Spatio-temporal representation of the pitch of complex tones in the auditory nerve and cochlear nucleus

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (leaves 73-79).Traditional models for pitch processing have relied either on a purely spatial representation based on the frequency selectivity and frequency-to-place mapping in the cochlea, or on a purely temporal representation dependent on neural phase locking to the stimulus period. However, rate-place cues to the pitch of harmonic complex tones in the auditory nerve (AN) saturate at high levels, and temporal cues fail to predict the strong pitch of resolved harmonics. Thus, neither pitch representation accounts for all key psychophysical observations. Recently, it has been shown that the AN also contains spatio-temporal cues to the individual harmonics of a complex tone that might be used in pitch extraction and are more consistent with psychophysical data (Cedolin 2006) This thesis aims to evaluate whether these cues are extracted in cochlear nucleus (CN) neurons, which receive inputs from AN fibers. We used transient complex stimuli ("Huffman sequences") designed to manipulate the relative timing between adjacent AN fibers to evaluate sensitivity of CN units to the spatio-temporal pattern of their inputs. A small minority of units were sensitive to the stimulus manipulations, with only a few sensitive in the direction consistent with cross-frequency coincidence detection. We also measured the strength of the rate representation for the pitch of harmonic complex tones in CN units and found a few units that maintained salient pitch cues at high stimulus levels. However there was no obvious correlation between spatio-temporal sensitivity and robust pitch cues. Instead of a conversion of spatio-temporal cues in the AN into rate cues, our results indicate that temporal sharpening occurs at the level of the CN.by Grace I. Wang.S.M

Coincidence detection in the cochlear nucleus : implications for the coding of pitch

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 165-177).The spatio-temporal pattern in the auditory nerve (AN), i.e. the temporal pattern of AN fiber activity across the tonotopic axis, provides cues to important features in sounds such as pitch, loudness, and spatial location. These spatio-temporal cues may be extracted by central neurons in the cochlear nucleus (CN) that receive inputs from AN fibers innervating different cochlear regions and are sensitive to their relative timing. One possible mechanism for this extraction is cross-frequency coincidence detection (CD), in which a central neuron converts the degree of cross-frequency coincidence in the AN into a rate response by preferentially firing when its AN inputs across the tonotopic axis discharge in synchrony. We implemented a CD model receiving AN inputs from varying extents of the tonotopic axis, and compared responses of model CD cells with those of single units recorded in the CN of the anesthetized cat. We used Huffman stimuli, which have flat magnitude spectra and a single phase transition, to systematically manipulate the relative timing across AN fibers and to evaluate the sensitivity of model CD cells and CN units to the spatiotemporal pattern of AN discharges. Using a maximum likelihood approach, we found that certain unit types (primary-like-with-notch and some phase lockers) had responses consistent with cross-frequency CD cell. Some of these CN units provide input to neurons in a binaural circuit that process cues for sound localization and are sensitive to interaural level differences. A possible functional role of a cross-frequency CD mechanism in the CN is to increase the dynamic range of these binaural neurons. However, many other CN units had responses more consistent with AN fibers than with CD cells. We hypothesized that CN units resembling cross-frequency CD cells (as determined by their responses to Huffman stimuli) would convert spatio-temporal cues to pitch in the AN into rate cues that are robust with level. We found that, in response to harmonic complex tones, cross-frequency CD cells and some CN units (primary-like-with-notch and choppers) maintained robust rate cues at high levels compared to AN fibers, suggesting that at least some CN neurons extend the dynamic range of rate representations of pitch beyond that found in AN fibers. However, there was no obvious correlation between robust rate cues in individual CN units and similarity to cross-frequency CD cells as determined by responses to Huffman stimuli. It is likely that a model including more realistic inputs, membrane channels, and spiking mechanism, or other mechanisms such as lateral inhibition or spatial and temporal summation over spatially distributed inputs would provide insight into the neural mechanisms that give rise to the robust rate cues observed in some CN units.by Grace I. Wang.Ph.D

Atomic Structure and Dynamics of Single Platinum Atom Interactions with Monolayer MoS

We have studied atomic level interactions between single Pt atoms and the surface of monolayer MoS₂ using aberration-corrected annular dark field scanning transmission electron microscopy at an accelerating voltage of 60 kV. Strong contrast from single Pt atoms on the atomically resolved monolayer MoS₂ lattice enables their exact position to be determined with respect to the MoS₂ lattice, revealing stable binding sites. In regions of MoS₂ free from surface contamination, the Pt atoms are localized in S vacancy sites and exhibit dynamic hopping to nearby vacancy sites driven by the energy supplied by the electron beam. However, in areas of MoS₂ contaminated with carbon surface layers, the Pt atoms appear at various positions with respect to the underlying MoS₂ lattice, including on top of Mo and in off-axis positions. These variations are due to the Pt bonding with the surrounding amorphous carbon layer, which disrupts the intrinsic Pt-MoS₂ interactions, leading to more varied positions. Density functional theory (DFT) calculations reveal that Pt atoms on the surface of MoS₂ have a small barrier for migration and are stabilized when bound to either a single or double sulfur vacancies. DFT calculations have been used to understand how the catalytic activity of the MoS₂ basal plane for hydrogen evolution reaction is influenced by Pt dopants by variation of the hydrogen adsorption free energy. This strong dependence of catalytic effect on interfacial configurations is shown to be common for a series of dopants, which may provide a means to create and optimize reaction centers

Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling

Structural Plasticity (SP) in the brain is a process that allows neuronal structure changes, in response to learning. Spiking Neural Networks (SNN) are an emerging form of artificial neural networks that uses brain-inspired techniques to learn. However, the application of SP in SNNs, its impact on overall learning and network behaviour is rarely explored. In the present study, we use an SNN with a single hidden layer, to apply SP in classifying Electroencephalography signals of two publicly available datasets. We considered classification accuracy as the learning capability and applied metaheuristics to derive the optimised number of neurons for the hidden layer along with other hyperparameters of the network. The optimised structure was then compared with overgrown and undergrown structures to compare the accuracy, stability, and behaviour of the network properties. Networks with SP yielded ~94% and ~92% accuracies in classifying wrist positions and mental states(stressed vs relaxed) respectively. The same SNN developed for mental state classification produced ~77% and ~73% accuracies in classifying arousal and valence. Moreover, the networks with SP demonstrated superior performance stability during iterative random initiations. Interestingly, these networks had a smaller number of inactive neurons and a preference for lowered neuron firing thresholds. This research highlights the importance of systematically selecting the hidden layer neurons over arbitrary settings, particularly for SNNs using Spike Time Dependent Plasticity learning and provides potential findings that may lead to the development of SP learning algorithms for SNNs

Observation of oscillatory relaxation in the Sn-terminated surface of epitaxial rock-salt SnSe {111}\{111\} topological crystalline insulator

Topological crystalline insulators have been recently predicted and observed in rock-salt structure SnSe $\{111\}$ thin films. Previous studies have suggested that the Se-terminated surface of this thin film with hydrogen passivation, has a reduced surface energy and is thus a preferred configuration. In this paper, synchrotron-based angle-resolved photoemission spectroscopy, along with density functional theory calculations, are used to demonstrate conclusively that a rock-salt SnSe $\{111\}$ thin film epitaxially-grown on \ce{Bi2Se3} has a stable Sn-terminated surface. These observations are supported by low energy electron diffraction (LEED) intensity-voltage measurements and dynamical LEED calculations, which further show that the Sn-terminated SnSe $\{111\}$ thin film has undergone a surface structural relaxation of the interlayer spacing between the Sn and Se atomic planes. In sharp contrast to the Se-terminated counterpart, the observed Dirac surface state in the Sn-terminated SnSe $\{111\}$ thin film is shown to yield a high Fermi velocity, $0.50\times10^6$m/s, which suggests a potential mechanism of engineering the Dirac surface state of topological materials by tuning the surface configuration.Comment: 12 pages, 13 figures, supplementary materials include

Shaping bursting by electrical coupling and noise

Gap-junctional coupling is an important way of communication between neurons and other excitable cells. Strong electrical coupling synchronizes activity across cell ensembles. Surprisingly, in the presence of noise synchronous oscillations generated by an electrically coupled network may differ qualitatively from the oscillations produced by uncoupled individual cells forming the network. A prominent example of such behavior is the synchronized bursting in islets of Langerhans formed by pancreatic \beta-cells, which in isolation are known to exhibit irregular spiking. At the heart of this intriguing phenomenon lies denoising, a remarkable ability of electrical coupling to diminish the effects of noise acting on individual cells. In this paper, we derive quantitative estimates characterizing denoising in electrically coupled networks of conductance-based models of square wave bursting cells. Our analysis reveals the interplay of the intrinsic properties of the individual cells and network topology and their respective contributions to this important effect. In particular, we show that networks on graphs with large algebraic connectivity or small total effective resistance are better equipped for implementing denoising. As a by-product of the analysis of denoising, we analytically estimate the rate with which trajectories converge to the synchronization subspace and the stability of the latter to random perturbations. These estimates reveal the role of the network topology in synchronization. The analysis is complemented by numerical simulations of electrically coupled conductance-based networks. Taken together, these results explain the mechanisms underlying synchronization and denoising in an important class of biological models

Improving Photoelectron Counting and Particle Identification in Scintillation Detectors with Bayesian Techniques

Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector.Comment: 16 pages, 16 figure

Psychosocial moderation of polygenic risk for cannabis involvement: the role of trauma exposure and frequency of religious service attendance

Cannabis use and disorders (CUD) are influenced by multiple genetic variants of small effect and by the psychosocial environment. However, this information has not been effectively incorporated into studies of gene-environment interaction (GxE). Polygenic risk scores (PRS) that aggregate the effects of genetic variants can aid in identifying the links between genetic risk and psychosocial factors. Using data from the Pasman et al. GWAS of cannabis use (meta-analysis of data from the International Cannabis Consortium and UK Biobank), we constructed PRS in the Collaborative Study on the Genetics of Alcoholism (COGA) participants of European (N: 7591) and African (N: 3359) ancestry. The primary analyses included only individuals of European ancestry, reflecting the ancestral composition of the discovery GWAS from which the PRS was derived. Secondary analyses included the African ancestry sample. Associations of PRS with cannabis use and DSM-5 CUD symptom count (CUDsx) and interactions with trauma exposure and frequency of religious service attendance were examined. Models were adjusted for sex, birth cohort, genotype array, and ancestry. Robustness models were adjusted for cross-term interactions. Higher PRS were associated with a greater likelihood of cannabis use and with CUDsx among participants of European ancestry (p < 0.05 and p < 0.1 thresholds, respectively). PRS only influenced cannabis use among those exposed to trauma (R2: 0.011 among the trauma exposed vs. R2: 0.002 in unexposed). PRS less consistently influenced cannabis use among those who attend religious services less frequently; PRS × religious service attendance effects were attenuated when cross-term interactions with ancestry and sex were included in the model. Polygenic liability to cannabis use was related to cannabis use and, less robustly, progression to symptoms of CUD. This study provides the first evidence of PRS × trauma for cannabis use and demonstrates that ignoring important aspects of the psychosocial environment may mask genetic influences on polygenic traits