Associative Hebbian synaptic plasticity in primate visual cortex

SYNAPTIC PLASTICITY IN THE INJURED BRAIN DEPENDS ON THE TEMPORAL PATTERN OF STIMULATION

Neurostimulation protocols are increasingly used as therapeutic interventions, including for brain injury. In addition to the direct activation of neurons, these stimulation protocols are also likely to have downstream effects on those neurons' synaptic outputs. It is well known that alterations in the strength of synaptic connections (long-term potentiation, LTP; long-term depression, LTD) are sensitive to the frequency of stimulation used for induction, however little is known about the contribution of the temporal pattern of stimulation to the downstream synaptic plasticity that may be induced by neurostimulation in the injured brain. We explored interactions of the temporal pattern and frequency of neurostimulation in the normal cerebral cortex and after mild traumatic brain injury (mTBI), to inform therapies to strengthen or weaken neural circuits in injured brains, as well as to better understand the role of these factors in normal brain plasticity. Whole-cell (WC) patch-clamp recordings of evoked postsynaptic potentials (PSPs) in individual neurons, as well as field potential (FP) recordings, were made from layer 2/3 of visual cortex in response to stimulation of layer 4, in acute slices from control (naïve), sham operated, and mTBI rats. We compared synaptic plasticity induced by different stimulation protocols, each consisting of a specific frequency (1 Hz, 10 Hz, or 100 Hz), continuity (continuous or discontinuous), and temporal pattern (perfectly regular, slightly irregular, or highly irregular). At the individual neuron level, dramatic differences in plasticity outcome occurred when the highly irregular stimulation protocol was used at 1 Hz or 10 Hz, producing an overall LTD in controls and shams, but a robust overall LTP after mTBI. Consistent with the individual neuron results, the plasticity outcomes for simultaneous FP recordings were similar, indicative of our results generalizing to a larger scale synaptic network than can be sampled by individual WC recordings alone. In addition to the differences in plasticity outcome between control (naïve or sham) and injured brains, the dynamics of the changes in synaptic responses that developed during stimulation were predictive of the final plasticity outcome. Our results demonstrate that the temporal pattern of stimulation plays a role in the polarity and magnitude of synaptic plasticity induced in the cerebral cortex while highlighting differences between normal and injured brain responses. Moreover, these results may be useful for optimization of neurostimulation therapies to treat mTBI and other brain disorders, in addition to providing new insights into downstream plasticity signaling mechanisms in the normal brain.

Leveraging neural plasticity for the treatment of amblyopia

Amblyopia is a form of visual cortical impairment that arises from abnormal visual experience early in life. Most often, amblyopia is a unilateral visual impairment that can develop as a result of strabismus, anisometropia, or a combination of these conditions that result in discordant binocular experience. Characterized by reduced visual acuity and impaired binocular function, amblyopia places a substantial burden on the developing child. Although frontline treatment with glasses and patching can improve visual acuity, residual amblyopia remains for most children. Newer binocular-based therapies can elicit rapid recovery of visual acuity and may also improve stereoacuity in some children. Nevertheless, for both treatment modalities full recovery is elusive, recurrence of amblyopia is common, and improvements are negligible when treatment is administered at older ages. Insights derived from animal models about the factors that govern neural plasticity have been leveraged to develop innovative treatments for amblyopia. These novel therapies exhibit efficacy to promote recovery, and some are effective even at ages when conventional treatments fail to yield benefit. Approaches for enhancing visual system plasticity and promoting recovery from amblyopia include altering the balance between excitatory and inhibitory mechanisms, reversing the accumulation of proteins that inhibit plasticity, and harnessing the principles of metaplasticity. Although these therapies have exhibited promising results in animal models, their safety and ability to remediate amblyopia need to be evaluated in humans.

Gamma oscillations and episodic memory

Enhanced gamma oscillatory activity (30-80 Hz) accompanies the successful formation and retrieval of episodic memories. While this co-occurrence is well documented, the mechanistic contributions of gamma oscillatory activity to episodic memory remain unclear. Here, we review how gamma oscillatory activity may facilitate spike timing-dependent plasticity, neural communication, and sequence encoding/retrieval, thereby ensuring the successful formation and/or retrieval of an episodic memory. Based on the evidence reviewed, we propose that multiple, distinct forms of gamma oscillation can be found within the canonical gamma band, each of which has a complementary role in the neural processes listed above. Further exploration of these theories using causal manipulations may be key to elucidating the relevance of gamma oscillatory activity to episodic memory.

Neural encoding with unsupervised spiking convolutional neural network

Accurately predicting the brain responses to various stimuli poses a significant challenge in neuroscience. Despite recent breakthroughs in neural encoding using convolutional neural networks (CNNs) in fMRI studies, there remain critical gaps between the computational rules of traditional artificial neurons and real biological neurons. To address this issue, a spiking CNN (SCNN)-based framework is presented in this study to achieve neural encoding in a more biologically plausible manner. The framework utilizes unsupervised SCNN to extract visual features of image stimuli and employs a receptive field-based regression algorithm to predict fMRI responses from the SCNN features. Experimental results on handwritten characters, handwritten digits and natural images demonstrate that the proposed approach can achieve remarkably good encoding performance and can be utilized for "brain reading" tasks such as image reconstruction and identification. This work suggests that SNN can serve as a promising tool for neural encoding.

Functional and phosphoproteomic analysis of β-adrenergic receptor signaling at excitatory synapses in the CA1 region of the ventral hippocampus

Activation of β-adrenergic receptors (β-ARs) not only enhances learning and memory but also facilitates the induction of long-term potentiation (LTP), a form of synaptic plasticity involved in memory formation. To identify the mechanisms underlying β-AR-dependent forms of LTP we examined the effects of the β-AR agonist isoproterenol on LTP induction at excitatory synapses onto CA1 pyramidal cells in the ventral hippocampus. LTP induction at these synapses is inhibited by activation of SK-type K⁺ channels, suggesting that β-AR activation might facilitate LTP induction by inhibiting SK channels. However, although the SK channel blocker apamin enhanced LTP induction, it did not fully mimic the effects of isoproterenol. We therefore searched for potential alternative mechanisms using liquid chromatography-tandem mass spectrometry to determine how β-AR activation regulates phosphorylation of postsynaptic density (PSD) proteins. Strikingly, β-AR activation regulated hundreds of phosphorylation sites in PSD proteins that have diverse roles in dendritic spine structure and function. Moreover, within the core scaffold machinery of the PSD, β-AR activation increased phosphorylation at several sites previously shown to be phosphorylated after LTP induction. Together, our results suggest that β-AR activation recruits a diverse set of signaling pathways that likely act in a concerted fashion to regulate LTP induction.

Metaplasticity: a key to visual recovery from amblyopia in adulthood?

PURPOSE OF REVIEW

We examine the development of amblyopia and the effectiveness of conventional and emerging therapies through the lens of the Bienenstock, Cooper, and Munro (BCM) theory of synaptic modification.

RECENT FINDINGS

The BCM theory posits metaplastic adjustment in the threshold for synaptic potentiation, governed by prior neuronal activity. Viewing established clinical principles of amblyopia treatment from the perspective of the BCM theory, occlusion, blur, or release of interocular suppression reduce visual cortical activity in the amblyopic state to lower the modification threshold and enable amblyopic eye strengthening. Although efficacy of these treatment approaches declines with age, significant loss of vision in the fellow eye by damage or disease can trigger visual acuity improvements in the amblyopic eye of adults. Likewise, reversible retinal inactivation stimulates recovery of amblyopic eye visual function in adult mice and cats.

SUMMARY

Conventional and emerging amblyopia treatment responses abide by the framework of BCM theory. Preclinical studies support that the dramatic reduction in cortical activity accompanying temporary retinal silencing can promote recovery from amblyopia even in adulthood, highlighting a promising therapeutic avenue.

Hyper-Sensitivity to Pitch and Poorer Prosody Processing in Adults With Autism: An ERP Study

Individuals with autism typically experience a range of symptoms, including abnormal sensory sensitivities. However, there are conflicting reports on the sensory profiles that characterize the sensory experience in autism that often depend on the type of stimulus. Here, we examine early auditory processing to simple changes in pitch and later auditory processing of more complex emotional utterances. We measured electroencephalography in 24 adults with autism and 28 controls. First, tones (1046.5Hz/C6, 1108.7Hz/C#6, or 1244.5Hz/D#6) were repeated three times or nine times before the pitch changed. Second, utterances of delight or frustration were repeated three or six times before the emotion changed. In response to the simple pitched tones, the autism group exhibited larger mismatch negativity (MMN) after nine standards compared to controls and produced greater trial-to-trial variability (TTV). In response to the prosodic utterances, the autism group showed smaller P3 responses when delight changed to frustration compared to controls. There was no significant correlation between ERPs to pitch and ERPs to prosody. Together, this suggests that early auditory processing is hyper-sensitive in autism whereas later processing of prosodic information is hypo-sensitive. The impact the different sensory profiles have on perceptual experience in autism may be key to identifying behavioral treatments to reduce symptoms.

Transsynaptic cerebellin 4-neogenin 1 signaling mediates LTP in the mouse dentate gyrus

SignificanceSynapses are controlled by transsynaptic adhesion complexes that mediate bidirectional signaling between pre- and postsynaptic compartments. Long-term potentiation (LTP) of synaptic transmission is thought to enable synaptic modifications during memory formation, but the signaling mechanisms involved remain poorly understood. We show that binding of cerebellin-4 (Cbln4), a secreted ligand of presynaptic neurexin adhesion molecules, to neogenin-1, a postsynaptic surface protein known as a developmental netrin receptor, is essential for normal LTP at entorhinal cortex→dentate gyrus synapses in mice. Cbln4 and neogenin-1 are dispensable for basal synaptic transmission and not involved in establishing synaptic connections as such. Our data identify a netrin receptor as a postsynaptic organizer of synaptic plasticity that collaborates specifically with the presynaptic neurexin-ligand Cbln4.

Integrating unsupervised and reinforcement learning in human categorical perception: A computational model

Categorical perception identifies a tuning of human perceptual systems that can occur during the execution of a categorisation task. Despite the fact that experimental studies and computational models suggest that this tuning is influenced by task-independent effects (e.g., based on Hebbian and unsupervised learning, UL) and task-dependent effects (e.g., based on reward signals and reinforcement learning, RL), no model studies the UL/RL interaction during the emergence of categorical perception. Here we have investigated the effects of this interaction, proposing a system-level neuro-inspired computational architecture in which a perceptual component integrates UL and RL processes. The model has been tested with a categorisation task and the results show that a balanced mix of unsupervised and reinforcement learning leads to the emergence of a suitable categorical perception and the best performance in the task. Indeed, an excessive unsupervised learning contribution tends to not identify task-relevant features while an excessive reinforcement learning contribution tends to initially learn slowly and then to reach sub-optimal performance. These results are consistent with the experimental evidence regarding categorical activations of extrastriate cortices in healthy conditions. Finally, the results produced by the two extreme cases of our model can explain the existence of several factors that may lead to sensory alterations in autistic people.

A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection

This paper proposes a Fully Spiking Hybrid Neural Network (FSHNN) for energy-efficient and robust object detection in resource-constrained platforms. The network architecture is based on a Spiking Convolutional Neural Network using leaky-integrate-fire neuron models. The model combines unsupervised Spike Time-Dependent Plasticity (STDP) learning with back-propagation (STBP) learning methods and also uses Monte Carlo Dropout to get an estimate of the uncertainty error. FSHNN provides better accuracy compared to DNN based object detectors while being more energy-efficient. It also outperforms these object detectors, when subjected to noisy input data and less labeled training data with a lower uncertainty error.

Calcium and Spike Timing-Dependent Plasticity

Since its discovery, spike timing-dependent synaptic plasticity (STDP) has been thought to be a primary mechanism underlying the brain's ability to learn and to form new memories. However, despite the enormous interest in both the experimental and theoretical neuroscience communities in activity-dependent plasticity, it is still unclear whether plasticity rules inferred from in vitro experiments apply to in vivo conditions. Among the multiple reasons why plasticity rules in vivo might differ significantly from in vitro studies is that extracellular calcium concentration use in most studies is higher than concentrations estimated in vivo. STDP, like many forms of long-term synaptic plasticity, strongly depends on intracellular calcium influx for its induction. Here, we discuss the importance of considering physiological levels of extracellular calcium concentration to study functional plasticity.

A Multisubcellular Compartment Model of AMPA Receptor Trafficking for Neuromodulation of Hebbian Synaptic Plasticity

Neuromodulation can profoundly impact the gain and polarity of postsynaptic changes in Hebbian synaptic plasticity. An emerging pattern observed in multiple central synapses is a pull–push type of control in which activation of receptors coupled to the G-protein Gs promote long-term potentiation (LTP) at the expense of long-term depression (LTD), whereas receptors coupled to Gq promote LTD at the expense of LTP. Notably, coactivation of both Gs- and Gq-coupled receptors enhances the gain of both LTP and LTD. To account for these observations, we propose a simple kinetic model in which AMPA receptors (AMPARs) are trafficked between multiple subcompartments in and around the postsynaptic spine. In the model AMPARs in the postsynaptic density compartment (PSD) are the primary contributors to synaptic conductance. During LTP induction, AMPARs are trafficked to the PSD primarily from a relatively small perisynaptic (peri-PSD) compartment. Gs-coupled receptors promote LTP by replenishing peri-PSD through increased AMPAR exocytosis from a pool of endocytic AMPAR. During LTD induction AMPARs are trafficked in the reverse direction, from the PSD to the peri-PSD compartment, and Gq-coupled receptors promote LTD by clearing the peri-PSD compartment through increased AMPAR endocytosis. We claim that the model not only captures essential features of the pull–push neuromodulation of synaptic plasticity, but it is also consistent with other actions of neuromodulators observed in slice experiments and is compatible with the current understanding of AMPAR trafficking.

Modelling thalamocortical circuitry shows that visually induced LTP changes laminar connectivity in human visual cortex

Neuroplasticity is essential to learning and memory in the brain; it has therefore also been implicated in numerous neurological and psychiatric disorders, making measuring the state of neuroplasticity of foremost importance to clinical neuroscience. Long-term potentiation (LTP) is a key mechanism of neuroplasticity and has been studied extensively, and invasively in non-human animals. Translation to human application largely relies on the validation of non-invasive measures of LTP. The current study presents a generative thalamocortical computational model of visual cortex for investigating and replicating interlaminar connectivity changes using non-invasive EEG recording of humans. The model is combined with a commonly used visual sensory LTP paradigm and fit to the empirical EEG data using dynamic causal modelling. The thalamocortical model demonstrated remarkable accuracy recapitulating post-tetanus changes seen in invasive research, including increased excitatory connectivity from thalamus to layer IV and from layer IV to II/III, established major sites of LTP in visual cortex. These findings provide justification for the implementation of the presented thalamocortical model for ERP research, including to provide increased detail on the nature of changes that underlie LTP induced in visual cortex. Future applications include translating rodent findings to non-invasive research in humans concerning deficits to LTP that may underlie neurological and psychiatric disease.

The brain’s ability to learn and form memories is governed by neuroplasticity. One of the major mechanisms of neuroplasticity is long-term potentiation (LTP). To study LTP in detail necessitates implanting electrodes in the brain of non-human animals. However, to translate this knowledge to humans requires a non-invasive method. Neural mass models use mathematical equations to describe the brain’s neural architecture and function over time. Fitting these models to real data, using methods such as dynamic causal modelling (DCM), helps to elucidate the connectivity and major channel changes that could have plausibly caused the observed effects in electroencephalography data recorded non-invasively from the scalp.

The current study presents a thalamocortical model of the neural architecture of the visual system combined with a thalamic compartment. The model is able to represent the basic transfer of visual information to the cortex, mediated by major receptor types. We combined the thalamocortical model with a visual processing task that uses black and white grating images to induce and measure LTP in visual cortex. We hypothesised that the changes in the model would be consistent with what is seen in animal invasive recordings.

The model demonstrated remarkable accuracy in recapitulating changes to neural architecture consistent with the induction of LTP in visual cortex. Additionally, the result demonstrated specificity to the visual input that induced LTP. Future applications include translating animal findings that are beginning to determine how disordered LTP may underlie neurological and psychiatric disease (for example depression, schizophrenia, autism, and dementia).

The role of Hebbian learning in human perception: a methodological and theoretical review of the human Visual Long-Term Potentiation paradigm

Long-term potentiation (LTP) is one of the most widely studied forms of neural plasticity, and is thought to be the principle mechanism underlying long-term memory and learning in the brain. Sensory paradigms utilising electroencephalography (EEG) and sensory stimulation to induce LTP have allowed translation from rodent and primate invasive research to non-invasive human investigations. This review focusses on visual sensory LTP induced using repetitive visual stimulation, resulting in changes in the visually evoked response recorded at the scalp with EEG. Across 15 years of use and replication in humans several major paradigm variants for eliciting visual LTP have emerged. The application of different paradigms, and the broad implementation of visual LTP across different populations combines to provide a rich and sensitive account of Hebbian LTP, and potentially non-Hebbian plasticity mechanisms. This review will conclude with a discussion of how these findings have advanced existing theories of perceptual learning by positioning Hebbian learning both alongside and within other major theories such as Predictive Coding and The Free Energy Principle.

Ketamine Enhances Visual Sensory Evoked Potential Long-term Potentiation in Patients With Major Depressive Disorder

BACKGROUND

The rapid-acting clinical effects of ketamine as a novel treatment for depression along with its complex pharmacology have made it a growing research area. One of the key mechanistic hypotheses for how ketamine works to alleviate depression is by enhancing long-term potentiation (LTP)-mediated neural plasticity.

METHODS

The objective of this study was to investigate the plasticity hypothesis in 30 patients with depression noninvasively using visual LTP as an index of neural plasticity. In a double-blind, active placebo-controlled crossover trial, electroencephalography-based LTP was recorded approximately 3 to 4 hours following a single 0.44-mg/kg intravenous dose of ketamine or active placebo (1.7 ng/mL remifentanil) in 30 patients. Montgomery-Åsberg Depression Rating Scale scores were used to measure clinical symptoms. Visual LTP was measured as a change in the visually evoked potential following high-frequency visual stimulation. Dynamic causal modeling investigated the underlying neural architecture of visual LTP and the contribution of ketamine.

RESULTS

Montgomery-Åsberg Depression Rating Scale scores revealed that 70% of participants experienced 50% or greater reduction in their depression symptoms within 1 day of receiving ketamine. LTP was demonstrated in the N1 (p = .00002) and P2 (p = 2.31 × 10^-11) visually evoked components. Ketamine specifically enhanced P2 potentiation compared with placebo (p = .017). Dynamic causal modeling replicated the recruitment of forward and intrinsic connections for visual LTP and showed complementary effects of ketamine indicative of downstream and proplasticity modulation.

CONCLUSIONS

This study provides evidence that LTP-based neural plasticity increases within the time frame of the antidepressant effects of ketamine in humans and supports the hypothesis that changes to neural plasticity may be key to the antidepressant properties of ketamine.

From membrane receptors to protein synthesis and actin cytoskeleton: Mechanisms underlying long lasting forms of synaptic plasticity

Synaptic plasticity, the activity dependent change in synaptic strength, forms the molecular foundation of learning and memory. Synaptic plasticity includes structural changes, with spines changing their size to accomodate insertion and removal of postynaptic receptors, which are correlated with functional changes. Of particular relevance for memory storage are the long lasting forms of synaptic plasticity which are protein synthesis dependent. Due to the importance of spine structural plasticity and protein synthesis, this review focuses on the signaling pathways that connect synaptic stimulation with regulation of protein synthesis and remodeling of the actin cytoskeleton. We also review computational models that implement novel aspects of molecular signaling in synaptic plasticity, such as the role of neuromodulators and spatial microdomains, as well as highlight the need for computational models that connect activation of memory kinases with spine actin dynamics.

First-Spike-Based Visual Categorization Using Reward-Modulated STDP

Reinforcement learning (RL) has recently regained popularity with major achievements such as beating the European game of Go champion. Here, for the first time, we show that RL can be used efficiently to train a spiking neural network (SNN) to perform object recognition in natural images without using an external classifier. We used a feedforward convolutional SNN and a temporal coding scheme where the most strongly activated neurons fire first, while less activated ones fire later, or not at all. In the highest layers, each neuron was assigned to an object category, and it was assumed that the stimulus category was the category of the first neuron to fire. If this assumption was correct, the neuron was rewarded, i.e., spike-timing-dependent plasticity (STDP) was applied, which reinforced the neuron's selectivity. Otherwise, anti-STDP was applied, which encouraged the neuron to learn something else. As demonstrated on various image data sets (Caltech, ETH-80, and NORB), this reward-modulated STDP (R-STDP) approach has extracted particularly discriminative visual features, whereas classic unsupervised STDP extracts any feature that consistently repeats. As a result, R-STDP has outperformed STDP on these data sets. Furthermore, R-STDP is suitable for online learning and can adapt to drastic changes such as label permutations. Finally, it is worth mentioning that both feature extraction and classification were done with spikes, using at most one spike per neuron. Thus, the network is hardware friendly and energy efficient.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity

Humans instantly recognize a previously seen face as “familiar.” To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher’s discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits.

Coexistence of Multiple Types of Synaptic Plasticity in Individual Hippocampal CA1 Pyramidal Neurons

Understanding learning and memory mechanisms is an important goal in neuroscience. To gain insights into the underlying cellular mechanisms for memory formation, synaptic plasticity processes are studied with various techniques in different brain regions. A valid model to scrutinize different ways to enhance or decrease synaptic transmission is recording of long-term potentiation (LTP) or long-term depression (LTD). At the single cell level, spike timing-dependent plasticity (STDP) protocols have emerged as a powerful tool to investigate synaptic plasticity with stimulation paradigms that also likely occur during memory formation in vivo. Such kind of plasticity can be induced by different STDP paradigms with multiple repeat numbers and stimulation patterns. They subsequently recruit or activate different molecular pathways and neuromodulators for induction and expression of STDP. Dopamine (DA) and brain-derived neurotrophic factor (BDNF) have been recently shown to be important modulators for hippocampal STDP at Schaffer collateral (SC)-CA1 synapses and are activated exclusively by distinguishable STDP paradigms. Distinct types of parallel synaptic plasticity in a given neuron depend on specific subcellular molecular prerequisites. Since the basal and apical dendrites of CA1 pyramidal neurons are known to be heterogeneous, and distance-dependent dendritic gradients for specific receptors and ion channels are described, the dendrites might provide domain specific locations for multiple types of synaptic plasticity in the same neuron. In addition to the distinct signaling and expression mechanisms of various types of LTP and LTD, activation of these different types of plasticity might depend on background brain activity states. In this article, we will discuss some ideas why multiple forms of synaptic plasticity can simultaneously and independently coexist and can contribute so effectively to increasing the efficacy of memory storage and processing capacity of the brain. We hypothesize that resolving the subcellular location of t-LTP and t-LTD mechanisms that are regulated by distinct neuromodulator systems will be essential to reach a more cohesive understanding of synaptic plasticity in memory formation.

Perceptual learning in a non-human primate model of artificial vision

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation.

A neural mechanism of dynamic gating of task-relevant information by top-down influence in primary visual cortex

Visual recognition involves bidirectional information flow, which consists of bottom-up information coding from retina and top-down information coding from higher visual areas. Recent studies have demonstrated the involvement of early visual areas such as primary visual area (V1) in recognition and memory formation. V1 neurons are not passive transformers of sensory inputs but work as adaptive processor, changing their function according to behavioral context. Top-down signals affect tuning property of V1 neurons and contribute to the gating of sensory information relevant to behavior. However, little is known about the neuronal mechanism underlying the gating of task-relevant information in V1. To address this issue, we focus on task-dependent tuning modulations of V1 neurons in two tasks of perceptual learning. We develop a model of the V1, which receives feedforward input from lateral geniculate nucleus and top-down input from a higher visual area. We show here that the change in a balance between excitation and inhibition in V1 connectivity is necessary for gating task-relevant information in V1. The balance change well accounts for the modulations of tuning characteristic and temporal properties of V1 neuronal responses. We also show that the balance change of V1 connectivity is shaped by top-down signals with temporal correlations reflecting the perceptual strategies of the two tasks. We propose a learning mechanism by which synaptic balance is modulated. To conclude, top-down signal changes the synaptic balance between excitation and inhibition in V1 connectivity, enabling early visual area such as V1 to gate context-dependent information under multiple task performances.

Distinct Eligibility Traces for LTP and LTD in Cortical Synapses

In reward-based learning, synaptic modifications depend on a brief stimulus and a temporally delayed reward, which poses the question of how synaptic activity patterns associate with a delayed reward. A theoretical solution to this so-called distal reward problem has been the notion of activity-generated "synaptic eligibility traces," silent and transient synaptic tags that can be converted into long-term changes in synaptic strength by reward-linked neuromodulators. Here we report the first experimental demonstration of eligibility traces in cortical synapses. We demonstrate the Hebbian induction of distinct traces for LTP and LTD and their subsequent timing-dependent transformation into lasting changes by specific monoaminergic receptors anchored to postsynaptic proteins. Notably, the temporal properties of these transient traces allow stable learning in a recurrent neural network that accurately predicts the timing of the reward, further validating the induction and transformation of eligibility traces for LTP and LTD as a plausible synaptic substrate for reward-based learning.

Metabotropic glutamate receptor signaling is required for NMDA receptor-dependent ocular dominance plasticity and LTD in visual cortex

A feature of early postnatal neocortical development is a transient peak in signaling via metabotropic glutamate receptor 5 (mGluR5). In visual cortex, this change coincides with increased sensitivity of excitatory synapses to monocular deprivation (MD). However, loss of visual responsiveness after MD occurs via mechanisms revealed by the study of long-term depression (LTD) of synaptic transmission, which in layer 4 is induced by acute activation of NMDA receptors (NMDARs) rather than mGluR5. Here we report that chronic postnatal down-regulation of mGluR5 signaling produces coordinated impairments in both NMDAR-dependent LTD in vitro and ocular dominance plasticity in vivo. The data suggest that ongoing mGluR5 signaling during a critical period of postnatal development establishes the biochemical conditions that are permissive for activity-dependent sculpting of excitatory synapses via the mechanism of NMDAR-dependent LTD.

Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory

Emotional arousal enhances perception and memory of high-priority information but impairs processing of other information. Here, we propose that, under arousal, local glutamate levels signal the current strength of a representation and interact with norepinephrine (NE) to enhance high priority representations and out-compete or suppress lower priority representations. In our "glutamate amplifies noradrenergic effects" (GANE) model, high glutamate at the site of prioritized representations increases local NE release from the locus coeruleus (LC) to generate "NE hotspots." At these NE hotspots, local glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. In contrast, arousal-induced LC activity inhibits less active representations via two mechanisms: 1) Where there are hotspots, lateral inhibition is amplified; 2) Where no hotspots emerge, NE levels are only high enough to activate low-threshold inhibitory adrenoreceptors. Thus, LC activation promotes a few hotspots of excitation in the context of widespread suppression, enhancing high priority representations while suppressing the rest. Hotspots also help synchronize oscillations across neural ensembles transmitting high-priority information. Furthermore, brain structures that detect stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during, or after encoding enhances synaptic plasticity at NE hotspots, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms promote selective attention and memory under arousal. GANE not only reconciles apparently contradictory findings in the emotion-cognition literature but also extends previous influential theories of LC neuromodulation by proposing specific mechanisms for how LC-NE activity increases neural gain.

In vivo evidence for neuroplasticity in older adults

Neuroplasticity can be conceptualized as an intrinsic property of the brain that enables modification of function and structure in response to environmental demands. Neuroplastic strengthening of synapses is believed to serve as a critical mechanism underlying learning, memory, and other cognitive functions. Ex vivo work investigating neuroplasticity has been done on hippocampal slices using high frequency stimulation. However, in vivo neuroplasticity in humans has been difficult to demonstrate. Recently, a long-term potentiation-like phenomenon, a form of neuroplastic change, was identified in young adults by differences in visual evoked potentials (VEPs) that were measured before and after tetanic visual stimulation (TVS). The current study investigated whether neuroplastic changes in the visual pathway can persist in older adults. Seventeen healthy subjects, 65 years and older, were recruited from the community. Subjects had a mean age of 77.4 years, mean education of 17 years, mean MMSE of 29.1, and demonstrated normal performance on neuropsychological tests. 1Hz checkerboard stimulation, presented randomly to the right or left visual hemi-field, was followed by 2min of 9Hz stimulation (TVS) to one hemi-field. After 2min of rest, 1Hz stimulation was repeated. Temporospatial principal component analysis was used to identify the N1b component of the VEPs, at lateral occipital locations, in response to 1Hz stimulation pre- and post-TVS. Results showed that the amplitude of factors representing the early and late N1b component was substantially larger after tetanic stimulation. These findings indicate that high frequency visual stimulation can enhance the N1b in cognitively high functioning old adults, suggesting that neuroplastic changes in visual pathways can continue into late life. Future studies are needed to determine the extent to which this marker of neuroplasticity is sustained over a longer period of time, and is influenced by age, cognitive status, and neurodegenerative disease.