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A new microendoscopic method reveals that hippocampal dendritic spines in the CA1 region undergo a complete turnover in less than six weeks in adult mice; this contrasts with the much greater stability of synapses in the neocortex and provides a physical basis for the fact that episodic memories are only retained by the mouse hippocampus for a few weeks. Dendritic spine turnover in the hippocampus Episodic memories are formed in the mammalian hippocampus but retained there only for a few weeks, compared to the months and years of memory storage provided in the neocortex. Mark Schnitzer and colleagues have used a new microendoscopic method to reveal that hippocampal dendritic spines in the CA1 region undergo complete turnover in less than six weeks in mice, in contrast to the much greater stability of synapses in the neocortex. This work illustrates a possible physical basis for the transience of hippocampal memory processes. The mammalian hippocampus is crucial for episodic memory formation 1 and transiently retains information for about 3–4 weeks in adult mice and longer in humans 2 . Although neuroscientists widely believe that neural synapses are elemental sites of information storage 3 , there has been no direct evidence that hippocampal synapses persist for time intervals commensurate with the duration of hippocampal-dependent memory. Here we tested the prediction that the lifetimes of hippocampal synapses match the longevity of hippocampal memory. By using time-lapse two-photon microendoscopy 4 in the CA1 hippocampal area of live mice, we monitored the turnover dynamics of the pyramidal neurons’ basal dendritic spines, postsynaptic structures whose turnover dynamics are thought to reflect those of excitatory synaptic connections 5 , 6 . Strikingly, CA1 spine turnover dynamics differed sharply from those seen previously in the neocortex 7 , 8 , 9 . Mathematical modelling revealed that the data best matched kinetic models with a single population of spines with a mean lifetime of approximately 1–2 weeks. This implies ∼100% turnover in ∼2–3 times this interval, a near full erasure of the synaptic connectivity pattern. Although N -methyl- d -aspartate (NMDA) receptor blockade stabilizes spines in the neocortex 10 , 11 , in CA1 it transiently increased the rate of spine loss and thus lowered spine density. These results reveal that adult neocortical and hippocampal pyramidal neurons have divergent patterns of spine regulation and quantitatively support the idea that the transience of hippocampal-dependent memory directly reflects the turnover dynamics of hippocampal synapses.

Optical imaging through the intact mouse skull is challenging because of skull-induced aberrations and scattering. We found that three-photon excitation provided improved optical sectioning compared with that obtained with two-photon excitation, even when we used the same excitation wavelength and imaging system. Here we demonstrate three-photon imaging of vasculature through the adult mouse skull at >500-μm depth, as well as GCaMP6s calcium imaging over weeks in cortical layers 2/3 and 4 in awake mice, with 8.5 frames per second and a field of view spanning hundreds of micrometers.

The authors use Ca 2+ imaging in freely behaving mice to look at the long-term dynamics of CA1 hippocampal place codes. They find that, in a familiar environment, there is substantial change in the population of place-coding cells over time, but the ensembles of these cells are sufficiently stable to preserve an accurate spatial representation across weeks. Using Ca 2+ imaging in freely behaving mice that repeatedly explored a familiar environment, we tracked thousands of CA1 pyramidal cells' place fields over weeks. Place coding was dynamic, as each day the ensemble representation of this environment involved a unique subset of cells. However, cells in the ∼15–25% overlap between any two of these subsets retained the same place fields, which sufficed to preserve an accurate spatial representation across weeks.

How the brain processes information accurately despite stochastic neural activity is a longstanding question 1 . For instance, perception is fundamentally limited by the information that the brain can extract from the noisy dynamics of sensory neurons. Seminal experiments 2 , 3 suggest that correlated noise in sensory cortical neural ensembles is what limits their coding accuracy 4 – 6 , although how correlated noise affects neural codes remains debated 7 – 11 . Recent theoretical work proposes that how a neural ensemble’s sensory tuning properties relate statistically to its correlated noise patterns is a greater determinant of coding accuracy than is absolute noise strength 12 – 14 . However, without simultaneous recordings from thousands of cortical neurons with shared sensory inputs, it is unknown whether correlated noise limits coding fidelity. Here we present a 16-beam, two-photon microscope to monitor activity across the mouse primary visual cortex, along with analyses to quantify the information conveyed by large neural ensembles. We found that, in the visual cortex, correlated noise constrained signalling for ensembles with 800–1,300 neurons. Several noise components of the ensemble dynamics grew proportionally to the ensemble size and the encoded visual signals, revealing the predicted information-limiting correlations 12 – 14 . Notably, visual signals were perpendicular to the largest noise mode, which therefore did not limit coding fidelity. The information-limiting noise modes were approximately ten times smaller and concordant with mouse visual acuity 15 . Therefore, cortical design principles appear to enhance coding accuracy by restricting around 90% of noise fluctuations to modes that do not limit signalling fidelity, whereas much weaker correlated noise modes inherently bound sensory discrimination. A microscopy system that enables simultaneous recording from hundreds of neurons in the mouse visual cortex reveals that the brain enhances its coding capacity by representing visual inputs in dimensions perpendicular to correlated noise.

How is it that groups of neurons dispersed through the brain interact to generate complex behaviors? Three papers in this issue present brain-scale studies of neuronal activity and dynamics (see the Perspective by Huk and Hart). Allen et al. found that in thirsty mice, there is widespread neural activity related to stimuli that elicit licking and drinking. Individual neurons encoded task-specific responses, but every brain area contained neurons with different types of response. Optogenetic stimulation of thirst-sensing neurons in one area of the brain reinstated drinking and neuronal activity across the brain that previously signaled thirst. Gründemann et al. investigated the activity of mouse basal amygdala neurons in relation to behavior during different tasks. Two ensembles of neurons showed orthogonal activity during exploratory and nonexploratory behaviors, possibly reflecting different levels of anxiety experienced in these areas. Stringer et al. analyzed spontaneous neuronal firing, finding that neurons in the primary visual cortex encoded both visual information and motor activity related to facial movements. The variability of neuronal responses to visual stimuli in the primary visual area is mainly related to arousal and reflects the encoding of latent behavioral states. Science , this issue p. eaav3932 , p. eaav8736 , p. eaav7893 ; see also p. 236 Longitudinal large-scale imaging of amygdala activity reveals dynamic encoding of behavioral states by two distinct neural ensembles. Internal states, including affective or homeostatic states, are important behavioral motivators. The amygdala regulates motivated behaviors, yet how distinct states are represented in amygdala circuits is unknown. By longitudinally imaging neural calcium dynamics in freely moving mice across different environments, we identified opponent changes in activity levels of two major, nonoverlapping populations of basal amygdala principal neurons. This population signature does not report global anxiety but predicts switches between exploratory and nonexploratory, defensive states. Moreover, the amygdala separately processes external stimuli and internal states and broadcasts state information via several output pathways to larger brain networks. Our findings extend the concept of thalamocortical “brain-state” coding to include affective and exploratory states and provide an entry point into the state dependency of brain function and behavior in defined circuits.

Two-photon microscopy is a mainstay technique for imaging in scattering media and normally provides frame-acquisition rates of ~10–30 Hz. To track high-speed phenomena, we created a two-photon microscope with 400 illumination beams that collectively sample 95,000–211,000 µm2 areas at rates up to 1 kHz. Using this microscope, we visualized microcirculatory flow, fast venous constrictions and neuronal Ca2+ spiking with millisecond-scale timing resolution in the brains of awake mice.

A collection of opsins for two-photon modulation of neuronal activity in vitro and in vivo is presented in this resource. The opsins have kinetic, expression and spectral properties ideally suited to typical raster-scanning two-photon microscopy. Also online, Packer et al . use the red-shifted opsin C1V1 T and simple raster-scanning illumination to stimulate individual spines and dendrites and map synaptic circuits. Optogenetics with microbial opsin genes has enabled high-speed control of genetically specified cell populations in intact tissue. However, it remains a challenge to independently control subsets of cells within the genetically targeted population. Although spatially precise excitation of target molecules can be achieved using two-photon laser-scanning microscopy (TPLSM) hardware, the integration of two-photon excitation with optogenetics has thus far required specialized equipment or scanning and has not yet been widely adopted. Here we take a complementary approach, developing opsins with custom kinetic, expression and spectral properties uniquely suited to scan times typical of the raster approach that is ubiquitous in TPLSM laboratories. We use a range of culture, slice and mammalian in vivo preparations to demonstrate the versatility of this toolbox, and we quantitatively map parameter space for fast excitation, inhibition and bistable control. Together these advances may help enable broad adoption of integrated optogenetic and TPLSM technologies across experimental fields and systems.

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.Learning new associations that reappraise the behavioral significance of previously irrelevant cues requires gamma-frequency synchronization between parvalbumin interneurons in the left and right prefrontal cortex.

Neurons in the CA1 area of the mouse hippocampus encode the position of the animal in an environment. However, given the variability in individual neurons responses, the accuracy of this code is still poorly understood. It was proposed that downstream areas could achieve high spatial accuracy by integrating the activity of thousands of neurons, but theoretical studies point to shared fluctuations in the firing rate as a potential limitation. Using high-throughput calcium imaging in freely moving mice, we demonstrated the limiting factors in the accuracy of the CA1 spatial code. We found that noise correlations in the hippocampus bound the estimation error of spatial coding to ~10 cm (the size of a mouse). Maximal accuracy was obtained using approximately [300–1400] neurons, depending on the animal. These findings reveal intrinsic limits in the brain’s representations of space and suggest that single neurons downstream of the hippocampus can extract maximal spatial information from several hundred inputs. CA1 neurons encode an animal's position within the environment. Here the authors identified in hippocampal neuronal activity a detrimental type of noise that limits accuracy of spatial position, relative to body size.

A longstanding goal in neuroscience has been to develop techniques for imaging the voltage dynamics of genetically defined subsets of neurons. Optical sensors of transmembrane voltage would enhance studies of neural activity in contexts ranging from individual neurons cultured in vitro to neuronal populations in awake-behaving animals. Recent progress has identified Archaerhodopsin (Arch) based sensors as a promising, genetically encoded class of fluorescent voltage indicators that can report single action potentials. Wild-type Arch exhibits sub-millisecond fluorescence responses to trans-membrane voltage, but its light-activated proton pump also responds to the imaging illumination. An Arch mutant (Arch-D95N) exhibits no photocurrent, but has a slower, ~40 ms response to voltage transients. Here we present Arch-derived voltage sensors with trafficking signals that enhance their localization to the neural membrane. We also describe Arch mutant sensors (Arch-EEN and -EEQ) that exhibit faster kinetics and greater fluorescence dynamic range than Arch-D95N, and no photocurrent at the illumination intensities normally used for imaging. We benchmarked these voltage sensors regarding their spike detection fidelity by using a signal detection theoretic framework that takes into account the experimentally measured photon shot noise and optical waveforms for single action potentials. This analysis revealed that by combining the sequence mutations and enhanced trafficking sequences, the new sensors improved the fidelity of spike detection by nearly three-fold in comparison to Arch-D95N.