Internal feedback in the cortical perception-action loop enables fast and accurate behavior.

Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control, drawing on control theory, have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional perception-action loop. However, the sensorimotor loop contains internal delays in sensory and motor pathways, which can lead to unstable control. We show here that these delays can be compensated by internal feedback signals that flow backward, from motor toward sensory areas. This internal feedback is ubiquitous in neural sensorimotor systems, and we show how internal feedback compensates internal delays. This is accomplished by filtering out self-generated and other predictable changes so that unpredicted, actionable information can be rapidly transmitted toward action by the fastest components, effectively compressing the sensory input to more efficiently use feedforward pathways: Tracts of fast, giant neurons necessarily convey less accurate signals than tracts with many smaller neurons, but they are crucial for fast and accurate behavior. We use a mathematically tractable control model to show that internal feedback has an indispensable role in achieving state estimation, localization of function (how different parts of the cortex control different parts of the body), and attention, all of which are crucial for effective sensorimotor control. This control model can explain anatomical, physiological, and behavioral observations, including motor signals in the visual cortex, heterogeneous kinetics of sensory receptors, and the presence of giant cells in the cortex of humans as well as internal feedback patterns and unexplained heterogeneity in neural systems.

Response to comment on 'A conserved strategy for inducing appendage regeneration in moon jellyfish, Drosophila, and mice'.

Previously we reported evidence that a regenerative response in the appendages of moon jellyfish, fruit flies, and mice can be promoted by nutrient modulation (Abrams et al., 2021). Sustar and Tuthill subsequently reported that they had not been able to reproduce the induced regenerative response in flies (Sustar and Tuthill, 2023). Here we discuss that differences in the amputation method, treatment concentrations, age of the animals, and stress management explain why they did not observe a regenerative response in flies. Typically, 30-50% of treated flies showed response in our assay.

De-glutathionylases: The resilient underdogs to keep neurodegeneration at bay.

Proteins become S-glutathionylated as a result of the derivatization of their cysteine thiols with the thiolate anion derivative of glutathione; this process is frequently linked to diseases and protein misbehavior. Along with the other well-known oxidative modifications like S-nitrosylation, S-glutathionylation has quickly emerged as a major contributor to a number of diseases, with a focus on neurodegeneration. The immense clinical significance of S-glutathionylation in cell signaling and the genesis of diseases are progressively coming to light with advanced research, which is also creating new opportunities for prompt diagnostics that utilize this phenomenon. In-depth investigation in recent years has revealed other significant deglutathionylases in addition to glutaredoxin, necessitating the hunt for their specific substrates. The precise catalytic mechanisms of these enzymes must also be understood, along with how the intracellular environment affects their impact on protein conformation and function. These insights must then be extrapolated to the understanding of neurodegeneration and the introduction of novel and clever therapeutic approaches to clinics. Clarifying the importance of the functional overlap of glutaredoxin and other deglutathionylases and examining their complementary functions as defense systems in the face of stress are essential prerequisites for predicting and promoting cell survival under high oxidative/nitrosative stress.

A conserved strategy for inducing appendage regeneration in moon jellyfish, Drosophila, and mice.

Can limb regeneration be induced? Few have pursued this question, and an evolutionarily conserved strategy has yet to emerge. This study reports a strategy for inducing regenerative response in appendages, which works across three species that span the animal phylogeny. In Cnidaria, the frequency of appendage regeneration in the moon jellyfish Aurelia was increased by feeding with the amino acid L-leucine and the growth hormone insulin. In insects, the same strategy induced tibia regeneration in adult Drosophila. Finally, in mammals, L-leucine and sucrose administration induced digit regeneration in adult mice, including dramatically from mid-phalangeal amputation. The conserved effect of L-leucine and insulin/sugar suggests a key role for energetic parameters in regeneration induction. The simplicity by which nutrient supplementation can induce appendage regeneration provides a testable hypothesis across animals.

The ability of animals to replace damaged or lost tissue (or 'regenerate') is a sliding scale, with some animals able to regenerate whole limbs, while others can only scar. But why some animals can regenerate while others have more limited capabilities has puzzled the scientific community for many years. The likes of Charles Darwin and August Weismann suggested regeneration only evolves in a particular organ. In contrast, Thomas Morgan suggested that all animals are equipped with the tools to regenerate but differ in whether they are able to activate these processes. If the latter were true, it could be possible to 'switch on' regeneration. Animals that keep growing throughout their life and do not regulate their body temperatures are more likely to be able to regenerate. But what do growth and temperature regulation have in common? Both are highly energy-intensive, with temperature regulation potentially diverting energy from other processes. A question therefore presents itself: could limb regeneration be switched on by supplying animals with more energy, either in the form of nutrients like sugars or amino acids, or by giving them growth hormones such as insulin? Abrams, Tan, Li et al. tested this hypothesis by amputating the limbs of jellyfish, flies and mice, and then supplementing their diet with sucrose (a sugar), leucine (an amino acid) and/or insulin for eight weeks while they healed. Typically, jellyfish rearrange their remaining arms when one is lost, while fruit flies are not known to regenerate limbs. House mice are usually only able to regenerate the very tip of an amputated digit. But in Abrams, Tan, Li et al.'s experiments, leucine and insulin supplements stimulated limb regeneration in jellyfish and adult fruit flies, and leucine and sucrose supplements allowed mice to regenerate digits from below the second knuckle. Although regeneration was not observed in all animals, these results demonstrate that regeneration can be induced, and that it can be done relatively easily, by feeding animals extra sugar and amino acids. These findings highlight increasing the energy supplies of different animals by manipulating their diets while they are healing from an amputated limb can aid in regeneration. This could in the future pave the way for new therapeutic approaches to tissue and organ regeneration.

CLoSES: A platform for closed-loop intracranial stimulation in humans.

Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is required to perform different tests with a single participant and to comply with clinical requirements. In order to investigate closed-loop stimulation for research and therapeutic use, we developed a Closed-Loop System for Electrical Stimulation (CLoSES) that computes neural features which are then used in a decision algorithm to trigger stimulation in near real-time. To summarize CLoSES, intracranial electroencephalography (iEEG) signals are acquired, band-pass filtered, and local and network features are continuously computed. If target features are detected (e.g. above a preset threshold for a certain duration), stimulation is triggered. Not only could the system trigger stimulation while detecting real-time neural features, but we incorporated a pipeline wherein we used an encoder/decoder model to estimate a hidden cognitive state from the neural features. CLoSES provides a flexible platform to implement a variety of closed-loop experimental paradigms in humans. CLoSES has been successfully used with twelve patients implanted with depth electrodes in the epilepsy monitoring unit. During cognitive tasks (N=5), stimulation in closed loop modified a cognitive hidden state on a trial by trial basis. Sleep spindle oscillations (N=6) and sharp transient epileptic activity (N=9) were detected in near real-time, and stimulation was applied during the event or at specified delays (N=3). In addition, we measured the capabilities of the CLoSES system. Total latency was related to the characteristics of the event being detected, with tens of milliseconds for epileptic activity and hundreds of milliseconds for spindle detection. Stepwise latency, the actual duration of each continuous step, was within the specified fixed-step duration and increased linearly with the number of channels and features. We anticipate that probing neural dynamics and interaction between brain states and stimulation responses with CLoSES will lead to novel insights into the mechanism of normal and pathological brain activity, the discovery and evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.

Volitional control of single-electrode high gamma local field potentials by people with paralysis.

Intracortical brain-computer interfaces (BCIs) can enable individuals to control effectors, such as a computer cursor, by directly decoding the user's movement intentions from action potentials and local field potentials (LFPs) recorded within the motor cortex. However, the accuracy and complexity of effector control achieved with such "biomimetic" BCIs will depend on the degree to which the intended movements used to elicit control modulate the neural activity. In particular, channels that do not record distinguishable action potentials and only record LFP modulations may be of limited use for BCI control. In contrast, a biofeedback approach may surpass these limitations by letting the participants generate new control signals and learn strategies that improve the volitional control of signals used for effector control. Here, we show that, by using a biofeedback paradigm, three individuals with tetraplegia achieved volitional control of gamma LFPs (40-400 Hz) recorded by a single microelectrode implanted in the precentral gyrus. Control was improved over a pair of consecutive sessions up to 3 days apart. In all but one session, the channel used to achieve control lacked distinguishable action potentials. Our results indicate that biofeedback LFP-based BCIs may potentially contribute to the neural modulation necessary to obtain reliable and useful control of effectors. NEW & NOTEWORTHY Our study demonstrates that people with tetraplegia can volitionally control individual high-gamma local-field potential (LFP) channels recorded from the motor cortex, and that this control can be improved using biofeedback. Motor cortical LFP signals are thought to be both informative and stable intracortical signals and, thus, of importance for future brain-computer interfaces.

Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals.

Restoring communication for people with locked-in syndrome remains a challenging clinical problem without a reliable solution. Recent studies have shown that people with paralysis can use brain-computer interfaces (BCIs) based on intracortical spiking activity to efficiently type messages. However, due to neuronal signal instability, most intracortical BCIs have required frequent calibration and continuous assistance of skilled engineers to maintain performance. Here, an individual with locked-in syndrome due to brain stem stroke and an individual with tetraplegia secondary to amyotrophic lateral sclerosis (ALS) used a simple communication BCI based on intracortical local field potentials (LFPs) for 76 and 138 days, respectively, without recalibration and without significant loss of performance. BCI spelling rates of 3.07 and 6.88 correct characters/minute allowed the participants to type messages and write emails. Our results indicate that people with locked-in syndrome could soon use a slow but reliable LFP-based BCI for everyday communication without ongoing intervention from a technician or caregiver. NEW & NOTEWORTHY This study demonstrates, for the first time, stable repeated use of an intracortical brain-computer interface by people with tetraplegia over up to four and a half months. The approach uses local field potentials (LFPs), signals that may be more stable than neuronal action potentials, to decode participants' commands. Throughout the several months of evaluation, the decoder remained unchanged; thus no technical interventions were required to maintain consistent brain-computer interface operation.

Rapid calibration of an intracortical brain-computer interface for people with tetraplegia.

OBJECTIVE: Brain-computer interfaces (BCIs) can enable individuals with tetraplegia to communicate and control external devices. Though much progress has been made in improving the speed and robustness of neural control provided by intracortical BCIs, little research has been devoted to minimizing the amount of time spent on decoder calibration. APPROACH: We investigated the amount of time users needed to calibrate decoders and achieve performance saturation using two markedly different decoding algorithms: the steady-state Kalman filter, and a novel technique using Gaussian process regression (GP-DKF). MAIN RESULTS: Three people with tetraplegia gained rapid closed-loop neural cursor control and peak, plateaued decoder performance within 3 min of initializing calibration. We also show that a BCI-naïve user (T5) was able to rapidly attain closed-loop neural cursor control with the GP-DKF using self-selected movement imagery on his first-ever day of closed-loop BCI use, acquiring a target 37 s after initiating calibration. SIGNIFICANCE: These results demonstrate the potential for an intracortical BCI to be used immediately after deployment by people with paralysis, without the need for user learning or extensive system calibration.

A modular, closed-loop platform for intracranial stimulation in people with neurological disorders.

Neuromodulation systems based on electrical stimulation can be used to investigate, probe, and potentially treat a range of neurological disorders. The effects of ongoing neural state and dynamics on stimulation response, and of stimulation parameters on neural state, have broad implications for the development of closed-loop neuro-modulation approaches. We describe the development of a modular, low-latency platform for pre-clinical, closed-loop neuromodulation studies with human participants. We illustrate the uses of the platform in a stimulation case study with a person with epilepsy undergoing neuro-monitoring prior to resective surgery. We demonstrate the efficacy of the system by tracking interictal epileptiform discharges in the local field potential to trigger intracranial electrical stimulation, and show that the response to stimulation depends on the neural state.

Retrospectively supervised click decoder calibration for self-calibrating point-and-click brain-computer interfaces.

Brain-computer interfaces (BCIs) aim to restore independence to people with severe motor disabilities by allowing control of acursor on a computer screen or other effectors with neural activity. However, physiological and/or recording-related nonstationarities in neural signals can limit long-term decoding stability, and it would be tedious for users to pause use of the BCI whenever neural control degrades to perform decoder recalibration routines. We recently demonstrated that a kinematic decoder (i.e. a decoder that controls cursor movement) can be recalibrated using data acquired during practical point-and-click control of the BCI by retrospectively inferring users' intended movement directions based on their subsequent selections. Here, we extend these methods to allow the click decoder to also be recalibrated using data acquired during practical BCI use. We retrospectively labeled neural data patterns as corresponding to "click" during all time bins in which the click log-likelihood (decoded using linear discriminant analysis, or LDA) had been above the click threshold that was used during real-time neural control. We labeled as "non-click" those periods that the kinematic decoder's retrospective target inference (RTI) heuristics determined to be consistent with intended cursor movement. Once these neural activity patterns were labeled, the click decoder was calibrated using standard supervised classifier training methods. Combined with real-time bias correction and baseline firing rate tracking, this set of "retrospectively labeled" decoder calibration methods enabled a BrainGate participant with amyotrophic lateral sclerosis (T9) to type freely across 11 research sessions spanning 29days, maintaining high-performance neural control over cursor movement and click without needing to interrupt virtual keyboard use for explicit calibration tasks. By eliminating the need for tedious calibration tasks with prescribed targets and pre-specified click times, this approach advances the potential clinical utility of intracortical BCIs for individuals with severe motor disability.

Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface.

Brain-computer interfaces (BCIs) promise to restore independence for people with severe motor disabilities by translating decoded neural activity directly into the control of a computer. However, recorded neural signals are not stationary (that is, can change over time), degrading the quality of decoding. Requiring users to pause what they are doing whenever signals change to perform decoder recalibration routines is time-consuming and impractical for everyday use of BCIs. We demonstrate that signal nonstationarity in an intracortical BCI can be mitigated automatically in software, enabling long periods (hours to days) of self-paced point-and-click typing by people with tetraplegia, without degradation in neural control. Three key innovations were included in our approach: tracking the statistics of the neural activity during self-timed pauses in neural control, velocity bias correction during neural control, and periodically recalibrating the decoder using data acquired during typing by mapping neural activity to movement intentions that are inferred retrospectively based on the user's self-selected targets. These methods, which can be extended to a variety of neurally controlled applications, advance the potential for intracortical BCIs to help restore independent communication and assistive device control for people with paralysis.

Clinical translation of a high-performance neural prosthesis.

Neural prostheses have the potential to improve the quality of life of individuals with paralysis by directly mapping neural activity to limb- and computer-control signals. We translated a neural prosthetic system previously developed in animal model studies for use by two individuals with amyotrophic lateral sclerosis who had intracortical microelectrode arrays placed in motor cortex. Measured more than 1 year after implant, the neural cursor-control system showed the highest published performance achieved by a person to date, more than double that of previous pilot clinical trial participants.

Neural population dynamics in human motor cortex during movements in people with ALS.

The prevailing view of motor cortex holds that motor cortical neural activity represents muscle or movement parameters. However, recent studies in non-human primates have shown that neural activity does not simply represent muscle or movement parameters; instead, its temporal structure is well-described by a dynamical system where activity during movement evolves lawfully from an initial pre-movement state. In this study, we analyze neuronal ensemble activity in motor cortex in two clinical trial participants diagnosed with Amyotrophic Lateral Sclerosis (ALS). We find that activity in human motor cortex has similar dynamical structure to that of non-human primates, indicating that human motor cortex contains a similar underlying dynamical system for movement generation.