Towards a metallic top contact electrode in molecular electronic devices exhibiting a large surface coverage by photoreduction of silver cations

In this contribution the photoreduction of silver ions coordinated onto a Langmuir–Blodgett monolayer is presented as an effective method for the deposition of the top contact electrode in metal/monolayer/metal devices. Silver cations were incorporated from an aqueous AgNO3 sub-phase of Langmuir films of 4,4'-(1,4-phenylenebis(ethyne-2,1-diyl))dibenzoic acid upon the transference of these films onto a metallic substrate. Subsequent irradiation of the silver-ion functionalized Langmuir–Blodgett films with 254 nm light results in the photoreduction of silver cations to produce metallic silver nanoparticles, which are distributed over the organic monolayer and exhibit a surface coverage as large as 76% of the monolayer surface. Electrical properties of these metal/monolayer/metal devices were determined by recording I–V curves, which show a sigmoidal behaviour indicative of well-behaved junctions free of metallic filaments and short-circuits. The integrity of the organic monolayer upon the irradiation process and formation of the silver top-contact electrode has also been demonstrated through cyclic voltammetry experiments

Towards molecular electronic devices based on 'all-carbon' wires

Nascent molecular electronic devices based on linear ‘all-carbon’ wires attached to gold electrodes through robust and reliable C–Au contacts are prepared via efficient in situ sequential cleavage of trimethylsilyl end groups from an oligoyne, Me3Si–(C[triple bond, length as m-dash]C)4–SiMe3 (1). In the first stage of the fabrication process, removal of one trimethylsilyl (TMS) group in the presence of a gold substrate, which ultimately serves as the bottom electrode, using a stoichiometric fluoride-driven process gives a highly-ordered monolayer, Au|C[triple bond, length as m-dash]CC[triple bond, length as m-dash]CC[triple bond, length as m-dash]CC[triple bond, length as m-dash]CSiMe3 (Au|C8SiMe3). In the second stage, treatment of Au|C8SiMe3 with excess fluoride results in removal of the remaining TMS protecting group to give a modified monolayer Au|C[triple bond, length as m-dash]CC[triple bond, length as m-dash]CC[triple bond, length as m-dash]CC[triple bond, length as m-dash]CH (Au|C8H). The reactive terminal C[triple bond, length as m-dash]C–H moiety in Au|C8H can be modified by ‘click’ reactions with (azidomethyl)ferrocene (N3CH2Fc) to introduce a redox probe, to give Au|C6C2N3HCH2Fc. Alternatively, incubation of the modified gold substrate supported monolayer Au|C8H in a solution of gold nanoparticles (GNPs), results in covalent attachment of GNPs on top of the film via a second alkynyl carbon–Au σ-bond, to give structures Au|C8|GNP in which the monolayer of linear, ‘all-carbon’ C8 chains is sandwiched between two macroscopic gold contacts. The covalent carbon–surface bond as well as the covalent attachment of the metal particles to the monolayer by cleavage of the alkyne C–H bond is confirmed by surface-enhanced Raman scattering (SERS). The integrity of the carbon chain in both Au|C6C2N3HCH2Fc systems and after formation of the gold top-contact electrode in Au|C8|GNP is demonstrated through electrochemical methods. The electrical properties of these nascent metal–monolayer–metal devices Au|C8|GNP featuring ‘all-carbon’ molecular wires were characterised by sigmoidal I–V curves, indicative of well-behaved junctions free of short circuits

Spatial representation of temporal information through spike timing dependent plasticity

We suggest a mechanism based on spike time dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model system of simplified integrate-and-fire type neurons densely connected by STDP synapses. All synapses are modified according to the so-called normal STDP rule observed in various real biological synapses. After conditioning through repeated input of a limited number of of temporal sequences the system is able to complete the temporal sequence upon receiving the input of a fraction of them. This is an example of effective unsupervised learning in an biologically realistic system. We investigate the dependence of learning success on entrainment time, system size and presence of noise. Possible applications include learning of motor sequences, recognition and prediction of temporal sensory information in the visual as well as the auditory system and late processing in the olfactory system of insects.Comment: 13 pages, 14 figures, completely revised and augmented versio

Self-organization in the olfactory system: one shot odor recognition in insects

We show in a model of spiking neurons that synaptic plasticity in the mushroom bodies in combination with the general fan-in, fan-out properties of the early processing layers of the olfactory system might be sufficient to account for its efficient recognition of odors. For a large variety of initial conditions the model system consistently finds a working solution without any fine-tuning, and is, therefore, inherently robust. We demonstrate that gain control through the known feedforward inhibition of lateral horn interneurons increases the capacity of the system but is not essential for its general function. We also predict an upper limit for the number of odor classes Drosophila can discriminate based on the number and connectivity of its olfactory neurons

Techniques for temporal detection of neural sensitivity to external stimulation

We propose a simple measure of neural sensitivity for characterizing stimulus coding. Sensitivity is defined as the fraction of neurons that show positive responses to n stimuli out of a total of N. To determine a positive response, we propose two methods: Fisherian statistical testing and a data-driven Bayesian approach to determine the response probability of a neuron. The latter is non-parametric, data-driven, and captures a lower bound for the probability of neural responses to sensory stimulation. Both methods are compared with a standard test that assumes normal probability distributions. We applied the sensitivity estimation based on the proposed method to experimental data recorded from the mushroom body (MB) of locusts. We show that there is a broad range of sensitivity that the MB response sweeps during odor stimulation. The neurons are initially tuned to specific odors, but tend to demonstrate a generalist behavior towards the end of the stimulus period, meaning that the emphasis shifts from discrimination to feature learning

Encoding Odorant Identity by Spiking Packets of Rate-Invariant Neurons in Awake Mice

Background: How do neural networks encode sensory information? Following sensory stimulation, neural coding is commonly assumed to be based on neurons changing their firing rate. In contrast, both theoretical works and experiments in several sensory systems showed that neurons could encode information as coordinated cell assemblies by adjusting their spike timing and without changing their firing rate. Nevertheless, in the olfactory system, there is little experimental evidence supporting such model. Methodology/Principal Findings: To study these issues, we implanted tetrodes in the olfactory bulb of awake mice to record the odorant-evoked activity of mitral/tufted (M/T) cells. We showed that following odorant presentation, most M/T neurons do not significantly change their firing rate over a breathing cycle but rather respond to odorant stimulation by redistributing their firing activity within respiratory cycles. In addition, we showed that sensory information can be encoded by cell assemblies composed of such neurons, thus supporting the idea that coordinated populations of globally rateinvariant neurons could be efficiently used to convey information about the odorant identity. We showed that different coding schemes can convey high amount of odorant information for specific read-out time window. Finally we showed that the optimal readout time window corresponds to the duration of gamma oscillations cycles. Conclusion: We propose that odorant can be encoded by population of cells that exhibit fine temporal tuning of spiking activity while displaying weak or no firing rate change. These cell assemblies may transfer sensory information in spikin

Gain control network conditions in early sensory coding

Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models