A state-based probabilistic method for decoding hand position during movement from ECoG signals in non-human primate.
一种基于状态的概率方法，用于从非人灵长类动物的 ECoG 信号解码运动过程中的手位置。
- 作者列表："Farrokhi B","Erfanian A
OBJECTIVE:In this study, we proposed a state-based probabilistic method for decoding hand positions during unilateral and bilateral movements using the ECoG signals recorded from the brain of Rhesus monkey. APPROACH:A customized electrode array was implanted subdurally in the right hemisphere of the brain covering from the primary motor cortex to the frontal cortex. Three different experimental paradigms were considered: ipsilateral, contralateral, and bilateral movements. During unilateral movement, the monkey was trained to get food with one hand, while during bilateral movement, the monkey used its left and right hands alternately to get food. To estimate the hand positions, a state-based probabilistic method was introduced which was based on the conditional probability of the hand movement state (i.e., idle, right hand movement, and left hand movement) and the conditional expectation of the hand position for each state. Moreover, a hybrid feature extraction method based on linear discriminant analysis (LDA) and partial least squares (PLS) was introduced. MAIN RESULTS:The proposed method could successfully decode the hand positions during ipsilateral, contralateral, and bilateral movements and significantly improved the decoding performance compared to the conventional Kalman and PLS regression methods (p<"0.05"). The proposed hybrid feature extraction method was found to outperform both the PLS and PCA methods (p<0.01). Investigating the kinematic information of each frequency band shows that more informative frequency bands were β (15-30 Hz) and γ_2 (50-100 Hz) for ipsilateral and γ_2 and γ_3 (100-200 Hz) for contralateral movements. It is observed that ipsilateral movement was decoded better than contralateral movement for θ-α (5-15 Hz) and β bands, while contralateral movements was decoded better for γ (30-200 Hz) and hfECoG (200-400 Hz) bands. SIGNIFICANCE:Accurate decoding the bilateral movement using the ECoG recorded from one brain hemisphere is an important issue toward real-life applications of the brain-machine interface technologies.
目的: 在本研究中，我们提出了一种基于状态的概率方法，利用恒河猴大脑记录的 ECoG 信号解码单侧和双侧运动过程中的手位置。 方法: 在大脑右侧半球皮下植入定制的电极阵列，覆盖从初级运动皮层到额叶皮层。考虑了三种不同的实验范式: 同侧、对侧和双侧运动。在单侧运动时，猴子被训练用一只手获取食物，而在双侧运动时，猴子用左右手交替获取食物。为了估计手的位置，引入了一种基于状态的概率方法，该方法基于手运动状态的条件概率 (i.e.,空闲、右手运动和左手运动) 和每种状态的手位置的条件期望。此外，介绍了一种基于线性判别分析 (LDA) 和偏最小二乘法 (PLS) 的混合特征提取方法。 主要结果: 该方法能成功解码同侧、对侧、与传统卡尔曼和 PLS 回归方法相比，双侧运动和显著提高了解码性能 (p<"0.05")。发现所提出的混合特征提取方法优于 PLS 和 PCA 方法 (p<0.01)。对各频段运动学信息的调查表明，信息较多的频段为 β (15-30Hz) 和 γ 2 (50-100Hz) 对于同侧和 γ 2 和 γ 3 (100-200Hz) 对侧运动。观察到对 θ-α (5-15Hz) 和 β 波段同侧运动解码优于对侧运动，对侧运动解码优于 γ (30-200Hz) 和 hfECoG (200-400Hz) 波段。 意义: 使用从一个大脑半球记录的 ECoG 对双侧运动进行准确解码是脑机接口技术现实应用的一个重要问题。
METHODS::In recent years, transcranial electrical stimulation (tES) has been used to improve cognitive and perceptual abilities and to boost learning. In the visual domain, transcranial random noise stimulation (tRNS), a type of tES in which electric current is randomly alternating in between two electrodes at high frequency, has shown potential in inducing long lasting perceptual improvements when coupled with tasks such as contrast detection. However, its cortical mechanisms and online effects have not been fully understood yet, and it is still unclear whether these long-term improvements are due to early-stage perceptual enhancements of contrast sensitivity or later stage mechanisms such as learning consolidation. Here we tested tRNS effects on multiple spatial frequencies and orientation, showing that tRNS enhances detection of a low contrast Gabor, but only for oblique orientation and high spatial frequency (12 cycles per degree of visual angle). No improvement was observed for low contrast and vertical stimuli. These results indicate that tRNS can enhance contrast sensitivity already after one training session, however this early onset is dependent on characteristics of the stimulus such as spatial frequency and orientation. In particular, the shallow depth of tRNS is likely to affect superficial layers of the visual cortex where neurons have higher preferred spatial frequencies than cells in further layers, while the lack of effect on vertical stimuli might reflect the optimization of the visual system to see cardinally oriented low contrast stimuli, leaving little room for short-term improvement. Taken together, these results suggest that online tRNS effects on visual perception are the result of a complex interaction between stimulus intensity and cortical anatomy, consistent with previous literature on brain stimulation.
METHODS:OBJECTIVE:There is growing interest in treating diseases by electrical stimulation and block of peripheral autonomic nerves, but a paucity of studies on excitation and block of small diameter autonomic axons. We conducted in vivo quantification of the strength-duration properties, activity-dependent slowing (ADS), and responses to kilohertz frequency (KHF) signals for the rat vagus nerve (VN). APPROACH:We conducted acute in vivo experiments in urethane-anesthetised rats. We placed two cuff electrodes on the left cervical VN and one cuff electrode on the anterior subdiaphragmatic VN. The rostral cervical cuff was used to deliver pulses to quantify recruitment and ADS. The caudal cervical cuff was used to deliver KHF signals. The subdiaphragmatic cuff was used to record compound action potentials (CAPs). MAIN RESULTS:We quantified the input-output recruitment and strength-duration curves. Fits to the data using standard strength-duration equations were qualitatively similar, but the resulting chronaxie and rheobase estimates varied substantially. We measured larger thresholds for the slowest fibres (0.5 to 1 m/s), especially at shorter pulse widths. Using a novel cross-correlation CAP-based analysis, we measured ADS of ~2.3% after 3 min of 2 Hz stimulation, which is comparable to ADS reported for sympathetic efferents in somatic nerves, but much smaller than ADS in cutaneous nociceptors. We found greater ADS with higher stimulation frequency and non-monotonic changes in CV in select cases. We found monotonically increasing block thresholds across frequencies from 10 to 80 kHz for both fast and slow fibres. Further, following 25 s of KHF signal, neural conduction could require tens of seconds to recover. SIGNIFICANCE:The quantification of mammalian autonomic nerve responses to conventional and KHF signals provides essential information for development of peripheral nerve stimulation therapies and for understanding their mechanisms of action.
METHODS:BACKGROUND:Early accounts of forced thought were reported at the onset of a focal seizure, and characterized as vague, repetitive, and involuntary intellectual auras distinct from perceptual or psychic hallucinations or illusions. Here, we examine the neural underpinnings involved in conceptual thought by presenting a series of 3 patients with epilepsy reporting intrusive thoughts during electrical stimulation of the left lateral prefrontal cortex (PFC) during invasive surgical evaluation. We illustrate the widespread networks involved through two independent brain imaging modalities: resting state functional magnetic resonance imaging (fMRI) (rs-fMRI) and task-based meta-analytic connectivity modeling (MACM). METHODS:We report the clinical and stimulation characteristics of three patients with left hemispheric language dominance who demonstrate forced thought with functional mapping. To examine the brain networks underlying this phenomenon, we used the regions of interest (ROI) centered at the active electrode pairs. We modeled functional networks using two approaches: (1) rs-fMRI functional connectivity analysis, representing 81 healthy controls and (2) meta-analytic connectivity modeling (MACM), representing 8260 healthy subjects. We also determined the overlapping regions between these three subjects' rs-fMRI and MACM networks through a conjunction analysis. RESULTS:We identified that left PFC was associated with a large-scale functional network including frontal, temporal, and parietal regions, a network that has been associated with multiple cognitive functions including semantics, speech, attention, working memory, and explicit memory. CONCLUSIONS:We illustrate the neural networks involved in conceptual thought through a unique patient population and argue that PFC supports this function through activation of a widespread network.