Minute-scale oscillatory sequences in medial entorhinal cortex.

The medial entorhinal cortex (MEC) hosts many of the brain's circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. Whereas location is known to be encoded by spatially tuned cell types in this brain region2,3, little is known about how the activity of entorhinal cells is tied together over time at behaviourally relevant time scales, in the second-to-minute regime. Here we show that MEC neuronal activity has the capacity to be organized into ultraslow oscillations, with periods ranging from tens of seconds to minutes. During these oscillations, the activity is further organized into periodic sequences. Oscillatory sequences manifested while mice ran at free pace on a rotating wheel in darkness, with no change in location or running direction and no scheduled rewards. The sequences involved nearly the entire cell population, and transcended epochs of immobility. Similar sequences were not observed in neighbouring parasubiculum or in visual cortex. Ultraslow oscillatory sequences in MEC may have the potential to couple neurons and circuits across extended time scales and serve as a template for new sequence formation during navigation and episodic memory formation.

Protracted neuronal recruitment in the temporal lobes of young children.

The temporal lobe of the human brain contains the entorhinal cortex (EC). This region of the brain is a highly interconnected integrative hub for sensory and spatial information; it also has a key role in episodic memory formation and is the main source of cortical hippocampal inputs1-4. The human EC continues to develop during childhood5, but neurogenesis and neuronal migration to the EC are widely considered to be complete by birth. Here we show that the human temporal lobe contains many young neurons migrating into the postnatal EC and adjacent regions, with a large tangential stream persisting until the age of around one year and radial dispersal continuing until around two to three years of age. By contrast, we found no equivalent postnatal migration in rhesus macaques (Macaca mulatta). Immunostaining and single-nucleus RNA sequencing of ganglionic eminence germinal zones, the EC stream and the postnatal EC revealed that most migrating cells in the EC stream are derived from the caudal ganglionic eminence and become LAMP5+RELN+ inhibitory interneurons. These late-arriving interneurons could continue to shape the processing of sensory and spatial information well into postnatal life, when children are actively interacting with their environment. The EC is one of the first regions of the brain to be affected in Alzheimer's disease, and previous work has linked cognitive decline to the loss of LAMP5+RELN+ cells6,7. Our investigation reveals that many of these cells arrive in the EC through a major postnatal migratory stream in early childhood.

Prefrontal feature representations drive memory recall.

Memory formation involves binding of contextual features into a unitary representation1-4, whereas memory recall can occur using partial combinations of these contextual features. The neural basis underlying the relationship between a contextual memory and its constituent features is not well understood; in particular, where features are represented in the brain and how they drive recall. Here, to gain insight into this question, we developed a behavioural task in which mice use features to recall an associated contextual memory. We performed longitudinal imaging in hippocampus as mice performed this task and identified robust representations of global context but not of individual features. To identify putative brain regions that provide feature inputs to hippocampus, we inhibited cortical afferents while imaging hippocampus during behaviour. We found that whereas inhibition of entorhinal cortex led to broad silencing of hippocampus, inhibition of prefrontal anterior cingulate led to a highly specific silencing of context neurons and deficits in feature-based recall. We next developed a preparation for simultaneous imaging of anterior cingulate and hippocampus during behaviour, which revealed robust population-level representation of features in anterior cingulate, that lag hippocampus context representations during training but dynamically reorganize to lead and target recruitment of context ensembles in hippocampus during recall. Together, we provide the first mechanistic insights into where contextual features are represented in the brain, how they emerge, and how they access long-range episodic representations to drive memory recall.

Toroidal topology of population activity in grid cells.

The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment1. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations2, and are organized in modules3 that collectively form a population code for the animal's allocentric position1. The invariance of the correlation structure of this population code across environments4,5 and behavioural states6,7, independent of specific sensory inputs, has pointed to intrinsic, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern1,8-11. However, whether grid cell networks show continuous attractor dynamics, and how they interface with inputs from the environment, has remained unclear owing to the small samples of cells obtained so far. Here, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold, as expected in a two-dimensional CAN. Positions on the torus correspond to positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep, as predicted by CAN models for grid cells but not by alternative feedforward models12. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.

Estradiol Regulates Polysialylated Form of the Neural Cell Adhesion Molecule Expression and Connectivity of O-LM Interneurons in the Hippocampus of Adult Female Mice.

The estrous cycle is caused by the changing concentration of ovarian hormones, particularly 17ß-estradiol, a hormone whose effect on excitatory circuits has been extensively reported. However, fewer studies have tried to elucidate how this cycle, or this hormone, affects the plasticity of inhibitory networks and the structure of interneurons. Among these cells, somatostatin-expressing O-LM neurons of the hippocampus are especially interesting. They have a role in the modulation of theta oscillations, and they receive direct input from the entorhinal cortex, which place them in the center of hippocampal function. In this study, we report that the expression of polysialylated form of the neural cell adhesion molecule (PSA-NCAM) in the hippocampus, a molecule involved in the plasticity of somatostatin-expressing interneurons in the adult brain, fluctuated through the different stages of the estrous cycle. Likewise, these stages and the expression of PSA-NCAM affected the density of dendritic spines of O-LM cells. We also describe that 17ß-estradiol replacement of adult ovariectomized female mice caused an increase in the perisomatic inhibitory puncta in O-LM interneurons as well as an increase in their axonal bouton density. Interestingly, this treatment also induced a decrease in their dendritic spine density, specifically in O-LM interneurons lacking PSA-NCAM expression. Finally, using an ex vivo real-time assay with entorhinal-hippocampal organotypic cultures, we show that this hormone decreased the dynamics in spinogenesis, altogether highlighting the modulatory effect that 17ß-estradiol has on inhibitory circuits.

Dentate gyrus and CA3 GABAergic interneurons bidirectionally modulate signatures of internal and external drive to CA1.

Specific classes of GABAergic neurons play specific roles in regulating information processing in the brain. In the hippocampus, two major classes, parvalbumin-expressing (PV+) and somatostatin-expressing (SST+), differentially regulate endogenous firing patterns and target subcellular compartments of principal cells. How these classes regulate the flow of information throughout the hippocampus is poorly understood. We hypothesize that PV+ and SST+ interneurons in the dentate gyrus (DG) and CA3 differentially modulate CA3 patterns of output, thereby altering the influence of CA3 on CA1. We find that while suppressing either interneuron class increases DG and CA3 output, the effects on CA1 were very different. Suppressing PV+ interneurons increases local field potential signatures of coupling from CA3 to CA1 and decreases signatures of coupling from entorhinal cortex to CA1; suppressing SST+ interneurons has the opposite effect. Thus, DG and CA3 PV+ and SST+ interneurons bidirectionally modulate the flow of information through the hippocampal circuit.

Cognitive control persistently enhances hippocampal information processing.

Could learning that uses cognitive control to judiciously use relevant information while ignoring distractions generally improve brain function, beyond forming explicit memories? According to a neuroplasticity hypothesis for how some cognitive behavioural therapies are effective, cognitive control training (CCT) changes neural circuit information processing1-3. Here we investigated whether CCT persistently alters hippocampal neural circuit function. We show that mice learned and remembered a conditioned place avoidance during CCT that required ignoring irrelevant locations of shock. CCT facilitated learning new tasks in novel environments for several weeks, relative to unconditioned controls and control mice that avoided the same place during reduced distraction. CCT rapidly changes entorhinal cortex-to-dentate gyrus synaptic circuit function, resulting in an excitatory-inhibitory subcircuit change that persists for months. CCT increases inhibition that attenuates the dentate response to medial entorhinal cortical input, and through disinhibition, potentiates the response to strong inputs, pointing to overall signal-to-noise enhancement. These neurobiological findings support the neuroplasticity hypothesis that, as well as storing item-event associations, CCT persistently optimizes neural circuit information processing.

The hippocampus converts dynamic entorhinal inputs into stable spatial maps.

The medial entorhinal cortex (MEC)-hippocampal network plays a key role in the processing, storage, and recall of spatial information. However, how the spatial code provided by MEC inputs relates to spatial representations generated by principal cell assemblies within hippocampal subfields remains enigmatic. To investigate this coding relationship, we employed two-photon calcium imaging in mice navigating through dissimilar virtual environments. Imaging large MEC bouton populations revealed spatially tuned activity patterns. MEC inputs drastically changed their preferred spatial field locations between environments, whereas hippocampal cells showed lower levels of place field reconfiguration. Decoding analysis indicated that higher place field reliability and larger context-dependent activity-rate differences allow low numbers of principal cells, particularly in the DG and CA1, to provide information about location and context more accurately and rapidly than MEC inputs. Thus, conversion of dynamic MEC inputs into stable spatial hippocampal maps may enable fast encoding and efficient recall of spatio-contextual information.

Acetylcholine prioritises direct synaptic inputs from entorhinal cortex to CA1 by differential modulation of feedforward inhibitory circuits.

Acetylcholine release in the hippocampus plays a central role in the formation of new memory representations. An influential but largely untested theory proposes that memory formation requires acetylcholine to enhance responses in CA1 to new sensory information from entorhinal cortex whilst depressing inputs from previously encoded representations in CA3. Here, we show that excitatory inputs from entorhinal cortex and CA3 are depressed equally by synaptic release of acetylcholine in CA1. However, feedforward inhibition from entorhinal cortex exhibits greater depression than CA3 resulting in a selective enhancement of excitatory-inhibitory balance and CA1 activation by entorhinal inputs. Entorhinal and CA3 pathways engage different feedforward interneuron subpopulations and cholinergic modulation of presynaptic function is mediated differentially by muscarinic M3 and M4 receptors, respectively. Thus, our data support a role and mechanisms for acetylcholine to prioritise novel information inputs to CA1 during memory formation.

Dopamine facilitates associative memory encoding in the entorhinal cortex.

Mounting evidence shows that dopamine in the striatum is critically involved in reward-based reinforcement learning1,2. However, it remains unclear how dopamine reward signals influence the entorhinal-hippocampal circuit, another brain network that is crucial for learning and memory3-5. Here, using cell-type-specific electrophysiological recording6, we show that dopamine signals from the ventral tegmental area and substantia nigra control the encoding of cue-reward association rules in layer 2a fan cells of the lateral entorhinal cortex (LEC). When mice learned novel olfactory cue-reward associations using a pre-learned association rule, spike representations of LEC fan cells grouped newly learned rewarded cues with a pre-learned rewarded cue, but separated them from a pre-learned unrewarded cue. Optogenetic inhibition of fan cells impaired the learning of new associations while sparing the retrieval of pre-learned memory. Using fibre photometry, we found that dopamine sends novelty-induced reward expectation signals to the LEC. Inhibition of LEC dopamine signals disrupted the associative encoding of fan cells and impaired learning performance. These results suggest that LEC fan cells represent a cognitive map of abstract task rules, and that LEC dopamine facilitates the incorporation of new memories into this map.

The grid code for ordered experience.

Entorhinal cortical grid cells fire in a periodic pattern that tiles space, which is suggestive of a spatial coordinate system. However, irregularities in the grid pattern as well as responses of grid cells in contexts other than spatial navigation have presented a challenge to existing models of entorhinal function. In this Perspective, we propose that hippocampal input provides a key informative drive to the grid network in both spatial and non-spatial circumstances, particularly around salient events. We build on previous models in which neural activity propagates through the entorhinal-hippocampal network in time. This temporal contiguity in network activity points to temporal order as a necessary characteristic of representations generated by the hippocampal formation. We advocate that interactions in the entorhinal-hippocampal loop build a topological representation that is rooted in the temporal order of experience. In this way, the structure of grid cell firing supports a learned topology rather than a rigid coordinate frame that is bound to measurements of the physical world.

Locally ordered representation of 3D space in the entorhinal cortex.

As animals navigate on a two-dimensional surface, neurons in the medial entorhinal cortex (MEC) known as grid cells are activated when the animal passes through multiple locations (firing fields) arranged in a hexagonal lattice that tiles the locomotion surface1. However, although our world is three-dimensional, it is unclear how the MEC represents 3D space2. Here we recorded from MEC cells in freely flying bats and identified several classes of spatial neurons, including 3D border cells, 3D head-direction cells, and neurons with multiple 3D firing fields. Many of these multifield neurons were 3D grid cells, whose neighbouring fields were separated by a characteristic distance-forming a local order-but lacked any global lattice arrangement of the fields. Thus, whereas 2D grid cells form a global lattice-characterized by both local and global order-3D grid cells exhibited only local order, creating a locally ordered metric for space. We modelled grid cells as emerging from pairwise interactions between fields, which yielded a hexagonal lattice in 2D and local order in 3D, thereby describing both 2D and 3D grid cells using one unifying model. Together, these data and model illuminate the fundamental differences and similarities between neural codes for 3D and 2D space in the mammalian brain.

Irregular distribution of grid cell firing fields in rats exploring a 3D volumetric space.

We investigated how entorhinal grid cells encode volumetric space. On a horizontal surface, grid cells usually produce multiple, spatially focal, approximately circular firing fields that are evenly sized and spaced to form a regular, close-packed, hexagonal array. This spatial regularity has been suggested to underlie navigational computations. In three dimensions, theoretically the equivalent firing pattern would be a regular, hexagonal close packing of evenly sized spherical fields. In the present study, we report that, in rats foraging in a cubic lattice, grid cells maintained normal temporal firing characteristics and produced spatially stable firing fields. However, although most grid fields were ellipsoid, they were sparser, larger, more variably sized and irregularly arranged, even when only fields abutting the lower surface (equivalent to the floor) were considered. Thus, grid self-organization is shaped by the environment's structure and/or movement affordances, and grids may not need to be regular to support spatial computations.

Amyloid-ß (1-42) peptide induces rapid NMDA receptor-dependent alterations at glutamatergic synapses in the entorhinal cortex.

The hippocampus and entorhinal cortex (EC) accumulate amyloid beta peptides (Aß) that promote neuropathology in Alzheimer's disease, but the early effects of Aß on excitatory synaptic transmission in the EC have not been well characterized. To assess the acute effects of Aß1-42 on glutamatergic synapses, acute brain slices from wildtype rats were exposed to Aß1-42 or control solution for 3 hours, and tissue was analyzed using protein immunoblotting and quantitative PCR. Presynaptically, Aß1-42 induced marked reductions in synaptophysin, synapsin-2a mRNA, and mGluR3 mRNA, and increased both VGluT2 protein and Ca2+-activated channel KCa2.2 mRNA levels. Postsynaptically, Aß1-42 reduced PSD95 and GluN2B protein, and also downregulated GluN2B and GluN2A mRNA, without affecting scaffolding elements SAP97 and PICK1. mGluR5 mRNA was strongly increased, while mGluR1 mRNA was unaffected. Blocking either GluN2A- or GluN2B-containing NMDA receptors did not significantly prevent synaptic changes induced by Aß1-42, but combined blockade did prevent synaptic alterations. These findings demonstrate that Aß1-42 rapidly disrupts glutamatergic transmission in the EC through mechanisms involving concurrent activation of GluN2A- and GluN2B-containing NMDA receptors.

Modeling the grid cell activity on non-horizontal surfaces based on oscillatory interference modulated by gravity.

Internal representation of the space is a fundamental and crucial function of the animal's brain. Grid cells in the medial entorhinal cortex are thought to provide an environment-invariant metric system for the navigation of the animal. Most experimental and theoretical studies have focused on the horizontal planar codes of grid cell, while how this metric coordinate system is configured in the actual three-dimensional space remains unclear. Evidence has implied the spatial cognition may not be fully volumetric. We proposed an oscillatory interference model with a novel gravity and body plane modulation to simulate grid cell activity in complex space for rodents. The animal can perceive the rotation of its body plane along the local surface by sensing the gravity, causing the modulation to the dendritic oscillations. The results not only reproduce the firing patterns of the grid cell recorded from known experiments, but also predict the grid codes in novel environments. It further demonstrates that the gravity signal is indispensable for the animal's navigation, and supports the hypothesis that the periodic firing of the grid cell is intrinsically not a volumetric code in three-dimensional space. This will provide new insights to understand the spatial representation of the actual world in the brain.

Modular Network between Postrhinal Visual Cortex, Amygdala, and Entorhinal Cortex.

The postrhinal area (POR) is a known center for integrating spatial with nonspatial visual information and a possible hub for influencing landmark navigation by affective input from the amygdala. This may involve specific circuits within muscarinic acetylcholine receptor 2 (M2)-positive (M2+) or M2- modules of POR that associate inputs from the thalamus, cortex, and amygdala, and send outputs to the entorhinal cortex. Using anterograde and retrograde labeling with conventional and viral tracers in male and female mice, we found that all higher visual areas of the ventral cortical stream project to the amygdala, while such inputs are absent from primary visual cortex and dorsal stream areas. Unexpectedly for the presumed salt-and-pepper organization of mouse extrastriate cortex, tracing results show that inputs from the dorsal lateral geniculate nucleus and lateral posterior nucleus were spatially clustered in layer 1 (L1) and overlapped with M2+ patches of POR. In contrast, input from the amygdala to L1 of POR terminated in M2- interpatches. Importantly, the amygdalocortical input to M2- interpatches in L1 overlapped preferentially with spatially clustered apical dendrites of POR neurons projecting to amygdala and entorhinal area lateral, medial (ENTm). The results suggest that subnetworks in POR, used to build spatial maps for navigation, do not receive direct thalamocortical M2+ patch-targeting inputs. Instead, they involve local networks of M2- interpatches, which are influenced by affective information from the amygdala and project to ENTm, whose cells respond to visual landmark cues for navigation.SIGNIFICANCE STATEMENT A central purpose of visual object recognition is identifying the salience of objects and approaching or avoiding them. However, it is not currently known how the visual cortex integrates the multiple streams of information, including affective and navigational cues, which are required to accomplish this task. We find that in a higher visual area, the postrhinal cortex, the cortical sheet is divided into interdigitating modules receiving distinct inputs from visual and emotion-related sources. One of these modules is preferentially connected with the amygdala and provides outputs to entorhinal cortex, constituting a processing stream that may assign emotional salience to objects and landmarks for the guidance of goal-directed navigation.

Biomimetic FPGA-based spatial navigation model with grid cells and place cells.

The mammalian spatial navigation system is characterized by an initial divergence of internal representations, with disparate classes of neurons responding to distinct features including location, speed, borders and head direction; an ensuing convergence finally enables navigation and path integration. Here, we report the algorithmic and hardware implementation of biomimetic neural structures encompassing a feed-forward trimodular, multi-layer architecture representing grid-cell, place-cell and decoding modules for navigation. The grid-cell module comprised of neurons that fired in a grid-like pattern, and was built of distinct layers that constituted the dorsoventral span of the medial entorhinal cortex. Each layer was built as an independent continuous attractor network with distinct grid-field spatial scales. The place-cell module comprised of neurons that fired at one or few spatial locations, organized into different clusters based on convergent modular inputs from different grid-cell layers, replicating the gradient in place-field size along the hippocampal dorso-ventral axis. The decoding module, a two-layer neural network that constitutes the convergence of the divergent representations in preceding modules, received inputs from the place-cell module and provided specific coordinates of the navigating object. After vital design optimizations involving all modules, we implemented the tri-modular structure on Zynq Ultrascale+ field-programmable gate array silicon chip, and demonstrated its capacity in precisely estimating the navigational trajectory with minimal overall resource consumption involving a mere 2.92% Look Up Table utilization. Our implementation of a biomimetic, digital spatial navigation system is stable, reliable, reconfigurable, real-time with execution time of about 32 s for 100k input samples (in contrast to 40 minutes on Intel Core i7-7700 CPU with 8 cores clocking at 3.60 GHz) and thus can be deployed for autonomous-robotic navigation without requiring additional sensors.

Two septal-entorhinal GABAergic projections differentially control coding properties of spatially tuned neurons in the medial entorhinal cortex.

Septal parvalbumin-expressing (PV+) and calbindin-expressing (CB+) projections inhibit low-threshold and fast-spiking interneurons, respectively, in the medial entorhinal cortex (MEC). We investigate how the two inputs control neuronal activity in the MEC in freely moving mice. Stimulation of PV+ and CB+ terminals causes disinhibition of spatially tuned MEC neurons, but exerts differential effects on temporal coding and burst firing. Thus, recruitment of PV+ projections disrupts theta-rhythmic firing of MEC neurons, while stimulation of CB+ projections increases burst firing of grid cells and enhances phase precession in a cell-type-specific manner. Inactivation of septal PV+ or CB+ neurons differentially affects context, reference, and working memory. Together, our results reveal how specific connectivity of septal GABAergic projections with MEC interneurons translates into differential modulation of MEC neuronal coding.

Perineuronal nets stabilize the grid cell network.

Grid cells are part of a widespread network which supports navigation and spatial memory. Stable grid patterns appear late in development, in concert with extracellular matrix aggregates termed perineuronal nets (PNNs) that condense around inhibitory neurons. It has been suggested that PNNs stabilize synaptic connections and long-term memories, but their role in the grid cell network remains elusive. We show that removal of PNNs leads to lower inhibitory spiking activity, and reduces grid cells' ability to create stable representations of a novel environment. Furthermore, in animals with disrupted PNNs, exposure to a novel arena corrupted the spatiotemporal relationships within grid cell modules, and the stored representations of a familiar arena. Finally, we show that PNN removal in entorhinal cortex distorted spatial representations in downstream hippocampal neurons. Together this work suggests that PNNs provide a key stabilizing element for the grid cell network.