Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

Editorial

19 December 2013

Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

Julie Wall

and

Cornelius Glackin

5,035 views

5 citations

Editors

Julie Wall

University of East London

Cornelius Glackin

Intelligent Voice Ltd

Impact

Hypothesis and Theory

15 November 2013

Generalized activity equations for spiking neural network dynamics

Michael A. Buice

and

Carson C. Chow

6,380 views

11 citations

Incorporation of new neurons into normal or damaged circuitry. (A) Natural context for DG neurogenesis. The DG has a roughly feed-forward architecture, allowing a sophisticated maturation process (different panels). Neurons are born continuously, so there is always a mixed population of neurons at different developmental stages (faded green). (B) Therapeutic context for cortical neural replacement. Injured or diseased region may suffer considerable neuronal loss and initiate restructuring of the local network. Proper cell replacement therapy, in which the correct types of new neurons are appropriately positioned in the region, could still suffer from aberrant maturation if the unique properties of developing neurons cause affect the functional wiring of the circuit. Ideal maturation would instead result in not only the proper neuronal layout, but also an appropriate functional circuit as well. (C) Cartoon illustration of how the dynamics of neural maturation can complicate a cell replacement therapy. (D) Cartoon illustration of how compensation makes simple reversal of impairments an insufficient strategy for returning system to normal function.

Perspective

06 November 2013

Perspectives for computational modeling of cell replacement for neurological disorders

James B. Aimone

and

Jason P. Weick

4,520 views

13 citations

Original Research

17 September 2013

Anisotropic connectivity implements motion-based prediction in a spiking neural network

Bernhard A. Kaplan

, 2 more and

Laurent U. Perrinet

5,318 views

17 citations

Original Research

18 July 2013

Rapid, parallel path planning by propagating wavefronts of spiking neural activity

Filip Ponulak

and

John J. Hopfield

Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware.

10,225 views

57 citations

Original Research

22 May 2013

Spike Timing Regulation on the Millisecond Scale by Distributed Synaptic Plasticity at the Cerebellum Input Stage: A Simulation Study

Jesús A. Garrido

, 1 more and

Egidio D’Angelo

Response patterns in the granular-layer model. Response of the model to a stimulation burst composed of three spikes at 100 Hz over 5 Hz background activity generated by random low-frequency firing in the MFs. (A) Response of network elements in control conditions. (Top) Raster plots of activity recorded in the MF (left), GrC (center), and GoC (right) populations, respectively. Note the three-spike bursts in MFs with 100-Hz average frequency and firing probability 0.7. GrC activity rises sharply in response to the first spike in the burst generating a single output spike. Then GrC activity is inhibited by the GoCs, which keep on firing in response to all the three MF burst spikes. (Bottom) Peristimulus-time histograms (PSTH) in MFs (left), GrCs (center), and GoCs (right) respectively. Note the single PSTH peak in GrCs in response to the first MF burst (bin size 1 ms). (B) PSTHs taken from GrCs and GoCs around the first MF spike are shown over-imposed on expanded scale. The Input/Output offset (I/O offset) represents the time with respect to the MF stimulation. Given the probabilistic distribution of MF burst activity around a mean time value (dotted line), the I/O offset can assume negative values at the beginning of discharge. Note that the GrC and GoC PSTH peaks are delayed with respect to the MF PSTH peak due to the integration time of incoming activity in the cells.

The way long-term synaptic plasticity regulates neuronal spike patterns is not completely understood. This issue is especially relevant for the cerebellum, which is endowed with several forms of long-term synaptic plasticity and has been predicted to operate as a timing and a learning machine. Here we have used a computational model to simulate the impact of multiple distributed synaptic weights in the cerebellar granular-layer network. In response to mossy fiber (MF) bursts, synaptic weights at multiple connections played a crucial role to regulate spike number and positioning in granule cells. The weight at MF to granule cell synapses regulated the delay of the first spike and the weight at MF and parallel fiber to Golgi cell synapses regulated the duration of the time-window during which the first-spike could be emitted. Moreover, the weights of synapses controlling Golgi cell activation regulated the intensity of granule cell inhibition and therefore the number of spikes that could be emitted. First-spike timing was regulated with millisecond precision and the number of spikes ranged from zero to three. Interestingly, different combinations of synaptic weights optimized either first-spike timing precision or spike number, efficiently controlling transmission and filtering properties. These results predict that distributed synaptic plasticity regulates the emission of quasi-digital spike patterns on the millisecond time-scale and allows the cerebellar granular layer to flexibly control burst transmission along the MF pathway.

5,996 views

48 citations