The learning of a motor task is known to be improved by sleep, and sleep spindles are thought to facilitate this learning by enabling synaptic plasticity. In this study subjects implanted with ...electrocorticography (ECoG) arrays for long-term epilepsy monitoring were trained to control a cursor on a computer screen by modulating either the high-gamma or mu/beta power at a single electrode located over the motor or premotor area. In all trained subjects, spindle density in posttraining sleep was increased with respect to pretraining sleep in a remarkably spatially specific manner. The pattern of increased spindle activity reflects the functionally specific regions that were involved in learning of a highly novel and salient task during wakefulness, supporting the idea that sleep spindles are involved in learning to use a motor-based brain–computer interface device.
The gold-standard method for determining cortical functional organization in the context of neurosurgical intervention is electrical cortical stimulation (ECS), which disrupts normal cortical ...function to evoke movement. This technique is imprecise, however, as motor responses are not limited to the precentral gyrus. Electrical cortical stimulation also can trigger seizures, is not always tolerated, and is often unsuccessful, especially in children. Alternatively, endogenous motor and sensory signals can be mapped by somatosensory evoked potentials (SSEPs), functional MRI (fMRI), and electrocorticography of high gamma (70-150 Hz) signal power, which reflect normal cortical function. The authors evaluated whether these 4 modalities of mapping sensorimotor function in children produce concurrent results.
The authors retrospectively examined the charts of all patients who underwent epilepsy surgery at Seattle Children's Hospital between July 20, 1999, and July 1, 2011, and they included all patients in whom the primary motor or somatosensory cortex was localized via 2 or more of the following tests: ECS, SSEP, fMRI, or high gamma electrocorticography (hgECoG).
Inclusion criteria were met by 50 patients, whose mean age at operation was 10.6 years. The youngest patient who underwent hgECoG mapping was 2 years and 10 months old, which is younger than any patient reported on in the literature. The authors localized the putative sensorimotor cortex most often with hgECoG, followed by SSEP and fMRI; ECS was most likely to fail to localize the sensorimotor cortex.
Electrical cortical stimulation, SSEP, fMRI, and hgECoG generally produced concordant localization of motor and sensory function in children. When attempting to localize the sensorimotor cortex in children, hgECoG was more likely to produce results, was faster, safer, and did not require cooperation. The hgECoG maps in pediatric patients are similar to those in adult patients published in the literature. The sensorimotor cortex can be mapped by hgECoG and fMRI in children younger than 3 years old to localize cortical function.
Human subjects can learn to control a one-dimensional electrocorticographic (ECoG) brain-computer interface (BCI) using modulation of primary motor (M1) high-gamma activity (signal power in the ...75-200 Hz range). However, the stability and dynamics of the signals over the course of new BCI skill acquisition have not been investigated. In this study, we report three characteristic periods in evolution of the high-gamma control signal during BCI training: initial, low task accuracy with corresponding low power modulation in the gamma spectrum, followed by a second period of improved task accuracy with increasing average power separation between activity and rest, and a final period of high task accuracy with stable (or decreasing) power separation and decreasing trial-to-trial variance. These findings may have implications in the design and implementation of BCI control algorithms.
Reconstruction of neural circuits from volume electron microscopy data requires the tracing of cells in their entirety, including all their neurites. Automated approaches have been developed for ...tracing, but their error rates are too high to generate reliable circuit diagrams without extensive human proofreading. We present flood-filling networks, a method for automated segmentation that, similar to most previous efforts, uses convolutional neural networks, but contains in addition a recurrent pathway that allows the iterative optimization and extension of individual neuronal processes. We used flood-filling networks to trace neurons in a dataset obtained by serial block-face electron microscopy of a zebra finch brain. Using our method, we achieved a mean error-free neurite path length of 1.1 mm, and we observed only four mergers in a test set with a path length of 97 mm. The performance of flood-filling networks was an order of magnitude better than that of previous approaches applied to this dataset, although with substantially increased computational costs.
To fully understand how the human brain works, knowledge of its structure at high resolution is needed. Presented here is a computationally intensive reconstruction of the ultrastructure of a cubic ...millimeter of human temporal cortex that was surgically removed to gain access to an underlying epileptic focus. It contains about 57,000 cells, about 230 millimeters of blood vessels, and about 150 million synapses and comprises 1.4 petabytes. Our analysis showed that glia outnumber neurons 2:1, oligodendrocytes were the most common cell, deep layer excitatory neurons could be classified on the basis of dendritic orientation, and among thousands of weak connections to each neuron, there exist rare powerful axonal inputs of up to 50 synapses. Further studies using this resource may bring valuable insights into the mysteries of the human brain.
Invasive and non-invasive brain–computer interface (BCI) studies have long focused on the motor cortex for kinematic control of artificial devices. Most of these studies have used single-neuron ...recordings or electroencephalography (EEG). Electrocorticography (ECoG) is a relatively new recording modality in BCI research that has primarily been built on successes in EEG recordings. We built on prior experiments related to single-neuron recording and quantitatively compare the extent to which different brain regions reflect kinematic tuning parameters of hand speed, direction, and velocity in both a reaching and tracing task in humans. Hand and arm movement experiments using ECoG have shown positive results before, but the tasks were not designed to tease out which kinematics are encoded. In non-human primates, the relationships among these kinematics have been more carefully documented, and we sought to begin elucidating that relationship in humans using ECoG. The largest modulation in ECoG activity for direction, speed, and velocity representation was found in the primary motor cortex. We also found consistent cosine tuning across both tasks, to hand direction and velocity in the high gamma band (70–160 Hz). Thus, the results of this study clarify the neural substrates involved in encoding aspects of motor preparation and execution and confirm the important role of the motor cortex in BCI applications.
All previous multiple-day brain-computer interface (BCI) experiments have dynamically adjusted the parameterization between the signals measured from the brain and the features used to control the ...interface. The authors present the results of a multiple-day electrocorticographic (ECoG) BCI experiment. A patient with a subdural electrode array implanted for seizure localization performed tongue motor tasks. After an initial screening and feature selection on the 1st day, 5 consecutive days of cursor-based feedback were performed with a fixed parameterization. Control of the interface was robust throughout all days, with performance increasing to a stable state in which high-frequency ECoG signal could immediately be translated into cursor control. These findings demonstrate that ECoG-based BCIs can be implemented for multiple-day control without the necessity for sophisticated retraining and adaptation.
INTRODUCTION:Our inability to tickle ourselves has led to the hypothesis that, when an efferent signal is produced and sent to the motor system, a correlate, known as efference copy, is created to ...distinguish sensations produced by the subjectʼs own actions from those generated by external stimuli.
METHODS:To demonstrate the existence of such entity, we used electrocorticography (ECoG) to measure activation timing in human primary motor (M1), premotor (PM) and somatosensory (S1) neurons in preparation for finger movements in 4 subjects with subdural grids for seizure localization. Cortical activation was determined by the onset of high gamma (HG) oscillation (70-150 Hz). The 3 cortical regions were mapped anatomically using a common brain atlas and confirmed with sensory stimulation. Subjects were given visual cues to flex each finger or pinch thumb and index finger. Movements were captured with a dataglove and time-locked with ECoG. A windowed covariance metric was used to identify the rising slope of HG power between 2 electrodes and compute their time lag. To combat noise, we subjected both time estimates and electrode sorting to statistical constraints. We used rank sum testing to verify the sequential activation of these cortical regions across 4 subjects.
RESULTS:In all 4 subjects, we found PM , S1 and M1 activated 385 (± 78), 312 (± 66), and 134 (± 34) msec ahead of finger movements. On average, PM activated approximately 251 msec ahead of M1 (P < .000), S1 activated approximately 178 msec ahead of M1 (P = .003) and PM lead S1 by approximately 73 msec (P = .11).
CONCLUSION:Firing of S1 neurons prior to any overt body movements supports the notion that these neurons may encode sensory information in anticipation of movements, ie, an efferent copy. Our data suggests that this modulation of S1 is likely coming from PM.
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