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PubMed1971

Memory grows.

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Cybernetics↗
PubMed1984

Simulation of vestibular semicircular canal responses during righting movements of a freely falling cat.

The righting maneuver of a freely falling cat was filmed at 1000 pictures per second, and the head position about the roll axis was digitized from each film frame using a graphics input tablet. The head angular velocity and acceleration were computed from the roll axis position trajectory. Head acceleration trajectories approximated two periods of a damped sinusoid at a frequency of 26 Hz. Head acceleration peak amplitudes exceeded 120,000 deg/s2. These trajectories were used as stimuli for the horizontal semicircular canals in a computer simulation of first-order afferent responses during the fall. Linear system afferent response dynamics, characterized in a previous study of the cat horizontal canal using pseudorandom rotations, provided the basis for linear predictions of falling cat afferent responses. Results showed predicted single afferent firing rates that exceeded physiological values; and variations in afferent sensitivities and phase were predicted among different neurons. Fast head movement information could be carried by ensemble populations of vestibular neurons, and a phase-locking encoding hypothesis is proposed which accomplishes this. Implications for central program versus peripheral vestibular feedback strategies for motor control during falling are presented and discussed.

Afferent Pathways↗
PubMed1984

Characterization of discrete and continuous modes of visual pattern discrimination.

Discrete and continuous modes of visual pattern discrimination performance are analyzed using a model for the investigation of discrete internal pattern representations described in previous papers (Foster, 1980a, b). A simple quantitative criterion is derived to characterize the two kinds of visual discrimination performance. Values predicted by this criterion are then compared with values obtained from experimental data.

Cybernetics↗
PubMed1984

Cable theory in neurons with active, linearized membranes.

This investigation aims at exploring some of the functional consequences of single neurons containing active, voltage dependent channels for information processing. Assuming that the voltage change in the dendritic tree of these neurons does not exceed a few millivolts, it is possible to linearize the non-linear channel conductance. The membrane can then be described in terms of resistances, capacitances and inductances, as for instance in the small-signal analysis of the squid giant axon. Depending on the channel kinetics and the associated ionic battery the linearization yields two basic types of membrane: a membrane modeled by a collection of resistances and capacitances and membranes containing in addition to these components inductances. Under certain specified conditions the latter type of membrane gives rise to a membrane impedance that displays a prominent maximum at some nonzero resonant frequency fmax. We call this type of membrane quasi-active, setting it apart from the usual passive membrane. We study the linearized behaviour of active channels giving rise to quasi-active membranes in extended neuronal structures and consider several instances where such membranes may subserve neuronal function: 1. The resonant frequency of a quasi-active membrane increases with increasing density of active channels. This might be one of the biophysical mechanisms generating the large range over which hair cells in the vertebrate cochlea display frequency tuning. 2. The voltage recorded from a cable with a quasi-active membrane can be proportional to the temporal derivative of the injected current. 3. We modeled a highly branched dendritic tree (delta-ganglion cell of the cat retina) using a quasi-active membrane. The voltage attenuation from a given synaptic site to the soma decreases with increasing frequency up to the resonant frequency, in sharp contrast to the behaviour of passive membranes.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1984

Simultaneous order in nervous nets from a functional standpoint.

A nervous net may be studied by an external observer who notes, for example, such features as the spatial lay-out of receptive fields, the existence of somatotopic maps, etc. It is not often acknowledged that many of such features have no functional relevance to the machine itself. Thus somatotopy from the sensor to the motor apparatus may appear important (and in certain respects it is), but it is irrelevant to the function of the organism as an abstract machine. For the abstract machine only functional relations, but not spatial relations per se, count. It is shown how, proceeding from purely functional relations (cross-correlations of signals), a simultaneous order of neural elements may be constructed. Such an order has an objective existence for the abstract machine, not merely for an external observer. It is argued that sensory modalities and the cohesion within modalities (e.g. the visual field) must be understood in such a functional manner. Thus the two-dimensionality of the visual field is objectively present in the cross-correlation structure of optic nerve signals, it exists independently from an external observer's description of the retina as a two-dimensional receptor array.

Animals↗