Cortical plasticity: from synapses to maps

Biophysical parameters control signal transfer in spiking network

Introduction

Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer.

Methods

The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error.

Results

Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates.

Discussion

Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.

Amblyopia: A review of unmet needs, current treatment options, and emerging therapies

Amblyopia is a global public health issue with extensive, multifaceted impacts on vision and quality of life (QoL) for both patients and families. Geographical variation exists in the management of amblyopia, with traditional mainstay treatments, optical correction, and fellow eye occlusion most successful when implemented at an early age. In recent years, however, studies demonstrating meaningful improvements in older children and adults have challenged the concept of a complete loss of visual processing plasticity beyond the critical period of visual development, with growing evidence supporting the potential efficacy of emerging, more engaging, binocular therapies in both adults and children. Binocular approaches aim to restore deficits in amblyopia that extend beyond monocular visual acuity impairment, including binocular fusion and visuomotor skills. In view of this, incorporating outcome measures that evaluate the visual performance and functional ability of individuals with amblyopia will provide a clearer understanding of the effect of amblyopia on QoL and a more comprehensive evaluation of amblyopia therapies.

Adaptive control of synaptic plasticity integrates micro- and macroscopic network function

Synaptic plasticity configures interactions between neurons and is therefore likely to be a primary driver of behavioral learning and development. How this microscopic-macroscopic interaction occurs is poorly understood, as researchers frequently examine models within particular ranges of abstraction and scale. Computational neuroscience and machine learning models offer theoretically powerful analyses of plasticity in neural networks, but results are often siloed and only coarsely linked to biology. In this review, we examine connections between these areas, asking how network computations change as a function of diverse features of plasticity and vice versa. We review how plasticity can be controlled at synapses by calcium dynamics and neuromodulatory signals, the manifestation of these changes in networks, and their impacts in specialized circuits. We conclude that metaplasticity-defined broadly as the adaptive control of plasticity-forges connections across scales by governing what groups of synapses can and can't learn about, when, and to what ends. The metaplasticity we discuss acts by co-opting Hebbian mechanisms, shifting network properties, and routing activity within and across brain systems. Asking how these operations can go awry should also be useful for understanding pathology, which we address in the context of autism, schizophrenia and Parkinson's disease.

Complex pattern of facial remapping in somatosensory cortex following congenital but not acquired hand loss

Cortical remapping after hand loss in the primary somatosensory cortex (S1) is thought to be predominantly dictated by cortical proximity, with adjacent body parts remapping into the deprived area. Traditionally, this remapping has been characterised by changes in the lip representation, which is assumed to be the immediate neighbour of the hand based on electrophysiological research in non-human primates. However, the orientation of facial somatotopy in humans is debated, with contrasting work reporting both an inverted and upright topography. We aimed to fill this gap in the S1 homunculus by investigating the topographic organisation of the face. Using both univariate and multivariate approaches we examined the extent of face-to-hand remapping in individuals with a congenital and acquired missing hand (hereafter one-handers and amputees, respectively), relative to two-handed controls. Participants were asked to move different facial parts (forehead, nose, lips, tongue) during functional MRI (fMRI) scanning. We first confirmed an upright face organisation in all three groups, with the upper-face and not the lips bordering the hand area. We further found little evidence for remapping of both forehead and lips in amputees, with no significant relationship to the chronicity of their phantom limb pain (PLP). In contrast, we found converging evidence for a complex pattern of face remapping in congenital one-handers across multiple facial parts, where relative to controls, the location of the cortical neighbour - the forehead - is shown to shift away from the deprived hand area, which is subsequently more activated by the lips and the tongue. Together, our findings demonstrate that the face representation in humans is highly plastic, but that this plasticity is restricted by the developmental stage of input deprivation, rather than cortical proximity.

Systematic determination of muscle groups and optimal stimulation intensity for simultaneous TMS mapping of multiple muscles in the upper limb

Transcranial magnetic stimulation has been used to assess plastic changes in the cortical motor representations of targeted muscles. The present study explored the optimal settings and stimulation intensity for simultaneous motor mapping of multiple upper-limb muscles across segments. In 15 healthy volunteers, we evaluated cortical representations simultaneously from one muscle in the shoulder, two in the upper arm, two in the forearm, and two intrinsic hand muscles, using five stimulation intensities, ranging from 40% to 100% of the maximum stimulator output. We represented the motor map area acquired at each intensity as a percentage of the maximum for each muscle. We defined a motor map area between 25% and 75% of the maximum as the optimal area size with sufficient scope for both up- and down-regulation, and stimulation intensities producing the map area size within this range as the optimal intensities. We found that motor maps with optimal area sizes could be produced simultaneously for the four distal muscles of the forearm and hand in most participants when the stimulation intensity was set at 120-140% of the resting motor threshold (RMT) of the first dorsal interosseous. For the remaining three proximal muscles, motor maps with optimal area sizes were produced only in a few participants, even when using a higher intensity (180-220% RMT). These findings suggest that cortical representations can be assessed simultaneously in a group of distal muscles using a relatively low stimulation intensity, while a separate operation is required to assess that of the proximal muscles.

Memory decay and generalization following distinct motor learning mechanisms

Motor skill learning is considered to arise out of contributions from multiple learning mechanisms, including error-based learning (EBL), use-dependent learning (UDL), and reinforcement learning (RL). These learning mechanisms exhibit dissociable roles and engage different neural circuits during skill acquisition. However, it remains largely unknown how a newly formed motor memory acquired through each learning mechanism decays over time and whether distinct learning mechanisms produce different generalization patterns. Here, we used variants of reaching paradigms that dissociated these learning mechanisms to examine the time course of memory decay following each learning and the generalization patterns of each learning. We found that motor memories acquired through these learning mechanisms decayed as a function of time. Notably, 15 min, 6 h, and 24 h after acquisition, the memory of EBL decayed much greater than that of RL. The memory acquired through UDL faded away within a few minutes. Motor memories formed through EBL and RL for given movement directions generalized to untrained movement directions, with the generalization of EBL being greater than that of RL. In contrast, motor memory of UDL could not generalize to untrained movement directions. These results suggest that distinct learning mechanisms exhibit different patterns of memory decay and generalization.NEW & NOTEWORTHY Motor skill learning is likely to involve error-based learning, use-dependent plasticity, and operant reinforcement. Here, we showed that these dissociable learning mechanisms exhibited distinct patterns of memory decay and generalization. With a better understanding of the characteristics of these learning mechanisms, it becomes possible to regulate each learning process separately to improve neurological rehabilitation.

Visual experience has opposing influences on the quality of stimulus representation in adult primary visual cortex

Transient dark exposure, typically 7–10 days in duration, followed by light reintroduction is an emerging treatment for improving the restoration of vision in amblyopic subjects whose occlusion is removed in adulthood. Dark exposure initiates homeostatic mechanisms that together with light-induced changes in cellular signaling pathways result in the re-engagement of juvenile-like plasticity in the adult such that previously deprived inputs can gain cortical territory. It is possible that dark exposure itself degrades visual responses, and this could place constraints on the optimal duration of dark exposure treatment. To determine whether eight days of dark exposure has a lasting negative impact on responses to classic grating stimuli, neural activity was recorded before and after dark exposure in awake head-fixed mice using two-photon calcium imaging. Neural discriminability, assessed using classifiers, was transiently reduced following dark exposure; a decrease in response reliability across a broad range of spatial frequencies likely contributed to the disruption. Both discriminability and reliability recovered. Fixed classifiers were used to demonstrate that stimulus representation rebounded to the original, pre-deprivation state, thus dark exposure did not appear to have a lasting negative impact on visual processing. Unexpectedly, we found that dark exposure significantly stabilized orientation preference and signal correlation. Our results reveal that natural vision exerts a disrupting influence on the stability of stimulus preference for classic grating stimuli and, at the same time, improves neural discriminability for both low and high-spatial frequency stimuli.

Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules

Cortical networks have the remarkable ability to self-assemble into dynamic regimes in which excitatory positive feedback is balanced by recurrent inhibition. This inhibition-stabilized regime is increasingly viewed as the default dynamic regime of the cortex, but how it emerges in an unsupervised manner remains unknown. We prove that classic forms of homeostatic plasticity are unable to drive recurrent networks to an inhibition-stabilized regime due to the well-known paradoxical effect. We next derive a novel family of cross-homeostatic rules that lead to the unsupervised emergence of inhibition-stabilized networks. These rules shed new light on how the brain may reach its default dynamic state and provide a valuable tool to self-assemble artificial neural networks into ideal computational regimes.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (W_E←E, W_E←I, W_I←E, and W_I←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of “cross-homeostatic” rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how—beginning from a silent network—self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

Neuropeptide S promotes maintenance of newly formed dendritic spines and performance improvement after motor learning in mice

Neuropeptide S (NPS), an endogenous neuropeptide consisting of 20 amino acids, selectively binds and activates G protein-coupled receptor named neuropeptide S receptor (NPSR) to regulate a variety of physiological functions. NPS/NPSR system has been shown to play a pivotal role in regulating learning and memory in rodents. However, it remains unclear that how NPS/NPSR system affects neuronal functions and synaptic plasticity after learning. We found that intracerebroventricular (i.c.v.) injection of NPS promoted performance improvement and reduced sleep duration after motor learning, which could be blocked by pre-treatment with intraperitoneal (i.p.) injection of NPSR antagonist SHA 68. Using intravital two-photon imaging, we examined the effect of NPS on the postsynaptic dendritic spines of layer V pyramidal neurons in the mouse primary motor cortex after motor learning. We found that i.c.v. injection of NPS strengthened learning-induce new spines and facilitated their survival over time. Furthermore, i.c.v. injection of NPS increased calcium activity of apical dendrites and dendritic spines of layer V pyramidal neurons in the mouse primary motor cortex during the running period. These findings suggest that activation of NPSR by NPS increases synaptic calcium activity and learning-related synapse maintenance, thereby contributing to performance improvement after motor learning.

Synaptic Plasticity Is Predicted by Spatiotemporal Firing Rate Patterns and Robust to In Vivo-like Variability

Synaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we investigate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a plasticity rule based on calcium dynamics. Using in vivo spike train recordings as inputs to different size clusters of spines, we show that plasticity is strongly robust to trial-to-trial variability of spike timing. In addition, we derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Synapses that strongly potentiated have greater firing rates and calcium concentration later in the trial, whereas strongly depressing synapses have hiring firing rates early in the trial. The neighboring synaptic activity influences the direction and magnitude of synaptic plasticity, with small clusters of spines producing the greatest increase in synaptic strength. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.

Sensory Integration Disorders in Patients with Multiple Sclerosis

Sensory integration disorder (SID) is also called, interchangeably, sensory processing disorder (SPD). Multiple sclerosis (MS) is an autoimmune, chronic, neurological disease of the central nervous system. Sensorimotor function disorders are present in both multiple sclerosis and SID. The study aimed to assess the SID among patients with MS and included 141 patients with relapse-remitting MS and 72 participants in the control group. To assess SID in both groups, a questionnaire prepared by Daniel Travis was used. Additionally, participants answered questions regarding their age, gender, handedness and in the study group about the duration of the disease, relapses in the past year and the advancement of the disease using EDSS. The occurrence of sensory seeking was significantly more frequent in the MS patients with relapses in the past year. Patients with MS had more often general disorders of sensory integration in the past. However, healthy subjects significantly more often showed the severity of social and emotional disorders in the past. Currently, the group of MS patients has a greater intensity of sensor-based motor abilities. The study revealed more severe SID in MS patients than in the control group. Still, more research is needed in this field.

Effect of cortical extracellular GABA on motor response

To elucidate how the flattening of sensory tuning due to a deficit in tonic inhibition slows motor responses, we simulated a neural network model in which a sensory cortical network ([Formula: see text]) and a motor cortical network ([Formula: see text]) are reciprocally connected, and the [Formula: see text] projects to spinal motoneurons (Mns). The [Formula: see text] was presented with a feature stimulus and the reaction time of Mns was measured. The flattening of sensory tuning in [Formula: see text] caused by decreasing the concentration of gamma-aminobutyric acid (GABA) in extracellular space resulted in a decrease in the stimulus-sensitive [Formula: see text] pyramidal cell activity while increasing the stimulus-insensitive [Formula: see text] pyramidal cell activity, thereby prolonging the reaction time of Mns to the applied feature stimulus. We suggest that a reduction in extracellular GABA concentration in sensory cortex may interfere with selective activation in motor cortex, leading to slowing the activation of spinal motoneurons and therefore to slowing motor responses.

Limited Pairings of Electrical Micro-stimulation of the Ventral Tegmental Area and a Visual Stimulus Enhance Visual Cortical Responses

Previous studies demonstrated that pairing a visual stimulus and electrical micro-stimulation of the ventral tegmental area (VTA-EM) for multiple days is sufficient to induce visual cortical plasticity and changes perception. However, a brief epoch of VTA-EM-stimulus pairing within a single day has been shown to result in a behavioral preference for the paired stimulus. Here, we investigated whether a brief single-day session of VTA-EM-stimulus pairings is sufficient to induce changes in visual cortical responses. We examined macaque posterior inferior temporal (PIT) cortex because previous studies demonstrated response changes after VTA-EM stimulus pairing in that area. Multi-unit recordings in PIT were interleaved with VTA-EM-stimulus pairing epochs. During the short VTA-EM-stimulus pairing epochs (60 pairings), one image (fractal) was paired with VTA-EM (STIM) whereas another, unpaired fractal was presented as control. Two other fractals (dummies) were presented only during the recordings. The difference in response between the STIM and control fractals already increased after the first VTA-EM-stimulus pairing epoch, reflecting a relative increase of the response to the STIM fractal. However, the response to the STIM fractal did not increase further with more VTA-EM-stimulus pairing epochs. The relative increase in firing rate for the paired fractal was present early in the response, in line with a local/ bottom-up origin. These effects were absent when comparing the responses to the dummies pre- and post-VTA-EM. This study shows that pairing a visual image and VTA-EM in a brief single-day session is sufficient to increase the response for the paired image in macaque PIT.

Efficacy of contralaterally controlled functional electrical stimulation compared to cyclic neuromuscular electrical stimulation and task-oriented training for recovery of hand function after stroke: study protocol for a multi-site randomized controlled trial

BACKGROUND

Multi-site studies in stroke rehabilitation are important for determining whether a technology and/or treatment can be successfully administered by sites other than the originating site and with similar positive outcomes. This study is the first multi-site clinical trial of a novel intervention for post-stroke upper limb rehabilitation called contralaterally controlled functional electrical stimulation (CCFES). Previous pilot and single-site studies showed positive effects of CCFES on upper limb impairment and hand dexterity in stroke survivors. The main purpose of this study is to confirm and demonstrate the efficacy of CCFES in a larger group of most likely responders across multiple clinical sites.

METHODS

Up to 129 stroke survivors with moderate to severe upper extremity hemiparesis at 4 clinical trial sites will be randomized to CCFES, cyclic neuromuscular electrical stimulation (cNMES), or task-oriented-training (TOT). Participants will receive 12 weeks of group-specific therapy. Blinded assessments of upper limb impairment and activity limitation, quality of life, and neurophysiology will be used to compare outcomes at baseline, after treatment, and up to 6 months post-treatment. The primary endpoint is change in dexterity from baseline to 6 months post-treatment.

DISCUSSION

Loss of hand function following stroke is a major rehabilitation problem affecting millions of people per year globally. More effective rehabilitation therapies are needed to restore hand function in these individuals. This study will determine whether CCFES therapy produces greater improvements in upper extremity function than cNMES or TOT, and will begin to elucidate the different mechanisms underlying each of the three treatments. This multi-site study is a critical step in advancing a novel method of rehabilitation toward clinical translation and widespread dissemination.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03574623 . Registered prior to first enrollment; July 2, 2018.

Brain and spinal cord paired stimulation coupled with locomotor training affects polysynaptic flexion reflex circuits in human spinal cord injury

Neurorecovery from locomotor training is well established in human spinal cord injury (SCI). However, neurorecovery resulting from combined interventions has not been widely studied. In this randomized clinical trial, we established the tibialis anterior (TA) flexion reflex modulation pattern when transcranial magnetic stimulation (TMS) of the primary motor cortex was paired with transcutaneous spinal cord (transspinal) stimulation over the thoracolumbar region during assisted step training. Single pulses of TMS were delivered either before (TMS-transspinal) or after (transspinal-TMS) transspinal stimulation during the stance phase of the less impaired leg. Eight individuals with chronic incomplete or complete SCI received at least 20 sessions of paired stimulation during assisted step training. Each session consisted of 240 paired stimuli delivered over 10-min blocks for 1 h during robotic-assisted step training with the Lokomat6 Pro^®. Body weight support, leg guidance force and treadmill speed were adjusted based on each participant's ability to step without knee buckling or toe dragging. Both the early and late TA flexion reflex remained unaltered after TMS-transspinal and locomotor training. In contrast, the early and late TA flexion reflexes were significantly depressed during stepping after transspinal-TMS and locomotor training. Reflex changes occurred at similar slopes and intercepts before and after training. Our findings support that targeted brain and spinal cord stimulation coupled with locomotor training reorganizes the function of flexion reflex pathways, which are a part of locomotor networks, in humans with varying levels of sensorimotor function after SCI.Trial registration number NCT04624607; Registered on November 12, 2020.

The impact of musical training in symbolic and non-symbolic audiovisual judgements of magnitude

Quantity estimation can be represented in either an analog or symbolic manner and recent evidence now suggests that analog and symbolic representation of quantities interact. Nonetheless, those two representational forms of quantities may be enhanced by convergent multisensory information. Here, we elucidate those interactions using high-density electroencephalography (EEG) and an audiovisual oddball paradigm. Participants were presented simultaneous audiovisual tokens in which the co-varying pitch of tones was combined with the embedded cardinality of dot patterns. Incongruencies were elicited independently from symbolic and non-symbolic modality within the audio-visual percept, violating the newly acquired rule that “the higher the pitch of the tone, the larger the cardinality of the figure.” The effect of neural plasticity in symbolic and non-symbolic numerical representations of quantities was investigated through a cross-sectional design, comparing musicians to musically naïve controls. Individual’s cortical activity was reconstructed and statistically modeled for a predefined time-window of the evoked response (130–170 ms). To summarize, we show that symbolic and non-symbolic processing of magnitudes is re-organized in cortical space, with professional musicians showing altered activity in motor and temporal areas. Thus, we argue that the symbolic representation of quantities is altered through musical training.

Intrinsic excitability mechanisms of neuronal ensemble formation

Neuronal ensembles are coactive groups of cortical neurons, found in spontaneous and evoked activity, that can mediate perception and behavior. To understand the mechanisms that lead to the formation of ensembles, we co-activated layer 2/3 pyramidal neurons in brain slices from mouse visual cortex, in animals of both sexes, replicating in vitro an optogenetic protocol to generate ensembles in vivo. Using whole-cell and perforated patch-clamp pair recordings we found that, after optogenetic or electrical stimulation, coactivated neurons increased their correlated activity, a hallmark of ensemble formation. Coactivated neurons showed small biphasic changes in presynaptic plasticity, with an initial depression followed by a potentiation after a recovery period. Optogenetic and electrical stimulation also induced significant increases in frequency and amplitude of spontaneous EPSPs, even after single-cell stimulation. In addition, we observed unexpected strong and persistent increases in neuronal excitability after stimulation, with increases in membrane resistance and reductions in spike threshold. A pharmacological agent that blocks changes in membrane resistance reverted this effect. These significant increases in excitability can explain the observed biphasic synaptic plasticity. We conclude that cell-intrinsic changes in excitability are involved in the formation of neuronal ensembles. We propose an ‘iceberg’ model, by which increased neuronal excitability makes subthreshold connections suprathreshold, enhancing the effect of already existing synapses, and generating a new neuronal ensemble.

In the brain, groups of neurons that are activated together – also known as neuronal ensembles – are the basic units that underpin perception and behavior. Yet, exactly how these coactive circuits are established remains under investigation.

In 1949, Canadian psychologist Donald Hebb proposed that, when brains learn something new, the neurons which are activated together connect to form ensembles, and their connections become stronger each time this specific piece of knowledge is recalled. This idea that ‘neurons that fire together, wire together’ can explain how memories are acquired and recalled, by strengthening their wiring.

However, recent studies have questioned whether strengthening connections is the only mechanism by which neural ensembles can be created. Changes in the excitability of neurons (how easily they are to fire and become activated) may also play a role. In other words, ensembles could emerge because certain neurons become more excitable and fire more readily.

To solve this conundrum, Alejandre-García et al. examined both hypotheses in the same system. Neurons in slices of the mouse visual cortex were stimulated electrically or optically, via a technique that controls neural activity with light. The activity of individual neurons and their connections was then measured with electrodes.

Spontaneous activity among connected neurons increased after stimulation, indicative of the formation of neuronal ensembles. Connected neurons also showed small changes in the strength of their connections, which first decreased and then rebounded after an initial recovery period.

Intriguingly, cells also showed unexpected strong and persistent increases in neuronal excitability after stimulation, such that neurons fired more readily to the same stimulus. In other words, neurons maintained a cellular memory of having been stimulated. The authors conclude that ensembles form because connected neurons become more excitable, which in turn, may strengthen connections of the circuit at a later stage.

These results provide fresh insights about the neural circuits underpinning learning and memory. In time, the findings could also help to understand disorders such as Alzheimer’s disease and schizophrenia, which are characterised by memory impairments and disordered thinking.

Malleability of the cortical hand map following a finger nerve block

Electrophysiological studies in monkeys show that finger amputation triggers local remapping within the deprived primary somatosensory cortex (S1). Human neuroimaging research, however, shows persistent S1 representation of the missing hand's fingers, even decades after amputation. Here, we explore whether this apparent contradiction stems from underestimating the distributed peripheral and central representation of fingers in the hand map. Using pharmacological single-finger nerve block and 7-tesla neuroimaging, we first replicated previous accounts (electrophysiological and other) of local S1 remapping. Local blocking also triggered activity changes to nonblocked fingers across the entire hand area. Using methods exploiting interfinger representational overlap, however, we also show that the blocked finger representation remained persistent despite input loss. Computational modeling suggests that both local stability and global reorganization are driven by distributed processing underlying the topographic map, combined with homeostatic mechanisms. Our findings reveal complex interfinger representational features that play a key role in brain (re)organization, beyond (re)mapping.

Temporally and functionally distinct large-scale brain network dynamics supporting task switching

Objective:

Our daily activities require frequent switches among competing responses at the millisecond time scale. We determined the spatiotemporal characteristics and functional significance of rapid, large-scale brain network dynamics during task switching.

Methods:

This cross-sectional study investigated patients with drug-resistant focal epilepsy who played a Lumosity cognitive flexibility training game during intracranial electroencephalography (iEEG) recording. According to a given task rule, unpredictably switching across trials, participants had to swipe the screen in the direction the stimulus was pointing or moving. Using this data, we described the spatiotemporal characteristics of iEEG high-gamma augmentation occurring more intensely during switch than repeat trials, unattributable to the effect of task rule (pointing or moving), within-stimulus congruence (the direction of stimulus pointing and moving was same or different in a given trial), or accuracy of an immediately preceding response. Diffusion-weighted imaging (DWI) tractography determined whether distant cortical regions showing enhanced activation during task switch trials were directly connected by white matter tracts. Trial-by-trial iEEG analysis deduced whether the intensity of task switch-related high-gamma augmentation was altered through practice and whether high-gamma amplitude predicted the accuracy of an upcoming response among switch trials.

Results:

The average number of completed trials during five-minute gameplay was 221.4 per patient (range: 171–285). Task switch trials increased the response times, whereas later trials reduced them. Analysis of iEEG signals sampled from 860 brain sites effectively elucidated the distinct spatiotemporal characteristics of task switch, task rule, and post-error-specific high-gamma modulations. Post-cue, task switch-related high-gamma augmentation was initiated in the right calcarine cortex after 260 ms, right precuneus after 330 ms, right entorhinal after 420 ms, and bilateral anterior middle-frontal gyri after 450 ms. DWI tractography successfully showed the presence of direct white matter tracts connecting the right visual areas to the precuneus and anterior middle-frontal regions but not between the right precuneus and anterior middle-frontal regions. Task-related high-gamma amplitudes in later trials were reduced in the calcarine, entorhinal and anterior middle-frontal regions, but increased in the precuneus. Functionally, enhanced post-cue precuneus high-gamma augmentation improved the accuracy of subsequent responses among switch trials.

Conclusions:

Our multimodal analysis uncovered two temporally and functionally distinct network dynamics supporting task switching. High-gamma augmentation in the visual-precuneus pathway may reflect the neural process facilitating an attentional shift to a given updated task rule. High-gamma activity in the visual-dorsolateral prefrontal pathway, rapidly reduced through practice, may reflect the cost of executing appropriate stimulus-response translation.

How Does the Central Nervous System for Posture and Locomotion Cope With Damage-Induced Neural Asymmetry?

In most vertebrates, posture and locomotion are achieved by a biomechanical apparatus whose effectors are symmetrically positioned around the main body axis. Logically, motor commands to these effectors are intrinsically adapted to such anatomical symmetry, and the underlying sensory-motor neural networks are correspondingly arranged during central nervous system (CNS) development. However, many developmental and/or life accidents may alter such neural organization and acutely generate asymmetries in motor operation that are often at least partially compensated for over time. First, we briefly present the basic sensory-motor organization of posturo-locomotor networks in vertebrates. Next, we review some aspects of neural plasticity that is implemented in response to unilateral central injury or asymmetrical sensory deprivation in order to substantially restore symmetry in the control of posturo-locomotor functions. Data are finally discussed in the context of CNS structure-function relationship.

From Hemispheric Asymmetry through Sensorimotor Experiences to Cognitive Outcomes in Children with Cerebral Palsy

Recent neuroimaging studies allowed us to explore abnormal brain structures and interhemispheric connectivity in children with cerebral palsy (CP). Behavioral researchers have long reported that children with CP exhibit suboptimal performance in different cognitive domains (e.g., receptive and expressive language skills, reading, mental imagery, spatial processing, subitizing, math, and executive functions). However, there has been very limited cross-domain research involving these two areas of scientific inquiry. To stimulate such research, this perspective paper proposes some possible neurological mechanisms involved in the cognitive delays and impairments in children with CP. Additionally, the paper examines the ways motor and sensorimotor experience during the development of these neural substrates could enable more optimal development for children with CP. Understanding these developmental mechanisms could guide more effective interventions to promote the development of both sensorimotor and cognitive skills in children with CP.

Stimulus-Selective Response Plasticity in Primary Visual Cortex: Progress and Puzzles

Stimulus-selective response plasticity (SRP) is a robust and lasting modification of primary visual cortex (V1) that occurs in response to exposure to novel visual stimuli. It is readily observed as a pronounced increase in the magnitude of visual evoked potentials (VEPs) recorded in response to phase-reversing grating stimuli in neocortical layer 4. The expression of SRP at the individual neuron level is equally robust, but the qualities vary depending on the neuronal type and how activity is measured. This form of plasticity is highly selective for stimulus features such as stimulus orientation, spatial frequency, and contrast. Several key insights into the significance and underlying mechanisms of SRP have recently been made. First, it occurs concomitantly and shares core mechanisms with behavioral habituation, indicating that SRP reflects the formation of long-term familiarity that can support recognition of innocuous stimuli. Second, SRP does not manifest within a recording session but only emerges after an off-line period of several hours that includes sleep. Third, SRP requires not only canonical molecular mechanisms of Hebbian synaptic plasticity within V1, but also the opposing engagement of two key subclasses of cortical inhibitory neuron: the parvalbumin- and somatostatin-expressing GABAergic interneurons. Fourth, pronounced shifts in the power of cortical oscillations from high frequency (gamma) to low frequency (alpha/beta) oscillations provide respective readouts of the engagement of these inhibitory neuronal subtypes following familiarization. In this article we will discuss the implications of these findings and the outstanding questions that remain to gain a deeper understanding of this striking form of experience-dependent plasticity.

General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity

Neuro-plasticity describes the ability of the brain in achieving novel functions, either by transforming its internal connectivity, or by changing the elements of which it is made, meaning that, only those changes, that affect both structural and functional aspects of the system, can be defined as "plastic." The concept of plasticity can be applied to molecular as well as to environmental events that can be recognized as the basic mechanism by which our brain reacts to the internal and external stimuli. When considering brain plasticity within a clinical context-that is the process linked with changes of brain functions following a lesion- the term "reorganization" is somewhat synonymous, referring to the specific types of structural/functional modifications observed as axonal sprouting, long-term synaptic potentiation/inhibition or to the plasticity related genomic responses. Furthermore, brain rewires during maturation, and aging thus maintaining a remarkable learning capacity, allowing it to acquire a wide range of skills, from motor actions to complex abstract reasoning, in a lifelong expression. In this review, the contribution on the "neuroplasticity" topic coming from advanced analysis of EEG rhythms is put forward.

Reward and plasticity: Implications for neurorehabilitation

Neuroplasticity follows nervous system injury in the presence or absence of rehabilitative treatments. Rehabilitative interventions can be used to modulate adaptive neuroplasticity, reducing motor impairment and improving activities of daily living in patients with brain lesions. Learning principles guide some rehabilitative interventions. While basic science research has shown that reward combined with training enhances learning, this principle has been only recently explored in the context of neurorehabilitation. Commonly used reinforcers may be more or less rewarding depending on the individual or the context in which the task is performed. Studies in healthy humans showed that both reward and punishment can enhance within-session motor performance; but reward, and not punishment, improves consolidation and retention of motor skills. On the other hand, neurorehabilitative training after brain lesions involves complex tasks (e.g., walking and activities of daily living). The contribution of reward to neurorehabilitation is incompletely understood. Here, we discuss recent research on the role of reward in neurorehabilitation and the needed directions of future research.

New tools for shaping plasticity to enhance recovery after stroke

Stroke is the second most common cause of death worldwide and its prevalence is projected to increase in the coming years in parallel with the increase of life expectancy. Despite the great improvements in the management of the acute phase of stroke, some residual disability persists in most patients thus requiring rehabilitation. One third of patients do not reach the maximal recovery potential and different approaches have been explored with the aim to boost up recovery. In this regard, noninvasive brain stimulation techniques have been widely used to induce neuroplasticity phenomena. Different protocols of repetitive transcranial magnetic stimulation (rTMS) and transcranial electrical stimulation (tES) can induce short- and long-term changes of synaptic excitability and are promising tools for enhancing recovery in stroke patients. New options for neuromodulation are currently under investigation. They include: vagal nerve stimulation (VNS) that can be delivered invasively, with implanted stimulators and noninvasively with transcutaneous VNS (tVNS); and extremely low-frequency (1-300Hz) magnetic fields. This chapter will provide an overview on the new techniques that are used for neuroprotection and for enhancing recovery after stroke.

Sleep and homeostatic control of plasticity

Sleep homeostasis is a complex neurobiologic phenomenon involving a number of molecular pathways, neurotransmitter release, synaptic activity, and factors modulating neural networks. Sleep plasticity allows for homeostatic optimization of neural networks and the replay-based consolidation of specific circuits, especially important for cognition, behavior, and information processing. Furthermore, research is currently moving from an essentially brain-focused to a more comprehensive view involving other systems, such as the immune system, hormonal status, and metabolic pathways. When dysfunctional, these systems contribute to sleep loss and fragmentation as well as to sleep need. In this chapter, the implications of neural plasticity and sleep homeostasis for the diagnosis and treatment of some major sleep disorders, such as insomnia and sleep deprivation, obstructive sleep apnea syndrome, restless legs syndrome, REM sleep behavior disorder, and narcolepsy are discussed in detail with their therapeutical implications. This chapter highlights that sleep is necessary for the maintenance of an optimal brain function and is sensitive to both genetic background and environmental enrichment. Even in pathologic conditions, sleep acts as a resilient plastic state that consolidates prior information and prioritizes network activity for efficient brain functioning.

Increasing stimulus similarity drives nonmonotonic representational change in hippocampus

Studies of hippocampal learning have obtained seemingly contradictory results, with manipulations that increase coactivation of memories sometimes leading to differentiation of these memories, but sometimes not. These results could potentially be reconciled using the nonmonotonic plasticity hypothesis, which posits that representational change (memories moving apart or together) is a U-shaped function of the coactivation of these memories during learning. Testing this hypothesis requires manipulating coactivation over a wide enough range to reveal the full U-shape. To accomplish this, we used a novel neural network image synthesis procedure to create pairs of stimuli that varied parametrically in their similarity in high-level visual regions that provide input to the hippocampus. Sequences of these pairs were shown to human participants during high-resolution fMRI. As predicted, learning changed the representations of paired images in the dentate gyrus as a U-shaped function of image similarity, with neural differentiation occurring only for moderately similar images.

A cortical circuit for audio-visual predictions

Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli. However, it is not well understood how these interactions are mediated or at what level of the processing hierarchy they occur. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices in mice. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons that are responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be communicated by long-range cortical connections and that, with learning, these cross-modal connections function to suppress responses to predictable input.

Sleep promotes the formation of dendritic filopodia and spines near learning-inactive existing spines

Changes in synaptic connections are believed to underlie long-term memory storage. Previous studies have suggested that sleep is important for synapse formation after learning, but how sleep is involved in the process of synapse formation remains unclear. To address this question, we used transcranial two-photon microscopy to investigate the effect of postlearning sleep on the location of newly formed dendritic filopodia and spines of layer 5 pyramidal neurons in the primary motor cortex of adolescent mice. We found that newly formed filopodia and spines were partially clustered with existing spines along individual dendritic segments 24 h after motor training. Notably, posttraining sleep was critical for promoting the formation of dendritic filopodia and spines clustered with existing spines within 8 h. A fraction of these filopodia was converted into new spines and contributed to clustered spine formation 24 h after motor training. This sleep-dependent spine formation via filopodia was different from retraining-induced new spine formation, which emerged from dendritic shafts without prior presence of filopodia. Furthermore, sleep-dependent new filopodia and spines tended to be formed away from existing spines that were active at the time of motor training. Taken together, these findings reveal a role of postlearning sleep in regulating the number and location of new synapses via promoting filopodial formation.

The Brain of an Outstanding Scientist-Inventor: Structural Organization of Area 10 of the Frontal Cortex

We studied structural organization of cortical area 10 of the prefrontal cortex in the left and right hemispheres of the brain of an outstanding scientist and inventor (age 78 years). To this end, continuous series of 20-μm Nissl-stained frontal slices were compared with cortex sections of the same area from senile men (control group). It was found that the cytoarchitectonic organization of the cortical area 10 of the prefrontal cortex of the brain of an outstanding scientist-inventor is characterized by more pronounced vertical striation, greater thickness of the cortex and association layer III, higher density and size of pyramid neurons and higher density of satellite glia.

Computational benefits of structural plasticity, illustrated in songbirds

The plasticity of nervous systems allows animals to quickly adapt to a changing environment. In particular, the structural plasticity of brain networks is often critical to the development of the central nervous system and the acquisition of complex behaviors. As an example, structural plasticity is central to the development of song-related brain circuits and may be critical for song acquisition in juvenile songbirds. Here, we review current evidences for structural plasticity and their significance from a computational point of view. We start by reviewing evidence for structural plasticity across species and categorizing them along the spatial axes as well as the along the time course during development. We introduce the vocal learning circuitry in zebra finches, as a useful example of structural plasticity, and use this specific case to explore the possible contributions of structural plasticity to computational models. Finally, we discuss current modeling studies incorporating structural plasticity and unexplored questions which are raised by such models.

Cross-Streams Through the Ventral Posteromedial Thalamic Nucleus to Convey Vibrissal Information

Whisker detection is crucial to adapt to the environment for some animals, but how the nervous system processes and integrates whisker information is still an open question. It is well-known that two main parallel pathways through Ventral posteromedial thalamic nucleus (VPM) ascend to the barrel cortex, and classical theory suggests that the cross-talk from trigeminal nucleus interpolaris (Sp5i) to principal nucleus (Pr5) between the main parallel pathways contributes to the multi-whisker integration in barrel columns. Moreover, some studies suggest there are other cross-streams between the parallel pathways. To confirm their existence, in this study we used a dual-viral labeling strategy and high-resolution, large-volume light imaging to get the complete morphology of individual VPM neurons and trace their projections. We found some new thalamocortical projections from the ventral lateral part of VPM (VPMvl) to barrel columns. In addition, the retrograde-viral labeling and imaging results showed there were the large trigeminothalamic projections from Sp5i to the dorsomedial section of VPM (VPMdm). Our results reveal new cross-streams between the parallel pathways through VPM, which may involve the execution of multi-whisker integration in barrel columns.

Is human face recognition lateralized to the right hemisphere due to neural competition with left-lateralized visual word recognition? A critical review

The right hemispheric lateralization of face recognition, which is well documented and appears to be specific to the human species, remains a scientific mystery. According to a long-standing view, the evolution of language, which is typically substantiated in the left hemisphere, competes with the cortical space in that hemisphere available for visuospatial processes, including face recognition. Over the last decade, a specific hypothesis derived from this view according to which neural competition in the left ventral occipito-temporal cortex with selective representations of letter strings causes right hemispheric lateralization of face recognition, has generated considerable interest and research in the scientific community. Here, a systematic review of studies performed in various populations (infants, children, literate and illiterate adults, left-handed adults) and methodologies (behavior, lesion studies, (intra)electroencephalography, neuroimaging) offers little if any support for this reading lateralized neural competition hypothesis. Specifically, right-lateralized face-selective neural activity already emerges at a few months of age, well before reading acquisition. Moreover, consistent evidence of face recognition performance and its right hemispheric lateralization being modulated by literacy level during development or at adulthood is lacking. Given the absence of solid alternative hypotheses and the key role of neural competition in the sensory-motor cortices for selectivity of representations, learning, and plasticity, a revised language-related neural competition hypothesis for the right hemispheric lateralization of face recognition should be further explored in future research, albeit with substantial conceptual clarification and advances in methodological rigor.

Presynaptic stochasticity improves energy efficiency and helps alleviate the stability-plasticity dilemma

When an action potential arrives at a synapse there is a large probability that no neurotransmitter is released. Surprisingly, simple computational models suggest that these synaptic failures enable information processing at lower metabolic costs. However, these models only consider information transmission at single synapses ignoring the remainder of the neural network as well as its overall computational goal. Here, we investigate how synaptic failures affect the energy efficiency of models of entire neural networks that solve a goal-driven task. We find that presynaptic stochasticity and plasticity improve energy efficiency and show that the network allocates most energy to a sparse subset of important synapses. We demonstrate that stabilising these synapses helps to alleviate the stability-plasticity dilemma, thus connecting a presynaptic notion of importance to a computational role in lifelong learning. Overall, our findings present a set of hypotheses for how presynaptic plasticity and stochasticity contribute to sparsity, energy efficiency and improved trade-offs in the stability-plasticity dilemma.

Using adaptive psychophysics to identify the neural network reset time in subsecond interval timing

State-dependent network models of sub-second interval timing propose that duration is encoded in states of neuronal populations that need to reset prior to a novel timing operation to maintain optimal timing performance. Previous research has shown that the approximate boundary of this reset interval can be inferred by varying the inter-stimulus interval between two to-be-timed intervals. However, the estimated boundary of this reset interval is broad (250–500 ms) and remains under-specified with implications for the characteristics of state-dependent network dynamics sub-serving interval timing. Here, we probed the interval specificity of this reset boundary by manipulating the inter-stimulus interval between standard and comparison intervals in two sub-second auditory duration discrimination tasks (100 and 200 ms) and a control (pitch) discrimination task using adaptive psychophysics. We found that discrimination thresholds improved with the introduction of a 333 ms inter-stimulus interval relative to a 250 ms inter-stimulus interval in both duration discrimination tasks, but not in the control task. This effect corroborates previous findings of a breakpoint in the discrimination performance for sub-second stimulus interval pairs as a function of an incremental inter-stimulus delay but more precisely localizes the minimal inter-stimulus delay range. These results suggest that state-dependent networks sub-serving sub-second timing require approximately 250–333 ms for the network to reset to maintain optimal interval timing.

Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions

Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.

Modulation of Theta Phase Synchrony during Syllable Processing as a Function of Interactive Acoustic Experience in Infancy

Plasticity, a prominent characteristic of the infant brain, supports formation of cortical representations as infants begin to interact with and adapt to environmental sensory events. Enhanced acoustic processing efficiency along with improved allocation of attentional resources at 7 months and establishment of well-defined phonemic maps at 9 months have been shown to be facilitated by early interactive acoustic experience (IAE). In this study, using an oddball paradigm and measures of theta phase synchrony at source level, we examined short- and long-term effects of nonspeech IAE on syllable processing. Results demonstrated that beyond maturation alone, IAE increased the efficiency of syllabic representation and discrimination, an effect that endured well beyond the immediate training period. As compared with naive controls, the IAE-trained group at 7, 9, and 18 months showed less theta phase synchrony for the standard syllable and at 7 and 18 months for the deviant syllable. The decreased theta phase synchrony exhibited by the trained group suggests more mature, efficient, acoustic processing, and thus, better cortical representation and discrimination of syllabic content. Further, the IAE modulatory effect observed on theta phase synchrony in left auditory cortex at 7 and 9 months was differentially associated with receptive and expressive language scores at 12 and 18 months of age.

Acquired olfactory loss alters functional connectivity and morphology

Removing function from a developed and functional sensory system is known to alter both cerebral morphology and functional connections. To date, a majority of studies assessing sensory-dependent plasticity have focused on effects from either early onset or long-term sensory loss and little is known how the recent sensory loss affects the human brain. With the aim of determining how recent sensory loss affects cerebral morphology and functional connectivity, we assessed differences between individuals with acquired olfactory loss (duration 7-36 months) and matched healthy controls in their grey matter volume, using multivariate pattern analyses, and functional connectivity, using dynamic connectivity analyses, within and from the olfactory cortex. Our results demonstrate that acquired olfactory loss is associated with altered grey matter volume in, among others, posterior piriform cortex, a core olfactory processing area, as well as the inferior frontal gyrus and angular gyrus. In addition, compared to controls, individuals with acquired anosmia displayed significantly stronger dynamic functional connectivity from the posterior piriform cortex to, among others, the angular gyrus, a known multisensory integration area. When assessing differences in dynamic functional connectivity from the angular gyrus, individuals with acquired anosmia had stronger connectivity from the angular gyrus to areas primary responsible for basic visual processing. These results demonstrate that recently acquired sensory loss is associated with both changed cerebral morphology within core olfactory areas and increase dynamic functional connectivity from olfactory cortex to cerebral areas processing multisensory integration.

Longitudinal fMRI measures of cortical reactivation and hand use with and without training after sensory loss in primates

In a series of previous studies, we demonstrated that damage to the dorsal column in the cervical spinal cord deactivates the contralateral somatosensory hand cortex and impairs hand use in a reach-to-grasp task in squirrel monkeys. Nevertheless, considerable cortical reactivation and behavioral recovery occurs over the following weeks to months after lesion. This timeframe may also be a window for targeted therapies to promote cortical reactivation and functional reorganization, aiding in the recovery process. Here we asked if and how task specific training of an impaired hand would improve behavioral recovery and cortical reorganization in predictable ways, and if recovery related cortical changes would be detectable using noninvasive functional magnetic resonance imaging (fMRI). We further asked if invasive neurophysiological mapping reflected fMRI results. A reach-to-grasp task was used to test impairment and recovery of hand use before and after dorsal column lesions (DC-lesion). The activation and organization of the affected primary somatosensory cortex (area 3b) was evaluated with two types of fMRI - either blood oxygenation level dependent (BOLD) or cerebral blood volume (CBV) with a contrast agent of monocrystalline iron oxide nanocolloid (MION) - before and after DC-lesion. At the end of the behavioral and fMRI studies, microelectrode recordings in the somatosensory areas 3a, 3b and 1 were used to characterize neuronal responses and verify the somatotopy of cortical reactivations. Our results indicate that even after nearly complete DC lesions, monkeys had both considerable post-lesion behavioral recovery, as well as cortical reactivation assessed with fMRI followed by extracellular recordings. Generalized linear regression analyses indicate that lesion extent is correlated with the behavioral outcome, as well as with the difference in the percent signal change from pre-lesion peak activation in fMRI. Monkeys showed behavioral recovery and nearly complete cortical reactivation by 9-12 weeks post-lesion (particularly when the DC-lesion was incomplete). Importantly, the specific training group revealed trends for earlier behavioral recovery and had higher magnitude of fMRI responses to digit stimulation by 5-8 weeks post-lesion. Specific kinematic measures of hand movements in the selected retrieval task predicted recovery time and related to lesion characteristics better than overall task performance success. For measures of cortical reactivation, we found that CBV scans provided stronger signals to vibrotactile digit stimulation as compared to BOLD scans, and thereby may be the preferred non-invasive way to study the cortical reactivation process after sensory deprivations from digits. When the reactivation of cortex for each of the digits was considered, the reactivation by digit 2 stimulation as measured with microelectrode maps and fMRI maps was best correlated with overall behavioral recovery.

Circuit mechanisms for cortical plasticity and learning

The cerebral cortex integrates sensory information with emotional states and internal representations to produce coherent percepts, form associations, and execute voluntary actions. For the cortex to optimize perception, its neuronal network needs to dynamically retrieve and encode new information. Over the last few decades, research has started to provide insight into how the cortex serves these functions. Building on classical Hebbian plasticity models, the latest hypotheses hold that throughout experience and learning, streams of feedforward, feedback, and modulatory information operate in selective and coordinated manners to alter the strength of synapses and ultimately change the response properties of cortical neurons. Here, we describe cortical plasticity mechanisms that involve the concerted action of feedforward and long-range feedback input onto pyramidal neurons as well as the implication of local disinhibitory circuit motifs in this process.

Paired associative stimulations: Novel tools for interacting with sensory and motor cortical plasticity

In the early 2000s, a novel non-invasive brain stimulation protocol, the paired associative stimulation (PAS), was introduced, allowing to induce and investigate Hebbian associative plasticity within the humans' motor system, with patterns resembling spike-timing-dependent plasticity properties found in cellular models. Since this evidence, PAS efficacy has been proved in healthy, and to a lesser extent, in clinical populations. Recently, novel 'modified' protocols targeting sensorimotor and crossmodal networks appeared in the literature. In the present work, we have reviewed recent advances using these 'modified' PAS protocols targeting sensory and motor cortical networks. To better categorize them, we propose a novel classification according to the nature of the peripheral and cortical stimulations (i.e., within-system, cross-systems, and cortico-cortical PAS). For each protocol of the categories mentioned above, we describe and discuss their main features, how they have been used to study and promote brain plasticity, and their advantages and disadvantages. Overall, current evidence suggests that these novel non-invasive brain stimulation protocols represent very promising tools to study the plastic properties of humans' sensorimotor and crossmodal networks, both in the healthy and in the damaged central nervous system.

Behavioral effect of mismatch negativity neurofeedback on foreign language learning

Listening is critical for foreign language learning. Listening difficulties can occur because of an inability to perceive or recognize sounds while listening to speech, whereas successful listening can boost understanding and improve speaking when learning a foreign language. Previous studies in our laboratory revealed that EEG-neurofeedback (NF) using mismatch negativity event-related brain potential successfully induced unconscious learning in terms of auditory discrimination of speech sounds. Here, we conducted a feasibility study with a small participant group (NF group and control group; six participants each) to examine the practical effects of mismatch negativity NF for improving the perception of speech sounds in a foreign language. Native Japanese speakers completed a task in which they learned to perceive and recognize spoken English words containing the consonants "l" or "r". Participants received neurofeedback training while not explicitly attending to auditory stimuli. The results revealed that NF training significantly improved the proportion of correct in discrimination and recognition trials, even though the training time for each word pair was reduced to 20% of the training time reported in our previous study. The learning effect was not affected by training with three pairs of words with different vowels. The current results indicate that NF resulted in long-term learning that persisted for at least 2 months.

Age-related changes in motor cortex plasticity assessed with non-invasive brain stimulation: an update and new perspectives

It is commonly accepted that the brains capacity to change, known as plasticity, declines into old age. Recent studies have used a variety of non-invasive brain stimulation (NIBS) techniques to examine this age-related decline in plasticity in the primary motor cortex (M1), but the effects seem inconsistent and difficult to unravel. The purpose of this review is to provide an update on studies that have used different NIBS techniques to assess M1 plasticity with advancing age and offer some new perspective on NIBS strategies to boost plasticity in the ageing brain. We find that early studies show clear differences in M1 plasticity between young and older adults, but many recent studies with motor training show no decline in use-dependent M1 plasticity with age. For NIBS-induced plasticity in M1, some protocols show more convincing differences with advancing age than others. Therefore, our view from the NIBS literature is that it should not be automatically assumed that M1 plasticity declines with age. Instead, the effects of age are likely to depend on how M1 plasticity is measured, and the characteristics of the elderly population tested. We also suggest that NIBS performed concurrently with motor training is likely to be most effective at producing improvements in M1 plasticity and motor skill learning in older adults. Proposed NIBS techniques for future studies include combining multiple NIBS protocols in a co-stimulation approach, or NIBS strategies to modulate intracortical inhibitory mechanisms, in an effort to more effectively boost M1 plasticity and improve motor skill learning in older adults.

Hand pose selection in a bimanual fine-manipulation task

Many daily tasks involve the collaboration of both hands. Humans dexterously adjust hand poses and modulate the forces exerted by fingers in response to task demands. Hand pose selection has been intensively studied in unimanual tasks, but little work has investigated bimanual tasks. This work examines hand poses selection in a bimanual high-precision-screwing task taken from watchmaking. Twenty right-handed subjects dismounted a screw on the watch face with a screwdriver in two conditions. Results showed that although subjects used similar hand poses across steps within the same experimental conditions, the hand poses differed significantly in the two conditions. In the free-base condition, subjects needed to stabilize the watch face on the table. The role distribution across hands was strongly influenced by hand dominance: the dominant hand manipulated the tool, whereas the nondominant hand controlled the additional degrees of freedom that might impair performance. In contrast, in the fixed-base condition, the watch face was stationary. Subjects used both hands even though single hand would have been sufficient. Importantly, hand poses decoupled the control of task-demanded force and torque across hands through virtual fingers that grouped multiple fingers into functional units. This preference for bimanual over unimanual control strategy could be an effort to reduce variability caused by mechanical couplings and to alleviate intrinsic sensorimotor processing burdens. To afford analysis of this variety of observations, a novel graphical matrix-based representation of the distribution of hand pose combinations was developed. Atypical hand poses that are not documented in extant hand taxonomies are also included.NEW & NOTEWORTHY We study hand poses selection in bimanual fine motor skills. To understand how roles and control variables are distributed across the hands and fingers, we compared two conditions when unscrewing a screw from a watch face. When the watch face needed positioning, role distribution was strongly influenced by hand dominance; when the watch face was stationary, a variety of hand pose combinations emerged. Control of independent task demands is distributed either across hands or across distinct groups of fingers.

Role of N-methyl-d-aspartate receptor subunits GluN2A and GluN2B in auditory thalamocortical long-term potentiation in adult mice

Cortical neurons undergo continuous remodelling throughout development and into adulthood, associated with long-term changes in the synaptic transmission of thalamocortical pathways, i.e., long-term potentiation (LTP); such plasticity is input-specific, reflected in the frequency-specificity of the auditory system. It is well established that thalamocortical LTP is dependent on the activation of N-methyl-d-aspartate (NMDA) receptors. In this study, the roles of NMDA receptor subunits GluN2A and GluN2B in LTP induction were examined in thalamocortical pathways of the auditory system using subunit-selective pharmacological inhibition and in vivo tetanic stimulation of the auditory thalamus, while recording neural response in the primary auditory cortex. Long-term enhancement of thalamocortical field excitatory postsynaptic potentials (i.e., thalamocortical LTP) were induced by high frequency tetanic stimulation of the ventral division of the medial geniculate body. Such enhancement in thalamocortical fEPSPs was decreased when a GluN2A blocker (NVP-M077) was applied to the recording site in the primary auditory cortex and was increased when a GluN2B blocker (Ro25-6981) was applied. Our data suggest that the induction of thalamocortical LTP is dependent on the differential expression of the GluN2A and GluN2B subunits of NMDA receptors in thalamocortical circuits.

High-Density Reconfigurable Synaptic Transistors Targeting a Minimalist Neural Network

Enormous synaptic devices are required to build a parallel, precise, and efficient neural computing system. To further improve the energy efficiency of neuromorphic computing, a single high-density synaptic (HDS) device with multiple nonvolatile synaptic states is suggested to reduce the number of synaptic devices in the neural network, although such a powerful synaptic device is rarely demonstrated. Here, a photoisomerism material, namely, diarylethene, whose energy level varies with the wavelength of illumination is first introduced to construct a powerful HDS device. The multiple synaptic states of the HDS device are intrinsically converted under UV-vis regulation and remain nonvolatile after the removal of illumination. More importantly, the conversion is reconfigurable and reversible under different light conditions, and the synaptic characteristics are comprehensively mimicked in each state. Finally, compared with a two-layer multilayer perceptron (MLP) architecture based on static synaptic devices, the HDS device-based architecture reduces the device number by 16 times to achieve a minimalist neural computing structure. The invention of the HDS device opens up a revolutionary paradigm for the establishment of a brain-like network.

From many to (n)one: Meditation and the plasticity of the predictive mind

How profoundly can humans change their own minds? In this paper we offer a unifying account of deconstructive meditation under the predictive processing view. We start from simple axioms. First, the brain makes predictions based on past experience, both phylogenetic and ontogenetic. Second, deconstructive meditation brings one closer to the here and now by disengaging anticipatory processes. We propose that practicing meditation therefore gradually reduces counterfactual temporally deep cognition, until all conceptual processing falls away, unveiling a state of pure awareness. Our account also places three main styles of meditation (focused attention, open monitoring, and non-dual) on a single continuum, where each technique relinquishes increasingly engrained habits of prediction, including the predicted self. This deconstruction can also permit certain insights by making the above processes available to introspection. Our framework is consistent with the state of empirical and (neuro)phenomenological evidence and illuminates the top-down plasticity of the predictive mind. Experimental rigor, neurophenomenology, and no-report paradigms are needed to further understanding of how meditation affects predictive processing and the self.

Effects of training of shadowing and reading aloud of second language on working memory and neural systems

Shadowing and reading aloud both involve multiple complex cognitive processes, and both are considered effective methods for second-language learning. The working memory system, particularly the phonological loop, has been suggested to be involved in shadowing and reading aloud. The purpose of this study was to investigate the effects of a 4-week intensive adaptive training including shadowing and reading aloud of second language on working-memory capacity, regional gray matter volume (rGMV), and functional activation related to the n-back working-memory task in young adults. The results showed that compared with the training groups without speaking (listening to compressed speech and active control involving the second language), the training groups with speaking (shadowing and reading aloud) showed a tendency for greater test-retest increases in digit-span scores, and significantly greater test-retest decreases in N-back task reaction time (increase in working memory performance). Imaging analyses revealed compared with the active control group, shadowing group exhibited decreases in rGMV and brain activity during the working memory task (2-back task), in the left cerebellum and reading group exhibited decreases in them in the right anterior insula. These regions are parts of the phonological loop, suggesting the presence of training-induced neural plasticity in these neurocognitive mechanisms.

Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation

Brain-computer interfaces (BCIs) designed for motor rehabilitation use brain signals associated with motor-processing states to guide neuroplastic changes in a state-dependent manner. These technologies are uniquely positioned to induce targeted and functionally relevant plastic changes in the human motor nervous system. However, while several studies have shown that BCI-based neuromodulation interventions may improve motor function in patients with lesions in the central nervous system, the neurophysiological structures and processes targeted with the BCI interventions have not been identified. In this review, we first summarize current knowledge of the changes in the central nervous system associated with learning new motor skills. Then, we propose a classification of current BCI paradigms for plasticity induction and motor rehabilitation based on the expected neural plastic changes promoted. This classification proposes four paradigms based on two criteria: the plasticity induction methods and the brain states targeted. The existing evidence regarding the brain circuits and processes targeted with these different BCIs is discussed in detail. The proposed classification aims to serve as a starting point for future studies trying to elucidate the underlying plastic changes following BCI interventions.

Evaluation of the Implementation and Effectiveness of Community-Based Brain-Computer Interface Cognitive Group Training in Healthy Community-Dwelling Older Adults: Randomized Controlled Implementation Trial

BACKGROUND

Cognitive training can improve cognition in healthy older adults.

OBJECTIVE

The objectives are to evaluate the implementation of community-based computerized cognitive training (CCT) and its effectiveness on cognition, gait, and balance in healthy older adults.

METHODS

A single-blind randomized controlled trial with baseline and follow-up assessments was conducted at two community centers in Singapore. Healthy community-dwelling adults aged 55 years and older participated in a 10-week CCT program with 2-hour instructor-led group classes twice a week. Participants used a mobile app to play games targeting attention, memory, decision making, visuospatial abilities, and cognitive flexibility. Implementation was assessed at the participant, provider, and community level (eg, reach, implementation, and facilitators and barriers). Effectiveness measures were the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Color Trails Test 2 (CTT-2), Berg Balance Scale, and GAITRite walkway measures (single and dual task gait speed, dual task cost, and single and dual task gait variability index [GVI]).

RESULTS

A total of 94 healthy community-dwelling adults participated in the CCT program (mean age 68.8 [SD 6.3] years). Implementation measures revealed high reach (125/155, 80.6%) and moderate adherence but poor penetration of sedentary older adults (43/125, 34.4%). The effectiveness data were based on intention-to-treat (ITT) and per-protocol (PP) analysis. In the ITT analysis, single task GVI increased (b=2.32, P=.02, 95% CI [0.30 to 4.35]) and RBANS list recognition subtest deteriorated (b=-0.57, P=.01, 95% CI [-1.00 to -0.14]) in both groups. In the PP analysis, time taken to complete CTT-2 (b=-13.5, P=.01, 95% CI [-23.95 to -3.14]; Cohen d effect size = 0.285) was faster in the intervention group. Single task gait speed was not statistically significantly maintained in the intervention group (b=5.38, P=.06, 95% CI [-0.30 to 11.36]) and declined in the control group (Cohen d effect size = 0.414). PP analyses also showed interaction terms for RBANS list recall subtest (b=-0.36, P=.08, 95% CI [-0.75 to 0.04]) and visuospatial domain (b=0.46, P=.08, 95% CI [-0.05 to 0.96]) that were not statistically significant.

CONCLUSIONS

CCT can be implemented in community settings to improve attention and executive function among healthy older adults. Findings help to identify suitable healthy aging programs that can be implemented on a larger scale within communities.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04439591; https://clinicaltrials.gov/ct2/show/NCT04439591.