Cerebral programming
First Claim
1. A method of training a biological neural network using a controller, comprising:
- applying a cycle comprising;
stimulating a neural network by said controller applying at least an input signal to the network;
detecting an output response of the network by said controller; and
modifying said stimulation by said controller for at least a period of time if said response matches a desired at least approximate response; and
repeating said cycle of stimulation, detection and modification at least one more time until said neural network is trained to generate a desired output response for said input signal.
0 Assignments
0 Petitions
Accused Products
Abstract
A method of training a biological neural network using a controller, comprising:
applying a cycle comprising:
stimulating a neural network by said controller applying at least an input signal to the network;
detecting an output response of the network by said controller; and
modifying said stimulation by said controller for at least a period of time if said response matches a desired at least approximate response; and
repeating said cycle of stimulation, detection and modification at least one more time until said neural network is trained to generate a desired output response for said input signal.
264 Citations
103 Claims
-
1. A method of training a biological neural network using a controller, comprising:
-
applying a cycle comprising;
stimulating a neural network by said controller applying at least an input signal to the network;
detecting an output response of the network by said controller; and
modifying said stimulation by said controller for at least a period of time if said response matches a desired at least approximate response; and
repeating said cycle of stimulation, detection and modification at least one more time until said neural network is trained to generate a desired output response for said input signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67)
-
-
68. Apparatus for training an in-vivo neural network, comprising:
-
an input stimulator that generates an input stimulation to said network;
a detector that detects at least an indication of a response of said network; and
a controller that selectively controls said input stimulator such that if a desired output is detected, said input stimulation is changed. - View Dependent Claims (69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82)
-
-
83. Apparatus for interfacing with an in-vivo neural network, that has been trained to include an unnatural input or output area in which a signal generated by the network is more easily detected or a signal input to the network will interact with similar functioning and inter-related neurons, comprising:
-
at least one of an neuronal input and a neuronal output;
a payload apparatus to be interfaced with said network; and
a controller that interfaces said payload and said network, by translating a signal from said trained area or to said area as being directed to said trained input or output. - View Dependent Claims (84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99)
-
-
100. A method of assaying a drug for psycho-active effects, comprising:
-
training a neural network under a first condition of the drug and measuring at least one parameter related to the training;
training the neural network under a second condition of the drug and measuring said at least one parameter; and
comparing the measurements. - View Dependent Claims (101, 102, 103)
-
Specification