Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.

Muscle spasms are common in chronic spinal cord injury (SCI), posing challenges to rehabilitation and daily activities. Pharmacological management of spasms mostly targets suppression of excitatory inputs, an approach known to hinder motor recovery. To identify better targets, we investigated changes in inhibitory and excitatory synaptic inputs to motoneurons as well as motoneuron excitability in chronic SCI. We induced either a complete or incomplete SCI in adult mice of either sex and divided those with incomplete injury into low or high functional recovery groups. Their sacrocaudal spinal cords were then extracted and used to study plasticity below injury, with tissue from naive animals as a control. Electrical stimulation of the dorsal roots elicited spasm-like activity in preparations of chronic severe SCI but not in the control. To evaluate overall synaptic inhibition activated by sensory stimulation, we measured the rate-dependent depression of spinal root reflexes. We found inhibitory inputs to be impaired in chronic injury models. When synaptic inhibition was blocked pharmacologically, all preparations became clearly spastic, even the control. However, preparations with chronic injuries generated longer spasms than control. We then measured excitatory postsynaptic currents (EPSCs) in motoneurons during sensory-evoked spasms. The data showed no difference in the amplitude of EPSCs or their conductance among animal groups. Nonetheless, we found that motoneuron persistent inward currents activated by the EPSCs were increased in chronic SCI. These findings suggest that changes in motoneuron excitability and synaptic inhibition, rather than excitation, contribute to spasms and are better suited for more effective therapeutic interventions.Significance Statement Neural plasticity following spinal cord injury is crucial for recovery of motor function. Unfortunately, this process is blemished by maladaptive changes that can cause muscle spasms. Pharmacological alleviation of spasms without compromising the recovery of motor function has proven to be challenging. Here, we investigated changes in fundamental spinal mechanisms that can cause spasms post-injury. Our data suggest that the current management strategy for spasms is misdirected toward suppressing excitatory inputs, a mechanism that we found unaltered after injury, which can lead to further motor weakness. Instead, this study shows that more promising approaches might involve restoring synaptic inhibition or modulating motoneuron excitability.

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their \"paradoxical response\", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

The epidemiological association between bacterial or viral maternal infections during pregnancy and increased risk for developing psychiatric disorders in offspring is well documented. Numerous rodent and non-human primate studies of viral- or, to a lesser extent, bacterial-induced maternal immune activation (MIA) have documented a series of neurological alterations that may contribute to understanding the pathophysiology of schizophrenia and autism spectrum disorders. Long-term neuronal and behavioral alterations are now ascribed to the effect of maternal proinflammatory cytokines rather than the infection itself. However, detailed electrophysiological alterations in brain areas relevant to psychiatric disorders, such as the dorsal hippocampus, are lacking in response to bacterial-induced MIA. This study determined if electrophysiological and morphological alterations converge in CA1 pyramidal cells (CA1 PC) from the dorsal hippocampus in bacterial-induced MIA offspring. A series of changes in the functional expression of K+ and Na+ ion channels altered the passive and active membrane properties and triggered hyperexcitability of CA1 PC. Contributing to the hyperexcitability, the somatic A-type potassium current (IA) was decreased in MIA CA1 PC. Likewise, the spontaneous glutamatergic and GABAergic inputs were dysregulated and biased toward increased excitation, thereby reshaping the excitation-inhibition balance. Consistent with these findings, the dendritic branching complexity of MIA CA1 PC was reduced. Together, these morphophysiological alterations modify CA1 PC computational capabilities and contribute to explaining cellular alterations that may underlie the cognitive symptoms of MIA-associated psychiatric disorders.

Neonatal brain injury renders the developing brain vulnerable to oxidative stress, leading to cognitive deficit. However, oxidative stress-induced damage to hippocampal circuits and the mechanisms underlying long-term changes in memory and learning are poorly understood. We used high oxygen tension or hyperoxia (HO) in neonatal mice of both sexes to investigate the role of oxidative stress in hippocampal damage. Perinatal HO induces reactive oxygen species and cell death, together with reduced interneuron maturation, inhibitory postsynaptic currents, and dentate progenitor proliferation. Postinjury interneuron stimulation surprisingly improved inhibitory activity and memory tasks, indicating reversibility. With decreased hippocampal levels of Wnt signaling components and somatostatin, HO aberrantly activated glycogen synthase kinase 3 β activity. Pharmacological inhibition or ablation of interneuron glycogen synthase kinase 3 β during HO challenge restored progenitor cell proliferation, interneuron development, inhibitory/excitatory balance, as well as hippocampal-dependent behavior. Biochemical targeting of interneuron function may benefit learning deficits caused by oxidative damage.SIGNIFICANCE STATEMENT Premature infants are especially vulnerable to oxidative stress, as their antioxidant defenses are underdeveloped. Indeed, high oxygen tension is associated with poor neurologic outcomes. Because of its sustained postnatal development and role in learning and memory, the hippocampus is especially vulnerable to oxidative damage in premature infants. However, the role of oxidative stress in the developing hippocampus has yet to be explored. With ever-rising rates of neonatal brain injury and no universally viable approach to maximize functional recovery, a better understanding of the mechanisms underlying neonatal brain injury is needed. Addressing this need, this study uses perinatal hyperoxia to study cognitive deficits, pathophysiology, and molecular mechanisms of oxidative damage in the developing hippocampus.

Altered neuronal excitation-inhibition (E-I) balance is strongly implicated in ASD. However, it is not known whether the direction and degree of changes in the E-I ratio in individuals with ASD correlates with intellectual disability often associated with this developmental disorder. The spectral slope of the aperiodic 1/f activity reflects the E-I balance at the scale of large neuronal populations and may uncover its putative alternations in individuals with ASD with and without intellectual disability.
Herein, we used magnetoencephalography (MEG) to test whether the 1/f slope would differentiate ASD children with average and below-average (< 85) IQ. MEG was recorded at rest with eyes open/closed in 49 boys with ASD aged 6-15 years with IQ ranging from 54 to 128, and in 49 age-matched typically developing (TD) boys. The cortical source activity was estimated using the beamformer approach and individual brain models. We then extracted the 1/f slope by fitting a linear function to the log-log-scale power spectra in the high-frequency range.
The global 1/f slope averaged over all cortical sources demonstrated high rank-order stability between the two conditions. Consistent with previous research, it was steeper in the eyes-closed than in the eyes-open condition and flattened with age. Regardless of condition, children with ASD and below-average IQ had flatter slopes than either TD or ASD children with average or above-average IQ. These group differences could not be explained by differences in signal-to-noise ratio or periodic (alpha and beta) activity.
Further research is needed to find out whether the observed changes in E-I ratios are characteristic of children with below-average IQ of other diagnostic groups.
The atypically flattened spectral slope of aperiodic activity in children with ASD and below-average IQ suggests a shift of the global E-I balance toward hyper-excitation. The spectral slope can provide an accessible noninvasive biomarker of the E-I ratio for making objective judgments about treatment effectiveness in people with ASD and comorbid intellectual disability.

Hierarchical synchronization of sleep oscillations establishes communication pathways to support memory reactivation, transfer, and consolidation. From an information-theoretical perspective, oscillations constitute highly structured network states that provide limited information-coding capacity. Recent findings indicate that sleep oscillations occur in transient bursts that are interleaved with aperiodic network states, which were previously considered to be random noise. We argue that aperiodic activity exhibits unique and variable spatiotemporal patterns, providing an ideal information-rich neurophysiological substrate for imprinting new mnemonic patterns onto existing circuits. We discuss novel avenues in conceptualizing and quantifying aperiodic network states during sleep to further understand their relevance and interplay with sleep oscillations in support of memory consolidation.

Synapses are the fundamental elements of the brain\'s complicated neural networks. Although the ultrastructure of synapses has been extensively studied, the difference in how synaptic inputs are organized onto distinct neuronal types is not yet fully understood. Here, we examined the cell-type-specific ultrastructure of proximal processes from the soma of parvalbumin-positive (PV+) and somatostatin-positive (SST+) GABAergic neurons in comparison with a pyramidal neuron in the mouse primary visual cortex (V1), using serial block-face scanning electron microscopy. Interestingly, each type of neuron organizes excitatory and inhibitory synapses in a unique way. First, we found that a subset of SST+ neurons are spiny, having spines on both soma and dendrites. Each of those spines has a highly complicated structure that has up to eight synaptic inputs. Next, the PV+ and SST+ neurons receive more robust excitatory inputs to their perisoma than does the pyramidal neuron. Notably, excitatory synapses on GABAergic neurons were often multiple-synapse boutons, making another synapse on distal dendrites. On the other hand, inhibitory synapses near the soma were often single-targeting multiple boutons. Collectively, our data demonstrate that synaptic inputs near the soma are differentially organized across cell types and form a network that balances inhibition and excitation in the V1.

Finely tuned excitation-inhibition balance is essential for proper brain function, and loss of balance resulting from reduced synaptic inhibition is associated with neurological disorders. Savardi and colleagues have discovered a novel inhibitor of a cation-chloride transporter that is required for synaptic inhibition, and which restores behaviors associated with Down syndrome (DS) and autism spectrum disorder (ASD).