Behavior of Nanosilica Filled Epoxies

Epoxy resins filled with silica are used in a wide array of applications. When used in microelectronic packaging, chiefly as an underfill encaplsulant, it is critical that such epoxy resins possess low viscosity as well as high fracture toughness. Traditionally, micron-size silica fillers are used but there is much interest in the use of nanometer size fillers as the feature size on silicon chips decreases. In this study, the rheological behavior of an epoxy resin containing nanosilica fillers was characterized in steady state shear using a Rheometerics ARES rheometer equipped with a Couette fixture. Two types of nanosilica particles were examined as potential fillers(22nm and 168nm in diameter) as well as mixtures of both. Interestingly, the unimodal formulations exhibited reduced viscosities larger than those predicted from Einstein\u27s equation, thus suggesting significant interactions between particles. Note that shear rate studies did not reveal the presence of a yield stress nor structure formation. Bimodal mixtures of nanosilica were also explored as a possible means to reduce the viscosity for a given nanosilica content. Initial results look promising even though the nanosilica content is lower than what is traditionally used in these systems.https://preserve.lehigh.edu/undergrad-scholarship-freed-posters/1023/thumbnail.jp

Decoding the activity of neuronal populations in macaque primary visual cortex

Visual function depends on the accuracy of signals carried by visual cortical neurons. Combining information across neurons should improve this accuracy because single neuron activity is variable. We examined the reliability of information inferred from populations of simultaneously recorded neurons in macaque primary visual cortex. We considered a decoding framework that computes the likelihood of visual stimuli from a pattern of population activity by linearly combining neuronal responses and tested this framework for orientation estimation and discrimination. We derived a simple parametric decoder assuming neuronal independence and a more sophisticated empirical decoder that learned the structure of the measured neuronal response distributions, including their correlated variability. The empirical decoder used the structure of these response distributions to perform better than its parametric variant, indicating that their structure contains critical information for sensory decoding. These results show how neuronal responses can best be used to inform perceptual decision-making

Neuronal Adaptation to Visual Motion in Area MT of the Macaque

AbstractThe responsivity of primary sensory cortical neurons is reduced following prolonged adaptation, but such adaptation has been little studied in higher sensory areas. Adaptation to visual motion has strong perceptual effects, so we studied the effect of prolonged stimulation on neuronal responsivity in the macaque's area MT, a cortical area whose importance to visual motion perception is well established. We adapted MT neurons with sinusoidal gratings drifting in the preferred or null direction. Preferred adaptation reduced the responsiveness of MT cells, primarily by changing their contrast gain, and this effect was spatially specific within the receptive field. Null adaptation reduced the ability of null gratings to inhibit the response to a simultaneously presented preferred stimulus. While both preferred and null adaptation alter MT responses, these effects probably do not occur in MT neurons but are likely to reflect adaptation-induced changes in contrast gain earlier in the visual pathway

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure

How do stimulus-dependent correlations between V1 neurons affect neural coding?

Nearby neurons in the visual cortex often partially synchronize their spiking activity. Despite the widespread observation of this phenomenon, its importance for visual coding and perception remains to be uncovered. We used information theory to study the coding of the contrast and direction of motion of visual stimuli by pairs of simultaneously recorded neurons in the macaque primary visual cortex. Direction coding showed weak synergistic effects at short timescales, trailing off to informational independence at long timescales. In comparison, contrast coding was dominated by redundancy due to the similarity in contrast tuning curves.Facultad de Ciencias Exacta

The role of correlations in direction and contrast coding in the primary visual cortex

The spiking activity of nearby cortical neurons is not independent. Numerous studies have explored the importance of this correlated responsivity for visual coding and perception, often by comparing the information conveyed by pairs of simultaneously recorded neurons with the sum of information provided by the respective individual cells. Pairwise responses typically provide slightly more information sothat encodingis weakly synergistic. The simple comparison between pairwise and summedindividual responses conflates several forms of correlation, however, making it impossible to judge the relative importance of synchronous spiking, basic tuning properties, and stimulus-independent and stimulus-dependent correlation. We have applied an information theoretic approach to this question, using the responses of pairs of neurons to drifting sinusoidal gratings of different directions and contrasts that have been recorded inthe primary visual cortex of anesthetized macaque monkeys. Our approach allows usto break downthe information provided by pairs of neurons into a number of components. This analysis reveals that, although synchrony is prevalent and informative, the additional information it provides frequently is offset by the redundancy arising from the similar tuning properties of the two cells. Thus coding is approximately independent with weak synergy or redundancy arising, depending on the similarity in tuning and the temporal precision of the analysis. We suggest that this would allow cortical circuits to enjoy the stability provided by having similarly tuned neurons without suffering the penalty of redundancy, because the associated information transmission deficit is compensated for by stimulus-dependent synchrony.Facultad de Ciencias Exacta

N-representability and stationarity in time-dependent density functional theory

To construct an N-representable time-dependent density-functional theory, a generalization to the time domain of the Levy-Lieb (LL) constrained search algorithm is required. That the action is only stationary in the Dirac-Frenkel variational principle eliminates the possibility of basing the search on the action itself. Instead, we use the norm of the partial functional derivative of the action in the Hilbert space of the wave functions in place of the energy of the LL search. The electron densities entering the formalism are $N$-representable, and the resulting universal action functional has a unique stationary point in the density at that corresponding to the solution of the Schr\"{o}dinger equation. The original Runge-Gross (RG) formulation is subsumed within the new formalism. Concerns in the literature about the meaning of the functional derivatives and the internal consistency of the RG formulation are allayed by clarifying the nature of the functional derivatives entering the formalism.Comment: 9 pages, 0 figures, Phys. Rev. A accepted. Introduction was expanded, subsections reorganized, appendix and new references adde