Biomedical subjects

Rodney J Douglas

Publications and source records attributed to Rodney J Douglas.

10 recordsLinked to original sources

PubMed2006

Fast oscillations trigger bursts of action potentials in neocortical neurons in vitro: a quasi-white-noise analysis study.

PURPOSE: Recent evidence supports the importance of action potential bursts in physiological neural coding, as well as in pathological epileptogenesis. To better understand the temporal dynamics of neuronal input currents that trigger burst firing, we characterized spectral patterns of stimulation current that generate bursts of action potentials from regularly spiking neocortical neurons in vitro. METHODS: Sharp microelectrodes were used for intracellular recording and stimulation of cortical neurons in rat brain slices. Quasi-white-noise (0-2 kHz) and "chirp" sine wave currents of decreasing wavelength were applied to represent a broad spectrum of stimulation frequencies. Action potential-related averaging of the stimulation current variations preceding bursting was used to characterize stimulation current patterns more likely to result in a burst rather than a single-spike response. RESULTS: Bursts of action potentials were most reliably generated by a preceding series of > or = 2 positive current transients at 164+/-37 Hz of the quasi-white-noise, and to sine wave currents with frequencies greater than 90 Hz. The intraburst action potential rate was linearly related to the frequency of the input sine wave current. CONCLUSIONS: This study demonstrates that regularly spiking cortical neurons in vitro burst in response to fast oscillations of input currents. In the presence of positive cortical feedback loops, encoding input frequency in the intraburst action potential rate may be safer than producing a high-frequency regular output spike train. This leads to the experimentally testable and therapeutically important hypothesis that burst firing could be an antiepileptogenic and/or anti-ictogenic mechanism.

Action Potentials↗

PubMed2006

Neuromorphic walking gait control.

We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

Animals↗

PubMed2004

A quantitative map of the circuit of cat primary visual cortex.

We developed a quantitative description of the circuits formed in cat area 17 by estimating the "weight" of the projections between different neuronal types. To achieve this, we made three-dimensional reconstructions of 39 single neurons and thalamic afferents labeled with horseradish peroxidase during intracellular recordings in vivo. These neurons served as representatives of the different types and provided the morphometrical data about the laminar distribution of the dendritic trees and synaptic boutons and the number of synapses formed by a given type of neuron. Extensive searches of the literature provided the estimates of numbers of the different neuronal types and their distribution across the cortical layers. Applying the simplification that synapses between different cell types are made in proportion to the boutons and dendrites that those cell types contribute to the neuropil in a given layer, we were able to estimate the probable source and number of synapses made between neurons in the six layers. The predicted synaptic maps were quantitatively close to the estimates derived from the experimental electron microscopic studies for the case of the main sources of excitatory and inhibitory input to the spiny stellate cells, which form a major target of layer 4 afferents. The map of the whole cortical circuit shows that there are very few "strong" but many "weak" excitatory projections, each of which may involve only a few percentage of the total complement of excitatory synapses of a single neuron.

Afferent Pathways↗

PubMed2004

Axons in cat visual cortex are topologically self-similar.

The axonal arbors of the different types of neocortical and thalamic neurons appear highly dissimilar when viewed in conventional 2D reconstructions. Nevertheless, we have found that their one-dimensional metrics and topologies are surprisingly similar. To discover this, we analysed the axonal branching pattern of 39 neurons (23 spiny, 13 smooth and three thalamic axons) that were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The axons were completely reconstructed and translated into dendrograms. Topological, fractal and Horton-Strahler analyses indicated that axons of smooth and spiny neurons had similar complexity, length ratios (a measure of the relative increase in the length of collateral segments as the axon branches) and bifurcation ratios (a measure of the relative increase in the number of collateral segments as the axon branches). We show that a simple random branching model (Galton-Watson process) predicts with reasonable accuracy the bifurcation ratio, length ratio and collateral length distribution of the axonal arbors.

Animals↗

PubMed2004

Neuronal circuits of the neocortex.

We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.

Animals↗

PubMed2003

Environmentally mediated synergy between perception and behaviour in mobile robots.

The notion that behaviour influences perception seems self-evident, but the mechanism of their interaction is not known. Perception and behaviour are usually considered to be separate processes. In this view, perceptual learning constructs compact representations of sensory events, reflecting their statistical properties, independently of behavioural relevance. Behavioural learning, however, forms associations between perception and action, organized by reinforcement, without regard for the construction of perception. It is generally assumed that the interaction between these two processes is internal to the agent, and can be explained solely in terms of the neuronal substrate. Here we show, instead, that perception and behaviour can interact synergistically via the environment. Using simulated and real mobile robots, we demonstrate that perceptual learning directly supports behavioural learning and so promotes a progressive structuring of behaviour. This structuring leads to a systematic bias in input sampling, which directly affects the organization of the perceptual system. This external, environmentally mediated feedback matches the perceptual system to the emerging behavioural structure, so that the behaviour is stabilized.

Adaptation, Physiological↗

PubMed2003

Self-correction mechanism for path integration in a modular navigation system on the basis of an egocentric spatial map.

Classical Computer Science approaches to navigation by autonomous robots continue to make good progress. However, we have only a limited understanding of how navigation is implemented in the neural networks of animals, which still perform very much better in navigational tasks than robots. In this paper we explore the implementation of neural network based navigation in a simple robot. We use a modular navigation system that contains separate representations of visual input and the path integration process. These representations are combined to influence the behavior of a robot. Both representations are encoded within recurrent neuronal networks. The outputs of the representations are vectors of polar values that encode the location of the nearest object, or of a specific place in the environment. The robot manoeuvres in relation to these attended locations, in the context of its egocentric spatial map. During ego-motion towards a goal, the network representation of the goal moves in a counter-movement due to applied motor feedback. The robot's position is continuously compared against its visual input, and mismatches between the visually perceived goal position and its spatial representation are corrected.

Ego↗

PubMed2003

Design for a brain revisited: the neuromorphic design and functionality of the interactive space 'Ada'.

While much is now known about the operation and organisation of the brain at the neuronal and microcircuit level, we are still some way from understanding it as a complete system from the lowest to the highest levels of description. One way to gain such an integrative understanding of neural systems is to construct them. We have built the largest neuromorphic system yet known, an interactive space called 'Ada' that is able to interact with many people simultaneously using a wide variety of sensory and behavioural modalities. 'She' received 553,700 visitors over 5 months during the Swiss Expo.02 in 2002. In this paper we present the broad motivations, design and technologies behind Ada, and discuss the construction and analysis of the system.

Behavior↗

PubMed2002

Attentional recruitment of inter-areal recurrent networks for selective gain control.

There is strong anatomical and physiological evidence that neurons with large receptive fields located in higher visual areas are recurrently connected to neurons with smaller receptive fields in lower areas. We have previously described a minimal neuronal network architecture in which top-down attentional signals to large receptive field neurons can bias and selectively read out the bottom-up sensory information to small receptive field neurons (Hahnloser, Douglas, Mahowald, & Hepp, 1999). Here we study an enhanced model, where the role of attention is to recruit specific inter-areal feedback loops (e.g., drive neurons above firing threshold). We first illustrate the operation of recruitment on a simple example of visual stimulus selection. In the subsequent analysis, we find that attentional recruitment operates by dynamical modulation of signal amplification and response multistability. In particular, we find that attentional stimulus selection necessitates increased recruitment when the stimulus to be selected is of small contrast and of small distance away from distractor stimuli. The selectability of a low-contrast stimulus is dependent on the gain of attentional effects; for example, low-contrast stimuli can be selected only when attention enhances neural responses. However, the dependence of attentional selection on stimulus-distractor distance is not contingent on whether attention enhances or suppresses responses. The computational implications of attentional recruitment are that cortical circuits can behave as winner-take-all mechanisms of variable strength and can achieve close to optimal signal discrimination in the presence of external noise.

Animals↗

PubMedDate not supplied

Chance or design? Some specific considerations concerning synaptic boutons in cat visual cortex.

To understand the rules by which axons lay down their synaptic boutons we analyzed the linear bouton distributions in 39 neurons (23 spiny, 13 smooth) and 3 thalamic axons, which were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The variation of the total number of boutons and the total axonal length was large (789-7,912 boutons, 12-126 mm). The overall linear bouton density for smooth cells was higher than that of spiny cells and thalamic afferents (mean +/- sd, 110 +/- 21 and 78 +/- 27 boutons per mm of axonal length). The distribution of boutons varied according to their location on the tree. Distal axon collaterals (first and second order segments in Horton-Strahler ordering) of smooth neurons had a 3.5 times higher, spiny cells and thalamic afferents a 2 times higher bouton density compared to the higher order (more proximal) segments. The distribution of interbouton intervals was positively skewed and similar for cells of the same type. In most cases a gamma-distribution fitted well, but the distributions had a tendency to have a heavier tail. To a first approximation these bouton distributions are consistent with both diffuse and specific models of interneuronal connections. Quite simple rules can explain these distributions and the connections between the different classes of neurons.

Animals↗