More than synaptic plasticity: role of nonsynaptic plasticity in learning and memory

Paradoxical Boosting of Weak and Strong Spatial Memories by Hippocampal Dopamine Uncaging

The ability to remember changes in the surroundings is fundamental for daily life. It has been proposed that novel events producing dopamine release in the hippocampal CA1 region could modulate spatial memory formation. However, the role of hippocampal dopamine increase on weak or strong spatial memories remains unclear. We show that male mice exploring two objects located in a familiar environment for 5 min created a short-term memory (weak) that cannot be retrieved 1 d later, whereas 10 min exploration created a long-term memory (strong) that can be retrieved 1 d later. Remarkably, hippocampal dopamine elevation during the encoding of weak object location memories (OLMs) allowed their retrieval 1 d later but dopamine elevation during the encoding of strong OLMs promoted the preference for a familiar object location over a novel object location after 24 h. Moreover, dopamine uncaging after the encoding of OLMs did not have effect on weak memories whereas on strong memories diminished the exploration of the novel object location. Additionally, hippocampal dopamine elevation during the retrieval of OLMs did not allow the recovery of weak memories and did not affect the retrieval of strong memory traces. Finally, dopamine elevation increased hippocampal theta oscillations, indicating that dopamine promotes the recurrent activation of specific groups of neurons. Our experiments demonstrate that hippocampal dopaminergic modulation during the encoding of OLMs depends on memory strength indicating that hyperdopaminergic levels that enhance weak experiences could compromise the normal storage of strong memories.

The Role of Cerebellar Intrinsic Neuronal Excitability, Synaptic Plasticity, and Perineuronal Nets in Eyeblink Conditioning

Evidence is strong that, in addition to fine motor control, there is an important role for the cerebellum in cognition and emotion. The deep nuclei of the mammalian cerebellum also contain the highest density of perineural nets-mesh-like structures that surround neurons-in the brain, and it appears there may be a connection between these nets and cognitive processes, particularly learning and memory. Here, we review how the cerebellum is involved in eyeblink conditioning-a particularly well-understood form of learning and memory-and focus on the role of perineuronal nets in intrinsic membrane excitability and synaptic plasticity that underlie eyeblink conditioning. We explore the development and role of perineuronal nets and the in vivo and in vitro evidence that manipulations of the perineuronal net in the deep cerebellar nuclei affect eyeblink conditioning. Together, these findings provide evidence of an important role for perineuronal net in learning and memory.

Adenosine and Cortical Plasticity

Brain plasticity is the ability of the nervous system to change its structure and functioning in response to experiences. These changes occur mainly at synaptic connections, and this plasticity is named synaptic plasticity. During postnatal development, environmental influences trigger changes in synaptic plasticity that will play a crucial role in the formation and refinement of brain circuits and their functions in adulthood. One of the greatest challenges of present neuroscience is to try to explain how synaptic connections change and cortical maps are formed and modified to generate the most suitable adaptive behavior after different external stimuli. Adenosine is emerging as a key player in these plastic changes at different brain areas. Here, we review the current knowledge of the mechanisms responsible for the induction and duration of synaptic plasticity at different postnatal brain development stages in which adenosine, probably released by astrocytes, directly participates in the induction of long-term synaptic plasticity and in the control of the duration of plasticity windows at different cortical synapses. In addition, we comment on the role of the different adenosine receptors in brain diseases and on the potential therapeutic effects of acting via adenosine receptors.

Evolving Dual-Threshold Bienenstock-Cooper-Munro Learning Rules in Echo State Networks

The strengthening and the weakening of synaptic strength in existing Bienenstock-Cooper-Munro (BCM) learning rule are determined by a long-term potentiation (LTP) sliding modification threshold and the afferent synaptic activities. However, synaptic long-term depression (LTD) even affects low-active synapses during the induction of synaptic plasticity, which may lead to information loss. Biological experiments have found another LTD threshold that can induce either potentiation or depression or no change, even at the activated synapses. In addition, existing BCM learning rules can only select a set of fixed rule parameters, which is biologically implausible and practically inflexible to learn the structural information of input signals. In this article, an evolved dual-threshold BCM learning rule is proposed to regulate the reservoir internal connection weights of the echo-state-network (ESN), which can contribute to alleviating information loss and enhancing learning performance by introducing different optimal LTD thresholds for different postsynaptic neurons. Our experimental results show that the evolved dual-threshold BCM learning rule can result in the synergistic learning of different plasticity rules, effectively improving the learning performance of an ESN in comparison with existing neural plasticity learning rules and some state-of-the-art ESN variants on three widely used benchmark tasks and the prediction of an esterification process.

Intrinsic plasticity of Purkinje cell serves homeostatic regulation of fear memory

Two forms of plasticity, synaptic and intrinsic, are neural substrates for learning and memory. Abnormalities in homeostatic plasticity cause severe neuropsychiatric diseases, such as schizophrenia and autism. This suggests that the balance between synaptic transmission and intrinsic excitability is important for physiological function in the brain. Despite the established role of synaptic plasticity between parallel fiber (PF) and Purkinje cell (PC) in fear memory, its relationship with intrinsic plasticity is not well understood. Here, patch clamp recording revealed depression of intrinsic excitability in PC following auditory fear conditioning (AFC). Depressed excitability balanced long-term potentiation of PF-PC synapse to serve homeostatic regulation of PF-evoked PC firing. We then optogenetically manipulated PC excitability during the early consolidation period resulting in bidirectional regulation of fear memory. Fear conditioning-induced synaptic plasticity was also regulated following optogenetic manipulation. These results propose intrinsic plasticity in PC as a novel mechanism of fear memory and elucidate that decreased intrinsic excitability in PC counterbalances PF-PC synaptic potentiation to maintain fear memory in a normal range.

Neuronal and synaptic adaptations underlying the benefits of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) is a well-established and effective treatment for patients with advanced Parkinson's disease (PD), yet its underlying mechanisms remain enigmatic. Optogenetics, primarily conducted in animal models, provides a unique approach that allows cell type- and projection-specific modulation that mirrors the frequency-dependent stimulus effects of DBS. Opto-DBS research in animal models plays a pivotal role in unraveling the neuronal and synaptic adaptations that contribute to the efficacy of DBS in PD treatment. DBS-induced neuronal responses rely on a complex interplay between the distributions of presynaptic inputs, frequency-dependent synaptic depression, and the intrinsic excitability of postsynaptic neurons. This orchestration leads to conversion of firing patterns, enabling both antidromic and orthodromic modulation of neural circuits. Understanding these mechanisms is vital for decoding position- and programming-dependent effects of DBS. Furthermore, patterned stimulation is emerging as a promising strategy yielding long-lasting therapeutic benefits. Research on the neuronal and synaptic adaptations to DBS may pave the way for the development of more enduring and precise modulation patterns. Advanced technologies, such as adaptive DBS or directional electrodes, can also be integrated for circuit-specific neuromodulation. These insights hold the potential to greatly improve the effectiveness of DBS and advance PD treatment to new levels.

Sex-dependent fear memory impairment in cocaine-sired rat offspring

Cocaine self-administration by male rats results in neuronal and behavioral alterations in offspring, including responses to cocaine. Given the high degree of overlap between the brain systems underlying the pathological responses to cocaine and stress, we examined whether sire cocaine taking would influence fear-associated behavioral effects in drug-naïve adult male and female progeny. Sire cocaine exposure had no effect on contextual fear conditioning or its extinction in either male or female offspring. During cued fear conditioning, freezing behavior was enhanced in female, but not male, cocaine-sired progeny. In contrast, male cocaine-sired progeny exhibited enhanced expression of cue-conditioned fear during extinction. Long-term potentiation (LTP) was robust in the basolateral amygdala (BLA), which encodes fear conditioning, of female offspring but was completely absent in male offspring of cocaine-exposed sires. Collectively, these results indicate that cued fear memory is enhanced in the male progeny of cocaine exposed sires, which also have BLA synaptic plasticity deficits.

Cerebellar interneurons control fear memory consolidation via learning-induced HCN plasticity

While synaptic plasticity is considered the basis of learning and memory, modifications of the intrinsic excitability of neurons can amplify the output of neuronal circuits and consequently change behavior. However, the mechanisms that underlie learning-induced changes in intrinsic excitability during memory formation are poorly understood. In the cerebellum, we find that silencing molecular layer interneurons completely abolishes fear memory, revealing their critical role in memory consolidation. The fear conditioning paradigm produces a lasting reduction in hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in these interneurons. This change increases intrinsic membrane excitability and enhances the response to synaptic stimuli. HCN loss is driven by a decrease in endocannabinoid levels via altered cGMP signaling. In contrast, an increase in release of cerebellar endocannabinoids during memory consolidation abolishes HCN plasticity. Thus, activity in cerebellar interneurons drives fear memory formation via a learning-specific increase in intrinsic excitability, and this process requires the loss of endocannabinoid-HCN signaling.

The study of plasticity has always been about gradients

The experimental study of learning and plasticity has always been driven by an implicit question: how can physiological changes be adaptive and improve performance? For example, in Hebbian plasticity only synapses from presynaptic neurons that were active are changed, avoiding useless changes. Similarly, in dopamine-gated learning synapse changes depend on reward or lack thereof and do not change when everything is predictable. Within machine learning we can make the question of which changes are adaptive concrete: performance improves when changes correlate with the gradient of an objective function quantifying performance. This result is general for any system that improves through small changes. As such, physiology has always implicitly been seeking mechanisms that allow the brain to approximate gradients. Coming from this perspective we review the existing literature on plasticity-related mechanisms, and we show how these mechanisms relate to gradient estimation. We argue that gradients are a unifying idea to explain the many facets of neuronal plasticity.

Engram neurons: Encoding, consolidation, retrieval, and forgetting of memory

Tremendous strides have been made in our understanding of the neurobiological substrates of memory - the so-called memory "engram". Here, we integrate recent progress in the engram field to illustrate how engram neurons transform across the "lifespan" of a memory - from initial memory encoding, to consolidation and retrieval, and ultimately to forgetting. To do so, we first describe how cell-intrinsic properties shape the initial emergence of the engram at memory encoding. Second, we highlight how these encoding neurons preferentially participate in synaptic- and systems-level consolidation of memory. Third, we describe how these changes during encoding and consolidation guide neural reactivation during retrieval, and facilitate memory recall. Fourth, we describe neurobiological mechanisms of forgetting, and how these mechanisms can counteract engram properties established during memory encoding, consolidation, and retrieval. Motivated by recent experimental results across these four sections, we conclude by proposing some conceptual extensions to the traditional view of the engram, including broadening the view of cell-type participation within engrams and across memory stages. In collection, our review synthesizes general principles of the engram across memory stages, and describes future avenues to further understand the dynamic engram.

Dynamic alteration of intrinsic properties of the cerebellar Purkinje cell during the motor memory consolidation

Intrinsic plasticity of the cerebellar Purkinje cell (PC) plays a critical role in motor memory consolidation. However, detailed changes in their intrinsic properties during memory consolidation are not well understood. Here, we report alterations in various properties involved in intrinsic excitability, such as the action potential (AP) threshold, AP width, afterhyperpolarization (AHP), and sag voltage, which are associated with the long-term depression of intrinsic excitability following the motor memory consolidation process. We analyzed data recorded from PCs before and 1, 4, and 24 h after cerebellum-dependent motor learning and found that these properties underwent dynamic changes during the consolidation process. We further analyzed data from PC-specific STIM1 knockout (STIM1^PKO) mice, which show memory consolidation deficits, and derived intrinsic properties showing distinct change patterns compared with those of wild-type littermates. The levels of memory retention in the STIM1^PKO mice were significantly different compared to wild-type mice between 1 and 4 h after training, and AP width, fast- and medium-AHP, and sag voltage showed different change patterns during this period. Our results provide information regarding alterations in intrinsic properties during a particular period that are critical for memory consolidation.

A C-shaped miniaturized coil for transcranial magnetic stimulation in rodents

Objective.Transcranial magnetic stimulation (TMS) is a non-invasive technique widely used for neuromodulation. Animal models are essential for investigating the underlying mechanisms of TMS. However, the lack of miniaturized coils hinders the TMS studies in small animals, since most commercial coils are designed for humans and thus incapable of focal stimulation in small animals. Furthermore, it is difficult to perform electrophysiological recordings at the TMS focal point using conventional coils.Approach.We designed, fabricated, and tested a novel miniaturized TMS coil (4-by-7 mm) that consisted of a C-shaped iron powder core and insulated copper wires (30 turns). The resulting magnetic and electric fields were characterized with experimental measurements and finite element modeling. The efficacy of this coil in neuromodulation was validated with electrophysiological recordings of single-unit activities (SUAs), somatosensory evoked potentials (SSEPs), and motor evoked potentials (MEPs) in rats (n= 32) following repetitive TMS (rTMS; 3 min, 10 Hz).Main results.This coil could generate a maximum magnetic field of 460 mT and an electric field of 7.2 V m-1in the rat brain according to our simulations. With subthreshold rTMS focally delivered over the sensorimotor cortex, mean firing rates of primary somatosensory and motor cortical neurons significantly increased (154±5% and 160±9% from the baseline level, respectively); MEP and SSEP amplitude significantly increased (136±9%) and decreased (74±4%), respectively.Significance.This miniaturized C-shaped coil enabled focal TMS and concurrent electrophysiological recording/stimulation at the TMS focal point. It provided a useful tool to investigate the neural responses and underlying mechanisms of TMS in small animal models. Using this paradigm, we for the first time observed distinct modulatory effects on SUAs, SSEPs, and MEPs with the same rTMS protocol in anesthetized rats. These results suggested that multiple neurobiological mechanisms in the sensorimotor pathways were differentially modulated by rTMS.

The molecular memory code and synaptic plasticity: A synthesis

The most widely accepted view of memory in the brain holds that synapses are the storage sites of memory, and that memories are formed through associative modification of synapses. This view has been challenged on conceptual and empirical grounds. As an alternative, it has been proposed that molecules within the cell body are the storage sites of memory, and that memories are formed through biochemical operations on these molecules. This paper proposes a synthesis of these two views, grounded in a computational model of memory. Synapses are conceived as storage sites for the parameters of an approximate posterior probability distribution over latent causes. Intracellular molecules are conceived as storage sites for the parameters of a generative model. The model stipulates how these two components work together as part of an integrated algorithm for learning and inference.

Rhythmically bursting songbird vocomotor neurons are organized into multiple sequences, suggesting a network/intrinsic properties model encoding song and error, not time

In zebra finch, basal ganglia projecting "HVC _X " neurons emit one or more spike bursts during each song motif (canonical sequence of syllables), which are thought to be driven in part by a process of spike rebound excitation. Zebra finch songs are highly stereotyped and recent results indicate that the intrinsic properties of HVC _X neurons are similar within each bird, vary among birds depending on similarity of the songs, and vary with song errors. We tested the hypothesis that the timing of spike bursts during singing also evince individual-specific distributions. Examining previously published data, we demonstrated that the intervals between bursts of multibursting HVC _X are similar for neurons within each bird, in many cases highly clustered at distinct peaks, with the patterns varying among birds. The fixed delay between bursts and different times when neurons are first recruited in the song yields precisely timed multiple sequences of bursts throughout the song, not the previously envisioned single sequence of bursts treated as events having statistically independent timing. A given moment in time engages multiple sequences and both single bursting and multibursting HVC _X simultaneously. This suggests a model where a population of HVC _X sharing common intrinsic properties driving spike rebound excitation influence the timing of a given HVC _X burst through lateral inhibitory interactions. Perturbations in burst timing, representing error, could propagate in time. Our results extend the concept of central pattern generators to complex vertebrate vocal learning and suggest that network activity (timing of inhibition) and HVC _X intrinsic properties become coordinated during developmental birdsong learning.

Disruptions in network plasticity precede deficits in memory following inhibition of retinoid signaling

Retinoic acid, the active metabolite of vitamin A, is important for vertebrate cognition and hippocampal plasticity, but few studies have examined its role in invertebrate learning and memory, and its actions in the invertebrate central nervous system are currently unknown. Using the mollusc Lymnaea stagnalis, we examined operant conditioning of the respiratory behavior, controlled by a well-defined central pattern generator (CPG), and used citral to inhibit retinoic acid signaling. Both citral- and vehicle-treated animals showed normal learning, but citral-treated animals failed to exhibit long-term memory at 24 h. Cohorts of citral- or vehicle-treated animals were dissected into semi-intact preparations, either 1 h after training, or after the memory test 24 h later. Simultaneous electrophysiological recordings from the CPG pacemaker cell (right pedal dorsal 1; RPeD1) and an identified motorneuron (VI) were made while monitoring respiratory activity (pneumostome opening). Activity of the CPG pneumostome opener interneuron (input 3 interneuron; IP3) was also monitored indirectly. Vehicle-treated conditioned preparations showed significant changes in network parameters immediately after learning, such as reduced motorneuron bursting activity (from IP3 input), delayed pneumostome opening, and decoupling of coincident IP3 input within the network. However, citral-treated preparations failed to exhibit these network changes and more closely resembled naïve preparations. Importantly, these citral-induced differences were manifested immediately after training and before any overt changes in the behavioral response (memory impairment). These studies shed light on where and when retinoid signaling might affect a central pattern-generating network to promote memory formation during conditioning of a homeostatic behavior.NEW & NOTEWORTHY We provide novel evidence for how conditioning-induced changes in a CPG network are disrupted when retinoid signaling is inhibited. Inhibition of retinoic acid signaling prevents long-term memory formation following operant conditioning, but has no effect on learning. Simultaneous electrophysiological and behavioral analyses indicate network changes immediately following learning, but these changes are prevented with inhibition of retinoid signaling, before any overt changes in behavior. These data suggest sites for retinoid actions during memory formation.

Defective synaptic plasticity in a model of Coffin-Lowry syndrome is rescued by simultaneously targeting PKA and MAPK pathways

Empirical and computational methods were combined to examine whether individual or dual-drug treatments can restore the deficit in long-term synaptic facilitation (LTF) of the Aplysia sensorimotor synapse observed in a cellular model of Coffin-Lowry syndrome (CLS). The model was produced by pharmacological inhibition of p90 ribosomal S6 kinase (RSK) activity. In this model, coapplication of an activator of the mitogen-activated protein kinase (MAPK) isoform ERK and an activator of protein kinase A (PKA) resulted in enhanced phosphorylation of RSK and enhanced LTF to a greater extent than either drug alone and also greater than their additive effects, which is termed synergism. The extent of synergism appeared to depend on another MAPK isoform, p38 MAPK. Inhibition of p38 MAPK facilitated serotonin (5-HT)-induced RSK phosphorylation, indicating that p38 MAPK inhibits activation of RSK. Inhibition of p38 MAPK combined with activation of PKA synergistically activated both ERK and RSK. Our results suggest that cellular models of disorders that affect synaptic plasticity and learning, such as CLS, may constitute a useful strategy to identify candidate drug combinations, and that combining computational models with empirical tests of model predictions can help explain synergism of drug combinations.

Dynamics and Mechanisms of ERK Activation after Different Protocols that Induce Long-Term Synaptic Facilitation in Aplysia

Phosphorylation of the MAPK family member extracellular signal-regulated kinase (ERK) is required to induce long-term synaptic plasticity, but little is known about its persistence. We examined ERK activation by three protocols that induce long-term synaptic facilitation (LTF) of the Aplysia sensorimotor synapse - the standard protocol (five 5-min pulses of 5-HT with interstimulus intervals (ISIs) of 20 min), the enhanced protocol (five pulses with irregular ISIs, which induces greater and longer-lasting LTF) and the two-pulse protocol (two pulses with ISI 45 min). Immunofluorescence revealed complex ERK activation. The standard and two-pulse protocols immediately increased active, phosphorylated ERK (pERK), which decayed within 5 h. A second wave of increased pERK was detected 18 h post-treatment for all protocols. This late phase was blocked by inhibitors of protein kinase A, TrkB and TGF-β. These results suggest that complex interactions among kinase pathways and growth factors contribute to the late increase of pERK. ERK activity returned to basal 24 h after the standard or two-pulse protocols, but remained elevated 24 h for the enhanced protocol. This 24-h elevation was also dependent on PKA and TGF-β, and partly on TrkB. These results begin to characterize long-lasting ERK activation, plausibly maintained by positive feedback involving growth factors and PKA, that appears essential to maintain LTF and LTM. Because many processes involved in LTF and late LTP are conserved among Aplysia and mammals, these findings highlight the importance of examining the dynamics of kinase cascades involved in vertebrate long-term memory.

Computational Modeling of Structural Synaptic Plasticity in Echo State Networks

Most existing studies on computational modeling of neural plasticity have focused on synaptic plasticity. However, regulation of the internal weights in the reservoir based on synaptic plasticity often results in unstable learning dynamics. In this article, a structural synaptic plasticity learning rule is proposed to train the weights and add or remove neurons within the reservoir, which is shown to be able to alleviate the instability of the synaptic plasticity, and to contribute to increase the memory capacity of the network as well. Our experimental results also reveal that a few stronger connections may last for a longer period of time in a constantly changing network structure, and are relatively resistant to decay or disruptions in the learning process. These results are consistent with the evidence observed in biological systems. Finally, we show that an echo state network (ESN) using the proposed structural plasticity rule outperforms an ESN using synaptic plasticity and three state-of-the-art ESNs on four benchmark tasks.

Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse

Neuromorphic computing targets the hardware embodiment of neural network, and device implementation of individual neuron and synapse has attracted considerable attention. The emulation of synaptic plasticity has shown promising results after the advent of memristors. However, neuronal intrinsic plasticity, which involves in learning process through interactions with synaptic plasticity, has been rarely demonstrated. Synaptic and intrinsic plasticity occur concomitantly in learning process, suggesting the need of the simultaneous implementation. Here, we report a neurosynaptic device that mimics synaptic and intrinsic plasticity concomitantly in a single cell. Threshold switch and phase change memory are merged in threshold switch-phase change memory device. Neuronal intrinsic plasticity is demonstrated based on bottom threshold switch layer, which resembles the modulation of firing frequency in biological neuron. Synaptic plasticity is also introduced through the nonvolatile switching of top phase change layer. Intrinsic and synaptic plasticity are simultaneously emulated in a single cell to establish the positive feedback between them. A positive feedback learning loop which mimics the retraining process in biological system is implemented in threshold switch-phase change memory array for accelerated training.

Synaptic plasticity and neuronal intrinsic plasticity are both involved in the learning process of hardware artificial neural network. Here, Lee et al. integrate a threshold switch and a phase change memory in a single device, which emulates biological synaptic and intrinsic plasticity simultaneously.

Understanding the physical basis of memory: Molecular mechanisms of the engram

Memory, defined as the storage and use of learned information in the brain, is necessary to modulate behavior and critical for animals to adapt to their environments and survive. Despite being a cornerstone of brain function, questions surrounding the molecular and cellular mechanisms of how information is encoded, stored, and recalled remain largely unanswered. One widely held theory is that an engram is formed by a group of neurons that are active during learning, which undergoes biochemical and physical changes to store information in a stable state, and that are later reactivated during recall of the memory. In the past decade, the development of engram labeling methodologies has proven useful to investigate the biology of memory at the molecular and cellular levels. Engram technology allows the study of individual memories associated with particular experiences and their evolution over time, with enough experimental resolution to discriminate between different memory processes: learning (encoding), consolidation (the passage from short-term to long-term memories), and storage (the maintenance of memory in the brain). Here, we review the current understanding of memory formation at a molecular and cellular level by focusing on insights provided using engram technology.

Reinforcement Learning for Central Pattern Generation in Dynamical Recurrent Neural Networks

Lifetime learning, or the change (or acquisition) of behaviors during a lifetime, based on experience, is a hallmark of living organisms. Multiple mechanisms may be involved, but biological neural circuits have repeatedly demonstrated a vital role in the learning process. These neural circuits are recurrent, dynamic, and non-linear and models of neural circuits employed in neuroscience and neuroethology tend to involve, accordingly, continuous-time, non-linear, and recurrently interconnected components. Currently, the main approach for finding configurations of dynamical recurrent neural networks that demonstrate behaviors of interest is using stochastic search techniques, such as evolutionary algorithms. In an evolutionary algorithm, these dynamic recurrent neural networks are evolved to perform the behavior over multiple generations, through selection, inheritance, and mutation, across a population of solutions. Although, these systems can be evolved to exhibit lifetime learning behavior, there are no explicit rules built into these dynamic recurrent neural networks that facilitate learning during their lifetime (e.g., reward signals). In this work, we examine a biologically plausible lifetime learning mechanism for dynamical recurrent neural networks. We focus on a recently proposed reinforcement learning mechanism inspired by neuromodulatory reward signals and ongoing fluctuations in synaptic strengths. Specifically, we extend one of the best-studied and most-commonly used dynamic recurrent neural networks to incorporate the reinforcement learning mechanism. First, we demonstrate that this extended dynamical system (model and learning mechanism) can autonomously learn to perform a central pattern generation task. Second, we compare the robustness and efficiency of the reinforcement learning rules in relation to two baseline models, a random walk and a hill-climbing walk through parameter space. Third, we systematically study the effect of the different meta-parameters of the learning mechanism on the behavioral learning performance. Finally, we report on preliminary results exploring the generality and scalability of this learning mechanism for dynamical neural networks as well as directions for future work.

Specific Plasticity Loci and Their Synergism Mediate Operant Conditioning

Despite numerous studies examining the mechanisms of operant conditioning (OC), the diversity of OC plasticity loci and their synergism have not been examined sufficiently. In the well-characterized feeding neural circuit of Aplysia, in vivo and in vitro appetitive OC increases neuronal excitability and electrical coupling among several neurons leading to an increase in expression of ingestive behavior. Here, we used the in vitro analog of OC to investigate whether OC reduces the excitability of a neuron, B4, whose inhibitory connections decrease expression of ingestive behavior. We found OC decreased the excitability of B4. This change appeared intrinsic to B4 because it could be replicated with an analog of OC in isolated cultures of B4 neurons. In addition to changes in B4 excitability, OC decreased the strength of B4's inhibitory connection to a key decision-making neuron, B51. The OC-induced changes were specific without affecting the excitability of another neuron critical for feeding behavior, B8, or the B4-to-B8 inhibitory connection. A conductance-based circuit model indicated that reducing the B4-to-B51 synapse, or increasing B51 excitability, mediated the OC phenotype more effectively than did decreasing B4 excitability. We combined these modifications to examine whether they could act synergistically. Combinations including B51 synergistically enhanced feeding. Taken together, these results suggest modifications of diverse loci work synergistically to mediate OC and that some neurons are well suited to work synergistically with plasticity in other loci.SIGNIFICANCE STATEMENT The ways in which synergism of diverse plasticity loci mediate the change in motor patterns in operant conditioning (OC) are poorly understood. Here, we found that OC was in part mediated by decreasing the intrinsic excitability of a critical neuron of Aplysia feeding behavior, and specifically reducing the strength of one of its inhibitory connections that targets a key decision-making neuron. A conductance-based computational model indicated that the known plasticity loci showed a surprising level of synergism to mediate the behavioral changes associated with OC. These results highlight the importance of understanding the diversity, specificity and synergy among different types of plasticity that encode memory. Also, because OC in Aplysia is mediated by dopamine (DA), the present study provides insights into specific and synergistic mechanisms of DA-mediated reinforcement of behaviors.

Neuronal population activity dynamics reveal a low-dimensional signature of operant learning in Aplysia

Learning engages a high-dimensional neuronal population space spanning multiple brain regions. However, it remains unknown whether it is possible to identify a low-dimensional signature associated with operant conditioning, a ubiquitous form of learning in which animals learn from the consequences of behavior. Using single-neuron resolution voltage imaging, here we identify two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Our findings point to a temporal shift in module recruitment as the primary signature of operant learning. Our findings can help guide characterization of learning signatures in systems in which only a smaller fraction of the relevant neuronal population can be monitored.

Costa et al. use single-neuron resolution voltage imaging to identify two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Their findings point to a temporal shift in module recruitment as the primary signature of operant learning.

Reading Specific Small Saccades Predict Individual Phonemic Awareness and Reading Speed

Small fixational eye-movements are a fundamental aspect of vision and thought to reflect fine shifts in covert attention during active viewing. While the perceptual benefits of these small eye movements have been demonstrated during a wide range of experimental tasks including during free viewing, their function during reading remains surprisingly unclear. Previous research demonstrated that readers with increased microsaccade rates displayed longer reading speeds. To what extent increased fixational eye movements are, however, specific to reading and might be indicative of reading skill deficits remains, however, unknown. To address this topic, we compared the eye movement scan paths of 13 neurotypical individuals and 13 subjects diagnosed with developmental dyslexia during short story reading and free viewing of natural scenes. We found that during reading only, dyslexics tended to display small eye movements more frequently compared to neurotypicals, though this effect was not significant at the population level, as it could also occur in slow readers not diagnosed as dyslexics. In line with previous research, neurotypical readers had twice as many regressive compared to progressive microsaccades, which did not occur during free viewing. In contrast, dyslexics showed similar amounts of regressive and progressive small fixational eye movements during both reading and free viewing. We also found that participants with smaller fixational saccades from both neurotypical and dyslexic samples displayed reduced reading speeds and lower scores during independent tests of reading skill. Slower readers also displayed greater variability in the landing points and temporal occurrence of their fixational saccades. Both the rate and spatio-temporal variability of fixational saccades were associated with lower phonemic awareness scores. As none of the observed differences between dyslexics and neurotypical readers occurred during control experiments with free viewing, the reported effects appear to be directly related to reading. In summary, our results highlight the predictive value of small saccades for reading skill, but not necessarily for developmental dyslexia.

Activation of D1/D5 Receptors Ameliorates Decreased Intrinsic Excitability of Hippocampal Neurons Induced by Neonatal Blockade of NMDA Receptors

BACKGROUND AND PURPOSE

Dysregulation of dopaminergic transmission combined with transient hypofunction of N-methyl-D-aspartate receptors (NMDARs) is a key mechanism that may underlie cognitive symptoms of schizophrenia.

EXPERIMENTAL APPROACH

Therefore, we aimed to identify electrophysiologic alterations in animals neonatally treated with the NMDA receptor antagonist, MK-801 or with saline solution.

KEY RESULTS

Patch-clamp whole-cell recordings from MK-801-treated animals revealed altered passive and active electrophysiologic properties compared with CA1 pyramidal cells from saline-treated animals, including upregulation of the K⁺ inward-rectifier conductance and fast-inactivating and slow/non-inactivating K⁺ currents. Upregulation of these membrane ionic currents reduced the overall excitability and altered the firing properties of CA1 pyramidal cells. We also explored the capability of cells treated with MK-801 to express intrinsic excitability potentiation, a non-synaptic form of hippocampal plasticity associated with cognition and memory formation. CA1 pyramidal cells from animals treated with MK-801 were unable to convey intrinsic excitability potentiation and had blunted synaptic potentiation. Furthermore, MK-801-treated animals also exhibited reduced cognitive performance in the Barnes maze task. Notably, activation of D1/D5 receptors with SKF-38, 393 partially restored electrophysiologic alterations caused by neonatal treatment with MK-801.

CONCLUSION AND IMPLICATIONS

Our results offer a molecular and mechanistic explanation based on dysregulation of glutamatergic in addition to dopaminergic transmission that may contribute to the understanding of the cognitive deterioration associated with schizophrenia.

The plasticity of nerve fibers: the prolonged effects of polarization of afferent fibers

The review surveys various aspects of the plasticity of nerve fibers, in particular the prolonged increase in their excitability evoked by polarization, focusing on a long-lasting increase in the excitability of myelinated afferent fibers traversing the dorsal columns of the spinal cord. We review the evidence that increased axonal excitability 1) follows epidurally applied direct current (DC) as well as relatively short (5 or 10 ms) current pulses and synaptically evoked intrinsic field potentials; 2) critically depends on the polarization of branching regions of afferent fibers at the sites where they bifurcate and give off axon collaterals entering the spinal gray matter in conjunction with actions of extrasynaptic GABA_A membrane receptors; and 3) shares the feature of being activity-independent with the short-lasting effects of polarization of peripheral nerve fibers. A comparison between the polarization evoked sustained increase in the excitability of dorsal column fibers and spinal motoneurons (plateau potentials) indicates the possibility that they are mediated by partly similar membrane channels (including noninactivating type L Cav⁺⁺ 1.3 but not Na⁺ channels) and partly different mechanisms. We finally consider under which conditions transspinally applied DC (tsDCS) might reproduce the effects of epidural polarization on dorsal column fibers and the possible advantages of increased excitability of afferent fibers for the rehabilitation of motor and sensory functions after spinal cord injuries.NEW & NOTEWORTHY This review supplements previous reviews of properties of nerve fibers by surveying recent experimental evidence for their long-term plasticity. It also extends recent descriptions of spinal effects of DC by reviewing effects of polarization of afferent nerve fibers within the dorsal columns, the mechanisms most likely underlying the long-lasting increase in their excitability and possible clinical implications.

Stable continual learning through structured multiscale plasticity manifolds

Biological plasticity is ubiquitous. How does the brain navigate this complex plasticity space, where any component can seemingly change, in adapting to an ever-changing environment? We build a systematic case that stable continuous learning is achieved by structured rules that enforce multiple, but not all, components to change together in specific directions. This rule-based low-dimensional plasticity manifold of permitted plasticity combinations emerges from cell type-specific molecular signaling and triggers cascading impacts that span multiple scales. These multiscale plasticity manifolds form the basis for behavioral learning and are dynamic entities that are altered by neuromodulation, metaplasticity, and pathology. We explore the strong links between heterogeneities, degeneracy, and plasticity manifolds and emphasize the need to incorporate plasticity manifolds into learning-theoretical frameworks and experimental designs.

Quantitative description of the interactions among kinase cascades underlying long-term plasticity of Aplysia sensory neurons

Kinases play critical roles in synaptic and neuronal changes involved in the formation of memory. However, significant gaps exist in the understanding of how interactions among kinase pathways contribute to the mechanistically distinct temporal domains of memory ranging from short-term memory to long-term memory (LTM). Activation of protein kinase A (PKA) and mitogen-activated protein kinase (MAPK)-ribosomal S6 kinase (RSK) pathways are critical for long-term enhancement of neuronal excitability (LTEE) and long-term synaptic facilitation (LTF), essential processes in memory formation. This study provides new insights into how these pathways contribute to the temporal domains of memory, using empirical and computational approaches. Empirical studies of Aplysia sensory neurons identified a positive feedforward loop in which the PKA and ERK pathways converge to regulate RSK, and a negative feedback loop in which p38 MAPK inhibits the activation of ERK and RSK. A computational model incorporated these findings to simulate the dynamics of kinase activity produced by different stimulus protocols and predict the critical roles of kinase interactions in the dynamics of these pathways. These findings may provide insights into the mechanisms underlying aberrant synaptic plasticity observed in genetic disorders such as RASopathies and Coffin-Lowry syndrome.

Exposure to RF-EMF Alters Postsynaptic Structure and Hinders Neurite Outgrowth in Developing Hippocampal Neurons of Early Postnatal Mice

Exposure to radiofrequency electromagnetic fields (RF-EMFs) has increased rapidly in children, but information on the effects of RF-EMF exposure to the central nervous system in children is limited. In this study, pups and dams were exposed to whole-body RF-EMF at 4.0 W/kg specific absorption rate (SAR) for 5 h per day for 4 weeks (from postnatal day (P) 1 to P28). The effects of RF-EMF exposure on neurons were evaluated by using both pups' hippocampus and primary cultured hippocampal neurons. The total number of dendritic spines showed statistically significant decreases in the dentate gyrus (DG) but was not altered in the cornu ammonis (CA1) in hippocampal neurons. In particular, the number of mushroom-type dendritic spines showed statistically significant decreases in the CA1 and DG. The expression of glutamate receptors was decreased in mushroom-type dendritic spines in the CA1 and DG of hippocampal neurons following RF-EMF exposure. The expression of brain-derived neurotrophic factor (BDNF) in the CA1 and DG was significantly lower statistically in RF-EMF-exposed mice. The number of post-synaptic density protein 95 (PSD95) puncta gradually increased over time but was significantly decreased statistically at days in vitro (DIV) 5, 7, and 9 following RF-EMF exposure. Decreased BDNF expression was restricted to the soma and was not observed in neurites of hippocampal neurons following RF-EMF exposure. The length of neurite outgrowth and number of branches showed statistically significant decreases, but no changes in the soma size of hippocampal neurons were observed. Further, the memory index showed statistically significant decreases in RF-EMF-exposed mice, suggesting that decreased synaptic density following RF-EMF exposure at early developmental stages may affect memory function. Collectively, these data suggest that hindered neuronal outgrowth following RF-EMF exposure may decrease overall synaptic density during early neurite development of hippocampal neurons.

The Immediate Early Gene Arc Is Not Required for Hippocampal Long-Term Potentiation

Memory consolidation is thought to occur through protein synthesis-dependent synaptic plasticity mechanisms such as long-term potentiation (LTP). Dynamic changes in gene expression and epigenetic modifications underlie the maintenance of LTP. Similar mechanisms may mediate the storage of memory. Key plasticity genes, such as the immediate early gene Arc, are induced by learning and by LTP induction. Mice that lack Arc have severe deficits in memory consolidation, and Arc has been implicated in numerous other forms of synaptic plasticity, including long-term depression and cell-to-cell signaling. Here, we take a comprehensive approach to determine if Arc is necessary for hippocampal LTP in male and female mice. Using a variety of Arc knock-out (KO) lines, we found that germline Arc KO mice show no deficits in CA1 LTP induced by high-frequency stimulation and enhanced LTP induced by theta-burst stimulation. Temporally restricting the removal of Arc to adult animals and spatially restricting it to the CA1 using Arc conditional KO mice did not have an effect on any form of LTP. Similarly, acute application of Arc antisense oligodeoxynucleotides had no effect on hippocampal CA1 LTP. Finally, the maintenance of in vivo LTP in the dentate gyrus of Arc KO mice was normal. We conclude that Arc is not necessary for hippocampal LTP and may mediate memory consolidation through alternative mechanisms.SIGNIFICANCE STATEMENT The immediate early gene Arc is critical for maintenance of long-term memory. How Arc mediates this process remains unclear, but it has been proposed to sustain Hebbian synaptic potentiation, which is a key component of memory encoding. This form of plasticity is modeled experimentally by induction of LTP, which increases Arc mRNA and protein expression. However, mechanistic data implicates Arc in the endocytosis of AMPA-type glutamate receptors and the weakening of synapses. Here, we took a comprehensive approach to determine if Arc is necessary for hippocampal LTP. We find that Arc is not required for LTP maintenance and may regulate memory storage through alternative mechanisms.

Electromagnetic field and TGF-β enhance the compensatory plasticity after sensory nerve injury in cockroach Periplaneta americana

Recovery of function after sensory nerves injury involves compensatory plasticity, which can be observed in invertebrates. The aim of the study was the evaluation of compensatory plasticity in the cockroach (Periplaneta americana) nervous system after the sensory nerve injury and assessment of the effect of electromagnetic field exposure (EMF, 50 Hz, 7 mT) and TGF-β on this process. The bioelectrical activities of nerves (pre-and post-synaptic parts of the sensory path) were recorded under wind stimulation of the cerci before and after right cercus ablation and in insects exposed to EMF and treated with TGF-β. Ablation of the right cercus caused an increase of activity of the left presynaptic part of the sensory path. Exposure to EMF and TGF-β induced an increase of activity in both parts of the sensory path. This suggests strengthening effects of EMF and TGF-β on the insect ability to recognize stimuli after one cercus ablation. Data from locomotor tests proved electrophysiological results. The takeover of the function of one cercus by the second one proves the existence of compensatory plasticity in the cockroach escape system, which makes it a good model for studying compensatory plasticity. We recommend further research on EMF as a useful factor in neurorehabilitation.

The structure dilemma in biological and artificial neural networks

Brain research up to date has revealed that structure and function are highly related. Thus, for example, studies have repeatedly shown that the brains of patients suffering from schizophrenia or other diseases have a different connectome compared to healthy people. Apart from stochastic processes, however, an inherent logic describing how neurons connect to each other has not yet been identified. We revisited this structural dilemma by comparing and analyzing artificial and biological-based neural networks. Namely, we used feed-forward and recurrent artificial neural networks as well as networks based on the structure of the micro-connectome of C. elegans and of the human macro-connectome. We trained these diverse networks, which markedly differ in their architecture, initialization and pruning technique, and we found remarkable parallels between biological-based and artificial neural networks, as we were additionally able to show that the dilemma is also present in artificial neural networks. Our findings show that structure contains all the information, but that this structure is not exclusive. Indeed, the same structure was able to solve completely different problems with only minimal adjustments. We particularly put interest on the influence of weights and the neuron offset value, as they show a different adaption behaviour. Our findings open up new questions in the fields of artificial and biological information processing research.

Ion-channel regulation of response decorrelation in a heterogeneous multi-scale model of the dentate gyrus

Heterogeneities in biological neural circuits manifest in afferent connectivity as well as in local-circuit components such as neuronal excitability, neural structure and local synaptic strengths. The expression of adult neurogenesis in the dentate gyrus (DG) amplifies local-circuit heterogeneities and guides heterogeneities in afferent connectivity. How do neurons and their networks endowed with these distinct forms of heterogeneities respond to perturbations to individual ion channels, which are known to change under several physiological and pathophysiological conditions? We sequentially traversed the ion channels-neurons-network scales and assessed the impact of eliminating individual ion channels on conductance-based neuronal and network models endowed with disparate local-circuit and afferent heterogeneities. We found that many ion channels differentially contributed to specific neuronal or network measurements, and the elimination of any given ion channel altered several functional measurements. We then quantified the impact of ion-channel elimination on response decorrelation, a well-established metric to assess the ability of neurons in a network to convey complementary information, in DG networks endowed with different forms of heterogeneities. Notably, we found that networks constructed with structurally immature neurons exhibited functional robustness, manifesting as minimal changes in response decorrelation in the face of ion-channel elimination. Importantly, the average change in output correlation was dependent on the eliminated ion channel but invariant to input correlation. Our analyses suggest that neurogenesis-driven structural heterogeneities could assist the DG network in providing functional resilience to molecular perturbations.

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Perturbations at one scale result in a cascading impact on physiology across scales.

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Heterogeneous multi-scale models used to assess the impact of ion-channel deletion.

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Mapping of structural components to functional outcomes is many-to-many.

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Differential & variable impact of ion channel deletion on response decorrelation.

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Neurogenesis-induced structural heterogeneity confers resilience to perturbations.

Intrinsic plasticity and birdsong learning

Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.

Comparing Theories for the Maintenance of Late LTP and Long-Term Memory: Computational Analysis of the Roles of Kinase Feedback Pathways and Synaptic Reactivation

A fundamental neuroscience question is how memories are maintained from days to a lifetime, given turnover of proteins that underlie expression of long-term synaptic potentiation (LTP) or “tag” synapses as eligible for LTP. A likely solution relies on synaptic positive feedback loops, prominently including persistent activation of Ca²⁺/calmodulin kinase II (CaMKII) and self-activated synthesis of protein kinase M ζ (PKMζ). Data also suggest positive feedback based on recurrent synaptic reactivation within neuron assemblies, or engrams, is necessary to maintain memories. The relative importance of these mechanisms is controversial. To explore the likelihood that each mechanism is necessary or sufficient to maintain memory, we simulated maintenance of LTP with a simplified model incorporating persistent kinase activation, synaptic tagging, and preferential reactivation of strong synapses, and analyzed implications of recent data. We simulated three model variants, each maintaining LTP with one feedback loop: autonomous, self-activated PKMζ synthesis (model variant I); self-activated CamKII (model variant II); and recurrent reactivation of strengthened synapses (model variant III). Variant I predicts that, for successful maintenance of LTP, either 1) PKMζ contributes to synaptic tagging, or 2) a low constitutive tag level persists during maintenance independent of PKMζ, or 3) maintenance of LTP is independent of tagging. Variant II maintains LTP and suggests persistent CaMKII activation could maintain PKMζ activity, a feedforward interaction not previously considered. However, we note data challenging the CaMKII feedback loop. In Variant III synaptic reactivation drives, and thus predicts, recurrent or persistent activation of CamKII and other necessary kinases, plausibly contributing to persistent elevation of PKMζ levels. Reactivation is thus predicted to sustain recurrent rounds of synaptic tagging and incorporation of plasticity-related proteins. We also suggest (model variant IV) that synaptic reactivation and autonomous kinase activation could synergistically maintain LTP. We propose experiments that could discriminate these maintenance mechanisms.

Dopamine as a Multifunctional Neurotransmitter in Gastropod Molluscs: An Evolutionary Hypothesis

AbstractThe catecholamine 3,4-dihydroxyphenethylamine, or dopamine, acts as a neurotransmitter across a broad phylogenetic spectrum. Functions attributed to dopamine in the mammalian brain include regulation of motor circuits, valuation of sensory stimuli, and mediation of reward or reinforcement signals. Considerable evidence also supports a neurotransmitter role for dopamine in gastropod molluscs, and there is growing appreciation for its potential common functions across phylogeny. This article reviews evidence for dopamine's transmitter role in the nervous systems of gastropods. The functional properties of identified dopaminergic neurons in well-characterized neural circuits suggest a hypothetical incremental sequence by which dopamine accumulated its diverse roles. The successive acquisition of dopamine functions is proposed in the context of gastropod feeding behavior: (1) sensation of potential nutrients, (2) activation of motor circuits, (3) selection of motor patterns from multifunctional circuits, (4) valuation of sensory stimuli with reference to internal state, (5) association of motor programs with their outcomes, and (6) coincidence detection between sensory stimuli and their consequences. At each stage of this sequence, it is proposed that existing functions of dopaminergic neurons favored their recruitment to fulfill additional information processing demands. Common functions of dopamine in other intensively studied groups, ranging from mammals and insects to nematodes, suggest an ancient origin for this progression.

High neural activity accelerates the decline of cognitive plasticity with age in Caenorhabditis elegans

The ability to learn progressively declines with age. Neural hyperactivity has been implicated in impairing cognitive plasticity with age, but the molecular mechanisms remain elusive. Here, we show that chronic excitation of the Caenorhabditis elegans O₂-sensing neurons during ageing causes a rapid decline of experience-dependent plasticity in response to environmental O₂ concentration, whereas sustaining lower activity of O₂-sensing neurons retains plasticity with age. We demonstrate that neural activity alters the ageing trajectory in the transcriptome of O₂-sensing neurons, and our data suggest that high-activity neurons redirect resources from maintaining plasticity to sustaining continuous firing. Sustaining plasticity with age requires the K⁺-dependent Na⁺/Ca²⁺ (NCKX) exchanger, whereas the decline of plasticity with age in high-activity neurons acts through calmodulin and the scaffold protein Kidins220. Our findings demonstrate directly that the activity of neurons alters neuronal homeostasis to govern the age-related decline of neural plasticity and throw light on the mechanisms involved.

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.

Deletion of Stk11 and Fos in mouse BLA projection neurons alters intrinsic excitability and impairs formation of long-term aversive memory

Conditioned taste aversion (CTA) is a form of one-trial learning dependent on basolateral amygdala projection neurons (BLApn). Its underlying cellular and molecular mechanisms remain poorly understood. RNAseq from BLApn identified changes in multiple candidate learning-related transcripts including the expected immediate early gene Fos and Stk11, a master kinase of the AMP-related kinase pathway with important roles in growth, metabolism and development, but not previously implicated in learning. Deletion of Stk11 in BLApn blocked memory prior to training, but not following it and increased neuronal excitability. Conversely, BLApn had reduced excitability following CTA. BLApn knockout of a second learning-related gene, Fos, also increased excitability and impaired learning. Independently increasing BLApn excitability chemogenetically during CTA also impaired memory. STK11 and C-FOS activation were independent of one another. These data suggest key roles for Stk11 and Fos in CTA long-term memory formation, dependent at least partly through convergent action on BLApn intrinsic excitability.

Efficient phase coding in hippocampal place cells

Neural codes have been postulated to build efficient representations of the external world. The hippocampus, an encoding system, employs neuronal firing rates and spike phases to encode external space. Although the biophysical origin of such codes is at a single neuronal level, the role of neural components in efficient coding is not understood. The complexity of this problem lies in the dimensionality of the parametric space encompassing neural components, and is amplified by the enormous biological heterogeneity observed in each parameter. A central question that spans encoding systems therefore is how neurons arrive at efficient codes in the face of widespread biological heterogeneities. To answer this, we developed a conductance-based spiking model for phase precession, a phase code of external space exhibited by hippocampal place cells. Our model accounted for several experimental observations on place cell firing and electrophysiology: the emergence of phase precession from exact spike timings of conductance-based models with neuron-specific ion channels and receptors; biological heterogeneities in neural components and excitability; the emergence of subthreshold voltage ramp, increased firing rate, enhanced theta power within the place field; a signature reduction in extracellular theta frequency compared to its intracellular counterpart; and experience-dependent asymmetry in firing-rate profile. We formulated phase-coding efficiency, using Shannon's information theory, as an information maximization problem with spike phase as the response and external space within a single place field as the stimulus. We employed an unbiased stochastic search spanning an 11-dimensional neural space, involving thousands of iterations that accounted for the biophysical richness and neuron-to-neuron heterogeneities. We found a small subset of models that exhibited efficient spatial information transfer through the phase code, and investigated the distinguishing features of this subpopulation at the parametric and functional scales. At the parametric scale, which spans the molecular components that defined the neuron, several nonunique parametric combinations with weak pairwise correlations yielded models with similar high phase-coding efficiency. Importantly, placing additional constraints on these models in terms of matching other aspects of hippocampal neural responses did not hamper parametric degeneracy. We provide quantitative evidence demonstrating this parametric degeneracy to be a consequence of a many-to-one relationship between the different parameters and phase-coding efficiency. At the functional scale, involving the cellular-scale neural properties, our analyses revealed an important higher-order constraint that was exclusive to models exhibiting efficient phase coding. Specifically, we found a counterbalancing negative correlation between neuronal gain and the strength of external synaptic inputs as a critical functional constraint for the emergence of efficient phase coding. These observations implicate intrinsic neural properties as important contributors in effectuating such counterbalance, which can be achieved by recruiting nonunique parametric combinations. Finally, we show that a change in afferent statistics, manifesting as input asymmetry onto these neuronal models, induced an adaptive shift in the phase code that preserved its efficiency. Together, our analyses unveil parametric degeneracy as a mechanism to harness widespread neuron-to-neuron heterogeneity towards accomplishing stable and efficient encoding, provided specific higher-order functional constraints on the relationship of neural gain to external inputs are satisfied.

Computational model of the distributed representation of operant reward memory: combinatoric engagement of intrinsic and synaptic plasticity mechanisms

Operant reward learning of feeding behavior in Aplysia increases the frequency and regularity of biting, as well as biases buccal motor patterns (BMPs) toward ingestion-like BMPs (iBMPs). The engram underlying this memory comprises cells that are part of a central pattern generating (CPG) circuit and includes increases in the intrinsic excitability of identified cells B30, B51, B63, and B65, and increases in B63-B30 and B63-B65 electrical synaptic coupling. To examine the ways in which sites of plasticity (individually and in combination) contribute to memory expression, a model of the CPG was developed. The model included conductance-based descriptions of cells CBI-2, B4, B8, B20, B30, B31, B34, B40, B51, B52, B63, B64, and B65, and their synaptic connections. The model generated patterned activity that resembled physiological BMPs, and implementation of the engram reproduced increases in frequency, regularity, and bias. Combined enhancement of B30, B63, and B65 excitabilities increased BMP frequency and regularity, but not bias toward iBMPs. Individually, B30 increased regularity and bias, B51 increased bias, B63 increased frequency, and B65 decreased all three BMP features. Combined synaptic plasticity contributed primarily to regularity, but also to frequency and bias. B63-B30 coupling contributed to regularity and bias, and B63-B65 coupling contributed to all BMP features. Each site of plasticity altered multiple BMP features simultaneously. Moreover, plasticity loci exhibited mutual dependence and synergism. These results indicate that the memory for operant reward learning emerged from the combinatoric engagement of multiple sites of plasticity.

Intrinsic neuronal properties represent song and error in zebra finch vocal learning

Neurons regulate their intrinsic physiological properties, which could influence network properties and contribute to behavioral plasticity. Recording from adult zebra finch brain slices we show that within each bird basal ganglia Area X-projecting (HVCX) neurons share similar spike waveform morphology and timing of spike trains, with modeling indicating similar magnitudes of five principal ion currents. These properties vary among birds in lawful relation to acoustic similarity of the birds' songs, with adult sibling pairs (same songs) sharing similar waveforms and spiking characteristics. The properties are maintained dynamically: HVCX within juveniles learning to sing show variable properties, whereas the uniformity rapidly degrades within hours in adults singing while exposed to abnormal (delayed) auditory feedback. Thus, within individual birds the population of current magnitudes covary over the arc of development, while rapidly responding to changes in feedback (in adults). This identifies network interactions with intrinsic properties that affect information storage and processing of learned vocalizations.

Functional MRI and Structural Connectome Analysis of Language Networks in Japanese-English Bilinguals

We aimed to clarify the mechanisms of neural plasticity involved in language. We hypothesized that alterations which occur in bilinguals could reflect the mechanisms of acquisition of a second language and simulate neural plasticity related to language. We compared spatial characteristics of story listening-related hemodynamic modulations and subcortical fiber networks between monolinguals and bilinguals. Participants were Japanese monolinguals and Japanese-English bilinguals whose first language was Japanese. We divided bilinguals into early and late bilinguals depending on whether the age of acquisition was before after 7 years of age. We applied intergroup analysis to investigate the following: (1) blood oxygen level-dependent response (BOLD) responses during story listening by block-based fMRI; (2) number of fibers (NOFs) between specific edges by DTI. Both bilingual samples showed larger BOLD responses (BRs) in the right putamen and bilateral superior temporal gyri compared to the Japanese monolinguals in fMRI. Late bilinguals demonstrated bigger BRs in the right anterior temporal lobe and left medial parietal lobe than early bilinguals. Early bilinguals showed a higher NOFs between the right putamen and precentral gyrus than monolinguals and late bilinguals in DTI. Late bilinguals showed a lower NOFs between the left superior temporal gyrus and supramarginal gyrus than monolinguals and early bilinguals. Early bilinguals reinforce the subcortical fiber network between the right putamen and precentral gyrus, and activate the right putamen to gain alternative language function. We conclude that these key cerebral regions and subcortical fiber networks could contribute to the neural plasticity of language.

Role of p90 ribosomal S6 kinase in long-term synaptic facilitation and enhanced neuronal excitability

Multiple kinases converge on the transcription factor cAMP response element-binding protein (CREB) to enhance the expression of proteins essential for long-term synaptic plasticity and memory. The p90 ribosomal S6 kinase (RSK) is one of these kinases, although its role is poorly understood. The present study exploited the technical advantages of the Aplysia sensorimotor culture system to examine the role of RSK in long-term synaptic facilitation (LTF) and long-term enhancement of neuronal excitability (LTEE), two correlates of long-term memory (LTM). Inhibition of RSK expression or RSK activity both significantly reduced CREB1 phosphorylation, LTF, and LTEE, suggesting RSK is required for learning-related synaptic plasticity and enhancement in neuronal excitability. In addition, knock down of RSK by RNAi in Aplysia sensory neurons impairs LTF, suggesting that this may be a useful single-cell system to study aspects of defective synaptic plasticity in Coffin-Lowry Syndrome (CLS), a cognitive disorder that is caused by mutations in rsk2 and associated with deficits in learning and memory. We found that the impairments in LTF and LTEE can be rescued by a computationally designed spaced training protocol, which was previously demonstrated to augment normal LTF and LTM.

Realistic spiking neural network: Non-synaptic mechanisms improve convergence in cell assembly

Learning in neural networks inspired by brain tissue has been studied for machine learning applications. However, existing works primarily focused on the concept of synaptic weight modulation, and other aspects of neuronal interactions, such as non-synaptic mechanisms, have been neglected. Non-synaptic interaction mechanisms have been shown to play significant roles in the brain, and four classes of these mechanisms can be highlighted: (i) electrotonic coupling; (ii) ephaptic interactions; (iii) electric field effects; and iv) extracellular ionic fluctuations. In this work, we proposed simple rules for learning inspired by recent findings in machine learning adapted to a realistic spiking neural network. We show that the inclusion of non-synaptic interaction mechanisms improves cell assembly convergence. By including extracellular ionic fluctuation represented by the extracellular electrodiffusion in the network, we showed the importance of these mechanisms to improve cell assembly convergence. Additionally, we observed a variety of electrophysiological patterns of neuronal activity, particularly bursting and synchronism when the convergence is improved.

Reward Devaluation Attenuates Cue-Evoked Sucrose Seeking and Is Associated with the Elimination of Excitability Differences between Ensemble and Non-ensemble Neurons in the Nucleus Accumbens

Animals must learn relationships between foods and the environmental cues that predict their availability for survival. Such cue–food associations are encoded in sparse sets of neurons or “neuronal ensembles” in the nucleus accumbens (NAc). For these ensemble-encoded, cue-controlled appetitive responses to remain adaptive, they must allow for their dynamic updating depending on acute changes in internal states such as physiological hunger or the perceived desirability of food. However, how these neuronal ensembles are recruited and physiologically modified following the update of such learned associations is unclear. To investigate this, we examined the effects of devaluation on ensemble plasticity at the levels of recruitment, intrinsic excitability, and synaptic physiology in sucrose-conditioned Fos-GFP mice that express green fluorescent protein (GFP) in recently activated neurons. Neuronal ensemble activation patterns and their physiology were examined using immunohistochemistry and slice electrophysiology, respectively. Reward-specific devaluation following 4 d of ad libitum sucrose consumption, but not general caloric devaluation, attenuated cue-evoked sucrose seeking. This suggests that changes in the hedonic and/or incentive value of sucrose, and not caloric need, drove this behavior. Moreover, devaluation attenuated the size of the neuronal ensemble recruited by the cue in the NAc shell. Finally, it eliminated the relative enhanced excitability of ensemble (GFP⁺) neurons against non-ensemble (GFP⁻) neurons observed under non-devalued conditions, and did not induce any ensemble-specific changes in excitatory synaptic physiology. Our findings provide new insights into neuronal ensemble mechanisms that underlie the changes in the incentive and/or hedonic impact of cues that support adaptive food seeking.