Memory Takes Time

Nanofluidic logic with mechano-ionic memristive switches

Neuromorphic systems are typically based on nanoscale electronic devices, but nature relies on ions for energy-efficient information processing. Nanofluidic memristive devices could thus potentially be used to construct electrolytic computers that mimic the brain down to its basic principles of operation. Here we report a nanofluidic device that is designed for circuit-scale in-memory processing. The device, which is fabricated using a scalable process, combines single-digit nanometric confinement and large entrance asymmetry and operates on the second timescale with a conductance ratio in the range of 9 to 60. In operando optical microscopy shows that the memory capabilities are due to the reversible formation of liquid blisters that modulate the conductance of the device. We use these mechano-ionic memristive switches to assemble logic circuits composed of two interactive devices and an ohmic resistor.

Decreased intrinsic neural timescale in treatment-naïve adolescent depression

BACKGROUND

Major depressive disorder (MDD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in emotional and cognitive processes, whose neurobiological basis remains unclear. In this study, we applied a relatively new developed resting-state functional magnetic resonance imaging (rs-fMRI) method of intrinsic neural timescale (INT), which reflects how long neural information is stored in a local brain area and reflects an ability of information integration, to investigate the local intrinsic neural dynamics using univariate and multivariate analyses in adolescent depression.

METHOD

Based on the rs-fMRI data of sixty-six treatment-naïve adolescents with MDD and fifty-two well-matched healthy controls (HCs), we calculated an INT by assessing the magnitude of autocorrelation of the resting-state brain activity, and then compared the difference of INT between the two groups. Correlation between abnormal INT and clinical features was performed. We also utilized multivariate pattern analysis to determine whether INT could differentiate MDD patients from HCs at the individual level.

RESULT

Compared with HCs, patients with MDD showed shorter INT widely distributed in cortical and partial subcortical regions. Interestingly, the decreased INT in the left hippocampus was related to disease severity of MDD. Furthermore, INT can distinguish MDD patients from HCs with the most discriminative regions located in the dorsolateral prefrontal cortex, angular, middle occipital gyrus, and cerebellar posterior lobe.

CONCLUSION

Our research aids in advancing understanding the brain abnormalities of treatment-naïve adolescents with MDD from the perspective of the local neural dynamics, highlighting the significant role of INT in understanding neurophysiological mechanisms. This study shows that the altered intrinsic timescales of local neural signals widely distributed in higher-order brain cortices regions may be the neurodynamic basis of cognitive and emotional disturbances in MDD patients, and provides preliminary support for the suggestion that these could be used to aid the identification of MDD patients in clinical practice.

The cognitive impact of light: illuminating ipRGC circuit mechanisms

Ever-present in our environments, light entrains circadian rhythms over long timescales, influencing daily activity patterns, health and performance. Increasing evidence indicates that light also acts independently of the circadian system to directly impact physiology and behaviour, including cognition. Exposure to light stimulates brain areas involved in cognition and appears to improve a broad range of cognitive functions. However, the extent of these effects and their mechanisms are unknown. Intrinsically photosensitive retinal ganglion cells (ipRGCs) have emerged as the primary conduit through which light impacts non-image-forming behaviours and are a prime candidate for mediating the direct effects of light on cognition. Here, we review the current state of understanding of these effects in humans and mice, and the tools available to uncover circuit-level and photoreceptor-specific mechanisms. We also address current barriers to progress in this area. Current and future efforts to unravel the circuits through which light influences cognitive functions may inform the tailoring of lighting landscapes to optimize health and cognitive function.

Why death and aging ? All memories are imperfect

Recent papers have emphasized the primary role of cellular information management in biological and evolutionary development. In this framework, intelligent cells collectively measure environmental cues to improve informational validity to support natural cellular engineering as collaborative decision-making and problem-solving in confrontation with environmental stresses. These collective actions are crucially dependent on cell-based memories as acquired patterns of response to environmental stressors. Notably, in a cellular self-referential framework, all biological information is ambiguous. This conditional requirement imposes a previously unexplored derivative. All cellular memories are imperfect. From this atypical background, a novel theory of aging and death is proposed. Since cellular decision-making is memory-dependent and biology is a continuous natural learning system, the accumulation of previously acquired imperfect memories eventually overwhelms the flexibility cells require to react adroitly to contemporaneous stresses to support continued cellular homeorhetic balance. The result is a gradual breakdown of the critical ability to efficiently measure environmental information and effect cell-cell communication. This age-dependent accretion governs senescence, ultimately ending in death as an organism-wide failure of cellular networking. This approach to aging and death is compatible with all prior theories. Each earlier approach illuminates different pertinent cellular signatures of this ongoing, obliged, living process.

Pattern detection in the TGFβ cascade controls the induction of long-term synaptic plasticity

Transforming growth factor β (TGFβ) is required for long-term memory (LTM) for sensitization in Aplysia. When LTM is induced using a two-trial training protocol, TGFβ inhibition only blocks LTM when administrated at the second, not the first trial. Here, we show that TGFβ acts as a "repetition detector" during the induction of two-trial LTM. Secretion of the biologically inert TGFβ proligand must coincide with its proteolytic activation by the Bone morphogenetic protein-1 (BMP-1/Tolloid) metalloprotease, which occurs specifically during trial two of our two-trial training paradigm. This paradigm establishes long-term synaptic facilitation (LTF), the cellular correlate of LTM. BMP-1 application paired with a single serotonin (5HT) pulse induced LTF, whereas neither a single 5HT pulse nor BMP-1 alone effectively did so. On the other hand, inhibition of endogenous BMP-1 activity blocked the induction of two-trial LTF. These results suggest a unique role for TGFβ in the interaction of repeated trials: during learning, repeated stimuli engage separate steps of the TGFβ cascade that together are necessary for the induction of long-lasting memories.

The Dynamic Relationship between the Glymphatic System, Aging, Memory, and Sleep

The process of memory entails the activation of numerous neural networks and biochemical pathways throughout the brain. The phenomenon of memory decline in relation to aging has been the subject of extensive research for several decades. The correlation between the process of aging and memory is intricate and has various aspects to consider. Throughout the aging process, there are various alterations that take place within the brain and, as expected, affect other functions that have already been linked to memory and its function such as involving microcirculation and sleep. Recent studies provide an understanding of how these mechanisms may be interconnected through the relatively new concept of the glymphatic system. The glymphatic system is strongly correlated to sleep processes. Sleep helps the glymphatic system remove brain waste solutes. Astrocytes expand and contract to form channels for cerebrospinal fluid (CSF) to wash through the brain and eliminate waste. However, the details have not been totally elusive, but the discovery of what we call the glymphatic system enables us to connect many pieces of physiology to understand how such factors are interconnected and the interplay between them. Thus, the purpose of this review is to discuss how the glymphatic system, sleep, memory, and aging are interconnected through a network of complex mechanisms and dynamic interactions.

Prediction in cultured cortical neural networks

Theory suggest that networks of neurons may predict their input. Prediction may underlie most aspects of information processing and is believed to be involved in motor and cognitive control and decision-making. Retinal cells have been shown to be capable of predicting visual stimuli, and there is some evidence for prediction of input in the visual cortex and hippocampus. However, there is no proof that the ability to predict is a generic feature of neural networks. We investigated whether random in vitro neuronal networks can predict stimulation, and how prediction is related to short- and long-term memory. To answer these questions, we applied two different stimulation modalities. Focal electrical stimulation has been shown to induce long-term memory traces, whereas global optogenetic stimulation did not. We used mutual information to quantify how much activity recorded from these networks reduces the uncertainty of upcoming stimuli (prediction) or recent past stimuli (short-term memory). Cortical neural networks did predict future stimuli, with the majority of all predictive information provided by the immediate network response to the stimulus. Interestingly, prediction strongly depended on short-term memory of recent sensory inputs during focal as well as global stimulation. However, prediction required less short-term memory during focal stimulation. Furthermore, the dependency on short-term memory decreased during 20 h of focal stimulation, when long-term connectivity changes were induced. These changes are fundamental for long-term memory formation, suggesting that besides short-term memory the formation of long-term memory traces may play a role in efficient prediction.

Precise timing of ERK phosphorylation/dephosphorylation determines the outcome of trial repetition during long-term memory formation

Two-trial learning in Aplysia reveals nonlinear interactions between training trials: A single trial has no effect, but two precisely spaced trials induce long-term memory. Extracellularly regulated kinase (ERK) activity is essential for intertrial interactions, but the mechanism remains unresolved. A combination of immunochemical and optogenetic tools reveals unexpected complexity of ERK signaling during the induction of long-term synaptic facilitation by two spaced pulses of serotonin (5-hydroxytryptamine, 5HT). Specifically, dual ERK phosphorylation at its activating TxY motif is accompanied by dephosphorylation at the pT position, leading to a buildup of inactive, singly phosphorylated pY-ERK. Phosphorylation and dephosphorylation occur concurrently but scale differently with varying 5HT concentrations, predicting that mixed two-trial protocols involving both "strong" and "weak" 5HT pulses should be sensitive to the precise order and timing of trials. Indeed, long-term synaptic facilitation is induced only when weak pulses precede strong, not vice versa. This may represent a physiological mechanism to prioritize memory of escalating threats.

Phosphorylation-dependent positive feedback on the oxytocin receptor through the kinase PKD1 contributes to long-term social memory

Social memory enables one to recognize and distinguish specific individuals. It is fundamental to social behaviors that can be mediated by the oxytocin receptor (OXTR), such as forming relationships. We investigated the molecular regulation and function of OXTR in animal behavior involving social memory. We found that Ser²⁶¹ in OXTR was phosphorylated by protein kinase D1 (PKD1). Neuronal Ca²⁺ signaling and behavior analyses revealed that rats expressing a mutated form of OXTR that cannot be phosphorylated at this residue (OXTR S261A) in the medial amygdala (MeA) exhibited impaired long-term social memory (LTSM). Blocking the phosphorylation of wild-type OXTR in the MeA using an interfering peptide in rats or through conditional knockout of Pkd1 in mice reduced social memory retention, whereas expression of a phosphomimetic mutant of OXTR rescued it. In HEK293A cells, the PKD1-mediated phosphorylation of OXTR promoted its binding to G_q protein and, in turn, OXTR-mediated phosphorylation of PKD1, indicating a positive feedback loop. In addition, OXTR with a single-nucleotide polymorphism found in humans (rs200362197), which has a mutation in the conserved recognition region in the PKD1 phosphorylation site, showed impaired activation and signaling in vitro and in HEK293A cells similar to that of the S216A mutant. Our findings describe a phosphoregulatory loop for OXTR and its critical role in social behavior that might be further explored in associated disorders.

Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study

Anterograde interference emerges when two opposite (B → A) or identical tasks (A → A) are learned in close temporal succession, suggesting that interference cannot be fully accounted for by competing memories. Informed by neurobiological evidence, this work tested the hypothesis that interference depends upon the degree of overlap between the neural networks involved in the learning of two tasks. In a fully within‐subject and counterbalanced design, participants (n = 24) took part in two learning sessions where the putative overlap between learning‐specific neural networks was behaviourally manipulated across four conditions by modifying reach direction and the effector used during gradual visuomotor adaptation. The results showed that anterograde interference emerged regardless of memory competition—that is, to a similar extent in the B → A and A → A conditions—and along a gradient as a function of the tasks' similarity. Specifically, learning under similar reaching conditions generated more anterograde interference than learning under dissimilar reaching conditions, suggesting that putatively overlapping neural networks are required to generate interference. Overall, these results indicate that competing memories are not the sole contributor to anterograde interference and suggest that overlapping neural networks between two learning sessions are required to trigger interference. One discussed possibility is that initial learning modifies the properties of its neural networks to constrain further plasticity induction and learning capabilities, therefore causing anterograde interference in a network‐dependent manner. One implication is that learning‐specific neural networks must be maximally dissociated to minimize the interfering influences of previous learning on subsequent learning.

A comparison of three different methods of eliciting rapid activity-dependent synaptic plasticity at the Drosophila NMJ

The Drosophila NMJ is a system of choice for investigating the mechanisms underlying the structural and functional modifications evoked during activity-dependent synaptic plasticity. Because fly genetics allows considerable versatility, many strategies can be employed to elicit this activity. Here, we compare three different stimulation methods for eliciting activity-dependent changes in structure and function at the Drosophila NMJ. We find that the method using patterned stimulations driven by a K+-rich solution creates robust structural modifications but reduces muscle viability, as assessed by resting potential and membrane resistance. We argue that, using this method, electrophysiological studies that consider the frequency of events, rather than their amplitude, are the only reliable studies. We contrast these results with the expression of CsChrimson channels and red-light stimulation at the NMJ, as well as with the expression of TRPA channels and temperature stimulation. With both these methods we observed reliable modifications of synaptic structures and consistent changes in electrophysiological properties. Indeed, we observed a rapid appearance of immature boutons that lack postsynaptic differentiation, and a potentiation of spontaneous neurotransmission frequency. Surprisingly, a patterned application of temperature changes alone is sufficient to provoke both structural and functional plasticity. In this context, temperature-dependent TRPA channel activation induces additional structural plasticity but no further increase in the frequency of spontaneous neurotransmission, suggesting an uncoupling of these mechanisms.

Disrupting the Interaction of nNOS with CAPON Prevents the Reinstatement of Morphine Conditioned Place Preference

Drug abuse is a dramatic challenge for the whole society because of high relapse rate. Environmental cues are crucial for the preference memory of drug abuse. Extinction therapy has been developed to inhibit the motivational effect of drug cues to prevent the reinstatement of morphine abuse. However, extinction therapy alone only forms a new kind of unstable inhibitory memory. We found that morphine conditioned place preference (CPP) extinction training increased the association of nitric oxide synthase (nNOS) with its carboxy-terminal PDZ ligand (CAPON) in the dorsal hippocampus (dHPC) significantly and blocking the morphine-induced nNOS-CAPON association using Tat-CAPON-12C during and after extinction training reversed morphine-induced hippocampal neuroplasticity defect and prevented the reinstatement and spontaneous recovery of morphine CPP. Moreover, in the hippocampal selective ERK2 knock-out or nNOS knockout mice, the effect of Tat-CAPON-12C on the reinstatement of morphine CPP and hippocampal neuroplasticity disappeared, suggesting ERK2 is necessary for the effects of Tat-CAPON-12C. Together, our findings suggest that nNOS-CAPON interaction in the dHPC may affect the consolidation of morphine CPP extinction and dissociating nNOS-CAPON prevents the reinstatement and spontaneous recovery of morphine CPP, possibly through ERK2-mediated neuroplasticity and extinction memory consolidation, offering a new target to prevent the reinstatement of drug abuse.

The Journal of Neuroscience's 40th Anniversary: Looking Back, Looking Forward

Some of us fortunate enough to have published a paper in The Journal of Neuroscience in its inaugural year (1981) have been asked to write a Progressions article addressing our views on the significance of the original work and how ideas about the topic of that work have evolved over the last 40 years. These questions cannot be effectively considered without placing them in the context of the incredible growth of the overall field of neuroscience over these last four decades. For openers, in 1981, the Nobel Prize was awarded to three neuroscience superstars: Roger Sperry, David Hubel, and Torsten Wiesel. Not a bad year to launch the Journal With this as a backdrop, I divide this Progressions article into two parts. First, I discuss our original (1981) paper describing classical conditioning in Aplysia californica, and place our results in the context of the state of the field at the time. Second, I fast forward to the present and consider some of remarkable progress in the broad field of learning and memory that has occurred in the last 40 years. Along the way, I also reflect briefly on some of the amazing advances, both technical and conceptual, that we in neuroscience have witnessed.

Learning the same motor task twice impairs its retention in a time- and dose-dependent manner

Anterograde interference emerges when two differing tasks are learned in close temporal proximity, an effect repeatedly attributed to a competition between differing task memories. However, recent development alternatively suggests that initial learning may trigger a refractory period that occludes neuroplasticity and impairs subsequent learning, consequently mediating interference independently of memory competition. Accordingly, this study tested the hypothesis that interference can emerge when the same motor task is being learned twice, that is when competition between memories is prevented. In a first experiment, the inter-session interval (ISI) between two identical motor learning sessions was manipulated to be 2 min, 1 h or 24 h. Results revealed that retention of the second session was impaired as compared to the first one when the ISI was 2 min but not when it was 1 h or 24 h, indicating a time-dependent process. Results from a second experiment replicated those of the first one and revealed that adding a third motor learning session with a 2 min ISI further impaired retention, indicating a dose-dependent process. Results from a third experiment revealed that the retention impairments did not take place when a learning session was preceded by simple rehearsal of the motor task without concurrent learning, thus ruling out fatigue and confirming that retention is impaired specifically when preceded by a learning session. Altogether, the present results suggest that competing memories is not the sole mechanism mediating anterograde interference and introduce the possibility that a time- and dose-dependent refractory period-independent of fatigue-also contributes to its emergence. One possibility is that learning transiently perturbs the homeostasis of learning-related neuronal substrates. Introducing additional learning when homeostasis is still perturbed may not only impair performance improvements, but also memory formation.

Circular RNAs in the Brain: A Possible Role in Memory?

Higher-order organisms possess information processing capabilities that are only made possible by their biological complexity. Emerging evidence indicates a critical role for regulatory RNAs in coordinating many aspects of cellular function that are directly involved in experience-dependent neural plasticity. Here, we focus on a structurally distinct class of RNAs known as circular RNAs. These closed loop, single-stranded RNA molecules are highly stable, enriched in the brain, and functionally active in both healthy and disease conditions. Current evidence implicating this ancient class of RNA as a contributor toward higher-order functions such as cognition and memory is discussed.

Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature.

Neuronal spike-rate adaptation supports working memory in language processing

Language processing involves the ability to store and integrate pieces of information in working memory over short periods of time. According to the dominant view, information is maintained through sustained, elevated neural activity. Other work has argued that short-term synaptic facilitation can serve as a substrate of memory. Here we propose an account where memory is supported by intrinsic plasticity that downregulates neuronal firing rates. Single neuron responses are dependent on experience, and we show through simulations that these adaptive changes in excitability provide memory on timescales ranging from milliseconds to seconds. On this account, spiking activity writes information into coupled dynamic variables that control adaptation and move at slower timescales than the membrane potential. From these variables, information is continuously read back into the active membrane state for processing. This neuronal memory mechanism does not rely on persistent activity, excitatory feedback, or synaptic plasticity for storage. Instead, information is maintained in adaptive conductances that reduce firing rates and can be accessed directly without cued retrieval. Memory span is systematically related to both the time constant of adaptation and baseline levels of neuronal excitability. Interference effects within memory arise when adaptation is long lasting. We demonstrate that this mechanism is sensitive to context and serial order which makes it suitable for temporal integration in sequence processing within the language domain. We also show that it enables the binding of linguistic features over time within dynamic memory registers. This work provides a step toward a computational neurobiology of language.

Predictive processing: Is the future just a memory?

Predictive processing seems like a radical departure from traditional theories of information processing in the brain, but a broader view of predictions highlights many similarities with standard frameworks. Predictive processing is memory and competitive bias in a new outlook-and we should use this correspondence to advance research on both fronts.

Propofol Modulates Early Memory Consolidation in Humans

Maintenance of memory across time is crucial for adaptive behavior. Current theories posit that the underlying consolidation process depends on stabilization of synapses and reorganization of interactions between hippocampus and neocortex. However, the temporal properties of hippocampal-neocortical network reconfiguration during consolidation are still a matter of debate. Translational research on this issue is challenged by the paucity of techniques to transiently interfere with memory in the healthy human brain. Here, we report a neuro-pharmacological approach with the GABA_Aergic anesthetic propofol and a memory task sensitive to hippocampal dysfunction. Patients undergoing minor surgery learned word lists before injection of an anesthetic dose of propofol. Results show that administration of the drug shortly after learning (∼13 min) impairs recall after awakening but spares recognition. By contrast, later administration (∼105 min) has no effect. These findings suggest significant changes in memory networks very early after learning that are decisive for later recall. Propofol general anesthesia provides an experimental tool to modulate the first steps of hippocampus-mediated memory consolidation in humans.

Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.

Learning-induced mRNA alterations in olfactory bulb mitral cells in neonatal rats

In the olfactory bulb, a cAMP/PKA/CREB-dependent form of learning occurs in the first week of life that provides a unique mammalian model for defining the epigenetic role of this evolutionarily ancient plasticity cascade. Odor preference learning in the week-old rat pup is rapidly induced by a 10-min pairing of odor and stroking. Memory is demonstrable at 24 h, but not 48 h, posttraining. Using this paradigm, pups that showed peppermint preference 30 min posttraining were sacrificed 20 min later for laser microdissection of odor-encoding mitral cells. Controls were given odor only. Microarray analysis revealed that 13 nonprotein-coding mRNAs linked to mRNA translation and splicing and 11 protein-coding mRNAs linked to transcription differed with odor preference training. MicroRNA23b, a translation inhibitor of multiple plasticity-related mRNAs, was down-regulated. Protein-coding transcription was up-regulated for Sec23b, Clic2, Rpp14, Dcbld1, Magee2, Mstn, Fam229b, RGD1566265, and Mgst2. Gng12 and Srcg1 mRNAs were down-regulated. Increases in Sec23b, Clic2, and Dcbld1 proteins were confirmed in mitral cells in situ at the same time point following training. The protein-coding changes are consistent with extracellular matrix remodeling and ryanodine receptor involvement in odor preference learning. A role for CREB and AP1 as triggers of memory-related mRNA regulation is supported. The small number of gene changes identified in the mitral cell input/output link for 24 h memory will facilitate investigation of the nature, and reversibility, of changes supporting temporally restricted long-term memory.

Reevaluating the Role of Persistent Neural Activity in Short-Term Memory

A traditional view of short-term working memory (STM) is that task-relevant information is maintained 'online' in persistent spiking activity. However, recent experimental and modeling studies have begun to question this long-held belief. In this review, we discuss new evidence demonstrating that information can be 'silently' maintained via short-term synaptic plasticity (STSP) without the need for persistent activity. We discuss how the neural mechanisms underlying STM are inextricably linked with the cognitive demands of the task, such that the passive maintenance and the active manipulation of information are subserved differently in the brain. Together, these recent findings point towards a more nuanced view of STM in which multiple substrates work in concert to support our ability to temporarily maintain and manipulate information.

Sleep and synaptic down-selection

The synaptic homeostasis hypothesis (SHY) proposes that sleep is an essential process needed by the brain to maintain the total amount of synaptic strength under control. SHY predicts that by the end of a waking day the synaptic connections of many neural circuits undergo a net increase in synaptic strength due to ongoing learning, which is mainly mediated by synaptic potentiation. Stronger synapses require more energy and supplies and are prone to saturation, creating the need for synaptic renormalization. Such renormalization should mainly occur during sleep, when the brain is disconnected from the environment and neural circuits can be broadly reactivated off-line to undergo a systematic but specific synaptic down-selection. In short, according to SHY sleep is the price to pay for waking plasticity, to avoid runaway potentiation, decreased signal-to-noise ratio, and impaired learning due to saturation. In this review, we briefly discuss the rationale of the hypothesis and recent supportive ultrastructural evidence obtained in our laboratory. We then examine recent studies by other groups showing the causal role of cortical slow waves and hippocampal sharp waves/ripples in sleep-dependent down-selection of neural activity and synaptic strength. Finally, we discuss some of the molecular mechanisms that could mediate synaptic weakening during sleep.

Non-Equilibrium Quantum Brain Dynamics: Super-Radiance and Equilibration in 21 Dimensions+

We derive time evolution equations, namely the Schrödinger-like equations and the Klein–Gordon equations for coherent fields and the Kadanoff–Baym (KB) equations for quantum fluctuations, in quantum electrodynamics (QED) with electric dipoles in 2+1 dimensions. Next we introduce a kinetic entropy current based on the KB equations in the first order of the gradient expansion. We show the H-theorem for the leading-order self-energy in the coupling expansion (the Hartree–Fock approximation). We show conserved energy in the spatially homogeneous systems in the time evolution. We derive aspects of the super-radiance and the equilibration in our single Lagrangian. Our analysis can be applied to quantum brain dynamics, that is QED, with water electric dipoles. The total energy consumption to maintain super-radiant states in microtubules seems to be within the energy consumption to maintain the ordered systems in a brain.

Mysterious Mechanisms of Memory Formation: Are the Answers Hidden in Synapses?

After decades of research on memory formation and retention, we are still searching for the definite concept and process behind neuroplasticity. This review article will address the relationship between synapses, memory formation, and memory retention and their genetic correlations. In the last six decades, there have been enormous improvements in the neurochemistry domain, especially in the area of neural plasticity. In the central nervous system, the complexity of the synapses between neurons allows communication among them. It is believed that each time certain types of sensory signals pass through sequences of synapses, these synapses can transmit the same signals more efficiently the following time. The concept of Hebb synapse has provided revolutionary thinking about the nature of neural mechanisms of learning and memory formation. To improve the local circuitry for memory formation and behavioral change and stabilization in the mammalian central nervous system, long-term potentiation and long-term depression are the crucial components of Hebbian plasticity. In this review, we will be discussing the role of glutamatergic synapses, engram cells, cytokines, neuropeptides, neurosteroids and many aspects, covering the synaptic basis of memory. Lastly, we have tried to cover the etiology of neurodegenerative disorders due to synaptic dysfunction. To enhance pharmacological interventions for neurodegenerative diseases, we need more research in this direction. With the help of technology, and a better understanding of the disease etiology, not only can we identify the missing pieces of synaptic functions, but we might also cure or even prevent serious neurodegenerative diseases like Alzheimer's disease (AD).

Proteins or RNA synthesis inhibitors suppressed induction of amnesia developing under impairment of memory reconsolidation by serotonin receptors antagonist

Studies have shown that retrieval of long-term memory can cause memory reconsolidation, and impaired reconsolidation leads to amnesia development. However, the mechanisms of amnesia induction due to impaired memory reconsolidation remains poorly described. Using experiments involving grape snails trained to conditioned food aversion, we studied the role of translation and transcription processes and the role of serotonin receptors in the mechanisms of amnesia induction. We found that administration of a serotonin receptor antagonist or a protein synthesis inhibitor before the administration of a reminder using a conditioned food stimulus induced amnesia development, whereas injections of mRNA synthesis inhibitor did not affect memory safety. Moreover, combined injections of an antagonist of serotonin receptor and inhibitors of protein or mRNA synthesis before reminder administration completely prevented amnesia development. In addition, inhibitors of protein or mRNA synthesis prevented amnesia development 3 h but not 9 h after the administration of a serotonin receptor antagonist/reminder. We hypothesize that the mechanisms of amnesia induction caused by impaired memory reconsolidation depend on protein and mRNA syntheses within a certain time window, similar to the mechanisms of induction of other long-term plastic brain rearrangements.

Nucleus reuniens of the thalamus controls fear memory intensity, specificity and long-term maintenance during consolidation

The thalamic nucleus reuniens (NR) has been shown to support bidirectional medial prefrontal cortex-hippocampus communication and synchronization relevant for cognitive processing. Using non-selective or prolonged inactivation of the NR, previous studies reported its activity positively modulates aversive memory consolidation. Here we examined the NR's role in consolidating contextual fear memories with varied strength, at both recent and more remote time points, using muscimol-induced temporary inactivation in rats. Results indicate the NR negatively modulates fear memory intensity, specificity, and long-term maintenance. The more intense, generalized, and enduring fear memory induced by NR inactivation during consolidation was less prone to behavioral suppression by extinction or reconsolidation disruption induced by clonidine, an alpha-2 adrenergic receptor agonist. Lastly, we used immunohistochemistry for Arc protein, which is involved in synaptic modifications underlying memory consolidation, to investigate whether treatment condition and/or conditioning status could change its levels not only in the NR, but also in the hippocampus (dorsal and ventral CA1 subregions) and the medial prefrontal cortex (anterior cingulate, prelimbic and infralimbic subregions). Results indicate a significant imbalance in the number of Arc-expressing neurons in the brain areas investigated in muscimol fear conditioned animals when compared with controls. Collectively, present results provide convergent evidence for the NR's role as a hub regulating quantitative and qualitative aspects of a contextual fear memory during its consolidation that seem to influence the subsequent susceptibility to experimental interventions aiming at attenuating its expression. They also indicate the selectivity and duration of a given inactivation approach may influence its outcomes.

Computational Principles of Supervised Learning in the Cerebellum

Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a brain area that supports numerous motor, sensory, and cognitive functions. We highlight recent discoveries indicating that the cerebellum implements supervised learning using the following organizational principles: ( a) extensive preprocessing of input representations (i.e., feature engineering), ( b) massively recurrent circuit architecture, ( c) linear input-output computations, ( d) sophisticated instructive signals that can be regulated and are predictive, ( e) adaptive mechanisms of plasticity with multiple timescales, and ( f) task-specific hardware specializations. The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.

How can memories last for days, years, or a lifetime? Proposed mechanisms for maintaining synaptic potentiation and memory

With memory encoding reliant on persistent changes in the properties of synapses, a key question is how can memories be maintained from days to months or a lifetime given molecular turnover? It is likely that positive feedback loops are necessary to persistently maintain the strength of synapses that participate in encoding. Such feedback may occur within signal-transduction cascades and/or the regulation of translation, and it may occur within specific subcellular compartments or within neuronal networks. Not surprisingly, numerous positive feedback loops have been proposed. Some posited loops operate at the level of biochemical signal-transduction cascades, such as persistent activation of Ca²⁺/calmodulin kinase II (CaMKII) or protein kinase Mζ. Another level consists of feedback loops involving transcriptional, epigenetic and translational pathways, and autocrine actions of growth factors such as BDNF. Finally, at the neuronal network level, recurrent reactivation of cell assemblies encoding memories is likely to be essential for late maintenance of memory. These levels are not isolated, but linked by shared components of feedback loops. Here, we review characteristics of some commonly discussed feedback loops proposed to underlie the maintenance of memory and long-term synaptic plasticity, assess evidence for and against their necessity, and suggest experiments that could further delineate the dynamics of these feedback loops. We also discuss crosstalk between proposed loops, and ways in which such interaction can facilitate the rapidity and robustness of memory formation and storage.

Energy-information coupling during integrative cognitive processes

The physical conception of energy is a natural and general approach to describe functional interactions in the brain at different levels starting from studies of molecular interactions up to the integrative studies of cognitive neuroimaging. In this article, we describe the representation of the brain as a fluctuating energy field, which adaptively reflects the environment. Within this neuroenergetic conception, we indicate a physically solid approach to the problem of the link between brain function and information processing - transmission and integration of information between neuroglial populations is coupled with the corresponding energy increase used for information encoding. We develop the integrative neuroenergetic model of face recognition, in which the input to the model tries to modify the fluctuations of activity according to the free-energy minimization principle corresponding to metabolic efficiency. Once the spatial path of integration in neural activity is known, the processed information can be decoded by spatial differentiation. Energy-based feedback with activity rescaling does not influence the possibility of decoding the information. The model provides further evidence that the conception of energy facilitates at both the computational and conceptual levels the understanding of brain function and its relation to cognition.

Atypical intrinsic neural timescale in autism

How long neural information is stored in a local brain area reflects functions of that region and is often estimated by the magnitude of the autocorrelation of intrinsic neural signals in the area. Here, we investigated such intrinsic neural timescales in high-functioning adults with autism and examined whether local brain dynamics reflected their atypical behaviours. By analysing resting-state fMRI data, we identified shorter neural timescales in the sensory/visual cortices and a longer timescale in the right caudate in autism. The shorter intrinsic timescales in the sensory/visual areas were correlated with the severity of autism, whereas the longer timescale in the caudate was associated with cognitive rigidity. These observations were confirmed from neurodevelopmental perspectives and replicated in two independent cross-sectional datasets. Moreover, the intrinsic timescale was correlated with local grey matter volume. This study shows that functional and structural atypicality in local brain areas is linked to higher-order cognitive symptoms in autism.

Autism is a brain disorder that affects how people interact with others. It occupies a spectrum, with severe autism at one end and high-functioning autism at the other. People with severe autism usually have intellectual impairments and little spoken language. Those with high-functioning autism have average or above average IQ, but struggle with more subtle aspects of communication, such as body language. As well as social difficulties, many individuals with autism show repetitive behaviors and have narrow interests.

The brains of people with autism process information differently to those of people without autism. The brain as a whole shows less coordinated activity in autism, for example. But whether individual brain regions themselves also work differently in autism is unclear. Watanabe et al. set out to answer this question by using a brain scanner to compare the resting brain activity of high-functioning people with autism to that of people without autism.

In both groups, networks of brain regions increased and decreased their activity in predictable patterns. But in individuals with autism, sensory areas of the brain showed more random activity than in individuals without autism. The most random activity occurred in those with the most severe autism. This suggests that the brains of people with autism cannot hold onto and process sensory input for as long as those of neurotypical people. By contrast, a brain region called the caudate showed the opposite pattern, being more predictable in individuals with autism. The most predictable caudate activity occurred in those individuals with the most inflexible, repetitive behaviors. These differences in this neural randomness appear to result from changes in the structure of the individual brain regions.

The findings of Watanabe et al. suggest that changes in the structure and activity of small brain regions give rise to complex symptoms in autism. If these differences also exist in young children, they could help doctors diagnose autism earlier. Future studies should investigate whether the differences in brain activity cause the symptoms of autism. If so, it may be possible to treat the symptoms by changing brain activity, for example, by applying magnetic stimulation to the scalp.

Improving the integrative memory model by integrating the temporal dynamics of memory

Despite highlighting the role of the attribution system and proposing a coherent large-scale architecture of declarative memory, the integrative memory model would be more “integrative” if the temporal dynamics of the interactions between its components was clarified. This is necessary to make predictions in patients with brain injury and hypothesize dissociations.

Enhancement of Declarative Memory: From Genetic Regulation to Non-invasive Stimulation

The problem of memory enhancement is extremely important in intellectual activity areas and therapy of different types of dementia, including Alzheimer's disease (AD). The attempts to solve this problem have come from different research fields. In the first part of our review, we describe the results of targeting certain genes involved in memory-associated molecular pathways. The second part of the review is focused on the deep stimulation of brain structures that can slow down memory loss in AD. The third part describes the results of the use of non-invasive brain stimulation techniques for memory modulation, consolidation, and retrieval in healthy people and animal models. Integration of data from different research fields is essential for the development of efficient strategies for memory enhancement.

Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization

Humans and most animals can learn new tasks without forgetting old ones. However, training artificial neural networks (ANNs) on new tasks typically causes them to forget previously learned tasks. This phenomenon is the result of "catastrophic forgetting," in which training an ANN disrupts connection weights that were important for solving previous tasks, degrading task performance. Several recent studies have proposed methods to stabilize connection weights of ANNs that are deemed most important for solving a task, which helps alleviate catastrophic forgetting. Here, drawing inspiration from algorithms that are believed to be implemented in vivo, we propose a complementary method: adding a context-dependent gating signal, such that only sparse, mostly nonoverlapping patterns of units are active for any one task. This method is easy to implement, requires little computational overhead, and allows ANNs to maintain high performance across large numbers of sequentially presented tasks, particularly when combined with weight stabilization. We show that this method works for both feedforward and recurrent network architectures, trained using either supervised or reinforcement-based learning. This suggests that using multiple, complementary methods, akin to what is believed to occur in the brain, can be a highly effective strategy to support continual learning.

Interplay of multiple pathways and activity-dependent rules in STDP

Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.

The brain’s capacity to treat information, learn and store memory relies on synaptic connectivity patterns, which are altered through synaptic plasticity mechanisms. Experimentally, such plasticities were evidenced through protocols involving numerous repetitive stimulations of a given synapse, and were shown to be supported by multiple pathways. Using a simple biologically grounded mathematical model, we show how activation timescales and inactivation levels of each pathway interact and alter plasticity in an intricate manner as stimuli are presented. Building upon data from the synapse between cortex and striatum, we show that synaptic changes may revert or re-emerge as stimuli are presented, and predict specific responses to changes in stimulus frequency or to distinct simulation patterns. Our general model shows that a given plasticity profile emerging in response to a repetitive stimulation protocol can unfold into various scenarii upon variations of the number of stimulus presentations or patterns, which tightly depends on the underlying activated pathways. Altogether, these results argue that in order to better understand learning and memory, single plasticity responses obtained through intensive stimulations do not reveal the complexity of the responses for smaller number of presentations, which may have a strong impact in fast learning of stimuli with low numbers of presentations.

A novel environment-evoked transcriptional signature predicts reactivity in single dentate granule neurons

Activity-induced remodeling of neuronal circuits is critical for memory formation. This process relies in part on transcription, but neither the rate of activity nor baseline transcription is equal across neuronal cell types. In this study, we isolated mouse hippocampal populations with different activity levels and used single nucleus RNA-seq to compare their transcriptional responses to activation. One hour after novel environment exposure, sparsely active dentate granule (DG) neurons had a much stronger transcriptional response compared to more highly active CA1 pyramidal cells and vasoactive intestinal polypeptide (VIP) interneurons. Activity continued to impact transcription in DG neurons up to 5 h, with increased heterogeneity. By re-exposing the mice to the same environment, we identified a unique transcriptional signature that selects DG neurons for reactivation upon re-exposure to the same environment. These results link transcriptional heterogeneity to functional heterogeneity and identify a transcriptional correlate of memory encoding in individual DG neurons.

Single nuclei RNA-seq has been used to characterize transcriptional signature of environment-related activity in cells of the dentate gyrus. Here the authors use this approach to show that whether a neuron will be reactivated in response to re-exposure to a previous environment can be predicted by its transcriptional signature.

Extinction and Reinstatement of Cocaine-seeking in Self-administering Mice is Associated with Bidirectional AMPAR-mediated Plasticity in the Nucleus Accumbens Shell

Experience-dependent synaptic plasticity is an important component of both learning and motivational disturbances found in addicted individuals. Here, we investigated the role of cocaine experience-dependent plasticity at excitatory synapses in the nucleus accumbens shell (NAcSh) in relapse-related behavior in mice with a history of volitional cocaine self-administration. Using an extinction/reinstatement paradigm of cocaine-seeking behavior, we demonstrate that cocaine-experienced mice with extinguished cocaine-seeking behavior show potentiation of synaptic strength at excitatory inputs onto NAcSh medium spiny neurons (MSNs). Conversely, we found that exposure to various distinct types of reinstating stimuli (cocaine, cocaine-associated cues, yohimbine "stress") after extinction can produce a relative depotentiation of NAcSh synapses that is strongly associated with the magnitude of cocaine-seeking behavior exhibited in response to these challenges. Furthermore, we show that these effects are due to α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-specific mechanisms that differ depending on the nature and context of the reinstatement-inducing stimuli. Together, our findings identify common themes as well as differential mechanisms that are likely important for the ability of diverse environmental stimuli to drive relapse to addictive-like cocaine-seeking behavior.

Principles of Temporal Processing Across the Cortical Hierarchy

The world is richly structured on multiple spatiotemporal scales. In order to represent spatial structure, many machine-learning models repeat a set of basic operations at each layer of a hierarchical architecture. These iterated spatial operations - including pooling, normalization and pattern completion - enable these systems to recognize and predict spatial structure, while robust to changes in the spatial scale, contrast and noisiness of the input signal. Because our brains also process temporal information that is rich and occurs across multiple time scales, might the brain employ an analogous set of operations for temporal information processing? Here we define a candidate set of temporal operations, and we review evidence that they are implemented in the mammalian cerebral cortex in a hierarchical manner. We conclude that multiple consecutive stages of cortical processing can be understood to perform temporal pooling, temporal normalization and temporal pattern completion.

Memory Synapses Are Defined by Distinct Molecular Complexes: A Proposal

Synapses are diverse in form and function. While there are strong evidential and theoretical reasons for believing that memories are stored at synapses, the concept of a specialized “memory synapse” is rarely discussed. Here, we review the evidence that memories are stored at the synapse and consider the opposing possibilities. We argue that if memories are stored in an active fashion at synapses, then these memory synapses must have distinct molecular complexes that distinguish them from other synapses. In particular, examples from Aplysia sensory-motor neuron synapses and synapses on defined engram neurons in rodent models are discussed. Specific hypotheses for molecular complexes that define memory synapses are presented, including persistently active kinases, transmitter receptor complexes and trans-synaptic adhesion proteins.

Taking memory beyond the brain: Does tobacco dream of the mosaic virus?

Memory is typically defined through animal behavior, but this point of view may limit our understanding of many related processes in diverse biological systems. The concept of memory can be broadened meaningfully by considering it from the perspective of time and homeostasis. On the one hand, this theoretical angle can help explain and predict the behavior of various non-neural systems such as insulin-secreting cells, plants, or signaling cascades. On the other hand, it emphasizes biological continuity between neural phenomena, such as synaptic plasticity, and their evolutionary precursors in cellular signaling.

Interleukin-6 is both necessary and sufficient to produce perioperative neurocognitive disorder in mice

BACKGROUND

Perioperative neurocognitive disorders (PND) result in long-term morbidity and mortality with no effective interventions available. Because interleukin-6 (IL-6), a pro-inflammatory cytokine, is consistently up-regulated by trauma, including after surgery, we determined whether IL-6 is a putative therapeutic target for PND in a mouse model.

METHODS

Following institutional approval, adult (12-14 weeks) male C57/Bl6 mice were pretreated with the IL-6 receptor (IL6R) blocking antibody tocilizumab prior to open tibia fracture with internal fixation under isoflurane anaesthesia. Inflammatory and behavioural responses in a trace fear conditioning (TFC) paradigm were assessed postoperatively. Separately, the effects of IL-6 administration or of depletion of bone marrow-derived monocytes (BM-DMs) with clodrolip on the inflammatory and behavioural responses were assessed. Blood brain barrier disruption, hippocampal microglial activation, and infiltration of BM-DMs were each assessed following IL-6 administration.

RESULTS

The surgery-induced decrement in freezing time in the TFC assay, indicative of cognitive decline, was attenuated by tocilizumab (P<0.01). The surgery-induced increase in pro-inflammatory mediators was significantly reduced by tocilizumab. Exogenously administered IL-6 significantly impaired freezing behaviour (P<0.05) and up-regulated pro-inflammatory cytokines; both responses were prevented by depletion of BM-DMs. IL-6 disrupted the blood brain barrier, and increased hippocampal activation of microglia and infiltration of BM-DMs.

CONCLUSIONS

IL-6 is both necessary and sufficient to produce cognitive decline. Following further preclinical testing of its perioperative safety, the IL6R blocker tocilizumab is a candidate for prevention and/or treatment of PND.