Rapid synaptic and gamma rhythm signature of mouse critical period plasticity.

Early-life experience enduringly sculpts thalamocortical (TC) axons and sensory processing. Here, we identify the very first synaptic targets that initiate critical period plasticity, heralded by altered cortical oscillations. Monocular deprivation (MD) acutely induced a transient (<3 h) peak in EEG γ-power (~40 Hz) specifically within the visual cortex, but only when the critical period was open (juvenile mice or adults after dark-rearing, Lynx1-deletion, or diazepam-rescued GAD65-deficiency). Rapid TC input loss onto parvalbumin-expressing (PV) inhibitory interneurons (but not onto nearby pyramidal cells) was observed within hours of MD in a TC slice preserving the visual pathway - again once critical periods opened. Computational TC modeling of the emergent γ-rhythm in response to MD delineated a cortical interneuronal gamma (ING) rhythm in networks of PV-cells bearing gap junctions at the start of the critical period. The ING rhythm effectively dissociated thalamic input from cortical spiking, leading to rapid loss of previously strong TC-to-PV connections through standard spike-timing-dependent plasticity rules. As a consequence, previously silent TC-to-PV connections could strengthen on a slower timescale, capturing the gradually increasing γ-frequency and eventual fade-out over time. Thus, ING enables cortical dynamics to transition from being dominated by the strongest TC input to one that senses the statistics of population TC input after MD. Taken together, our findings reveal the initial synaptic events underlying critical period plasticity and suggest that the fleeting ING accompanying a brief sensory perturbation may serve as a robust readout of TC network state with which to probe developmental trajectories.

Critical period regulation across multiple timescales.

Brain plasticity is dynamically regulated across the life span, peaking during windows of early life. Typically assessed in the physiological range of milliseconds (real time), these trajectories are also influenced on the longer timescales of developmental time (nurture) and evolutionary time (nature), which shape neural architectures that support plasticity. Properly sequenced critical periods of circuit refinement build up complex cognitive functions, such as language, from more primary modalities. Here, we consider recent progress in the biological basis of critical periods as a unifying rubric for understanding plasticity across multiple timescales. Notably, the maturation of parvalbumin-positive (PV) inhibitory neurons is pivotal. These fast-spiking cells generate gamma oscillations associated with critical period plasticity, are sensitive to circadian gene manipulation, emerge at different rates across brain regions, acquire perineuronal nets with age, and may be influenced by epigenetic factors over generations. These features provide further novel insight into the impact of early adversity and neurodevelopmental risk factors for mental disorders.

A practical guide to applying machine learning to infant EEG data.

Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challenging due to the low number of trials, low signal-to-noise ratio, high inter-subject variability, and high inter-trial variability. Here, we provide a step-by-step tutorial on how to apply ML to classify cognitive states in infants. We describe the type of brain attributes that are widely used for EEG classification and also introduce a Riemannian geometry based approach for deriving connectivity estimates that account for inter-trial and inter-subject variability. We present pipelines for learning classifiers using trials from a single infant and from multiple infants, and demonstrate the application of these pipelines on a standard infant EEG dataset of forty 12-month-old infants collected under an auditory oddball paradigm. While we classify perceptual states induced by frequent versus rare stimuli, the presented pipelines can be easily adapted for other experimental designs and stimuli using the associated code that we have made publicly available.

Identification of a population of sleep-active cerebral cortex neurons.

The presence of large-amplitude, slow waves in the EEG is a primary characteristic that distinguishes cerebral activity during sleep from that which occurs during wakefulness. Although sleep-active neurons have been identified in other brain areas, neurons that are specifically activated during slow-wave sleep have not previously been described in the cerebral cortex. We have identified a population of cells in the cortex that is activated during sleep in three mammalian species. These cortical neurons are a subset of GABAergic interneurons that express neuronal NOS (nNOS). Because Fos expression in these sleep-active, nNOS-immunoreactive (nNOS-ir) neurons parallels changes in the intensity of slow-wave activity in the EEG, and these neurons are innvervated by neurotransmitter systems previously implicated in sleep/wake control, cortical nNOS-ir neurons may be part of the neurobiological substrate that underlies homeostatic sleep regulation.

Distributional learning of speech sound categories is gated by sensitive periods.

Perceptual attunement to the native phonetic repertoire occurs over the first year of life: an infant's discrimination of non-native phonetic contrasts declines while their discrimination of native phonetic contrasts improves, with the timing of change consistent with sensitive periods. The statistics of speech sound distributions is one source of input used to collapse non-native phonetic category boundaries, while sharpening native ones. Distributional learning can be a domain-general mechanism, yet given the timing of perceptual attunement, we hypothesized that this learning mechanism may be maturationally delimited in the content domain of phonetic categories. Here, we assessed whether sensitivity to the distribution of speech sounds in the environment declines as the period of perceptual attunement closes. We used electroencephalography (EEG) to investigate whether neuronal responses to native 'ra' and 'la' phones are modulated differently in older vs young infants by exposure to either a bimodal or unimodal sound distribution spanning the [r] ~ [l] phoneme space. The native contrast, ra-la, is discriminable at all three ages, ensuring that we were testing the distributional learning mechanism, rather than confounding it with a decline in discrimination to a non-native distinction. English monolingual infants (n = 131) at 5-, 9- and 12-months-old were familiarized to either a unimodal or bimodal distribution of /ra/-/la/ speech sounds. Immediately following familiarization, an ERP oddball task was used to assess discrimination. Results showed that brief exposure to a bi- vs uni-modal distribution is sufficient to alter neuronal responses to subsequent /ra/ vs /la/ speech sounds at 5-months and 9-months, but not at 12-months. These results are the first to capture a progressive decline in sensitivity to distributional statistics in the environment. A potential mechanistic explanation based on critical period biology is discussed.

The role of norepinephrine in differential response to stress in an animal model of posttraumatic stress disorder.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder precipitated by exposure to extreme traumatic stress. Yet, most individuals exposed to traumatic stress do not develop PTSD and may be considered psychologically resilient. The neural circuits involved in susceptibility or resiliency to PTSD remain unclear, but clinical evidence implicates changes in the noradrenergic system. METHODS: An animal model of PTSD called Traumatic Experience with Reminders of Stress (TERS) was developed by exposing C57BL/6 mice to a single shock (2 mA, 10 sec) followed by exposure to six contextual 1-minute reminders of the shock over a 25-day period. Acoustic startle response (ASR) testing before the shock and after the last reminder allowed experimenters to separate the shocked mice into two cohorts: mice that developed a greatly increased ASR (TERS-susceptible mice) and mice that did not (TERS-resilient mice). RESULTS: Aggressive and social behavioral correlates of PTSD increased in TERS-susceptible mice but not in TERS-resilient mice or control mice. Characterization of c-Fos expression in stress-related brain regions revealed that TERS-susceptible and TERS-resilient mice displayed divergent brain activation following swim stress compared with control mice. Pharmacological activation of noradrenergic inhibitory autoreceptors or blockade of postsynaptic α(1)-adrenoreceptors normalized ASR, aggression, and social interaction in TERS-susceptible mice. The TERS-resilient, but not TERS-susceptible, mice showed a trend toward decreased behavioral responsiveness to noradrenergic autoreceptor blockade compared with control mice. CONCLUSIONS: These data implicate the noradrenergic system as a possible site of pathological and perhaps also adaptive plasticity in response to traumatic stress.