Thalamic relay neurons have well-characterized dual firing modes: bursting and tonic spiking. Studies in brain slices have led to a model in which rhythmic synchronized spiking (phasic firing) in a population of relay neurons leads to hyper-synchronous oscillatory cortico-thalamo-cortical rhythms that result in absence seizures. This model suggests that blocking thalamocortical phasic firing would treat absence seizures. However, recent in vivo studies in anesthetized animals have questioned this simple model. Here we resolve this issue by developing a real-time, mode-switching approach to drive thalamocortical neurons into or out of a phasic firing mode in two freely behaving genetic rodent models of absence epilepsy. Toggling between phasic and tonic firing in thalamocortical neurons launched and aborted absence seizures, respectively. Thus, a synchronous thalamocortical phasic firing state is required for absence seizures, and switching to tonic firing rapidly halts absences. This approach should be useful for modulating other networks that have mode-dependent behaviors.

Organisms must learn new strategies to adapt to changing environments. Activity in different neurons often exhibits synchronization that can dynamically enhance their communication and might create flexible brain states that facilitate changes in behavior. We studied the role of gamma-frequency (~40 Hz) synchrony between prefrontal parvalbumin (PV) interneurons in mice learning multiple new cue-reward associations. Voltage indicators revealed cell-type-specific increases of cross-hemispheric gamma synchrony between PV interneurons when mice received feedback that previously learned associations were no longer valid. Disrupting this synchronization by delivering out-of-phase optogenetic stimulation caused mice to perseverate on outdated associations, an effect not reproduced by in-phase stimulation or out-of-phase stimulation at other frequencies. Gamma synchrony was specifically required when new associations used familiar cues that were previously irrelevant to behavioral outcomes, not when associations involved new cues or for reversing previously learned associations. Thus, gamma synchrony is indispensable for reappraising the behavioral salience of external cues.

Organisms must learn new strategies to adapt to changing environments. Activity in different neurons often exhibits synchronization that can dynamically enhance their communication and might create flexible brain states that facilitate changes in behavior. We studied the role of gamma-frequency (~40 Hz) synchrony between prefrontal parvalbumin (PV) interneurons in mice learning multiple new cue-reward associations. Voltage indicators revealed cell-type-specific increases of cross-hemispheric gamma synchrony between PV interneurons when mice received feedback that previously learned associations were no longer valid. Disrupting this synchronization by delivering out-of-phase optogenetic stimulation caused mice to perseverate on outdated associations, an effect not reproduced by in-phase stimulation or out-of-phase stimulation at other frequencies. Gamma synchrony was specifically required when new associations used familiar cues that were previously irrelevant to behavioral outcomes, not when associations involved new cues or for reversing previously learned associations. Thus, gamma synchrony is indispensable for reappraising the behavioral salience of external cues.

The hippocampus is a mammalian brain structure that expresses spatial representations¹ and is crucial for navigation^2,3. Navigation, in turn, intricately depends on locomotion; however, current accounts suggest a dissociation between hippocampal spatial representations and the details of locomotor processes. Specifically, the hippocampus is thought to represent mainly higher-order cognitive and locomotor variables such as position, speed and direction of movement^4-7, whereas the limb movements that propel the animal can be computed and represented primarily in subcortical circuits, including the spinal cord, brainstem and cerebellum^8-11. Whether hippocampal representations are actually decoupled from the detailed structure of locomotor processes remains unknown. To address this question, here we simultaneously monitored hippocampal spatial representations and ongoing limb movements underlying locomotion at fast timescales. We found that the forelimb stepping cycle in freely behaving rats is rhythmic and peaks at around 8 Hz during movement, matching the approximately 8 Hz modulation of hippocampal activity and spatial representations during locomotion¹². We also discovered precisely timed coordination between the time at which the forelimbs touch the ground ('plant' times of the stepping cycle) and the hippocampal representation of space. Notably, plant times coincide with hippocampal representations that are closest to the actual position of the nose of the rat, whereas between these plant times, the hippocampal representation progresses towards possible future locations. This synchronization was specifically detectable when rats approached spatial decisions. Together, our results reveal a profound and dynamic coordination on a timescale of tens of milliseconds between central cognitive representations and peripheral motor processes. This coordination engages and disengages rapidly in association with cognitive demands and is well suited to support rapid information exchange between cognitive and sensory-motor circuits.

Anxiety-related conditions are among the most difficult neuropsychiatric diseases to treat pharmacologically, but respond to cognitive therapies. There has therefore been interest in identifying relevant top-down pathways from cognitive control regions in medial prefrontal cortex (mPFC). Identification of such pathways could contribute to our understanding of the cognitive regulation of affect, and provide pathways for intervention. Previous studies have suggested that dorsal and ventral mPFC subregions exert opposing effects on fear, as do subregions of other structures. However, precise causal targets for top-down connections among these diverse possibilities have not been established. Here we show that the basomedial amygdala (BMA) represents the major target of ventral mPFC in amygdala in mice. Moreover, BMA neurons differentiate safe and aversive environments, and BMA activation decreases fear-related freezing and high-anxiety states. Lastly, we show that the ventral mPFC-BMA projection implements top-down control of anxiety state and learned freezing, both at baseline and in stress-induced anxiety, defining a broadly relevant new top-down behavioural regulation pathway.

ABSTRACT

Neurodata Without Borders: Neurophysiology (NWB:N) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. With NWB:N version 2.0 (NWB:N 2.0) we made significant advances towards creating a usable standard, software ecosystem, and vibrant community for standardizing neurophysiology data. In this manuscript we focus in particular on the NWB:N data standard schema and present advances towards creating an accessible data standard for neurophysiology.