基于图论算法的脊髓损伤后大脑皮层运动区神经元网络分析

 脊髓损伤(SCI)后大脑皮层运动区神经元的功能重组对机体功能康复的影响仍然不为人知。脊髓损伤前后,对一只在跑步机上直立行走的恒河猴的大脑皮层运动区神经元信号进行记录,利用不同神经元动作电位序列间的相关系数建立神经元网络图。为了研究神经元活动模式的变化与功能康复之间的联系,利用图论算法计算了神经元网络图的全局效能指标和神经元脆弱性指标。结果显示,不同时期神经元活动模式的显著变化意味着运动区神经元的功能重组(神经可塑性)与脊髓损伤后猴子的功能康复状态紧密相关,且这种神经功能重组对于猴子步行功能的康复起了非常重要的积极作用。     

Practising orientation identification improves orientation coding in V1 neurons

The adult brain shows remarkable plasticity, as demonstrated by the improvement in fine sensorial discriminations after intensive practice. The behavioural aspects of such perceptual learning are well documented, especially in the visual system. Specificity for stimulus attributes clearly implicates an early cortical site, where receptive fields retain fine selectivity for these attributes; however, the neuronal correlates of a simple visual discrimination task remained unidentified. Here we report electrophysiological correlates in the primary visual cortex (V1) of monkeys for learning orientation identification. We link the behavioural improvement in this type of learning to an improved neuronal performance of trained compared to naive neurons. Improved long-term neuronal performance resulted from changes in the characteristics of orientation tuning of individual neurons. More particularly, the slope of the orientation tuning curve that was measured at the trained orientation increased only for the subgroup of trained neurons most likely to code the orientation identified by the monkey. No modifications of the tuning curve were observed for orientations for which the monkey had not been trained. Thus training induces a specific and efficient increase in neuronal sensitivity in V1.     

Relation of neurons in the nonprimary motor cortex to bilateral hand movement

In the primate cerebral cortex there are at least two somatotopically organized, nonprimary motor fields rostral to the primary motor area. To understand the functions of these multiple motor representations we have compared the neuronal activity in each of these fields while monkeys performed a trained motor task, using right, left or both hands. In the nonprimary motor cortex, activity in a number of neurons was related to the movement the animal chose and performed, whereas in the primary motor cortex, changes in the firing of most neurons were simply related to activity in the contralateral muscles. This result indicates that the nonprimary motor cortex is involved in higher-order coding of the laterality of the motor response, implying that it exerts its motor control function at a higher hierarchical level than its counterpart in the primary motor cortex.     

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.     

Neuronal ensemble control of prosthetic devices by a human with tetraplegia

Neuromotor prostheses (NMPs) aim to replace or restore lost motor functions in paralysed humans by routeing movement-related signals from the brain, around damaged parts of the nervous system, to external effectors. To translate preclinical results from intact animals to a clinically useful NMP, movement signals must persist in cortex after spinal cord injury and be engaged by movement intent when sensory inputs and limb movement are long absent. Furthermore, NMPs would require that intention-driven neuronal activity be converted into a control signal that enables useful tasks. Here we show initial results for a tetraplegic human (MN) using a pilot NMP. Neuronal ensemble activity recorded through a 96-microelectrode array implanted in primary motor cortex demonstrated that intended hand motion modulates cortical spiking patterns three years after spinal cord injury. Decoders were created, providing a 'neural cursor' with which MN opened simulated e-mail and operated devices such as a television, even while conversing. Furthermore, MN used neural control to open and close a prosthetic hand, and perform rudimentary actions with a multi-jointed robotic arm. These early results suggest that NMPs based upon intracortical neuronal ensemble spiking activity could provide a valuable new neurotechnology to restore independence for humans with paralysis.     

Synaptic facilitation requires paired activation of convergent pathways in the neocortex

In associative learning, the activated neurones undergo a variety of concomitant functional alterations--increases or decreases of firing activity and modifications of membrane potential or resistance and of synaptic responsiveness. Synaptic transmission which can be strengthened only when there is paired activity in two pathways is of particular interest in relation to mechanisms for associative learning. For the neocortex, there are few observations of the plastic changes, induced by conditioning procedures, in the effectiveness of individual synapses. We now report that various regimes with joint stimulations of convergent excitatory pathways on to intracellularly recorded neurones in the motor cortex of the cat result in synaptic facilitation lasting for up to 30 min.     

Activity of striatal neurons reflects dynamic encoding and recoding of procedural memories

Learning to perform a behavioural procedure as a well-ingrained habit requires extensive repetition of the behavioural sequence, and learning not to perform such behaviours is notoriously difficult. Yet regaining a habit can occur quickly, with even one or a few exposures to cues previously triggering the behaviour. To identify neural mechanisms that might underlie such learning dynamics, we made long-term recordings from multiple neurons in the sensorimotor striatum, a basal ganglia structure implicated in habit formation, in rats successively trained on a reward-based procedural task, given extinction training and then given reacquisition training. The spike activity of striatal output neurons, nodal points in cortico-basal ganglia circuits, changed markedly across multiple dimensions during each of these phases of learning. First, new patterns of task-related ensemble firing successively formed, reversed and then re-emerged. Second, task-irrelevant firing was suppressed, then rebounded, and then was suppressed again. These changing spike activity patterns were highly correlated with changes in behavioural performance. We propose that these changes in task representation in cortico-basal ganglia circuits represent neural equivalents of the explore-exploit behaviour characteristic of habit learning.     

Graded persistent activity in entorhinal cortex neurons

Working memory represents the ability of the brain to hold externally or internally driven information for relatively short periods of time. Persistent neuronal activity is the elementary process underlying working memory but its cellular basis remains unknown. The most widely accepted hypothesis is that persistent activity is based on synaptic reverberations in recurrent circuits. The entorhinal cortex in the parahippocampal region is crucially involved in the acquisition, consolidation and retrieval of long-term memory traces for which working memory operations are essential. Here we show that individual neurons from layer V of the entorhinal cortex-which link the hippocampus to extensive cortical regions-respond to consecutive stimuli with graded changes in firing frequency that remain stable after each stimulus presentation. In addition, the sustained levels of firing frequency can be either increased or decreased in an input-specific manner. This firing behaviour displays robustness to distractors; it is linked to cholinergic muscarinic receptor activation, and relies on activity-dependent changes of a Ca2+-sensitive cationic current. Such an intrinsic neuronal ability to generate graded persistent activity constitutes an elementary mechanism for working memory.     

Active tactile exploration using a brain-machine-brain interface

Brain-machine interfaces use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain-machine interfaces can be used to restore the normal sensorimotor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain-machine-brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.     

Development of an invasive brain machine interface with a monkey model

Brain-machine interfaces (BMIs) translate neural activities of the brain into specific instructions that can be carried out by external devices. BMIs have the potential to restore or augment motor functions of paralyzed patients suffering from spinal cord damage. The neural activities have been used to predict the 2D or 3D movement trajectory of monkey’s arm or hand in many studies. However, there are few studies on decoding the wrist movement from neural activities in center-out paradigm. The present study developed an invasive BMI system with a monkey model using a 10×10-microelectrode array in the primary motor cortex. The monkey was trained to perform a two-dimensional forelimb wrist movement paradigm where neural activities and movement signals were simultaneous recorded. Results showed that neuronal firing rates highly correlated with forelimb wrist movement; > 70% (105/149) neurons exhibited specific firing changes during movement and > 36% (54/149) neurons were used to discriminate directional pairs. The neuronal firing rates were also used to predict the wrist moving directions and continuous trajectories of the forelimb wrist. The four directions could be classified with 96% accuracy using a support vector machine, and the correlation coefficients of trajectory prediction using a general regression neural network were above 0.8 for both horizontal and vertical directions. Results showed that this BMI system could predict monkey wrist movements in high accuracy through the use of neuronal firing information.     

Rapid strengthening of thalamo-amygdala synapses mediates cue-reward learning

What neural changes underlie individual differences in goal-directed learning? The lateral amygdala (LA) is important for assigning emotional and motivational significance to discrete environmental cues, including those that signal rewarding events. Recognizing that a cue predicts a reward enhances an animal's ability to acquire that reward; however, the cellular and synaptic mechanisms that underlie cue-reward learning are unclear. Here we show that marked changes in both cue-induced neuronal firing and input-specific synaptic strength occur with the successful acquisition of a cue-reward association within a single training session. We performed both in vivo and ex vivo electrophysiological recordings in the LA of rats trained to self-administer sucrose. We observed that reward-learning success increased in proportion to the number of amygdala neurons that responded phasically to a reward-predictive cue. Furthermore, cue-reward learning induced an AMPA (alpha-amino-3-hydroxy-5-methyl-isoxazole propionic acid)-receptor-mediated increase in the strength of thalamic, but not cortical, synapses in the LA that was apparent immediately after the first training session. The level of learning attained by individual subjects was highly correlated with the degree of synaptic strength enhancement. Importantly, intra-LA NMDA (N-methyl-d-aspartate)-receptor blockade impaired reward-learning performance and attenuated the associated increase in synaptic strength. These findings provide evidence of a connection between LA synaptic plasticity and cue-reward learning, potentially representing a key mechanism underlying goal-directed behaviour.     

Long-term plasticity in hippocampal place-cell representation of environmental geometry

The hippocampus is widely believed to be involved in the storage or consolidation of long-term memories. Several reports have shown short-term changes in single hippocampal unit activity during memory and plasticity experiments, but there has been no experimental demonstration of long-term persistent changes in neuronal activity in any region except primary cortical areas. Here we report that, in rats repeatedly exposed to two differently shaped environments, the hippocampal-place-cell representations of those environments gradually and incrementally diverge; this divergence is specific to environmental shape, occurs independently of explicit reward, persists for periods of at least one month, and transfers to new enclosures of the same shape. These results indicate that place cells may be a neural substrate for long-term incidental learning, and demonstrate the long-term stability of an experience-dependent firing pattern in the hippocampal formation.     

A cellular analogue of visual cortical plasticity

Neuronal activity plays an important role in the development of the visual pathway. The modulation of synaptic transmission by temporal correlation between pre- and postsynaptic activity is one mechanism which could underly visual cortical plasticity. We report here that functional changes in single neurons of area 17, analogous to those known to take place during epigenesis of visual cortex, can be induced experimentally during the time of recording. This was done by a differential pairing procedure, during which iontophoresis was used to artificially increase the visual response for a given stimulus, and to decrease (or block) the response for a second stimulus which differed in ocularity or orientation. Long-term modifications in ocular dominance and orientation selectivity were produced in 33% and 43% of recorded cells respectively. Neuronal selectivity was nearly always displaced towards the stimulus paired with the reinforced visual response. The largest changes were obtained at the peak of the critical period in normally reared and visually deprived kittens, but changes were also observed in adults. Our findings support the role of temporal correlation between pre- and postsynaptic activity in the induction of long-lasting modifications of synaptic transmission during development, and in associative learning.     

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

The ability to learn new skills and perfect them with practice applies not only to physical skills but also to abstract skills, like motor planning or neuroprosthetic actions. Although plasticity in corticostriatal circuits has been implicated in learning physical skills, it remains unclear if similar circuits or processes are required for abstract skill learning. Here we use a novel behavioural task in rodents to investigate the role of corticostriatal plasticity in abstract skill learning. Rodents learned to control the pitch of an auditory cursor to reach one of two targets by modulating activity in primary motor cortex irrespective of physical movement. Degradation of the relation between action and outcome, as well as sensory-specific devaluation and omission tests, demonstrate that these learned neuroprosthetic actions are intentional and goal-directed, rather than habitual. Striatal neurons change their activity with learning, with more neurons modulating their activity in relation to target-reaching as learning progresses. Concomitantly, strong relations between the activity of neurons in motor cortex and the striatum emerge. Specific deletion of striatal NMDA receptors impairs the development of this corticostriatal plasticity, and disrupts the ability to learn neuroprosthetic skills. These results suggest that corticostriatal plasticity is necessary for abstract skill learning, and that neuroprosthetic movements capitalize on the neural circuitry involved in natural motor learning.     

Entrained rhythmic activities of neuronal ensembles as perceptual memory of time interval

The ability to process temporal information is fundamental to sensory perception, cognitive processing and motor behaviour of all living organisms, from amoebae to humans. Neural circuit mechanisms based on neuronal and synaptic properties have been shown to process temporal information over the range of tens of microseconds to hundreds of milliseconds. How neural circuits process temporal information in the range of seconds to minutes is much less understood. Studies of working memory in monkeys and rats have shown that neurons in the prefrontal cortex, the parietal cortex and the thalamus exhibit ramping activities that linearly correlate with the lapse of time until the end of a specific time interval of several seconds that the animal is trained to memorize. Many organisms can also memorize the time interval of rhythmic sensory stimuli in the timescale of seconds and can coordinate motor behaviour accordingly, for example, by keeping the rhythm after exposure to the beat of music. Here we report a form of rhythmic activity among specific neuronal ensembles in the zebrafish optic tectum, which retains the memory of the time interval (in the order of seconds) of repetitive sensory stimuli for a duration of up to approximately 20 s. After repetitive visual conditioning stimulation (CS) of zebrafish larvae, we observed rhythmic post-CS activities among specific tectal neuronal ensembles, with a regular interval that closely matched the CS. Visuomotor behaviour of the zebrafish larvae also showed regular post-CS repetitions at the entrained time interval that correlated with rhythmic neuronal ensemble activities in the tectum. Thus, rhythmic activities among specific neuronal ensembles may act as an adjustable 'metronome' for time intervals in the order of seconds, and serve as a mechanism for the short-term perceptual memory of rhythmic sensory experience.     

Early motor activity drives spindle bursts in the developing somatosensory cortex

Sensorimotor coordination emerges early in development. The maturation period is characterized by the establishment of somatotopic cortical maps, the emergence of long-range cortical connections, heightened experience-dependent plasticity and spontaneous uncoordinated skeletal movement. How these various processes cooperate to allow the somatosensory system to form a three-dimensional representation of the body is not known. In the visual system, interactions between spontaneous network patterns and afferent activity have been suggested to be vital for normal development. Although several intrinsic cortical patterns of correlated neuronal activity have been described in developing somatosensory cortex in vitro, the in vivo patterns in the critical developmental period and the influence of physiological sensory inputs on these patterns remain unknown. We report here that in the intact somatosensory cortex of the newborn rat in vivo, spatially confined spindle bursts represent the first and only organized network pattern. The localized spindles are selectively triggered in a somatotopic manner by spontaneous muscle twitches, motor patterns analogous to human fetal movements. We suggest that the interaction between movement-triggered sensory feedback signals and self-organized spindle oscillations shapes the formation of cortical connections required for sensorimotor coordination.     

Local sleep in awake rats

In an awake state, neurons in the cerebral cortex fire irregularly and electroencephalogram (EEG) recordings display low-amplitude, high-frequency fluctuations. During sleep, neurons oscillate between 'on' periods, when they fire as in an awake brain, and 'off' periods, when they stop firing altogether and the EEG displays high-amplitude slow waves. However, what happens to neuronal firing after a long period of being awake is not known. Here we show that in freely behaving rats after a long period in an awake state, cortical neurons can go briefly 'offline' as in sleep, accompanied by slow waves in the local EEG. Neurons often go offline in one cortical area but not in another, and during these periods of 'local sleep', the incidence of which increases with the duration of the awake state, rats are active and display an 'awake' EEG. However, they are progressively impaired in a sugar pellet reaching task. Thus, although both the EEG and behaviour indicate wakefulness, local populations of neurons in the cortex may be falling asleep, with negative consequences for performance.     

Repetitive motor learning induces coordinated formation of clustered dendritic spines in vivo

Many lines of evidence suggest that memory in the mammalian brain is stored with distinct spatiotemporal patterns. Despite recent progresses in identifying neuronal populations involved in memory coding, the synapse-level mechanism is still poorly understood. Computational models and electrophysiological data have shown that functional clustering of synapses along dendritic branches leads to nonlinear summation of synaptic inputs and greatly expands the computing power of a neural network. However, whether neighbouring synapses are involved in encoding similar memory and how task-specific cortical networks develop during learning remain elusive. Using transcranial two-photon microscopy, we followed apical dendrites of layer 5 pyramidal neurons in the motor cortex while mice practised novel forelimb skills. Here we show that a third of new dendritic spines (postsynaptic structures of most excitatory synapses) formed during the acquisition phase of learning emerge in clusters, and that most such clusters are neighbouring spine pairs. These clustered new spines are more likely to persist throughout prolonged learning sessions, and even long after training stops, than non-clustered counterparts. Moreover, formation of new spine clusters requires repetition of the same motor task, and the emergence of succedent new spine(s) accompanies the strengthening of the first new spine in the cluster. We also show that under control conditions new spines appear to avoid existing stable spines, rather than being uniformly added along dendrites. However, succedent new spines in clusters overcome such a spatial constraint and form in close vicinity to neighbouring stable spines. Our findings suggest that clustering of new synapses along dendrites is induced by repetitive activation of the cortical circuitry during learning, providing a structural basis for spatial coding of motor memory in the mammalian brain.     

Behavioural report of single neuron stimulation in somatosensory cortex

Understanding how neural activity in sensory cortices relates to perception is a central theme of neuroscience. Action potentials of sensory cortical neurons can be strongly correlated to properties of sensory stimuli and reflect the subjective judgements of an individual about stimuli. Microstimulation experiments have established a direct link from sensory activity to behaviour, suggesting that small neuronal populations can influence sensory decisions. However, microstimulation does not allow identification and quantification of the stimulated cellular elements. The sensory impact of individual cortical neurons therefore remains unknown. Here we show that stimulation of single neurons in somatosensory cortex affects behavioural responses in a detection task. We trained rats to respond to microstimulation of barrel cortex at low current intensities. We then initiated short trains of action potentials in single neurons by juxtacellular stimulation. Animals responded significantly more often in single-cell stimulation trials than in catch trials without stimulation. Stimulation effects varied greatly between cells, and on average in 5% of trials a response was induced. Whereas stimulation of putative excitatory neurons led to weak biases towards responding, stimulation of putative inhibitory neurons led to more variable and stronger sensory effects. Reaction times for single-cell stimulation were long and variable. Our results demonstrate that single neuron activity can cause a change in the animal's detection behaviour, suggesting a much sparser cortical code for sensations than previously anticipated.     

Hippocampal remapping and grid realignment in entorhinal cortex

A fundamental property of many associative memory networks is the ability to decorrelate overlapping input patterns before information is stored. In the hippocampus, this neuronal pattern separation is expressed as the tendency of ensembles of place cells to undergo extensive 'remapping' in response to changes in the sensory or motivational inputs to the hippocampus. Remapping is expressed under some conditions as a change of firing rates in the presence of a stable place code ('rate remapping'), and under other conditions as a complete reorganization of the hippocampal place code in which both place and rate of firing take statistically independent values ('global remapping'). Here we show that the nature of hippocampal remapping can be predicted by ensemble dynamics in place-selective grid cells in the medial entorhinal cortex, one synapse upstream of the hippocampus. Whereas rate remapping is associated with stable grid fields, global remapping is always accompanied by a coordinate shift in the firing vertices of the grid cells. Grid fields of co-localized medial entorhinal cortex cells move and rotate in concert during this realignment. In contrast to the multiple environment-specific representations coded by place cells in the hippocampus, local ensembles of grid cells thus maintain a constant spatial phase structure, allowing position to be represented and updated by the same translation mechanism in all environments encountered by the animal.