Temporal pattern separation in hippocampal neurons through multiplexed neural codes

Postnatal hypofunction of N-methyl-D-aspartate receptors alters perforant path synaptic plasticity and filtering and impairs dentate gyrus-mediated spatial discrimination

BACKGROUND AND PURPOSE

Transient hypofunction of the NMDA receptor represents a convergence point for the onset and further development of psychiatric disorders, including schizophrenia. Although the cumulative evidence indicates dysregulation of the hippocampal formation in schizophrenia, the integrity of the synaptic transmission and plasticity conveyed by the somatosensorial inputs to the dentate gyrus, the perforant pathway synapses, have barely been explored in this pathological condition.

EXPERIMENTAL APPROACH

We identified a series of synaptic alterations of the lateral and medial perforant paths in animals postnatally treated with the NMDA antagonist MK-801. This dysregulation suggests decreased cognitive performance, for which the dentate gyrus is critical.

KEY RESULTS

We identified alterations in the synaptic properties of the lateral and medial perforant paths to the dentate gyrus synapses in slices from MK-801-treated animals. Altered glutamate release and decreased synaptic strength precede an impairment in the induction and expression of long-term potentiation (LTP) and CB1 receptor-mediated long-term depression (LTD). Remarkably, by inhibiting the degradation of 2-arachidonoylglycerol (2-AG), an endogenous ligand of the CB1 receptor, we restored the LTD in animals treated with MK-801. Additionally, we showed for the first time, that spatial discrimination, a cognitive task that requires dentate gyrus integrity, is impaired in animals exposed to transient hypofunction of NMDA receptors.

CONCLUSION AND IMPLICATIONS

Dysregulation of glutamatergic transmission and synaptic plasticity from the entorhinal cortex to the dentate gyrus has been demonstrated, which may explain the cellular dysregulations underlying the altered cognitive processing in the dentate gyrus associated with schizophrenia.

Event Integration and Temporal Differentiation: How Hierarchical Knowledge Emerges in Hippocampal Subfields through Learning

Everyday life is composed of events organized by changes in contexts, with each event containing an unfolding sequence of occurrences. A major challenge facing our memory systems is how to integrate sequential occurrences within events while also maintaining their details and avoiding over-integration across different contexts. We asked if and how distinct hippocampal subfields come to hierarchically and, in parallel, represent both event context and subevent occurrences with learning. Female and male human participants viewed sequential events defined as sequences of objects superimposed on shared color frames while undergoing high-resolution fMRI. Importantly, these events were repeated to induce learning. Event segmentation, as indexed by increased reaction times at event boundaries, was observed in all repetitions. Temporal memory decisions were quicker for items from the same event compared to across different events, indicating that events shaped memory. With learning, hippocampal CA3 multivoxel activation patterns clustered to reflect the event context, with more clustering correlated with behavioral facilitation during event transitions. In contrast, in the dentate gyrus (DG), temporally proximal items that belonged to the same event became associated with more differentiated neural patterns. A computational model explained these results by dynamic inhibition in the DG. Additional similarity measures support the notion that CA3 clustered representations reflect shared voxel populations, while DG's distinct item representations reflect different voxel populations. These findings suggest an interplay between temporal differentiation in the DG and attractor dynamics in CA3. They advance our understanding of how knowledge is structured through integration and separation across time and context.

Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus

Pattern separation is a valuable computational function performed by neuronal circuits, such as the dentate gyrus, where dissimilarity between inputs is increased, reducing noise and increasing the storage capacity of downstream networks. Pattern separation is studied from both in vivo experimental and computational perspectives and, a number of different measures (such as orthogonalisation, decorrelation, or spike train distance) have been applied to quantify the process of pattern separation. However, these are known to give conclusions that can differ qualitatively depending on the choice of measure and the parameters used to calculate it. We here demonstrate that arbitrarily increasing sparsity, a noticeable feature of dentate granule cell firing and one that is believed to be key to pattern separation, typically leads to improved classical measures for pattern separation even, inappropriately, up to the point where almost all information about the inputs is lost. Standard measures therefore both cannot differentiate between pattern separation and pattern destruction, and give results that may depend on arbitrary parameter choices. We propose that techniques from information theory, in particular mutual information, transfer entropy, and redundancy, should be applied to penalise the potential for lost information (often due to increased sparsity) that is neglected by existing measures. We compare five commonly-used measures of pattern separation with three novel techniques based on information theory, showing that the latter can be applied in a principled way and provide a robust and reliable measure for comparing the pattern separation performance of different neurons and networks. We demonstrate our new measures on detailed compartmental models of individual dentate granule cells and a dentate microcircuit, and show how structural changes associated with epilepsy affect pattern separation performance. We also demonstrate how our measures of pattern separation can predict pattern completion accuracy. Overall, our measures solve a widely acknowledged problem in assessing the pattern separation of neural circuits such as the dentate gyrus, as well as the cerebellum and mushroom body. Finally we provide a publicly available toolbox allowing for easy analysis of pattern separation in spike train ensembles.

Granule cells perform frequency-dependent pattern separation in a computational model of the dentate gyrus

Mnemonic discrimination (MD) may be dependent on oscillatory perforant path input frequencies to the hippocampus in a "U"-shaped fashion, where some studies show that slow and fast input frequencies support MD, while other studies show that intermediate frequencies disrupt MD. We hypothesize that pattern separation (PS) underlies frequency-dependent MD performance. We aim to study, in a computational model of the hippocampal dentate gyrus (DG), the network and cellular mechanisms governing this putative "U"-shaped PS relationship. We implemented a biophysical model of the DG that produces the hypothesized "U"-shaped input frequency-PS relationship, and its associated oscillatory electrophysiological signatures. We subsequently evaluated the network's PS ability using an adapted spatiotemporal task. We undertook systematic lesion studies to identify the network-level mechanisms driving the "U"-shaped input frequency-PS relationship. A minimal circuit of a single granule cell (GC) stimulated with oscillatory inputs was also used to study potential cellular-level mechanisms. Lesioning synapses onto GCs did not impact the "U"-shaped input frequency-PS relationship. Furthermore, GC inhibition limits PS performance for fast frequency inputs, while enhancing PS for slow frequency inputs. GC interspike interval was found to be input frequency dependent in a "U"-shaped fashion, paralleling frequency-dependent PS observed at the network level. Additionally, GCs showed an attenuated firing response for fast frequency inputs. We conclude that independent of network-level inhibition, GCs may intrinsically be capable of producing a "U"-shaped input frequency-PS relationship. GCs may preferentially decorrelate slow and fast inputs via spike timing reorganization and high frequency filtering.

Early deficits in dentate circuit and behavioral pattern separation after concussive brain injury

Traumatic brain injury leads to cellular and circuit changes in the dentate gyrus, a gateway to hippocampal information processing. Intrinsic granule cell firing properties and strong feedback inhibition in the dentate are proposed as critical to its ability to generate unique representation of similar inputs by a process known as pattern separation. Here we evaluate the impact of brain injury on cellular decorrelation of temporally patterned inputs in slices and behavioral discrimination of spatial locations in vivo one week after concussive lateral fluid percussion injury (FPI) in mice. Despite posttraumatic increases in perforant path evoked excitatory drive to granule cells and enhanced ΔFosB labeling, indicating sustained increase in excitability, the reliability of granule cell spiking was not compromised after FPI. Although granule cells continued to effectively decorrelate output spike trains recorded in response to similar temporally patterned input sets after FPI, their ability to decorrelate highly similar input patterns was reduced. In parallel, encoding of similar spatial locations in a novel object location task that involves the dentate inhibitory circuits was impaired one week after FPI. Injury induced changes in pattern separation were accompanied by loss of somatostatin expressing inhibitory neurons in the hilus. Together, these data suggest that the early posttraumatic changes in the dentate circuit undermine dentate circuit decorrelation of temporal input patterns as well as behavioral discrimination of similar spatial locations, both of which could contribute to deficits in episodic memory.

Phase information is conserved in sparse, synchronous population-rate-codes via phase-to-rate recoding

Neural computation is often traced in terms of either rate- or phase-codes. However, most circuit operations will simultaneously affect information across both coding schemes. It remains unclear how phase and rate coded information is transmitted, in the face of continuous modification at consecutive processing stages. Here, we study this question in the entorhinal cortex (EC)- dentate gyrus (DG)- CA3 system using three distinct computational models. We demonstrate that DG feedback inhibition leverages EC phase information to improve rate-coding, a computation we term phase-to-rate recoding. Our results suggest that it i) supports the conservation of phase information within sparse rate-codes and ii) enhances the efficiency of plasticity in downstream CA3 via increased synchrony. Given the ubiquity of both phase-coding and feedback circuits, our results raise the question whether phase-to-rate recoding is a recurring computational motif, which supports the generation of sparse, synchronous population-rate-codes in areas beyond the DG.

Early Deficits in Dentate Circuit and Behavioral Pattern Separation after Concussive Brain Injury

Traumatic brain injury leads to cellular and circuit changes in the dentate gyrus, a gateway to hippocampal information processing. Intrinsic granule cell firing properties and strong feedback inhibition in the dentate are proposed as critical to its ability to generate unique representation of similar inputs by a process known as pattern separation. Here we evaluate the impact of brain injury on cellular decorrelation of temporally patterned inputs in slices and behavioral discrimination of spatial locations in vivo one week after concussive lateral fluid percussion injury (FPI) in mice. Despite posttraumatic increases in perforant path evoked excitatory drive to granule cells and enhanced ΔFosB labeling, indicating sustained increase in excitability, the reliability of granule cell spiking was not compromised after FPI. Although granule cells continued to effectively decorrelate output spike trains recorded in response to similar temporally patterned input sets after FPI, their ability to decorrelate highly similar input patterns was reduced. In parallel, encoding of similar spatial locations in a novel object location task that involves the dentate inhibitory circuits was impaired one week after FPI. Injury induced changes in pattern separation were accompanied by loss of somatostatin expressing inhibitory neurons in the hilus. Together, these data suggest that the early posttraumatic changes in the dentate circuit undermine dentate circuit decorrelation of temporal input patterns as well as behavioral discrimination of similar spatial locations, both of which could contribute to deficits in episodic memory.

Patterns of Pathology

Deficits in Behavioral and Neuronal Pattern Separation in Temporal Lobe Epilepsy Madar AD, Pfammatter JA, Bordenave J, Plumley EI, Ravi S, Cowie M, Wallace EP, Hermann BP, Maganti RK, Jones MV. J Neurosci . 2021;41(46):9669-9686. doi:10.1523/JNEUROSCI.2439-20.2021 In temporal lobe epilepsy, the ability of the dentate gyrus to limit excitatory cortical input to the hippocampus breaks down, leading to seizures. The dentate gyrus is also thought to help discriminate between similar memories by performing pattern separation, but whether epilepsy leads to a breakdown in this neural computation, and thus to mnemonic discrimination impairments, remains unknown. Here we show that temporal lobe epilepsy is characterized by behavioral deficits in mnemonic discrimination tasks, in both humans (females and males) and mice (C57Bl6 males, systemic low-dose kainate model). Using a recently developed assay in brain slices of the same epileptic mice, we reveal a decreased ability of the dentate gyrus to perform certain forms of pattern separation. This is because of a subset of granule cells with abnormal bursting that can develop independently of early EEG abnormalities. Overall, our results linking physiology, computation, and cognition in the same mice advance our understanding of episodic memory mechanisms and their dysfunction in epilepsy.

Moderate effect of early-life experience on dentate gyrus function

The development, maturation, and plasticity of neural circuits are strongly influenced by experience and the interaction of an individual with their environment can have a long-lasting effect on cognitive function. Using an enriched environment (EE) paradigm, we have recently demonstrated that enhancing social, physical, and sensory activity during the pre-weaning time in mice led to an increase of inhibitory and excitatory synapses in the dentate gyrus (DG) of the hippocampus. The structural plasticity induced by experience may affect information processing in the circuit. The DG performs pattern separation, a computation that enables the encoding of very similar and overlapping inputs into dissimilar outputs. In the presented study, we have tested the hypothesis that an EE in juvenile mice will affect DG's functions that are relevant for pattern separation: the decorrelation of the inputs from the entorhinal cortex (EC) and the recruitment of the principal excitatory granule cell (GC) during behavior. First, using a novel slice electrophysiology protocol, we found that the transformation of the incoming signal from the EC afferents by individual GC is moderately affected by EE. We further show that EE does not affect behaviorally induced recruitment of principal excitatory GC. Lastly, using the novel object recognition task, a hippocampus-dependent memory test, we show that the ontogeny of this discrimination task was similar among the EE mice and the controls. Taken together, our work demonstrates that pre-weaning enrichment moderately affects DG function.

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

Neurogenesis in aging and age-related neurodegenerative diseases

Adult neurogenesis, the process by which neurons are generated in certain areas of the adult brain, declines in an age-dependent manner and is one potential target for extending cognitive healthspan. Aging is a major risk factor for neurodegenerative diseases and, as lifespans are increasing, these health challenges are becoming more prevalent. An age-associated loss in neural stem cell number and/or activity could cause this decline in brain function, so interventions that reverse aging in stem cells might increase the human cognitive healthspan. In this review, we describe the involvement of adult neurogenesis in neurodegenerative diseases and address the molecular mechanistic aspects of neurogenesis that involve some of the key aggregation-prone proteins in the brain (i.e., tau, Aβ, α-synuclein, …). We summarize the research pertaining to interventions that increase neurogenesis and regulate known targets in aging research, such as mTOR and sirtuins. Lastly, we share our outlook on restoring the levels of neurogenesis to physiological levels in elderly individuals and those with neurodegeneration. We suggest that modulating neurogenesis represents a potential target for interventions that could help in the fight against neurodegeneration and cognitive decline.

A Model of Pattern Separation by Single Neurons

For efficient processing, spatiotemporal spike patterns representing similar input must be able to transform into a less similar output. A new computational model with physiologically plausible parameters shows how the neuronal process referred to as “pattern separation” can be very well achieved by single neurons if the temporal qualities of the output patterns are considered. Spike patterns generated by a varying number of neurons firing with fixed different frequencies within a gamma range are used as input. The temporal and spatial summation of dendritic input combined with theta-oscillating excitability in the output neuron by subthreshold membrane potential oscillations (SMOs) lead to high temporal separation by different delays of output spikes of similar input patterns. A Winner Takes All (WTA) mechanism with backward inhibition suffices to transform the spatial overlap of input patterns to much less temporal overlap of the output patterns. The conversion of spatial patterns input into an output with differently delayed spikes enables high separation effects. Incomplete random connectivity spreads the times up to the first spike across a spatially expanded ensemble of output neurons. With the expansion, random connectivity becomes the spatial distribution mechanism of temporal features. Additionally, a “synfire chain” circuit is proposed to reconvert temporal differences into spatial ones.

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 processing^1-3. 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.

Deficits in Behavioral and Neuronal Pattern Separation in Temporal Lobe Epilepsy

In temporal lobe epilepsy, the ability of the dentate gyrus to limit excitatory cortical input to the hippocampus breaks down, leading to seizures. The dentate gyrus is also thought to help discriminate between similar memories by performing pattern separation, but whether epilepsy leads to a breakdown in this neural computation, and thus to mnemonic discrimination impairments, remains unknown. Here we show that temporal lobe epilepsy is characterized by behavioral deficits in mnemonic discrimination tasks, in both humans (females and males) and mice (C57Bl6 males, systemic low-dose kainate model). Using a recently developed assay in brain slices of the same epileptic mice, we reveal a decreased ability of the dentate gyrus to perform certain forms of pattern separation. This is because of a subset of granule cells with abnormal bursting that can develop independently of early EEG abnormalities. Overall, our results linking physiology, computation, and cognition in the same mice advance our understanding of episodic memory mechanisms and their dysfunction in epilepsy.SIGNIFICANCE STATEMENT People with temporal lobe epilepsy (TLE) often have learning and memory impairments, sometimes occurring earlier than the first seizure, but those symptoms and their biological underpinnings are poorly understood. We focused on the dentate gyrus, a brain region that is critical to avoid confusion between similar memories and is anatomically disorganized in TLE. We show that both humans and mice with TLE experience confusion between similar situations. This impairment coincides with a failure of the dentate gyrus to disambiguate similar input signals because of pathologic bursting in a subset of neurons. Our work bridges seizure-oriented and memory-oriented views of the dentate gyrus function, suggests a mechanism for cognitive symptoms in TLE, and supports a long-standing hypothesis of episodic memory theories.

Hippocampal Representations of Event Structure and Temporal Context during Episodic Temporal Order Memory

The hippocampus plays an important role in representing spatial locations and sequences and in transforming representations. How these representational structures and operations support memory for the temporal order of random items is still poorly understood. We addressed this question by leveraging the method of loci, a powerful mnemonic strategy for temporal order memory that particularly recruits hippocampus-dependent computations of spatial locations and associations. Applying representational similarity analysis to functional magnetic resonance imaging activation patterns revealed that hippocampal subfields contained representations of multiple features of sequence structure, including spatial locations, location distance, and sequence boundaries, as well as episodic-like temporal context. Critically, the hippocampal CA1 exhibited spatial transformation of representational patterns, showing lower pattern similarity for items in same locations than closely matched different locations during retrieval, whereas the CA23DG exhibited sequential transformation of representational patterns, showing lower pattern similarity for items in near locations than in far locations during encoding. These transformations enabled the encoding of multiple items in the same location and disambiguation of adjacent items. Our results suggest that the hippocampus can flexibly reconfigure multiplexed event structure representations to support accurate temporal order memory.

Experience-Dependent Inhibitory Plasticity Is Mediated by CCK+ Basket Cells in the Developing Dentate Gyrus

Early postnatal experience shapes both inhibitory and excitatory networks in the hippocampus. However, the underlying circuit plasticity is unclear. Using an enriched environment (EE) paradigm during the preweaning period in mice of either sex, we assessed the circuit plasticity of inhibitory cell types in the hippocampus. We found that cholecystokinin (CCK)-expressing basket cells strongly increased somatic inhibition on the excitatory granular cells (GCs) following EE, whereas another pivotal inhibitory cell type, parvalbumin (PV)-expressing cells, did not show changes. Using electrophysiological analysis and the use of cannabinoid receptor 1 (CB1R) agonist WIN 55 212-2, we demonstrate that the change in somatic inhibition from CCK+ neurons increases CB1R-mediated inhibition in the circuit. By inhibiting activity of the entorhinal cortex (EC) using a chemogenetic approach, we further demonstrate that the activity of the projections from the EC mediates the developmental assembly of CCK+ basket cell network. Altogether, our study places the experience-dependent remodeling of CCK+ basket cell innervation as a central process to adjust inhibition in the dentate gyrus and shows that cortical inputs to the hippocampus play an instructional role in controlling the refinement of the synaptic connections during the preweaning period.SIGNIFICANCE STATEMENT Brain plasticity is triggered by experience during postnatal brain development and shapes the maturing neural circuits. In humans, altered experience-dependent plasticity can have long-lasting detrimental effects on circuit function and lead to psychiatric disorders. Yet, the cellular mechanisms governing how early experience fine-tunes the maturing synaptic network is not fully understood. Here, taking advantage of an enrichment-housing paradigm, we unravel a new plasticity mechanism involved in the maintenance of the inhibitory to excitatory balance in the hippocampus. Our findings demonstrate that cortical activity instructs the assembly of the CCK+ basket cell network. Considering the importance of this specific cell type for learning and memory, experience-dependent remodeling of CCK+ cells may be a critical determinant for establishing appropriate neural networks.

Distinct Dorsal and Ventral Hippocampal CA3 Outputs Govern Contextual Fear Discrimination

Considerable work emphasizes a role for hippocampal circuits in governing contextual fear discrimination. However· the intra- and extrahippocampal pathways that route contextual information to cortical and subcortical circuits to guide adaptive behavioral responses are poorly understood. Using terminal-specific optogenetic silencing in a contextual fear discrimination learning paradigm· we identify opposing roles for dorsal CA3-CA1 (dCA3-dCA1) projections and dorsal CA3-dorsolateral septum (dCA3-DLS) projections in calibrating fear responses to certain and ambiguous contextual threats· respectively. Ventral CA3-DLS (vCA3-DLS) projections suppress fear responses in both certain and ambiguous contexts· whereas ventral CA3-CA1 (vCA3-vCA1) projections promote fear responses in both these contexts. Lastly· using retrograde monosynaptic tracing· ex vivo electrophysiological recordings· and optogenetics,· we identify a sparse population of DLS parvalbumin (PV) neurons as putative relays of dCA3-DLS projections to diverse subcortical circuits. Taken together· these studies illuminate how distinct dCA3 and vCA3 outputs calibrate contextual fear discrimination.

Besnard et al. show that dorsal and ventral hippocampal CA3 projections to CA1 and dorsolateral septum (DLS) play distinct roles in calibration of contextual fear discrimination. DLS parvalbumin inhibitory neurons receive monosynaptic dorsal CA3 inputs and modulate fear responses in a context-specific manner.

Ion-channel regulation of response decorrelation in a heterogeneous multi-scale model of the dentate gyrus

Heterogeneities in biological neural circuits manifest in afferent connectivity as well as in local-circuit components such as neuronal excitability, neural structure and local synaptic strengths. The expression of adult neurogenesis in the dentate gyrus (DG) amplifies local-circuit heterogeneities and guides heterogeneities in afferent connectivity. How do neurons and their networks endowed with these distinct forms of heterogeneities respond to perturbations to individual ion channels, which are known to change under several physiological and pathophysiological conditions? We sequentially traversed the ion channels-neurons-network scales and assessed the impact of eliminating individual ion channels on conductance-based neuronal and network models endowed with disparate local-circuit and afferent heterogeneities. We found that many ion channels differentially contributed to specific neuronal or network measurements, and the elimination of any given ion channel altered several functional measurements. We then quantified the impact of ion-channel elimination on response decorrelation, a well-established metric to assess the ability of neurons in a network to convey complementary information, in DG networks endowed with different forms of heterogeneities. Notably, we found that networks constructed with structurally immature neurons exhibited functional robustness, manifesting as minimal changes in response decorrelation in the face of ion-channel elimination. Importantly, the average change in output correlation was dependent on the eliminated ion channel but invariant to input correlation. Our analyses suggest that neurogenesis-driven structural heterogeneities could assist the DG network in providing functional resilience to molecular perturbations.

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Perturbations at one scale result in a cascading impact on physiology across scales.

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Heterogeneous multi-scale models used to assess the impact of ion-channel deletion.

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Mapping of structural components to functional outcomes is many-to-many.

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Differential & variable impact of ion channel deletion on response decorrelation.

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Neurogenesis-induced structural heterogeneity confers resilience to perturbations.

Alterations of Neuronal Dynamics as a Mechanism for Cognitive Impairment in Epilepsy

Epilepsy is commonly associated with cognitive and behavioral deficits that dramatically affect the quality of life of patients. In order to identify novel therapeutic strategies aimed at reducing these deficits, it is critical first to understand the mechanisms leading to cognitive impairments in epilepsy. Traditionally, seizures and epileptiform activity in addition to neuronal injury have been considered to be the most significant contributors to cognitive dysfunction. In this review we however highlight the role of a new mechanism: alterations of neuronal dynamics, i.e. the timing at which neurons and networks receive and process neural information. These alterations, caused by the underlying etiologies of epilepsy syndromes, are observed in both animal models and patients in the form of abnormal oscillation patterns in unit firing, local field potentials, and electroencephalogram (EEG). Evidence suggests that such mechanisms significantly contribute to cognitive impairment in epilepsy, independently of seizures and interictal epileptiform activity. Therefore, therapeutic strategies directly targeting neuronal dynamics rather than seizure reduction may significantly benefit the quality of life of patients.

Dendritic morphology and inhibitory regulation distinguish dentate semilunar granule cells from granule cells through distinct stages of postnatal development

Semilunar granule cells (SGCs) have been proposed as a morpho-functionally distinct class of hippocampal dentate projection neurons contributing to feedback inhibition and memory processing in juvenile rats. However, the structural and physiological features that can reliably classify granule cells (GCs) from SGCs through postnatal development remain unresolved. Focusing on postnatal days 11-13, 28-42, and > 120, corresponding with human infancy, adolescence, and adulthood, we examined the somato-dendritic morphology and inhibitory regulation in SGCs and GCs to determine the cell-type specific features. Unsupervised cluster analysis confirmed that morphological features reliably distinguish SGCs from GCs irrespective of animal age. SGCs maintain higher spontaneous inhibitory postsynaptic current (sIPSC) frequency than GCs from infancy through adulthood. Although sIPSC frequency in SGCs was particularly enhanced during adolescence, sIPSC amplitude and cumulative charge transfer declined from infancy to adulthood and were not different between GCs and SGCs. Extrasynaptic GABA current amplitude peaked in adolescence in both cell types and was significantly greater in SGCs than in GCs only during adolescence. Although GC input resistance was higher than in SGCs during infancy and adolescence, input resistance decreased with developmental age in GCs, while it progressively increased in SGCs. Consequently, GCs' input resistance was significantly lower than SGCs in adults. The data delineate the structural features that can reliably distinguish GCs from SGCs through development. The results reveal developmental differences in passive membrane properties and steady-state inhibition between GCs and SGCs which could confound their use in classifying the cell types.

Enhancing adult neurogenesis promotes contextual fear memory discrimination and activation of hippocampal-dorsolateral septal circuits

Hippocampal circuitry is continuously modified by integration of adult-born dentate granule cells (DGCs). Prior work has shown that enhancing adult hippocampal neurogenesis decreases interference or overlap or conflict between ensembles of similar contexts and promotes discrimination of a shock-associated context from a similar, neutral context. However, the impact of enhanced integration of adult-born neurons on hippocampal network activity or downstream circuits such as the dorsolateral septum that mediate defensive behavioral responses is poorly understood. Here, we first replicated our finding that genetic expansion of the population of adult-born dentate granule cells (8 weeks and younger) promotes contextual fear discrimination. We found that enhanced contextual fear discrimination is associated with greater c-Fos expression in discrete hippocampal subfields along the proximo-distal and dorsoventral axis. Examination of the dorsolateral septum revealed an increase in activation of somatostatin expressing neurons consistent with recent characterization of these cells as calibrators of defensive behavior. Together, these findings begin to shed light on how genetically enhancing adult hippocampal neurogenesis affects activity of hippocampal-dorsolateral septal circuits.

Distinct cellular mediators drive the Janus faces of toll-like receptor 4 regulation of network excitability which impacts working memory performance after brain injury

The mechanisms by which the neurophysiological and inflammatory responses to brain injury contribute to memory impairments are not fully understood. Recently, we reported that the innate immune receptor, toll-like receptor 4 (TLR4) enhances AMPA receptor (AMPAR) currents and excitability in the dentate gyrus after fluid percussion brain injury (FPI) while limiting excitability in controls. Here, we examine the cellular mediators underlying TLR4 regulation of dentate excitability and its impact on memory performance. In ex vivo slices, astrocytic and microglial metabolic inhibitors selectively abolished TLR4 antagonist modulation of excitability in controls, but not in rats after FPI, demonstrating that glial signaling contributes to TLR4 regulation of excitability in controls. In glia-depleted neuronal cultures from naïve mice, TLR4 ligands bidirectionally modulated AMPAR charge transfer consistent with neuronal TLR4 regulation of excitability, as observed after brain injury. In vivo TLR4 antagonism reduced early post-injury increases in mediators of MyD88-dependent and independent TLR4 signaling without altering expression in controls. Blocking TNFα, a downstream effector of TLR4, mimicked effects of TLR4 antagonist and occluded TLR4 agonist modulation of excitability in slices from both control and FPI rats. Functionally, transiently blocking TLR4 in vivo improved impairments in working memory observed one week and one month after FPI, while the same treatment impaired memory function in uninjured controls. Together these data identify that distinct cellular signaling mechanisms converge on TNFα to mediate TLR4 modulation of network excitability in the uninjured and injured brain and demonstrate a role for TLR4 in regulation of working memory function.

Quantitative properties of a feedback circuit predict frequency-dependent pattern separation

Feedback inhibitory motifs are thought to be important for pattern separation across species. How feedback circuits may implement pattern separation of biologically plausible, temporally structured input in mammals is, however, poorly understood. We have quantitatively determined key properties of netfeedback inhibition in the mouse dentate gyrus, a region critically involved in pattern separation. Feedback inhibition is recruited steeply with a low dynamic range (0% to 4% of active GCs), and with a non-uniform spatial profile. Additionally, net feedback inhibition shows frequency-dependent facilitation, driven by strongly facilitating mossy fiber inputs. Computational analyses show a significant contribution of the feedback circuit to pattern separation of theta modulated inputs, even within individual theta cycles. Moreover, pattern separation was selectively boosted at gamma frequencies, in particular for highly similar inputs. This effect was highly robust, suggesting that frequency-dependent pattern separation is a key feature of the feedback inhibitory microcircuit.

You can probably recall where you left your car this morning without too much trouble. But assuming you use the same busy parking lot every day, can you remember which space you parked in yesterday? Or the day before that? Most people find this difficult not because they cannot remember what happened two or three days ago, but because it requires distinguishing between very similar memories. The car, the parking lot, and the time of day were the same on each occasion. So how do you remember where you parked this morning?

This ability to distinguish between memories of similar events depends on a brain region called the hippocampus. A subregion of the hippocampus called the dentate gyrus generates different patterns of activity in response to events that are similar but distinct. This process is called pattern separation, and it helps ensure that you do not look for your car in yesterday’s parking space.

Pattern separation in the dentate gyrus is thought to involve a form of negative feedback called feedback inhibition, a phenomenon where the output of a process acts to limit or stop the same process. To test this idea, Braganza et al. studied feedback inhibition in the dentate gyrus of mice, before building a computer model simulating the inhibition process and supplying the model with two types of realistic input. The first consisted of low-frequency theta brainwaves, which occur, for instance, in the dentate gyrus when animals explore their environment. The second consisted of higher frequency gamma brainwaves, which occur, for example, when animals experience something new.

Testing the model showed that feedback inhibition contributes to pattern separation with both theta and gamma inputs. However, pattern separation is stronger with gamma input. This suggests that high frequency brainwaves in the hippocampus could help animals distinguish new events from old ones by promoting pattern separation.

Various brain disorders, including Alzheimer’s disease, schizophrenia and epilepsy, involve changes in the dentate gyrus and altered brain rhythms. The current findings could help reveal how these changes contribute to memory impairments and to a reduced ability to distinguish similar experiences.