Neuronal Populations Research Articles

Alzheimer Disease

Alzheimer's disease (AD) is typified by memory deficiencies that worsen with time, along with cognitive and behavioral abnormalities that eventually result in dementia. AD is one of the most difficult diseases to treat because of its prevalence, high cost of care, effects on patients and caregivers, and lack of mechanism-based therapies. The malfunction and loss of neurons in particular circuits and locations, especially in the populations of nerve cells supporting memory and cognition, causes the AD condition.The neuropathology of AD is characterized by intracellular and extracellular protein aggregation accumulations. In the neuronal perikarya and dystrophic neurites, abnormally phosphorylated tau forms paired helical filaments (PHFs) that combine to form neurofibrillary tangles (NFTs). The extracellular deposition of β-pleated assemblies of Aβ peptide, which result in widespread and neuritic senile plaques, is the second pathogenic hallmark.

Some aspects of bidomain modeling with volume conductors

The concept of dynamic multiscaling has changed our approach to multi-neuronal cable theory. Previously, computational neuroscientists considered individual neurons as neural masses or compartmental models, but now, a distributed representation of single neurons as ionic cable structures is most likely to lead to a greater understanding of how the distribution of ionic channels and synaptic input along the dendrites of a few neurons can offset the collective behavior of a large ensemble of neurons and, therefore, provide a measure of the dynamical brain. This change in perspective forms the basis of volume conductor-bidomain modeling, a new method that captures multiscalar electrophysiology.

Cortical networks relating to arousal are differentially coupled to neural activity and hemodynamics.

Even in the absence of specific sensory input or a behavioral task, the brain produces structured patterns of activity. This organized activity is modulated by changes in arousal. Here, we use wide-field voltage imaging to establish how arousal relates to cortical network voltage and hemodynamic activity in spontaneously behaving head-fixed male and female mice expressing the voltage-sensitive fluorescent FRET sensor Butterfly 1.2. We find that global voltage and hemodynamic signals are both positively correlated with changes in arousal with a maximum correlation of 0.5 and 0.25 respectively at a time lag of 0 seconds. We next show that arousal influences distinct cortical regions for both voltage and hemodynamic signals. These include a broad positive correlation across most sensory-motor cortices extending posteriorly to the primary visual cortex observed in both signals. In contrast, activity in prefrontal cortex is positively correlated to changes in arousal for the voltage signal while it is a slight net negative correlation observed in the hemodynamic signal. Additionally, we show that coherence between voltage and hemodynamic signals relative to arousal is strongest for slow frequencies below 0.15 Hz and is near zero for frequencies greater than 1Hz. We finally show that coupling patterns are dependent on the behavioral state of the animal with correlations being driven by periods of increased orofacial movement. Our results indicate that while hemodynamic signals show strong relations to behavior and arousal, these relations are distinct from those observed by voltage activity.Significance Statement We leverage wide-field voltage imaging to examine the relation between cortical changes in membrane potential dynamics and hemodynamics. These two signals are then examined with respect to changes in arousal, as measured by pupil diameter, in awake head fixed mice. Our results show similarities as well as important differences in the correlation of arousal with neuronal population activity dynamics and the hemodynamic signal. Further, the spatial activity correlation maps with arousal depended differentially on the behavioral state of the animal in a frequency dependent manner. Our results indicate that the modulation of brain networks by arousal is dynamically regulated, and only partly overlap between functional networks determined from hemodynamic or voltage activity.

A role of dentate gyrus mechanistic target of rapamycin activation in epileptogenesis in a mouse model of posttraumatic epilepsy.

The mechanistic target of rapamycin (mTOR) pathway has been implicated in promoting epileptogenesis in animal models of acquired epilepsy, such as posttraumatic epilepsy (PTE) following traumatic brain injury (TBI). However, the specific anatomical regions and neuronal populations mediating mTOR's role in epileptogenesis are not well defined. In this study, we tested the hypothesis that mTOR activation in dentate gyrus granule cells promotes neuronal death, mossy fiber sprouting, and PTE in the controlled cortical impact (CCI) model of TBI. An adeno-associated virus (AAV)-Cre viral vector was injected into the hippocampus of Rptorflox/flox (regulatory-associated protein of mTOR) mutant mice to inhibit mTOR activation in dentate gyrus granule cells. Four weeks after AAV-Cre or AAV-vehicle injection, mice underwent CCI injury and were subsequently assessed for mTOR pathway activation by Western blotting, neuronal death, and mossy fiber sprouting by immunopathological analysis, and posttraumatic seizures by video-electroencephalographic monitoring. AAV-Cre injection primarily affected the dentate gyrus and inhibited hippocampal mTOR activation following CCI injury. AAV-Cre-injected mice had reduced neuronal death in dentate gyrus detected by Fluoro-Jade B staining and decreased mossy fiber sprouting by ZnT3 immunostaining. Finally, AAV-Cre-injected mice exhibited a decrease in incidence of PTE. mTOR pathway activation in dentate gyrus granule cells may at least partly mediate pathological abnormalities and epileptogenesis in models of TBI and PTE. Targeted modulation of mTOR activity in this hippocampal network may represent a focused therapeutic approach for antiepileptogenesis and prevention of PTE.

Cellular resolution contributions to ictal population signals.

The increased amplitude of ictal activity is a common feature of epileptic seizures, but the determinants of this amplitude have not been identified. Clinically, ictal amplitudes are measured electrographically (using, e.g., electroencephalography, electrocorticography, and depth electrodes), but these methods do not enable the assessment of the activity of individual neurons. Population signal may increase from three potential sources: (1) increased synchrony (i.e., more coactive neurons); (2) altered active state, from bursts of action potentials and/or paroxysmal depolarizing shifts in membrane potential; and (3) altered subthreshold state, which includes all lower levels of activity. Here, we quantify the fraction of ictal signal from each source. To identify the cellular determinants of the ictal signal, we measured single cell and population electrical activity and neuronal calcium levels via optical imaging of the genetically encoded calcium indicator (GECI) GCaMP. Spontaneous seizure activity was assessed with microendoscopy in an APP/PS1 mouse with focal cortical injury and via widefield imaging in the organotypic hippocampal slice cultures (OHSCs) model of posttraumatic epilepsy. Single cell calcium signals were linked to a range of electrical activities by performing simultaneous GECI-based calcium imaging and whole-cell patch-clamp recordings in spontaneously seizing OHSCs. Neuronal resolution calcium imaging of spontaneous seizures was then used to quantify the cellular contributions to population-level ictal signal. The seizure onset signal was primarily driven by increased subthreshold activity, consistent with either barrages of excitatory postsynaptic potentials or sustained membrane depolarization. Unsurprisingly, more neurons entered the active state as seizure activity progressed. However, the increasing fraction of active cells was primarily driven by synchronous reactivation and not from continued recruitment of new populations of neurons into the seizure. This work provides a critical link between single neuron activity and population measures of seizure activity.

A strong direct link from the layer 3/4 border to layer 6 of cat primary visual cortex.

The cat primary visual cortex (V1) is a cortical area for which we have one of the most detailed estimates of the connection 'weights' (expressed as number of synapses) between different neural populations in different layers (Binzegger et al in J Neurosci 24:8441-8453, 2004). Nevertheless, the majority of excitatory input sources to layer 6, the deepest layer in a local translaminar excitatory feedforward loop, was not accounted for by the known neuron types used to generate the quantitative Binzegger diagram. We aimed to fill this gap by using a retrograde tracer that would label neural cell bodies in and outside V1 that directly connect to layer 6 of V1. We found that more than 80% of labeled neurons projecting to layer 6 were within V1 itself. Our data indicate that a substantial fraction of the missing input is provided by a previously unidentified population of layer 3/4 border neurons, laterally distributed and connecting more strongly to layer 6 than the typical superficial layer pyramidal neurons considered by Binzegger et al. (Binzegger et al in J Neurosci 24:8441-8453, 2004). This layer 3/4 to layer 6 connection may be a parallel route to the layer 3 - layer 5 - layer 6 feedforward pathway, be associated with the fast-conducting, movement-related Y pathway and provide convergent input from distant (5-10 degrees) regions of the visual field.

Neuronal population activity in the olivocerebellum encodes the frequency of essential tremor in mice and patients.

Essential tremor (ET) is the most prevalent movement disorder, characterized primarily by action tremor, an involuntary rhythmic movement with a specific frequency. However, the neuronal mechanism underlying the coding of tremor frequency remains unexplored. Here, we used in vivo electrophysiology, optogenetics, and simultaneous motion tracking in the Grid2dupE3 mouse model to investigate whether and how neuronal activity in the olivocerebellum determines the frequency of essential tremor. We report that tremor frequency was encoded by the temporal coherence of population neuronal firing within the olivocerebellums of these mice, leading to frequency-dependent cerebellar oscillations and tremors. This mechanism was precise and generalizable, enabling us to use optogenetic stimulation of the deep cerebellar nuclei to induce frequency-specific tremors in wild-type mice or alter tremor frequencies in tremor mice. In patients with ET, we showed that deep brain stimulation of the thalamus suppressed tremor symptoms but did not eliminate cerebellar oscillations measured by electroencephalgraphy, indicating that tremor-related oscillations in the cerebellum do not require the reciprocal interactions with the thalamus. Frequency-disrupting transcranial alternating current stimulation of the cerebellum could suppress tremor amplitudes, confirming the frequency modulatory role of the cerebellum in patients with ET. These findings offer a neurodynamic basis for the frequency-dependent stimulation of the cerebellum to treat essential tremor.

De novo motor learning creates structure in neural activity that shapes adaptation

Animals can quickly adapt learned movements to external perturbations, and their existing motor repertoire likely influences their ease of adaptation. Long-term learning causes lasting changes in neural connectivity, which shapes the activity patterns that can be produced during adaptation. Here, we examined how a neural population’s existing activity patterns, acquired through de novo learning, affect subsequent adaptation by modeling motor cortical neural population dynamics with recurrent neural networks. We trained networks on different motor repertoires comprising varying numbers of movements, which they acquired following various learning experiences. Networks with multiple movements had more constrained and robust dynamics, which were associated with more defined neural ‘structure’—organization in the available population activity patterns. This structure facilitated adaptation, but only when the changes imposed by the perturbation were congruent with the organization of the inputs and the structure in neural activity acquired during de novo learning. These results highlight trade-offs in skill acquisition and demonstrate how different learning experiences can shape the geometrical properties of neural population activity and subsequent adaptation.

Differential transcriptional profiles of vagal sensory neurons in female and male mice

Differential transcriptional profiles of vagal sensory neurons in female and male mice

High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?

Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60-150 Hz), ripple (80-250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms, and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.

Neuron-specific RNA-sequencing reveals different responses in peripheral neurons after nerve injury

Peripheral neurons are heterogeneous and functionally diverse, but all share the capability to switch to a pro-regenerative state after nerve injury. Despite the assumption that the injury response is similar among neuronal subtypes, functional recovery may differ. Understanding the distinct intrinsic regenerative properties between neurons may help to improve the quality of regeneration, prioritizing the growth of axon subpopulations to their targets. Here, we present a comparative analysis of regeneration across four key peripheral neuron populations: motoneurons, proprioceptors, cutaneous mechanoreceptors, and nociceptors. Using Cre/Ai9 mice that allow fluorescent labeling of neuronal subtypes, we found that nociceptors showed the greater regeneration after a sciatic crush, followed by motoneurons, mechanoreceptors, and, finally, proprioceptors. By breeding these Cre mice with Ribotag mice, we isolated specific translatomes and defined the regenerative response of these neuronal subtypes after axotomy. Only 20% of the regulated genes were common, revealing a diverse response to injury among neurons, which was also supported by the differential influence of neurotrophins among neuron subtypes. Among differentially regulated genes, we proposed MED12 as a specific regulator of the regeneration of proprioceptors. Altogether, we demonstrate that the intrinsic regenerative capacity differs between peripheral neuron subtypes, opening the door to selectively modulate these responses.

Neuron-specific RNA-sequencing reveals different responses in peripheral neurons after nerve injury.

Peripheral neurons are heterogeneous and functionally diverse, but all share the capability to switch to a pro-regenerative state after nerve injury. Despite the assumption that the injury response is similar among neuronal subtypes, functional recovery may differ. Understanding the distinct intrinsic regenerative properties between neurons may help to improve the quality of regeneration, prioritizing the growth of axon subpopulations to their targets. Here, we present a comparative analysis of regeneration across four key peripheral neuron populations: motoneurons, proprioceptors, cutaneous mechanoreceptors, and nociceptors. Using Cre/Ai9 mice that allow fluorescent labeling of neuronal subtypes, we found that nociceptors showed the greater regeneration after a sciatic crush, followed by motoneurons, mechanoreceptors, and, finally, proprioceptors. By breeding these Cre mice with Ribotag mice, we isolated specific translatomes and defined the regenerative response of these neuronal subtypes after axotomy. Only 20% of the regulated genes were common, revealing a diverse response to injury among neurons, which was also supported by the differential influence of neurotrophins among neuron subtypes. Among differentially regulated genes, we proposed MED12 as a specific regulator of the regeneration of proprioceptors. Altogether, we demonstrate that the intrinsic regenerative capacity differs between peripheral neuron subtypes, opening the door to selectively modulate these responses.

The tuning of tuning: How adaptation influences single cell information transfer.

Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the 'h-current', and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed.

Separate cue- and alpha-related mechanisms for distractor suppression.

Research on selective attention has largely focused on the enhancement of behaviorally important information, with less focus on the suppression of distracting information. Enhancement and suppression can operate through a push-pull relationship attributable to competitive interactions among neural populations. There has been considerable debate, however, regarding (i) whether suppression can be voluntarily deployed, independent of enhancement, and (ii) whether the voluntary deployment of suppression is associated with neural processes that occur prior to distractor onset. Here, we investigated the interplay between pre- and post-distractor neural processes, while male and female human subjects performed a visual search task with a cue that indicated the location of an upcoming distractor. We utilized two established EEG markers of suppression: the distractor positivity (PD) and alpha power (∼8-15 Hz). The PD-a component of event-related potentials-has been linked with successful distractor suppression, and increased alpha power has been linked with attenuated sensory processing. Cueing the location of an upcoming distractor speeded responses and led to an earlier PD, consistent with earlier suppression due to the strategic use of a spatial cue. In comparison, higher pre-distractor alpha power contralateral to distractors led to a later PD, consistent with later suppression. Lower alpha power contralateral to distractors instead led to distractor-related attentional capture. Lateralization of alpha power was not linked to the spatial cue. This observation, combined with differences in the timing of successful suppression-as indexed by earlier and later PD components-demonstrates that cue-related, voluntary suppression can occur separate from alpha-related gating of sensory processing.Significance Statement Selective suppression of distracting information is important for survival. There are ongoing debates, however, regarding whether and how selective enhancement can be voluntarily deployed independent of selective enhancement. Here, we recorded EEG while subjects performed a visual search task with cues that indicated the location of upcoming distractors. Behavioral and electrophysiological results revealed that foreknowledge of a distractor's location speeded suppression (relative to non-cued trials), thereby facilitating target detection. The results further revealed that such cue-related suppression of a distractor can occur separate from alpha-related gating of sensory processing. That is, alpha-related suppression in the present task occurred independent of the spatially informative cue (i.e., on both cued and non-cued trials) and later than cue-related suppression (as indexed by later and earlier PD components).

Multifunctional and Flexible Neural Probe with Thermally Drawn Fibers for Bidirectional Synaptic Probing in the Brain.

Synapses in the brain utilize two distinct communication mechanisms: chemical and electrical. For a comprehensive investigation of neural circuitry, neural interfaces should be capable of both monitoring and stimulating these types of physiological interactions. However, previously developed interfaces for neurotransmitter monitoring have been limited in interaction modality due to constraints in device size, fabrication techniques, and the usage of flexible materials. To address this obstacle, we propose a multifunctional and flexible fiber probe fabricated through the microwire codrawing thermal drawing process, which enables the high-density integration of functional components with various materials such as polymers, metals, and carbon fibers. The fiber enables real-time monitoring of transient dopamine release in vivo, real-time stimulation of cell-specific neuronal populations via optogenetic stimulation, single-unit electrophysiology of individual neurons localized to the tip of the neural probe, and chemical stimulation via drug delivery. This fiber will improve the accessibility and functionality of bidirectional interrogation of neurochemical mechanisms in implantable neural probes.

Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network

Abstract Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.

Bidirectional regulation of levodopa-induced dyskinesia by a specific neural ensemble in globus pallidus external segment.

Levodopa-induced dyskinesia (LID) is an intractable motor complication arising in Parkinson's disease with the progression of disease and chronic treatment of levodopa. However, the specific cell assemblies mediating dyskinesia have not been fully elucidated. Here, we utilize the activity-dependent tool to identify three brain regions (globus pallidus external segment [GPe], parafascicular thalamic nucleus, and subthalamic nucleus) that specifically contain dyskinesia-activated ensembles. An intensity-dependent hyperactivity in the dyskinesia-activated subpopulation in GPe (GPeTRAPed in LID) is observed during dyskinesia. Optogenetic inhibition of GPeTRAPed in LID significantly ameliorates LID, whereas reactivation of GPeTRAPed in LID evokes dyskinetic behavior in the levodopa-off state. Simultaneous chemogenetic reactivation of GPeTRAPed in LID and another previously reported ensemble in striatum fully reproduces the dyskinesia induced by high-dose levodopa. Finally, we characterize GPeTRAPed in LID as a subset of prototypic neurons in GPe. These findings provide theoretical foundations for precision medication and modulation of LID in the future.

Distributed and dynamical communication: a mechanism for flexible cortico-cortical interactions and its functional roles in visual attention

Perceptual and cognitive processing relies on flexible communication among cortical areas; however, the underlying neural mechanism remains unclear. Here we report a mechanism based on the realistic spatiotemporal dynamics of propagating wave patterns in neural population activity. Using a biophysically plausible, multiarea spiking neural circuit model, we demonstrate that these wave patterns, characterized by their rich and complex dynamics, can account for a wide variety of empirically observed neural processes. The coordinated interactions of these wave patterns give rise to distributed and dynamic communication (DDC) that enables flexible and rapid routing of neural activity across cortical areas. We elucidate how DDC unifies the previously proposed oscillation synchronization-based and subspace-based views of interareal communication, offering experimentally testable predictions that we validate through the analysis of Allen Institute Neuropixels data. Furthermore, we demonstrate that DDC can be effectively modulated during attention tasks through the interplay of neuromodulators and cortical feedback loops. This modulation process explains many neural effects of attention, underscoring the fundamental functional role of DDC in cognition.

Immunological isolation and characterization of neuronal progenitors from human dental pulp: A laboratory-based investigation.

Dental pulp stem cells (DPSCs) contain a population of stem cells with a broad range of differentiation potentials, as well as more lineage-committed progenitors. Such heterogeneity is a significant obstacle to experimental and clinical applications. The aim of this study is to isolate and characterize a homogenous neuronal progenitor cell population from human DPSCs. Polysialylated-neural cell adhesion molecule (PSA-NCAM+) neural progenitors were isolated from the dental pulp of three independent donors using magnetic-activated cell sorting (MACS) technology. Immunofluorescent staining with a panel of neural and non-neural markers was used to characterize the magnetically isolated PSA-NCAM+ fraction. PSA-NCAM+ cells were then cultured in Neurobasal A supplemented with neurotrophic factors: dibutyryl cyclic-AMP, neurotrophin-3, B27 and N2 supplements to induce neuronal differentiation. Both PSA-NCAM+ and differentiated PSA-NCAM+ cells were used in Ca2+ imaging studies to assess the functionality of P2X3 receptors as well as membrane depolarization. PSA-NCAM+ neural progenitors were isolated from a heterogeneous population of hDPSCs using magnetic-activated cell sorting and anti-PSA-NCAM MicroBeads. Flow cytometry analysis demonstrated that immunomagnetic sorting significantly increased the purity of PSA-NCAM+ cells. Immunofluorescent staining revealed expression of pan-neuronal and mature neuronal markers, PGP9.5 and MAP2, respectively, as well as weak expression of the mature sensory markers, peripherin and islet1. ATP-induced response was mediated predominately by P2X3 receptors in both undifferentiated and differentiated cells, with a greater magnitude observed in the latter. In addition, membrane depolarizations were also detected in cells before and after differentiation when loaded with fast-voltage-responding fluorescent molecule, FluoVolt™ in response to potassium chloride. Interestingly, only differentiated PSA-NCAM+ cells were capable of spontaneous membrane oscillations. In summary, DPSCs contain a population of neuronal progenitors with enhanced neural differentiation and functional neural-like properties that can be effectively isolated with magnetic-activated cell sorting (MACS).

Drift of neural ensembles driven by slow fluctuations of intrinsic excitability.

Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not known. Since intrinsic neural excitability is suggested to play a key role in regulating memory allocation, fluctuations of excitability could bias the reactivation of previously stored memory ensembles and therefore act as a motor for drift. Here, we propose a rate-based plastic recurrent neural network with slow fluctuations of intrinsic excitability. We first show that subsequent reactivations of a neural ensemble can lead to drift of this ensemble. The model predicts that drift is induced by co-activation of previously active neurons along with neurons with high excitability which leads to remodeling of the recurrent weights. Consistent with previous experimental works, the drifting ensemble is informative about its temporal history. Crucially, we show that the gradual nature of the drift is necessary for decoding temporal information from the activity of the ensemble. Finally, we show that the memory is preserved and can be decoded by an output neuron having plastic synapses with the main region.