A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal was to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software is released as open source to enable broad community reuse and encourage novel applications.

Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories.

Spatial periodicity in grid cell firing has been interpreted as a neural metric for space providing animals with a coordinate system in navigating physical and mental spaces. However, the specific computational problem being solved by grid cells has remained elusive. Here, we provide mathematical proof that spatial periodicity in grid cell firing is the only possible solution to a neural sequence code of 2-D trajectories and that the hexagonal firing pattern of grid cells is the most parsimonious solution to such a sequence code. We thereby provide a teleological cause for the existence of grid cells and reveal the underlying nature of the global geometric organization in grid maps as a direct consequence of a simple local sequence code. A sequence code by grid cells provides intuitive explanations for many previously puzzling experimental observations and may transform our thinking about grid cells.

Temporal dynamics of cholinergic activity in the septo-hippocampal system.

Cholinergic projection neurons in the medial septum and diagonal band of Broca are the major source of cholinergic modulation of hippocampal circuit functions that support neural coding of location and running speed. Changes in cholinergic modulation are known to correlate with changes in brain states, cognitive functions, and behavior. However, whether cholinergic modulation can change fast enough to serve as a potential speed signal in hippocampal and parahippocampal cortices and whether the temporal dynamics in such a signal depend on the presence of visual cues remain unknown. In this study, we use a fiber-photometric approach to quantify the temporal dynamics of cholinergic activity in freely moving mice as a function of the animal's movement speed and visual cues. We show that the population activity of cholinergic neurons in the medial septum and diagonal band of Broca changes fast enough to be aligned well with changes in the animal's running speed and is strongly and linearly correlated to the logarithm of the animal's running speed. Intriguingly, the cholinergic modulation remains strongly and linearly correlated to the speed of the animal's neck movements during periods of stationary activity. Furthermore, we show that cholinergic modulation is unaltered during darkness. Lastly, we identify rearing, a stereotypic behavior where the mouse stands on its hindlimbs to scan the environment from an elevated perspective, is associated with higher cholinergic activity than expected from neck movements on the horizontal plane alone. Taken together, these data show that temporal dynamics in the cholinergic modulation of hippocampal circuits are fast enough to provide a potential running speed signal in real-time. Moreover, the data show that cholinergic modulation is primarily a function of the logarithm of the animal's movement speed, both during locomotion and during stationary activity, with no significant interaction with visual inputs. These data advance our understanding of temporal dynamics in cholinergic modulation of hippocampal circuits and their functions in the context of neural coding of location and running speed.

The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation.

The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.

Neurophysiological coding of space and time in the hippocampus, entorhinal cortex, and retrosplenial cortex.

Neurophysiological recordings in behaving rodents demonstrate neuronal response properties that may code space and time for episodic memory and goal-directed behaviour. Here, we review recordings from hippocampus, entorhinal cortex, and retrosplenial cortex to address the problem of how neurons encode multiple overlapping spatiotemporal trajectories and disambiguate these for accurate memory-guided behaviour. The solution could involve neurons in the entorhinal cortex and hippocampus that show mixed selectivity, coding both time and location. Some grid cells and place cells that code space also respond selectively as time cells, allowing differentiation of time intervals when a rat runs in the same location during a delay period. Cells in these regions also develop new representations that differentially code the context of prior or future behaviour allowing disambiguation of overlapping trajectories. Spiking activity is also modulated by running speed and head direction, supporting the coding of episodic memory not as a series of snapshots but as a trajectory that can also be distinguished on the basis of speed and direction. Recent data also address the mechanisms by which sensory input could distinguish different spatial locations. Changes in firing rate reflect running speed on long but not short time intervals, and few cells code movement direction, arguing against path integration for coding location. Instead, new evidence for neural coding of environmental boundaries in egocentric coordinates fits with a modelling framework in which egocentric coding of barriers combined with head direction generates distinct allocentric coding of location. The egocentric input can be used both for coding the location of spatiotemporal trajectories and for retrieving specific viewpoints of the environment. Overall, these different patterns of neural activity can be used for encoding and disambiguation of prior episodic spatiotemporal trajectories or for planning of future goal-directed spatiotemporal trajectories.

Effects of visual inputs on neural dynamics for coding of location and running speed in medial entorhinal cortex.

Neuronal representations of spatial location and movement speed in the medial entorhinal cortex during the 'active' theta state of the brain are important for memory-guided navigation and rely on visual inputs. However, little is known about how visual inputs change neural dynamics as a function of running speed and time. By manipulating visual inputs in mice, we demonstrate that changes in spatial stability of grid cell firing correlate with changes in a proposed speed signal by local field potential theta frequency. In contrast, visual inputs do not alter the running speed-dependent gain in neuronal firing rates. Moreover, we provide evidence that sensory inputs other than visual inputs can support grid cell firing, though less accurately, in complete darkness. Finally, changes in spatial accuracy of grid cell firing on a 10 s time scale suggest that grid cell firing is a function of velocity signals integrated over past time.

Overview of computational models of hippocampus and related structures: Introduction to the special issue.

Extensive computational modeling has focused on the hippocampal formation and associated cortical structures. This overview describes some of the factors that have motivated the strong focus on these structures, including major experimental findings and their impact on computational models. This overview provides a framework for describing the topics addressed by individual articles in this special issue of the journal Hippocampus.

The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition.

Behavioral research in human verbal memory function led to the initial definition of episodic memory and semantic memory. A complete model of the neural mechanisms of episodic memory must include the capacity to encode and mentally reconstruct everything that humans can recall from their experience. This article proposes new model features necessary to address the complexity of episodic memory encoding and recall in the context of broader cognition and the functional properties of neurons that could contribute to this broader scope of memory. Many episodic memory models represent individual snapshots of the world with a sequence of vectors, but a full model must represent complex functions encoding and retrieving the relations between multiple stimulus features across space and time on multiple hierarchical scales. Episodic memory involves not only the space and time of an agent experiencing events within an episode but also features shown in neurophysiological data such as coding of speed, direction, boundaries, and objects. Episodic memory includes not only a spatio-temporal trajectory of a single agent but also segments of spatio-temporal trajectories for other agents and objects encountered in the environment consistent with data on encoding the position and angle of sensory features of objects and boundaries. We will discuss potential interactions of episodic memory circuits in the hippocampus and entorhinal cortex with distributed neocortical circuits that must represent all features of human cognition.

The Firing Rate Speed Code of Entorhinal Speed Cells Differs across Behaviorally Relevant Time Scales and Does Not Depend on Medial Septum Inputs.

The firing rate of speed cells, a dedicated subpopulation of neurons in the medial entorhinal cortex (MEC), is correlated with running speed. This correlation has been interpreted as a speed code used in various computational models for path integration. These models consider firing rate to be linearly tuned by running speed in real-time. However, estimation of firing rates requires integration of spiking events over time, setting constraints on the temporal accuracy of the proposed speed code. We therefore tested whether the proposed speed code by firing rate is accurate at short time scales using data obtained from open-field recordings in male rats and mice. We applied a novel filtering approach differentiating between speed codes at multiple time scales ranging from deciseconds to minutes. In addition, we determined the optimal integration time window for firing-rate estimation using a general likelihood framework and calculated the integration time window that maximizes the correlation between firing rate and running speed. Data show that these time windows are on the order of seconds, setting constraints on real-time speed coding by firing rate. We further show that optogenetic inhibition of either cholinergic, GABAergic, or glutamatergic neurons in the medial septum/diagonal band of Broca does not affect modulation of firing rates by running speed at each time scale tested. These results are relevant for models of path integration and for our understanding of how behavioral activity states may modulate firing rates and likely information processing in the MEC.SIGNIFICANCE STATEMENT Path integration is the most basic form of navigation relying on self-motion cues. Models of path integration use medial septum/diagonal band of Broca (MSDB)-dependent MEC grid-cell firing patterns as the neurophysiological substrate of path integration. These models use a linear speed code by firing rate, but do not consider temporal constraints of integration over time for firing-rate estimation. We show that firing-rate estimation for speed cells requires integration over seconds. Using optogenetics, we show that modulation of firing rates by running speed is independent of MSDB inputs. These results enhance our understanding of path integration mechanisms and the role of the MSDB for information processing in the MEC.

Specific Basal Forebrain-Cortical Cholinergic Circuits Coordinate Cognitive Operations.

Based on recent molecular genetics, as well as functional and quantitative anatomical studies, the basal forebrain (BF) cholinergic projections, once viewed as a diffuse system, are emerging as being remarkably specific in connectivity. Acetylcholine (ACh) can rapidly and selectively modulate activity of specific circuits and ACh release can be coordinated in multiple areas that are related to particular aspects of cognitive processing. This review discusses how a combination of multiple new approaches with more established techniques are being used to finally reveal how cholinergic neurons, together with other BF neurons, provide temporal structure for behavior, contribute to local cortical state regulation, and coordinate activity between different functionally related cortical circuits. ACh selectively modulates dynamics for encoding and attention within individual cortical circuits, allows for important transitions during sleep, and shapes the fidelity of sensory processing by changing the correlation structure of neural firing. The importance of this system for integrated and fluid behavioral function is underscored by its disease-modifying role; the demise of BF cholinergic neurons has long been established in Alzheimer's disease and recent studies have revealed the involvement of the cholinergic system in modulation of anxiety-related circuits. Therefore, the BF cholinergic system plays a pivotal role in modulating the dynamics of the brain during sleep and behavior, as foretold by the intricacies of its anatomical map.

Neural mechanisms of navigation involving interactions of cortical and subcortical structures.

Animals must perform spatial navigation for a range of different behaviors, including selection of trajectories toward goal locations and foraging for food sources. To serve this function, a number of different brain regions play a role in coding different dimensions of sensory input important for spatial behavior, including the entorhinal cortex, the retrosplenial cortex, the hippocampus, and the medial septum. This article will review data concerning the coding of the spatial aspects of animal behavior, including location of the animal within an environment, the speed of movement, the trajectory of movement, the direction of the head in the environment, and the position of barriers and objects both relative to the animal's head direction (egocentric) and relative to the layout of the environment (allocentric). The mechanisms for coding these important spatial representations are not yet fully understood but could involve mechanisms including integration of self-motion information or coding of location based on the angle of sensory features in the environment. We will review available data and theories about the mechanisms for coding of spatial representations. The computation of different aspects of spatial representation from available sensory input requires complex cortical processing mechanisms for transformation from egocentric to allocentric coordinates that will only be understood through a combination of neurophysiological studies and computational modeling.

Models of spatial and temporal dimensions of memory.

Episodic memory involves coding of the spatial location and time of individual events. Coding of space and time is also relevant to working memory, spatial navigation, and the disambiguation of overlapping memory representations. Neurophysiological data demonstrate that neuronal activity codes the current, past and future location of an animal as well as temporal intervals within a task. Models have addressed how neural coding of space and time for memory function could arise, with both dimensions coded by the same neurons. Neural coding could depend upon network oscillatory and attractor dynamics as well as modulation of neuronal intrinsic properties. These models are relevant to the coding of space and time involving structures including the hippocampus, entorhinal cortex, retrosplenial cortex, striatum and parahippocampal gyrus, which have been implicated in both animal and human studies.

Modulation of Hippocampal Circuits by Muscarinic and Nicotinic Receptors.

This article provides a review of the effects of activation of muscarinic and nicotinic receptors on the physiological properties of circuits in the hippocampal formation. Previous articles have described detailed computational hypotheses about the role of cholinergic neuromodulation in enhancing the dynamics for encoding in cortical structures and the role of reduced cholinergic modulation in allowing consolidation of previously encoded information. This article will focus on addressing the broad scope of different modulatory effects observed within hippocampal circuits, highlighting the heterogeneity of cholinergic modulation in terms of the physiological effects of activation of muscarinic and nicotinic receptors and the heterogeneity of effects on different subclasses of neurons.

Potential roles of cholinergic modulation in the neural coding of location and movement speed.

Behavioral data suggest that cholinergic modulation may play a role in certain aspects of spatial memory, and neurophysiological data demonstrate neurons that fire in response to spatial dimensions, including grid cells and place cells that respond on the basis of location and running speed. These neurons show firing responses that depend upon the visual configuration of the environment, due to coding in visually-responsive regions of the neocortex. This review focuses on the physiological effects of acetylcholine that may influence the sensory coding of spatial dimensions relevant to behavior. In particular, the local circuit effects of acetylcholine within the cortex regulate the influence of sensory input relative to internal memory representations via presynaptic inhibition of excitatory and inhibitory synaptic transmission, and the modulation of intrinsic currents in cortical excitatory and inhibitory neurons. In addition, circuit effects of acetylcholine regulate the dynamics of cortical circuits including oscillations at theta and gamma frequencies. These effects of acetylcholine on local circuits and network dynamics could underlie the role of acetylcholine in coding of spatial information for the performance of spatial memory tasks.

Astrocyte Intermediaries of Septal Cholinergic Modulation in the Hippocampus.

The neurotransmitter acetylcholine, derived from the medial septum/diagonal band of Broca complex, has been accorded an important role in hippocampal learning and memory processes. However, the precise mechanisms whereby acetylcholine released from septohippocampal cholinergic neurons acts to modulate hippocampal microcircuits remain unknown. Here, we show that acetylcholine release from cholinergic septohippocampal projections causes a long-lasting GABAergic inhibition of hippocampal dentate granule cells in vivo and in vitro. This inhibition is caused by cholinergic activation of hilar astrocytes, which provide glutamatergic excitation of hilar inhibitory interneurons. These results demonstrate that acetylcholine release can cause slow inhibition of principal neuronal activity via astrocyte intermediaries.

Synergy of direct and indirect cholinergic septo-hippocampal pathways coordinates firing in hippocampal networks.

The medial septum/diagonal band of Broca complex (MSDB) is a key structure that modulates hippocampal rhythmogenesis. Cholinergic neurons of the MSDB play a central role in generating and pacing theta-band oscillations in the hippocampal formation during exploration, novelty detection, and memory encoding. How precisely cholinergic neurons affect hippocampal network dynamics in vivo, however, has remained elusive. In this study, we show that stimulation of cholinergic MSDB neurons in urethane-anesthetized mice acts on hippocampal networks via two distinct pathways. A direct septo-hippocampal cholinergic projection causes increased firing of hippocampal inhibitory interneurons with concomitantly decreased firing of principal cells. In addition, cholinergic neurons recruit noncholinergic neurons within the MSDB. This indirect pathway is required for hippocampal theta synchronization. Activation of both pathways causes a reduction in pyramidal neuron firing and a more precise coupling to the theta oscillatory phase. These two anatomically and functionally distinct pathways are likely relevant for cholinergic control of encoding versus retrieval modes in the hippocampus.

Signal regulatory protein-beta1: a microglial modulator of phagocytosis in Alzheimer's disease.

The signal regulatory protein-beta1 (SIRPbeta1) is a DAP12-associated transmembrane receptor expressed in a subset of hematopoietic cells. Recently, it was shown that peritoneal macrophages express SIRPbeta1, which positively regulated phagocytosis. Here, we found that SIRPbeta1 was up-regulated and acted as a phagocytic receptor on microglia in amyloid precursor protein J20 (APP/J20) transgenic mice and in Alzheimer's disease (AD) patients. Interferon (IFN)-gamma and IFN-beta stimulated gene transcription of SIRPbeta1 in cultured microglia. Activation of SIRPbeta1 on cultured microglia by cross-linking antibodies induced reorganization of the cytoskeleton protein beta-actin and suppressed lipopolysaccharide-induced gene transcription of tumor necrosis factor-alpha and nitric oxide synthase-2. Furthermore, activation of SIRPbeta1 increased phagocytosis of microsphere beads, neural debris, and fibrillary amyloid-beta (Abeta). Phagocytosis of neural cell debris and Abeta was impaired after lentiviral knockdown of SIRPbeta1 in primary microglial cells. Thus, SIRPbeta1 is a novel IFN-induced microglial receptor that supports clearance of neural debris and Abeta aggregates by stimulating phagocytosis.