Brain Stores Research Articles

Orchestrated ensemble activities constitute a hippocampal memory engram

The brain stores and recalls memories through a set of neurons, termed engram cells. However, it is unclear how these cells are organized to constitute a corresponding memory trace. We established a unique imaging system that combines Ca2+ imaging and engram identification to extract the characteristics of engram activity by visualizing and discriminating between engram and non-engram cells. Here, we show that engram cells detected in the hippocampus display higher repetitive activity than non-engram cells during novel context learning. The total activity pattern of the engram cells during learning is stable across post-learning memory processing. Within a single engram population, we detected several sub-ensembles composed of neurons collectively activated during learning. Some sub-ensembles preferentially reappear during post-learning sleep, and these replayed sub-ensembles are more likely to be reactivated during retrieval. These results indicate that sub-ensembles represent distinct pieces of information, which are then orchestrated to constitute an entire memory.

Sparse neural codes and convexity

Determining how the brain stores information is one of the most pressing problems in neuroscience. In many instances, the collection of stimuli for a given neuron can be modeled by a convex set in $\mathbb{R}^d$. Combinatorial objects known as \emph{neural codes} can then be used to extract features of the space covered by these convex regions. We apply results from convex geometry to determine which neural codes can be realized by arrangements of open convex sets. We restrict our attention primarily to sparse codes in low dimensions. We find that intersection-completeness characterizes realizable $2$-sparse codes, and show that any realizable $2$-sparse code has embedding dimension at most $3$. Furthermore, we prove that in $\mathbb{R}^2$ and $\mathbb{R}^3$, realizations of $2$-sparse codes using closed sets are equivalent to those with open sets, and this allows us to provide some preliminary results on distinguishing which $2$-sparse codes have embedding dimension at most $2$.

Separating the present and the future.

The brain stores information that is needed immediately and information that will be needed in the future in different ways.

Memory systems 2018 - Towards a new paradigm.

The multiple memory systems theory (MMS) postulates that the brain stores information based on the independent and parallel activity of a number of modules, each with distinct properties, dynamics, and neural basis. Much of the evidence for this theory comes from dissociation studies indicating that damage to restricted brain areas cause selective types of memory deficits. MMS has been the prevalent paradigm in memory research for more than thirty years, even as it has been adjusted several times to accommodate new data. However, recent empirical results indicating that the memory systems are not always dissociable constitute a challenge to fundamental tenets of the current theory because they suggest that representations formed by individual memory systems can contribute to more than one type of memory-driven behavioral strategy. This problem can be addressed by applying a dynamic network perspective to memory architecture. According to this view, memory networks can reconfigure or transiently couple in response to environmental demands. Within this context, the neural network underlying a specific memory system can act as an independent unit or as an integrated component of a higher order meta-network. This dynamic network model proposes a way in which empirical evidence that challenges the idea of distinct memory systems can be incorporated within a modular memory architecture. The model also provides a framework to account for the complex interactions among memory systems demonstrated at the behavioral level. Advances in the study of dynamic networks can generate new ideas to experimentally manipulate and control memory in basic or clinical research.

Computational models of memory consolidation and long-term synaptic plasticity during sleep.

The brain stores memories by persistently changing the connectivity between neurons. Sleep is known to be critical for these changes to endure. Research on the neurobiology of sleep and the mechanisms of long-term synaptic plasticity has provided data in support of various theories of how brain activity during sleep affects long-term synaptic plasticity. The experimental findings - and therefore the theories - are apparently quite contradictory, with some evidence pointing to a role of sleep in the forgetting of irrelevant memories, whereas other results indicate that sleep supports the reinforcement of the most valuable recollections. A unified theoretical framework is in need. Computational modeling and simulation provide grounds for the quantitative testing and comparison of theoretical predictions and observed data, and might serve as a strategy to organize the rather complicated and diverse pool of data and methodologies used in sleep research. This review article outlines the emerging progress in the computational modeling and simulation of the main theories on the role of sleep in memory consolidation.

Tool Use and Generalized Motor Programs: We All Are Natural Born Poly-Dexters

For most people, human tool use is inextricably entwined with manual dexterity. This folk belief is widespread among scientists too. In this line, human tool use is based on motor programs about how the hand interacts with tools, implying that the use of end-effectors other than the hand should generate motor control difficulties (e.g., inability to reproduce a specific tool-use action over time), because these so-called programs characterize the spatiotemporal parameters of hand movements, but not of other end-effectors. To test this, we asked participants to perform three tool-use actions (e.g., pounding a nail) with four end-effectors (i.e., right foot, right elbow, left hand, right hand). We show that participants not only spontaneously performed the tool-use actions effectively, but also crucially kept tools’ spatiotemporal parameters constant among the end-effectors. This phenomenon, which we call poly-dexterity, is at odds with the view that the human brain stores hand-centered motor programs for tool use. Poly-dexterity is instead consistent with the idea that, once the tool-use action is formed mentally, general motor programs can be applied to a variety of end-effectors. Reversing the usual evolutionary perspective, our findings support that, in the course of evolution, manual dexterity has come after tool-use skills.

Disentangling specific memories

Neuroscience Each memory is stored in a distinct memory trace in the brain, in a specific population of neurons called engram cells. How does the brain store and define the identity of a specific memory when two memories interact and are encoded in a shared engram? Abdou et al. used optogenetic reactivation coupled with manipulations of long-term potentiation to analyze engrams that share neurons in the lateral amygdala (see the Perspective by Ramirez). Synapse-specific plasticity guaranteed the storage and the identity of individual memories in a shared engram. Moreover, synaptic plasticity between specific engram assemblies was necessary and sufficient for memory engram formation. Science , this issue p. [1227][1]; see also p. [1182][2] [1]: /lookup/doi/10.1126/science.aat3810 [2]: /lookup/doi/10.1126/science.aau0043

Danger Changes the Way the Mammalian Brain Stores Information About Innocuous Events: A Study of Sensory Preconditioning in Rats.

The amygdala is a critical substrate for learning about cues that signal danger. Less is known about its role in processing innocuous or background information. The present study addressed this question using a sensory preconditioning protocol in male rats. In each experiment, rats were exposed to pairings of two innocuous stimuli in stage 1, S2 and S1, and then to pairings of S1 and shock in stage 2. As a consequence of this training, control rats displayed defensive reactions (freezing) when tested with both S2 and S1. The freezing to S2 is a product of two associations formed in training: an S2-S1 association in stage 1 and an S1-shock association in stage 2. We examined the roles of two medial temporal lobe (MTL) structures in consolidation of the S2-S1 association: the perirhinal cortex (PRh) and basolateral complex of the amygdala (BLA). When the S2-S1 association formed in a safe context, its consolidation required neuronal activity in the PRh (but not BLA), including activation of AMPA receptors and MAPK signaling. In contrast, when the S2-S1 association formed in a dangerous context, or when the context was rendered dangerous immediately after the association had formed, its consolidation required neuronal activity in the BLA (but not PRh), including activation of AMPA receptors and MAPK signaling. These roles of the PRh and BLA show that danger changes the way the mammalian brain stores information about innocuous events. They are discussed with respect to danger-induced changes in stimulus processing.

How our sleeping brain stores away memories

At last, we've seen how the brain stores memories when we sleep. By scanning slumbering people, researchers have watched how the trace of a memory moves from one region of the brain to another. The initial memory trace kind of disappears, and at the same time, another emerges, says Shahab Vahdat at Stanford University in California. It is the first time memories have been observed being filed away in humans during sleep, he says. His team thinks that movement-related memories are transferred to deeper brain regions for long-term storage. This chimes with the hypothesis that the brain's cortex must free up space so that it can continue to learn new information, says Christoph Nissen at University Psychiatric Services in Bern, Switzerland

Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity.

It is widely believed that persistent neural activity underlies short-term memory. Yet, as we show, the degradation of information stored directly in such networks behaves differently from human short-term memory performance. We build a more general framework where memory is viewed as a problem of passing information through noisy channels whose degradation characteristics resemble those of persistent activity networks. If the brain first encoded the information appropriately before passing the information into such networks, the information can be stored substantially more faithfully. Within this framework, we derive a fundamental lower-bound on recall precision, which declines with storage duration and number of stored items. We show that human performance, though inconsistent with models involving direct (uncoded) storage in persistent activity networks, can be well-fit by the theoretical bound. This finding is consistent with the view that if the brain stores information in patterns of persistent activity, it might use codes that minimize the effects of noise, motivating the search for such codes in the brain.

A multisensory perspective on object memory

Traditional studies of memory and object recognition involved objects presented within a single sensory modality (i.e., purely visual or purely auditory objects). However, in naturalistic settings, objects are often evaluated and processed in a multisensory manner. This begets the question of how object representations that combine information from the different senses are created and utilised by memory functions. Here we review research that has demonstrated that a single multisensory exposure can influence memory for both visual and auditory objects. In an old/new object discrimination task, objects that were presented initially with a task-irrelevant stimulus in another sense were better remembered compared to stimuli presented alone, most notably when the two stimuli were semantically congruent. The brain discriminates between these two types of object representations within the first 100ms post-stimulus onset, indicating early “tagging” of objects/events by the brain based on the nature of their initial presentation context. Interestingly, the specific brain networks supporting the improved object recognition vary based on a variety of factors, including the effectiveness of the initial multisensory presentation and the sense that is task-relevant. We specify the requisite conditions for multisensory contexts to improve object discrimination following single exposures, and the individual differences that exist with respect to these improvements. Our results shed light onto how memory operates on the multisensory nature of object representations as well as how the brain stores and retrieves memories of objects.

Linking actions and objects: Context-specific learning of novel weight priors

Distinct explicit and implicit memory processes support weight predictions used when lifting objects and making perceptual judgments about weight, respectively. The first time that an object is encountered weight is predicted on the basis of learned associations, or priors, linking size and material to weight. A fundamental question is whether the brain maintains a single, global representation of priors, or multiple representations that can be updated in a context specific way. A second key question is whether the updating of priors, or the ability to scale lifting forces when repeatedly lifting unusually weighted objects requires focused attention. To investigate these questions we compared the adaptability of weight predictions used when lifting objects and judging their weights in different groups of participants who experienced size-weight inverted objects passively (with the objects placed on the hands) or actively (where participants lift the objects) under full or divided attention. To assess weight judgments we measured the size-weight illusion after every 20 trials of experience with the inverted objects both passively and actively. The attenuation of the illusion that arises when lifting inverted object was found to be context-specific such that the attenuation was larger when the mode of interaction with the inverted objects matched the method of assessment of the illusion. Dividing attention during interaction with the inverted objects had no effect on attenuation of the illusion, but did slow the rate at which lifting forces were scaled to the weight inverted objects. These findings suggest that the brain stores multiple representations of priors that are context specific, and that focused attention is important for scaling lifting forces, but not for updating weight predictions used when judging object weight.

Electrophysiological Evidence for Early and Interactive Symbol Access and Rule Processing in Retrieving and Combining Language Constructions.

The human brain stores an immense repertoire of linguistic symbols (morphemes, words) and combines them into a virtually unlimited set of well-formed strings (phrases, sentences) that serve as efficient communicative tools. Communication is hampered, however, if strings include meaningless items (e.g., "pseudomorphemes"), or if the rules for combining string elements are violated. Prior research suggests that, when participants attentively process sentences in a linguistic task, syntactic processing can occur quite early, but lexicosemantic processing, or any interaction involving this factor, is manifest later in time (ca. 400 msec or later). In contrast, recent evidence from passive speech perception paradigms suggests early processing of both combinatorial (morphosyntactic) and storage-related (lexicosemantic) properties. A crucial question is whether these parallel processes might also interact early in processing. Using ERPs in an orthogonal design, we presented spoken word strings to participants while they were distracted from incoming speech to obtain information about automatic language processing mechanisms unaffected by task-related strategies. Stimuli were either (1) well-formed miniconstructions (short pronoun-verb sentences), (2) "unstored" strings containing a pseudomorpheme, (3) "ill-combined" strings violating subject-verb agreement rules, or (4) double violations including both types of errors. We found that by 70-210 msec after the onset of the phrase-final syllable that disambiguated the strings, interactions of lexicosemantic and morphosyntactic deviance were evident in the ERPs. These results argue against serial processing of lexical storage, morphosyntactic combination and their interaction, and in favor of early, simultaneous, and interactive processing of symbols and their combinatorial structures.

Holy Hippocampus: A Conversation in Couplets

Holy Hippocampus:A Conversation in Couplets Maureen Seaton (bio) and Denise Duhamel (bio) The human brain stores a million gigabytes of memory, so why is itI can’t recall where I plunked down my keys or orange flash drive? If only I could access the words of Proust I read at twenty or whatyou said yesterday about how to treat a cold—was it frankincense? Frank remembers you so clearly but you can’t access his face evenlooking at his picture. High school classmates, grade school teachers: a blur! I’ve always wanted to tell you that my mother with Alzheimer’srecalled her Carteret childhood in encyclopedic detail—but that was it. Did she forget being a mother and your childhood? I love reimaginedretro postcards: I left my baby on the bus! Or I forgot to have children. That’s my Mom! Unable to spell the world backward by fifty-five. d-lr-o-w. They say the brain alters a memory simply by remembering it. That is why I remember my second-grade accordion as goldbut in pictures it is maroon. In one my hair has a green tint—impossible, or ahead of your time, as always! They also say our short-term memoryholds only seven pieces of information at a time. Holy Hippocampus! Number 8: Where did I park my car? nudges out Conan O’Brien’s punchline and whether or not I turned off the coffee pot. My remote key beeps, [End Page 93] but the kid who insisted on pushing my grocery cart is telling me wherehe snowshoes (9), my cell’s ringing in the surreal distance of some pocket in my jacket or purse or reusable tote and I fear someone I loveis in trouble—an accident, a broken heart, a bounced check. Hello? My brain needs an upgrade. Higher resolution for those mistywatercolored tidbits that pixilate rebelliously as I furrow my brow. What I do remember is Bert’s chalk sidewalk drawing turninginto a painting when it rained. Or was it Mary Poppins’ magic? I know you’re not thinking I’d remember a movie I only saw five times,are you? What about that annoying link between memory and hormones? Or that stress kills memory cells? I read that doing certain taskscan stimulate the growth of brain cells, but I can’t remember which tasks. Well, we’re both good at math! Today I read that it takes the brain 80milliseconds to process info. For that time we’re actually living in the past. [End Page 94] Maureen Seaton Maureen Seaton has authored numerous poetry collections, both solo and collaborative—most recently, with Denise Duhamel: Caprice: Collected, Uncol-lected, and New Collaborations (Sibling Rivalry Press). She currently teaches in the Creative Writing Program at the University of Miami. Denise Duhamel Denise Duhamel’s most recent book of poetry is Scald (Pittsburgh). Blowout (Pittsburgh) was a finalist for the National Book Critics Circle Award. Her other titles include Ka-Ching! (Pittsburgh); Two and Two (Pittsburgh); Queen for a Day: Selected and New Poems (Pittsburgh); The Star-Spangled Banner (Southern Illinois up); and Kinky (Orhisis). She and Maureen Seaton co-authored Caprice: Collected, Uncollected, and New Collaborations (Sibling Rivalry Press). Duhamel is a recipient of fellowships from the Guggenheim Foundation and the nea. The guest editor of The Best American Poetry 2013, she is a professor at Florida International University in Miami. Copyright © 2017 University of Nebraska Press

Rapid and independent memory formation in the parietal cortex

Previous evidence indicates that the brain stores memory in two complementary systems, allowing both rapid plasticity and stable representations at different sites. For memory to be established in a long-lasting neocortical store, many learning repetitions are considered necessary after initial encoding into hippocampal circuits. To elucidate the dynamics of hippocampal and neocortical contributions to the early phases of memory formation, we closely followed changes in human functional brain activity while volunteers navigated through two different, initially unknown virtual environments. In one condition, they were able to encode new information continuously about the spatial layout of the maze. In the control condition, no information could be learned because the layout changed constantly. Our results show that the posterior parietal cortex (PPC) encodes memories for spatial locations rapidly, beginning already with the first visit to a location and steadily increasing activity with each additional encounter. Hippocampal activity and connectivity between the PPC and hippocampus, on the other hand, are strongest during initial encoding, and both decline with additional encounters. Importantly, stronger PPC activity related to higher memory-based performance. Compared with the nonlearnable control condition, PPC activity in the learned environment remained elevated after a 24-h interval, indicating a stable change. Our findings reflect the rapid creation of a memory representation in the PPC, which belongs to a recently proposed parietal memory network. The emerging parietal representation is specific for individual episodes of experience, predicts behavior, and remains stable over offline periods, and must therefore hold a mnemonic function.

How Old Brains Got New Neurons

The brain is the command center of our bodies, integrating information from the periphery and providing sophisticated control over behavior. The brain stores memories and is considered to determine who we are. This concept goes hand in hand with an important feature of the brain: neurons are some of the few cell types in the body that do not divide once they have matured, meaning that the sets of neurons generated during our in utero and early postnatal development are the only building blocks of the brain.

Polytopes as vehicles of informational content in feedforward neural networks

Localizing content in neural networks provides a bridge to understanding the way in which the brain stores and processes information. In this paper, I propose the existence of polytopes in the state space of the hidden layer of feedforward neural networks as vehicles of content. I analyze these geometrical structures from an information-theoretic point of view, invoking mutual information to help define the content stored within them. I establish how this proposal addresses the problem of misclassification and provide a novel solution to the disjunction problem, which hinges on the precise nature of the causal-informational framework for content advocated herein.

Attention promotes episodic encoding by stabilizing hippocampal representations

Attention influences what is later remembered, but little is known about how this occurs in the brain. We hypothesized that behavioral goals modulate the attentional state of the hippocampus to prioritize goal-relevant aspects of experience for encoding. Participants viewed rooms with paintings, attending to room layouts or painting styles on different trials during high-resolution functional MRI. We identified template activity patterns in each hippocampal subfield that corresponded to the attentional state induced by each task. Participants then incidentally encoded new rooms with art while attending to the layout or painting style, and memory was subsequently tested. We found that when task-relevant information was better remembered, the hippocampus was more likely to have been in the correct attentional state during encoding. This effect was specific to the hippocampus, and not found in medial temporal lobe cortex, category-selective areas of the visual system, or elsewhere in the brain. These findings provide mechanistic insight into how attention transforms percepts into memories.

Mathematical modelling of ICAN-mediated persistent firing in hippocampal neurons

Persistent neural activity has been the focus of neuroscientific research since it was first associated with complex cognitive behaviours. In particular, persistent firing has long been thought to be the neural mechanisms underlying short-term memory encoding and storage [1]. This activity is often elicited by short transient stimuli that have to be retained in memory for long delay periods, in the order of several seconds, after the original stimulus disappeared. In this scenario, the brain stores information for future execution of action depending on that information. Persistent activity elicited in a recurrent network comprising strong excitation in the local circuit has been extensively described in the literature (for a review see [2]). However, recent findings have shown that memory can also be encoded in brain regions which do not display such recurrent connection topology, including the CA1 hippocampal area [3]. Emerging studies are pointing towards intrinsic neural mechanisms independent of synaptic connections, as a complementary mechanism for the maintenance of persistent activity in the hippocampus [4]. These include various cytoplasmic currents flowing through the membrane, characterised by slow ion channel kinetics, and particular neurotransmitter modulation. Our work investigates persistent firing activity in networks of hippocampal neurons, elicited by leveraging intrinsic currents rather than network dynamics. Building on previous findings [5], we model a hippocampal pyramidal neuron using the Hodgkin-Huxley model, with low-threshold Ca2+ currents governing the inward flow of calcium ions in the cell membrane. The intracellular calcium concentration mediates the opening of calcium-activated non-specific (CAN) ion channels [6], which causes an increase in the ionic flow through the cell membrane. Therefore the CAN channels equip the neuron with an after-spike depolarisation mechanism, which enables it to emit action potentials in the absence of external stimulation. Given a transient 250ms 200pA current injection, the neuron is capable of eliciting and maintaining persistent activity with a firing rate of 6Hz for long delay periods (~30s). Moreover, this behaviour is in accord with that displayed in neural recordings of hippocampal slice preparations [4]. Connecting these persistent firing neurons in a network comprising strong local excitation yields a wide range of behaviours depending on the interaction between CAN and synaptic currents. Indeed, our network model is capable of displaying rhythmic behaviour in the form of short synchronised bursts with intra-burst frequencies of 20-40Hz and inter-burst frequencies of 3Hz. These results hint towards a possible mechanism for the generation of memory-related oscillatory activity in the hippocampus.

Formal concept analysis approach to cognitive functionalities of bidirectional associative memory

Abstract Pattern association is one among the ways through which human brain stores and recalls information. From the literature, it is evident that cognitive abilities of human brain such as learning, memorizing, recalling and updating of information are performed via concepts and their connections. In this work we have made use of Formal Concept Analysis (FCA), a mathematical framework for data and knowledge processing, to represent memories and to perform some of the cognitive functions of human brain. In particular, we model the functionalities of bidirectional associative memories. The proposed model can learn, memorize the learnt information, bi-directionally recall the information that is associated with the presented cue with the help of object-attribute relations that exists in the scenario and update the knowledge when there is a change in the considered scenario. Also when a noisy cue is given, the model is capable of recalling the most closely associated pattern by exploiting the concept hierarchy principle of FCA. Similarly, when a new information is presented on a learnt scenario, the proposed model can update its knowledge by avoiding the need to re-learn scenario. We illustrate the proposed model with a case study and validate with experiments on few real world datasets.