What does engram encode?: Heterogeneous memory engrams for different aspects of experience

Long-lasting synaptic changes within the neuronal network mediate memory. Neurons bearing such physical traces of memory (memory engram cells) are often equated with neurons expressing immediate early genes (IEGs) during a specific experience. However, past studies observed the expression of different IEGs in non-overlapping neurons or synaptic plasticity in neurons that do not express a particular IEG. Importantly, recent studies revealed that distinct subsets of neurons expressing different IEGs or even IEG negative-(yet active) neurons support different aspects of memory or computation, suggesting a more complex nature of memory engram cells than previously thought. In this short review, we introduce studies revealing such heterogeneous composition of the memory engram and discuss how the memory system benefits from it.     

Basic mechanisms for graded persistent activity: discrete attractors,continuous attractors,and dynamic representations

Persistent neural activity is observed in many systems, and is thought to be a neural substrate for holding memories over time delays of a few seconds. Recent work has addressed two issues. First, how can networks of neurons robustly hold such an active memory? Computer systems obtain significant robustness to noise by approximating analogue quantities with discrete digital representations. In a similar manner, theoretical models of persistent activity in spiking neurons have shown that the most robust and stable way to store the short-term memory of a continuous parameter is to approximate it with a discrete representation. This general idea applies very broadly to mechanisms that range from biochemical networks to single cells and to large circuits of neurons. Second, why is it commonly observed that persistent activity in the cortex can be strongly time-varying? This observation is almost ubiquitous, and therefore must be taken into account in our models and our understanding of how short-term memories are held in the cortex.     

Stress,hippocampal neurogenesis and cognition: functional correlations

The brain of many species including humans, harbors stem cells that continue to generate new neurons up into adulthood. This form of structural plasticity occurs in a limited number of brain regions, i.e. the subventricular zone and the hippocampal dentate gyrus and is regulated by environmental and hormonal factors. In this minireview, we provide an overview of the effects of stress and glucocorticoid hormones on adult hippocampal neurogenesis and discuss how these effects may be relevant for cognitive function and possibly, brain disease. While its exact functional role remains elusive, adult neurogenesis has been implicated in learning and memory, fear and mood regulation and recently, adult-born neurons were found to be involved in specific cognitive functions such as pattern separation (i.e. the ability to form unique memory representations) and cognitive flexibility. The process of adult neurogenesis is influenced by several factors; whereas e.g. exercise stimulates, exposure to stress and stress hormones generally inhibit neurogenesis. Effects of acute, mild stress are generally short-lasting and recover quickly, but chronic or severe forms of stress can induce lasting reductions in adult neurogenesis. Some of the inhibitory effects of stress can be rescued by exercise, by allowing a period of recovery from stress, by drugs that target the stress system, or by some, but not all, antidepressants. Stress may, partly through its effects on adult neurogenesis, alter structure and plasticity of the hippocampal circuit. This can lead to subsequent changes in stress responsivity and aspects of memory processing, which may be particularly relevant for stress related psychopathology or brain diseases that involve perturbed memory processing.     

Adult neurogenesis and pattern separation in rodents: A critical evaluation of data,tasks and interpretation

The ability to discriminate and store similar inputs as distinct representations in memory is thought to rely on a process called pattern separation in the dentate gyrus of the hippocampus. Recent computational and empirical findings support a role for adult-born granule neurons in spatial pattern separation. We reviewed rodent studies that have manipulated both hippocampal adult neurogenesis and assessed pattern separation. The majority of studies report a supporting role of adult born neurons in pattern separation as measured at the behavioral level. However, closer evaluation of the published findings reveals variation in both pattern separation tasks and in the interpretation of behavioral performance that, taken together, suggests that the role of hippocampal adult neurogenesis in pattern separation may be less established than is currently assumed. Assessment of pattern separation at the network level through the use of immediate early gene expression, optogenetic, pharmacogenetic and/or in vivo electrophysiology studies could be instrumental in further confirming a role of adult born neurons in pattern separation further. Finally, hippocampal adult neurogenesis and pattern separation are not an exclusive pair, as evidence for hippocampal adult neurogenesis contributing to the temporal separation of events in memory, forgetting and cognitive flexibility has also been found. We conclude that whereas current empirical evidence for the involvement of hippocampal adult neurogenesis in pattern separation seems supportive, there is a need for careful interpretation of behavioral findings and an integration of the various proposed functions of adult born neurons.     

Synaptic plasticity, memory and the hippocampus: a neural network approach to causality

Two facts about the hippocampus have been common currency among neuroscientists for several decades. First, lesions of the hippocampus in humans prevent the acquisition of new episodic memories; second, activity-dependent synaptic plasticity is a prominent feature of hippocampal synapses. Given this background, the hypothesis that hippocampus-dependent memory is mediated, at least in part, by hippocampal synaptic plasticity has seemed as cogent in theory as it has been difficult to prove in practice. Here we argue that the recent development of transgenic molecular devices will encourage a shift from mechanistic investigations of synaptic plasticity in single neurons towards an analysis of how networks of neurons encode and represent memory, and we suggest ways in which this might be achieved. In the process, the hypothesis that synaptic plasticity is necessary and sufficient for information storage in the brain may finally be validated.     

The search for a hippocampal engram

Understanding the molecular and cellular changes that underlie memory, the engram, requires the identification, isolation and manipulation of the neurons involved. This presents a major difficulty for complex forms of memory, for example hippocampus-dependent declarative memory, where the participating neurons are likely to be sparse, anatomically distributed and unique to each individual brain and learning event. In this paper, I discuss several new approaches to this problem. In vivo calcium imaging techniques provide a means of assessing the activity patterns of large numbers of neurons over long periods of time with precise anatomical identification. This provides important insight into how the brain represents complex information and how this is altered with learning. The development of techniques for the genetic modification of neural ensembles based on their natural, sensory-evoked, activity along with optogenetics allows direct tests of the coding function of these ensembles. These approaches provide a new methodological framework in which to examine the mechanisms of complex forms of learning at the level of the neurons involved in a specific memory.     

Epigenetic mechanisms in cognition

Although the critical role for epigenetic mechanisms in development and cell differentiation has long been appreciated, recent evidence reveals that these mechanisms are also employed in postmitotic neurons as a means of consolidating and stabilizing cognitive-behavioral memories. In this review, we discuss evidence for an "epigenetic code" in the central nervous system that mediates synaptic plasticity, learning, and memory. We consider how specific epigenetic changes are regulated and may interact with each other during memory formation and how these changes manifest functionally at the cellular and circuit levels. We also describe a central role for mitogen-activated protein kinases in controlling chromatin signaling in plasticity and memory. Finally, we consider how aberrant epigenetic modifications may lead to cognitive disorders that affect learning and memory, and we review the therapeutic potential of epigenetic treatments for the amelioration of these conditions.     

The chronotron: a neuron that learns to fire temporally precise spike patterns

In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.     

A pair of inhibitory neurons are required to sustain labile memory in the Drosophila mushroom body

Labile memory is thought to be held in the brain as persistent neural network activity. However, it is not known how biologically relevant memory circuits are organized and operate. Labile and persistent appetitive memory in Drosophila requires output after training from the α'β' subset of mushroom body (MB) neurons and from a pair of modulatory dorsal paired medial (DPM) neurons. DPM neurons innervate the entire MB lobe region and appear to be pre- and postsynaptic to the MB, consistent with a recurrent network model. Here we identify a role after training for synaptic output from the GABAergic anterior paired lateral (APL) neurons. Blocking synaptic output from APL neurons after training disrupts labile memory but does not affect long-term memory. APL neurons contact DPM neurons most densely in the α'β' lobes, although their processes are intertwined and contact throughout all of the lobes. Furthermore, APL contacts MB neurons in the α' lobe but makes little direct contact with those in the distal α lobe. We propose that APL neurons provide widespread inhibition to stabilize and maintain synaptic specificity of a labile memory trace in a recurrent DPM and MB α'β' neuron circuit.     

Cultured Cortical Neurons Can Perform Blind Source Separation According to the Free-Energy Principle

Blind source separation is the computation underlying the cocktail party effect––a partygoer can distinguish a particular talker’s voice from the ambient noise. Early studies indicated that the brain might use blind source separation as a signal processing strategy for sensory perception and numerous mathematical models have been proposed; however, it remains unclear how the neural networks extract particular sources from a complex mixture of inputs. We discovered that neurons in cultures of dissociated rat cortical cells could learn to represent particular sources while filtering out other signals. Specifically, the distinct classes of neurons in the culture learned to respond to the distinct sources after repeating training stimulation. Moreover, the neural network structures changed to reduce free energy, as predicted by the free-energy principle, a candidate unified theory of learning and memory, and by Jaynes’ principle of maximum entropy. This implicit learning can only be explained by some form of Hebbian plasticity. These results are the first in vitro (as opposed to in silico) demonstration of neural networks performing blind source separation, and the first formal demonstration of neuronal self-organization under the free energy principle.     

Synaptic Potentiation Facilitates Memory-like Attractor Dynamics in Cultured In Vitro Hippocampal Networks

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more “errant” spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.     

Multiple forms of activity-dependent competition refine hippocampal circuits in vivo

Efficient memory formation relies on the establishment of functional hippocampal circuits. It has been proposed that synaptic connections are refined by neural activity to form functional brain circuitry. However, it is not known whether and how hippocampal connections are refined by neural activity in vivo. Using a mouse genetic system in which restricted populations of neurons in the hippocampal circuit are inactivated, we show that inactive axons are eliminated after they develop through a competition with active axons. Remarkably, in the dentate gyrus, which undergoes neurogenesis throughout life, axon refinement is achieved by a competition between mature and young neurons. These results demonstrate that activity-dependent competition plays multiple roles in the establishment of functional memory circuits in vivo.     

Memory retention in pyramidal neurons: a unified model of energy-based homo and heterosynaptic plasticity with homeostasis

The brain can learn new tasks without forgetting old ones. This memory retention is closely associated with the long-term stability of synaptic strength. To understand the capacity of pyramidal neurons to preserve memory under different tasks, we established a plasticity model based on the postsynaptic membrane energy state, in which the change in synaptic strength depends on the difference between the energy state after stimulation and the resting energy state. If the post-stimulation energy state is higher than the resting energy state, then synaptic depression occurs. On the contrary, the synapse is strengthened. Our model unifies homo- and heterosynaptic plasticity and can reproduce synaptic plasticity observed in multiple experiments, such as spike-timing-dependent plasticity, and cooperative plasticity with few and common parameters. Based on the proposed plasticity model, we conducted a simulation study on how the activation patterns of dendritic branches by different tasks affect the synaptic connection strength of pyramidal neurons. We further investigate the formation mechanism by which different tasks activate different dendritic branches. Simulation results show that compare to the classic plasticity model, the plasticity model we proposed can achieve a better spatial separation of different branches activated by different tasks in pyramidal neurons, which deepens our insight into the memory retention mechanism of brains.     

Inception of a false memory by optogenetic manipulation of a hippocampal memory engram

Memories can be easily distorted, and a lack of relevant animal models has largely hindered our understanding of false-memory formation. Here, we first identified a population of cells in the dentate gyrus (DG) of the hippocampus that bear the engrams for a specific context; these cells were naturally activated during the encoding phase of fear conditioning and their artificial reactivation using optogenetics in an unrelated context was sufficient for inducing the fear memory specific to the conditioned context. In a further study, DG or CA1 neurons activated by exposure to a particular context were labelled with channelrhodopsin-2 (ChR2). These neurons were later optically reactivated during fear conditioning in a different context. The DG experimental group showed increased freezing in the original context in which a foot shock was never delivered. The recall of this false memory was context specific, activated similar downstream regions engaged during natural fear-memory recall, and was also capable of driving an active fear response. Together, our data demonstrate that by substituting a natural conditioned stimulus with optogenetically reactivated DG cells that bear contextual memory engrams, it is possible to incept an internally and behaviourally represented false fear memory.     

Pattern recognition and associative memory as dynamical processes in a synergetic system

We consider a model for associative memory and pattern recognition which was devised by Haken (1987b). This model treats the activity of the neurons as continuous variables and exploits an analogy with pattern formation in synergetic systems. The capability of such a system to act as associative memory is demonstrated by the reconstruction of faces which are partially offered to the system, and which are restored by the corresponding dynamical process. We demonstrate how this model can be cast into a form which is translation invariant and how partially hidden faces in scenes can be recognized by means of the control of attention parameters of specific patterns.     

Spatial relational memory requires hippocampal adult neurogenesis

The dentate gyrus of the hippocampus is one of the few regions of the mammalian brain where new neurons are generated throughout adulthood. This adult neurogenesis has been proposed as a novel mechanism that mediates spatial memory. However, data showing a causal relationship between neurogenesis and spatial memory are controversial. Here, we developed an inducible transgenic strategy allowing specific ablation of adult-born hippocampal neurons. This resulted in an impairment of spatial relational memory, which supports a capacity for flexible, inferential memory expression. In contrast, less complex forms of spatial knowledge were unaltered. These findings demonstrate that adult-born neurons are necessary for complex forms of hippocampus-mediated learning.     

Is bigger always better? A critical appraisal of the use of volumetric analysis in the study of the hippocampus

A well-developed spatial memory is important for many animals, but appears especially important for scatter-hoarding species. Consequently, the scatter-hoarding system provides an excellent paradigm in which to study the integrative aspects of memory use within an ecological and evolutionary framework. One of the main tenets of this paradigm is that selection for enhanced spatial memory for cache locations should specialize the brain areas involved in memory. One such brain area is the hippocampus (Hp). Many studies have examined this adaptive specialization hypothesis, typically relating spatial memory to Hp volume. However, it is unclear how the volume of the Hp is related to its function for spatial memory. Thus, the goal of this article is to evaluate volume as a main measurement of the degree of morphological and physiological adaptation of the Hp as it relates to memory. We will briefly review the evidence for the specialization of memory in food-hoarding animals and discuss the philosophy behind volume as the main currency. We will then examine the problems associated with this approach, attempting to understand the advantages and limitations of using volume and discuss alternatives that might yield more specific hypotheses. Overall, there is strong evidence that the Hp is involved in the specialization of spatial memory in scatter-hoarding animals. However, volume may be only a coarse proxy for more relevant and subtle changes in the structure of the brain underlying changes in behaviour. To better understand the nature of this brain/memory relationship, we suggest focusing on more specific and relevant features of the Hp, such as the number or size of neurons, variation in connectivity depending on dendritic and axonal arborization and the number of synapses. These should generate more specific hypotheses derived from a solid theoretical background and should provide a better understanding of both neural mechanisms of memory and their evolution.     

Pavlovian fear conditioning activates a common pattern of neurons in the lateral amygdala of individual brains

Understanding the physical encoding of a memory (the engram) is a fundamental question in neuroscience. Although it has been established that the lateral amygdala is a key site for encoding associative fear memory, it is currently unclear whether the spatial distribution of neurons encoding a given memory is random or stable. Here we used spatial principal components analysis to quantify the topography of activated neurons, in a select region of the lateral amygdala, from rat brains encoding a Pavlovian conditioned fear memory. Our results demonstrate a stable, spatially patterned organization of amygdala neurons are activated during the formation of a Pavlovian conditioned fear memory. We suggest that this stable neuronal assembly constitutes a spatial dimension of the engram.     

A computer model for learning processes and the role of the cerebral commissures

A computer model of the two brain hemispheres is constructed of discrete populations of neurons, and it is shown to exhibit the characteristics of the great cerebral commissures, as has been pointed out by Sperry and others. For the range of parameters used we find that such systems respond in a specific manner to specific stimuli, and furthermore, whatever memory is transferred to one simulated hemisphere is also transferred to the other. However, this behavior changes when the two hemispheres are separated. We find that memory is not transferred from one hemisphere to the other when the interconnecting commissures are severed. The above findings verify Sperry's experimental observation that the split brain behaves as if it were indeed two separate brains, each performing concurrently and simultaneously diametrically opposite tasks.