We propose a model for the neuronal implementation of selective visual attention based on temporal correlation among groups of neurons. Neurons in primary visual cortex respond to visual stimuli with a Poisson distrib...
The localization and orientation to various novel or interesting events in the environment is a critical sensorimotor ability in all animals, predator or prey. In mammals, the superior colliculus (SC) plays a major ro...
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The localization and orientation to various novel or interesting events in the environment is a critical sensorimotor ability in all animals, predator or prey. In mammals, the superior colliculus (SC) plays a major ro...
The localization and orientation to various novel or interesting events in the environment is a critical sensorimotor ability in all animals, predator or prey. In mammals, the superior colliculus (SC) plays a major role in this behavior, the deeper layers exhibiting topographically mapped responses to visual, auditory, and somatosensory stimuli. Sensory information arriving from different modalities should then be represented in the same coordinate frame. Auditory cues, in particular, are thought to be computed in head-based coordinates which must then be transformed to retinal coordinates. In this paper, an analog VLSI implementation for auditory localization in the azimuthal plane is described which extends the architecture proposed for the barn owl to a primate eye movement system where further transformation is required. This transformation is intended to model the projection in primates from auditory cortical areas to the deeper layers of the primate superior colliculus. This system is interfaced with an analog VLSI-based saccadic eye movement system also being constructed in our laboratory.
作者：
BOWER, JM1. Division of Biology
Computation and Neural Systems Program California Institute of Technology 91125 Pasadena CA
During learning of overlapping input patterns in an associative memory, recall of previously stored patterns can interfere with the learning of new patterns. Most associative memory models avoid this difficulty by ign...
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During learning of overlapping input patterns in an associative memory, recall of previously stored patterns can interfere with the learning of new patterns. Most associative memory models avoid this difficulty by ignoring the effect of previously modified connections during learning, by clamping network activity to the patterns to be learned. Through the interaction of experimental and modeling techniques, we now have evidence to suggest that a somewhat analogous approach may have been taken by biology within the olfactory cerebral cortex. Specifically we have recently discovered that the naturally occurring neuromodulator acetylcholine produces a variety of effects on cortical cells and circuits which, when taken together, can prevent memory interference in a biologically realistic memory model. Further, it has been demonstrated that these biological mechanisms can actually improve the memory storage performance of previously published abstract ''neural network'' associative memory models.
We propose a model for the neuronal implementation of selective visual attention based on the temporal structure of neuronal activity. In particular, we set out to explain the electrophysiological data from areas V4 a...
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We propose a model for the neuronal implementation of selective visual attention based on the temporal structure of neuronal activity. In particular, we set out to explain the electrophysiological data from areas V4 and IT in monkey cortex of Moran and Desimone [(1985) Science, 229, 782-784] using the ''temporal tagging'' hypothesis of Crick and Koch [(1990a) Cold Spring Harbor Symposiums in Quantitative Biology, LV, 953-962;(1990b) Seminars in the neurosciences (pp. 1-36)]. Neurons in primary visual cortex respond to visual stimuli with a Poisson distributed spike train with an appropriate, stimulus-dependent mean firing rate. The firing rate of neurons whose receptive fields overlap with the ''focus of attention'' is modulated with a periodic function in the 40 Hz range, such that their mean firing rate is identical to the mean firing rate of neurons in ''non-attended'' areas. This modulation is detected by inhibitory interneurons in V4 and is used to suppress the response of V4 cells associated with non-attended visual stimuli. Using very simple single-cell models, we obtain quantitative agreement with Moran and Desimone's (1985) experiments.
High-frequency oscillations in the 40-Hz range are the Rosetta stone of the brain and play a crucial role in figure-ground segmentation, perception and even consciousness. A string of publications by R. R. Llinas a...
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High-frequency oscillations in the 40-Hz range are the Rosetta stone of the brain and play a crucial role in figure-ground segmentation, perception and even consciousness. A string of publications by R. R. Llinas and colleagues concerning 40-Hz oscillatory activity throughout the cortex is examined.
Signal processing and classification algorithms often have limited applicability resulting from an inaccurate model of the signal's underlying structure. We present here an efficient, Bayesian algorithm for modeli...
Signal processing and classification algorithms often have limited applicability resulting from an inaccurate model of the signal's underlying structure. We present here an efficient, Bayesian algorithm for modeling a signal composed of the superposition of brief, Poisson-distributed functions. This methodology is applied to the specific problem of modeling and classifying extracellular neural waveforms which are composed of a superposition of an unknown number of action potentials (APs). Previous approaches have had limited success due largely to the problems of determining the spike shapes, deciding how many are shapes distinct, and decomposing overlapping APs. A Bayesian solution to each of these problems is obtained by inferring a probabilistic model of the waveform. This approach quantifies the uncertainty of the form and number of the inferred AP shapes and is used to obtain an efficient method for decomposing complex overlaps. This algorithm can extract many times more information than previous methods and facilitates the extracellular investigation of neuronal classes and of interactions within neuronal circuits.
In an effort to understand saccadic eye movements and their relation to visual attention and other forms of eye movements, we - in collaboration with a number of other laboratories - are carrying out a large-scale eff...
In an effort to understand saccadic eye movements and their relation to visual attention and other forms of eye movements, we - in collaboration with a number of other laboratories - are carrying out a large-scale effort to design and build a complete primate oculomotor system using analog CMOS VLSI technology. Using this technology, a low power, compact, multi-chip system has been built which works in real-time using real-world visual inputs. We describe in this paper the performance of an early version of such a system including a 1-D array of photoreceptors mimicking the retina, a circuit computing the mean location of activity representing the superior colliculus, a saccadic burst generator, and a one degree-of-freedom rotational platform which models the dynamic properties of the primate oculomotor plant.
Intradendritic electrophysiological recordings reveal a bewildering repertoire of complex electrical spikes and plateaus that are difficult to reconcile with conventional notions of neuronal function. In this paper we...
Intradendritic electrophysiological recordings reveal a bewildering repertoire of complex electrical spikes and plateaus that are difficult to reconcile with conventional notions of neuronal function. In this paper we argue that such dendritic events are just an exuberant expression of a more important mechanism - a proportional current amplifier whose primary task is to offset electrotonic losses. Using the example of functionally important synaptic inputs to the superficial layers of an anatomically and electrophysiologically reconstructed layer 5 pyramidal neuron, we derive and simulate the properties of conductances that linearize and amplify distal synaptic input current in a graded manner. The amplification depends on a potassium conductance in the apical tuft and calcium conductances in the apical trunk.
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