26 research outputs found
Inverse Current Source Density Method in Two Dimensions: Inferring Neural Activation from Multielectrode Recordings
The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets
Optimal Control of Saccades by Spatial-Temporal Activity Patterns in the Monkey Superior Colliculus
A major challenge in computational neurobiology is to understand how populations of noisy, broadly-tuned neurons produce accurate goal-directed actions such as saccades. Saccades are high-velocity eye movements that have stereotyped, nonlinear kinematics; their duration increases with amplitude, while peak eye-velocity saturates for large saccades. Recent theories suggest that these characteristics reflect a deliberate strategy that optimizes a speed-accuracy tradeoff in the presence of signal-dependent noise in the neural control signals. Here we argue that the midbrain superior colliculus (SC), a key sensorimotor interface that contains a topographically-organized map of saccade vectors, is in an ideal position to implement such an optimization principle. Most models attribute the nonlinear saccade kinematics to saturation in the brainstem pulse generator downstream from the SC. However, there is little data to support this assumption. We now present new neurophysiological evidence for an alternative scheme, which proposes that these properties reside in the spatial-temporal dynamics of SC activity. As predicted by this scheme, we found a remarkably systematic organization in the burst properties of saccade-related neurons along the rostral-to-caudal (i.e., amplitude-coding) dimension of the SC motor map: peak firing-rates systematically decrease for cells encoding larger saccades, while burst durations and skewness increase, suggesting that this spatial gradient underlies the increase in duration and skewness of the eye velocity profiles with amplitude. We also show that all neurons in the recruited population synchronize their burst profiles, indicating that the burst-timing of each cell is determined by the planned saccade vector in which it participates, rather than by its anatomical location. Together with the observation that saccade-related SC cells indeed show signal-dependent noise, this precisely tuned organization of SC burst activity strongly supports the notion of an optimal motor-control principle embedded in the SC motor map as it fully accounts for the straight trajectories and kinematic nonlinearity of saccades
A spiking neural network model of the midbrain superior colliculus that generates saccadic motor commands
Exploring the Superior Colliculus In Vitro
The superior colliculus plays an important role in the translation of sensory signals that encode the location of objects in space into motor signals that encode vectors of the shifts in gaze direction called saccades. Since the late 1990s, our two laboratories have been applying whole cell patch-clamp techniques to in vitro slice preparations of rodent superior colliculus to analyze the structure and function of its circuitry at the cellular level. This review describes the results of these experiments and discusses their contributions to our understanding of the mechanisms responsible for sensorimotor integration in the superior colliculus. The experiments analyze vertical interactions between its superficial visuosensory and intermediate premotor layers and propose how they might contribute to express saccades and to saccadic suppression. They also compare and contrast the circuitry within each of these layers and propose how this circuitry might contribute to the selection of the targets for saccades and to the build-up of the premotor commands that precede saccades. Experiments also explore in vitro the roles of extrinsic inputs to the superior colliculus, including cholinergic inputs from the parabigeminal and parabrachial nuclei and GABAergic inputs from the substantia nigra pars reticulata, in modulating the activity of the collicular circuitry. The results extend and clarify our understanding of the multiple roles the superior colliculus plays in sensorimotor integration