Spatial coding in the hippocampus and hyperpallium of flying owls.

The elucidation of spatial coding in the hippocampus requires exploring diverse animal species. While robust place-cells are found in the mammalian hippocampus, much less is known about spatial coding in the hippocampus of birds. Here we used a wireless-electrophysiology system to record single neurons in the hippocampus and other two dorsal pallial structures from freely flying barn owls (Tyto alba), a central-place nocturnal predator species with excellent navigational abilities. The owl's 3D position was monitored while it flew between perches. We found place cells-neurons that fired when the owl flew through a spatially restricted region in at least one direction-as well as neurons that encoded the direction of flight, and neurons that represented the owl's perching position between flights. Many neurons encoded combinations of position, direction, and perching. Spatial coding was maintained stable and invariant to lighting conditions. Place cells were observed in owls performing two different types of flying tasks, highlighting the generality of the result. Place coding was found in the anterior hippocampus and in the posterior part of the hyperpallium apicale, and to a lesser extent in the visual Wulst. The finding of place-cells in flying owls suggests commonalities in spatial coding across mammals and birds.

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.

ASCT1 (Slc1a4) transporter is a physiologic regulator of brain d-serine and neurodevelopment.

d-serine is a physiologic coagonist of NMDA receptors, but little is known about the regulation of its synthesis and synaptic turnover. The amino acid exchangers ASCT1 (Slc1a4) and ASCT2 (Slc1a5) are candidates for regulating d-serine levels. Using ASCT1 and ASCT2 KO mice, we report that ASCT1, rather than ASCT2, is a physiologic regulator of d-serine metabolism. ASCT1 is a major d-serine uptake system in astrocytes and can also export l-serine via heteroexchange, supplying neurons with the substrate for d-serine synthesis. ASCT1-KO mice display lower levels of brain d-serine along with higher levels of l-alanine, l-threonine, and glycine. Deletion of ASCT1 was associated with neurodevelopmental alterations including lower hippocampal and striatal volumes and changes in the expression of neurodevelopmental-relevant genes. Furthermore, ASCT1-KO mice exhibited deficits in motor function, spatial learning, and affective behavior, along with changes in the relative contributions of d-serine vs. glycine in mediating NMDA receptor activity. In vivo microdialysis demonstrated lower levels of extracellular d-serine in ASCT1-KO mice, confirming altered d-serine metabolism. These alterations are reminiscent of some of the neurodevelopmental phenotypes exhibited by patients with ASCT1 mutations. ASCT1-KO mice provide a useful model for potential therapeutic interventions aimed at correcting the metabolic impairments in patients with ASCT1 mutations.

Role of the head-direction signal in spatial tasks: when and how does it guide behavior?

Since their discovery, mammalian head-direction (HD) cells have been extensively researched in terms of sensory origins, external cue control, and circuitry. However, the relationship of HD cells to behavior is not yet fully understood. In the current review, we examine the anatomical clues for information flow in the HD circuit and an emerging body of evidence that links neural activity of HD cells and spatial orientation. We hypothesize from results obtained in spatial orientation tasks involving HD cells that when properly aligned with available external cues, the HD signal could be used for guiding rats to a goal location. However, contradictory inputs from separate sensory systems may reduce the influence of the HD signal such that animals are able to switch between this and other systems according to their impact on behavior.

Spatial cognition in a virtual reality home-cage extension for freely moving rodents.

Virtual reality (VR) environments are a powerful tool to investigate brain mechanisms involved in the behavior of animals. With this technique, animals are usually head fixed or secured in a harness, and training for cognitively more complex VR paradigms is time consuming. A VR apparatus allowing free animal movement and the constant operator-independent training of tasks would enable many new applications. Key prospective usages include brain imaging of animal behavior when carrying a miniaturized mobile device such as a fluorescence microscope or an optetrode. Here, we introduce the Servoball, a spherical VR treadmill based on the closed-loop tracking of a freely moving animal and feedback counterrotation of the ball. Furthermore, we present the complete integration of this experimental system with the animals' group home cage, from which single individuals can voluntarily enter through a tunnel with radio-frequency identification (RFID)-automated access control and commence experiments. This automated animal sorter functions as a mechanical replacement of the experimenter. We automatically trained rats using visual or acoustic cues to solve spatial cognitive tasks and recorded spatially modulated entorhinal cells. When electrophysiological extracellular recordings from awake behaving rats were performed, head fixation can dramatically alter results, so that any complex behavior that requires head movement is impossible to achieve. We circumvented this problem with the use of the Servoball in open-field scenarios, as it allows the combination of open-field behavior with the recording of nerve cells, along with all the flexibility that a virtual environment brings. This integrated home cage with a VR arena experimental system permits highly efficient experimentation for complex cognitive experiments.NEW & NOTEWORTHY Virtual reality (VR) environments are a powerful tool for the investigation of brain mechanisms. We introduce the Servoball, a VR treadmill for freely moving rodents. The Servoball is integrated with the animals' group home cage. Single individuals voluntarily enter using automated access control. Training is highly time-efficient, even for cognitively complex VR paradigms.

Coding of object location in the vibrissal thalamocortical system.

In whisking rodents, object location is encoded at the receptor level by a combination of motor and sensory related signals. Recoding of the encoded signals can result in various forms of internal representations. Here, we examined the coding schemes occurring at the first forebrain level that receives inputs necessary for generating such internal representations--the thalamocortical network. Single units were recorded in 8 thalamic and cortical stations in artificially whisking anesthetized rats. Neuronal representations of object location generated across these stations and expressed in response latency and magnitude were classified based on graded and binary coding schemes. Both graded and binary coding schemes occurred across the entire thalamocortical network, with a general tendency of graded-to-binary transformation from thalamus to cortex. Overall, 63% of the neurons of the thalamocortical network coded object position in their firing. Thalamocortical responses exhibited a slow dynamics during which the amount of coded information increased across 4-5 whisking cycles and then stabilized. Taken together, the results indicate that the thalamocortical network contains dynamic mechanisms that can converge over time on multiple coding schemes of object location, schemes which essentially transform temporal coding to rate coding and gradual to labeled-line coding.

Grid cells correlation structure suggests organized feedforward projections into superficial layers of the medial entorhinal cortex.

Navigation requires integration of external and internal inputs to form a representation of location. Part of this integration is considered to be carried out by the grid cells network in the medial entorhinal cortex (MEC). However, the structure of this neural network is unknown. To shed light on this structure, we measured noise correlations between 508 pairs of simultaneous previously recorded grid cells. We differentiated between pure grid and conjunctive cells (pure grid in Layers II, III, and VI vs. conjunctive in Layers III and V--only Layer III was bi-modal), and devised a new method to classify cell pairs as belonging/not-belonging to the same module. We found that pairs from the same module show significantly more correlations than pairs from different modules. The correlations between pure grid cells decreased in strength as their relative spatial phase increased. However, correlations were mostly at 0 time-lag, suggesting that the source of correlations was not only synaptic, but rather resulted mostly from common input. Given our measured correlations, the two functional groups of grid cells (pure vs. conjunctive), and the known disorganized recurrent connections within Layer II, we propose the following model: conjunctive cells in deep layers form an attractor network whose activity is governed by velocity-controlled signals. A second manifold in Layer II receives organized feedforward projections from the deep layers, giving rise to pure grid cells. Numerical simulations indicate that organized projections induce such correlations as we measure in superficial layers. Our results provide new evidence for the functional anatomy of the entorhinal circuit-suggesting that strong phase-organized feedforward projections support grid fields in the superficial layers.

Representational drift as a result of implicit regularization.

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; and (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.

Representational drift as a result of implicit regularization.

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.

The chicken and egg problem of grid cells and place cells.

Place cells and grid cells are major building blocks of the hippocampal cognitive map. The prominent forward model postulates that grid-cell modules are generated by a continuous attractor network; that a velocity signal evoked during locomotion moves entorhinal activity bumps; and that place-cell activity constitutes summation of entorhinal grid-cell modules. Experimental data support the first postulate, but not the latter two. Several families of solutions that depart from these postulates have been put forward. We suggest a modified model (spatial modulation continuous attractor network; SCAN), whereby place cells are generated from spatially selective nongrid cells. Locomotion causes these cells to move the hippocampal activity bump, leading to movement of the entorhinal manifolds. Such inversion accords with the shift of hippocampal thought from navigation to more abstract functions.

Use it or lose it.

Blocking the activity of neurons in a region of the brain involved in memory leads to cell death, which could help explain the spatiotemporal disorientation observed in Alzheimer's disease.

Active experience, not time, determines within-day representational drift in dorsal CA1.

Memories of past events can be recalled long after the event, indicating stability. But new experiences are also integrated into existing memories, indicating plasticity. In the hippocampus, spatial representations are known to remain stable but have also been shown to drift over long periods of time. We hypothesized that experience, more than the passage of time, is the driving force behind representational drift. We compared the within-day stability of place cells' representations in dorsal CA1 of the hippocampus of mice traversing two similar, familiar tracks for different durations. We found that the more time the animals spent actively traversing the environment, the greater the representational drift, regardless of the total elapsed time between visits. Our results suggest that spatial representation is a dynamic process, related to the ongoing experiences within a specific context, and is related to memory update rather than to passive forgetting.

Are grid cells used for navigation? On local metrics, subjective spaces, and black holes.

The symmetric, lattice-like spatial pattern of grid-cell activity is thought to provide a neuronal global metric for space. This view is compatible with grid cells recorded in empty boxes but inconsistent with data from more naturalistic settings. We review evidence arguing against the global-metric notion, including the distortion and disintegration of the grid pattern in complex and three-dimensional environments. We argue that deviations from lattice symmetry are key for understanding grid-cell function. We propose three possible functions for grid cells, which treat real-world grid distortions as a feature rather than a bug. First, grid cells may constitute a local metric for proximal space rather than a global metric for all space. Second, grid cells could form a metric for subjective action-relevant space rather than physical space. Third, distortions may represent salient locations. Finally, we discuss mechanisms that can underlie these functions. These ideas may transform our thinking about grid cells.

Flexible coding of time or distance in hippocampal cells.

Analysis of neuronal activity in the hippocampus of behaving animals has revealed cells acting as 'Time Cells', which exhibit selective spiking patterns at specific time intervals since a triggering event, and 'Distance Cells', which encode the traversal of specific distances. Other neurons exhibit a combination of these features, alongside place selectivity. This study aims to investigate how the task performed by animals during recording sessions influences the formation of these representations. We analyzed data from a treadmill running study conducted by Kraus et al., 2013, in which rats were trained to run at different velocities. The rats were recorded in two trial contexts: a 'fixed time' condition, where the animal ran on the treadmill for a predetermined duration before proceeding, and a 'fixed distance' condition, where the animal ran a specific distance on the treadmill. Our findings indicate that the type of experimental condition significantly influenced the encoding of hippocampal cells. Specifically, distance-encoding cells dominated in fixed-distance experiments, whereas time-encoding cells dominated in fixed-time experiments. These results underscore the flexible coding capabilities of the hippocampus, which are shaped by over-representation of salient variables associated with reward conditions.

Dori Derdikman.

Interview with Dori Derdikman, who studies spatial memory and navigation at the Technion - Israel Institute of Technology.

Hippocampal sub-networks exhibit distinct spatial representation deficits in Alzheimer's disease model mice.

Not much is known about how the dentate gyrus (DG) and hippocampal CA3 networks, critical for memory and spatial processing, malfunction in Alzheimer's disease (AD). While studies of associative memory deficits in AD have focused mainly on behavior, here, we directly measured neurophysiological network dysfunction. We asked what the pattern of deterioration of different networks is during disease progression. We investigated how the associative memory-processing capabilities in different hippocampal subfields are affected by familial AD (fAD) mutations leading to amyloid-ß dyshomeostasis. Specifically, we focused on the DG and CA3, which are known to be involved in pattern completion and separation and are susceptible to pathological alterations in AD. To identify AD-related deficits in neural-ensemble dynamics, we recorded single-unit activity in wild-type (WT) and fAD model mice (APPSwe+PSEN1/ΔE9) in a novel tactile morph task, which utilizes the extremely developed somatosensory modality of mice. As expected from the sub-network regional specialization, we found that tactile changes induced lower rate map correlations in the DG than in CA3 of WT mice. This reflects DG pattern separation and CA3 pattern completion. In contrast, in fAD model mice, we observed pattern separation deficits in the DG and pattern completion deficits in CA3. This demonstration of region-dependent impairments in fAD model mice contributes to understanding of brain networks deterioration during fAD progression. Furthermore, it implies that the deterioration cannot be studied generally throughout the hippocampus but must be researched at a finer resolution of microcircuits. This opens novel systems-level approaches for analyzing AD-related neural network deficits.

Directional tuning in the hippocampal formation of birds.

Birds strongly rely on spatial memory and navigation. Therefore, it is of utmost interest to reveal how space is represented in the avian brain. Here we used tetrodes to record neurons from the hippocampal formation of Japanese quails-a ground-dwelling species-while the quails roamed in an open-field arena. Whereas spatially modulated cells (place cells, grid cells, border cells) were generally not encountered, the firing rate of about 12% of the neurons was unimodally and significantly modulated by the head azimuth-i.e., these were head-direction cells (HD cells). Typically, HD cells were maximally active at one preferred direction and minimally at the opposite null direction, with preferred directions spanning all 360° across the population. The preferred direction was independent of the animal's position and speed and was stable during the recording session. The HD tuning was broader compared to that of HD cells in rodents, and most cells had non-zero baseline firing in all directions. However, similar to findings in rodents, the HD tuning usually rotated with the rotation of a salient visual cue in the arena. Thus, these findings support the existence of an allocentric HD representation in the quail hippocampal formation and provide the first demonstration of HD cells in birds.

Territorial blueprint in the hippocampal system.

As we skillfully navigate through familiar places, neural computations of distances and coordinates escape our attention. However, we perceive clearly the division of space into socially meaningful territories. 'My space' versus 'your space' is a distinction familiar to all of us. Spatial frontiers are social in nature since they regulate individuals' access to utilities in space depending on hierarchy and affiliation. How does the brain integrate spatial geometry with social territory? We propose that the action of oxytocin (OT) in the entorhinal-hippocampal regions supports this process. Grounded on the functional role of the hypothalamic neuropeptide in the hippocampal system, we show how OT-induced plasticity may bias the geometrical coding of place and grid cells to represent social territories.

Parallel thalamic pathways for whisking and touch signals in the rat.

In active sensation, sensory information is acquired via movements of sensory organs; rats move their whiskers repetitively to scan the environment, thus detecting, localizing, and identifying objects. Sensory information, in turn, affects future motor movements. How this motor-sensory-motor functional loop is implemented across anatomical loops of the whisker system is not yet known. While inducing artificial whisking in anesthetized rats, we recorded the activity of individual neurons from three thalamic nuclei of the whisker system, each belonging to a different major afferent pathway: paralemniscal, extralemniscal (a recently discovered pathway), or lemniscal. We found that different sensory signals related to active touch are conveyed separately via the thalamus by these three parallel afferent pathways. The paralemniscal pathway conveys sensor motion (whisking) signals, the extralemniscal conveys contact (touch) signals, and the lemniscal pathway conveys combined whisking-touch signals. This functional segregation of anatomical pathways raises the possibility that different sensory-motor processes, such as those related to motion control, object localization, and object identification, are implemented along different motor-sensory-motor loops.

During hippocampal inactivation, grid cells maintain synchrony, even when the grid pattern is lost.

The grid cell network in the medial entorhinal cortex (MEC) has been subject to thorough testing and analysis, and many theories for their formation have been suggested. To test some of these theories, we re-analyzed data from Bonnevie et al., 2013, in which the hippocampus was inactivated and grid cells were recorded in the rat MEC. We investigated whether the firing associations of grid cells depend on hippocampal inputs. Specifically, we examined temporal and spatial correlations in the firing times of simultaneously recorded grid cells before and during hippocampal inactivation. Our analysis revealed evidence of network coherence in grid cells even in the absence of hippocampal input to the MEC, both in regular grid cells and in those that became head-direction cells after hippocampal inactivation. This favors models, which suggest that phase relations between grid cells in the MEC are dependent on intrinsic connectivity within the MEC.