Modulation of spike timing by sensory deprivation during induction of cortical map plasticity

Experience-dependent regulation of dopaminergic signaling in the somatosensory cortex

Dopamine critically influences reward processing, sensory perception, and motor control. Yet, the modulation of dopaminergic signaling by sensory experiences is not fully delineated. Here, by manipulating sensory experience using bilateral single-row whisker deprivation, we demonstrated that gene transcription in the dopaminergic signaling pathway (DSP) undergoes experience-dependent plasticity in both granular and supragranular layers of the primary somatosensory (barrel) cortex (S1). Sensory experience and deprivation compete for the regulation of DSP transcription across neighboring cortical columns, and sensory deprivation-induced changes in DSP are topographically constrained. These changes in DSP extend beyond cortical map plasticity and influence neuronal information processing. Pharmacological regulation of D2 receptors, a key component of DSP, revealed that D2 receptor activation suppresses excitatory neuronal excitability, hyperpolarizes the action potential threshold, and reduces the instantaneous firing rate. These findings suggest that the dopaminergic drive originating from midbrain dopaminergic neurons, targeting the sensory cortex, is subject to experience-dependent regulation and might create a regulatory feedback loop for modulating sensory processing. Finally, using topological gene network analysis and mutual information, we identify the molecular hubs of experience-dependent plasticity of DSP. These findings provide new insights into the mechanisms by which sensory experience shapes dopaminergic signaling in the brain and might help unravel the sensory deficits observed after dopamine depletion.

The tuning of tuning: How adaptation influences single cell information transfer

Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the 'h-current', and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed.

Artificial cerebellum on FPGA: realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control

The cerebellum plays a central role in motor control and learning. Its neuronal network architecture, firing characteristics of component neurons, and learning rules at their synapses have been well understood in terms of anatomy and physiology. A realistic artificial cerebellum with mimetic network architecture and synaptic plasticity mechanisms may allow us to analyze cerebellar information processing in the real world by applying it to adaptive control of actual machines. Several artificial cerebellums have previously been constructed, but they require high-performance hardware to run in real-time for real-world machine control. Presently, we implemented an artificial cerebellum with the size of 104 spiking neuron models on a field-programmable gate array (FPGA) which is compact, lightweight, portable, and low-power-consumption. In the implementation three novel techniques are employed: (1) 16-bit fixed-point operation and randomized rounding, (2) fully connected spike information transmission, and (3) alternative memory that uses pseudo-random number generators. We demonstrate that the FPGA artificial cerebellum runs in real-time, and its component neuron models behave as those in the corresponding artificial cerebellum configured on a personal computer in Python. We applied the FPGA artificial cerebellum to the adaptive control of a machine in the real world and demonstrated that the artificial cerebellum is capable of adaptively reducing control error after sudden load changes. This is the first implementation and demonstration of a spiking artificial cerebellum on an FPGA applicable to real-world adaptive control. The FPGA artificial cerebellum may provide neuroscientific insights into cerebellar information processing in adaptive motor control and may be applied to various neuro-devices to augment and extend human motor control capabilities.

Conditioning and pseudoconditioning differently change intrinsic excitability of inhibitory interneurons in the neocortex

Many studies indicate a broad role of various classes of GABAergic interneurons in the processes related to learning. However, little is known about how the learning process affects intrinsic excitability of specific classes of interneurons in the neocortex. To determine this, we employed a simple model of conditional learning in mice where vibrissae stimulation was used as a conditioned stimulus and a tail shock as an unconditioned one. In vitro whole-cell patch-clamp recordings showed an increase in intrinsic excitability of low-threshold spiking somatostatin-expressing interneurons (SST-INs) in layer 4 (L4) of the somatosensory (barrel) cortex after the conditioning paradigm. In contrast, pseudoconditioning reduced intrinsic excitability of SST-LTS, parvalbumin-expressing interneurons (PV-INs), and vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) with accommodating pattern in L4 of the barrel cortex. In general, increased intrinsic excitability was accompanied by narrowing of action potentials (APs), whereas decreased intrinsic excitability coincided with AP broadening. Altogether, these results show that both conditioning and pseudoconditioning lead to plastic changes in intrinsic excitability of GABAergic interneurons in a cell-specific manner. In this way, changes in intrinsic excitability can be perceived as a common mechanism of learning-induced plasticity in the GABAergic system.

Timing to be precise? An overview of spike timing-dependent plasticity, brain rhythmicity, and glial cells interplay within neuronal circuits

In the mammalian brain information processing and storage rely on the complex coding and decoding events performed by neuronal networks. These actions are based on the computational ability of neurons and their functional engagement in neuronal assemblies where precise timing of action potential firing is crucial. Neuronal circuits manage a myriad of spatially and temporally overlapping inputs to compute specific outputs that are proposed to underly memory traces formation, sensory perception, and cognitive behaviors. Spike-timing-dependent plasticity (STDP) and electrical brain rhythms are suggested to underlie such functions while the physiological evidence of assembly structures and mechanisms driving both processes continues to be scarce. Here, we review foundational and current evidence on timing precision and cooperative neuronal electrical activity driving STDP and brain rhythms, their interactions, and the emerging role of glial cells in such processes. We also provide an overview of their cognitive correlates and discuss current limitations and controversies, future perspectives on experimental approaches, and their application in humans.

Neuronal and astrocyte determinants of critical periods of plasticity

Windows of plasticity allow environmental experiences to produce intense activity-dependent changes during postnatal development. The reordering and refinement of neural connections occurs during these periods, significantly influencing the formation of brain circuits and physiological processes in adults. Recent advances have shed light on factors that determine the onset and duration of sensitive and critical periods of plasticity. Although GABAergic inhibition has classically been implicated in closing windows of plasticity, astrocytes and adenosinergic inhibition have also emerged more recently as key determinants of the duration of these periods of plasticity. Here, we review novel aspects of the involvement of GABAergic inhibition, the possible role of presynaptic NMDARs, and the emerging roles of astrocytes and adenosinergic inhibition in determining the duration of windows of plasticity in different brain regions.

Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on 1D supramolecular nanofibres

Mimicking synaptic functions in hardware devices is a crucial step in realizing brain-like computing beyond the von Neumann architecture. 1D nanomaterials with spatial extensions of a few μm, similar to biological neurons, gain significance given the ease of electrical transport as well as directionality. Herein, we report a two-terminal optically active device based on 1D supramolecular nanofibres consisting of CS (coronene tetracarboxylate) and DMV (dimethyl viologen) forming alternating D-A (donor-acceptor) pairs, emulating synaptic functions such as the STP (short-term potentiation), LTP (long-term potentiation), PPF (paired-pulse facilitation), STDP (spike-time dependent plasticity) and learning-relearning behaviors. In addition, an extensive study on the less explored Ebbinghaus forgetting curve has been carried out. The supramolecular nanofibres being light sensitive, the potential of the device as a visual system is demonstrated using a 3 × 3 pixel array.

Endocannabinoid-dependent formation of columnar axonal projection in the mouse cerebral cortex

Columnar structure is one of the most fundamental morphological features of the cerebral cortex and is thought to be the basis of information processing in higher animals. Yet, how such a topographically precise structure is formed is largely unknown. Formation of columnar projection of layer 4 (L4) axons is preceded by thalamocortical formation, in which type 1 cannabinoid receptors (CB1R) play an important role in shaping barrel-specific targeted projection by operating spike timing-dependent plasticity during development (Itami et al., J. Neurosci. 36, 7039-7054 [2016]; Kimura & Itami, J. Neurosci. 39, 3784-3791 [2019]). Right after the formation of thalamocortical projections, CB1Rs start to function at L4 axon terminals (Itami & Kimura, J. Neurosci. 32, 15000-15011 [2012]), which coincides with the timing of columnar shaping of L4 axons. Here, we show that the endocannabinoid 2-arachidonoylglycerol (2-AG) plays a crucial role in columnar shaping. We found that L4 axon projections were less organized until P12 and then became columnar after CB1Rs became functional. By contrast, the columnar organization of L4 axons was collapsed in mice genetically lacking diacylglycerol lipase α, the major enzyme for 2-AG synthesis. Intraperitoneally administered CB1R agonists shortened axon length, whereas knockout of CB1R in L4 neurons impaired columnar projection of their axons. Our results suggest that endocannabinoid signaling is crucial for shaping columnar axonal projection in the cerebral cortex.

Ultralow Power Wearable Organic Ferroelectric Device for Optoelectronic Neuromorphic Computing

In order to imitate brain-inspired biological information processing systems, various neuromorphic computing devices have been proposed, most of which were prepared on rigid substrates and have energy consumption levels several orders of magnitude higher than those of biological synapses (∼10 fJ per spike). Herein, a new type of wearable organic ferroelectric artificial synapse is proposed, which has two modulation modes (optical and electrical modulation). Because of the high photosensitivity of organic semiconductors and the ultrafast polarization switching of ferroelectric materials, the synaptic device has an ultrafast operation speed of 30 ns and an ultralow power consumption of 0.0675 aJ per synaptic event. Under combined photoelectric modulation, the artificial synapse realizes associative learning. The proposed artificial synapse with ultralow power consumption demonstrates good synaptic plasticity under different bending strains. This provides new avenues for the construction of ultralow power artificial intelligence system and the development of future wearable devices.

Neuromorphic computing hardware and neural architectures for robotics

Neuromorphic hardware enables fast and power-efficient neural network-based artificial intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be further developed following neural computing principles and neural network architectures inspired by biological neural systems. In this Viewpoint, we provide an overview of recent insights from neuroscience that could enhance signal processing in artificial neural networks on chip and unlock innovative applications in robotics and autonomous intelligent systems. These insights uncover computing principles, primitives, and algorithms on different levels of abstraction and call for more research into the basis of neural computation and neuronally inspired computing hardware.

Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex

Humans are exquisitely sensitive to the microstructure and material properties of surfaces. In the peripheral nerves, texture information is conveyed via two mechanisms: coarse textural features are encoded in spatial patterns of activation that reflect their spatial layout, and fine features are encoded in highly repeatable, texture-specific temporal spiking patterns evoked as the skin moves across the surface. Here, we examined whether this temporal code is preserved in the responses of neurons in somatosensory cortex. We scanned a diverse set of everyday textures across the fingertip of awake macaques while recording the responses evoked in individual cortical neurons. We found that temporal spiking patterns are highly repeatable across multiple presentations of the same texture, with millisecond precision. As a result, texture identity can be reliably decoded from the temporal patterns themselves, even after information carried in the spike rates is eliminated. However, the combination of rate and timing is more informative than either code in isolation. The temporal precision of the texture response is heterogenous across cortical neurons and depends on the submodality composition of their input and on their location along the somatosensory neuraxis. Furthermore, temporal spiking patterns in cortex dilate and contract with decreases and increases in scanning speed, respectively, and this systematic relationship between speed and patterning may contribute to the observed perceptual invariance to speed. Finally, we find that the quality of a texture percept can be better predicted when these temporal patterns are taken into consideration. We conclude that high-precision spike timing complements rate-based signals to encode texture in somatosensory cortex.

Neuroscientists seek to understand how neuronal signals carry information and drive perception. Here, the authors show that millisecond-level spike timing in somatosensory cortex is informative about texture and shapes the evoked sensory experience.

Cortical Representation of Touch in Silico

With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

The Role of Interhemispheric Interactions in Cortical Plasticity

Despite the fact that there is a growing awareness to the callosal connections between hemispheres the two hemispheres of the brain are commonly treated as independent structures when peripheral or cortical manipulations are applied to one of them. The contralateral hemisphere is often used as a within-animal control of plastic changes induced onto the other side of the brain. This ensures uniform conditions for producing experimental and control data, but it may overlook possible interhemispheric interactions. In this paper we provide, for the first time, direct proof that cortical, experience-dependent plasticity is not a unilateral, independent process. We mapped metabolic brain activity in rats with 2-[¹⁴C] deoxyglucose (2DG) following experience-dependent plasticity induction after a month of unilateral (left), partial whiskers deprivation (only row B was left). This resulted in ∼45% widening of the cortical sensory representation of the spared whiskers in the right, contralateral barrel field (BF). We show that the width of 2DG visualized representation is less than 20% when only contralateral stimulation of the spared row of whiskers is applied in immobilized animals. This means that cortical map remodeling, which is induced by experience-dependent plasticity mechanisms, depends partially on the contralateral hemisphere. The response, which is observed by 2DG brain mapping in the partially deprived BF after standard synchronous bilateral whiskers stimulation, is therefore the outcome of at least two separately activated plasticity mechanisms. A focus on the integrated nature of cortical plasticity, which is the outcome of the emergent interactions between deprived and non-deprived areas in both hemispheres may have important implications for learning and rehabilitation. There is also a clear implication that there is nothing like “control hemisphere” since any plastic changes in one hemisphere have to have influence on functioning of the opposite one.

Flexible organic field-effect transistor arrays for wearable neuromorphic device applications

With the advent of wearable microelectronic devices in the interdisciplinary bio-electronics research field, synaptic devices with capability of neuromorphic computing are attracting more and more attention as the building blocks for the next generation computing structure. Conventional flash-like synaptic transistors are built on rigid solid-state substrates, and the inorganic materials and the high-temperature processing steps have severely limited their applications in various flexible electronic devices and systems. Here, flexible organic flash-like synaptic devices have been fabricated on a flexible substrate with the organic C8-BTBT as the conducting channel. The device exhibits a memory window greater than 20 V and excellent synaptic functions including short/long-term synaptic plasticity and spike-timing-dependent plasticity. In addition, even under the bending condition (7 mm bending radius), the transistor can still stably achieve a variety of synaptic functions. This work shows that low-temperature processing technology with the integration of organic materials can pave a promising pathway for the realization of flexible synaptic systems and the future development of wearable electronic devices.

Optical Analysis of Acute Changes after Peripheral Nerve Injury in Spatio-Temporal Pattern of Neural Response to Forelimb Stimulation in Rat Somatosensory Cortex

Peripheral nerve injury induces functional reorganization of the central nervous system. The mechanisms underlying this reorganization have been widely studied. Our previous study involving multiple-site optical recording reported that a neural excitatory wave induced by somatic stimulation begins in a small area and propagates in the cortex. In the present study, to examine the possible role of this propagation wave in cortical reorganization, we analyzed the early changes in the spatio-temporal pattern of the sensory-evoked wave immediately, and 30 min, after nerve injury. The response to hypothenar stimulation, innervated by the ulnar nerve and adjoining the median nerve area, persisted after injury to either the ulnar or median nerve. Initially, we assessed changes in the response pattern at the focus. The latency increased after ulnar nerve injury, whereas no change was observed after median nerve injury. Similarly, no change was noted in the duration of the response signal with either nerve injury. Second, changes in the propagation wave pattern were analyzed. Ulnar nerve injury decreased the propagation velocity in the medial direction but the median nerve injury induced no changes. These results indicated that the propagation wave pattern is readily altered, even immediately after nerve injury, and suggest that this immediate change in the spatio-temporal pattern is one of the factors contributing to the cortical reorganization.

How the Barrel Cortex Became a Working Model for Developmental Plasticity: A Historical Perspective

For half a century now, the barrel cortex of common laboratory rodents has been an exceptionally useful model for studying the formation of topographically organized maps, neural patterning, and plasticity, both in development and in maturity. We present a historical perspective on how barrels were discovered, and how thereafter, they became a workhorse for developmental neuroscientists and for studies on brain plasticity and activity-dependent modeling of brain circuits. What is particularly remarkable about this sensory system is a cellular patterning that is induced by signals derived from the sensory receptors surrounding the snout whiskers and transmitted centrally to the brainstem (barrelettes), the thalamus (barreloids), and the neocortex (barrels). Injury to the sensory receptors shortly after birth leads to predictable pattern alterations at all levels of the system. Mouse genetics have increased our understanding of how barrels are constructed and revealed the interplay of the molecular programs that direct axon growth and cell specification, with activity-dependent mechanisms. There is an ever-rising interest in this sensory system as a neurobiological model to study development of somatotopy, patterning, and plasticity at both the morphologic and physiological levels. This article is part of a group of articles commemorating the 50th anniversary of the Society for Neuroscience.

Dual-Component Structural Plasticity Mediated by αCaMKII Autophosphorylation on Basal Dendrites of Cortical Layer 2/3 Neurones

Sensory cortex exhibits receptive field plasticity throughout life in response to changes in sensory experience and offers the experimental possibility of aligning functional changes in receptive field properties with underpinning structural changes in synapses. We looked at the effects on structural plasticity of two different patterns of whisker deprivation in male and female mice: chessboard deprivation, which causes functional plasticity; and all deprived, which does not. Using 2-photon microscopy and chronic imaging through a cranial window over the barrel cortex, we found that layer 2/3 neurones exhibit robust structural plasticity, but only in response to whisker deprivation patterns that cause functional plasticity. Chessboard pattern deprivation caused dual-component plasticity in layer 2/3 by (1) increasing production of new spines that subsequently persisted for weeks and (2) enlarging spine head sizes in the preexisting stable spine population. Structural plasticity occurred on basal dendrites, but not apical dendrites. Both components of plasticity were absent in αCaMKII-T286A mutants that lack LTP and experience-dependent potentiation in barrel cortex, implying that αCaMKII autophosphorylation is not only important for stabilization and enlargement of spines, but also for new spine production. These studies therefore reveal the relationship between spared whisker potentiation in layer 2/3 neurones and the form and mechanisms of structural plasticity processes that underlie them.SIGNIFICANCE STATEMENT This study provides a missing link in a chain of reasoning that connects LTP to experience-dependent functional plasticity in vivo We found that increases in dendritic spine formation and spine enlargement (both of which are characteristic of LTP) only occurred in barrel cortex during sensory deprivation that produced potentiation of sensory responses. Furthermore, the dendritic spine plasticity did not occur during sensory deprivation in mice lacking LTP and experience-dependent potentiation (αCaMKII autophosphorylation mutants). We also found that the dual-component dendritic spine plasticity only occurred on basal dendrites and not on apical dendrites, thereby resolving a paradox in the literature suggesting that layer 2/3 neurones lack structural plasticity in response to sensory deprivation.

Cellular and synaptic phenotypes lead to disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex

Sensory hypersensitivity is a common and debilitating feature of neurodevelopmental disorders such as Fragile X Syndrome (FXS). How developmental changes in neuronal function culminate in network dysfunction that underlies sensory hypersensitivities is unknown. By systematically studying cellular and synaptic properties of layer 4 neurons combined with cellular and network simulations, we explored how the array of phenotypes in Fmr1-knockout (KO) mice produce circuit pathology during development. We show that many of the cellular and synaptic pathologies in Fmr1-KO mice are antagonistic, mitigating circuit dysfunction, and hence may be compensatory to the primary pathology. Overall, the layer 4 network in the Fmr1-KO exhibits significant alterations in spike output in response to thalamocortical input and distorted sensory encoding. This developmental loss of layer 4 sensory encoding precision would contribute to subsequent developmental alterations in layer 4-to-layer 2/3 connectivity and plasticity observed in Fmr1-KO mice, and circuit dysfunction underlying sensory hypersensitivity.

Real-time contextual feedback for close-loop control of navigation

OBJECTIVE

Close-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors.

APPROACH

Here we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization.

MAIN RESULTS

As a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity (⩾49 dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20 min).

SIGNIFICANCE

Neuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.

A Hypothetical Model Concerning How Spike-Timing-Dependent Plasticity Contributes to Neural Circuit Formation and Initiation of the Critical Period in Barrel Cortex

Spike timing is an important factor in the modification of synaptic strength. Various forms of spike timing-dependent plasticity (STDP) occur in the brains of diverse species, from insects to humans. In unimodal STDP, only LTP or LTD occurs at the synapse, regardless of which neuron spikes first; the magnitude of potentiation or depression increases as the time between presynaptic and postsynaptic spikes decreases. This from of STDP may promote developmental strengthening or weakening of early projections. In bidirectional Hebbian STDP, the magnitude and the sign (potentiation or depression) of plasticity depend, respectively, on the timing and the order of presynaptic and postsynaptic spikes. In the rodent barrel cortex, multiple forms of STDP appear sequentially during development, and they contribute to network formation, retraction, or fine-scale functional reorganization. Hebbian STDP appears at L4-L2/3 synapses starting at postnatal day (P) 15; the synapses exhibit unimodal "all-LTP STDP" before that age. The appearance of Hebbian STDP at L4-L2/3 synapses coincides with the maturation of parvalbumin-containing GABA interneurons in L4, which contributes to the generation of L4-before-L2/3 spiking in response to thalamic input by producing fast feedforward suppression of both L4 and L2/3 cells. After P15, L4-L2/3 STDP mediates fine-scale circuit refinement, essential for the critical period in the barrel cortex. In this review, we first briefly describe the relevance of STDP to map plasticity in the barrel cortex, then look over roles of distinct forms of STDP during development. Finally, we propose a hypothesis that explains the transition from network formation to the initiation of the critical period in the barrel cortex.

A databank for intracellular electrophysiological mapping of the adult somatosensory cortex

Background

Neurons in the supragranular layers of the somatosensory cortex integrate sensory (bottom-up) and cognitive/perceptual (top-down) information as they orchestrate communication across cortical columns. It has been inferred, based on intracellular recordings from juvenile animals, that supragranular neurons are electrically mature by the fourth postnatal week. However, the dynamics of the neuronal integration in adulthood is largely unknown. Electrophysiological characterization of the active properties of these neurons throughout adulthood will help to address the biophysical and computational principles of the neuronal integration.

Findings

Here, we provide a database of whole-cell intracellular recordings from 315 neurons located in the supragranular layers (L2/3) of the primary somatosensory cortex in adult mice (9–45 weeks old) from both sexes (females, N = 195; males, N = 120). Data include 361 somatic current-clamp (CC) and 476 voltage-clamp (VC) experiments, recorded using a step-and-hold protocol (CC, N = 257; VC, N = 46), frozen noise injections (CC, N = 104) and triangular voltage sweeps (VC, 10 (N = 132), 50 (N = 146) and 100 ms (N = 152)), from regular spiking (N = 169) and fast-spiking neurons (N = 66).

Conclusions

The data can be used to systematically study the properties of somatic integration and the principles of action potential generation across sexes and across electrically characterized neuronal classes in adulthood. Understanding the principles of the somatic transformation of postsynaptic potentials into action potentials will shed light onto the computational principles of intracellular information transfer in single neurons and information processing in neuronal networks, helping to recreate neuronal functions in artificial systems.

Neocortical Microdissection at Columnar and Laminar Resolution for Molecular Interrogation

The heterogeneous organization of the mammalian neocortex poses a challenge for elucidating the molecular mechanisms underlying its physiological processes. Although high-throughput molecular methods are increasingly deployed in neuroscience, their anatomical specificity is often lacking. In this unit, we introduce a targeted microdissection technique that enables extraction of high-quality RNA and proteins at high anatomical resolution from acutely prepared brain slices. We exemplify its utility by isolating single cortical columns and laminae from the mouse primary somatosensory (barrel) cortex. Tissues can be isolated from living slices in minutes, and the extracted RNA and protein are of sufficient quantity and quality to be used for RNA sequencing and mass spectrometry. This technique will help to increase the anatomical specificity of molecular studies of the neocortex, and the brain in general, as it is applicable to any brain structure that can be identified using optical landmarks in living slices. © 2018 by John Wiley & Sons, Inc.

Functional Relevance of Endocannabinoid-Dependent Synaptic Plasticity in the Central Nervous System

The endocannabinoid (eCB) signaling system plays a key role in short-term and long-term synaptic plasticity in brain regions involved in various neural functions ranging from action selection to appetite control. This review will explore the role of eCBs in shaping neural circuit function to regulate behaviors. In particular, we will discuss the behavioral consequences of eCB mediated long-term synaptic plasticity in different brain regions. This review brings together evidence from in vitro and ex vivo studies and points out the need for more in vivo studies.

Neural coding: A single neuron's perspective

What any sensory neuron knows about the world is one of the cardinal questions in Neuroscience. Information from the sensory periphery travels across synaptically coupled neurons as each neuron encodes information by varying the rate and timing of its action potentials (spikes). Spatiotemporally correlated changes in this spiking regimen across neuronal populations are the neural basis of sensory representations. In the somatosensory cortex, however, spiking of individual (or pairs of) cortical neurons is only minimally informative about the world. Recent studies showed that one solution neurons implement to counteract this information loss is adapting their rate of information transfer to the ongoing synaptic activity by changing the membrane potential at which spike is generated. Here we first introduce the principles of information flow from the sensory periphery to the primary sensory cortex in a model sensory (whisker) system, and subsequently discuss how the adaptive spike threshold gates the intracellular information transfer from the somatic post-synaptic potential to action potentials, controlling the information content of communication across somatosensory cortical neurons.

The pial vasculature of the mouse develops according to a sensory-independent program

The cerebral vasculature is organized to supply the brain’s metabolic needs. Sensory deprivation during the early postnatal period causes altered neural activity and lower metabolic demand. Neural activity is instructional for some aspects of vascular development, and deprivation causes changes in capillary density in the deprived brain region. However, it is not known if the pial arteriole network, which contains many leptomeningeal anastomoses (LMAs) that endow the network with redundancy against occlusions, is also affected by sensory deprivation. We quantified the effects of early-life sensory deprivation via whisker plucking on the densities of LMAs and penetrating arterioles (PAs) in anatomically-identified primary sensory regions (vibrissae cortex, forelimb/hindlimb cortex, visual cortex and auditory cortex) in mice. We found that the densities of penetrating arterioles were the same across cortical regions, though the hindlimb representation had a higher density of LMAs than other sensory regions. We found that the densities of PAs and LMAs, as well as quantitative measures of network topology, were not affected by sensory deprivation. Our results show that the postnatal development of the pial arterial network is robust to sensory deprivation.

Using Blogs as Practice Writing About Original Neuroscience Papers Enhances Students' Confidence in Their Critical Analysis of Research

Increasing emphasis is being put on providing students with opportunities to read and write about primary scientific literature in undergraduate neuroscience education. Extensive research has indicated that students' attitudes and self-efficacy as well as writing quality improve when they are provided with opportunities for practice and feedback. Here we tested the value of using a blog format to practice writing about scientific research articles. Students were assigned small groups and did work on their own individual schedules to build toward time allotted in class to discuss the articles with their groups. Our goal was to build confidence in the students' ability to read and analyze original research articles. We found that the students in the junior-level Systems Neuroscience course had high confidence in their ability to read and analyze papers at the end of the blogging experience. Surprisingly, however, this did not manifest in a change in quality of final, higher stakes, written reports on original research articles when compared to a control sample from a previous year that did not include the blog assignments. We conclude that blogs provide a useful format for students to discuss research articles collaboratively while building confidence in their ability to analyze and discuss original neuroscience articles. Although the final reports' quality did not change compared to the earlier offering of the course, we believe that the blog experience is a valuable tool for building confidence and creating a positive experience for students in learning to read and analyze original neuroscience research articles.

Coordinated neuronal ensembles in primary auditory cortical columns

The synchronous activity of groups of neurons is increasingly thought to be important in cortical information processing and transmission. However, most studies of processing in the primary auditory cortex (AI) have viewed neurons as independent filters; little is known about how coordinated AI neuronal activity is expressed throughout cortical columns and how it might enhance the processing of auditory information. To address this, we recorded from populations of neurons in AI cortical columns of anesthetized rats and, using dimensionality reduction techniques, identified multiple coordinated neuronal ensembles (cNEs), which are groups of neurons with reliable synchronous activity. We show that cNEs reflect local network configurations with enhanced information encoding properties that cannot be accounted for by stimulus-driven synchronization alone. Furthermore, similar cNEs were identified in both spontaneous and evoked activity, indicating that columnar cNEs are stable functional constructs that may represent principal units of information processing in AI.

Transcriptional mapping of the primary somatosensory cortex upon sensory deprivation

Experience-dependent plasticity (EDP) is essential for anatomical and functional maturation of sensory circuits during development. Although the principal synaptic and circuit mechanisms of EDP are increasingly well studied experimentally and computationally, its molecular mechanisms remain largely elusive. EDP can be readily studied in the rodent barrel cortex, where each “barrel column” preferentially represents deflections of its own principal whisker. Depriving select whiskers while sparing their neighbours introduces competition between barrel columns, ultimately leading to weakening of intracortical, translaminar (i.e., cortical layer (L)4-to-L2/3) feed-forward excitatory projections in the deprived columns. The same synapses are potentiated in the neighbouring spared columns. These experience-dependent alterations of synaptic strength are thought to underlie somatosensory map plasticity. We used RNA sequencing in this model system to uncover cortical-column and -layer specific changes on the transcriptome level that are induced by altered sensory experience. Column- and layer-specific barrel cortical tissues were collected from juvenile mice with all whiskers intact and mice that received 11–12 days of long whisker (C-row) deprivation before high-quality RNA was purified and sequenced. The current dataset entails an average of 50 million paired-end reads per sample, 75 base pairs in length. On average, 90.15% of reads could be uniquely mapped to the mm10 reference mouse genome. The current data reveal the transcriptional changes in gene expression in the barrel cortex upon altered sensory experience in juvenile mice and will help to molecularly map the mechanisms of cortical plasticity.

Robustness of STDP to spike timing jitter

In Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing. Spike-timing-dependent plasticity (STDP), a synaptic Hebbian learning rule, relies on the order and timing of the paired activities in pre- and postsynaptic neurons. Classically, in ex vivo experiments, STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that differs from biological variability. Hence, STDP emergence from noisy inputs as occurring in in vivo-like firing remains unresolved. Here, we used noisy STDP pairings where the spike timing and/or interval between pairings were jittered. We explored with electrophysiology and mathematical modeling, the impact of jitter on three forms of STDP at corticostriatal synapses: NMDAR-LTP, endocannabinoid-LTD and endocannabinoid-LTP. We found that NMDAR-LTP was highly fragile to jitter, whereas endocannabinoid-plasticity appeared more resistant. When the frequency or number of pairings was increased, NMDAR-LTP became more robust and could be expressed despite strong jittering. Our results identify endocannabinoid-plasticity as a robust form of STDP, whereas the sensitivity to jitter of NMDAR-LTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like activity.

Somatosensory maps

Somatosensory areas containing topographic maps of the body surface are a major feature of parietal cortex. In primates, parietal cortex contains four somatosensory areas, each with its own map, with the primary cutaneous map in area 3b. Rodents have at least three parietal somatosensory areas. Maps are not isomorphic to the body surface, but magnify behaviorally important skin regions, which include the hands and face in primates, and the whiskers in rodents. Within each map, intracortical circuits process tactile information, mediate spatial integration, and support active sensation. Maps may also contain fine-scale representations of touch submodalities, or direction of tactile motion. Functional representations are more overlapping than suggested by textbook depictions of map topography. The whisker map in rodent somatosensory cortex is a canonic system for studying cortical microcircuits, sensory coding, and map plasticity. Somatosensory maps are plastic throughout life in response to altered use or injury. This chapter reviews basic principles and recent findings in primate, human, and rodent somatosensory maps.

Multiple shared mechanisms for homeostatic plasticity in rodent somatosensory and visual cortex

We compare the circuit and cellular mechanisms for homeostatic plasticity that have been discovered in rodent somatosensory (S1) and visual (V1) cortex. Both areas use similar mechanisms to restore mean firing rate after sensory deprivation. Two time scales of homeostasis are evident, with distinct mechanisms. Slow homeostasis occurs over several days, and is mediated by homeostatic synaptic scaling in excitatory networks and, in some cases, homeostatic adjustment of pyramidal cell intrinsic excitability. Fast homeostasis occurs within less than 1 day, and is mediated by rapid disinhibition, implemented by activity-dependent plasticity in parvalbumin interneuron circuits. These processes interact with Hebbian synaptic plasticity to maintain cortical firing rates during learned adjustments in sensory representations.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

Cellular diversity of the somatosensory cortical map plasticity

Sensory maps are representations of the sensory epithelia in the brain. Despite the intuitive explanatory power behind sensory maps as being neuronal precursors to sensory perception, and sensory cortical plasticity as a neural correlate of perceptual learning, molecular mechanisms that regulate map plasticity are not well understood. Here we perform a meta-analysis of transcriptional and translational changes during altered whisker use to nominate the major molecular correlates of experience-dependent map plasticity in the barrel cortex. We argue that brain plasticity is a systems level response, involving all cell classes, from neuron and glia to non-neuronal cells including endothelia. Using molecular pathway analysis, we further propose a gene regulatory network that could couple activity dependent changes in neurons to adaptive changes in neurovasculature, and finally we show that transcriptional regulations observed in major brain disorders target genes that are modulated by altered sensory experience. Thus, understanding the molecular mechanisms of experience-dependent plasticity of sensory maps might help to unravel the cellular events that shape brain plasticity in health and disease.

Proteomic landscape of the primary somatosensory cortex upon sensory deprivation

Experience-dependent plasticity (EDP) powerfully shapes neural circuits by inducing long-lasting molecular changes in the brain. Molecular mechanisms of EDP have been traditionally studied by identifying single or small subsets of targets along the biochemical pathways that link synaptic receptors to nuclear processes. Recent technological advances in large-scale analysis of gene transcription and translation now allow systematic observation of thousands of molecules simultaneously. Here we employed label-free quantitative mass spectrometry to address experience-dependent changes in the proteome after sensory deprivation of the primary somatosensory cortex. Cortical column- and layer-specific tissue samples were collected from control animals, with all whiskers intact, and animals whose C-row whiskers were bilaterally plucked for 11–14 days. Thirty-three samples from cortical layers (L) 2/3 and L4 spanning across control, deprived, and first- and second-order spared columns yielded at least 10 000 peptides mapping to ∼5000 protein groups. Of these, 4676 were identified with high confidence, and >3000 were found in all samples. This comprehensive database provides a snapshot of the proteome after whisker deprivation, a protocol that has been widely used to unravel the synaptic, cellular, and network mechanisms of EDP. Complementing the recently made available transcriptome for identical experimental conditions (see the accompanying article by Kole et al.), the database can be used to (i) mine novel targets whose translation is modulated by sensory organ use, (ii) cross-validate experimental protocols from the same developmental time point, and (iii) statistically map the molecular pathways of cortical plasticity at a columnar and laminar resolution.

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability

If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures impedes the achievement of three-dimensional interconnectivity, high-device density, or flexibility. Here we report flexible three-dimensional artificial chemical synapse networks, in which two-terminal memristive devices, namely, electronic synapses (e-synapses), are connected by vertically stacking crossbar electrodes. The e-synapses resemble the key features of biological synapses: unilateral connection, long-term potentiation/depression, a spike-timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow-power consumption. The three-dimensional artificial synapse networks enable a direct emulation of correlated learning and trainable memory capability with strong tolerances to input faults and variations, which shows the feasibility of using them in futuristic electronic devices and can provide a physical platform for the realization of smart memories and machine learning and for operation of the complex algorithms involving hierarchical neural networks.High-density information storage calls for the development of modern electronics with multiple stacking architectures that increase the complexity of three-dimensional interconnectivity. Here, Wu et al. build a stacked yet flexible artificial synapse network using layer-by-layer solution processing.

The role of glutamate transporters in the pathophysiology of neuropsychiatric disorders

Altered glutamate transporter expression is a common feature of many neuropsychiatric conditions, including schizophrenia. Excitatory amino acid transporters (EAATs) are responsible for the reuptake of glutamate, preventing non-physiological spillover from the synapse. Postmortem studies have revealed significant dysregulation of EAAT expression in various brain regions at the cellular and subcellular level. Recent animal studies have also demonstrated a role for glutamate spillover as a mechanism of disease. In this review, we describe current evidence for the role of glutamate transporters in regulating synaptic plasticity and transmission. In neuropsychiatric conditions, EAAT splice variant expression is altered. There are changes in the localization of the transporters and disruption of the metabolic and structural protein network that supports EAAT activity. This results in aberrant neuroplasticity and excitatory signaling, contributing to the symptoms associated with neuropsychiatric disease. Understanding the complex functions of glutamate transporters will clarify the relevance of their role in the pathophysiology of neuropsychiatric disorders.

Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate

Synaptic plasticity is sensitive to the rate and the timing of presynaptic and postsynaptic action potentials. In experimental protocols inducing plasticity, the imposed spike trains are typically regular and the relative timing between every presynaptic and postsynaptic spike is fixed. This is at odds with firing patterns observed in the cortex of intact animals, where cells fire irregularly and the timing between presynaptic and postsynaptic spikes varies. To investigate synaptic changes elicited by in vivo-like firing, we used numerical simulations and mathematical analysis of synaptic plasticity models. We found that the influence of spike timing on plasticity is weaker than expected from regular stimulation protocols. Moreover, when neurons fire irregularly, synaptic changes induced by precise spike timing can be equivalently induced by a modest firing rate variation. Our findings bridge the gap between existing results on synaptic plasticity and plasticity occurring in vivo, and challenge the dominant role of spike timing in plasticity.

SIGNIFICANCE STATEMENT

Synaptic plasticity, the change in efficacy of connections between neurons, is thought to underlie learning and memory. The dominant paradigm posits that the precise timing of neural action potentials (APs) is central for plasticity induction. This concept is based on experiments using highly regular and stereotyped patterns of APs, in stark contrast with natural neuronal activity. Using synaptic plasticity models, we investigated how irregular, in vivo-like activity shapes synaptic plasticity. We found that synaptic changes induced by precise timing of APs are much weaker than suggested by regular stimulation protocols, and can be equivalently induced by modest variations of the AP rate alone. Our results call into question the dominant role of precise AP timing for plasticity in natural conditions.

Symmetry of learning rate in synaptic plasticity modulates formation of flexible and stable memories

Spike-timing-dependent plasticity (STDP) is considered critical to learning and memory functions in the human brain. Across various types of synapse, STDP is observed as different profiles of Hebbian and anti-Hebbian learning rules. However, the specific roles of diverse STDP profiles in memory formation still remain elusive. Here, we show that the symmetry of the learning rate profile in STDP is crucial to determining the character of stored memory. Using computer simulations, we found that an asymmetric learning rate generates flexible memory that is volatile and easily overwritten by newly appended information. Moreover, a symmetric learning rate generates stable memory that can coexist with newly appended information. In addition, by combining these two conditions, we could realize a hybrid memory type that operates in a way intermediate between stable and flexible memory. Our results demonstrate that various attributes of memory functions may originate from differences in the synaptic stability.

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.

Anisomorphic cortical reorganization in asymmetric sensorineural hearing loss

Acoustic trauma or inner ear disease may predominantly injure one ear, causing asymmetric sensorineural hearing loss (SNHL). While characteristic frequency (CF) map plasticity of primary auditory cortex (AI) contralateral to the injured ear has been detailed, there is no study that also evaluates ipsilateral AI to compare cortical reorganization across both hemispheres. We assess whether the normal isomorphic mirror-image relationship between the two hemispheres is maintained or disrupted in mild-to-moderate asymmetric SNHL of adult squirrel monkeys. At week 24 after induction of acoustic injury to the right ear, functional organization of the two hemispheres differs in direction and magnitude of interaural CF difference, percentage of recording sites with spectrally nonoverlapping binaural activation, and the concurrence of peripheral and central activation thresholds. The emergence of this anisomorphic cortical reorganization of the two hemispheres is replicated by simulation based on spike timing-dependent plasticity, where 1) AI input from the contralateral ear is dominant, 2) reestablishment of relatively shorter contralateral ear input timing drives reorganization, and 3) only AI contralateral to the injured ear undergoes major realignment of interaural frequency maps that evolve over months. Asymmetric SNHL disrupts isomorphic organization between the two hemispheres and results in relative local hemispheric autonomy, potentially impairing performance of tasks that require binaural input alignment or interhemispheric processing.NEW & NOTEWORTHY Mild-to-moderate hearing loss in one ear and essentially normal hearing in the other triggers cortical reorganization that is different in the two hemispheres. Asymmetry of cochlea sensitivities does not simply propagate to the two auditory cortices in mirror-image fashion. The resulting anisomorphic cortical reorganization may be a neurophysiological basis of clinical deficits in asymmetric hearing loss, such as difficulty with hearing in noise, impaired spatial hearing, and accelerated decline of the poorer ear.

Time-course and mechanisms of homeostatic plasticity in layers 2/3 and 5 of the barrel cortex

Recent studies have shown that ocular dominance plasticity in layer 2/3 of the visual cortex exhibits a form of homeostatic plasticity that is related to synaptic scaling and depends on TNFα. In this study, we tested whether a similar form of plasticity was present in layer 2/3 of the barrel cortex and, therefore, whether the mechanism was likely to be a general property of cortical neurons. We found that whisker deprivation could induce homeostatic plasticity in layer 2/3 of barrel cortex, but not in a mouse strain lacking synaptic scaling. The time-course of homeostatic plasticity in layer 2/3 was similar to that of L5 regular spiking (RS) neurons (L5RS), but slower than that of L5 intrinsic bursting (IB) neurons (L5IB). In layer 5, the strength of evoked whisker responses and ex vivo miniature excitatory post-synaptic currents (mEPSCs) amplitudes showed an identical time-course for homeostatic plasticity, implying that plasticity at excitatory synapses contacting layer 5 neurons is sufficient to explain the changes in evoked responses. Spontaneous firing rate also showed homeostatic behaviour for L5IB cells, but was absent for L5RS cells over the time-course studied. Spontaneous firing rate homeostasis was found to be independent of evoked response homeostasis suggesting that the two depend on different mechanisms.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

Hebbian Spike-Timing Dependent Plasticity at the Cerebellar Input Stage

Spike-timing-dependent plasticity (STDP) is a form of long-term synaptic plasticity exploiting the time relationship between postsynaptic action potentials (APs) and EPSPs. Surprisingly enough, very little was known about STDP in the cerebellum, although it is thought to play a critical role for learning appropriate timing of actions. We speculated that low-frequency oscillations observed in the granular layer may provide a reference for repetitive EPSP/AP phase coupling. Here we show that EPSP-spike pairing at 6 Hz can optimally induce STDP at the mossy fiber-granule cell synapse in rats. Spike timing-dependent long-term potentiation and depression (st-LTP and st-LTD) were confined to a ±25 ms time-window. Because EPSPs led APs in st-LTP while APs led EPSPs in st-LTD, STDP was Hebbian in nature. STDP occurred at 6-10 Hz but vanished >50 Hz or <1 Hz (where only LTP or LTD occurred). STDP disappeared with randomized EPSP/AP pairing or high intracellular Ca²⁺ buffering, and its sign was inverted by GABA-A receptor activation. Both st-LTP and st-LTD required NMDA receptors, but st-LTP also required reinforcing signals mediated by mGluRs and intracellular calcium stores. Importantly, st-LTP and st-LTD were significantly larger than LTP and LTD obtained by modulating the frequency and duration of mossy fiber bursts, probably because STDP expression involved postsynaptic in addition to presynaptic mechanisms. These results thus show that a Hebbian form of STDP occurs at the cerebellum input stage, providing the substrate for phase-dependent binding of mossy fiber spikes to repetitive theta-frequency cycles of granule cell activity.SIGNIFICANCE STATEMENT Long-term synaptic plasticity is a fundamental property of the brain, causing persistent modifications of neuronal communication thought to provide the cellular basis of learning and memory. The cerebellum is critical for learning the appropriate timing of sensorimotor behaviors, but whether and how appropriate spike patterns could drive long-term synaptic plasticity remained unknown. Here, we show that this can actually occur through a form of spike-timing-dependent plasticity (STDP) at the cerebellar inputs stage. Pairing presynaptic and postsynaptic spikes at 6-10 Hz reliably induced STDP at the mossy fiber-granule cell synapse, with potentiation and depression symmetrically distributed within a ±25 ms time window. Thus, STDP can bind plasticity to the mossy fiber burst phase with high temporal precision.

Reduced Inhibition within Layer IV of Sert Knockout Rat Barrel Cortex is Associated with Faster Sensory Integration

Neural activity is essential for the maturation of sensory systems. In the rodent primary somatosensory cortex (S1), high extracellular serotonin (5-HT) levels during development impair neural transmission between the thalamus and cortical input layer IV (LIV). Rodent models of impaired 5-HT transporter (SERT) function show disruption in their topological organization of S1 and in the expression of activity-regulated genes essential for inhibitory cortical network formation. It remains unclear how such alterations affect the sensory information processing within cortical LIV. Using serotonin transporter knockout (Sert-/-) rats, we demonstrate that high extracellular serotonin levels are associated with impaired feedforward inhibition (FFI), fewer perisomatic inhibitory synapses, a depolarized GABA reversal potential and reduced expression of KCC2 transporters in juvenile animals. At the neural population level, reduced FFI increases the excitatory drive originating from LIV, facilitating evoked representations in the supragranular layers II/III. The behavioral consequence of these changes in network excitability is faster integration of the sensory information during whisker-based tactile navigation, as Sert-/- rats require fewer whisker contacts with tactile targets and perform object localization with faster reaction times. These results highlight the association of serotonergic homeostasis with formation and excitability of sensory cortical networks, and consequently with sensory perception.

Spike Timing-Dependent Plasticity in the Mouse Barrel Cortex Is Strongly Modulated by Sensory Learning and Depends on Activity of Matrix Metalloproteinase 9

Experience and learning in adult primary somatosensory cortex are known to affect neuronal circuits by modifying both excitatory and inhibitory transmission. Synaptic plasticity phenomena provide a key substrate for cognitive processes, but precise description of the cellular and molecular correlates of learning is hampered by multiplicity of these mechanisms in various projections and in different types of neurons. Herein, we investigated the impact of associative learning on neuronal plasticity in distinct types of postsynaptic neurons by checking the impact of classical conditioning (pairing whisker stroking with tail shock) on the spike timing-dependent plasticity (t-LTP and t-LTD) in the layer IV to II/III vertical pathway of the mouse barrel cortex. Learning in this paradigm practically prevented t-LTP measured in pyramidal neurons but had no effect on t-LTD. Since classical conditioning is known to affect inhibition in the barrel cortex, we examined its effect on tonic GABAergic currents and found a strong downregulation of these currents in the layer II/III interneurons but not in pyramidal cells. Matrix metalloproteinases emerged as crucial players in synaptic plasticity and learning. We report that the blockade of MMP-9 (but not MMP-3) abolished t-LTP having no effect on t-LTD. Moreover, associative learning resulted in an upregulation of gelatinolytic activity within the "trained" barrel. We conclude that LTP induced by spike timing-dependent plasticity (STDP) paradigm is strongly correlated with associative learning and critically depends on the activity of MMP-9.

Synaptic Learning Rules, Cortical Circuits, and Visual Function

Sensory experience is essential for the refinement of neuronal circuits during development and for learning and memory in the adult brain. Such experience-dependent plasticity is largely mediated by activity-dependent synaptic modification. In this review, we focus on a spike timing-dependent synaptic learning rule, in which the direction and magnitude of synaptic modification depend on the relative spike timing of presynaptic and postsynaptic neurons. We discuss a series of recent studies exploring the functional implications of this learning rule in the visual system. These studies show that temporally patterned visual stimuli can cause rapid changes in visual circuits, neuronal receptive fields, and visual perception, with a temporal specificity of tens of milliseconds. Particularly, motion stimuli that are common in natural scenes may interact strongly with the spike timing-dependent learning rule, leaving distinct marks in the perceptual function of the mature brain.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

A neuron is a tiny computer that transforms electrical inputs into electrical outputs. While neurons have been investigated and modeled for many decades, some aspects remain elusive. Recently, it was demonstrated that the membrane (voltage) state of a neuron determines its threshold to spiking. In the present study we asked, what are the consequences of this dependence for the computation the neuron performs. We find that this so called adaptive threshold allows neurons to be more focused on inputs which arrive close in time with other inputs. Also, it allows neurons to represent their information more robustly, such that a readout of their activity is less influenced by the state the brain is in. The present use of information theory provides a solid foundation for these results. We obtained the results primarily in detailed simulations, but performed neural recordings to verify these properties in real neurons. In summary, an adaptive spiking threshold allows neurons to specifically compute robustly with a focus on tight temporal correlations in their input.

Whisker Deprivation Drives Two Phases of Inhibitory Synapse Weakening in Layer 4 of Rat Somatosensory Cortex

Inhibitory synapse development in sensory neocortex is experience-dependent, with sustained sensory deprivation yielding fewer and weaker inhibitory synapses. Whether this represents arrest of synapse maturation, or a more complex set of processes, is unclear. To test this, we measured the dynamics of inhibitory synapse development in layer 4 of rat somatosensory cortex (S1) during continuous whisker deprivation from postnatal day 7, and in age-matched controls. In deprived columns, spontaneous miniature inhibitory postsynaptic currents (mIPSCs) and evoked IPSCs developed normally until P15, when IPSC amplitude transiently decreased, recovering by P16 despite ongoing deprivation. IPSCs remained normal until P22, when a second, sustained phase of weakening began. Delaying deprivation onset by 5 days prevented the P15 weakening. Both early and late phase weakening involved measurable reduction in IPSC amplitude relative to prior time points. Thus, deprivation appears to drive two distinct phases of active IPSC weakening, rather than simple arrest of synapse maturation.

Neonatal Restriction of Tactile Inputs Leads to Long-Lasting Impairments of Cross-Modal Processing

Optimal behavior relies on the combination of inputs from multiple senses through complex interactions within neocortical networks. The ontogeny of this multisensory interplay is still unknown. Here, we identify critical factors that control the development of visual-tactile processing by combining in vivo electrophysiology with anatomical/functional assessment of cortico-cortical communication and behavioral investigation of pigmented rats. We demonstrate that the transient reduction of unimodal (tactile) inputs during a short period of neonatal development prior to the first cross-modal experience affects feed-forward subcortico-cortical interactions by attenuating the cross-modal enhancement of evoked responses in the adult primary somatosensory cortex. Moreover, the neonatal manipulation alters cortico-cortical interactions by decreasing the cross-modal synchrony and directionality in line with the sparsification of direct projections between primary somatosensory and visual cortices. At the behavioral level, these functional and structural deficits resulted in lower cross-modal matching abilities. Thus, neonatal unimodal experience during defined developmental stages is necessary for setting up the neuronal networks of multisensory processing.

Reducing unisensory experience during neonatal development causes permanent disruption of connectivity between primary sensory cortices, resulting in impaired multisensory abilities.

Our senses, working together, enable us to interact with the environment. To obtain a unified percept of the world, diverse sensory inputs need to be bound together within distributed but strongly interconnected neuronal networks. Many multisensory abilities emerge or mature late in life, long after the maturation of the individual senses, yet the factors and mechanisms controlling their development are largely unknown. Here, we provide evidence for the critical role of unisensory experience during early postnatal life for the development of multisensory integration. Focusing on visual-tactile interactions in pigmented rats with good visual acuity, we show that a transient reduction of tactile inputs during neonatal development leads to sparser direct connections between adult primary visual and somatosensory cortices. As a result, these animals showed reduced neuronal activation following co-occurring tactile and visual stimuli, as well as impaired communication within visual-somatosensory networks. The structural and functional deficits resulting from an early manipulation of tactile experience had major behavioral consequences, impairing the rats’ ability to transfer information about encountered objects between senses. Thus, unisensory experience during early development shapes the neuronal networks of multisensory processing and the ability to transfer cross-modal information.

A Developmental Switch for Hebbian Plasticity

Hebbian forms of synaptic plasticity are required for the orderly development of sensory circuits in the brain and are powerful modulators of learning and memory in adulthood. During development, emergence of Hebbian plasticity leads to formation of functional circuits. By modeling the dynamics of neurotransmitter release during early postnatal cortical development we show that a developmentally regulated switch in vesicle exocytosis mode triggers associative (i.e. Hebbian) plasticity. Early in development spontaneous vesicle exocytosis (SVE), often considered as 'synaptic noise', is important for homogenization of synaptic weights and maintenance of synaptic weights in the appropriate dynamic range. Our results demonstrate that SVE has a permissive, whereas subsequent evoked vesicle exocytosis (EVE) has an instructive role in the expression of Hebbian plasticity. A timed onset for Hebbian plasticity can be achieved by switching from SVE to EVE and the balance between SVE and EVE can control the effective rate of Hebbian plasticity. We further show that this developmental switch in neurotransmitter release mode enables maturation of spike-timing dependent plasticity. A mis-timed or inadequate SVE to EVE switch may lead to malformation of brain networks thereby contributing to the etiology of neurodevelopmental disorders.

Neurotransmitter release is the principal form of chemical communication in the brain. When an action potential reaches a synapse, calcium influx activates the machinery for neurotransmitter release. During early neuronal development this machinery matures such that neurotransmitter release becomes time-locked to action potentials. By modeling this change in neurotransmitter release, we mechanistically show that the maturation process can be solely responsible for switching on associative (i.e. Hebbian) plasticity in the brain. The relevant proteins of the release machinery can thereby regulate the rate at which neural circuits represent sensory input, providing a novel mechanism to control the learning rate and onset. Appropriately timing of the onset of Hebbian plasticity is important because during early development sensory experience fine-tunes, often irreversibly, the neural wiring in our brain.