Time and experience differentially affect distinct aspects of hippocampal representational drift.

Hippocampal activity is critical for spatial memory. Within a fixed, familiar environment, hippocampal codes gradually change over timescales of days to weeks-a phenomenon known as representational drift. The passage of time and the amount of experience are two factors that profoundly affect memory. However, thus far, it has remained unclear to what extent these factors drive hippocampal representational drift. Here, we longitudinally recorded large populations of hippocampal neurons in mice while they repeatedly explored two different familiar environments that they visited at different time intervals over weeks. We found that time and experience differentially affected distinct aspects of representational drift: the passage of time drove changes in neuronal activity rates, whereas experience drove changes in the cells' spatial tuning. Changes in spatial tuning were context specific and largely independent of changes in activity rates. Thus, our results suggest that representational drift is a multi-faceted process governed by distinct neuronal mechanisms.

Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code.

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we performed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

Exercise increases information content and affects long-term stability of hippocampal place codes.

Physical exercise is known to augment brain functioning, improving memory and cognition. However, while some of the physiological effects of physical activity on the brain are known, little is known about its effects on the neural code. Using calcium imaging in freely behaving mice, we study how voluntary exercise affects the quality and long-term stability of hippocampal place codes. We find that running accelerates the emergence of a more informative spatial code in novel environments and increases code stability over days and weeks. Paradoxically, although runners demonstrated an overall more stable place code than their sedentary peers, their place code changed faster when controlling for code quality level. A model-based simulation shows that the combination of improved code quality and faster representational drift in runners, but neither of these effects alone, could account for our results. Thus, exercise may enhance hippocampal function via a more informative and dynamic place code.

Hippocampal astrocytes encode reward location.

Astrocytic calcium dynamics has been implicated in the encoding of sensory information1-5, and modulation of calcium in astrocytes has been shown to affect behaviour6-10. However, longitudinal investigation of the real-time calcium activity of astrocytes in the hippocampus of awake mice is lacking. Here we used two-photon microscopy to chronically image CA1 astrocytes as mice ran in familiar or new virtual environments to obtain water rewards. We found that astrocytes exhibit persistent ramping activity towards the reward location in a familiar environment, but not in a new one. Shifting the reward location within a familiar environment also resulted in diminished ramping. After additional training, as the mice became familiar with the new context or new reward location, the ramping was re-established. Using linear decoders, we could predict the location of the mouse in a familiar environment from astrocyte activity alone. We could not do the same in a new environment, suggesting that the spatial modulation of astrocytic activity is experience dependent. Our results indicate that astrocytes can encode the expected reward location in spatial contexts, thereby extending their known computational abilities and their role in cognitive functions.

Cerium metal oxidation studied by IR reflection-absorption and Raman scattering spectroscopies.

Oxidation of cerium metal is a complex process which is strongly affected by the presence of water vapor in the oxidative atmosphere. Here, we explore, by means of infrared reflection-absorption spectroscopy (IRRAS) and Raman scattering spectroscopies, thin oxide films, formed on cerium metal during oxidation, under dry vs ambient (humid) air conditions (∼0.2% and ∼50% relative humidities, respectively) and compare them with a thin film of CeO2deposited on a Si substrate. Complementary analysis of the thin films using x-ray diffraction and focused ion beam-scanning electron microscopy enables the correlation between their structure and spectroscopic characterizations. The initial oxidation of cerium metal results in the formation of highly sub-stoichiometric CeO2-x. Under dry air conditions, a major fraction of that oxide reacts with oxygen to form CeO∼2, which is spectroscopically detected by Raman scatteringF2gsymmetry mode and by IRAASF1usymmetry mode, splitted into doubly-degenerate transverse optic and mono-degenerate longitudinally optic (LO) modes. In contrast, under ambient (humid) conditions, the oxide formed is more heterogenous, as the reaction of CeO2-xdiverges towards the dominant formation of Ce(OH)3. Prior to the spectral emergence of Ce(OH)3, hydrogen ions incorporate into the highly sub-stoichiometric oxide, as manifested by Ce-H local vibrational mode detected in the Raman spectrum. The spectroscopic response of the thin oxide layer thus formed is more complex; particularly noted is the absence of the LO mode. It is attributed to the high density of microstructural and compositional defects in the oxide layer, which results in a heterogenous dielectric nature of the thin film, far from being representable by a single phase of CeO∼2.

Bias-free estimation of information content in temporally sparse neuronal activity.

Applying information theoretic measures to neuronal activity data enables the quantification of neuronal encoding quality. However, when the sample size is limited, a naïve estimation of the information content typically contains a systematic overestimation (upward bias), which may lead to misinterpretation of coding characteristics. This bias is exacerbated in Ca2+ imaging because of the temporal sparsity of elevated Ca2+ signals. Here, we introduce methods to correct for the bias in the naïve estimation of information content from limited sample sizes and temporally sparse neuronal activity. We demonstrate the higher accuracy of our methods over previous ones, when applied to Ca2+ imaging data recorded from the mouse hippocampus and primary visual cortex, as well as to simulated data with matching tuning properties and firing statistics. Our bias-correction methods allowed an accurate estimation of the information place cells carry about the animal's position (spatial information) and uncovered the spatial resolution of hippocampal coding. Furthermore, using our methods, we found that cells with higher peak firing rates carry higher spatial information per spike and exposed differences between distinct hippocampal subfields in the long-term evolution of the spatial code. These results could be masked by the bias when applying the commonly used naïve calculation of information content. Thus, a bias-free estimation of information content can uncover otherwise overlooked properties of the neural code.

Consistent population activity on the scale of minutes in the mouse hippocampus.

Neurons in the hippocampus fire in consistent sequence over the timescale of seconds during the delay period of some memory experiments. For longer timescales, the firing of hippocampal neurons also changes slowly over minutes within experimental sessions. It was thought that these slow dynamics are caused by stochastic drift or a continuous change in the representation of the episode, rather than consistent sequences unfolding over minutes. This paper studies the consistency of contextual drift in three chronic calcium imaging recordings from the hippocampus CA1 region in mice. Computational measures of consistency show reliable sequences within experimental trials at the scale of seconds as one would expect from time cells or place cells during the trial, as well as across experimental trials on the scale of minutes within a recording session. Consistent sequences in the hippocampus are observed over a wide range of time scales, from seconds to minutes. The hippocampal activity could reflect a scale-invariant spatiotemporal context as suggested by theories of memory from cognitive psychology.

Representational drift in the mouse visual cortex.

Recent studies have shown that neuronal representations gradually change over time despite no changes in the stimulus, environment, or behavior. However, such representational drift has been assumed to be a property of high-level brain structures, whereas earlier circuits, such as sensory cortices, have been assumed to stably encode information over time. Here, we analyzed large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. Contrary to the prevailing notion, we found representational drift over timescales spanning minutes to days across multiple visual areas, cortical layers, and cell types. Notably, neural-code stability did not reflect the hierarchy of information flow across areas. Although individual neurons showed time-dependent changes in their coding properties, the structure of the relationships between population activity patterns remained stable and stereotypic. Such population-level organization may underlie stable visual perception despite continuous changes in neuronal responses.

Multiple Maps of the Same Spatial Context Can Stably Coexist in the Mouse Hippocampus.

Hippocampal place cells selectively fire when an animal traverses a particular location and are considered a neural substrate of spatial memory. Place cells were shown to change their activity patterns (remap) across different spatial contexts but to maintain their spatial tuning in a fixed familiar context. Here, we show that mouse hippocampal neurons can globally remap, forming multiple distinct representations (maps) of the same familiar environment, without any apparent changes in sensory input or behavior. Alternations between maps occurred only across separate visits to the environment, implying switching between distinct stable attractors in the hippocampal network. Importantly, the different maps were spatially informative and persistent over weeks, demonstrating that they can be reliably stored and retrieved from long-term memory. Taken together, our results suggest that a memory of a given spatial context could be associated with multiple distinct neuronal representations, rather than just one.

Revealing neural correlates of behavior without behavioral measurements.

Measuring neuronal tuning curves has been instrumental for many discoveries in neuroscience but requires a priori assumptions regarding the identity of the encoded variables. We applied unsupervised learning to large-scale neuronal recordings in behaving mice from circuits involved in spatial cognition and uncovered a highly-organized internal structure of ensemble activity patterns. This emergent structure allowed defining for each neuron an 'internal tuning-curve' that characterizes its activity relative to the network activity, rather than relative to any predefined external variable, revealing place-tuning and head-direction tuning without relying on measurements of place or head-direction. Similar investigation in prefrontal cortex revealed schematic representations of distances and actions, and exposed a previously unknown variable, the 'trajectory-phase'. The internal structure was conserved across mice, allowing using one animal's data to decode another animal's behavior. Thus, the internal structure of neuronal activity itself enables reconstructing internal representations and discovering new behavioral variables hidden within a neural code.

Nonoscillatory Phase Coding and Synchronization in the Bat Hippocampal Formation.

Hippocampal theta oscillations were proposed to be important for multiple functions, including memory and temporal coding of position. However, previous findings from bats have questioned these proposals by reporting absence of theta rhythmicity in bat hippocampal formation. Does this mean that temporal coding is unique to rodent hippocampus and does not generalize to other species? Here, we report that, surprisingly, bat hippocampal neurons do exhibit temporal coding similar to rodents, albeit without any continuous oscillations at the 1-20 Hz range. Bat neurons exhibited very strong locking to the non-rhythmic fluctuations of the field potential, such that neurons were synchronized together despite the absence of oscillations. Further, some neurons exhibited "phase precession" and phase coding of the bat's position-with spike phases shifting earlier as the animal moved through the place field. This demonstrates an unexpected type of neural coding in the mammalian brain-nonoscillatory phase coding-and highlights the importance of synchrony and temporal coding for hippocampal function across species.

Tracking the Same Neurons across Multiple Days in Ca2+ Imaging Data.

Ca2+ imaging techniques permit time-lapse recordings of neuronal activity from large populations over weeks. However, without identifying the same neurons across imaging sessions (cell registration), longitudinal analysis of the neural code is restricted to population-level statistics. Accurate cell registration becomes challenging with increased numbers of cells, sessions, and inter-session intervals. Current cell registration practices, whether manual or automatic, do not quantitatively evaluate registration accuracy, possibly leading to data misinterpretation. We developed a probabilistic method that automatically registers cells across multiple sessions and estimates the registration confidence for each registered cell. Using large-scale Ca2+ imaging data recorded over weeks from the hippocampus and cortex of freely behaving mice, we show that our method performs more accurate registration than previously used routines, yielding estimated error rates <5%, and that the registration is scalable for many sessions. Thus, our method allows reliable longitudinal analysis of the same neurons over long time periods.

Hippocampal ensemble dynamics timestamp events in long-term memory.

The capacity to remember temporal relationships between different events is essential to episodic memory, but little is currently known about its underlying mechanisms. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of episodic representations, despite stable place field locations and constant remapping between the two environments. These dynamics time-stamped experienced events via neuronal ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred. Temporally remote episodes had distinct timestamps, even if they occurred within the same spatial context. Our results suggest that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance.

Three-dimensional head-direction coding in the bat brain.

Navigation requires a sense of direction ('compass'), which in mammals is thought to be provided by head-direction cells, neurons that discharge when the animal's head points to a specific azimuth. However, it remains unclear whether a three-dimensional (3D) compass exists in the brain. Here we conducted neural recordings in bats, mammals well-adapted to 3D spatial behaviours, and found head-direction cells tuned to azimuth, pitch or roll, or to conjunctive combinations of 3D angles, in both crawling and flying bats. Head-direction cells were organized along a functional-anatomical gradient in the presubiculum, transitioning from 2D to 3D representations. In inverted bats, the azimuth-tuning of neurons shifted by 180°, suggesting that 3D head direction is represented in azimuth × pitch toroidal coordinates. Consistent with our toroidal model, pitch-cell tuning was unimodal, circular, and continuous within the available 360° of pitch. Taken together, these results demonstrate a 3D head-direction mechanism in mammals, which could support navigation in 3D space.

Encoding of head direction by hippocampal place cells in bats.

Most theories of navigation rely on the concept of a mental map and compass. Hippocampal place cells are neurons thought to be important for representing the mental map; these neurons become active when the animal traverses a specific location in the environment (the "place field"). Head-direction cells are found outside the hippocampus, and encode the animal's head orientation, thus implementing a neural compass. The prevailing view is that the activity of head-direction cells is not tuned to a single place, while place cells do not encode head direction. However, little work has been done to investigate in detail the possible head-directional tuning of hippocampal place cells across species. Here we addressed this by recording the activity of single neurons in the hippocampus of two evolutionarily distant bat species, Egyptian fruit bat and big brown bat, which crawled randomly in three different open-field arenas. We found that a large fraction of hippocampal neurons, in both bat species, showed conjunctive sensitivity to the animal's spatial position (place field) and to its head direction. We introduced analytical methods to demonstrate that the head-direction tuning was significant even after controlling for the behavioral coupling between position and head direction. Surprisingly, some hippocampal neurons preserved their head direction tuning even outside the neuron's place field, suggesting that "spontaneous" extra-field spikes are not noise, but in fact carry head-direction information. Overall, these findings suggest that bat hippocampal neurons can convey both map information and compass information.

Scaling laws of associative memory retrieval.

Most people have great difficulty in recalling unrelated items. For example, in free recall experiments, lists of more than a few randomly selected words cannot be accurately repeated. Here we introduce a phenomenological model of memory retrieval inspired by theories of neuronal population coding of information. The model predicts nontrivial scaling behaviors for the mean and standard deviation of the number of recalled words for lists of increasing length. Our results suggest that associative information retrieval is a dominating factor that limits the number of recalled items.