Interactions between excitatory and inhibitory neurons in the cerebral cortex give rise to different regimes of activity and modulate brain oscillations. A prominent regime in the cortex is the inhibition-stabilized network (ISN), defined by strong recurrent excitation balanced by inhibition. While theoretical models have captured the response of brain circuits in the ISN state, their connectivity is typically hard-wired, leaving unanswered how a network may self-organize to an ISN state and dynamically switch between ISN and non-ISN states to modulate oscillations. Here, we introduce a mean-rate model of coupled Wilson-Cowan equations, link ISN and non-ISN states to Kolmogorov-Sinai entropy, and demonstrate how homeostatic plasticity (HP) allows the network to express both states depending on its level of tonic activity. This mechanism enables the model to capture a broad range of experimental effects, including (i) a paradoxical decrease in inhibitory activity, (ii) a phase offset between excitation and inhibition, and (iii) damped gamma oscillations. Further, the model accounts for experimental work on asynchronous quenching, where an external input suppresses intrinsic oscillations. Together, findings show that oscillatory activity is modulated by the dynamical regime of the network under the control of HP, thus advancing a framework that bridges neural dynamics, entropy, oscillations, and synaptic plasticity.

Vision training protocols, especially those for subjects with brain impairments, often employ a form of visual discrimination in which specific stimuli must be identified over the course of many days. Trainers can control exercise difficulty by modifying the stimuli in several ways, e.g., Gaussian smoothing, affine transformations, adding pixel noise or varying contrast and brightness. Typically, subjects improve performance in training, but such gains do not generalize afterwards. In a previous paper, we introduced a Kalman Filter model of vision training that, when coupled with a Shannon-type information-theoretic assessment technology, "mutual information", might be used to assess a protocol’s potential for lasting acuity gains. Our empirical observation, based on about 300 training protocols with only one image (stimulus) pair, was that including correlated noise, as a training feature, seemed to improve the chances of a good generalization outcome. In this paper, using a sample of more than 3000 vision training protocols, with 5 image pairs of various complexities (entropies), 11 pixel noise levels, 8 pixel noise correlation types and 7 image distortion strategies, we extend and enhance the previous arguments. That is, we believe our models can be used to better understand which protocols may inhibit or enhance perceptual learning and, hence, show the way to improved brain training for individuals with cortical blindness. This would be a significant breakthrough since, currently, vision training, for this condition, is often ineffective. We also discuss how one might apply simple statistical techniques to interpolate, extrapolate or optimize protocol features. Future work, targeted for 2025, will focus on laboratory experiments that will allow us to explore and validate our ideas and observations.

Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons comprising those connections may themselves be particularly susceptible to neurostimulation. Here, we test this hypothesis by identifying long-range projections in single-unit recordings from nonhuman primates receiving transcranial alternating current stimulation. We find that putative long-range projections are more strongly affected by stimulation than other cells. Specifically, they are both more entrained on average and account for occurrences of extremely strong entrainment. Given that stimulation appears to target the edges, rather than nodes, of neural networks, it may be necessary to rethink how neurostimulation strategies are designed.

Cortical area V4 is thought to be critical for visual object recognition. It contains millimeter-scale domains in which neurons are highly selective for stimulus features such as shape, motion, and color. In theory, many different stimuli can be decoded from neural activity in each of these domains, but whether the brain actually makes use of this information is unknown. Here we have tested this hypothesis, using reversible inactivation of V4 in non-human primates performing a shape discrimination task. We find that training with the stimuli preferred by a particular domain causes the brain to develop a simple readout that ignores much of the information in the V4 neural population. In contrast, training with other stimuli leads to a more distributed readout of the V4 population. Thus, specialized cortical domains do not necessarily have a fixed behavioral function, but they can powerfully influence the learning of new perceptual tasks. ### Competing Interest Statement The authors have declared no competing interest.

Anatomical studies have revealed a prominent role for feedback projections in the primate visual cortex. Theoretical models suggest that these projections support important brain functions such as attention, prediction, and learning. However, these models make different predictions about the relationship between feedback connectivity and neuronal stimulus selectivity. We have therefore performed simultaneous recordings in different regions of the primate dorsal visual pathway. Specifically, we recorded neural activity from the medial superior temporal (MST) area, and one of its main feedback targets, the middle temporal (MT) area. We estimated functional connectivity from correlations in the single-neuron spike trains and performed electrical microstimulation in MST to determine its causal influence on MT. Both methods revealed that inhibitory feedback occurred more commonly when the source and target neurons had very different stimulus preferences. At the same time, the strength of feedback suppression was greater for neurons with similar preferences. Excitatory feedback projections, in contrast, showed no consistent relationship with stimulus preferences. These results suggest that corticocortical feedback could play a role in shaping sensory responses according to behavioral or environmental context.NEW & NOTEWORTHY Here, we show that corticocortical feedback influences are often determined by the selectivity of the individual neurons. A common motif is the occurrence of inhibitory feedback among neurons with very different stimulus preferences. This results in strong suppression of responses in area MT when MST is electrically stimulated. Interestingly, this feedback shows a complex interaction with ongoing visual stimulation, being powerfully suppressive when visual inputs are strong, yet excitatory when visual inputs are weak.

Perception is a function of both stimulus features and active sensory sampling. The illusion of perceptual filling-in occurs when eye gaze is kept still: visual boundary perception may fail, causing adjacent visual features to remarkably merge into one uniform visual surface. Microsaccades-small, involuntary eye movements during gaze fixation-counteract perceptual filling-in, but the mechanisms underlying this process are not well-understood. We investigated whether microsaccade efficacy for preventing filling-in depends on two boundary properties, namely, color contrast and retinal eccentricity (distance from gaze center). Twenty-one human participants (male and female) fixated on a point until they experienced filling-in between two isoluminant colored surfaces. We found that increased color contrast independently extends the duration before filling-in, but does not alter the impact of individual microsaccades. Conversely, lower eccentricity delayed filling-in only by increasing microsaccade efficacy. We propose that microsaccades facilitate stable boundary perception via a transient retinal motion signal that scales with eccentricity but is invariant to boundary contrast. These results shed light on how incessant eye movements integrate with ongoing stimulus processing to stabilize perceptual detail, with implications for visual rehabilitation and the optimization of visual presentations in virtual and augmented reality environments.

Humans and other primates are capable of learning to recognize new visual stimuli throughout their lifetimes. Most theoretical models assume that such learning occurs through the adjustment of the large number of synaptic weights connecting the visual cortex to downstream decision-making areas. While this approach to learning can optimize performance on behavioral tasks, it can also be costly in terms of time and energy. An alternative hypothesis is that the brain favors simpler learning rules that do not necessarily optimize the readout of information from visual cortical neurons. Here, we have examined these hypotheses by reversibly inactivating visual area V4 in non-human primates at different stages of training on form discrimination tasks. We find that V4 inactivation generally has a behavioral effect for only a subset of the stimuli that are encoded in the V4 population activity, specifically those that can be represented efficiently in the population firing rate. As a result, neural measures of discriminability do not necessarily predict the causal contribution of V4 neurons to task performance. This pattern of results can be explained by incorporating a strong inductive bias for simpler perceptual readouts into existing theoretical frameworks. Such a simplicity bias is suboptimal in the sense that it ignores information that could theoretically be extracted from the neural population, but it has the likely advantage of facilitating efficient learning on ecologically relevant timescales.

Abstract Electrical stimulation can regulate brain activity, producing clear clinical benefits, but focal and effective neuromodulation often requires surgically implanted electrodes. Recent studies argue that temporal interference (TI) stimulation may provide similar outcomes non-invasively. During TI, scalp electrodes generate multiple electrical fields in the brain, modulating neural activity only at their intersection. Despite considerable enthusiasm for this approach, little empirical evidence demonstrates its effectiveness, especially under conditions suitable for human use. Here, using single-neuron recordings in non-human primates, we establish that TI reliably alters the timing, but not the rate, of spiking activity. However, we show that TI requires strategies—high carrier frequencies, multiple electrodes, and amplitude-modulated waveforms—that also limit its effectiveness. Combined, these factors make TI 80 % weaker than other forms of non-invasive brain stimulation. Although unlikely to cause widespread neuronal entrainment, TI may be ideal for disrupting pathological oscillatory activity, a hallmark of many neurological disorders.

The primate visual cortex contains various regions that exhibit specialization for different stimulus properties, such as motion, shape, and color. Within each region, there is often further specialization, such that particular stimulus features, such as horizontal and vertical orientations, are over-represented. These asymmetries are associated with well-known perceptual biases, but little is known about how they influence visual learning. Most theories would predict that learning is optimal, in the sense that it is unaffected by these asymmetries. However, other approaches to learning would result in specific patterns of perceptual biases. To distinguish between these possibilities, we trained human observers to discriminate between expanding and contracting motion patterns, which have a highly asymmetrical representation in the visual cortex. Observers exhibited biased percepts of these stimuli, and these biases were affected by training in ways that were often suboptimal. We simulated different neural network models and found that a learning rule that involved only adjustments to decision criteria, rather than connection weights, could account for our data. These results suggest that cortical asymmetries influence visual perception and that human observers often rely on suboptimal strategies for learning.

Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there is a longstanding debate about whether CP reflects a causal influence on decisions or an echo of decision-making activity elsewhere in the brain. Here, we show that CP can reflect a third variable, namely, the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of primate cortex responded more strongly during trials that involved a saccade toward their receptive fields. This variability accounted for much of the CP observed across the neuronal population, and it arose through training. Moreover, pharmacological inactivation of MT biased behavioral responses away from the corresponding visual field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions and that this plasticity can shape the neural circuitry of perceptual decision-making.

Perceptual learning is the process by which experience alters how incoming sensory information is processed by the brain to give rise to behavior—it is critical for how humans educate children, train experts, treat diseases, and promote health and well-being throughout the lifespan. Knowledge of perceptual learning requires basic and applied research in humans and nonhuman animal models, which informs strategic targets for advancing applications. Commercial products to induce perceptual learning are proliferating rapidly with limited regulation (e.g., for rehabilitation), while at the same time basic science is increasingly restricted by changing regulations (such as new granting-agency definitions of clinical trials). Realizing the full potential of perceptual learning requires balancing basic and translational science to advance new knowledge, while serving and protecting consumers. Reforms can promote open, accessible, and representative research, and the translation of this research to applications across different sectors of society.

In this issue of Neuron, Khazali et al.(1) record neural activity during coordinated reaches and saccades. They find that excitatory neurons link arm and eye movement regions of parietal cortex, creating a multiregional mode that predicts movement timing and direction.

Transcranial electrical stimulation (tES) is one of the oldest and yet least understood forms of brain stimulation. The idea that a weak electrical stimulus, applied outside the head, can meaningfully affect neural activity is often regarded as mysterious. Here, we argue that the direct effects of tES are not so mysterious: Extensive data from a wide range of model systems shows it has appreciable effects on the activity of individual neurons. Instead, the real mysteries are how tES interacts with the brain’s own activity and how these dynamics can be controlled to produce desirable therapeutic effects. These are challenging problems, akin to repairing a complex machine while it is running, but they are not unique to tES or even neuroscience. We suggest that models of coupled oscillators, a common tool for studying interactions in other fields, may provide valuable insights. By combining these tools with our growing, interdisciplinary knowledge of brain dynamics, we are now in a good position to make progress in this area and meet the high demand for effective neuromodulation in neuroscience and psychiatry.

Background: Cortical blindness is a form of severe vision loss that is caused by damage to the primary visual cortex (V1) or its afferents. This condition has devastating effects on quality of life and independence. While there are few treatments currently available, accumulating evidence shows that certain visual functions can be restored with appropriate perceptual training: Stimulus sensitivity can be increased within portions of the blind visual field. However, this increased sensitivity often remains highly specific to the trained stimulus, limiting the overall improvement in visual function. Objective: Recent advances in the field of perceptual learning show that such specificity can be overcome with training paradigms that leverage the properties of higher-level visual cortical structures, which have greater capacity to generalize across stimulus positions and features. This targeting can be accomplished by using more complex training stimuli that elicit robust responses in these visual structures. Methods: We trained cortically blind subjects with a complex optic flow motion stimulus that was presented in a location of their blind field. Participants were instructed to train with the stimulus at home for approximately 30 minutes per day. Once performance plateaued, the stimulus was moved deeper into the blind field. A battery of pre- and post-training measures, with careful eye tracking, was performed to quantify the improvements. Results: We show that 1) optic flow motion discrimination can be relearned in cortically blind fields; 2) training with an optic flow stimulus can lead to improvements that transfer to different tasks and untrained locations; and 3) such training leads to a significant expansion of the visual field. The observed expansion of the visual field was present even when eye movements were carefully controlled. Finally, we show that regular training is critical for improved visual function, as sporadic training reduced the benefits of training, even when the total numbers of training sessions were equated. Conclusions: These findings are consistent with the hypothesis that complex training stimuli can improve outcomes in cortical blindness, provided that patients adhere to a regular training regimen. Nevertheless, such interventions remain limited in their ability to restore functional vision.

Background: Cortical visual impairment (CVI) is a severe loss of visual function caused by damage to the visual cortex or its afferents, often as a consequence of hypoxic insults during birth. It is one of the leading causes of vision loss in children, and it is most often permanent. Objective: Several studies have demonstrated limited vision restoration in adults who trained on well-controlled psychophysical tasks, after acquiring CVI late in life. Other studies have shown improvements in children who underwent vision training. However, little is known about the prospects for the large number of patients who acquired CVI at birth but received no formal therapy as children. Methods: We, therefore, conducted a proof-of-principle study in one CVI patient long after the onset of cortical damage (age 18), to test the training speed, efficacy and generalizability of vision rehabilitation using protocols that had previously proven successful in adults. The patient trained at home and in the laboratory, on a psychophysical task that required discrimination of complex motion stimuli presented in the blind field. Visual functionwas assessed before and after training, using perimetric measures, as well as a battery of psychophysical tests. Results: The patient showed remarkably rapid improvements on the training task, with performance going from chance to 80% correct over the span of 11 sessions. With further training, improved vision was found for untrained stimuli and for perimetric measures of visual sensitivity. Some, but not all, of these performance gains were retained upon retesting after one year. Conclusions: These results suggest that existing vision rehabilitation programs can be highly effective in adult patients who acquired CVI at a young age. Validation with a large sample size is critical, and future work should also focus on improving the usability and accessibility of these programs for younger patients.

Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively. In particular, tACS is often used as a targeted intervention that enhances a neural oscillation at a specific frequency to affect a particular behavior. However, these interventions often yield highly variable results. Here, we provide a potential explanation for this variability: tACS competes with the brain's ongoing oscillations. Using neural recordings from alert nonhuman primates, we find that when neural firing is independent of ongoing brain oscillations, tACS readily entrains spiking activity, but when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead. Consequently, tACS can yield categorically different results on neural activity, even when the stimulation protocol is fixed. Mathematical analysis suggests that this competition is likely to occur under many experimental conditions. Attempting to impose an external rhythm on the brain may therefore often yield precisely the opposite effect.

Visual plasticity declines sharply after the critical period, yet we easily learn to recognize new faces and places, even as adults. Such learning is often characterized by a "moment of insight,'' an abrupt and dramatic improvement in recognition. The mechanisms that support abrupt learning are unknown, but one hypothesis is that they involve changes in synchronization between brain regions. To test this hypothesis, we used a behavioral task in which non-human primates rapidly learned to recognize novel images and to associate them with specific responses. Simultaneous recordings from inferotemporal and prefrontal cortices revealed a transient synchronization of neural activity between these areas that peaked around the moment of insight. Synchronization was strongest between inferotemporal sites that encoded images and reward-sensitive prefrontal sites. Moreover, its magnitude intensified gradually over image exposures, suggesting that abrupt learning is the culmination of a search for informative signals within a circuit linking sensory information to task demands.

Background. Cortical visual impairment (CVI) is a severe loss of visual function caused by damage to the visual cortex or its afferents, usually as a consequence of stroke or hypoxic insult. It is one of the leading causes of vision loss in children. Objective. Several studies have demonstrated limited vision restoration in adult CVI patients who trained on well-controlled psychophysical tasks involving complex motion stimuli. Given the greater potential for plasticity in the young brain, we hypothesized that similar vision training would be more effective in young patients. Methods. To test this hypothesis, we conducted a proof-of-principle study in one young CVI patient (age 18), to test the training speed, efficacy and generalizability of vision rehabilitation using complex motion stimuli. The patient trained at home and in the laboratory, on a psychophysical task that required discrimination of motion stimuli presented in the blind field. Visual function was assessed before and after training, using perimetric measures, as well as a battery of psychophysical tests. Results. The patient showed rapid improvements on the training task, with performance going from chance to 80% correct over the span of 11 sessions. With further training, improved vision was found for untrained stimuli and for perimetric measures of visual sensitivity. Some, but not all, of these performance gains were retained upon retesting after one year. Conclusion. These results suggest that existing vision rehabilitation programs can be highly effective in pediatric patients. Validation with a large sample size is critical, and future work should also focus on improving the usability and accessibility of these programs for young patients.

Visual perceptual learning (VPL) is an improvement in visual function following training. Although the practical utility of VPL was once thought to be limited by its specificity to the precise stimuli used during training, more recent work has shown that such specificity can be overcome with appropriate training protocols. In contrast, relatively little is known about the extent to which VPL exhibits motor specificity. Previous studies have yielded mixed results. In this work, we have examined the effector specificity of VPL by training observers on a motion discrimination task that maintains the same visual stimulus (drifting grating) and task structure, but that requires different effectors to indicate the response (saccade vs. button press). We find that, in these conditions, VPL transfers fully between a manual and an oculomotor response. These results are consistent with the idea that VPL entails the learning of a decision rule that can generalize across effectors.