US 6,581,046 B1 · Neuronal phase-locked loops

Abstract

A neuronal phase-locked loop (NPLL) that can decode temporally-encoded information and convert it to a rate code is based on an algorithm similar to that of the electronic PLL, but is a stochastic device, implemented by neural networks (real or simulated). The simplest embodiment of the NPLL includes a phase detector (that is, a neuronal-plausible version of an ideal coincidence detector) and a controllable local oscillator that are connected in a negative feedback loop. The phase detector compares the firing times of the local oscillator and the input and provides an output whose firing rate is monotonically related to the time difference. The output rate is fed back to the local oscillator and forces it to phase-lock to the input. Every temporal interval at the input is associated with a specific pair of output rate and time difference values; the higher the output rate the further the local oscillator is driven from its intrinsic frequency. Sequences of input intervals, which, by definition, encode input information, are thus represented by sequences of firing rates at the NPLL's output. The NPLL is an adaptive device which can deal with signals whose exact characteristics are not known in advance and can adapt to changing conditions.

Claims62

Dependent claims

A neuronal component, comprising:

an input element for receiving an input signal including a sequence of pulses which are temporally modulated;
an output element for providing an output which is phase locked to said input signal;
at least one first neural network element configured as a phase detector having first and second inputs for receiving temporally modulated signals, and an output for supplying a signal having a firing rate which is a function of a time difference between said temporally modulated signals, said first input being connected to receive said input signal, and said output of said at least one neural network element being connected to said output element;
and
at least one second neural network element configured as a rate controlled oscillator having an input connected to said output of said at least one first neural network element, and an output connected to said second input of said at least one first neural network element.

2 more elements

A spatial encoding device comprising:

a sensor array having a matrix of individual sensors each detecting spatial information from objects in a field of view;
a controller controlling said sensor array to control scanning of said field of view at least at one predetermined frequency and in at least one predetermined direction whereby objects in said field of view trace a path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from detectors in said matrix to determine spatial location and movement of said objects within said field of view;
wherein said processor includes a phase locked loop circuit comprised of
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

5 more elements

A spatial encoding device comprising:

a sensor array having a matrix of individual sensors each detecting spatial information from objects in a field of view;
a controller controlling said sensor array to scan said field of view at least at one predetermined frequency and in at least one predetermined direction, whereby objects in said field of view trace a path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from detectors in said matrix to determine spatial location and movement of said objects within said field of view, said processor comprising
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

4 more elements

Apparatus for determining at least one of spatial location and movement of an object within a contact area, comprising:

a tactual sensor array having a matrix of individual tactual sensors each detecting spatial information from objects in said contact area;
a controller controlling said tactual sensor array to scan said contact area at least at one predetermined frequency and in at least one predetermined direction, whereby objects in said contact area trace at least one path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from sensors in said matrix to determine spatial location and movement of said objects within said contact area;
said processor comprising a phase locked loop circuit comprised of:
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one-neuron having an intrinsic oscillating frequency, a spiking input train to −and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

5 more elements

An object identification apparatus, comprising:

a tactual sensor array having a matrix of individual tactual sensors each detecting spatial information from objects in a contact area;
a controller for controlling said tactual sensor array to scan said contact area at least at one predetermined frequency and in at least one predetermined direction, whereby objects in said contact area view trace at least one path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from sensors in said matrix to identify an object within said contact area;
said processor comprising a phase locked loop circuit comprised of at least one neuronal phase detector comprising a neural component composed of
a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

5 more elements

A grip control apparatus, comprising:

at least one finger adapted to contact an object within a contact area on a surface of said object;
a tactual sensor array having a matrix of individual tactual sensors disposed on a tip of said finger and contacting said contact area of said object, for detecting spatial information characterizing surface features in said contact area;
a controller for controlling said sensor array to scan said contact area at at least one predetermined frequency and in at least one predetermined direction, whereby surface features in said contact area trace at least one path across said matrix;
a processor for processing relative phase and frequency information contained in output signals from detectors in said matrix to determine movements of said objects;
and
a regulator for regulating a force exerted on said contact area in response to an output of said processor;
said processor comprising a phase locked loop circuit comprised of
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

7 more elements

Apparatus for determining at least one of spatial location and movement of an object within a field of view, comprising:

an optical sensor device having a matrix of individual sensors each detecting spatial information from objects in a field of view;
a controller for controlling said optical sensor device to scan said field of view at at least one predetermined frequency and in at least one predetermined direction, whereby objects in said field of view trace a path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from detectors in said matrix to determine spatial location and movement of said objects within said field of view;
said processor comprising a phase locked loop circuit comprised of
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

5 more elements

A slip control apparatus, comprising:

an optical sensor device having a matrix of individual sensors each detecting spatial information from objects in a field of view;
a controller for controlling said optical sensor device to scan said field of view at least at one predetermined frequency and in at least one predetermined direction, whereby objects in said field of view trace a path across said matrix;
and
a processor for processing relative phase and frequency information contained in output signals from detectors in said matrix to determine spatial location and movement of said objects within said field of view,
said processor comprises a phase locked loop circuit comprised of
at least one neuronal phase detector comprising a neural component composed of a single layer of at least one neuron, a first and second input to each neuron in the single layer, and an output from each neuron in the single layer having a value that is one of an AND function and an OR function of its inputs, and
at least one neuronal oscillator comprising a neural component being composed of a single layer of at least one neuron having an intrinsic oscillating frequency, a spiking input train to and a spiking output train from each neuron of the single layer of the neural component, where the rate of the spiking input train to each said neural component controls the oscillating frequency of the neuronal oscillator,
said spiking input train to the neuronal oscillator being the output of the neuronal phase detector, and said spiking output train of said neuronal oscillator being one of the inputs to the neuronal phase detector.

5 more elements

Dependencies are inferred from the claim text.

Neuronal phase-locked loops

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Neuronal phase-locked loops

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Abstract

Claims62