Abstract: A method that is implemented by one or more data processing devices can include receiving a training set that includes a plurality of representations of topological structures in patterns of activity in a source neural network and training a neural network using the representations either as an input to the neural network or as a target answer vector. The activity is responsive to an input into the source neural network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing activity in a recurrent artificial neural network. In one aspect, a method includes outputting digits from a recurrent artificial neural network, wherein each digit represents whether or not activity within a particular group of nodes in the recurrent artificial neural network comports with a respective pattern of activity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing activity in a recurrent artificial neural network. In one aspect, a method can include characterizing activity in an artificial neural network. The method is performed by data processing apparatus and can include identifying clique patterns of activity of the artificial neural network. The clique patterns of activity can enclose cavities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.

Abstract: Compositions for treatment or prevention of autism disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of autism disorders are also provided, and the methods include administering such compositions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.

Abstract: Compositions for treatment or prevention of autism disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of autism disorders are also provided, and the methods include administering such compositions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.

Abstract: The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron to an other spatially-extended neuron along the arborized projection, defining a second temporal filter for the conveyance of input from yet another neuron to the spatially-extended neuron along the arborized projection, replacing, in the neural network model, the first, spatially-extended neuron with a first, spatially-constrained neuron and the arborized projection with a first connection extending between the first, spatially-constrained neuron and the second neuron, wherein the first connection filters input from the second neuron in accordance with the first temporal filter and a second connection extending between the first spatially-constrained neuron and the third neuron.

Abstract: In one aspect, a method includes generating a functional subgraph of a network from a structural graph of the network. The structural graph comprises a set of vertices and structural connections between the vertices. Generating the functional subgraph includes identifying a directed functional edge of the functional subgraph based on presence of structural connection and directional communication of information across the same structural connection.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reconstructing and simulating neocortical microcircuitry. In one aspect, a method includes providing a model of neural tissue, the model including different types of neural cells and dynamic synaptic interconnections between the neural cells, changing a parameter in the model; and identifying a change in a computational state of the model of the neural tissue responsive to the change in the parameter. The change in the parameter can, e.g., change behavior of neural cells of at least one type, change interconnectivity between neural cells, or target a location within a volume in the model that interacts with multiple types of neural cells.

Abstract: Compositions tor prevention or treatment of non-inflammatory neuronal damage from brain trauma and strokes are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of non-inflammatory neuronal damage from brain trauma and strokes are also provided, and the methods include administering such compositions.

Abstract: Compositions for prevention or treatment of non-inflammatory neuronal damage from brain trauma and strokes are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of non-inflammatory neuronal damage from brain trauma and strokes are also provided, and the methods include administering such compositions.

Abstract: Compositions for treatment or prevention of depression are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Icilin and combinations thereof. Methods for treatment or prevention of depression are also provided, and the methods include administering such compositions.

Abstract: Compositions for treatment or prevention of neurodegenerative disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of neurodegenerative disorders are also provided, and the methods include administering such compositions.

Abstract: Compositions for treatment or prevention of autism disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of autism disorders are also provided, and the methods include administering such compositions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.

Abstract: Computer-implemented methods, software, and systems for determining functional synapses from given structural touches between cells in a neuronal circuit are described. One computer-implemented method for determining functional synapses from predetermined synapses of connections between two cells in a neuronal circuit, includes determining, from the predetermined synapses, the functional synapses by leaving a portion of the connections unused, e.g. for activation by plasticity mechanisms.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for encoding and decoding information. In one aspect, methods of encoding information in an encoder include receiving a signal representing information using a collection of discrete digits, converting, by an encoder, the received signal into a time-based code, and outputting the time-based code. The time-based code is divided into time intervals. Each of the time intervals of the time-based code corresponds to a digit in the received signal. Each digit of a first state of the received signal is expressed as an event occurring at a first time within the corresponding time interval of the time-based code. Each digit of a second state of the received signal is expressed as an event occurring at a second time within the corresponding time intervals of the time-based code, the first time is distinguishable from the second time.

Abstract: Computer-implemented methods, software, and systems for determining functional synapses from given structural touches between cells in a neuronal circuit are described. One computer-implemented method for determining functional synapses from predetermined synapses of connections between two cells in a neuronal circuit, includes determining, from the predetermined synapses, the functional synapses by leaving a portion of the connections unused, e.g. for activation by plasticity mechanisms.