Temporal pattern separation in hippocampal neurons through multiplexed neural codes
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ABSTRACT:
SUBMITTER: Antoine Madar
PROVIDER: S-BSST219 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Pattern separation is a central concept in current theories of episodic memory: this computation is thought to support our ability to avoid confusion between similar memories by transforming similar cortical input patterns of neural activity into dissimilar output patterns before their long-term storage in the hippocampus. Because there are many ways one can define patterns of neuronal activity and the similarity between them, pattern separation could in theory be achieved through multiple coding strategies. Using our recently developed assay that evaluates pattern separation in isolated tissue by controlling and recording the input and output spike trains of single hippocampal neurons, we explored neural codes through which pattern separation is performed by systematic testing of different similarity metrics and various time resolutions. We discovered that granule cells, the projection neurons of the dentate gyrus, can exhibit both pattern separation and its opposite computation, pattern convergence, depending on the neural code considered and the statistical structure of the input patterns. Pattern separation is favored when inputs are highly similar, and is achieved through spike time reorganization at short time scales (< 100 ms) as well as through variations in firing rate and burstiness at longer time scales. These multiplexed forms of pattern separation are network phenomena, notably controlled by GABAergic inhibition, that involve many celltypes with input-output transformations that participate in pattern separation to different extents and with complementary neural codes: a rate code for dentate fast-spiking interneurons, a burstiness code for hilar mossy cells and a synchrony code at long time scales for CA3 pyramidal cells. Therefore, the isolated hippocampal circuit itself is capable of performing temporal pattern separation using multiplexed coding strategies that might be essential to optimally disambiguate multimodal mnemonic representations.
| S-EPMC6476466 | biostudies-literature
Project description:Pattern separation is a process that minimizes overlap between patterns of neuronal activity representing similar experiences. Theoretical work suggests that the dentate gyrus (DG) performs this role for memory processing but a direct demonstration is lacking. One limitation is the difficulty to measure DG inputs and outputs simultaneously. To rigorously assess pattern separation by DG circuitry, we used mouse brain slices to stimulate DG afferents and simultaneously record DG granule cells (GCs) and interneurons. Output spiketrains of GCs are more dissimilar than their input spiketrains, demonstrating for the first time temporal pattern separation at the level of single neurons in the DG. Pattern separation is larger in GCs than in fast-spiking interneurons and hilar mossy cells, and is amplified in CA3 pyramidal cells. Analysis of the neural noise and computational modelling suggest that this form of pattern separation is not explained by simple randomness and arises from specific presynaptic dynamics. Overall, by reframing the concept of pattern separation in dynamic terms and by connecting it to the physiology of different types of neurons, our study offers a new window of understanding in how hippocampal networks might support episodic memory.
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Project description:Episodic memory is the ability to remember events from our past accurately. The process of pattern separation is hypothesized to underpin this ability and is defined as the capacity to orthogonalize memory traces, to maximize the features that make them unique. Contemporary cognitive neuroscience suggests that pattern separation entails complex interactions between the hippocampus and neocortex, where specific hippocampal subregions shape neural reinstatement in the neocortex. To test this hypothesis, the current work studied both healthy controls and patients with temporal lobe epilepsy who presented with hippocampal structural anomalies. We measured neural activity in all participants using functional MRI while they retrieved memorized items or lure items, which shared features with the target. Behaviourally, patients with temporal lobe epilepsy were less able to exclude lures than controls and showed a reduction in pattern separation. To assess the hypothesized relationship between neural patterns in the hippocampus and neocortex, we identified the topographic gradients of intrinsic connectivity along neocortical and hippocampal subfield surfaces and determined the topographic profile of the neural activity accompanying pattern separation. In healthy controls, pattern separation followed a graded topography of neural activity, both along the hippocampal long axis (and peaked in anterior segments that are more heavily engaged in transmodal processing) and along the neocortical hierarchy running from unimodal to transmodal regions (peaking in transmodal default mode regions). In patients with temporal lobe epilepsy, however, this concordance between task-based functional activations and topographic gradients was markedly reduced. Furthermore, person-specific measures of concordance between task-related activity and connectivity gradients in patients and controls were related to inter-individual differences in behavioural measures of pattern separation and episodic memory, highlighting the functional relevance of the observed topographic motifs. Our work is consistent with an emerging understanding that successful discrimination between memories with similar features entails a shift in the locus of neural activity away from sensory systems, a pattern that is mirrored along the hippocampal long axis and with respect to neocortical hierarchies. More broadly, our study establishes topographic profiling using intrinsic connectivity gradients, capturing the functional underpinnings of episodic memory processes in a manner that is sensitive to their reorganization in pathology.
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Project description:Animals rely on learned associations to make decisions. Associations can be based on relationships between object features (e.g., the three leaflets of poison ivy leaves) and outcomes (e.g., rash). More often, outcomes are linked to multidimensional states (e.g., poison ivy is green in summer but red in spring). Feature-based reinforcement learning fails when the values of individual features depend on the other features present. One solution is to assign value to multi-featural conjunctive representations. Here, we test if the hippocampus forms separable conjunctive representations that enables the learning of response contingencies for stimuli of the form: AB+, B-, AC-, C+. Pattern analyses on functional MRI data show the hippocampus forms conjunctive representations that are dissociable from feature components and that these representations, along with those of cortex, influence striatal prediction errors. Our results establish a novel role for hippocampal pattern separation and conjunctive representation in reinforcement learning.
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Project description:The medial temporal lobe (MTL) is known to support episodic memory and spatial navigation, raising the possibility that its true function is to form "cognitive maps" of any kind of information. Studies in humans and animals support the idea that the hippocampal theta rhythm (4 to 8 Hz) is key to this mapping function, as it has been repeatedly observed during spatial navigation tasks. If episodic memory and spatial navigation are 2 sides of the same coin, we hypothesized that theta oscillations might reflect relations between explicitly nonspatial items, such as words. We asked 189 neurosurgical patients to perform a verbal free-recall task, of which 96 had indwelling electrodes placed in the MTL. Subjects were instructed to remember short lists of sequentially presented nouns. We found that hippocampal theta power and connectivity during item retrieval coded for semantic distances between words, as measured using word2vec-derived subspaces. Additionally, hippocampal theta indexed temporal distances between words after filtering lists on recall performance, to ensure adequate dynamic range in time. Theta effects were noted only for semantic subspaces of 1 dimension, indicating a substantial compression of the possible semantic feature space. These results lend further support to our growing confidence that the MTL forms cognitive maps of arbitrary representational spaces, helping to reconcile longstanding differences between the spatial and episodic memory literatures.
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Project description:The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window), and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code.
| S-EPMC3210806 | biostudies-other
Project description: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.
| S-EPMC9103200 | biostudies-literature
Project description:It has long been hypothesized that a primary function of the hippocampus is to discover and exploit temporal relationships between events. Previously, it has been reported that sequences of "time cells" in the hippocampus extend for tens of seconds. Other studies have shown that neuronal firing in the hippocampus fluctuates over hours and days. Both of these mechanisms could enable temporal encoding of events over very different timescales. However, thus far, these two classes of phenomena have never been observed simultaneously, which is necessary to ascribe broad-range temporal coding to the hippocampus. Using in vivo calcium imaging in unrestrained mice, we observed sequences of hippocampal neurons that bridged a 10 s delay. Similar sequences were observed over multiple days, but the set of neurons participating in those sequences changed gradually. Thus, the same population of neurons that encodes temporal information over seconds can also be used to distinguish periods of time over much longer timescales. These results unify two previously separate paradigms of temporal processing in the hippocampus that support episodic memory.
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Project description:Emotional arousal, mediated by the amygdala, is known to modulate episodic memories stored by the hippocampus, a region involved in pattern separation (the process by which similar representations are independently stored). While emotional modulation and pattern separation have been examined independently, this study attempts to link the two areas of research to propose an alternative account for how emotion modulates episodic memory. We used an emotional discrimination task designed to tax pattern separation of emotional information by concurrently varying emotional valence and similarity of stimuli. To examine emotional modulation of memory at the level of hippocampal subfields, we used high-resolution fMRI (1.5 mm isotropic) of the medial temporal lobe. Consistent with prior reports, we observed engagement of the hippocampal dentate gyrus (DG) and CA3 during accurate discrimination of highly similar items (behavioral correlate of pattern separation). Furthermore, we observed an emotional modulation of this signal (negative > neutral) specific to trials on which participants accurately discriminated similar emotional items. The amygdala was also modulated by emotion, regardless of the accuracy of discrimination. Additionally, we found aberrant amygdala-hippocampal network activity in a sample of adults with depressive symptoms. In this sample, amygdala activation was enhanced and DG/CA3 activation was diminished during emotional discrimination compared to those without depressive symptoms. Depressive symptom severity was also negatively correlated with DG/CA3 activity. This study suggests a novel mechanistic account for how emotional information is processed by hippocampal subfields as well as how this network may be altered in mood disorders.
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Project description:Adult hippocampal neurogenesis is a unique form of neural circuit plasticity that results in the generation of new neurons in the dentate gyrus throughout life. Neurons that arise in adults (adult-born neurons) show heightened synaptic plasticity during their maturation and can account for up to ten per cent of the entire granule cell population. Moreover, levels of adult hippocampal neurogenesis are increased by interventions that are associated with beneficial effects on cognition and mood, such as learning, environmental enrichment, exercise and chronic treatment with antidepressants. Together, these properties of adult neurogenesis indicate that this process could be harnessed to improve hippocampal functions. However, despite a substantial number of studies demonstrating that adult-born neurons are necessary for mediating specific cognitive functions, as well as some of the behavioural effects of antidepressants, it is unknown whether an increase in adult hippocampal neurogenesis is sufficient to improve cognition and mood. Here we show that inducible genetic expansion of the population of adult-born neurons through enhancing their survival improves performance in a specific cognitive task in which two similar contexts need to be distinguished. Mice with increased adult hippocampal neurogenesis show normal object recognition, spatial learning, contextual fear conditioning and extinction learning but are more efficient in differentiating between overlapping contextual representations, which is indicative of enhanced pattern separation. Furthermore, stimulation of adult hippocampal neurogenesis, when combined with an intervention such as voluntary exercise, produces a robust increase in exploratory behaviour. However, increasing adult hippocampal neurogenesis alone does not produce a behavioural response like that induced by anxiolytic agents or antidepressants. Together, our findings suggest that strategies that are designed to increase adult hippocampal neurogenesis specifically, by targeting the cell death of adult-born neurons or by other mechanisms, may have therapeutic potential for reversing impairments in pattern separation and dentate gyrus dysfunction such as those seen during normal ageing.
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