Targeted Chemical Processing Initiating Biosome Action-Potential-Matched Artificial Synapses for the Brain-Machine Interface.

A great gap still exists between artificial synapses and their biological counterparts in operation voltage or stimulation duration. Here, an artificial synaptic device based on a thin-film transistor with an operating voltage (-50-50 mV) analogous to biological action potential is developed by targeted chemical processing with the help of supercritical fluids. Chemical molecules [hexamethyldisilazane (HMDS)] are elaborately chosen and brought into the target interface to form charge receptors through supercritical processing. These charge receptors with the ability of capturing electrons mimic neurotransmitter receptors in terms of mechanism and constitute key players accounting for the synaptic behaviors. The relatively lower electrical barrier height contributes to an action-potential-matched operating voltage and considerably low power consumption (∼1 pJ/synaptic event), minimizing the divide with biological synapse for a seamless linkage to the biosystem or brain-machine interface. The stable synaptic behaviors also lead to near-ideal accuracy in pattern recognition. Moreover, this methodology that introduces chemical groups into a target interface can be viewed as a platform technology that could be adapted to other conventional devices with suitable chemical molecules to reach designed synaptic behaviors. This environmentally friendly and low-temperature processing method, which can be performed even after device fabrication, has the potential to play an important role in the future development of bionic devices.

An Aqueous Electrolyte Gated Artificial Synapse with Synaptic Plasticity Selectively Mediated by Biomolecules.

The emulation of functions and behaviors of biological synapses using electronic devices has inspired the development of artificial neural networks (ANNs) in biomedical interfaces. Despite the achievements, artificial synapses that can be selectively responsive to non-electroactive biomolecules and directly operate in biological environments are still lacking. Herein, we report an artificial synapse based on organic electrochemical transistors and investigate the selective modulation of its synaptic plasticity by glucose. The enzymatic reaction between glucose and glucose oxidase results in long-term modulation of the channel conductance, mimicking selective binding of biomolecules to their receptors and consequent long-term modulation of the synaptic weight. Moreover, the device shows enhanced synaptic behaviors in the blood serum at a higher glucose concentration, which suggests its potential application in vivo as artificial neurons. This work provides a step towards the fabrication of ANNs with synaptic plasticity selectively mediated by biomolecules for neuro-prosthetics and human-machine interfaces.

Hippocampal Proteomics Reveals the Role of Glutamatergic Synapse Activation in the Depression Induced by Perfluorooctane Sulfonate.

Perfluorooctane sulfonate (PFOS), a new type of persistent organic pollutant in the environment of water, has drawn significant attention in recent years due to its widespread prevalence and high toxicity. Neurotoxicity is regarded as one of the major toxic effects of PFOS, while research studies on PFOS-induced depression and the underlying mechanisms remain scarce. In this study, behavioral tests revealed the depressive-like behaviors in PFOS-exposed male mice. Neuron damages including pyknosis and staining deepening were identified through hematoxylin and eosin staining. Then, we noticed the elevation of glutamate and proline levels as well as the decline of glutamine and tryptophan levels. Proteomics analysis identified 105 differentially expressed proteins that change in a dose-dependent manner and revealed that PFOS exposure activated the glutamatergic synapse signaling pathway, which were further confirmed by Western blot, and the data were consistent with the findings of the proteomics analysis. Additionally, the downstream signaling cyclic AMP-responsive element-binding protein (CREB)/brain-derived neurotrophic factor (BDNF) and synaptic plasticity-related postsynaptic density protein 95, synaptophysin, were downregulated. Our results highlight that PFOS exposure may inhibit the synaptic plasticity of the hippocampus via glutamatergic synapse and the CREB/BDNF signaling pathway to cause depressive-like behaviors in male mice.

Tactile tribotronic reconfigurable p-n junctions for artificial synapses.

The emulation of biological synapses with learning and memory functions and versatile plasticity is significantly promising for neuromorphic computing systems. Here, a robust and continuously adjustable mechanoplastic semifloating-gate transistor is demonstrated based on an integrated graphene/hexagonal boron nitride/tungsten diselenide van der Waals heterostructure and a triboelectric nanogenerator (TENG). The working states (p-n junction or n+-n junction) can be manipulated and switched under the sophisticated modulation of triboelectric potential derived from mechanical actions, which is attributed to carriers trapping and detrapping in the graphene layer. Furthermore, a reconfigurable artificial synapse is constructed based on such mechanoplastic transistor that can simulate typical synaptic plasticity and implement dynamic control correlations in each response mode by further designing the amplitude and duration. The artificial synapse can work with ultra-low energy consumption at 74.2 fJ per synaptic event and the extended synaptic weights. Under the synergetic effect of the semifloating gate, the synaptic device can enable successive mechanical facilitation/depression, short-/long-term plasticity and learning-experience behavior, exhibiting the mechanical behavior derived synaptic plasticity. Such reconfigurable and mechanoplastic features provide an insight into the applications of energy-efficient and real-time interactive neuromodulation in the future artificial intelligent system beyond von Neumann architecture.

Wavelength and Polarization Sensitive Synaptic Phototransistor Based on Organic n-type Semiconductor/Supramolecular J-Aggregate Heterostructure.

Human retina- and brain-inspired optoelectronic synapses, which integrate light detection and signal memory functions for data processing, have significant interest because of their potential applications for artificial vision technology. In nature, many animals such as mantis shrimp use polarized light information as well as scalar information including wavelength and intensity; however, a spectropolarimetric organic optoelectronic synapse has been seldom investigated. Herein, we report an organic synaptic phototransistor, consisting of a charge trapping liquid-crystalline perylene bisimide J-aggregate and a charge transporting crystalline dichlorinated naphthalene diimide, that can detect both wavelength and polarization information. The device shows persistent positive and negative photocurrents under low and high voltage conditions, respectively. Furthermore, the aligned organic heterostructure in the thin-film enables linearly polarized light to be absorbed with a dichroic ratio of 1.4 and 3.7 under transverse polarized blue and red light illumination, respectively. These features allow polarized light sensitive postsynaptic functions in the device. Consequently, a simple polarization imaging sensor array is successfully demonstrated using photonic synapses, which suggests that a supramolecular material is an important candidate for the development of spectropolarimetric neuromorphic vision systems.

Optoelectronic Artificial Synaptic Device Based on Amorphous InAlZnO Films for Learning Simulations.

Neuromorphic computing, which mimics brain function, can address the shortcomings of the "von Neumann" system and is one of the critical components of next-generation computing. The use of light to stimulate artificial synapses has the advantages of low power consumption, low latency, and high stability. We demonstrate amorphous InAlZnO-based light-stimulated artificial synaptic devices with a thin-film transistor structure. The devices exhibit fundamental synaptic properties, including excitatory postsynaptic current, paired-pulse facilitation (PPF), and short-term plasticity to long-term plasticity conversion under light stimulation. The PPF index stimulated by 375 nm light is 155.9% when the time interval is 0.1 s. The energy consumption of each synaptic event is 2.3 pJ, much lower than that of ordinary MOS devices and other optical-controlled synaptic devices. The relaxation time constant reaches 277 s after only 10 light spikes, which shows the great synaptic plasticity of the device. In addition, we simulated the learning-forgetting-relearning-forgetting behavior and learning efficiency of human beings under different moods by changing the gate voltage. This work is expected to promote the development of high-performance optoelectronic synaptic devices for neuromorphic computing.

A non-linear two-dimensional float gate transistor as a lateral inhibitory synapse for retinal early visual processing.

Synaptic transistors that accommodate concurrent signal transmission and learning in a neural network are attracting enormous interest for neuromorphic sensory processing. To remove redundant sensory information while keeping important features, artificial synaptic transistors with non-linear conductance are desired to apply filter processing to sensory inputs. Here, we report the realization of non-linear synapses using a two-dimensional van der Waals (vdW) heterostructure (MoS2/h-BN/graphene) based float gate memory device, in which the semiconductor channel is tailored via a surface acceptor (ZnPc) for subthreshold operation. In addition to usual synaptic plasticity, the memory device exhibits highly non-linear conductance (rectification ratio >106), allowing bidirectional yet only negative/inhibitory current to pass through. We demonstrate that in a lateral coupling network, such a float gate memory device resembles the key lateral inhibition function of horizontal cells for the formation of an ON-center/OFF-surround receptive field. When combined with synaptic plasticity, the lateral inhibition weights are further tunable to enable adjustable edge enhancement for early visual processing. Our results here hopefully open a new scheme toward early sensory perception via lateral inhibitory synaptic transistors.

Flexible Artificial Optoelectronic Synapse based on Lead-Free Metal Halide Nanocrystals for Neuromorphic Computing and Color Recognition.

Optoelectronic synapses combining optical-sensing and synaptic functions are playing an increasingly vital role in the neuromorphic computing systems development, which can efficiently process visual information and complex recognition, memory, and learning. Metal halides are considered promising candidates for synaptic devices due to their excellent optoelectronic properties. However, the toxicity of lead and the further development of device functions are the recognized problems at present. Herein, a flexible optoelectronic synapses system based on high-quality lead-free Cs3 Bi2 I9 nanocrystals is demonstrated, in which the carrier confinement caused by the band mismatching between the Cs3 Bi2 I9 and the organic semiconductor layer provides the possibility to simulate synaptic behaviors. The synaptic functions including long/short-term memory and learning-forgetting-relearning are demonstrated in this device and visual perception, visual memory, and color recognition functions are successfully implemented. Additionally, the flexible device exhibits excellent robustness and can realize imaging of light distribution under curved hemispheres similar to the human eye. Finally, through the simulation based on an artificial neural network algorithm, the device successfully realizes the high-precision recognition of handwritten digital images and possesses a strong fault tolerant capability even in bending states. These results are expected to drive the practical progress of metal halide for neuromorphic computing.

Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach.

The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the abundance of its constituent proteins both spatially, in different brain areas, and temporally, during development, circadian rhythm, and also in response to various stimuli. In this study we ran large-scale stochastic simulations of protein binding events to predict the presence and distribution of PSD complexes. We simulated the interactions of seven major PSD proteins (NMDAR, AMPAR, PSD-95, SynGAP, GKAP, Shank3, Homer1) based on previously published, experimentally determined protein abundance data from 22 different brain areas and 42 patients (altogether 524 different simulations). Our results demonstrate that the relative ratio of the emerging protein complexes can be sensitive to even subtle changes in protein abundances and thus explicit simulations are invaluable to understand the relationships between protein availability and complex formation. Our observations are compatible with a scenario where larger supercomplexes are formed from available smaller binary and ternary associations of PSD proteins. Specifically, Homer1 and Shank3 self-association reactions substantially promote the emergence of very large protein complexes. The described simulations represent a first approximation to assess PSD complex abundance, and as such, use significant simplifications. Therefore, their direct biological relevance might be limited but we believe that the major qualitative findings can contribute to the understanding of the molecular features of the postsynapse.

The ability of carbon nanoparticles to increase transmembrane current of cations coincides with impaired synaptic neurotransmission.

Here, carbon nanodots synthesized from ß-alanine (Ala-CDs) and detonation nanodiamonds (NDs) were assessed using (1) radiolabeled excitatory neurotransmitters L-[14C]glutamate, D-[2,33H]aspartate, and inhibitory ones [3H]GABA, [3H]glycine for registration of their extracellular concentrations in rat cortex nerve terminals; (2) the fluorescent ratiometric probe NR12S and pH-sensitive probe acridine orange for registration of the membrane lipid order and synaptic vesicle acidification, respectively; (3) suspended bilayer lipid membrane (BLM) to monitor changes in transmembrane current. In nerve terminals, Ala-CDs and NDs increased the extracellular concentrations of neurotransmitters and decreased acidification of synaptic vesicles, whereas have not changed sufficiently the lipid order of membrane. Both nanoparticles, Ala-CDs and NDs, were capable of increasing the conductance of the BLM by inducing stable potential-dependent cation-selective pores. Introduction of divalent cations, Zn2+ or Cd2+ on the particles` application side (cis-side) increased the rate of Ala-CDs pore-formation in the BLM. The application of positive potential (+100 mV) to the cis-chamber with Ala-CDs or NDs also activated the insertion as compared with the negative potential (-100 mV). The Ala-CD pores exhibited a wide-range distribution of conductances between 10 and 60 pS and consecutive increase in conductance of each major peak by ~10 pS, which suggest the clustering of the same basic ion-conductive structure. NDs also formed ion-conductive pores ranging from 6 pS to 60 pS with the major peak of conductance at ~12 pS in cholesterol-containing membrane. Observed Ala-CDs and NDs-induced increase in transmembrane current coincides with disturbance of excitatory and inhibitory neurotransmitter transport in nerve terminals.

Volumetric super-resolution imaging by serial ultrasectioning and stochastic optical reconstruction microscopy in mouse neural tissue.

Here, we present a protocol for collecting large-volume, four-color, single-molecule localization imaging data from neural tissue. We have applied this technique to map the location and identities of chemical synapses across whole cells in mouse retinae. Our sample preparation approach improves 3D STORM image quality by reducing tissue scattering, photobleaching, and optical distortions associated with deep imaging. This approach can be extended for use on other tissue types enabling life scientists to perform volumetric super-resolution imaging in diverse biological models. For complete details on the use and execution of this protocol, please refer to Sigal et al. (2015).

Activating Silent Synapses in Sulfurized Indium Selenide for Neuromorphic Computing.

The transformation from silent to functional synapses is accompanied by the evolutionary process of human brain development and is essential to hardware implementation of the evolutionary artificial neural network but remains a challenge for mimicking silent to functional synapse activation. Here, we developed a simple approach to successfully realize activation of silent to functional synapses by controlled sulfurization of chemical vapor deposition-grown indium selenide crystals. The underlying mechanism is attributed to the migration of sulfur anions introduced by sulfurization. One of our most important findings is that the functional synaptic behaviors can be modulated by the degree of sulfurization and temperature. In addition, the essential synaptic behaviors including potentiation/depression, paired-pulse facilitation, and spike-rate-dependent plasticity are successfully implemented in the partially sulfurized functional synaptic device. The developed simple approach of introducing sulfur anions in layered selenide opens an effective new avenue to realize activation of silent synapses for application in evolutionary artificial neural networks.

Nanoscale organization of Nicastrin, the substrate receptor of the γ-secretase complex, as independent molecular domains.

Alterations in the canonical processing of Amyloid Precursor Protein generate proteoforms that contribute to the onset of Alzheimer's Disease. Modified composition of γ-secretase or mutations in its subunits has been directly linked to altered generation of Amyloid beta. Despite biochemical evidence about the role of γ-secretase in the generation of APP, the molecular origin of how spatial heterogeneity in the generation of proteoforms arises is not well understood. Here, we evaluated the localization of Nicastrin, a γ-secretase subunit, at nanometer sized functional zones of the synapse. With the help of super resolution microscopy, we confirm that Nicastrin is organized into nanodomains of high molecular density within an excitatory synapse. A similar nanoorganization was also observed for APP and the catalytic subunit of γ-secretase, Presenilin 1, that were discretely associated with Nicastrin nanodomains. Though Nicastrin is a functional subunit of γ-secretase, the Nicastrin and Presenilin1 nanodomains were either colocalized or localized independent of each other. The Nicastrin and Presenilin domains highlight a potential independent regulation of these molecules different from their canonical secretase function. The collisions between secretases and substrate molecules decide the probability and rate of product formation for transmembrane proteolysis. Our observations of secretase nanodomains indicate a spatial difference in the confinement of substrate and secretases, affecting the local probability of product formation by increasing their molecular availability, resulting in differential generation of proteoforms even within single synapses.

Optically Modulated HfS2-Based Synapses for Artificial Vision Systems.

The simulation of human brain neurons by synaptic devices could be an effective strategy to break through the notorious "von Neumann Bottleneck" and "Memory Wall". Herein, opto-electronic synapses based on layered hafnium disulfide (HfS2) transistors have been investigated. The basic functions of biological synapses are realized and optimized by modifying pulsed light conditions. Furthermore, 2 × 2 pixel imaging chips have also been developed. Two-pixel visual information is illuminated on diagonal pixels of the imaging array by applying light pulses (λ = 405 nm) with different pulse frequencies, mimicking short-term memory and long-term memory characteristics of the human vision system. In addition, an optically/electrically driven neuromorphic computation is demonstrated by machine learning to classify hand-written numbers with an accuracy of about 88.5%. This work will be an important step toward an artificial neural network comprising neuromorphic vision sensing and training functions.

Amyloid pathology and synaptic loss in pathological aging.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory dysfunction and cognitive decline. Pathological aging (PA) describes patients who are amyloid-positive but cognitively unimpaired at time of death. Both AD and PA contain amyloid plaques dominated by amyloid ß (Aß) peptides. In this study, we investigated and compared synaptic protein levels, amyloid plaque load, and Aß peptide patterns between AD and PA. Two cohorts of post-mortem brain tissue were investigated. In the first, consisting of controls, PA, AD, and familial AD (FAD) individuals, synaptic proteins extracted with tris(hydroxymethyl)aminomethane-buffered saline (TBS) were analyzed. In the second, consisting of tissue from AD and PA patients from three different regions (occipital lobe, frontal lobe, and cerebellum), a two-step extraction was performed. Five synaptic proteins were extracted using TBS, and from the remaining portion Aß peptides were extracted using formic acid. Subsequently, immunoprecipitation with several antibodies targeting different proteins/peptides was performed for both fractions, which were subsequently analyzed by mass spectrometry. The levels of synaptic proteins were lower in AD (and FAD) compared with PA (and controls), confirming synaptic loss in AD patients. The amyloid plaque load was increased in AD compared with PA, and the relative amount of Aß40 was higher in AD while for Aß42 it was higher in PA. In AD loss of synaptic function was associated with increased plaque load and increased amounts of Aß40 compared with PA cases, suggesting that synaptic function is preserved in PA cases even in the presence of Aß.

Clathrin packets move in slow axonal transport and deliver functional payloads to synapses.

In non-neuronal cells, clathrin has established roles in endocytosis, with clathrin cages enclosing plasma membrane infoldings, followed by rapid disassembly and reuse of monomers. However, in neurons, clathrin is conveyed in slow axonal transport over days to weeks, and the underlying transport/targeting mechanisms, mobile cargo structures, and even its precise presynaptic localization and physiologic role are unclear. Combining live imaging, photobleaching/conversion, mass spectrometry, electron microscopy, and super-resolution imaging, we found that unlike in dendrites, where clathrin cages rapidly assemble and disassemble, in axons, clathrin and related proteins organize into stable "transport packets" that are unrelated to endocytosis and move intermittently on microtubules, generating an overall slow anterograde flow. At synapses, multiple clathrin packets abut synaptic vesicle (SV) clusters, and clathrin packets also exchange between synaptic boutons in a microtubule-dependent "superpool." Within synaptic boundaries, clathrin is surprisingly dynamic, continuously exchanging between local clathrin assemblies, and its depletion impairs SV recycling. Our data provide a conceptual framework for understanding clathrin trafficking and presynaptic targeting that has functional implications.

Grain-Boundary Engineering of Monolayer MoS2 for Energy-Efficient Lateral Synaptic Devices.

Synaptic devices based on 2D-layered materials have emerged as high-efficiency electronic synapses and neurons for neuromorphic computing. Lateral 2D synaptic devices have the advantages of multiple functionalities by responding to diverse stimuli, but they consume large amounts of energy, far more than the human brain. Moreover, current lateral devices employ several mechanisms based on conductive filaments and grain boundaries (GBs), but their formation is random and difficult to control, also hindering their practical applications. Here, four-terminal, lateral synaptic devices with artificially engineered GBs are reported, which are made from monolayer MoS2 . With lithography-free, direct-laser-writing-controlled MoS2 /MoS2- x Oδ GBs, such synaptic devices exhibit short-term and long-term plasticity characteristics that are responsive to electric and light stimulation simultaneously. This enables detailed simulations of biological learning and cognitive processes as well as image perception and processing. In particular, the device exhibits low energy consumption, similar to that of the human brain and much lower than those of other lateral 2D synaptic devices. This work provides an effective way to fabricate lateral synaptic devices for practical application development and sheds light on controllable electrical state switching for neuromorphic computing.

Modeling the role of gap junctions between excitatory neurons in the developing visual cortex.

Recent experiments in the developing mammalian visual cortex have revealed that gap junctions couple excitatory cells and potentially influence the formation of chemical synapses. In particular, cells that were coupled by a gap junction during development tend to share an orientation preference and are preferentially coupled by a chemical synapse in the adult cortex, a property that is diminished when gap junctions are blocked. In this work, we construct a simplified model of the developing mouse visual cortex including spike-timing-dependent plasticity of both the feedforward synaptic inputs and recurrent cortical synapses. We use this model to show that synchrony among gap-junction-coupled cells underlies their preference to form strong recurrent synapses and develop similar orientation preference; this effect decreases with an increase in coupling density. Additionally, we demonstrate that gap-junction coupling works, together with the relative timing of synaptic development of the feedforward and recurrent synapses, to determine the resulting cortical map of orientation preference.