Journal of neurophysiology最新文献

This review was inspired by a January 2024 conference held at Friday Harbor Laboratories, WA, honoring the pioneering work of A.O. Dennis Willows, who initiated research on the sea slug Tritonia diomedea (now T. exsulans). A chance discovery while he was a student at a summer course there has, over the years, led to many insights into the roles of identified neurons in neural circuits and their influence on behavior. Among Dennis's trainees was Peter Getting, whose later groundbreaking work on central pattern generators profoundly influenced the field and included one of the earliest uses of realistic modeling for understanding neural circuits. Research on Tritonia has led to key conceptual advances in polymorphic or multifunctional neural networks, intrinsic neuromodulation, and the evolution of neural circuits. It also has enhanced our understanding of geomagnetic sensing, learning and memory mechanisms, prepulse inhibition, and even drug-induced hallucinations. Although the community of researchers studying Tritonia has never been large, its contributions to neuroscience have been substantial, underscoring the importance of examining a diverse array of animal species rather than focusing on a small number of standard model organisms.

The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support discrimination of sensory stimuli or to generate an internal model of the sensory world is unclear. Correlated variability across a neural population (noise correlations) is commonly observed experimentally, and many studies demonstrate that correlated variability improves discriminative sensory coding compared to a null model with no correlations. However, such results do not address whether correlated variability is optimal for discriminative sensory coding. If the computational goal of sensory coding is discriminative, than correlated variability should be optimized to support that goal. We assessed optimality of noise correlations for discriminative sensory coding in diverse datasets by developing two novel null models, each with a biological interpretation. Across datasets, we found that correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Furthermore, biological constraints prevent many subsets of the neural populations from achieving optimality, and subselecting based on biological criteria leaves red discriminative coding performance suboptimal. Finally, we show that optimal subpopulations are exponentially small as the population size grows. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.NEW & NOTEWORTHY The brain represents the world through the activity of neural populations that exhibit correlated variability. We assessed optimality of correlated variability for discriminative sensory coding in diverse datasets by developing two novel null models. Across datasets, correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Biological constraints prevent the neural populations from achieving optimality. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.

The high-frequency activity (HFA; 80-150 Hz) in human intracranial recordings shows a differential modulation to different degrees in contrast when stimuli are behaviorally relevant, indicating a feedforward process. However, the HFA is also significantly dominated by superficial layers and exhibits a peak before 200 ms, suggesting that it is more likely a feedback signal. Magnetoencephalographic (MEG) recordings are suited to reveal an HFA modulation similar to its modulation in intracranial recordings. This allows for noninvasive, direct comparison of HFA with the C1, an established measure for feedforward input to V1, to test whether HFA represents feedforward or rather feedback. In simultaneous recordings, we used the EEG-C1 event-related potential (ERP) component and MEG-HFA to define feedforward processing in visual cortices. C1 latency preceded the HFA peak modulation, which had a more sustained response. Furthermore, modulation parameters like onset, peak time, and peak amplitude were uncorrelated. Most importantly, the C1 but not HFA distinguished small task-irrelevant contrast differences in visual stimulation. These results highlight the differential roles for the C1 and HFA in visual processing with the C1 measuring feedforward discrimination ability and HFA indexing feedforward and feedback processing.NEW & NOTEWORTHY Whether the broadband high-frequency activity (HFA) represents exclusively feedforward or feedback processing remains unclear. In this study, we compared the response characteristics of the HFA-magnetoencephalographic (MEG) and the C1-EEG component to systematic contrast modulations of task-irrelevant visual stimulation. Our findings reveal that the more sustained HFA follows the C1 component and, unlike the C1, is not modulated by task-irrelevant contrast differences. This timing of the HFA modulation suggests that HFA encompasses both feedforward and feedback processing.

A fundamental question in neuroscience is how the brain integrates egocentric (body-centered) and allocentric (landmark-centered) visual cues, but for many years this question was ignored in sensorimotor studies. This changed in recent behavioral experiments, but the underlying physiology of ego/allocentric integration remained largely unstudied. The specific goal of this review is to explain how prefrontal neurons integrate eye-centered and landmark-centered visual codes for optimal gaze behavior. First, we briefly review the whole brain/behavioral mechanisms for ego/allocentric integration in the human and summarize egocentric coding mechanisms in the primate gaze system. We then focus in more depth on cellular mechanisms for ego/allocentric coding in the frontal and supplementary eye fields. We first explain how prefrontal visual responses integrate eye-centered target and landmark codes to produce a transformation toward landmark-centered coordinates. Next, we describe what happens when a landmark shifts during the delay between seeing and acquiring a remembered target, initially resulting in independently coexisting ego/allocentric memory codes. We then describe how these codes are reintegrated in the motor burst for the gaze shift. Deep network simulations suggest that these properties emerge spontaneously for optimal gaze behavior. Finally, we synthesize these observations and relate them to normal brain function through a simplified conceptual model. Together, these results show that integration of visuospatial features continues well beyond visual cortex and suggest a general cellular mechanism for goal-directed visual behavior.

Integrated multisensory feedback plays a crucial role in balance control. Minimal fingertip contact with a surface (light touch), reduces the center of pressure (CoP) by adding sensory information about postural orientation and balance state. Electrical vestibular stimulation (EVS) can increase sway by adding erroneous vestibular cues. This juxtaposition of conflicting sensory cues can be exploited to explore the dynamics of sensorimotor adaptations. We used continuous stochastic EVS (0-25 Hz; ±4 mA; 200-300 s) to evoke balance responses in CoP (experiment 1, experiment 2). Systems analyses (coherence, gain) quantified coupling and size of balance responses to EVS. We had participants either touch (TOUCH; <2 N) or not touch (NO-TOUCH) a load cell during EVS (experiment 1, experiment 2), or we intermittently removed the touch surface (experiment 2) to measure the effects of light touch on vestibular-evoked balance responses. We hypothesized that coherence and gain between EVS and CoP would decrease, consistent with the central nervous system (CNS) down-weighting vestibular cues that conflict with light touch. Light touch reduced CoP displacement but increased variation in the CoP signal explained by EVS input. Significant coherence between EVS and CoP was observed up to ∼30 Hz in both conditions but was significantly greater in the TOUCH condition from 12 to 28.5 Hz. Conversely, EVS-CoP gain was 63% lower in TOUCH compared with NO-TOUCH. Our findings show that light touch can reduce the size of vestibular-evoked responses but also increase high-frequency vestibular contributions for sway. This suggests that the CNS can use discrete changes in sensory inputs to alter balance behavior but cannot fully suppress responses to a potent cue.NEW & NOTEWORTHY This study reveals that minimal fingertip contact (light touch) during balance tasks not only diminishes the impact of electrical vestibular stimulation (EVS) on sway but also exposes a high-frequency center of pressure element, correlated to vestibular inputs, not typically seen in free standing. Specifically, light touch decreases the magnitude of EVS-induced sway while increasing coherence with EVS at higher frequencies. This illustrates the central nervous system's capacity to adaptively reweight sensorimotor processes for balance control.

Respiration is governed by a central rhythm and pattern generator, which has the pre-Bötzinger complex as the inspiratory oscillator initiating the coordinated activity of several respiratory muscles, including the diaphragm, intercostals, and upper airway muscles. The diaphragm is the main inspiratory pump muscle driving inflow, whereas dilator upper airway muscles, such as tongue muscles, reduce airway resistance during inspiration. Breathing exhibits a marked state-dependent pattern attributed to changes in neuromodulatory tone in respiratory-related brain regions, including decreases in noradrenaline and serotonin and increases in acetylcholine levels during rapid eye movement (REM) sleep. Here, we discuss respiratory modulation by acetylcholine acting on its metabotropic muscarinic receptors, focusing on the regulation of upper airway muscle activity during sleep and wakefulness and its changing effects with postnatal maturation. We focus on experimental data examining muscarinic receptor distribution patterns, the ion channels they modulate, and how these distribution patterns change with postnatal maturation. We also consider experimental data highlighting cholinergic cellular and synaptic effects on hypoglossal motoneurons and pre-Bötzinger complex neurons and how they might explain changes in the effects of cholinergic modulation with development. Overall, this discussion is critical to comprehending the postnatal maturation in the cholinergic modulation of the respiratory control system leading to opposing effects of muscarinic receptors on upper airway muscle activity in neonate (excitatory) and adult (inhibitory) preparations. The changes in cholinergic pathways associated with dysfunctional upper airway patency control are also discussed in the context of pathologies such as sleep-disordered breathing.

Deep dry needling (DDN) is a method to treat muscle trigger points (TrPs) often found in persons with neuromuscular pain and spasticity. Currently, its neurophysiological actions are not well established. Thus, to understand how DDN affects spinal cord physiology, we investigated the effects of TrP DDN on spinal reflexes. In 17 adults with latent TrPs in the medial gastrocnemius (MG) without known neurological or orthopedic injuries, the H reflex, M wave, and reciprocal inhibition in the soleus, MG, and lateral gastrocnemius (LG) and passive ankle range of motion (ROM) were measured before and immediately, 90 min, and 72 h after a single bout of DDN at the MG TrPs. The MG maximum M wave (M_max) amplitude was decreased immediately and 90 min post DDN (by -14% and -18%) and returned to pre-DDN level at 72 h post. LG and soleus M_max did not change. The maximum H reflex (H_max) amplitude did not change in any of the triceps surae. Soleus inhibition was increased significantly immediately (+30%) and 72 h (+36%) post DDN. ROM was increased by ≈4° immediately and ≈3° at 72 h post DDN. Temporary reduction of MG (but not soleus or LG) M_max amplitude after DDN and its recovery at 72 h post indicate temporary and specific effects of DDN in the treated muscle. The immediate and 72 h post increases in the ROM and soleus inhibition with no changes in H_max suggest complex effects of DDN at the spinal level.NEW & NOTEWORTHY In this study, we examined the effects of deep dry needling (DDN) on spinal reflexes in the triceps surae. We found that the H reflex (an excitatory reflex) did not change after DDN but soleus inhibition was increased immediately and 72 h after DDN, corresponding to increases in ankle range of motion. Differential effects of DDN on excitatory and inhibitory reflexes over the first 72 h may reflect its complex neurophysiological effects at the spinal level.

Surface electromyography (sEMG) is useful for studying muscle function and controlling prosthetics, but cross talk from nearby muscles often limits its effectiveness. High-density surface EMG (HD-sEMG) improves spatial resolution, allowing for the isolation of M-waves in the densely packed forearm muscles. This study assessed HD-sEMG for localizing M-waves and evaluated the impact of spatial filters on cross talk reduction. We administered peripheral nerve stimulation to activate forearm muscles in five participants. We analyzed cross talk by correlating the shape of M-waves between electrodes and used ultrasound to confirm muscle identity and location. At low-stimulation intensities, we successfully isolated M-waves with minimal cross talk without spatial filtering. Higher recruitment levels produced significant cross talk, which was reduced by applying bipolar or tripolar spatial filters. M-waves from the monopolar HD-sEMG montage showed high correlations between electrodes (r = 0.97 transversely; r = 0.95 longitudinally), while bipolar and tripolar montages showed lower correlations (bipolar: r = 0.41 transversely; r = 0.19 longitudinally; tripolar: r = 0.17 transversely; r = 0.01 longitudinally). The tripolar filter significantly reduced cross talk (51.10% amplitude decay one electrode away) compared with no filter (10.32% amplitude decay one electrode away), effectively reducing cross talk to negligible levels at distances ≥2.55 cm. Ultrasound was crucial for distinguishing true activation from artifacts caused by converging signals along muscle boundaries. Spatially filtered HD-sEMG accurately detects and isolates M-waves in the forearm, and ultrasound imaging is useful for verifying the location and identity of the muscles underlying the HD-sEMG grids.NEW & NOTEWORTHY This study introduces an innovative approach to enhancing evoked potential measurements using high-density surface electromyography (HD-sEMG). The precision and localization of evoked potentials are significantly improved by spatial filters and ultrasound imaging, offering a novel method for better assessing motor pathway integrity. These advancements could lead to more accurate tools for detecting and treating neurological deficits, making it a significant contribution to neurophysiological research.

In a recently developed associative rehabilitative brain-computer interface (BCI) system, electroencephalography (EEG) is used to identify the most active phase of the motor cortex during attempted movement and deliver precisely timed peripheral stimulation during training. This approach has been demonstrated to facilitate corticospinal excitability and functional recovery in patients with lower limb weakness following stroke. The current study expands those findings by investigating changes in corticospinal excitability following the associative BCI intervention in patients with post stroke with upper limb weakness. In a randomized controlled trial, 24 patients with subacute stroke, subdivided into an intervention group and a "sham" control group, performed 30 wrist extensions. The intervention comprised 30 pairings of single peripheral nerve stimulation at the motor threshold, timed so that the generated afferent volley arrived at the motor cortex during the peak negativity of the movement-related cortical potential (MRCP), which was identified with EEG. The sham group underwent the same intervention, though the intensity of the nerve stimulation was below the perception threshold. Immediately after training, patients in the associative group exhibited significantly larger amplitudes of muscular-evoked potentials, compared with pretraining measurements in response to transcranial magnetic stimulation. These changes persisted for at least 30 min and were not observed in the sham group. We demonstrate that motor-evoked potential amplitudes increased significantly following paired associative BCI training targeting upper limb muscles in patients with subacute stroke, which is in line with results from lower limb studies.NEW & NOTEWORTHY We have demonstrated that a single training session with an associative brain-computer interface increased corticospinal excitability in patients suffering from upper limb weakness following stroke. This is the first time such an effect is described in the upper limb, which paves the way for effect augmentation of existing upper limb rehabilitation protocols.

Due to spinal reflex loops, descending activation from the brain is not the only source of muscle activation that ultimately generates movement. This study directly estimates descending activation patterns from measured patterns of muscle activation (electromyographic; EMG) during human arm movements. A simple model of the spinal stretch reflex is calibrated in a postural unloading task and then used to estimate descending activation patterns from muscle EMG patterns and kinematics during voluntary arm motion performed at different speeds. We observed three key features of the estimated descending activation patterns: 1) Within about the first 15% of movement duration, descending and muscle activations are temporally aligned. Thereafter, they diverge and develop qualitatively different temporal profiles. 2) The time course of descending activation is monotonic for slow movements, nonmonotonic for fast movements. 3) Varying model parameters such as the spinal reflex gain or the level of cocontraction do not qualitatively change the temporal pattern of estimated descending activation. Our findings highlight the substantial contribution of spinal reflex loops to movement generation, while at the same time providing evidence that the brain must generate qualitatively different descending activation patterns for movements that vary in their mechanical dynamics.NEW & NOTEWORTHY We propose a new method that directly estimates descending activation from measured electromyographic (EMG) signals and arm kinematics by inverting a model of the spinal stretch reflex, without the need for muscle models or an arm dynamics model. This approach identifies key features of the time structure of descending activation as movement speed is varied, while also revealing the significant contribution of the spinal stretch reflex to movement generation.