Information processing with frequency-dependent synaptic connections

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

We show that a diffusive memristor with analogue switching characteristics can be achieved in a layer of gold nanoparticles (AuNPs) functionalized with charged self-assembled monolayers (deprotonated 11-mercaptoundecanoic acid). The nanoparticle core and the anchored stationary charges are jammed within the layer while the mobile counterions [N(CH3)4+] can respond to the electric field and spontaneously diffuse back to the initial positions upon removal of the field. This metal nanoparticle device is set-step free, energy consumption efficient, mechanically flexible, and analogous to bio-Ca2+ dynamics and has tunable conductance modulation capabilities at the counterion concentrations. The gradual resistive switching behavior enables us to implement several important synaptic functions such as potentiation/depression, spike voltage-dependent plasticity, spike duration-dependent plasticity, spike frequency-dependent plasticity, and paired-pulse facilitation. Finally, on the basis of the paired-pulse facilitation characteristics, the metal nanoparticle diffusive artificial synapse is used for edge extraction with exhibits excellent performance.

In-Sensor Computing Realization Using Fully CMOS-Compatible TiN/HfOx-Based Neuristor Array

With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneous integration methods such as chiplet technology can significantly reduce unnecessary data movement; however, they fail to address the fundamental issue of the substantial time and energy overheads resulting from the physical separation of computing and sensory components. Brain-inspired in-sensor neuromorphic computing (ISNC) has plenty of room for such data-intensive applications. However, one key obstacle in developing ISNC systems is the lack of compatibility between material systems and manufacturing processes deployed in sensors and computing units. This study successfully addresses this challenge by implementing fully CMOS-compatible TiN/HfOx-based neuristor array. The developed ISNC system demonstrates several advantageous features, including multilevel analogue modulation, minimal dispersion, and no significant degradation in conductance (@125 °C). These characteristics enable stable and reproducible neuromorphic computing. Additionally, the device exhibits modulatable sensory and multi-store memory processes. Furthermore, the system achieves information recognition with a high accuracy rate of 93%, along with frequency selectivity and notable activity-dependent plasticity. This work provides a promising route to affordable and highly efficient sensory neuromorphic systems.

Mimicking biological synapses with a-HfSiOx-based memristor: implications for artificial intelligence and memory applications

Memristors, owing to their uncomplicated structure and resemblance to biological synapses, are predicted to see increased usage in the domain of artificial intelligence. Additionally, to augment the capacity for multilayer data storage in high-density memory applications, meticulous regulation of quantized conduction with an extremely low transition energy is required. In this work, an a-HfSiO_x-based memristor was grown through atomic layer deposition (ALD) and investigated for its electrical and biological properties for use in multilevel switching memory and neuromorphic computing systems. The crystal structure and chemical distribution of the HfSiOx/TaN layers were analyzed using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), respectively. The Pt/a-HfSiO_x/TaN memristor was confirmed by transmission electron microscopy (TEM) and showed analog bipolar switching behavior with high endurance stability (1000 cycles), long data retention performance (10⁴ s), and uniform voltage distribution. Its multilevel capability was demonstrated by restricting current compliance (CC) and stopping the reset voltage. The memristor exhibited synaptic properties, such as short-term plasticity, excitatory postsynaptic current (EPSC), spiking-rate-dependent plasticity (SRDP), post-tetanic potentiation (PTP), and paired-pulse facilitation (PPF). Furthermore, it demonstrated 94.6% pattern accuracy in neural network simulations. Thus, a-HfSiO_x-based memristors have great potential for use in multilevel memory and neuromorphic computing systems.

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.

Route to synchronization in coupled phase oscillators with frequency-dependent coupling: Explosive or continuous?

Interconnected dynamical systems often transition between states of incoherence and synchronization due to changes in system parameters. These transitions could be continuous (gradual) or explosive (sudden) and may result in failures, which makes determining their nature important. In this study, we abstract dynamical networks as an ensemble of globally coupled Kuramoto-like phase oscillators with frequency-dependent coupling and investigate the mechanisms for transition between incoherent and synchronized dynamics. The characteristics that dictate a continuous or explosive route to synchronization are the distribution of the natural frequencies of the oscillators, quantified by a probability density function g(ω), and the relation between the coupling strength and natural frequency of an oscillator, defined by a frequency-coupling strength correlation function f(ω). Our main results are conditions on f(ω) and g(ω) that result in continuous or explosive routes to synchronization and explain the underlying physics. The analytical developments are validated through numerical examples.

Water-Soluble Polythiophene-Conjugated Polyelectrolyte-Based Memristors for Transient Electronics

The key to protect sensitive information stored in electronic memory devices from disclosure is to develop transient electronic devices that are capable of being destroyed quickly in an emergency. By using a highly water-soluble polythiophene-conjugated polyelectrolyte PTT-NMI⁺Br^- as an active material, which was synthesized by the reaction of poly[thiophene-alt-4,4-bis(6-bromohexyl)-4H-cyclopenta(1,2-b:5,4-b')dithiophene] with N-methylimidazole, a flexible electronic device, Al/PTT-NMI⁺Br^-/ITO-coated PET (ITO: indium tin oxide; PET: polyethylene terephthalate), is successfully fabricated. This device shows a typical nonvolatile rewritable resistive random access memory (RRAM) effect at a sweep voltage range of ±3 V and a history-dependent memristive switching performance at a small sweep voltage range of ±1 V. Both the learning/memorizing functions and the synaptic potentiation/depression of biological systems have been emulated. The switching mechanism for the PTT-NMI⁺Br^--based electronic device may be highly associated with ion migration under bias. Once water is added to this device, it will be destructed rapidly within 20 s due to the dissolution of the active layer. This device is not only a typical transient device but can also be used for constructing conventional memristors with long-term stability after electronic packaging. Furthermore, the soluble active layer in the device can be easily recycled from its aqueous solution and reused for fabricating new transient memristors. This work offers a train of new thoughts for designing and constructing a neuromorphic computing system that can be quickly destroyed with water in the near future.

Artificial Neural Pathway Based on a Memristor Synapse for Optically Mediated Motion Learning

Animals execute intelligent and efficient interactions with their surroundings through neural pathways, exhibiting learning, memory, and cognition. Artificial autonomous devices that generate self-optimizing feedback mimicking biological systems are essential in pursuing future intelligent robots. Here, we report an artificial neural pathway (ANP) based on a memristor synapse to emulate neuromorphic learning behaviors. In our ANP, optical stimulations are detected and converted into electrical signals through a flexible perovskite photoreceptor. The acquired electrical signals are further processed in a zeolitic imidazolate frameworks-8 (ZIF-8)-based memristor device. By controlling the growth of the ZIF-8 nanoparticles, the conductance of the memristor can be finely modulated with electrical stimulations to mimic the modulation of synaptic plasticity. The device is employed in the ANP to implement synaptic functions of learning and memory. Subsequently, the synaptic feedbacks are used to direct a robotic arm to perform responding motions. Upon repeatedly "reviewing" the optical stimulation, the ANP is able to learn, memorize, and complete the specific motions. This work provides a promising strategy toward the design of intelligent autonomous devices and bioinspired robots through memristor-based systems.

Methamphetamine augments HIV-1 gp120 inhibition of synaptic transmission and plasticity in rat hippocampal slices: Implications for methamphetamine exacerbation of HIV-associated neurocognitive disorders

Methamphetamine (Meth) abuse and human immunodeficiency virus type 1 (HIV-1) infection are two major public health problems worldwide. Being frequently comorbid with HIV-1 infection, Meth abuse exacerbates neurocognitive impairment in HIV-1-infected individuals even in the era of combined antiretroviral therapy. While a large body of research have studied the individual effects of Meth and HIV-1 envelope glycoprotein 120 (gp120) in the brain, far less has focused on their synergistic influence. Moreover, it is well-documented that the hippocampus is the primary site of spatial learning and long-term memory formation. Dysregulation of activity-dependent synaptic transmission and plasticity in the hippocampus is believed to impair neurocognitive function. To uncover the underlying mechanisms for increased incidence and severity of HIV-1-associated neurocognitive disorders (HAND) in HIV-1-infected patients with Meth abuse, we investigated acute individual and combined effects of Meth (20 μM) and gp120 (200 pM) on synaptic transmission and plasticity in the CA1 region of young adult male rat hippocampus, a brain region known to be vulnerable to HIV-1 infection. Our results showed that acute localized application of Meth and gp120 each alone onto the CA1 region reduced short-term dynamics of input-output responses and frequency facilitation, and attenuated long-term potentiation (LTP) induced by either high frequency stimulation or theta burst stimulation. A synergistic augmentation on activity-dependent synaptic plasticity was observed when Meth and gp120 were applied in combination. Paired-pulse facilitation results exhibited an altered facilitation ratio, suggesting a presynaptic site of action. Further studies revealed an involvement of microglia NLRP3 inflammasome activation in Meth augmentation of gp120-mediated attenuation of LTP. Taken together, our results demonstrated Meth augmented gp120 attenuation of LTP in the hippocampus. Since LTP is the accepted experimental analog of learning at the synaptic level, such augmentation may underlie Meth exacerbation of HAND observed clinically.

Donor-acceptor-type poly[chalcogenoviologen-alt-triphenylamine] for synaptic biomimicking and neuromorphic computing

Polymer memristors are preeminent candidates for low-power edge computing paradigms. Poly[chalcogenoviologen-alt-triphenylamine] (PCVTPA) has been synthesized by direct coupling of chalcogeno-viologen as electron acceptor and 4-(bromomethyl)-N-(4-(bromo-methyl)phenyl)-N-phenylaniline as electron donor. The introduction of chalcogen atoms (S, Se, Te) into viologen scaffolds can greatly improve electrical conductive, electrochemical, and electrochromic properties of the materials when compared with the conventional viologens. Taking PTeVTPA as an example, the as-fabricated electronic device with a configuration of Al/PTeVTPA/ITO exhibits excellent multilevel storage and history-dependent memristive switching performance. Associated with the unique memristive behavior, the PTeVTPA-based device can not only be used to emulate the synaptic potentiation/depression, the human's learning and memorizing functions, and the transition from short-term synaptic plasticity to long-term plasticity but also carry out decimal arithmetic operations as well. This work will be expected to offer a train of new thought for constructing high-performance synaptic biomimicking and neuromorphic computing system in the near future.

The Functional Organization of Cortical and Thalamic Inputs onto Five Types of Striatal Neurons Is Determined by Source and Target Cell Identities

To understand striatal function, it is essential to know the functional organization of the numerous inputs targeting the diverse population of striatal neurons. Using optogenetics, we activated terminals from ipsi- or contralateral primary somatosensory cortex (S1) or primary motor cortex (M1), or thalamus while obtaining simultaneous whole-cell recordings from pairs or triplets of striatal medium spiny neurons (MSNs) and adjacent interneurons. Ipsilateral corticostriatal projections provided stronger excitation to fast-spiking interneurons (FSIs) than to MSNs and only sparse and weak excitation to low threshold-spiking interneurons (LTSIs) and cholinergic interneurons (ChINs). Projections from contralateral M1 evoked the strongest responses in LTSIs but none in ChINs, whereas thalamus provided the strongest excitation to ChINs but none to LTSIs. In addition, inputs varied in their glutamate receptor composition and their short-term plasticity. Our data revealed a highly selective organization of excitatory striatal afferents, which is determined by both pre- and postsynaptic neuronal identity.

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Whole-cell recordings are obtained from neighboring striatal neurons of different types

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FSIs receive the strongest inputs from S1, M1, and thalamic PF

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LTSIs are primarily excited by contralateral M1

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ChINs are primarily excited by PF and receive no input from contralateral M1 and S1

Synaptic inhibition in the neocortex: Orchestration and computation through canonical circuits and variations on the theme

The neocortex plays a crucial role in all basic and abstract cognitive functions. Conscious mental processes are achieved through a correct flow of information within and across neocortical networks, whose particular activity state results from a tight balance between excitation and inhibition. The proper equilibrium between these indissoluble forces is operated with multiscale organization: along the dendro-somatic axis of single neurons and at the network level. Fast synaptic inhibition is assured by a multitude of inhibitory interneurons. During cortical activities, these cells operate a finely tuned division of labor that is epitomized by their detailed connectivity scheme. Recent results combining the use of mouse genetics, cutting-edge optical and neurophysiological approaches have highlighted the role of fast synaptic inhibition in driving cognition-related activity through a canonical cortical circuit, involving several major interneuron subtypes and principal neurons. Here we detail the organization of this cortical blueprint and we highlight the crucial role played by different neuron types in fundamental cortical computations. In addition, we argue that this canonical circuit is prone to many variations on the theme, depending on the resolution of the classification of neuronal types, and the cortical area investigated. Finally, we discuss how specific alterations of distinct inhibitory circuits can underlie several devastating brain diseases.

A dual mode electronic synapse based on layered SnSe films fabricated by pulsed laser deposition

An artificial synapse, such as a memristive electronic synapse, has caught world-wide attention due to its potential in neuromorphic computing, which may tremendously reduce computer volume and energy consumption. The introduction of layered two-dimensional materials has been reported to enhance the performance of the memristive electronic synapse. However, it is still a challenge to fabricate large-area layered two-dimensional films by scalable methods, which has greatly limited the industrial application potential of two-dimensional materials. In this work, a scalable pulsed laser deposition (PLD) method has been utilized to fabricate large-area layered SnSe films, which are used as the functional layers of the memristive electronic synapse with dual modes. Both long-term memristive behaviour with gradually changed resistance (Mode 1) and short-term memristive behavior with abruptly reduced resistance (Mode 2) have been achieved in this SnSe-based memristive electronic synapse. The switching between Mode 1 and Mode 2 can be realized by a series of voltage sweeping and programmed pulses. The formation and recovery of Sn vacancies were believed to induce the short-term memristive behaviour, and the joint action of Ag filament formation/rupture and Schottky barrier modulation can be the origin of long-term memristive behaviour. DFT calculations were performed to further illustrate how Ag atoms and Sn vacancies diffuse through the SnSe layer and form filaments. The successful emulation of synaptic functions by the layered chalcogenide memristor fabricated by the PLD method suggests the application potential in future neuromorphic computers.

Self-Doping Memristors with Equivalently Synaptic Ion Dynamics for Neuromorphic Computing

The accumulation and extrusion of Ca²⁺ ions in the pre- and post-synaptic terminals play crucial roles in initiating short- and long-term plasticity (STP and LTP) in biological synapses, respectively. Mimicking these synaptic behaviors by electronic devices represents a vital step toward realization of neuromorphic computing. However, the majority of reported synaptic devices usually focus on the emulation of qualitatively synaptic behaviors; devices that can truly emulate the physical behavior of the synaptic Ca²⁺ ion dynamics in STP and LTP are rarely reported. In this work, Ag/Ag:Ta₂O₅/Pt self-doping memristors were developed to equivalently emulate the Ca²⁺ ion dynamics of biological synapses. With conductive filaments from double sources, these memristors produced unique double-switching behavior under voltage sweeps and demonstrated several essential synaptic behaviors under pulse stimuli, including STP, LTP, STP to LTP transition, and spike-rate-dependent plasticity. Experimental results and nanoparticle dynamic simulations both showed that Ag atoms from double sources could mimic Ca²⁺ dynamics in the pre- and post-synaptic terminals under stimuli. A perceptron network with an STP to LTP transition layer based on the self-doping memristors was also introduced and evaluated; simulations showed that this network could solve noisy figure recognition tasks efficiently. All of these results indicate that the self-doping memristors are promising components for future hardware creation of neuromorphic systems and emulate the characteristics of the brain.

The Synaptomic Theory of Behavior and Brain Disease

The purpose of this article is to outline a new molecular and synaptic theory of behavior called the "synaptomic theory," named because it is centered on the synaptome-the complement of synapses in the brain. Synaptomic theory posits that synapses are structures of high molecular complexity and vast diversity that are observable in maps of the brain and that these synaptome maps are fundamental to behavior. Synaptome maps are a means of writing or storing information that can be retrieved by the patterns of activity that stimulate synapses. Synaptome maps have the capacity to store large amounts of information, including multiple representations within the same map. The dynamic properties of synapses allow synaptome maps to store dynamic sequences of representations that could serve to program behavioral sequences. Synaptome maps are genetically programmed and experience-dependent, thereby storing innate and learned behaviors, respectively. Although learning occurs by modification of the synapse proteome, it does not require long-term potentiation (LTP) of synaptic weight or growth of new synapses, and the theory predicts that LTP modulates information recall. The spatial architecture of synaptome maps arise from an underlying molecular hierarchy linking the genome to the supramolecular assembly of proteins into complexes and supercomplexes. This molecular hierarchy can explain how genome evolution results in the behavioral repertoire of the organism. Mutations disrupting this molecular hierarchy change the architecture of synaptome maps, potentially accounting for the behavioral phenotypes associated with neurological and psychiatric disorders.

Long-Term Activity Dynamics of Single Neurons and Networks

The firing rate of neuronal spiking in vitro and in vivo significantly varies over extended timescales, characterized by long-memory processes and complex statistics, and appears in spontaneous as well as evoked activity upon repeated stimulus presentation. These variations in response features and their statistics, in face of repeated instances of a given physical input, are ubiquitous in all levels of brain-behavior organization. They are expressed in single neuron and network response variability but even appear in variations of subjective percepts or psychophysical choices and have been described as stemming from history-dependent, stochastic, or rate-determined processes.But what are the sources underlying these temporally rich variations in firing rate? Are they determined by interactions of the nervous system as a whole, or do isolated, single neurons or neuronal networks already express these fluctuations independent of higher levels? These questions motivated the application of a method that allows for controlled and specific long-term activation of a single neuron or neuronal network, isolated from higher levels of cortical organization.This chapter highlights the research done in cultured cortical networks to study (1) the inherent non-stationarity of neuronal network activity, (2) single neuron response fluctuations and underlying processes, and (3) the interface layer between network and single cell, the non-stationary efficacy of the ensemble of synapses impinging onto the observed neuron.

Target-cell-specific Short-term Plasticity Reduces the Excitatory Drive onto CA1 Interneurons Relative to Pyramidal Cells During Physiologically-derived Spike Trains

Short-term plasticity enables synaptic strength to be dynamically regulated by input timing. Excitatory synapses arising from the same axon can have profoundly different presynaptic forms of short-term plasticity onto inhibitory and excitatory neurons. We previously showed that Schaffer collateral synapses onto most hippocampal CA1 stratum radiatum interneurons have less paired-pulse facilitation than synapses onto CA1 pyramidal cells, but little difference in steady-state short-term depression. However, less is known about how synapses onto interneurons respond to temporally complex patterns that occur in vivo. Here we compared Schaffer collateral synapses onto stratum radiatum interneurons and pyramidal cells in acute hippocampal slices in response to physiologically-derived spike trains. We find that synapses onto interneurons have less short-term facilitation than synapses onto pyramidal cells, and a subset expresses only short-term depression. Mathematical modeling predicts this target cell-specific short-term plasticity occurs through differences in initial release probability. All three groups have more short-term facilitation during physiologically-derived train stimulation than during constant-frequency stimulation at the same frequency, indicating that variability in stimulus timing is important. These target-cell specific differences in short-term plasticity reduce the strength of excitatory input onto interneurons relative to pyramidal cells, and of depression interneurons relative to facilitation interneurons, during high frequency portions of the train. This occurs to a similar extent at 25 °C and at 33 °C, and is even greater at physiological extracellular calcium. Target-cell specific differences in short-term plasticity enable synapses to have different temporal filtering characteristics, which may help to dynamically regulate the balance of inhibition and excitation in CA1.

A gradient of frequency-dependent synaptic properties along the longitudinal hippocampal axis

Background

The hippocampus is a functionally heterogeneous brain structure and specializations of the intrinsic neuronal network may crucially support the functional segregation along the longitudinal axis of the hippocampus. Short-term synaptic plasticity plays fundamental roles in information processing and may be importantly involved in diversifying the properties of local neuronal network along the hippocampus long axis. Therefore, we aimed to examine the properties of the cornu ammonis 1 (CA1) synapses along the entire dorsoventral axis of the rat hippocampus using field excitatory postsynaptic potentials from transverse rat hippocampal slices and a frequency stimulation paradigm.

Results

Applying a ten-pulse stimulus train at frequencies from 0.1 to 100 Hz to the Schaffer collaterals we found a gradually diversified pattern of frequency-dependent synaptic effects along the dorsoventral hippocampus axis. The first conditioned response was facilitated along the whole hippocampus for stimulus frequencies 10–40 Hz. However, steady-state responses or averaged responses generally ranged from maximum synaptic facilitation in the most dorsal segment of the hippocampus to maximum synaptic depression in the most ventral segment of the hippocampus. In particular, dorsal synapses facilitated for stimulus frequency up to 50 Hz while they depressed at higher frequencies (75–100 Hz). Facilitation at dorsal synapses was maximal at stimulus frequency of 20 Hz. On the contrary, the most ventral synapses showed depression regardless of the stimulus frequency, only displaying a transient facilitation at the beginning of 10–50 Hz stimulation. Importantly, the synapses in the medial hippocampus displayed a transitory behavior. Finally, as a whole the hippocampal synapses maximally facilitated at 20 Hz and increasingly depressed at 50–100 Hz.

Conclusion

The short-term synaptic dynamics change gradually along the hippocampal long axis in a frequency-dependent fashion conveying distinct properties of information processing to successive segments of the structure, thereby crucially supporting functional segregation along the dorsoventral axis of the hippocampus.

Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials

Emulation of biological synapses that perform memory and learning functions is an essential step toward realization of bioinspired neuromorphic systems. Artificial synaptic devices have been developed based mostly on inorganic materials and conventional semiconductor device fabrication processes. Here, we propose flexible biomemristor devices based on lignin by a simple solution process. Lignin is one of the most abundant organic polymers on Earth and is biocompatible, biodegradable, as well as environmentally benign. This memristor emulates several essential synaptic behaviors, including analog memory switching, short-term plasticity, long-term plasticity, spike-rate-dependent plasticity, and short-term to long-term transition. A flexible lignin-based artificial synapse device can be operated without noticeable degradation under mechanical bending test. These results suggest lignin can be a promising key component for artificial synapses and flexible electronic devices.

Evidence for frequency-dependent cortical plasticity in the human brain

Frequency-dependent plasticity (FDP) describes adaptation at the synapse in response to stimulation at different frequencies. Its consequence on the structure and function of cortical networks is unknown. We tested whether cortical "resonance," favorable stimulation frequencies at which the sensory cortices respond maximally, influenced the impact of FDP on perception, functional topography, and connectivity of the primary somatosensory cortex using psychophysics and functional imaging (fMRI). We costimulated two digits on the hand synchronously at, above, or below the resonance frequency of the somatosensory cortex, and tested subjects' accuracy and speed on tactile localization before and after costimulation. More errors and slower response times followed costimulation at above- or below-resonance, respectively. Response times were faster after at-resonance costimulation. In the fMRI, the cortical representations of the two digits costimulated above-resonance shifted closer, potentially accounting for the poorer performance. Costimulation at-resonance did not shift the digit regions, but increased the functional coupling between them, potentially accounting for the improved response time. To relate these results to synaptic plasticity, we simulated a network of oscillators incorporating Hebbian learning. Two neighboring patches embedded in a cortical sheet, mimicking the two digit regions, were costimulated at different frequencies. Network activation outside the stimulated patches was greatest at above-resonance frequencies, reproducing the spread of digit representations seen with fMRI. Connection strengths within the patches increased following at-resonance costimulation, reproducing the increased fMRI connectivity. We show that FDP extends to the cortical level and is influenced by cortical resonance.

Degeneracy in the regulation of short-term plasticity and synaptic filtering by presynaptic mechanisms

KEY POINTS

We develop a new biophysically rooted, physiologically constrained conductance-based synaptic model to mechanistically account for short-term facilitation and depression, respectively through residual calcium and transmitter depletion kinetics. We address the specific question of how presynaptic components (including voltage-gated ion channels, pumps, buffers and release-handling mechanisms) and interactions among them define synaptic filtering and short-term plasticity profiles. Employing global sensitivity analyses (GSAs), we show that near-identical synaptic filters and short-term plasticity profiles could emerge from disparate presynaptic parametric combinations with weak pairwise correlations. Using virtual knockout models, a technique to address the question of channel-specific contributions within the GSA framework, we unveil the differential and variable impact of each ion channel on synaptic physiology. Our conclusions strengthen the argument that parametric and interactional complexity in biological systems should not be viewed from the limited curse-of-dimensionality standpoint, but from the evolutionarily advantageous perspective of providing functional robustness through degeneracy.

ABSTRACT

Information processing in neurons is known to emerge as a gestalt of pre- and post-synaptic filtering. However, the impact of presynaptic mechanisms on synaptic filters has not been quantitatively assessed. Here, we developed a biophysically rooted, conductance-based model synapse that was endowed with six different voltage-gated ion channels, calcium pumps, calcium buffer and neurotransmitter-replenishment mechanisms in the presynaptic terminal. We tuned our model to match the short-term plasticity profile and band-pass structure of Schaffer collateral synapses, and performed sensitivity analyses to demonstrate that presynaptic voltage-gated ion channels regulated synaptic filters through changes in excitability and associated calcium influx. These sensitivity analyses also revealed that calcium- and release-control mechanisms were effective regulators of synaptic filters, but accomplished this without changes in terminal excitability or calcium influx. Next, to perform global sensitivity analysis, we generated 7000 randomized models spanning 15 presynaptic parameters, and computed eight different physiological measurements in each of these models. We validated these models by applying experimentally obtained bounds on their measurements, and found 104 (∼1.5%) models to match the validation criteria for all eight measurements. Analysing these valid models, we demonstrate that analogous synaptic filters emerge from disparate combinations of presynaptic parameters exhibiting weak pairwise correlations. Finally, using virtual knockout models, we establish the variable and differential impact of different presynaptic channels on synaptic filters, underlining the critical importance of interactions among different presynaptic components in defining synaptic physiology. Our results have significant implications for protein-localization strategies required for physiological robustness and for degeneracy in long-term synaptic plasticity profiles.

Target Cell Type-Dependent Differences in Ca2+ Channel Function Underlie Distinct Release Probabilities at Hippocampal Glutamatergic Terminals

Target cell type-dependent differences in presynaptic release probability (P_r ) and short-term plasticity are intriguing features of cortical microcircuits that increase the computational power of neuronal networks. Here, we tested the hypothesis that different voltage-gated Ca²⁺ channel densities in presynaptic active zones (AZs) underlie different P_r values. Two-photon Ca²⁺ imaging, triple immunofluorescent labeling, and 3D electron microscopic (EM) reconstruction of rat CA3 pyramidal cell axon terminals revealed ∼1.7-1.9 times higher Ca²⁺ inflow per AZ area in high P_r boutons synapsing onto parvalbumin-positive interneurons (INs) than in low P_r boutons synapsing onto mGluR1α-positive INs. EM replica immunogold labeling, however, demonstrated only 1.15 times larger Cav2.1 and Cav2.2 subunit densities in high P_r AZs. Our results indicate target cell type-specific modulation of voltage-gated Ca²⁺ channel function or different subunit composition as possible mechanisms underlying the functional differences. In addition, high P_r synapses are also characterized by a higher density of docked vesicles, suggesting that a concerted action of these mechanisms underlies the functional differences.SIGNIFICANCE STATEMENT Target cell type-dependent variability in presynaptic properties is an intriguing feature of cortical synapses. When a single cortical pyramidal cell establishes a synapse onto a somatostatin-expressing interneuron (IN), the synapse releases glutamate with low probability, whereas the next bouton of the same axon has high release probability when its postsynaptic target is a parvalbumin-expressing IN. Here, we used combined molecular, imaging, and anatomical approaches to investigate the mechanisms underlying these differences. Our functional experiments implied an approximately twofold larger Ca²⁺ channel density in high release probability boutons, whereas freeze-fracture immunolocalization demonstrated only a 15% difference in Ca²⁺ channel subunit densities. Our results point toward a postsynaptic target cell type-dependent regulation of Ca²⁺ channel function or different subunit composition as the underlying mechanism.

Untangling Basal Ganglia Network Dynamics and Function: Role of Dopamine Depletion and Inhibition Investigated in a Spiking Network Model

The basal ganglia are a crucial brain system for behavioral selection, and their function is disturbed in Parkinson's disease (PD), where neurons exhibit inappropriate synchronization and oscillations. We present a spiking neural model of basal ganglia including plausible details on synaptic dynamics, connectivity patterns, neuron behavior, and dopamine effects. Recordings of neuronal activity in the subthalamic nucleus and Type A (TA; arkypallidal) and Type I (TI; prototypical) neurons in globus pallidus externa were used to validate the model. Simulation experiments predict that both local inhibition in striatum and the existence of an indirect pathway are important for basal ganglia to function properly over a large range of cortical drives. The dopamine depletion-induced increase of AMPA efficacy in corticostriatal synapses to medium spiny neurons (MSNs) with dopamine receptor D2 synapses (CTX-MSN D2) and the reduction of MSN lateral connectivity (MSN-MSN) were found to contribute significantly to the enhanced synchrony and oscillations seen in PD. Additionally, reversing the dopamine depletion-induced changes to CTX-MSN D1, CTX-MSN D2, TA-MSN, and MSN-MSN couplings could improve or restore basal ganglia action selection ability. In summary, we found multiple changes of parameters for synaptic efficacy and neural excitability that could improve action selection ability and at the same time reduce oscillations. Identification of such targets could potentially generate ideas for treatments of PD and increase our understanding of the relation between network dynamics and network function.

Parvalbumin- and vasoactive intestinal polypeptide-expressing neocortical interneurons impose differential inhibition on Martinotti cells

Disinhibition of cortical excitatory cell gate information flow through and between cortical columns. The major contribution of Martinotti cells (MC) is providing dendritic inhibition to excitatory neurons and therefore they are a main component of disinhibitory connections. Here we show by means of optogenetics that MC in layers II/III of the mouse primary somatosensory cortex are inhibited by both parvalbumin (PV)- and vasoactive intestinal polypeptide (VIP)-expressing cells. Paired recordings revealed stronger synaptic input onto MC from PV cells than from VIP cells. Moreover, PV cell input showed frequency-independent depression, whereas VIP cell input facilitated at high frequencies. These differences in the properties of the two unitary connections enable disinhibition with distinct temporal features.

Martinotti cells disinhibit excitatory cells in the brain cortex and play an important role in information flow. Here the authors study the role of parvalbumin and vasoactive intestinal polypeptide interneurons on the inhibition of Martinotti cells in the mouse somatosensory cortex.

Memory Stacking in Hierarchical Networks

Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

An organic terpyridyl-iron polymer based memristor for synaptic plasticity and learning behavior simulation

Conductance of the viologen/terpyridyl-iron polymer bilayer structure has been effectively modulated by an electrochemical redox reaction for synaptic emulation.

Inhibitory Gating of Input Comparison in the CA1 Microcircuit

Spatial and temporal features of synaptic inputs engage integration mechanisms on multiple scales, including presynaptic release sites, postsynaptic dendrites, and networks of inhibitory interneurons. Here we investigate how these mechanisms cooperate to filter synaptic input in hippocampal area CA1. Dendritic recordings from CA1 pyramidal neurons reveal that proximal inputs from CA3 as well as distal inputs from entorhinal cortex layer III (ECIII) sum sublinearly or linearly at low firing rates due to feedforward inhibition, but sum supralinearly at high firing rates due to synaptic facilitation, producing a high-pass filter. However, during ECIII and CA3 input comparison, supralinear dendritic integration is dynamically balanced by feedforward and feedback inhibition, resulting in suppression of dendritic complex spiking. We find that a particular subpopulation of CA1 interneurons expressing neuropeptide Y (NPY) contributes prominently to this dynamic filter by integrating both ECIII and CA3 input pathways and potently inhibiting CA1 pyramidal neuron dendrites.

Memristive and neuromorphic behavior in a Li(x)CoO2 nanobattery

The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of Li(x)CoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.

High bandwidth synaptic communication and frequency tracking in human neocortex

Neuronal firing, synaptic transmission, and its plasticity form the building blocks for processing and storage of information in the brain. It is unknown whether adult human synapses are more efficient in transferring information between neurons than rodent synapses. To test this, we recorded from connected pairs of pyramidal neurons in acute brain slices of adult human and mouse temporal cortex and probed the dynamical properties of use-dependent plasticity. We found that human synaptic connections were purely depressing and that they recovered three to four times more swiftly from depression than synapses in rodent neocortex. Thereby, during realistic spike trains, the temporal resolution of synaptic information exchange in human synapses substantially surpasses that in mice. Using information theory, we calculate that information transfer between human pyramidal neurons exceeds that of mouse pyramidal neurons by four to nine times, well into the beta and gamma frequency range. In addition, we found that human principal cells tracked fine temporal features, conveyed in received synaptic inputs, at a wider bandwidth than for rodents. Action potential firing probability was reliably phase-locked to input transients up to 1,000 cycles/s because of a steep onset of action potentials in human pyramidal neurons during spike trains, unlike in rodent neurons. Our data show that, in contrast to the widely held views of limited information transfer in rodent depressing synapses, fast recovering synapses of human neurons can actually transfer substantial amounts of information during spike trains. In addition, human pyramidal neurons are equipped to encode high synaptic information content. Thus, adult human cortical microcircuits relay information at a wider bandwidth than rodent microcircuits.

Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms

Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation. Neuromorphic devices offer a number of advantages over conventional computing architectures, such as high emulation speed or low power consumption, but this usually comes at the price of reduced configurability and precision. In this article, we investigate the consequences of several such factors that are common to neuromorphic devices, more specifically limited hardware resources, limited parameter configurability and parameter variations due to fixed-pattern noise and trial-to-trial variability. Our final aim is to provide an array of methods for coping with such inevitable distortion mechanisms. As a platform for testing our proposed strategies, we use an executable system specification (ESS) of the BrainScaleS neuromorphic system, which has been designed as a universal emulation back-end for neuroscientific modeling. We address the most essential limitations of this device in detail and study their effects on three prototypical benchmark network models within a well-defined, systematic workflow. For each network model, we start by defining quantifiable functionality measures by which we then assess the effects of typical hardware-specific distortion mechanisms, both in idealized software simulations and on the ESS. For those effects that cause unacceptable deviations from the original network dynamics, we suggest generic compensation mechanisms and demonstrate their effectiveness. Both the suggested workflow and the investigated compensation mechanisms are largely back-end independent and do not require additional hardware configurability beyond the one required to emulate the benchmark networks in the first place. We hereby provide a generic methodological environment for configurable neuromorphic devices that are targeted at emulating large-scale, functional neural networks.

Synaptic dynamics contribute to long-term single neuron response fluctuations

Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses–activated in response to a given stimulus–on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.

Memory decay and loss of criticality in quorum percolation

In this paper, we present the effects of memory decay on a bootstrap percolation model applied to random directed graphs (quorum percolation). The addition of decay was motivated by its natural occurrence in physical systems previously described by percolation theory, such as cultured neuronal networks, where decay originates from ionic leakage through the membrane of neurons and/or synaptic depression. Surprisingly, this feature alone appears to change the critical behavior of the percolation transition, where discontinuities are replaced by steep but finite slopes. Using different numerical approaches, we show evidence for this qualitative change even for very small decay values. In experiments where the steepest slopes can not be resolved and still appear as discontinuities, decay produces nonetheless a quantitative difference on the location of the apparent critical point. We discuss how this shift impacts network connectivity previously estimated without considering decay. In addition to this particular example, we believe that other percolation models are worth reinvestigating, taking into account similar sorts of memory decay.

Cholinergic modulation of hippocampal network function

Cholinergic septohippocampal projections from the medial septal area to the hippocampus are proposed to have important roles in cognition by modulating properties of the hippocampal network. However, the precise spatial and temporal profile of acetylcholine release in the hippocampus remains unclear making it difficult to define specific roles for cholinergic transmission in hippocampal dependent behaviors. This is partly due to a lack of tools enabling specific intervention in, and recording of, cholinergic transmission. Here, we review the organization of septohippocampal cholinergic projections and hippocampal acetylcholine receptors as well as the role of cholinergic transmission in modulating cellular excitability, synaptic plasticity, and rhythmic network oscillations. We point to a number of open questions that remain unanswered and discuss the potential for recently developed techniques to provide a radical reappraisal of the function of cholinergic inputs to the hippocampus.

Optical modulation of neurotransmission using calcium photocurrents through the ion channel LiGluR

A wide range of light-activated molecules (photoswitches and phototriggers) have been used to the study of computational properties of an isolated neuron by acting pre and postsynaptically. However, new tools are being pursued to elicit a presynaptic calcium influx that triggers the release of neurotransmitters, most of them based in calcium-permeable Channelrhodopsin-2 mutants. Here we describe a method to control exocytosis of synaptic vesicles through the use of a light-gated glutamate receptor (LiGluR), which has recently been demonstrated that supports secretion by means of calcium influx in chromaffin cells. Expression of LiGluR in hippocampal neurons enables reversible control of neurotransmission with light, and allows modulating the firing rate of the postsynaptic neuron with the wavelength of illumination. This method may be useful for the determination of the complex transfer function of individual synapses.

Dynamic afferent synapses to decision-making networks improve performance in tasks requiring stimulus associations and discriminations

Animals must often make opposing responses to similar complex stimuli. Multiple sensory inputs from such stimuli combine to produce stimulus-specific patterns of neural activity. It is the differences between these activity patterns, even when small, that provide the basis for any differences in behavioral response. In the present study, we investigate three tasks with differing degrees of overlap in the inputs, each with just two response possibilities. We simulate behavioral output via winner-takes-all activity in one of two pools of neurons forming a biologically based decision-making layer. The decision-making layer receives inputs either in a direct stimulus-dependent manner or via an intervening recurrent network of neurons that form the associative layer, whose activity helps distinguish the stimuli of each task. We show that synaptic facilitation of synapses to the decision-making layer improves performance in these tasks, robustly increasing accuracy and speed of responses across multiple configurations of network inputs. Conversely, we find that synaptic depression worsens performance. In a linearly nonseparable task with exclusive-or logic, the benefit of synaptic facilitation lies in its superlinear transmission: effective synaptic strength increases with presynaptic firing rate, which enhances the already present superlinearity of presynaptic firing rate as a function of stimulus-dependent input. In linearly separable single-stimulus discrimination tasks, we find that facilitating synapses are always beneficial because synaptic facilitation always enhances any differences between inputs. Thus we predict that for optimal decision-making accuracy and speed, synapses from sensory or associative areas to decision-making or premotor areas should be facilitating.

Short-term plasticity optimizes synaptic information transmission

Short-term synaptic plasticity (STP) is widely thought to play an important role in information processing. This major function of STP has recently been challenged, however, by several computational studies indicating that transmission of information by dynamic synapses is broadband, i.e., frequency independent. Here we developed an analytical approach to quantify time- and rate-dependent synaptic information transfer during arbitrary spike trains using a realistic model of synaptic dynamics in excitatory hippocampal synapses. We found that STP indeed increases information transfer in a wide range of input rates, which corresponds well to the naturally occurring spike frequencies at these synapses. This increased information transfer is observed both during Poisson-distributed spike trains with a constant rate and during naturalistic spike trains recorded in hippocampal place cells in exploring rodents. Interestingly, we found that the presence of STP in low release probability excitatory synapses leads to optimization of information transfer specifically for short high-frequency bursts, which are indeed commonly observed in many excitatory hippocampal neurons. In contrast, more reliable high release probability synapses that express dominant short-term depression are predicted to have optimal information transmission for single spikes rather than bursts. This prediction is verified in analyses of experimental recordings from high release probability inhibitory synapses in mouse hippocampal slices and fits well with the observation that inhibitory hippocampal interneurons do not commonly fire spike bursts. We conclude that STP indeed contributes significantly to synaptic information transfer and may serve to maximize information transfer for specific firing patterns of the corresponding neurons.

A history of spike-timing-dependent plasticity

How learning and memory is achieved in the brain is a central question in neuroscience. Key to today's research into information storage in the brain is the concept of synaptic plasticity, a notion that has been heavily influenced by Hebb's (1949) postulate. Hebb conjectured that repeatedly and persistently co-active cells should increase connective strength among populations of interconnected neurons as a means of storing a memory trace, also known as an engram. Hebb certainly was not the first to make such a conjecture, as we show in this history. Nevertheless, literally thousands of studies into the classical frequency-dependent paradigm of cellular learning rules were directly inspired by the Hebbian postulate. But in more recent years, a novel concept in cellular learning has emerged, where temporal order instead of frequency is emphasized. This new learning paradigm - known as spike-timing-dependent plasticity (STDP) - has rapidly gained tremendous interest, perhaps because of its combination of elegant simplicity, biological plausibility, and computational power. But what are the roots of today's STDP concept? Here, we discuss several centuries of diverse thinking, beginning with philosophers such as Aristotle, Locke, and Ribot, traversing, e.g., Lugaro's plasticità and Rosenblatt's perceptron, and culminating with the discovery of STDP. We highlight interactions between theoretical and experimental fields, showing how discoveries sometimes occurred in parallel, seemingly without much knowledge of the other field, and sometimes via concrete back-and-forth communication. We point out where the future directions may lie, which includes interneuron STDP, the functional impact of STDP, its mechanisms and its neuromodulatory regulation, and the linking of STDP to the developmental formation and continuous plasticity of neuronal networks.

Stimulus-specific adaptation and deviance detection in the rat auditory cortex

Stimulus-specific adaptation (SSA) is the specific decrease in the response to a frequent ('standard') stimulus, which does not generalize, or generalizes only partially, to another, rare stimulus ('deviant'). Stimulus-specific adaptation could result simply from the depression of the responses to the standard. Alternatively, there may be an increase in the responses to the deviant stimulus due to the violation of expectations set by the standard, indicating the presence of true deviance detection. We studied SSA in the auditory cortex of halothane-anesthetized rats, recording local field potentials and multi-unit activity. We tested the responses to pure tones of one frequency when embedded in sequences that differed from each other in the frequency and probability of the tones composing them. The responses to tones of the same frequency were larger when deviant than when standard, even with inter-stimulus time intervals of almost 2 seconds. Thus, SSA is present and strong in rat auditory cortex. SSA was present even when the frequency difference between deviants and standards was as small as 10%, substantially smaller than the typical width of cortical tuning curves, revealing hyper-resolution in frequency. Strong responses were evoked also by a rare tone presented by itself, and by rare tones presented as part of a sequence of many widely spaced frequencies. On the other hand, when presented within a sequence of narrowly spaced frequencies, the responses to a tone, even when rare, were smaller. A model of SSA that included only adaptation of the responses in narrow frequency channels predicted responses to the deviants that were substantially smaller than the observed ones. Thus, the response to a deviant is at least partially due to the change it represents relative to the regularity set by the standard tone, indicating the presence of true deviance detection in rat auditory cortex.

Synaptic short-term plasticity in auditory cortical circuits

The auditory system must be able to adapt to changing acoustic environment and still maintain accurate representation of signals. Mechanistically, this is a difficult task because the responsiveness of a large heterogeneous population of interconnected neurons must be adjusted properly and precisely. Synaptic short-term plasticity (STP) is widely regarded as a viable mechanism for adaptive processes. Although the cellular mechanism for STP is well characterized, the overall effect on information processing at the network level is poorly understood. The main challenge is that there are many cell types in auditory cortex, each of which exhibit different forms and degrees of STP. In this article, I will review the basic properties of STP in auditory cortical circuits and discuss the possible impact on signal processing.

Short-term synaptic plasticity and intensity coding

Alterations in synaptic strength over short time scales, termed short-term synaptic plasticity, can gate the flow of information through neural circuits. Different information can be extracted from the same presynaptic spike train depending on the activity- and time-dependent properties of the plasticity at a given synapse. The parallel processing in the brain stem auditory pathways provides an excellent model system for investigating the functional implications of short-term plasticity in neural coding. We review recent evidence that short-term plasticity differs in different pathways with a special emphasis on the 'intensity' pathway. While short-term depression dominates the 'timing' pathway, the intensity pathway is characterized by a balance of short-term depression and facilitation that allows linear transmission of rate-coded intensity information. Target-specific regulation of presynaptic plasticity mechanisms underlies the differential expression of depression and facilitation. The potential contribution of short-term plasticity to different aspects of 'intensity'-related information processing, such as interaural level/intensity difference coding, amplitude modulation coding, and intensity-dependent gain control coding, is discussed.

A rapid form of activity-dependent recovery from short-term synaptic depression in the intensity pathway of the auditory brainstem

Short-term synaptic plasticity acts as a time- and firing rate-dependent filter that mediates the transmission of information across synapses. In the avian auditory brainstem, specific forms of plasticity are expressed at different terminals of the same auditory nerve fibers and contribute to the divergence of acoustic timing and intensity information. To identify key differences in the plasticity properties, we made patch-clamp recordings from neurons in the cochlear nucleus responsible for intensity coding, nucleus angularis, and measured the time course of the recovery of excitatory postsynaptic currents following short-term synaptic depression. These synaptic responses showed a very rapid recovery, following a bi-exponential time course with a fast time constant of approximately 40 ms and a dependence on the presynaptic activity levels, resulting in a crossing over of the recovery trajectories following high-rate versus low-rate stimulation trains. We also show that the recorded recovery in the intensity pathway differs from similar recordings in the timing pathway, specifically the cochlear nucleus magnocellularis, in two ways: (1) a fast recovery that was not due to recovery from postsynaptic receptor desensitization and (2) a recovery trajectory that was characterized by a non-monotonic bump that may be due in part to facilitation mechanisms more prevalent in the intensity pathway. We tested whether a previously proposed model of synaptic transmission based on vesicle depletion and sequential steps of vesicle replenishment could account for the recovery responses, and found it was insufficient, suggesting an activity-dependent feedback mechanism is present. We propose that the rapid recovery following depression allows improved coding of natural auditory signals that often consist of sound bursts separated by short gaps.

Functional division of hippocampal area CA1 via modulatory gating of entorhinal cortical inputs

The hippocampus receives two streams of information, spatial and nonspatial, via major afferent inputs from the medial (MEC) and lateral entorhinal cortexes (LEC). The MEC and LEC projections in the temporoammonic pathway are topographically organized along the transverse-axis of area CA1. The potential for functional segregation of area CA1, however, remains relatively unexplored. Here, we demonstrated differential novelty-induced c-Fos expression along the transverse-axis of area CA1 corresponding to topographic projections of MEC and LEC inputs. We found that, while novel place exposure induced a uniform c-Fos expression along the transverse-axis of area CA1, novel object exposure primarily activated the distal half of CA1 neurons. In hippocampal slices, we observed distinct presynaptic properties between LEC and MEC terminals, and application of either DA or NE produced a largely selective influence on one set of inputs (LEC). Finally, we demonstrated that differential c-Fos expression along the transverse axis of area CA1 was largely abolished by an antagonist of neuromodulatory receptors, clozapine. Our results suggest that neuromodulators can control topographic TA projections allowing the hippocampus to differentially encode new information along the transverse axis of area CA1.

CB1 modulation of temporally distinct synaptic facilitation among local circuit interneurons mediated by N-type calcium channels in CA1

One of the critical factors in determining network behavior of neurons is the influence of local circuit connections among interneurons. The short-term synaptic plasticity and the subtype of presynaptic calcium channels used at local circuit connections of inhibitory interneurons in CA1 were investigated using dual whole-cell recordings combined with biocytin and double immunofluorescence labeling in acute slices of P18- to 21-day-old rat stratum radiatum (SR) and stratum lacunosum molecular (SLM). Two forms of temporally distinct synaptic facilitation were observed among interneuron connections involving presynaptic cholecystokinin (CCK)-positive cells in SR, frequency-dependent facilitation, and a delayed onset of release (45-80 ms) with subsequent facilitation (DORF). Inhibition at both these synapses was under tonic cannabinoid-type 1 (CB1) receptor activity. DORF synapses did not display conventional release-dependent properties; however, blocking CB1 receptors with antagonist AM-251 (10 μM) altered the synaptic transmission to frequency-dependent depression with a fast onset of release (2-4 ms). Presynaptic CCK-negative interneurons in SLM elicited inhibitory postsynaptic potentials (IPSPs) insensitive to CB1 receptor pharmacology displayed frequency-dependent depression. Release of GABA at facilitating synapses was solely mediated via N-type presynaptic calcium channels, whereas depressing synapses utilized P/Q-type channels. These data reveal two distinct models of neurotransmitter release patterns among interneuron circuits that correlate with the subtype of presynaptic calcium channel. These data suggest that endocannabinoids act via CB1 receptors to selectively modulate N-type calcium channels to alter signal transmission.

Presynaptic development at L4 to l2/3 excitatory synapses follows different time courses in visual and somatosensory cortex

Visual and somatosensory cortices exhibit profound experience-dependent plasticity during development and adulthood and are common model systems for probing the synaptic and molecular mechanisms of plasticity. However, comparisons between the two areas may be confounded by a lack of accurate information on their relative rates of development. In this study, we used whole-cell recording in acute brain slices to study synaptic development in mouse barrel and visual cortex. We found that short-term plasticity (STP) switched from strong depression at postnatal day (P)12 to weaker depression and facilitation in mature cortex. However, presynaptic maturation was delayed by ∼2 weeks at layer (L)4 to L2/3 excitatory synapses in visual cortex relative to barrel cortex. This developmental delay was pathway-specific; maturation of L2/3 to L2/3 synapses occurred over similar timescales in barrel and visual cortex. The developmental increase in the paired-pulse ratio to values greater than unity was mirrored by a developmental decrease in presynaptic release probability. Therefore, L4 to L2/3 excitatory synapses had lower release probabilities and showed greater short-term facilitation in barrel cortex than in visual cortex at P28. Postsynaptic mechanisms could not account for the delayed maturation of STP in visual cortex. These findings indicate that synaptic development is delayed in the L4 to L2/3 pathway in visual cortex, and emphasize the need to take into account the changes in synaptic properties that occur during development when comparing plasticity mechanisms in different cortical areas.

Distinct roles of GABAergic interneurons in the regulation of striatal output pathways

Striatal GABAergic microcircuits are critical for motor function, yet their properties remain enigmatic due to difficulties in targeting striatal interneurons for electrophysiological analysis. Here, we use Lhx6-GFP transgenic mice to identify GABAergic interneurons and investigate their regulation of striatal direct- and indirect-pathway medium spiny neurons (MSNs). We find that the two major interneuron populations, persistent low-threshold spiking (PLTS) and fast spiking (FS) interneurons, differ substantially in their excitatory inputs and inhibitory outputs. Excitatory synaptic currents recorded from PLTS interneurons are characterized by a small, nonrectifying AMPA receptor-mediated component and a NMDA receptor-mediated component. In contrast, glutamatergic synaptic currents in FS interneurons have a large, strongly rectifying AMPA receptor-mediated component, but no detectable NMDA receptor-mediated responses. Consistent with their axonal morphology, the output of individual PLTS interneurons is relatively weak and sparse, whereas FS interneurons are robustly connected to MSNs and other FS interneurons and appear to mediate the bulk of feedforward inhibition. Synaptic depression of FS outputs is relatively insensitive to firing frequency, and dynamic-clamp experiments reveal that these short-term dynamics enable feedforward inhibition to remain efficacious across a broad frequency range. Surprisingly, we find that FS interneurons preferentially target direct-pathway MSNs over indirect-pathway MSNs, suggesting a potential mechanism for rapid pathway-specific regulation of striatal output pathways.

Encoding and decoding bursts by NMDA spikes in basal dendrites of layer 5 pyramidal neurons

Bursts of action potentials are important information-bearing signals in the brain, although the neuronal specializations underlying burst generation and detection are only partially understood. In apical dendrites of neocortical pyramidal neurons, calcium spikes are known to contribute to burst generation, but a comparable understanding of basal dendritic mechanisms is lacking. Here we show that NMDA spikes in basal dendrites mediate both detection and generation of bursts through a postsynaptic mechanism. High-frequency inputs to basal dendrites markedly facilitated NMDA spike initiation compared with low-frequency activation or single inputs. Unlike conventional temporal summation effects based on voltage, however, NMDA spike facilitation depended mainly on residual glutamate bound to NMDA receptors from previous activations. Once triggered by an input burst, we found that NMDA spikes in turn reliably trigger output bursts under in vivo-like stimulus conditions. Through their unique biophysical properties, NMDA spikes are thus ideally suited to promote the propagation of bursts through the cortical network.

Enhanced long-term microcircuit plasticity in the valproic Acid animal model of autism

A single intra-peritoneal injection of valproic acid (VPA) on embryonic day (ED) 11.5 to pregnant rats has been shown to produce severe autistic-like symptoms in the offspring. Previous studies showed that the microcircuitry is hyperreactive due to hyperconnectivity of glutamatergic synapses and hyperplastic due to over-expression of NMDA receptors. These changes were restricted to the dimensions of a minicolumn (<50 μm). In the present study, we explored whether Long Term Microcircuit Plasticity (LTMP) was altered in this animal model. We performed multi-neuron patch-clamp recordings on clusters of layer 5 pyramidal cells in somatosensory cortex brain slices (PN 12-15), mapped the connectivity and characterized the synaptic properties for connected neurons. Pipettes were then withdrawn and the slice was perfused with 100 μM sodium glutamate in artificial cerebrospinal fluid in the recording chamber for 12 h. When we re-patched the same cluster of neurons, we found enhanced LTMP only at inter-somatic distances beyond minicolumnar dimensions. These data suggest that hyperconnectivity is already near its peak within the dimensions of the minicolumn in the treated animals and that LTMP, which is normally restricted to within a minicolumn, spills over to drive hyperconnectivity across the dimensions of a minicolumn. This study provides further evidence to support the notion that the neocortex is highly plastic in response to new experiences in this animal model of autism.

Long-term plasticity is proportional to theta-activity

Background

Theta rhythm in the hippocampal formation is a main feature of exploratory behaviour and is believed to enable the encoding of new spatial information and the modification of synaptic weights. Cyclic changes of dentate gyrus excitability during theta rhythm are related to its function, but whether theta epochs per se are able to alter network properties of dentate gyrus for long time-periods is still poorly understood.

Methodology/Principal Findings

We used low-frequency stimulation protocols that amplify the power of endogenous theta oscillations, in order to estimate the plasticity effect of endogenous theta oscillations on a population level. We found that stimulation-induced augmentation of the theta rhythm is linked to a subsequent increase of neuronal excitability and decrease of the synaptic response. This EPSP-to-Spike uncoupling is related to an increased postsynaptic spiking on the positive phases of theta frequency oscillations. Parallel increase of the field EPSP slope and the population spike occurs only after concurrent pre- and postsynaptic activation. Furthermore, we observed that long-term potentiation (>24 h) occurs in the dentate gyrus of freely behaving adult rats after phasic activity of entorhinal afferents in the theta-frequency range. This plasticity is proportional to the field bursting activity of granule cells during the stimulation, and may comprise a key step in spatial information transfer. Long-term potentiation of the synaptic component occurs only when the afferent stimulus precedes the evoked population burst, and is input-specific.

Conclusions/Significance

Our data confirm the role of the dentate gyrus in filtering information to the subsequent network during the activated state of the hippocampus.