In this paper, we present a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.

This is achieved by relying on integral images for image convolutions; by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor); and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard evaluation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF's strong performance.

/pdf/surf-speeded-up-robust-features-1fje09jteo.pdf

SURF: speeded up robust features

The study of decision making spans such varied fields as neuroscience, psychology, economics, statistics, political science, and computer science. Despite this diversity of applications, most decisions share common elements including deliberation and commitment. Here we evaluate recent progress in understanding how these basic elements of decision formation are implemented in the brain. We focus on simple decisions that can be studied in the laboratory but emphasize general principles likely to extend to other settings.

/pdf/the-neural-basis-of-decision-making-2p5agsty56.pdf

The Neural Basis of Decision Making

Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

/pdf/spiking-neuron-models-single-neurons-populations-plasticity-58gzrd6ih6.pdf

Spiking Neuron Models: Single Neurons, Populations, Plasticity

Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.

The Perception of the Visual World. By James J. Gibson. U.S.A.: Houghton Mifflin Company, 1950 (George Allen & Unwin, Ltd., London). Price 35s.

Neuronal Synchrony: A Versatile Code for the Definition of Relations?

The possibility has been explored that a subset of physiologically identifiable cells in the visual cortex is especially suited for the processing of stereoscopic depth information. First, characteristics of a disparity detector that would be useful for such processing were outlined. Then, a method was devised by which detailed binocular response data were obtained from cortical cells. In addition, a model of the disparity detector was developed that includes a plausible hierarchical arrangement of cortical cells. Data from the cells compare well with the requirements for the archetypal disparity detector and are in excellent agreement with the predictions of the model. These results demonstrate that a specific type of cortical neuron exhibits the desired characteristics of a disparity detector.

https://science.sciencemag.org/content/sci/249/4972/1037.full.pdf

Stereoscopic depth discrimination in the visual cortex: neurons ideally suited as disparity detectors

Human observers combine multiple sensory cues synergistically to achieve greater perceptual sensitivity, but little is known about the underlying neuronal mechanisms. We recorded the activity of neurons in the dorsal medial superior temporal (MSTd) area during a task in which trained monkeys combined visual and vestibular cues near-optimally to discriminate heading. During bimodal stimulation, MSTd neurons combined visual and vestibular inputs linearly with subadditive weights. Neurons with congruent heading preferences for visual and vestibular stimuli showed improvements in sensitivity that parallel behavioral effects. In contrast, neurons with opposite preferences showed diminished sensitivity under cue combination. Responses of congruent cells were more strongly correlated with monkeys' perceptual decisions than were responses of opposite cells, suggesting that the monkey monitored the activity of congruent cells to a greater extent during cue integration. These findings show that perceptual cue integration occurs in nonhuman primates and identify a population of neurons that may form its neural basis.

Neural correlates of multisensory cue integration in macaque MSTd

1. The classically defined receptive field of a visual neuron is the area of visual space over which the cell responds to visual stimuli. It is well established, however, that the discharge produced by an optimal stimulus can be modulated by the presence of additional stimuli that by themselves do not produce any response. This study examines inhibitory influences that originate from areas located outside of the classical (i.e., excitatory) receptive field. Previous work has shown that for some cells the response to a properly oriented bar of light becomes attenuated when the bar extends beyond the receptive field, a phenomenon known as end-inhibition (or length tuning). Analogously, it has been shown that increasing the number of cycles of a drifting grating stimulus may also inhibit the firing of some cells, an effect known as side-inhibition (or width tuning). Very little information is available, however, about the relationship between end- and side-inhibition. We have examined the spatial organization and tuning characteristics of these inhibitory effects by recording extracellularly from single neurons in the cat's striate cortex (Area 17). 2. For each cortical neuron, length and width tuning curves were obtained with the use of rectangular patches of drifting sinusoidal gratings that have variable length and width. Results from 82 cells show that the strengths of end- and side-inhibition tend to be correlated. Most cells that exhibit clear end-inhibition also show a similar degree of side-inhibition. For these cells, the excitatory receptive field is surrounded on all sides by inhibitory zones. Some cells exhibit only end- or side-inhibition, but not both. Data for 28 binocular cells show that length and width tuning curves for the dominant and nondominant eyes tend to be closely matched. 3. We also measured tuning characteristics of end- and side-inhibition. To obtain these data, the excitatory receptive field was stimulated with a grating patch having optimal orientation, spatial frequency, and size, whereas the end- or side-inhibitory regions were stimulated with patches of gratings that had a variable parameter (such as orientation). Results show that end- and side-inhibition tend to be strongest at the orientation and spatial frequency that yield maximal excitation. However, orientation and spatial frequency tuning curves for inhibition are considerably broader than those for excitation, suggesting that inhibition is mediated by a pool of neurons.(ABSTRACT TRUNCATED AT 400 WORDS)

Length and width tuning of neurons in the cat's primary visual cortex

https://www.cell.com/trends/neurosciences/pdf/0166-2236(95)94496-R.pdf

Receptive-field dynamics in the central visual pathways

1. Most studies of cortical neurons have focused on the spatial structure of receptive fields. For a more complete functional description of these neurons, it is necessary to consider receptive-field structure in the joint domain of space and time. We have studied the spatiotemporal receptive-field structure of 233 simple cells recorded from the striate cortex of adult cats and kittens at 4 and 8 wk postnatal. The dual goal of this study is to provide a detailed quantitative description of spatiotemporal receptive-field structure and to compare the developmental time courses of spatial and temporal response properties. 2. Spatiotemporal receptive-field profiles have been measured with the use of a reverse correlation method, in which we compute the cross-correlation between a neuron's response and a random sequence of small, briefly presented bright and dark stimuli. The receptive-field profiles of some simple cells are space-time separable, meaning that spatial and temporal response characteristics can be dissociated. Other cells have receptive-field profiles that are space-time inseparable. In these cases, a particular spatial location cannot be designated, unambiguously, as belonging to either an on or off subregion. However, separate on and off subregions may be clearly distinguished in the joint space-time domain. These subregions are generally tilted along an oblique axis. 3. Our observations show that spatial and temporal aspects of receptive-field structure mature with clearly different time courses. By 4 wk postnatal, the spatial symmetry and periodicity of simple-cell receptive fields have reached maturity. The spatial extent (or size) of these receptive fields is adult-like by 8 wk postnatal. In contrast, the response latency and time duration of spatiotemporal receptive fields do not mature until well beyond 8 wk postnatal. 4. By applying Fourier analysis to spatiotemporal receptive-field profiles, we have examined the postnatal development of spatial and temporal selectivity in the frequency domain. By 8 wk postnatal, spatial frequency tuning has clearly reached maturity. On the contrary, temporal frequency selectivity remains markedly immature at 8 wk. We have also examined the joint distribution of optimal spatial and temporal frequencies. From 4 wk postnatal until 8 wk postnatal, the range of optimal spatial frequencies increases substantially, whereas the range of optimal temporal frequencies remains largely unchanged. From 8 wk postnatal until adulthood, there is a large increase in optimal temporal frequencies for cells tuned to low spatial frequencies. For cells tuned to high spatial frequencies, the distribution of optimal temporal frequencies does not change much beyond 8 wk postnatal.(ABSTRACT TRUNCATED AT 400 WORDS)

Gregory C. DeAngelis

Papers

Stereoscopic depth discrimination in the visual cortex: neurons ideally suited as disparity detectors

Neural correlates of multisensory cue integration in macaque MSTd

Length and width tuning of neurons in the cat's primary visual cortex

Receptive-field dynamics in the central visual pathways

Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. I: General characteristics and postnatal development