Successful neurological rehabilitation depends on accurate diagnosis, effective treatment, and quantitative evaluation. Neural coding, a technology for interpretation of functional and structural information of the nervous system, has contributed to the advancements in neuroimaging, brain-machine interface (BMI), and design of training devices for rehabilitation purposes. In this review, we summarized the latest breakthroughs in neuroimaging from microscale to macroscale levels with potential diagnostic applications for rehabilitation. We also reviewed the achievements in electrocorticography (ECoG) coding with both animal models and human beings for BMI design, electromyography (EMG) interpretation for interaction with external robotic systems, and robot-assisted quantitative evaluation on the progress of rehabilitation programs. Future rehabilitation would be more home-based, automatic, and self-served by patients. Further investigations and breakthroughs are mainly needed in aspects of improving the computational efficiency in neuroimaging and multichannel ECoG by selection of localized neuroinformatics, validation of the effectiveness in BMI guided rehabilitation programs, and simplification of the system operation in training devices.

Animals seek out relevant information by moving through a dynamic world, but sensory systems are usually studied under highly constrained and passive conditions that may not probe important dimensions of the neural code. Here, we explored neural coding in the barrel cortex of head-fixed mice that tracked walls with their whiskers in tactile virtual reality. Optogenetic manipulations revealed that barrel cortex plays a role in wall-tracking. Closed-loop optogenetic control of layer 4 neurons can substitute for whisker-object contact to guide behavior resembling wall tracking. We measured neural activity using two-photon calcium imaging and extracellular recordings. Neurons were tuned to the distance between the animal snout and the contralateral wall, with monotonic, unimodal, and multimodal tuning curves. This rich representation of object location in the barrel cortex could not be predicted based on simple stimulus-response relationships involving individual whiskers and likely emerges within cortical circuits.

Animals flexibly switch between different actions by changing neural activity patterns for motor control. Courting Drosophila melanogaster males produce two different acoustic signals, pulse and sine song, each of which can be promoted by artificial activation of distinct neurons. However, how the activity of these neurons implements flexible song production is unknown. Here, we developed an assay to record neuronal calcium signals in the ventral nerve cord, which contains the song motor circuit, in singing flies. We found that sine-promoting neurons, but not pulse-promoting neurons, show strong activation during sine song. In contrast, both pulse- and sine-promoting neurons are active during pulse song. Furthermore, population calcium imaging in the song circuit suggests that sine song involves activation of a subset of neurons that are also active during pulse song. Thus, differential activation of overlapping, rather than distinct, neural populations underlies flexible motor actions during acoustic communication in D. melanogaster.

Stimulus intensity is a fundamental perceptual feature in all sensory systems. In olfaction, perceived odor intensity depends on at least two variables: odor concentration; and duration of the odor exposure or adaptation. To examine how neural activity at early stages of the olfactory system represents features relevant to intensity perception, we studied the responses of mitral/tufted cells (MTCs) while manipulating odor concentration and exposure duration. Temporal profiles of MTC responses to odors changed both as a function of concentration and with adaptation. However, despite the complexity of these responses, adaptation and concentration dependencies behaved similarly. These similarities were visualized by principal component analysis of average population responses and were quantified by discriminant analysis in a trial-by-trial manner. The qualitative functional dependencies of neuronal responses paralleled psychophysics results in humans. We suggest that temporal patterns of MTC responses in the olfactory bulb contribute to an internal perceptual variable: odor intensity.

In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.

When the contrast of an image flickers as it moves, humans perceive an illusory reversal in the direction of motion. This classic illusion, called reverse-phi motion, has been well-characterized using psychophysics, and several models have been proposed to account for its effects. Here, we show that Drosophila melanogaster also respond behaviorally to the reverse-phi illusion and that the illusion is present in dendritic calcium signals of motion-sensitive neurons in the fly lobula plate. These results closely match the predictions of the predominant model of fly motion detection. However, high flicker rates cause an inversion of the reverse-phi behavioral response that is also present in calcium signals of lobula plate tangential cell dendrites but not predicted by the model. The fly’s behavioral and neural responses to the reverse-phi illusion reveal unexpected interactions between motion and flicker signals in the fly visual system and suggest that a similar correlation-based mechanism underlies visual motion detection across the animal kingdom.

Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed Drosophila melanogaster walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body, a toroidal structure in the centre of the fly brain. The neural population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity, a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors, network structures that have been proposed to support the function of navigational brain circuits.

Most behaviors involve neural dynamics in high-dimensional activity spaces. A common approach is to extract dimensions that capture task-related variability, such as those separating stimuli or choices, yielding low-dimensional, task-aligned neural activity subspaces (“coding dimensions”). However, whether these dimensions actively drive decisions or merely reflect underlying computations remains unclear. Moreover, neural activity outside these coding subspaces (“residual dimensions”) is often ignored, though it could also causally shape neural dynamics driving behavior. We developed a recurrent neural network model that fits population activity and uncovers the dynamic interactions between coding and residual subspaces on single trials. Applied to electrophysiological recordings from the anterior lateral motor cortex (ALM) and motor thalamus in mice performing a delayed response task, our model demonstrates that perturbations of residual dimensions reliably alter behavioral choices, whereas perturbations of the choice dimension, which strongly encodes the animal’s upcoming decision, are largely ineffective. These perturbation effects arise because residual dimensions drive transient amplification across an intermediate number of coding and residual dimensions (\~10), before the dynamics collapse into discrete attractor states corresponding to the animal’s choice. By dissecting the low-dimensional variability underlying error trials, we find that it primarily shifts trajectories along residual dimensions, biasing single decisions. Residual activity in thalamus shapes cortical decision dynamics, implicating weakly selective thalamic populations in the emergence of cortical selectivity. Our findings challenge the conventional focus on low-dimensional coding subspaces as sufficient framework for understanding neural computations, demonstrating that dimensions previously considered task-irrelevant and accounting for little variance can have a critical role in driving behavior.

Sensory inputs are often fluctuating and intermittent, yet animals reliably utilize them to direct behavior. Here we ask how natural stimulus fluctuations influence the dynamic neural encoding of odors. Using the locust olfactory system, we isolated two main causes of odor intermittency: chaotic odor plumes and active sampling behaviors. Despite their irregularity, chaotic odor plumes still drove dynamic neural response features including the synchronization, temporal patterning, and short-term plasticity of spiking in projection neurons, enabling classifier-based stimulus identification and activating downstream decoders (Kenyon cells). Locusts can also impose odor intermittency through active sampling movements with their unrestrained antennae. Odors triggered immediate, spatially targeted antennal scanning that, paradoxically, weakened individual neural responses. However, these frequent but weaker responses were highly informative about stimulus location. Thus, not only are odor-elicited dynamic neural responses compatible with natural stimulus fluctuations and important for stimulus identification, but locusts actively increase intermittency, possibly to improve stimulus localization.