STDP in the Developing Sensory Neocortex

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.

A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.

Brain is modulated by neuronal plasticity during postnatal development

Neuroplasticity is referred to the ability of the nervous system to change its structure or functions as a result of former stimuli. It is a plausible mechanism underlying a dynamic brain through adaptation processes of neural structure and activity patterns. Nevertheless, it is still unclear how the plastic neural systems achieve and maintain their equilibrium. Additionally, the alterations of balanced brain dynamics under different plasticity rules have not been explored either. Therefore, the present article primarily aims to review recent research studies regarding homosynaptic and heterosynaptic neuroplasticity characterized by the manipulation of excitatory and inhibitory synaptic inputs. Moreover, it attempts to understand different mechanisms related to the main forms of synaptic plasticity at the excitatory and inhibitory synapses during the brain development processes. Hence, this study comprised surveying those articles published since 1988 and available through PubMed, Google Scholar and science direct databases on a keyword-based search paradigm. All in all, the study results presented extensive and corroborative pieces of evidence for the main types of plasticity, including the long-term potentiation (LTP) and long-term depression (LTD) of the excitatory and inhibitory postsynaptic potentials (EPSPs and IPSPs).

Sub-Optimality of the Early Visual System Explained Through Biologically Plausible Plasticity

The early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often studied under the assumption that neural populations are optimised for the most efficient (in terms of energy, information, spikes, etc.) representation of natural statistics. Normative models such as Independent Component Analysis (ICA) and Sparse Coding (SC) consider the phenomenon as a generative, minimisation problem which they assume the early cortical populations have evolved to solve. However, measurements in monkey and cat suggest that receptive fields (RFs) in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the RFs do not emerge through a global minimisation of generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity (STDP). Using a network endowed with an abstract, rank-based STDP rule, we show that the shape and orientation tuning of the converged units are remarkably close to single-cell measurements in the macaque primary visual cortex. We quantify this similarity using physiological parameters (frequency-normalised spread vectors), information theoretic measures [Kullback–Leibler (KL) divergence and Gini index], as well as simulations of a typical electrophysiology experiment designed to estimate orientation tuning curves. Taken together, our results suggest that compared to purely generative schemes, process-based biophysical models may offer a better description of the suboptimality observed in the early visual cortex.

A Primer on Constructing Plasticity Phenotypes to Classify Experience-Dependent Development of the Visual Cortex

Many neural mechanisms regulate experience-dependent plasticity in the visual cortex (V1), and new techniques for quantifying large numbers of proteins or genes are transforming how plasticity is studied into the era of big data. With those large data sets comes the challenge of extracting biologically meaningful results about visual plasticity from data-driven analytical methods designed for high-dimensional data. In other areas of neuroscience, high-information content methodologies are revealing more subtle aspects of neural development and individual variations that give rise to a richer picture of brain disorders. We have developed an approach for studying V1 plasticity that takes advantage of the known functions of many synaptic proteins for regulating visual plasticity. We use that knowledge to rebrand protein measurements into plasticity features and combine those into a plasticity phenotype. Here, we provide a primer for analyzing experience-dependent plasticity in V1 using example R code to identify high-dimensional changes in a group of proteins. We describe using PCA to classify high-dimensional plasticity features and use them to construct a plasticity phenotype. In the examples, we show how to use this analytical framework to study and compare experience-dependent development and plasticity of V1 and apply the plasticity phenotype to translational research questions. We include an R package “PlasticityPhenotypes” that aggregates the coding packages and custom code written in RStudio to construct and analyze plasticity phenotypes.

Evaluating Cholinergic Receptor Expression in Guinea Pig Primary Auditory and Rostral Belt Cortices After Noise Damage Using [3H]Scopolamine and [18F]Flubatine Autoradiography

Noise-induced hearing loss leads to anatomic and physiologic changes in primary auditory cortex (A1) and the adjacent dorsal rostral belt (RB). Since acetylcholine is known to modulate plasticity in other cortical areas, changes in A1 and RB following noise damage may be due to changes in cholinergic receptor expression. We used [³H]scopolamine and [¹⁸F]flubatine binding to measure muscarinic acetylcholine receptor (mAChR) and nicotinic acetylcholine receptor (nAChR) expression, respectively, in guinea pig A1 and RB 3 weeks following unilateral, left ear noise exposure, and a temporary threshold shift in hearing. [³H]Scopolamine binding decreased in right A1 and RB (contralateral to noise) compared to sham controls across all cortical layers. [¹⁸F]Flubatine binding showed a nonsignificant upward trend in right A1 following noise but only significantly increased in right RB and 2 layers of left RB (ipsilateral to noise). This selective response may ultimately influence cortical plasticity and function. The mechanism(s) by which cholinergic receptors are altered following noise exposure remain unknown. However, these data demonstrate noise exposure may differentially influence mAChRs that typically populate interneurons in A1 and RB more than nAChRs that are traditionally located on thalamocortical projections and provide motivation for cholinergic imaging in clinical patient populations of temporary or permanent hearing loss.

The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX) Version 2.0: Modelling in vitro electrical stimulation of brain tissue

Neuronal circuits can be modelled in detail allowing us to predict the effects of stimulation on individual neurons. Electrical stimulation of neuronal circuits in vitro and in vivo excites a range of neurons within the tissue and measurements of neural activity, e.g the local field potential (LFP), are again an aggregate of a large pool of cells. The previous version of our Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX) allowed for the simulation of the LFP generated by a patch of brain tissue. Here, we extend VERTEX to simulate the effect of electrical stimulation through a focal electric field. We observe both direct changes in neural activity and changes in synaptic plasticity. Testing our software in a model of a rat neocortical slice, we determine the currents contributing to the LFP, the effects of paired pulse stimulation to induce short term plasticity (STP), and the effect of theta burst stimulation (TBS) to induce long term potentiation (LTP).

Emergence of Binocular Disparity Selectivity through Hebbian Learning

Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989; Atick and Redlich, 1992; Olshausen and Field, 1996), an explanation as to how the cortex might develop the computational architecture to support these encoding schemes remains elusive. Here, using the more realistic example of binocular vision as opposed to monocular luminance-field images, we show how a simple Hebbian coincidence-detector is capable of accounting for the emergence of binocular, disparity selective, receptive fields. We propose a model based on spike timing-dependent plasticity, which not only converges to realistic single-cell and population characteristics, but also demonstrates how known biases in natural statistics may influence population encoding and downstream correlates of behavior. Furthermore, we show that the receptive fields we obtain are closer in structure to electrophysiological data reported in macaques than those predicted by normative encoding schemes (Ringach, 2002). We also demonstrate the robustness of our model to the input dataset, noise at various processing stages, and internal parameter variation. Together, our modeling results suggest that Hebbian coincidence detection is an important computational principle and could provide a biologically plausible mechanism for the emergence of selectivity to natural statistics in the early sensory cortex.SIGNIFICANCE STATEMENT Neural selectivity in the early visual cortex is often explained through encoding schemes that postulate that the computational aim of early sensory processing is to use the least possible resources (neurons, energy) to code the most informative features of the stimulus (information efficiency). In this article, using stereo images of natural scenes, we demonstrate how a simple Hebbian rule can lead to the emergence of a disparity-selective neural population that not only shows realistic single-cell and population tunings, but also demonstrates how known biases in natural statistics may influence population encoding and downstream correlates of behavior. Our approach allows us to view early neural selectivity, not as an optimization problem, but as an emergent property driven by biological rules of plasticity.

Prostaglandin Signaling Governs Spike Timing-Dependent Plasticity at Sensory Synapses onto Mouse Spinal Projection Neurons

Highly correlated presynaptic and postsynaptic activity evokes spike timing-dependent long-term potentiation (t-LTP) at primary afferent synapses onto spinal projection neurons. While prior evidence indicates that t-LTP depends upon an elevation in intracellular Ca²⁺ within projection neurons, the downstream signaling pathways that trigger the observed increase in glutamate release from sensory neurons remain poorly understood. Using in vitro patch-clamp recordings from female mouse lamina I spino-parabrachial neurons, the present study demonstrates a critical role for prostaglandin synthesis in the generation of t-LTP. Bath application of the selective phospholipase A₂ (PLA₂) inhibitor arachidonyl trifluoromethyl ketone (AACOCF₃) or the cyclooxygenase 2 (Cox-2) inhibitor nimesulide prevented t-LTP at sensory synapses onto spino-parabrachial neurons. Similar results were observed following the block of the EP2 subtype of prostaglandin E₂ (PGE₂) receptor with PF 04418948. Meanwhile, perfusion with PGE₂ or the EP2 agonist butaprost potentiated the amplitude of monosynaptic primary afferent-evoked EPSCs while decreasing the paired-pulse ratio, suggesting a presynaptic site of action. Cox-2 was constitutively expressed in both spinal microglia and lamina I projection neurons within the superficial dorsal horn (SDH). Suppression of microglial activation with minocycline had no effect on the production of t-LTP, suggesting the possibility that prostaglandins produced within projection neurons could contribute to an enhanced probability of glutamate release at primary afferent synapses. Collectively, the results suggest that the amplification of ascending nociceptive transmission by the spinal SDH network is governed by PLA₂-Cox-2-PGE₂ signaling.SIGNIFICANCE STATEMENT Long-term potentiation (LTP) of primary afferent synapses contributes to the sensitization of spinal nociceptive circuits and has been linked to greater pain sensation in humans. Prior work has implicated elevated glutamate release in the generation of spike timing-dependent LTP (t-LTP) at sensory synapses onto ascending spinal projection neurons, but the underlying mechanisms remain unknown. Here we provide evidence that the activation of EP2 prostaglandin receptors by prostaglandin E₂, occurring downstream of phospholipase A₂ and cyclooxygenase 2 activation, mediates t-LTP at these synapses via changes in presynaptic function. This suggests that prostaglandins can increase the flow of nociceptive information from the spinal cord to the brain independently of their known ability to suppress synaptic inhibition within the dorsal horn.

Neuromodulatory Correlates of Pupil Dilation

Pupillometry has long been used as a measure of brain state. Changes in pupil diameter are thought to coincide with the activity of neuromodulators, including noradrenaline and acetylcholine, producing alterations in the brain state and corresponding changes in behavior. Here we review mechanisms underlying the control of pupil diameter and how these mechanisms are correlated with changes in cortical activity and the recruitment of neuromodulatory circuits.

Neonatal Tissue Damage Promotes Spike Timing-Dependent Synaptic Long-Term Potentiation in Adult Spinal Projection Neurons

Mounting evidence from both humans and rodents suggests that tissue damage during the neonatal period can "prime" developing nociceptive pathways such that a subsequent injury during adulthood causes an exacerbated degree of pain hypersensitivity. However, the cellular and molecular mechanisms that underlie this priming effect remain poorly understood. Here, we demonstrate that neonatal surgical injury relaxes the timing rules governing long-term potentiation (LTP) at mouse primary afferent synapses onto mature lamina I projection neurons, which serve as a major output of the spinal nociceptive network and are essential for pain perception. In addition, whereas LTP in naive mice was only observed if the presynaptic input preceded postsynaptic firing, early tissue injury removed this temporal requirement and LTP was observed regardless of the order in which the inputs were activated. Neonatal tissue damage also reduced the dependence of spike-timing-dependent LTP on NMDAR activation and unmasked a novel contribution of Ca(2+)-permeable AMPARs. These results suggest for the first time that transient tissue damage during early life creates a more permissive environment for the production of LTP within adult spinal nociceptive circuits. This persistent metaplasticity may promote the excessive amplification of ascending nociceptive transmission to the mature brain and thereby facilitate the generation of chronic pain after injury, thus representing a novel potential mechanism by which early trauma can prime adult pain pathways in the CNS.

SIGNIFICANCE STATEMENT

Tissue damage during early life can "prime" developing nociceptive pathways in the CNS, leading to greater pain severity after repeat injury via mechanisms that remain poorly understood. Here, we demonstrate that neonatal surgical injury widens the timing window during which correlated presynaptic and postsynaptic activity can evoke long-term potentiation (LTP) at sensory synapses onto adult lamina I projection neurons, which serve as a major output of the spinal nociceptive circuit and are essential for pain perception. This persistent increase in the likelihood of LTP induction after neonatal injury is predicted to favor the excessive amplification of ascending nociceptive transmission to the mature brain in response to subsequent injury and thereby exacerbate chronic pain.

Timing-dependent LTP and LTD in mouse primary visual cortex following different visual deprivation models

Visual deprivation during the critical period induces long-lasting changes in cortical circuitry by adaptively modifying neuro-transmission and synaptic connectivity at synapses. Spike timing-dependent plasticity (STDP) is considered a strong candidate for experience-dependent changes. However, the visual deprivation forms that affect timing-dependent long-term potentiation(LTP) and long-term depression(LTD) remain unclear. Here, we demonstrated the temporal window changes of tLTP and tLTD, elicited by coincidental pre- and post-synaptic firing, following different modes of 6-day visual deprivation. Markedly broader temporal windows were found in robust tLTP and tLTD in the V1M of the deprived visual cortex in mice after 6-day MD and DE. The underlying mechanism for the changes seen with visual deprivation in juvenile mice using 6 days of dark exposure or monocular lid suture involves an increased fraction of NR2b-containing NMDAR and the consequent prolongation of NMDAR-mediated response duration. Moreover, a decrease in NR2A protein expression at the synapse is attributable to the reduction of the NR2A/2B ratio in the deprived cortex.

Rewiring of Developing Spinal Nociceptive Circuits by Neonatal Injury and Its Implications for Pediatric Chronic Pain

Significant evidence now suggests that neonatal tissue damage can evoke long-lasting changes in pain sensitivity, but the underlying cellular and molecular mechanisms remain unclear. This review highlights recent advances in our understanding of how injuries during a critical period of early life modulate the functional organization of synaptic networks in the superficial dorsal horn (SDH) of the spinal cord in a manner that favors the excessive amplification of ascending nociceptive signaling to the brain, which likely contributes to the generation and/or maintenance of pediatric chronic pain. These persistent alterations in synaptic function within the SDH may also contribute to the well-documented "priming" of developing pain pathways by neonatal tissue injury.

An Embodied Brain Model of the Human Foetus

Cortical learning via sensorimotor experiences evoked by bodily movements begins as early as the foetal period. However, the learning mechanisms by which sensorimotor experiences guide cortical learning remain unknown owing to technical and ethical difficulties. To bridge this gap, we present an embodied brain model of a human foetus as a coupled brain-body-environment system by integrating anatomical/physiological data. Using this model, we show how intrauterine sensorimotor experiences related to bodily movements induce specific statistical regularities in somatosensory feedback that facilitate cortical learning of body representations and subsequent visual-somatosensory integration. We also show how extrauterine sensorimotor experiences affect these processes. Our embodied brain model can provide a novel computational approach to the mechanistic understanding of cortical learning based on sensorimotor experiences mediated by complex interactions between the body, environment and nervous system.

Long-Term Potentiation by Theta-Burst Stimulation Using Extracellular Field Potential Recordings in Acute Hippocampal Slices

This protocol describes how to carry out theta-burst long-term potentiation (LTP) with extracellular field recordings in acute rodent hippocampal slices. This method is relatively simple and noninvasive and provides a way to sample many neurons simultaneously, making it suitable for applications requiring higher throughput than whole-cell recording.

Roles of Presynaptic NMDA Receptors in Neurotransmission and Plasticity

Presynaptic NMDA receptors (preNMDARs) play pivotal roles in excitatory neurotransmission and synaptic plasticity. They facilitate presynaptic neurotransmitter release and modulate mechanisms controlling synaptic maturation and plasticity during formative periods of brain development. There is an increasing understanding of the roles of preNMDARs in experience-dependent synaptic and circuit-specific computation. In this review we summarize the latest understanding of compartment-specific expression and function of preNMDARs, and how they contribute to synapse-specific and circuit-level information processing.

Synapse-type-specific plasticity in local circuits

Neuroscientists spent decades debating whether synaptic plasticity was presynaptically or postsynaptically expressed. It was eventually concluded that plasticity depends on many factors, including cell type. More recently, it has become increasingly clear that plasticity is regulated at an even finer grained level; it is specific to the synapse type, a concept we denote synapse-type-specific plasticity (STSP). Here, we review recent developments in the field of STSP, discussing both long-term and short-term variants and with particular emphasis on neocortical function. As there are dozens of neocortical cell types, there is a multiplicity of forms of STSP, the vast majority of which have never been explored. We argue that to understand the brain and synaptic diseases, we have to grapple with STSP.

Bimodal stimulus timing-dependent plasticity in primary auditory cortex is altered after noise exposure with and without tinnitus

Central auditory circuits are influenced by the somatosensory system, a relationship that may underlie tinnitus generation. In the guinea pig dorsal cochlear nucleus (DCN), pairing spinal trigeminal nucleus (Sp5) stimulation with tones at specific intervals and orders facilitated or suppressed subsequent tone-evoked neural responses, reflecting spike timing-dependent plasticity (STDP). Furthermore, after noise-induced tinnitus, bimodal responses in DCN were shifted from Hebbian to anti-Hebbian timing rules with less discrete temporal windows, suggesting a role for bimodal plasticity in tinnitus. Here, we aimed to determine if multisensory STDP principles like those in DCN also exist in primary auditory cortex (A1), and whether they change following noise-induced tinnitus. Tone-evoked and spontaneous neural responses were recorded before and 15 min after bimodal stimulation in which the intervals and orders of auditory-somatosensory stimuli were randomized. Tone-evoked and spontaneous firing rates were influenced by the interval and order of the bimodal stimuli, and in sham-controls Hebbian-like timing rules predominated as was seen in DCN. In noise-exposed animals with and without tinnitus, timing rules shifted away from those found in sham-controls to more anti-Hebbian rules. Only those animals with evidence of tinnitus showed increased spontaneous firing rates, a purported neurophysiological correlate of tinnitus in A1. Together, these findings suggest that bimodal plasticity is also evident in A1 following noise damage and may have implications for tinnitus generation and therapeutic intervention across the central auditory circuit.

Plasticity of cortical excitatory-inhibitory balance

Synapses are highly plastic and are modified by changes in patterns of neural activity or sensory experience. Plasticity of cortical excitatory synapses is thought to be important for learning and memory, leading to alterations in sensory representations and cognitive maps. However, these changes must be coordinated across other synapses within local circuits to preserve neural coding schemes and the organization of excitatory and inhibitory inputs, i.e., excitatory-inhibitory balance. Recent studies indicate that inhibitory synapses are also plastic and are controlled directly by a large number of neuromodulators, particularly during episodes of learning. Many modulators transiently alter excitatory-inhibitory balance by decreasing inhibition, and thus disinhibition has emerged as a major mechanism by which neuromodulation might enable long-term synaptic modifications naturally. This review examines the relationships between neuromodulation and synaptic plasticity, focusing on the induction of long-term changes that collectively enhance cortical excitatory-inhibitory balance for improving perception and behavior.

Synapse-specific control of experience-dependent plasticity by presynaptic NMDA receptors

Sensory experience orchestrates the development of cortical circuitry by adaptively modifying neurotransmission and synaptic connectivity. However, the mechanisms underlying these experience-dependent modifications remain elusive. Here we demonstrate that visual experience suppresses a presynaptic NMDA receptor (preNMDAR)-mediated form of timing-dependent long-term depression (tLTD) at visual cortex layer (L) 4-2/3 synapses. This tLTD can be maintained during development, or reinstated in adulthood, by sensory deprivation. The changes in tLTD are mirrored by changes in glutamate release; visual deprivation enhances both tLTD and glutamate release. These effects require the GluN3A NMDAR subunit, the levels of which are increased by visual deprivation. Further, by coupling the pathway-specific optogenetic induction of tLTD with cell-type-specific NMDAR deletion, we find that visual experience modifies preNMDAR-mediated plasticity specifically at L4-L2/3 synapses.

The Convallis rule for unsupervised learning in cortical networks

The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the "Convallis rule", mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex.

A role for silent synapses in the development of the pathway from layer 2/3 to 5 pyramidal cells in the neocortex

The integration of neurons within the developing cerebral cortex is a prolonged process dependent on a combination of molecular and physiological cues. To examine the latter we used laser scanning photostimulation (LSPS) of caged glutamate in conjunction with whole-cell patch-clamp electrophysiology to probe the integration of pyramidal cells in the sensorimotor regions of the mouse neocortex. In the days immediately after postnatal day 5 (P5) the origin of the LSPS-evoked AMPA receptor (AMPAR)-mediated synaptic inputs were diffuse and poorly defined with considerable variability between cells. Over the subsequent week this coalesced and shifted, primarily influenced by an increased contribution from layers 2/3 cells, which became a prominent motif of the afferent input onto layer 5 pyramidal cells regardless of cortical region. To further investigate this particular emergent translaminar connection, we alternated our mapping protocol between two holding potentials (-70 and +40 mV) allowing us to detect exclusively NMDA receptor (NMDAR)-mediated inputs. This revealed distal MK-801-sensitive synaptic inputs that predict the formation of the mature, canonical layer 2/3 to 5 pathway. However, these were a transient feature and had been almost entirely converted to AMPAR synapses at a later age (P16). To examine the role of activity in the recruitment of early NMDAR synapses, we evoked brief periods (20 min) of rhythmic bursting. Short intense periods of activity could cause a prolonged augmentation of the total input onto pyramidal cells up until P12; a time point when the canonical circuit has been instated and synaptic integration shifts to a more consolidatory phase.

Long-term memory search across the visual brain

Signal transmission from the human retina to visual cortex and connectivity of visual brain areas are relatively well understood. How specific visual perceptions transform into corresponding long-term memories remains unknown. Here, I will review recent Blood Oxygenation Level-Dependent functional Magnetic Resonance Imaging (BOLD fMRI) in humans together with molecular biology studies (animal models) aiming to understand how the retinal image gets transformed into so-called visual (retinotropic) maps. The broken object paradigm has been chosen in order to illustrate the complexity of multisensory perception of simple objects subject to visual —rather than semantic— type of memory encoding. The author explores how amygdala projections to the visual cortex affect the memory formation and proposes the choice of experimental techniques needed to explain our massive visual memory capacity. Maintenance of the visual long-term memories is suggested to require recycling of GluR2-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPAR) and β₂-adrenoreceptors at the postsynaptic membrane, which critically depends on the catalytic activity of the N-ethylmaleimide-sensitive factor (NSF) and protein kinase PKMζ.

NR3A-containing NMDARs promote neurotransmitter release and spike timing-dependent plasticity

Recent evidence suggests that presynaptic-acting NMDA receptors (preNMDARs) are important for neocortical synaptic transmission and plasticity. We found that unique properties of the NR3A subunit enable preNMDARs to enhance spontaneous and evoked glutamate release and that NR3A is required for spike timing-dependent long-term depression in the juvenile mouse visual cortex. In the mature cortex, NR2B-containing preNMDARs enhanced neurotransmission in the absence of magnesium, indicating that presynaptic NMDARs may function under depolarizing conditions throughout life. Our findings indicate that NR3A relieves preNMDARs from the dual-activation requirement of ligand-binding and depolarization; the developmental removal of NR3A limits preNMDAR functionality by restoring this associative property.