Search results for "Quantitative Biology - Neurons and Cognition"
showing 10 items of 23 documents
Mapping brain activity with flexible graphene micro-transistors
2016
arXiv:1611.05693v1.-- et al.
Quantum field inspired model of decision making: Asymptotic stabilization of belief state via interaction with surrounding mental environment
2018
This paper is devoted to justification of quantum-like models of the process of decision making based on the theory of open quantum systems, i.e. decision making is considered as decoherence. This process is modeled as interaction of a decision maker, Alice, with a mental (information) environment ${\cal R}$ surrounding her. Such an interaction generates "dissipation of uncertainty" from Alice's belief-state $\rho(t)$ into ${\cal R}$ and asymptotic stabilization of $\rho(t)$ to a steady belief-state. The latter is treated as the decision state. Mathematically the problem under study is about finding constraints on ${\cal R}$ guaranteeing such stabilization. We found a partial solution of th…
Derivatives and inverse of a linear-nonlinear multi-layer spatial vision model
2016
Linear-nonlinear transforms are interesting in vision science because they are key in modeling a number of perceptual experiences such as color, motion or spatial texture. Here we first show that a number of issues in vision may be addressed through an analytic expression of the Jacobian of these linear-nonlinear transforms. The particular model analyzed afterwards (an extension of [Malo & Simoncelli SPIE 2015]) is illustrative because it consists of a cascade of standard linear-nonlinear modules. Each module roughly corresponds to a known psychophysical mechanism: (1) linear spectral integration and nonlinear brightness-from-luminance computation, (2) linear pooling of local brightness…
Appropriate kernels for Divisive Normalization explained by Wilson-Cowan equations
2018
The interaction between wavelet-like sensors in Divisive Normalization is classically described through Gaussian kernels that decay with spatial distance, angular distance and frequency distance. However, simultaneous explanation of (a) distortion perception in natural image databases and (b) contrast perception of artificial stimuli requires very specific modifications in classical Divisive Normalization. First, the wavelet response has to be high-pass filtered before the Gaussian interaction is applied. Then, distinct weights per subband are also required after the Gaussian interaction. In summary, the classical Gaussian kernel has to be left- and right-multiplied by two extra diagonal ma…
On Contextuality in Behavioral Data
2015
Dzhafarov, Zhang, and Kujala (Phil. Trans. Roy. Soc. A 374, 20150099) reviewed several behavioral data sets imitating the formal design of the quantum-mechanical contextuality experiments. The conclusion was that none of these data sets exhibited contextuality if understood in the generalized sense proposed in Dzhafarov, Kujala, and Larsson (Found. Phys. 7, 762-782, 2015), while the traditional definition of contextuality does not apply to these data because they violate the condition of consistent connectedness (also known as marginal selectivity, no-signaling condition, no-disturbance principle, etc.). In this paper we clarify the relationship between (in)consistent connectedness and (non…
Multiscale Granger causality analysis by à trous wavelet transform
2017
Since interactions in neural systems occur across multiple temporal scales, it is likely that information flow will exhibit a multiscale structure, thus requiring a multiscale generalization of classical temporal precedence causality analysis like Granger's approach. However, the computation of multiscale measures of information dynamics is complicated by theoretical and practical issues such as filtering and undersampling: to overcome these problems, we propose a wavelet-based approach for multiscale Granger causality (GC) analysis, which is characterized by the following properties: (i) only the candidate driver variable is wavelet transformed (ii) the decomposition is performed using the…
An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains
2021
Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…
The Hilbert transform of horizontal gaze position during natural image classification by saccades
2006
Eye movements are a behavioral response that can be involved in tasks as complicated as natural image classification. This report confirms that pro- and anti-saccades can be used by a volunteer to designate target (animal) or non-target images that were centered 16 degrees off the fixation point. With more than 86% correct responses, 11 participants responded to targets in 470 milliseconds on average, starting as quick as 245 milliseconds. Furthermore, tracking the gaze position is considered a powerful method in the studies of recognition as the saccade response times, ocular dynamics and the events around the response time can be calculated from the data sampled 240 times per second. The …
Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis
2016
Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…
Disentangling the Link Between Image Statistics and Human Perception
2023
In the 1950s Horace Barlow and Fred Attneave suggested a connection between sensory systems and how they are adapted to the environment: early vision evolved to maximise the information it conveys about incoming signals. Following Shannon's definition, this information was described using the probability of the images taken from natural scenes. Previously, direct accurate predictions of image probabilities were not possible due to computational limitations. Despite the exploration of this idea being indirect, mainly based on oversimplified models of the image density or on system design methods, these methods had success in reproducing a wide range of physiological and psychophysical phenom…