signatures in the primary sensorimotor and higher-level regions for haptic three-dimensional curved surface exploration

Haptic object perception begins with continuous exploratory contact, and the human brain needs to accumulate sensory information continuously over time. However, it is still unclear how the primary sensorimotor cortex (PSC) interacts with these higher-level regions during haptic exploration over time. This functional magnetic resonance imaging (fMRI) study investigates time-dependent haptic object processing by examining brain activity during haptic 3D curve and roughness estimations. For this experiment, we designed sixteen haptic stimuli (4 kinds of curves × 4 varieties of roughness) for the haptic curve and roughness estimation tasks. Twenty participants were asked to move their right index and middle fingers along the surface twice and to estimate one of the two features-roughness or curvature-depending on the task instruction. We found that the brain activity in several higher-level regions (e.g., the bilateral posterior parietal cortex) linearly increased as the number of curves increased during the haptic exploration phase. Surprisingly, we found that the contralateral PSC was parametrically modulated by the number of curves only during the late exploration phase but not during the early exploration phase. In contrast, we found no similar parametric modulation activity patterns during the haptic roughness estimation task in either the contralateral PSC or in higher-level regions. Thus, our findings suggest that haptic 3D object perception is processed across the cortical hierarchy, whereas the contralateral PSC interacts with other higher-level regions across time in a manner that is dependent upon the features of the object.

Reversal of Visual Feedback Modulates Somatosensory Plasticity

Reversed visual feedback during unimanual training increases transfer of skills to the opposite untrained hand and modulates plasticity in motor areas of the brain. However, it is unclear if unimanual training with reversed visual feedback also affects somatosensory areas. Here we manipulated visual input during unimanual training using left-right optical reversing spectacles and tested whether unimanual training with reversed vision modulates somatosensory cortical excitability to facilitate motor performance. Thirty participants practiced a unimanual ball-rotation task using the right hand with either left-right reversed vision (incongruent visual and somatosensory feedback) or direct vision (congruent feedback) of the moving hand. We estimated cortical excitability in primary somatosensory cortex (S1) before and after unimanual training by measuring somatosensory evoked potentials (SEPs). This was done by electrically stimulating the median nerve in the wrist while participants rested, and recording potentials over both hemispheres using electroencephalography. Performance of the ball-rotation task improved for both the right (trained) and left (untrained) hand after training across both direct and reversed vision conditions. Participants with direct vision of the right hand during training showed SEPs amplitudes increased bilaterally. In contrast, participants in the reversed visual condition showed attenuated SEPs following training. The results suggest that cortical suppression of S1 activity supports skilled motor performance after unimanual training with reversed vision, presumably by sensory gating of afferent signals from the movement. This finding provides insight into the mechanisms by which visual input interacts with the sensorimotor system and induces neuroplastic changes in S1 to support skilled motor performance.

The brain and behavioral correlates of motor-related analgesia (MRA)

The human motor system has the capacity to act as an internal form of analgesia. Since the discovery of the potential influence of motor systems on analgesia in rodent models, clinical applications of targeting the motor system for analgesia have been implemented. However, a neurobiological basis for motor activation's effects on analgesia is not well defined. Motor-related analgesia (MRA) is a phenomenon wherein a decrease in pain symptoms can be achieved through either indirect or direct activation of the motor axis. To date, research has focused on (a) evaluating the pain-motor interaction as one focused on the acute protection from painful stimuli; (b) motor cortex stimulation for chronic pain; or (c) exercise as a method of improving chronic pain in animal and human models. This review evaluates (1) current knowledge surrounding how pain interferes with canonical neurological performance throughout the motor axis; and (2) the physiological basis for motor-related analgesia as a means to reduce pain symptom loads for patients. A proposal for future research directions is provided.

Sensory gating and suppression of subjective peripheral sensations during voluntary muscle contraction

BACKGROUND

During voluntary muscle contraction, sensory information induced by electrostimulation of the nerves supplying the contracting muscle is inhibited and the somatosensory evoked potentials (SEPs) amplitude decreases. This depression of sensory input during voluntary muscle contraction has been demonstrated by many studies using electrophysiological methods. However, the association between the electrophysiological response of the sensory system during sustained muscle contraction and subjective peripheral sensation (SPS) is still unclear. The aim of this study was to investigate changes in spinal excitability, SEPs, and SPS during voluntary muscle contraction.

RESULTS

The appearance rate of the F-wave was significantly higher during muscle contraction than rest, whereas no significant difference was observed in F-wave latency between muscle contraction and rest. Furthermore, the P25 amplitude of SEPs was significantly lower during muscle contraction than rest, whereas the N20 amplitude of SEPs exhibited no significant differences. The SPS was significantly lower during muscle contraction than rest CONCLUSIONS: We conclude that sensory gating, which is found in the P25 component of SEPs during muscle contraction, is one of the neurophysiological mechanisms underlying the suppression of SPS.

Beta Rebound as an Index of Temporal Integration of Somatosensory and Motor Signals

Modulation of cortical beta rhythm (15–30 Hz) is present during preparation for and execution of voluntary movements as well as during somatosensory stimulation. A rebound in beta synchronization is observed after the end of voluntary movements as well as after somatosensory stimulation and is believed to describe the return to baseline of sensorimotor networks. However, the contribution of efferent and afferent signals to the beta rebound remains poorly understood. Here, we applied electrical median nerve stimulation (MNS) to the right side followed by transcranial magnetic stimulation (TMS) on the left primary motor cortex after either 15 or 25 ms. Because the afferent volley reaches the somatosensory cortex after about 20 ms, TMS on the motor cortex was either anticipating or following the cortical arrival of the peripheral stimulus. We show modulations in different beta sub-bands and in both hemispheres, following a pattern of greater resynchronization when motor signals are paired with a peripheral one. The beta rebound in the left hemisphere (stimulated) is modulated in its lower frequency range when TMS precedes the cortical arrival of the afferent volley. In the right hemisphere (unstimulated), instead, the increase is limited to higher beta frequencies when TMS is delivered after the arrival of the afferent signal. In general, we demonstrate that the temporal integration of afferent and efferent signals plays a key role in the genesis of the beta rebound and that these signals may be carried in parallel by different beta sub-bands.

Sensory Feedback in Upper Limb Amputees Impacts Cortical Activity as Revealed by Multiscale Connectivity Analysis

Sensory feedback in upper limb amputees is crucial for improving movement decoding and also to enhance embodiment of the prosthetic limb. Recently, an increasing number of invasive and noninvasive solutions for sensory stimulation have demonstrated the capability of providing a range of sensations to upper limb amputees. However, the cortical impact of restored sensation is not clearly understood. Particularly, understanding the cortical connectivity changes at multiple scales (nodal and modular) in response to sensory stimulation, can reveal crucial information on how amputees brain process the sensory stimuli. Using Electroencephalography (EEG) signals, we compared the cortical connectivity network in response to sensory feedback provided by targeted transcutaneous electrical nerve stimulation (tTENS) in an upper limb amputee during phantom upper limb movements. We focused our cortical connectivity analysis on four functional modules comprising of 20 brain regions that are primarily associated with a visually guided motor task (visual, motor, somatosensory and multisensory integration (MI)) used in this study. At the modular level, we observed that the hubness (a graph theoretic measure quantifying the importance of brain regions in integrating brain function) of the motor module decreases whereas that of the somatosensory module increases in presence of tTENS feedback. At the nodal level, similar observations were made for the visual and MI regions. This is the first work to reveal the impact of sensory feedback at multiple scales in the cortex of amputees in response to sensory stimulation.

A stacked sparse auto-encoder and back propagation network model for sensory event detection via a flexible ECoG

Current prostheses are limited in their ability to provide direct sensory feedback to users with missing limb. Several efforts have been made to restore tactile sensation to amputees but the somatotopic tactile feedback often results in unnatural sensations, and it is yet unclear how and what information the somatosensory system receives during voluntary movement. The present study proposes an efficient model of stacked sparse autoencoder and back propagation neural network for detecting sensory events from a highly flexible electrocorticography (ECoG) electrode. During the mechanical stimulation with Von Frey (VF) filament on the plantar surface of rats' foot, simultaneous recordings of tactile afferent signals were obtained from primary somatosensory cortex (S1) in the brain. In order to achieve a model with optimal performance, Particle Swarm Optimization and Adaptive Moment Estimation (Adam) were adopted to select the appropriate number of neurons, hidden layers and learning rate of each sparse auto-encoder. We evaluated the stimulus-evoked sensation by using an automated up-down (UD) method otherwise called UDReader. The assessment of tactile thresholds with VF shows that the right side of the hind-paw was significantly more sensitive at the tibia-(p = 6.50 × 10^-4), followed by the saphenous-(p = 7.84 × 10^-4), and sural-(p = 8.24 × 10^-4). We then validated our proposed model by comparing with the state-of-the-art methods, and recorded accuracy of 98.8%, sensitivity of 96.8%, and specificity of 99.1%. Hence, we demonstrated the effectiveness of our algorithms in detecting sensory events through flexible ECoG recordings which could be a viable option in restoring somatosensory feedback.

Altered Topological Patterns of Gray Matter Networks in Tinnitus: A Graph-Theoretical-Based Study

Objective

Tinnitus is a prevalent hearing disorder, which could have a devastating impact on a patient’s life. Functional studies have revealed connectivity pattern changes in the tinnitus brains that suggested a change of network dynamics as well as topological organization. However, no studies have yet provided evidence for the topological network changes in the gray matter. In this research, we aim to use the graph-theoretical approach to investigate the changes of topology in the tinnitus brain using structural MRI data, which could provide insights into the underlying anatomical basis for the neural mechanism in generating phantom sounds.

Methods

We collected 3D MRI images on 46 bilateral tinnitus patients and 46 age and gender-matched healthy controls. Brain networks were constructed with correlation matrices of the cortical thickness and subcortical volumes of 80 cortical/subcortical regions of interests. Global network properties were analyzed using local and global efficiency, clustering coefficient, and small-world coefficient, and regional network properties were evaluated using the betweenness coefficient for hub connectivity, and interregional correlations for edge properties. Between-group differences in cortical thickness and subcortical volumes were assessed using independent sample t-tests, and local efficiency, global efficiency, clustering coefficient, sigma, and interregional correlation were compared using non-parametric permutation tests.

Results

Tinnitus was found to have increased global efficiency, local efficiency, and cluster coefficient, indicating generally heightened connectivity of the network. The small-world coefficient remained normal for tinnitus, indicating intact small-worldness. Betweenness centrality analysis showed that hubs in the amygdala and parahippocampus were only found for tinnitus but not controls. In contrast, hubs in the auditory cortex, insula, and thalamus were only found for controls but not tinnitus. Interregional correlation analysis further found in tinnitus enhanced connectivity between the auditory cortex and prefrontal lobe, and decreased connectivity of the insula with anterior cingulate gyrus and parahippocampus.

Conclusion

These findings provided the first morphological evidence of altered topological organization of the brain networks in tinnitus. These alterations suggest that heightened efficiency of the brain network and altered auditory-limbic connection for tinnitus, which could be developed in compensation for the auditory deafferentation, leading to overcompensation and, ultimately, an emotional and cognitive burden.