Firing rate homeostasis in visual cortex of freely behaving rodents

Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency

Objective.Brain computer interfaces (BCIs) require substantial cognitive flexibility to optimize control performance. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales. Here, we propose a meta plasticity model of BCI learning and skill consolidation at the single cell and population levels comprised of three elements: (a) behavioral time scale synaptic plasticity (BTSP), (b) intrinsic plasticity (IP) and (c) synaptic scaling (SS) operating at time scales from seconds to minutes to hours and days. Notably, the model is able to explainrepresentational drift-a frequent and widespread phenomenon that adversely affects BCI control and continued use.Approach.We developed an all-optical approach to characterize IP, BTSP and SS with single cell resolution in awake mice using fluorescent two photon (2P) GCaMP7s imaging and optogenetic stimulation of the soma targeted ChRmineKv2.1. We further trained mice on a one-dimensional BCI control task and systematically characterized within session (seconds to minutes) learning as well as across sessions (days and weeks) with different neural ensembles.Main results.On the time scale of seconds, substantial BTSP could be induced and was followed by significant IP over minutes. Over the time scale of days and weeks, these changes could predict BCI control proficiency, suggesting that BTSP and IP might be complemented by SS to stabilize and consolidate BCI control.Significance.Our results provide early experimental support for a meta plasticity model of continual BCI learning and skill consolidation. The model predictions may be used to design and calibrate neural decoders with complete autonomy while considering the temporal and spatial scales of plasticity mechanisms. With the power of modern-day machine learning and artificial Intelligence, fully autonomous neural decoding and adaptation in BCIs might be achieved with minimal to no human intervention.

Using Electrophysiology to Study Homeostatic Plasticity at the Drosophila Neuromuscular Junction

The Drosophila melanogaster neuromuscular junction (NMJ) is a superb system for studying synapse function. Beyond that, the NMJ is also great for studying forms of synaptic plasticity. Over the last 25 years, Drosophila NMJ neuroscientists have pioneered understanding of a form of plasticity called homeostatic synaptic plasticity, which imparts functional stability on synaptic connections. The reason is straightforward: The NMJ has a robust capacity for stability. Moreover, many strategies that the NMJ uses to maintain appropriate levels of function are mirrored at other metazoan synapses. Here, we introduce core approaches that neurophysiologists use to study homeostatic synaptic plasticity at the peripheral Drosophila NMJ. We focus on methods to study a specific form of homeostatic plasticity termed presynaptic homeostatic potentiation (PHP), which is the most well-characterized one. Other forms such as presynaptic homeostatic depression and developmental forms of homeostasis are briefly discussed. Finally, we share lists of several dozen factors and conditions known to influence the execution of PHP.

Impaired folate metabolism reshapes auditory response profiles and impairs loudness perception in MTHFR-deficient mice

Folate metabolism, regulated by methylenetetrahydrofolate reductase (MTHFR), is crucial for proper neurodevelopment, and disruptions-whether due to genetic polymorphisms or maternal nutritional deficits-have been linked to cognitive and behavioral impairments. Notably, MTHFR-deficient mouse models display altered social interaction and auditory communication, hinting at disruptions in auditory-related circuits and prompting the question of whether impaired folate metabolism might also affect sound processing and perception. Here, using two-photon calcium imaging, we show that MTHFR deficiency increases both spontaneous and sound-evoked activity in the auditory cortex and significantly shifts neuronal response profiles, which in turn elevates perceived loudness while reducing sound-level discrimination. These findings underscore the potential role of compromised folate metabolism in driving the atypical auditory responses and may have broader relevance for understanding sensory dysfunction in various neurodevelopmental conditions.

Rapid prey capture learning drives a slow resetting of network activity in rodent binocular visual cortex

Neocortical neurons possess stable firing rate set points to which they faithfully return when perturbed. These set points are established early and are stable through adulthood, suggesting they are immutable. Here we challenge this idea using an ethological vision-dependent prey capture learning paradigm in juvenile rats. This learning required visual cortex (V1), and enhanced tuning of V1 neurons to specific behavioral epochs. Chronic recordings revealed a slow, state-dependent increase in V1 firing that began after learning was complete and persisted for days. This upward firing rate plasticity was gradual, gated by wake states, and in L2/3 was driven by a TNFα-dependent increase in excitatory synapses onto pyramidal neurons - all features of homeostatic plasticity within V1. Finally, TNFα inhibition after learning reduced retention of hunting skills. Thus, naturalistic learning in juvenile animals co-opts homeostatic forms of plasticity to reset firing rate setpoints within V1, in a process that facilitates skill consolidation.

Premature vision drives aberrant development of response properties in primary visual cortex

Development of the mammalian visual system is thought to proceed in two stages. In the first stage, before birth in primates and before eye opening in altricial mammals, spontaneous activity generated by the retina and cortex shapes visual brain circuits in an activity-dependent but experience-independent manner. In the second stage, visual activity generated by sensory experience refines receptive fields. Here we investigated the consequences of altering this sequence of events by prematurely opening one or both eyes of ferrets and examining visual receptive fields in monocular cortex after the closure of the critical period for ocular dominance plasticity. We observed that many cells in animals with prematurely-opened eyes exhibited low-pass temporal frequency tuning and increased temporal frequency bandwidths, and these cells showed slightly increased orientation and direction selectivity index values. Spontaneous activity was greatly elevated in both hemispheres following the premature opening of one or both eyes, suggesting a global change in circuit excitability that was not restricted to cells that viewed the world through the prematurely opened eye. No major changes were noted in spatial frequency tuning. These results suggest that premature visual experience alters circuit excitability and visual receptive fields, in particular with respect to temporal processing. We speculate that closed lids in altricial mammals serve to prevent visual experience until circuits are initially established and are ready to be refined by visual experience.

Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness

Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse plasticity rules, synaptic scaling presents indispensable effects on homeostasis maintenance and synaptic strength regulation. In the current modeling of brain-inspired spiking neural networks (SNN), backpropagation through time is widely adopted because it can achieve high performance using a small number of time steps. Nevertheless, the synaptic scaling mechanism has not yet been well touched. In this work, we propose an experience-dependent adaptive synaptic scaling mechanism (AS-SNN) for spiking neural networks. The learning process has two stages: First, in the forward path, adaptive short-term potentiation or depression is triggered for each synapse according to afferent stimuli intensity accumulated by presynaptic historical neural activities. Second, in the backward path, long-term consolidation is executed through gradient signals regulated by the corresponding scaling factor. This mechanism shapes the pattern selectivity of synapses and the information transfer they mediate. We theoretically prove that the proposed adaptive synaptic scaling function follows a contraction map and finally converges to an expected fixed point, in accordance with state-of-the-art results in three tasks on perturbation resistance, continual learning, and graph learning. Specifically, for the perturbation resistance and continual learning tasks, our approach improves the accuracy on the N-MNIST benchmark over the baseline by 44% and 25%, respectively. An expected firing rate callback and sparse coding can be observed in graph learning. Extensive experiments on ablation study and cost evaluation evidence the effectiveness and efficiency of our nonparametric adaptive scaling method, which demonstrates the great potential of SNN in continual learning and robust learning.

Modular Arrangement of Synaptic and Intrinsic Homeostatic Plasticity within Visual Cortical Circuits

Neocortical circuits use synaptic and intrinsic forms of homeostatic plasticity to stabilize key features of network activity, but whether these different homeostatic mechanisms act redundantly, or can be independently recruited to stabilize different network features, is unknown. Here we used pharmacological and genetic perturbations both in vitro and in vivo to determine whether synaptic scaling and intrinsic homeostatic plasticity (IHP) are arranged and recruited in a hierarchical or modular manner within L2/3 pyramidal neurons in rodent V1. Surprisingly, although the expression of synaptic scaling and IHP was dependent on overlapping signaling pathways, they could be independently recruited by manipulating spiking activity or NMDAR signaling, respectively. Further, we found that changes in visual experience that affect NMDAR activation but not mean firing selectively trigger IHP, without recruiting synaptic scaling. These findings support a modular model in which synaptic and intrinsic homeostatic plasticity respond to and stabilize distinct aspects of network activity.

Prey capture learning drives critical period-specific plasticity in mouse binocular visual cortex

Critical periods are developmental windows of high experience-dependent plasticity essential for the correct refinement of neuronal circuitry and function. While the consequences for the visual system of sensory deprivation during the critical period have been well-characterized, far less is known about the effects of enhanced sensory experience. Here, we use prey capture learning to assess structural and functional plasticity mediating visual learning in the primary visual cortex of critical period mice. We show that prey capture learning improves temporal frequency discrimination and drives a profound remodeling of visual circuitry through an increase in excitatory connectivity and spine turnover. This global and persistent rewiring is not observed in adult hunters and is mediated by TNFα-dependent mechanisms. Our findings demonstrate that enhanced visual experience in a naturalistic paradigm during the critical period can drive structural plasticity to improve visual function, and promotes a long-lasting increase in spine dynamics that could enhance subsequent plasticity.

NMDA receptors regulate the firing rate set point of hippocampal circuits without altering single-cell dynamics

Understanding how neuronal circuits stabilize their activity is a fundamental yet poorly understood aspect of neuroscience. Here, we show that hippocampal network properties, such as firing rate distribution and dimensionality, are actively regulated, despite perturbations and single-cell drift. Continuous inhibition of N-methyl-D-aspartate receptors (NMDARs) ex vivo lowers the excitation/inhibition ratio and network firing rates while preserving resilience to perturbations. This establishes a new network firing rate set point via NMDAR-eEF2K signaling pathway. NMDARs' capacity to modulate and stabilize network firing is mediated by excitatory synapses and the intrinsic excitability of parvalbumin-positive neurons, respectively. In behaving mice, continuous NMDAR blockade in CA1 reduces network firing without altering single-neuron drift or triggering a compensatory response. These findings expand NMDAR function beyond their canonical role in synaptic plasticity and raise the possibility that some NMDAR-dependent behavioral effects are mediated by their unique regulation of population activity set points.

Excitatory-inhibitory homeostasis and bifurcation control in the Wilson-Cowan model of cortical dynamics

Although the primary function of excitatory-inhibitory (E-I) homeostasis is the maintenance of mean firing rates, the conjugation of multiple homeostatic mechanisms is thought to be pivotal to ensuring edge-of-bifurcation dynamics in cortical circuits. However, computational studies on E-I homeostasis have focused solely on the plasticity of inhibition, neglecting the impact of different modes of E-I homeostasis on cortical dynamics. Therefore, we investigate how the diverse mechanisms of E-I homeostasis employed by cortical networks shape oscillations and edge-of-bifurcation dynamics. Using the Wilson-Cowan model, we explore how distinct modes of E-I homeostasis maintain stable firing rates in models with varying levels of input and how it affects circuit dynamics. Our results confirm that E-I homeostasis can be leveraged to control edge-of-bifurcation dynamics and that some modes of homeostasis maintain mean firing rates under higher levels of input by modulating the distance to the bifurcation. Additionally, relying on multiple modes of homeostasis ensures stable activity while keeping oscillation frequencies within a physiological range. Our findings tie relevant features of cortical networks, such as E-I balance, the generation of gamma oscillations, and edge-of-bifurcation dynamics, under the framework of firing-rate homeostasis, providing a mechanistic explanation for the heterogeneity in the distance to the bifurcation found across cortical areas. In addition, we reveal the functional benefits of relying upon different homeostatic mechanisms, providing a robust method to regulate network dynamics with minimal perturbation to the generation of gamma rhythms and explaining the correlation between inhibition and gamma frequencies found in cortical networks.

Daily rhythms drive dynamism in sleep, oscillations and interneuron firing, while excitatory firing remains stable across 24 h

The adaptation to the daily 24-h light-dark cycle is ubiquitous across animal species and is crucial for maintaining fitness. This free-running cycle occurs innately within multiple bodily systems, such as endogenous circadian rhythms in clock-gene expression and synaptic plasticity. These phenomena are well studied; however, it is unknown if and how the 24-h clock affects electrophysiologic network function in vivo. The hippocampus is a region of interest for long timescale (>8 h) studies because it is critical for cognitive function and exhibits time-of-day effects in learning. We recorded single cell spiking activity and local field potentials (LFPs) in mouse hippocampus across the 24-h (12:12-h light/dark) cycle to quantify how electrophysiological network function is modulated across the 24-h day. We found that while inhibitory population firing rates and LFP oscillations exhibit modulation across the day, average excitatory population firing is static. This excitatory stability, despite inhibitory dynamism, may enable consistent around-the-clock function of neural circuits.

Homeostatic synaptic normalization optimizes learning in network models of neural population codes

Studying and understanding the code of large neural populations hinge on accurate statistical models of population activity. A novel class of models, based on learning to weigh sparse nonlinear Random Projections (RP) of the population, has demonstrated high accuracy, efficiency, and scalability. Importantly, these RP models have a clear and biologically plausible implementation as shallow neural networks. We present a new class of RP models that are learned by optimizing the randomly selected sparse projections themselves. This 'reshaping' of projections is akin to changing synaptic connections in just one layer of the corresponding neural circuit model. We show that Reshaped RP models are more accurate and efficient than the standard RP models in recapitulating the code of tens of cortical neurons from behaving monkeys. Incorporating more biological features and utilizing synaptic normalization in the learning process, results in accurate models that are more efficient. Remarkably, these models exhibit homeostasis in firing rates and total synaptic weights of projection neurons. We further show that these sparse homeostatic reshaped RP models outperform fully connected neural network models. Thus, our new scalable, efficient, and highly accurate population code models are not only biologically plausible but are actually optimized due to their biological features. These findings suggest a dual functional role of synaptic normalization in neural circuits: maintaining spiking and synaptic homeostasis while concurrently optimizing network performance and efficiency in encoding information and learning.

Dendritic Spines of Layer 5 Pyramidal Neurons of the Aging Somatosensory Cortex Exhibit Reduced Volumetric Remodeling

Impairments in synaptic dynamics and stability are observed both in neurodegenerative disorders and in the healthy aging cortex, which exhibits elevated dendritic spine turnover and decreased long-term stability of excitatory connections at baseline, as well as an altered response to plasticity induction. In addition to the discrete gain and loss of synapses, spines also change in size and strength both during learning and in the absence of neural activity, and synaptic volume has been associated with stability and incorporation into memory traces. Furthermore, intrinsic dynamics, an apparently stochastic component of spine volume changes, may serve as a homeostatic mechanism to prevent stabilization of superfluous connections. However, the effects of age on modulation of synaptic weights remain unknown. Using two-photon excitation (2PE) microscopy of spines during chemical plasticity induction in vitro and analyzing longitudinal in vivo 2PE images after a plasticity-inducing manipulation, we characterize the effects of age on volumetric changes of spines of the apical tuft of layer 5 pyramidal neurons of mouse primary somatosensory cortex. Aged mice exhibit decreased volumetric volatility and delayed rearrangement of synaptic weights of persistent connections, as well as greater susceptibility to spine shrinkage in response to chemical long-term depression. These results suggest a deficit in the aging brain's ability to fine-tune synaptic weights to properly incorporate and retain novel memories. This research provides the first evidence of alterations in spine volumetric dynamics in healthy aging and may support a model of impaired processing and learning in the aged somatosensory system.

Homeostatic regulation of brain activity: from endogenous mechanisms to homeostatic nanomachines

After the initial concepts of the constancy of the internal milieu or homeostasis, put forward by Claude Bernard and Walter Cannon, homeostasis emerged as a mechanism to control oscillations of biologically meaningful variables within narrow physiological ranges. This is a primary need in the central nervous system that is continuously subjected to a multitude of stimuli from the internal and external environments that affect its function and structure, allowing to adapt the individual to the ever-changing daily conditions. Preserving physiological levels of activity despite disturbances that could either depress neural computation or excessively stimulate neural activity is fundamental, and failure of these homeostatic mechanisms can lead to brain diseases. In this review, we cover the role and main mechanisms of homeostatic plasticity involving the regulation of excitability and synaptic strength from the single neuron to the network level. We analyze the relationships between homeostatic and Hebbian plasticity and the conditions under which the preservation of the excitatory/inhibitory balance fails, triggering epileptogenesis and eventually epilepsy. Several therapeutic strategies to cure epilepsy have been designed to strengthen homeostasis when endogenous homeostatic plasticity mechanisms have become insufficient or ineffective to contrast hyperactivity. We describe "on demand" gene therapy strategies, including optogenetics, chemogenetics, and chemo-optogenetics, and particularly focus on new closed loop sensor-actuator strategies mimicking homeostatic plasticity that can be endogenously expressed to strengthen the homeostatic defenses against brain diseases.

Aberrant encoding of event saliency in the orbitofrontal cortex following loss of the psychiatric-associated circular RNA, circHomer1

CircHomer1 is an activity-dependent circular RNA (circRNA) isoform produced from back-splicing of the Homer1 transcript. Homer1 isoforms are well-known regulators of homeostatic synaptic plasticity through post-synaptic density scaffold regulation. Homer1 polymorphisms have been associated with psychiatric diseases including schizophrenia (SCZ) and bipolar disorder (BD). Postmortem tissue from patients with SCZ and BD displayed reduced circHomer1 levels within the orbitofrontal cortex (OFC), a region that tracks event saliency important for modulating behavioral flexibility. While dysregulation of circHomer1 expression has recently been identified across multiple psychiatric and neurodegenerative disorders and is associated with impaired behavioral flexibility in mice, it is unknown whether circHomer1 can induce electrophysiological signatures relevant to cognitive dysfunction in these disorders. To examine the role of circHomer1 in neuronal signaling, we bilaterally knocked down circHomer1 in the OFC of C57BL/6 J male mice and recorded neural activity from the OFC during a touchscreen reversal learning task then measured molecular changes of synaptic regulators following knockdown. Knockdown of circHomer1 within the OFC induced choice-dependent changes in multiunit firing rate and local field potential coordination and power to salient stimuli during reversal learning. Further, these electrophysiological changes were associated with transcriptional downregulation of glutamatergic signaling effectors and behavioral alterations leading to impaired cognitive flexibility. CircHomer1 is a stable biomolecule, whose knockdown in rodent OFC produces lasting electrophysiological and transcriptional changes important for efficient reversal learning. This is, to our knowledge, the first demonstration of a psychiatric-associated circRNA contributing to electrophysiological, transcriptional, and behavioral alterations relevant to psychiatric phenotypes.

Rectified activity-dependent population plasticity implicates cortical adaptation for memory and cognitive functions

Cortical network undergoes rewiring everyday due to learning and memory events. To investigate the trends of population adaptation in neocortex overtime, we record cellular activity of large-scale cortical populations in response to neutral environments and conditioned contexts and identify a general intrinsic cortical adaptation mechanism, naming rectified activity-dependent population plasticity (RAPP). Comparing each adjacent day, the previously activated neurons reduce activity, but remain with residual potentiation, and increase population variability in proportion to their activity during previous recall trials. RAPP predicts both the decay of context-induced activity patterns and the emergence of sparse memory traces. Simulation analysis reveal that the local inhibitory connections might account for the residual potentiation in RAPP. Intriguingly, introducing the RAPP phenomenon in the artificial neural network show promising improvement in small sample size pattern recognition tasks. Thus, RAPP represents a phenomenon of cortical adaptation, contributing to the emergence of long-lasting memory and high cognitive functions.

Failure in a population: Tauopathy disrupts homeostatic set-points in emergent dynamics despite stability in the constituent neurons

Homeostatic regulation of neuronal activity is essential for robust computation; set-points, such as firing rate, are actively stabilized to compensate for perturbations. The disruption of brain function central to neurodegenerative disease likely arises from impairments of computationally essential set-points. Here, we systematically investigated the effects of tau-mediated neurodegeneration on all known set-points in neuronal activity. We continuously tracked hippocampal neuronal activity across the lifetime of a mouse model of tauopathy. We were unable to detect effects of disease in measures of single-neuron firing activity. By contrast, as tauopathy progressed, there was disruption of network-level neuronal activity, quantified by measuring neuronal pairwise interactions and criticality, a homeostatically controlled, ideal computational regime. Deviations in criticality correlated with symptoms, predicted underlying anatomical pathology, occurred in a sleep-wake-dependent manner, and could be used to reliably classify an animal's genotype. This work illustrates how neurodegeneration may disrupt the computational capacity of neurobiological systems.

Hibernation reduces GABA signaling in the brainstem to enhance motor activity of breathing at cool temperatures

BACKGROUND

Neural circuits produce reliable activity patterns despite disturbances in the environment. For this to occur, neurons elicit synaptic plasticity during perturbations. However, recent work suggests that plasticity not only regulates circuit activity during disturbances, but these modifications may also linger to stabilize circuits during future perturbations. The implementation of such a regulation scheme for real-life environmental challenges of animals remains unclear. Amphibians provide insight into this problem in a rather extreme way, as circuits that generate breathing are inactive for several months during underwater hibernation and use compensatory plasticity to promote ventilation upon emergence.

RESULTS

Using ex vivo brainstem preparations and electrophysiology, we find that hibernation in American bullfrogs reduces GABAA receptor (GABAAR) inhibition in respiratory rhythm generating circuits and motor neurons, consistent with a compensatory response to chronic inactivity. Although GABAARs are normally critical for breathing, baseline network output at warm temperatures was not affected. However, when assessed across a range of temperatures, hibernators with reduced GABAAR signaling had greater activity at cooler temperatures, enhancing respiratory motor output under conditions that otherwise strongly depress breathing.

CONCLUSIONS

Hibernation reduces GABAAR signaling to promote robust respiratory output only at cooler temperatures. Although frogs do not ventilate lungs during underwater hibernation, we suggest this would be beneficial for stabilizing breathing when the animal passes through a large temperature range during emergence in the spring. More broadly, these results demonstrate that compensatory synaptic plasticity can increase the operating range of circuits in harsh environments, thereby promoting adaptive behavior in conditions that suppress activity.

Daily light-induced transcription in visual cortex neurons drives downward firing rate homeostasis and stabilizes sensory processing

Balancing plasticity and stability in neural circuits is essential for an animal's ability to learn from its environment while preserving proper processing and perception of sensory information. However, unlike the mechanisms that drive plasticity in neural circuits, the activity-induced molecular mechanisms that convey functional stability remain poorly understood. Focusing on the visual cortex of adult mice and combining transcriptomics, electrophysiology, and in vivo calcium imaging, we find that the daily appearance of light induces, in excitatory neurons, a large gene program along with rapid and transient increases in the ratio of excitation and inhibition (E/I ratio) and neural activity. Furthermore, we find that the light-induced transcription factor NPAS4 drives these daily normalizations of the E/I ratio and neural activity rates and that it stabilizes the neurons' response properties. These findings indicate that daily sensory-induced transcription normalizes the E/I ratio and drives downward firing rate homeostasis to maintain proper sensory processing and perception.

Experience Dependence of Alpha Rhythms and Neural Dynamics in the Mouse Visual Cortex

The role of experience in the development and maintenance of emergent network properties such as cortical oscillations and states is poorly understood. To define how early-life experience affects cortical dynamics in the visual cortex of adult, head-fixed mice, we examined the effects of two forms of blindness initiated before eye opening and continuing through recording: (1) bilateral loss of retinal input (enucleation) and (2) degradation of visual input (eyelid suture). Neither form of deprivation fundamentally altered the state-dependent regulation of firing rates or local field potentials. However, each deprivation caused unique changes in network behavior. Laminar analysis revealed two different generative mechanisms for low-frequency synchronization: one prevalent during movement and the other during quiet wakefulness. The former was absent in enucleated mice, suggesting a mouse homolog of human alpha oscillations. In addition, neurons in enucleated animals were less correlated and fired more regularly, but no change in mean firing rate. Eyelid suture decreased firing rates during quiet wakefulness, but not during movement, with no effect on neural correlations or regularity. Sutured animals showed a broadband increase in depth EEG power and an increased occurrence, but reduced central frequency, of narrowband gamma oscillations. The complementary-rather than additive-effects of lid suture and enucleation suggest that the development of emergent network properties does not require vision but is plastic to modified input. Our results suggest a complex interaction of internal set points and experience determines mature cortical activity, with low-frequency synchronization being particularly susceptible to early deprivation.

Blockade of GluN2B-Containing NMDA Receptors Prevents Potentiation and Depression of Responses during Ocular Dominance Plasticity

Monocular deprivation (MD) causes an initial decrease in synaptic responses to the deprived eye in juvenile mouse primary visual cortex (V1) through Hebbian long-term depression (LTD). This is followed by a homeostatic increase, which has been attributed either to synaptic scaling or to a slide threshold for Hebbian long-term potentiation (LTP) rather than scaling. We therefore asked in mice of all sexes whether the homeostatic increase during MD requires GluN2B-containing NMDA receptor activity, which is required to slide the plasticity threshold but not for synaptic scaling. Selective GluN2B blockade from 2-6 d after monocular lid suture prevented the homeostatic increase in miniature excitatory postsynaptic current (mEPSC) amplitude in monocular V1 of acute slices and prevented the increase in visually evoked responses in binocular V1 in vivo. The decrease in mEPSC amplitude and visually evoked responses during the first 2 d of MD also required GluN2B activity. Together, these results support the idea that GluN2B-containing NMDA receptors first play a role in LTD immediately following eye closure and then promote homeostasis during prolonged MD by sliding the plasticity threshold in favor of LTP.

Homeostatic Regulation of Spike Rate within Bursts in Two Distinct Preparations

Homeostatic plasticity represents a set of mechanisms thought to stabilize some function of neural activity. Here, we identified the specific features of cellular or network activity that were maintained after the perturbation of GABAergic blockade in two different systems: mouse cortical neuronal cultures where GABA is inhibitory and motoneurons in the isolated embryonic chick spinal cord where GABA is excitatory (males and females combined in both systems). We conducted a comprehensive analysis of various spiking activity characteristics following GABAergic blockade. We observed significant variability in many features after blocking GABAA receptors (e.g., burst frequency, burst duration, overall spike frequency in culture). These results are consistent with the idea that neuronal networks achieve activity goals using different strategies (degeneracy). On the other hand, some features were consistently altered after receptor blockade in the spinal cord preparation (e.g., overall spike frequency). Regardless, these features did not express strong homeostatic recoveries when tracking individual preparations over time. One feature showed a consistent change and homeostatic recovery following GABAA receptor block. We found that spike rate within a burst (SRWB) increased after receptor block in both the spinal cord preparation and cortical cultures and then returned to baseline within hours. These changes in SRWB occurred at both single cell and population levels. Our findings indicate that the network prioritizes the burst spike rate, which appears to be a variable under tight homeostatic regulation. The result is consistent with the idea that networks can maintain an appropriate behavioral response in the face of challenges.

Keeping Your Brain in Balance: Homeostatic Regulation of Network Function

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

GABAergic synaptic scaling is triggered by changes in spiking activity rather than AMPA receptor activation

Homeostatic plasticity represents a set of mechanisms that are thought to recover some aspect of neural function. One such mechanism called AMPAergic scaling was thought to be a likely candidate to homeostatically control spiking activity. However, recent findings have forced us to reconsider this idea as several studies suggest AMPAergic scaling is not directly triggered by changes in spiking. Moreover, studies examining homeostatic perturbations in vivo have suggested that GABAergic synapses may be more critical in terms of spiking homeostasis. Here, we show results that GABAergic scaling can act to homeostatically control spiking levels. We found that perturbations which increased or decreased spiking in cortical cultures triggered multiplicative GABAergic upscaling and downscaling, respectively. In contrast, we found that changes in AMPA receptor (AMPAR) or GABAR transmission only influence GABAergic scaling through their indirect effect on spiking. We propose that GABAergic scaling represents a stronger candidate for spike rate homeostat than AMPAergic scaling.

At the onset of active whisking, the input layer of barrel cortex exhibits a 24 h window of increased excitability that depends on prior experience

The development of motor control over sensory organs is a critical milestone in sensory processing, enabling active exploration and shaping of the sensory environment. However, whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we discovered a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, precisely coinciding with the onset of active whisking at postnatal day 14 (P14). This increase in neuronal gain was specific to layer IV, independent of changes in synaptic strength, and required prior sensory experience. Strikingly, the effect was not observed in layer II/III of the barrel cortex or in the visual cortex upon eye opening, suggesting a unique interaction between the development of active sensing and the thalamocortical input layer in the somatosensory system. Predictive modeling indicated that changes in active membrane conductances alone could reliably distinguish P14 neurons in control but not whisker-deprived hemispheres. Our findings demonstrate an experience-dependent, lamina-specific refinement of neuronal excitability tightly linked to the emergence of active whisking. This transient increase in the gain of the thalamic input layer coincides with a critical period for synaptic plasticity in downstream layers, suggesting a role in facilitating cortical maturation and sensory processing. Together, our results provide evidence for a direct interaction between the development of motor control and sensory cortex, offering new insights into the experience-dependent development and refinement of sensory systems. These findings have broad implications for understanding the interplay between motor and sensory development, and how the mechanisms of perception cooperate with behavior.

Visual Deprivation during Mouse Critical Period Reorganizes Network-Level Functional Connectivity

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we use wide-field fluorescence optical imaging (WFOI) to characterize calcium-based resting-state functional connectivity during acute (3 d) MD in female and male mice with genetically encoded calcium indicators (Thy1-GCaMP6f). We first establish the fundamental performance of WFOI by computing signal to noise properties throughout our data processing pipeline. Following MD, we found that Δ band (0.4-4 Hz) GCaMP6 activity in the deprived visual cortex decreased, suggesting that excitatory activity in this region was reduced by MD. In addition, interhemispheric visual homotopic functional connectivity decreased following MD, which was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between the visual and parietal cortex that peaked 2 d after MD. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including the association cortices.

Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks

The brain's functionality is developed and maintained through synaptic plasticity. As synapses undergo plasticity, they also affect each other. The nature of such 'co-dependency' is difficult to disentangle experimentally, because multiple synapses must be monitored simultaneously. To help understand the experimentally observed phenomena, we introduce a framework that formalizes synaptic co-dependency between different connection types. The resulting model explains how inhibition can gate excitatory plasticity while neighboring excitatory-excitatory interactions determine the strength of long-term potentiation. Furthermore, we show how the interplay between excitatory and inhibitory synapses can account for the quick rise and long-term stability of a variety of synaptic weight profiles, such as orientation tuning and dendritic clustering of co-active synapses. In recurrent neuronal networks, co-dependent plasticity produces rich and stable motor cortex-like dynamics with high input sensitivity. Our results suggest an essential role for the neighborly synaptic interaction during learning, connecting micro-level physiology with network-wide phenomena.

Upconversion-Mediated Optogenetics for the Treatment of Surgery-Induced Postoperative Neurocognitive Dysfunction

Perioperative neurocognitive disorder (PND) is a common complication in surgical patients. While many interventions to prevent PND have been studied, the availability of treatment methods is limited. Thus, it is crucial to delve into the mechanisms of PND, pinpoint therapeutic targets, and develop effective treatment approaches. In this study, reduced dorsal tenia tecta (DTT) neuronal activity was found to be associated with tibial fracture surgery-induced PND, indicating that a neuronal excitation-inhibition (E-I) imbalance could contribute to PND. Optogenetics in the DTT brain region was conducted using upconversion nanoparticles (UCNPs) with the ability to convert 808 nm near-infrared light to visible wavelengths, which triggered the activation of excitatory neurons with minimal damage in the DTT brain region, thus improving cognitive impairment symptoms in the PND model. Moreover, this noninvasive intervention to modulate E-I imbalance showed a positive influence on mouse behavior in the Morris water maze test, which demonstrates that UCNP-mediated optogenetics is a promising tool for the treatment of neurological imbalance disorders.

Linking activity dyshomeostasis and sleep disturbances in Alzheimer disease

The presymptomatic phase of Alzheimer disease (AD) starts with the deposition of amyloid-β in the cortex and begins a decade or more before the emergence of cognitive decline. The trajectory towards dementia and neurodegeneration is shaped by the pathological load and the resilience of neural circuits to the effects of this pathology. In this Perspective, I focus on recent advances that have uncovered the vulnerability of neural circuits at early stages of AD to hyperexcitability, particularly when the brain is in a low-arousal states (such as sleep and anaesthesia). Notably, this hyperexcitability manifests before overt symptoms such as sleep and memory deficits. Using the principles of control theory, I analyse the bidirectional relationship between homeostasis of neuronal activity and sleep and propose that impaired activity homeostasis during sleep leads to hyperexcitability and subsequent sleep disturbances, whereas sleep disturbances mitigate hyperexcitability via negative feedback. Understanding the interplay among activity homeostasis, neuronal excitability and sleep is crucial for elucidating the mechanisms of vulnerability to and resilience against AD pathology and for identifying new therapeutic avenues.

Ocular surface information seen from the somatosensory thalamus and cortex

Ocular Surface (OS) somatosensory innervation detects external stimuli producing perceptions, such as pain or dryness, the most relevant symptoms in many OS pathologies. Nevertheless, little is known about the central nervous system circuits involved in these perceptions, and how they integrate multimodal inputs in general. Here, we aim to describe the thalamic and cortical activity in response to OS stimulation of different modalities. Electrophysiological extracellular recordings in anaesthetized rats were used to record neural activity, while saline drops at different temperatures were applied to stimulate the OS. Neurons were recorded in the ophthalmic branch of the trigeminal ganglion (TG, 49 units), the thalamic VPM-POm nuclei representing the face (Th, 69 units) and the primary somatosensory cortex (S1, 101 units). The precise locations for Th and S1 neurons receiving OS information are reported here for the first time. Interestingly, all recorded nuclei encode modality both at the single neuron and population levels, with noxious stimulation producing a qualitatively different activity profile from other modalities. Moreover, neurons responding to new combinations of stimulus modalities not present in the peripheral TG subsequently appear in Th and S1, being organized in space through the formation of clusters. Besides, neurons that present higher multimodality display higher spontaneous activity. These results constitute the first anatomical and functional characterization of the thalamocortical representation of the OS. Furthermore, they provide insight into how information from different modalities gets integrated from the peripheral nervous system into the complex cortical networks of the brain. KEY POINTS: Anatomical location of thalamic and cortical ocular surface representation. Thalamic and cortical neuronal responses to multimodal stimulation of the ocular surface. Increasing functional complexity along trigeminal neuroaxis. Proposal of a new perspective on how peripheral activity shapes central nervous system function.

Deprivation-Induced Plasticity in the Early Central Circuits of the Rodent Visual, Auditory, and Olfactory Systems

Activity-dependent neuronal plasticity is crucial for animals to adapt to dynamic sensory environments. Traditionally, it has been investigated using deprivation approaches in animal models primarily in sensory cortices. Nevertheless, emerging evidence emphasizes its significance in sensory organs and in subcortical regions where cranial nerves relay information to the brain. Additionally, critical questions started to arise. Do different sensory modalities share common cellular mechanisms for deprivation-induced plasticity at these central entry points? Does the deprivation duration correlate with specific plasticity mechanisms? This study systematically reviews and meta-analyzes research papers that investigated visual, auditory, or olfactory deprivation in rodents of both sexes. It examines the consequences of sensory deprivation in homologous regions at the first central synapse following cranial nerve transmission (vision - lateral geniculate nucleus and superior colliculus; audition - ventral and dorsal cochlear nucleus; olfaction - olfactory bulb). The systematic search yielded 91 papers (39 vision, 22 audition, 30 olfaction), revealing substantial heterogeneity in publication trends, experimental methods, measures of plasticity, and reporting across the sensory modalities. Despite these differences, commonalities emerged when correlating plasticity mechanisms with the duration of sensory deprivation. Short-term deprivation (up to 1 d) reduced activity and increased disinhibition, medium-term deprivation (1 d to a week) involved glial changes and synaptic remodeling, and long-term deprivation (over a week) primarily led to structural alterations. These findings underscore the importance of standardizing methodologies and reporting practices. Additionally, they highlight the value of cross-modal synthesis for understanding how the nervous system, including peripheral, precortical, and cortical areas, respond to and compensate for sensory inputs loss.

Sleep restores an optimal computational regime in cortical networks

Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep. By recording cortical neuron activity continuously for 10-14 d in freely behaving rats, we show that normal waking experience progressively disrupts criticality and that sleep functions to restore critical dynamics. Criticality is perturbed in a context-dependent manner, and waking experience is causal in driving these effects. The degree of deviation from criticality predicts future sleep/wake behavior more accurately than SWA, behavioral history or other neural measures. Our results demonstrate that perturbation and recovery of criticality is a network homeostatic mechanism consistent with the core, restorative function of sleep.

Amyloid Pathology Impairs Experience-Dependent Inhibitory Synaptic Plasticity

Alzheimer's disease patients and mouse models exhibit aberrant neuronal activity and altered excitatory-to-inhibitory synaptic ratio. Using multicolor two-photon microscopy, we test how amyloid pathology alters the structural dynamics of excitatory and inhibitory synapses and their adaptation to altered visual experience in vivo in the visual cortex. We show that the baseline dynamics of mature excitatory synapses and their adaptation to visual deprivation are not altered in amyloidosis. Likewise, the baseline dynamics of inhibitory synapses are not affected. In contrast, visual deprivation fails to induce inhibitory synapse loss in amyloidosis, a phenomenon observed in nonpathological conditions. Intriguingly, inhibitory synapse loss associated with visual deprivation in nonpathological mice is accompanied by subtle broadening of spontaneous but not visually evoked calcium transients. However, such broadening does not manifest in the context of amyloidosis. We also show that excitatory and inhibitory synapse loss is locally clustered under the nonpathological state. In contrast, a fraction of synapse loss is not locally clustered in amyloidosis, indicating an impairment in inhibitory synapse adaptation to changes in excitatory synaptic activity.

Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective

We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity's description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of "fast time" dynamics are shaped by the structure of a differential equation and its connectivity parameters, which themselves evolve over "slow time" driven by state-dependent and state-independent plasticity mechanisms. Finally, the adjustment of plasticity processes (metaplasticity) takes place in an "ultraslow" time scale. Psychedelics flatten the neural landscape, leading to heightened entropy and complexity of neural dynamics, as observed in neuroimaging and modeling studies linking increases in complexity with a disruption of functional integration. We highlight the relationship between criticality, the complexity of fast neural dynamics, and synaptic plasticity. Pathological, rigid, or "canalized" neural dynamics result in an ultrastable confined repertoire, allowing slower plastic changes to consolidate them further. However, under the influence of psychedelics, the destabilizing emergence of complex dynamics leads to a more fluid and adaptable neural state in a process that is amplified by the plasticity-enhancing effects of psychedelics. This shift manifests as an acute systemic increase of disorder and a possibly longer-lasting increase in complexity affecting both short-term dynamics and long-term plastic processes. Our framework offers a holistic perspective on the acute effects of these substances and their potential long-term impacts on neural structure and function.

Synaptopodin Regulates Denervation-Induced Plasticity at Hippocampal Mossy Fiber Synapses

Neurological diseases can lead to the denervation of brain regions caused by demyelination, traumatic injury or cell death. The molecular and structural mechanisms underlying lesion-induced reorganization of denervated brain regions, however, are a matter of ongoing investigation. In order to address this issue, we performed an entorhinal cortex lesion (ECL) in mouse organotypic entorhino-hippocampal tissue cultures of both sexes and studied denervation-induced plasticity of mossy fiber synapses, which connect dentate granule cells (dGCs) with CA3 pyramidal cells (CA3-PCs) and play important roles in learning and memory formation. Partial denervation caused a strengthening of excitatory neurotransmission in dGCs, CA3-PCs and their direct synaptic connections, as revealed by paired recordings (dGC-to-CA3-PC). These functional changes were accompanied by ultrastructural reorganization of mossy fiber synapses, which regularly contain the plasticity-regulating protein synaptopodin and the spine apparatus organelle. We demonstrate that the spine apparatus organelle and synaptopodin are related to ribosomes in close proximity to synaptic sites and reveal a synaptopodin-related transcriptome. Notably, synaptopodin-deficient tissue preparations that lack the spine apparatus organelle failed to express lesion-induced synaptic adjustments. Hence, synaptopodin and the spine apparatus organelle play a crucial role in regulating lesion-induced synaptic plasticity at hippocampal mossy fiber synapses.

Basal forebrain cholinergic activity is necessary for upward firing rate homeostasis in the rodent visual cortex

Bidirectional homeostatic plasticity allows neurons and circuits to maintain stable firing in the face of developmental or learning-induced perturbations. In the primary visual cortex (V1), upward firing rate homeostasis (FRH) only occurs during active wake (AW) and downward during sleep, but how this behavioral state-dependent gating is accomplished is unknown. Here, we focus on how AW enables upward FRH in V1 of juvenile Long Evans rats. A major difference between quiet wake (QW), when upward FRH is absent, and AW, when it is present, is increased cholinergic (ACh) tone, and the main cholinergic projections to V1 arise from the horizontal diagonal band of the basal forebrain (HDB ACh). We therefore chemogenetically inhibited HDB ACh neurons while inducing upward homeostatic compensation using direct activity-suppression in V1. We found that synaptic scaling up and intrinsic homeostatic plasticity, two important cellular mediators of upward FRH, were both impaired when HDB ACh neurons were inhibited. Most strikingly, HDB ACh inhibition flipped the sign of intrinsic plasticity so that it became anti-homeostatic, and this effect was phenocopied by knockdown of the M1 ACh receptor in V1, indicating that this modulation of intrinsic plasticity is the result of direct actions of ACh within V1. Finally, we found that upward FRH induced by visual deprivation was completely prevented by HDB ACh inhibition. Together, our results show that HDB ACh modulation is a key enabler of upward homeostatic plasticity and FRH, and more broadly suggest that neuromodulatory inputs can segregate upward and downward homeostatic plasticity into distinct behavioral states.

Cortical reactivations predict future sensory responses

Many theories of offline memory consolidation posit that the pattern of neurons activated during a salient sensory experience will be faithfully reactivated, thereby stabilizing the pattern1,2. However, sensory-evoked patterns are not stable but, instead, drift across repeated experiences3-6. Here, to investigate the relationship between reactivations and the drift of sensory representations, we imaged the calcium activity of thousands of excitatory neurons in the mouse lateral visual cortex. During the minute after a visual stimulus, we observed transient, stimulus-specific reactivations, often coupled with hippocampal sharp-wave ripples. Stimulus-specific reactivations were abolished by local cortical silencing during the preceding stimulus. Reactivations early in a session systematically differed from the pattern evoked by the previous stimulus-they were more similar to future stimulus response patterns, thereby predicting both within-day and across-day representational drift. In particular, neurons that participated proportionally more or less in early stimulus reactivations than in stimulus response patterns gradually increased or decreased their future stimulus responses, respectively. Indeed, we could accurately predict future changes in stimulus responses and the separation of responses to distinct stimuli using only the rate and content of reactivations. Thus, reactivations may contribute to a gradual drift and separation in sensory cortical response patterns, thereby enhancing sensory discrimination7.

Disrupted synaptic homeostasis and partial occlusion of associative long-term potentiation in the human cortex during social isolation

Social isolation often occurs in the military mission of soldiers but has increased in the general population since the COVID-19 epidemic. Overall synaptic homeostasis along with associative plasticity for the activity-dependent refinement of transmission across single synapses represent basic neural network function and adaptive behavior mechanisms. Here, we use electrophysiological and behavioral indices to non-invasively study the net synaptic strength and long-term potentiation (LTP)-like plasticity of humans in social isolation environments. The theta activity of electroencephalography (EEG) signals and transcranial magnetic stimulation (TMS) intensity to elicit a predefined amplitude of motor-evoked potential (MEP) demonstrate the disrupted synaptic homeostasis in the human cortex during social isolation. Furthermore, the induced MEP change by paired associative stimulation (PAS) demonstrates the partial occlusion of LTP-like plasticity, further behavior performances in a word-pair task are also identified as a potential index. Our study indicates that social isolation disrupts synaptic homeostasis and occludes associative LTP-like plasticity in the human cortex, decreasing behavior performance related to declarative memory.

Visual deprivation during mouse critical period reorganizes network-level functional connectivity

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we used longitudinal wide-field optical calcium imaging to measure resting-state functional connectivity during acute (3-day) MD in mice. First, delta GCaMP6 power in the deprived visual cortex decreased, suggesting that excitatory activity was reduced in the region. In parallel, interhemispheric visual homotopic functional connectivity was rapidly reduced by the disruption of visual drive through MD and was sustained significantly below baseline state. This reduction of visual homotopic connectivity was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between visual and parietal cortex that peaked at MD2. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including association cortices.

Age-related dysregulation of homeostatic control in neuronal microcircuits

Neuronal homeostasis prevents hyperactivity and hypoactivity. Age-related hyperactivity suggests homeostasis may be dysregulated in later life. However, plasticity mechanisms preventing age-related hyperactivity and their efficacy in later life are unclear. We identify the adult cortical plasticity response to elevated activity driven by sensory overstimulation, then test how plasticity changes with age. We use in vivo two-photon imaging of calcium-mediated cellular/synaptic activity, electrophysiology and c-Fos-activity tagging to show control of neuronal activity is dysregulated in the visual cortex in late adulthood. Specifically, in young adult cortex, mGluR5-dependent population-wide excitatory synaptic weakening and inhibitory synaptogenesis reduce cortical activity following overstimulation. In later life, these mechanisms are downregulated, so that overstimulation results in synaptic strengthening and elevated activity. We also find overstimulation disrupts cognition in older but not younger animals. We propose that specific plasticity mechanisms fail in later life dysregulating neuronal microcircuit homeostasis and that the age-related response to overstimulation can impact cognitive performance.

Increased excitability and reduced GABAergic levels in somatosensory cortex under chronic spinal cord injury

The complete or partial damage of ascending somatosensory pathways produced by a spinal cord injury triggers changes in the somatosensory cortex consisting in a functional expansion of activity from intact cortical regions towards deafferented ones, a process known as cortical reorganization. However, it is still unclear whether cortical reorganization depends on the severity of the spinal cord damage or if a spinal cord injury always leads to a similar cortical reorganization process in the somatosensory cortex. To answer these open questions in the field, we obtained longitudinal somatosensory evoked responses from bilateral hindlimb and forelimb cortex from animals with chronic full-transection or contusive spinal cord injury at thoracic level (T9-T10) to induce sensory deprivation of hindlimb cortex while preserving intact the forelimb cortex. Electrophysiological recordings from the four locations were obtained before lesion and weekly for up to 4 weeks. Our results show that cortical reorganization depends on the type of spinal cord injury, which tends to be more bilateral in full transection while is more unilateral in the model of contusive spinal cord injury. Moreover, in full transection of spinal cord, the deafferented and intact cortex exhibited similar increments of somatosensory evoked responses in both models of spinal cord injury - a feature observed in about 80% of subjects. The other 20% were unaffected by the injury indicating that cortical reorganization does not undergo in all subjects. In addition, we demonstrated an increased probability of triggered up-states in animals with spinal cord injury. This data indicates increased cortical excitability that could be proposed as a new feature of cortical reorganization. Finally, decreased levels of GABA marker GAD67 across cortical layers were only found in those animals with increased somatosensory evoked responses, but not in the unaffected population. In conclusion, cortical reorganization depends on the types of spinal cord injuries, and suggest that the phenomenon is strongly determined by cortical circuits. Moreover, changes in GABAergic transmission at the deprived cortex may be considered one of the mechanisms underlying the process of cortical reorganization and increased excitability.

Amyloid pathology impairs experience-dependent inhibitory synaptic plasticity

Alzheimer's disease patients and mouse models exhibit aberrant neuronal activity and altered excitatory-to-inhibitory synaptic ratio. Using multicolor two-photon microscopy, we test how amyloid pathology alters the structural dynamics of excitatory and inhibitory synapses and their adaptation to altered visual experience in vivo in the visual cortex. We show that the baseline dynamics of mature excitatory synapses and their adaptation to visual deprivation are not altered in amyloidosis. Likewise, the baseline dynamics of inhibitory synapses are not affected. In contrast, visual deprivation fails to induce inhibitory synapse loss in amyloidosis, a phenomenon observed in nonpathological conditions. Intriguingly, inhibitory synapse loss associated with visual deprivation in nonpathological mice is accompanied by the broadening of spontaneous but not visually evoked calcium transients. However, such broadening does not manifest in the context of amyloidosis. We also show that excitatory and inhibitory synapse loss is locally clustered under the nonpathological state. In contrast, a fraction of synapse loss is not locally clustered in amyloidosis, indicating an impairment in inhibitory synapse adaptation to changes in excitatory synaptic activity.

Electrophysiological properties of layer 2/3 pyramidal neurons in the primary visual cortex of a retinitis pigmentosa mouse model (rd10)

Retinal degeneration is one of the main causes of visual impairment and blindness. One group of retinal degenerative diseases, leading to the loss of photoreceptors, is collectively termed retinitis pigmentosa. In this group of diseases, the remaining retina is largely spared from initial cell death making retinal ganglion cells an interesting target for vision restoration methods. However, it is unknown how downstream brain areas, in particular the visual cortex, are affected by the progression of blindness. Visual deprivation studies have shown dramatic changes in the electrophysiological properties of visual cortex neurons, but changes on a cellular level in retinitis pigmentosa have not been investigated yet. Therefore, we used the rd10 mouse model to perform patch-clamp recordings of pyramidal neurons in layer 2/3 of the primary visual cortex to screen for potential changes in electrophysiological properties resulting from retinal degeneration. Compared to wild-type C57BL/6 mice, we only found an increase in intrinsic excitability around the time point of maximal retinal degeneration. In addition, we saw an increase in the current amplitude of spontaneous putative inhibitory events after a longer progression of retinal degeneration. However, we did not observe a long-lasting shift in excitability after prolonged retinal degeneration. Together, our results provide evidence of an intact visual cortex with promising potential for future therapeutic strategies to restore vision.

Circuit-level theories for sensory dysfunction in autism: convergence across mouse models

Individuals with autism spectrum disorder (ASD) exhibit a diverse range of behavioral features and genetic backgrounds, but whether different genetic forms of autism involve convergent pathophysiology of brain function is unknown. Here, we analyze evidence for convergent deficits in neural circuit function across multiple transgenic mouse models of ASD. We focus on sensory areas of neocortex, where circuit differences may underlie atypical sensory processing, a central feature of autism. Many distinct circuit-level theories for ASD have been proposed, including increased excitation-inhibition (E-I) ratio and hyperexcitability, hypofunction of parvalbumin (PV) interneuron circuits, impaired homeostatic plasticity, degraded sensory coding, and others. We review these theories and assess the degree of convergence across ASD mouse models for each. Behaviorally, our analysis reveals that innate sensory detection behavior is heightened and sensory discrimination behavior is impaired across many ASD models. Neurophysiologically, PV hypofunction and increased E-I ratio are prevalent but only rarely generate hyperexcitability and excess spiking. Instead, sensory tuning and other aspects of neural coding are commonly degraded and may explain impaired discrimination behavior. Two distinct phenotypic clusters with opposing neural circuit signatures are evident across mouse models. Such clustering could suggest physiological subtypes of autism, which may facilitate the development of tailored therapeutic approaches.

Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not in the activity of individual neurons

The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the network's nearness to criticality, an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animal's genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.

Extensive topographic remapping and functional sharpening in the adult rat visual pathway upon first visual experience

Understanding the dynamics of stability/plasticity balances during adulthood is pivotal for learning, disease, and recovery from injury. However, the brain-wide topography of sensory remapping remains unknown. Here, using a first-of-its-kind setup for delivering patterned visual stimuli in a rodent magnetic resonance imaging (MRI) scanner, coupled with biologically inspired computational models, we noninvasively mapped brain-wide properties-receptive fields (RFs) and spatial frequency (SF) tuning curves-that were insofar only available from invasive electrophysiology or optical imaging. We then tracked the RF dynamics in the chronic visual deprivation model (VDM) of plasticity and found that light exposure progressively promoted a large-scale topographic remapping in adult rats. Upon light exposure, the initially unspecialized visual pathway progressively evidenced sharpened RFs (smaller and more spatially selective) and enhanced SF tuning curves. Our findings reveal that visual experience following VDM reshapes both structure and function of the visual system and shifts the stability/plasticity balance in adults.

Emerging V1 neuronal ensembles with enhanced connectivity after associative learning

Introduction

The visual stimulus-specific responses in the primary visual cortex (V1) undergo plastic changes after associative learning. During the learning process, neuronal ensembles, defined as groups of coactive neurons, are well known to be related to learning and memory. However, it remains unclear what effect learning has on ensembles, and which neuronal subgroups within those ensembles play a key role in associative learning.

Methods

We used two-photon calcium imaging in mice to record the activity of V1 neurons before and after fear conditioning associated with a visual cue (blue light). We first defined neuronal ensembles by thresholding their functional connectivity in response to blue (conditioned) or green (control) light. We defined neurons that existed both before and after conditioning as stable neurons. Neurons which were recruited after conditioning were defined as new neurons. The graph theory-based analysis was performed to quantify the changes in connectivity within ensembles after conditioning.

Results

A significant enhancement in the connectivity strength (the average correlation with other neurons) was observed in the blue ensembles after conditioning. We found that stable neurons within the blue ensembles showed a significantly smaller clustering coefficient (the value represented the degree of interconnectedness among a node's neighbors) after conditioning than they were before conditioning. Additionally, new neurons within the blue ensembles had a larger clustering coefficient, similar relative degree (the value represented the number of functional connections between neurons) and connectivity strength compared to stable neurons in the same ensembles.

Discussion

Overall, our results demonstrated that the plastic changes caused by conditioning occurred in subgroups of neurons in the ensembles. Moreover, new neurons from conditioned ensembles may play a crucial role in memory formation, as they exhibited not only similar connection competence in relative degree and connectivity strength as stable neurons, but also showed a significantly larger clustering coefficient compared to the stable neurons within the same ensembles after conditioning.

Amplified cortical neural responses as animals learn to use novel activity patterns

Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.

Short-term homeostatic visual neuroplasticity in adolescents after two hours of monocular deprivation

In healthy adults with normal vision, temporary deprivation of one eye's visual experience produces transient yet robust homeostatic plasticity effects, where the deprived eye becomes more dominant. This shift in ocular dominance is short-lived and compensatory. Previous work shows that monocular deprivation decreases resting state gamma aminobutyric acid (GABA; inhibitory neurotransmitter) levels in visual cortex, and that those with the greatest reduction in GABA have stronger shifts due to monocular deprivation. Components of the GABAergic system in visual cortex vary with age (early childhood, early teen years, ageing); hence if GABA is critical to homeostatic plasticity within the visual system, adolescence may be a key developmental period where differences in plasticity manifest. Here we measured short-term visual deprivation effects on binocular rivalry in 24 adolescents (aged 10-15 years) and 23 young adults (aged 20-25 years). Despite differences in baseline features of binocular rivalry (adolescents showed more mixed percept p < 0.001 and a tendency for faster switching p = 0.06 compared to adults), deprived eye dominance increased (p = 0.01) similarly for adolescents and adults after two hours of patching. Other aspects of binocular rivalry - time to first switch (heralding the onset of rivalry) and mixed percept - were unaltered by patching. These findings suggest that binocular rivalry after patching can be used as a behavioral proxy for experience-dependent visual cortical plasticity in adolescents in the same way as adults, and that homeostatic plasticity to compensate for temporarily reduced visual input is established and effective by adolescence.

Responses of pyramidal cell somata and apical dendrites in mouse visual cortex over multiple days

The apical dendrites of pyramidal neurons in sensory cortex receive primarily top-down signals from associative and motor regions, while cell bodies and nearby dendrites are heavily targeted by locally recurrent or bottom-up inputs from the sensory periphery. Based on these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in learning. However, due to technical challenges in data collection, little data is available for comparing the responses of apical dendrites to cell bodies over multiple days. Here we present a dataset collected through the Allen Institute Mindscope's OpenScope program that addresses this need. This dataset comprises high-quality two-photon calcium imaging from the apical dendrites and the cell bodies of visual cortical pyramidal neurons, acquired over multiple days in awake, behaving mice that were presented with visual stimuli. Many of the cell bodies and dendrite segments were tracked over days, enabling analyses of how their responses change over time. This dataset allows neuroscientists to explore the differences between apical and somatic processing and plasticity.