Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

The measurement of meaning

One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation involving the posterior density. In this article, we review variational inference (VI), a method from machine learning that approximates probability densities through optimization. VI has been used in many applications and tends to be faster than classical methods, such as Markov chain Monte Carlo sampling. The idea behind VI is to first posit a family of densities and then to find a member of that family which is close to the target density. Closeness is measured by Kullback–Leibler divergence. We review the ideas behind mean-field variational inference, discuss the special case of VI applied to exponential family models, present a full example with a Bayesian mixture of Gaussians, and derive a variant that uses stochastic optimization to scale up to massive data...

Variational Inference: A Review for Statisticians

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

Covertly directing visual attention toward a spatial location in the absence of visual stimulation enhances future visual processing at the attended position. The neuronal correlates of these attention shifts involve modulation of neuronal "baseline" activity in early visual areas, presumably through top-down control from higher-order attentional systems. We used electroencephalography to study the largely unknown relationship between these neuronal modulations and behavioral outcome in an attention orienting paradigm. Covert visuospatial attention shifts to either a left or right peripheral position in the absence of visual stimulation resulted in differential modulations of oscillatory alpha-band (8-14 Hz) activity over left versus right posterior sites. These changes were driven by varying degrees of alpha-decreases being maximal contralateral to the attended position. When expressed as a lateralization index, these alpha-changes differed significantly between attention conditions, with negative values (alpha_right < alpha_left) indexing leftward and more positive values (alpha_left < or = alpha_right) indexing rightward attention. Moreover, this index appeared deterministic for processing of forthcoming visual targets. Collapsed over trials, there was an advantage for left target processing in accordance with an overall negative bias in alpha-index values. Across trials, left targets were detected most rapidly when preceded by negative index values. Detection of right targets was fastest in trials with most positive values. Our data indicate that collateral modulations of posterior alpha-activity, the momentary bias of visuospatial attention, and imminent visual processing are linked. They suggest that the momentary direction of attention, predicting spatial biases in imminent visual processing, can be estimated from a lateralization index of posterior alpha-activity.

https://www.jneurosci.org/content/jneuro/26/37/9494.full.pdf

α-Band Electroencephalographic Activity over Occipital Cortex Indexes Visuospatial Attention Bias and Predicts Visual Target Detection

https://www.cs.helsinki.fi/u/ahyvarin/teaching/niseminar/papers/MEG_variationalbayes.pdf

Hierarchical Bayesian estimation for MEG inverse problem.

Attentional modulation of oscillatory activity in human visual cortex

Transformation from image-based to perceptual representation of materials along the human ventral visual pathway.

Attentional shifts towards an expected visual target alter the level of alpha-band oscillatory activity in the human calcarine cortex

For more than a century, the process of stabilization has been a central issue in the research of learning and memory. Namely, after a skill or memory is acquired, it must be consolidated before it becomes resistant to disruption by subsequent learning. Although it is clear that there are many cases in which learning can be disrupted, it is unclear when learning something new disrupts what has already been learned. Herein, we provide two answers to this question with the demonstration that perceptual learning of a visual stimulus disrupts or interferes with the consolidation of a previously learned visual stimulus. In this study, we trained subjects on two different hyperacuity tasks and determined whether learning of the second task disrupted that of the first. We first show that disruption of learning occurs between visual stimuli presented at the same orientation in the same retinotopic location but not for the same stimuli presented at retinotopically disparate locations or different orientations at the same location. Second, we show that disruption from stimuli in the same retinotopic location is ameliorated if the subjects wait for 1 h before training on the second task. These results indicate that disruption, at least in visual learning, is specific to features of the tasks and that a temporal delay of 1 h can stabilize visual learning. This research shows that visual learning is susceptible to disruption and elucidates the processes by which the brain can consolidate learning and thus protect what is learned from being overwritten.

https://www.pnas.org/content/pnas/102/41/14895.full.pdf

Naokazu Goda

Papers

Hierarchical Bayesian estimation for MEG inverse problem.

Attentional modulation of oscillatory activity in human visual cortex

Transformation from image-based to perceptual representation of materials along the human ventral visual pathway.

Attentional shifts towards an expected visual target alter the level of alpha-band oscillatory activity in the human calcarine cortex

Task-specific disruption of perceptual learning.