Neuronal Correlates of the Set-Size Effect in Monkey Lateral Intraparietal Area

It has long been known that the brain is limited in the amount of sensory information that it can process at any given time. A well-known form of capacity limitation in vision is the set-size effect, whereby the time needed to find a target increases in the presence of distractors. The set-size effect implies that inputs from multiple objects interfere with each other, but the loci and mechanisms of this interference are unknown. Here we show that the set-size effect has a neural correlate in competitive visuo-visual interactions in the lateral intraparietal area, an area related to spatial attention and eye movements. Monkeys performed a covert visual search task in which they discriminated the orientation of a visual target surrounded by distractors. Neurons encoded target location, but responses associated with both target and distractors declined as a function of distractor number (set size). Firing rates associated with the target in the receptive field correlated with reaction time both within and across set sizes. The findings suggest that competitive visuo-visual interactions in areas related to spatial attention contribute to capacity limitations in visual searches

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

3D PML-FDTD simulation of ground penetrating radar on dispersive earth media

A 3D finite-difference time-domain simulation of ground penetrating radar (GPR) is described. The soil material is characterized by inhomogeneities, conductive loss and strong dispersion. The dispersion is modelled by a N-th order Lorentz model and implemented by recursive convolution. The Perfectly Matched Layer (PML) is used as an absorbing boundary condition (ABC). This formulation facilitates the parallelization of the code. A code is written for a 32 processor system. Almost linear speedup is observed. Results include the radargrams of buried objects.link_to_subscribed_fulltex

Parallel 3D PML-FDTD simulation of GPR on dispersive, inhomogeneous and conductive media

A 3D FDTD simulation of ground penetrating radar (GPR) is described. The soil material is characterized by inhomogeneities, conductive loss and strong dispersion. The dispersion is modelled by a N-th order Lorentz model and implemented by recursive convolution. The perfectly matched layer (PML) Is used as an absorbing boundary condition (ABC). This formulation facilitates the parallelization of the code. A code is written for a 32 processor system. Almost linear speedup is observed. Results include the radargrams of buried objects.link_to_subscribed_fulltex

Finite-difference time-domain simulation of ground penetrating radar on dispersive, inhomogeneous, and conductive soils

A three-dimensional (3-D) time-domain numerical scheme for simulation of ground penetrating radar (GPR) on dispersive and inhomogeneous soils with conductive loss is described. The finite-difference time-domain (FDTD) method is used to discretize the partial differential equations for time stepping of the electromagnetic fields. The soil dispersion is modeled by multiterm Lorentz and/or Debye models and incorporated into the FDTD scheme by using the piecewise-linear recursive convolution (PLRC) technique. The dispersive soil parameters are obtained by fitting the model to reported experimental data. The perfectly matched layer (PML) is extended to match dispersive media and used as an absorbing boundary condition to simulate an open space. Examples are given to verify the numerical solution and demonstrate its applications. The 3-D PML-PLRC-FDTD formulation facilitates the parallelization of the code. A version of the code is written for a 32-processor system, and an almost linear speedup is observed. © 1998 IEEE.link_to_subscribed_fulltex