Biomedical subjects

D H Ballard

Publications and source records attributed to D H Ballard.

12 recordsLinked to original sources

PubMed2000

A virtual reality testbed for brain-computer interface research.

Virtual reality promises to extend the realm of possible brain-computer interface (BCI) prototypes. Most of the work using electroencephalograph (EEG) signals in VR has focussed on brain-body actuated control, where biological signals from the body as well as the brain are used. We show that when subjects are allowed to move and act normally in an immersive virtual environment, cognitive evoked potential signals can still be obtained and used reliably. A single trial accuracy average of 85% for recognizing the differences between evoked potentials at red and yellow stop lights will be presented and future directions discussed.

Adult↗

PubMed2000

Spatio-temporal organization of behavior.

One of the most widely used terms in the study of human performance is attention. Yet it can also be argued that it is one of the most confusing and misunderstood. Huge variations in performance, from not noticing large changes in images or natural situations, to differences of tens of milliseconds have all been described as attentional effects. We argue that the large disparity in results can be more easily understood in the context of a fairly complete model of human performance that describes the execution of a set of complex natural tasks via a collection of visual routines that extract crucial information from the optical array. The description of visual routines is hierarchical. At the most abstract level, a scheduler must pick a small set of programs for the current tasks. Each program contains steps which are keyed to information in the scene. This is extracted by visual routines which run during a single fixation and extract pertinent information. The library of routines themselves are designed to execute quickly, but their actual performance depends on signal-to-noise characteristics of the imaged scene. The hierarchical description of behavior shows that questions about attention make sense in the context of the descriptive level in which they are embedded. We illustrate these principles with examples of driving behaviors.

Attention↗

PubMed1999

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.

We describe a model of visual processing in which feedback connections from a higher- to a lower-order visual cortical area carry predictions of lower-level neural activities, whereas the feedforward connections carry the residual errors between the predictions and the actual lower-level activities. When exposed to natural images, a hierarchical network of model neurons implementing such a model developed simple-cell-like receptive fields. A subset of neurons responsible for carrying the residual errors showed endstopping and other extra-classical receptive-field effects. These results suggest that rather than being exclusively feedforward phenomena, nonclassical surround effects in the visual cortex may also result from cortico-cortical feedback as a consequence of the visual system using an efficient hierarchical strategy for encoding natural images.

Feedback↗

PubMed1998

Task constraints in visual working memory.

This paper examines the nature of visual representations that direct ongoing performance in sensorimotor tasks. Performance of such natural tasks requires relating visual information from different gaze positions. To explore this we used the technique of making task relevant display changes during saccadic eye movements. Subjects copied a pattern of colored blocks on a computer monitor, using the mouse to drag the blocks across the screen. Eye position was monitored using a dual-purkinje eye tracker, and the color of blocks in the pattern was changed at different points in task performance. When the target of the saccade changed color during the saccade, the duration of fixations on the model pattern increased, depending on the point in the task that the change was made. Thus different fixations on the same visual stimulus served a different purpose. The results also indicated that the visual information that is retained across successive fixations depends on moment by moment task demands. This is consistent with previous suggestions that visual representations are limited and task dependent. Changes in blocks in addition to the saccade target led to greater increases in fixation duration. This indicated that some global aspect of the pattern was retained across different fixations. Fixation durations revealed effects of the display changes that were not revealed in perceptual report. This can be understood by distinguishing between processes that operate at different levels of description and different time scales. Our conscious experience of the world may reflect events over a longer time scale than those underlying the substructure of the perceptuo-motor machinery.

Color Perception↗

PubMed1998

Development of localized oriented receptive fields by learning a translation-invariant code for natural images.

Neurons in the mammalian primary visual cortex are known to possess spatially localized, oriented receptive fields. It has previously been suggested that these distinctive properties may reflect an efficient image encoding strategy based on maximizing the sparseness of the distribution of output neuronal activities or alternately, extracting the independent components of natural image ensembles. Here, we show that a strategy for transformation-invariant coding of images based on a first-order Taylor series expansion of an image also causes localized, oriented receptive fields to be learned from natural image inputs. These receptive fields, which approximate localized first-order differential operators at various orientations, allow a pair of cooperating neural networks, one estimating object identity ('what') and the other estimating object transformations ('where'), to simultaneously recognize an object and estimate its pose by jointly maximizing the a posteriori probability of generating the observed visual data. We provide experimental results demonstrating the ability of such networks to factor retinal stimuli into object-centred features and object-invariant transformation estimates.

Animals↗

PubMed1997

Dynamic model of visual recognition predicts neural response properties in the visual cortex.

The responses of visual cortical neurons during fixation tasks can be significantly modulated by stimuli from beyond the classical receptive field. Modulatory effects in neural responses have also been recently reported in a task where a monkey freely views a natural scene. In this article, we describe a hierarchical network model of visual recognition that explains these experimental observations by using a form of the extended Kalman filter as given by the minimum description length (MDL) principle. The model dynamically combines input-driven bottom-up signals with expectation-driven top-down signals to predict current recognition state. Synaptic weights in the model are adapted in a Hebbian manner according to a learning rule also derived from the MDL principle. The resulting prediction-learning scheme can be viewed as implementing a form of expectation-maximization (EM) algorithm. The architecture of the model posits an active computational role of the reciprocal connections between adjoining visual cortical areas in determining neural response properties. In particular, the model demonstrates the possible role of feedback from higher cortical areas in mediating neurophysiological effects due to stimuli from beyond the classical receptive field. Simulations of the model are provided that help explain the experimental observations regarding neural responses in both free viewing and fixation conditions.

Animals↗

PubMed1997

Learning-dependent synaptic modifications in the cerebellar cortex of the adult rat persist for at least four weeks.

Several experiments have demonstrated increased synapse number within the cerebellar cortex in association with motor skill learning but not with motor activity alone. The persistence of these synaptic changes in the absence of continued training was examined in the present experiment. Adult female rats were randomly allocated to either an acrobatic condition (AC) or a motor activity condition (MC). The AC animals were trained to traverse a complex series of obstacles, and each AC animal was pair-matched with an MC animal that traversed an obstacle-free runway. These animals were further assigned to one of three training conditions. Animals in the EARLY condition were trained for 10 consecutive days before being killed, animals in the DELAY, condition received the same 10 d of training followed by a 28 d period without training, and animals in the CONTINUOUS condition were trained for the entire 38 d. Unbiased stereological techniques were used to obtain estimates of the number of synapses per Purkinje cell within the cerebellar paramedian lobule. Results showed the AC animals to have significantly more synapses per Purkinje cell than the MC animals in all three training conditions. There were no differences in the number of synapses per Purkinje cell among the EARLY, DELAY, and CONTINUOUS conditions. These data demonstrate that both the motor skills and the increases in synapse number presumed to support them persist in the absence of continued training.

Animals↗

PubMed1997

Deictic codes for the embodiment of cognition.

To describe phenomena that occur at different time scales, computational models of the brain must incorporate different levels of abstraction. At time scales of approximately 1/3 of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level--more abstract than that used to capture natural phenomena but less abstract than what is traditionally used to study high-level cognitive processes such as reasoning. At this "embodiment level," the constraints of the physical system determine the nature of cognitive operations. The key synergy is that at time scales of about 1/3 of a second, the natural sequentiality of body movements can be matched to the natural computational economies of sequential decision systems through a system of implicit reference called deictic in which pointing movements are used to bind objects in the world to cognitive programs. This target article focuses on how deictic binding make it possible to perform natural tasks. Deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. One of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements.

Brain↗

PubMed1996

Goal-directed arm movements change eye-head coordination.

We compared the head movements accompanying gaze shifts while our subjects executed different manual operations, requiring gaze shifts of about 30 degrees. The different tasks yielded different latencies between gaze shifts and hand movements, and different maximum velocities of the hand. These changes in eye-hand coordination had a clear effect on eye-head coordination: the latencies and maximum velocities of head and hand were correlated. The same correlation between movements of the head and hand was also found within a task. Therefore, the changes in eye-head coordination are not caused by changes in the strategy of the subjects. We conclude that head movements and saccades during gaze shifts are not based on the same command: head movements depend both on the actual saccade and on possible future gaze shifts.

Arm↗

PubMed1992

Hand-eye coordination during sequential tasks.

The small angle subtended by the human fovea places a premium on the ability to quickly and accurately direct the gaze to targets of interest. Thus the resultant saccadic eye fixations are a very instructive behaviour, revealing much about the underlying cognitive mechanisms that guide them. Of particular interest are the eye fixations used in hand-eye coordination. Such coordination has been extensively studied for single movements from a source location to a target location. In contrast, we have studied multiple fixations where the sources and targets are a function of a task and chosen dynamically by the subject according to task requirements. The task chosen is a copying task: subjects must copy a figure made up of contiguous coloured blocks as fast as possible. The main observation is that although eye fixations are used for the terminal phase of hand movements, they are used for other tasks before and after that phase. The analysis of the spatial and temporal details of these fixations suggests that the underlying decision process that moves the eyes leaves key decisions until just before they are required.

Eye Movements↗

PubMed1987

Interpolation coding: a representation for numbers in neural models.

A central task of perception can be defined as one of computing hierarchies of invariants. One way of representing such invariants in intermediate levels of abstraction in this hierarchy is to use discrete units. These have been termed value units. A problem with such an encoding is that there has not been a good way to represent accurate numerical quantities using these units. This paper remedies the deficiency by describing a scheme that interpolates values between units representing fixed numerical quantities. The scheme has nice properties: it extends across functional mappings and it allows different sources of evidence to be combined.

Animals↗

PubMedDate not supplied

Parallel visual computation.

The functional abilities and parallel architecture of the human visual system are a rich source of ideas about visual processing. Any visual task that we can perform quickly and effortlessly is likely to have a computational solution using a parallel algorithm. Recently, several such parallel algorithms have been found that exploit information implicit in an image to compute intrinsic properties of surfaces, such as surface orientation, reflectance and depth. These algorithms require a computational architecture that has similarities to that of visual cortex in primates.

Computers↗