Juan Huo

Adaptation of barn owl localization system with spike timing dependent plasticity

To localize a seen object, the superior colliculus of the barn owl integrates the visual and auditory localization cues which are accessed from the sensory system of the brain. These cues are formed as visual and auditory maps, thus the alignment between visual and auditory maps is very important for accurate localization in prey behavior. Blindness or prism wearing may disturb this alignment. The juvenile barn owl could adapt its auditory map to this mismatch after several weeks training. Here we investigate this process by building a computational model of auditory and visual integration with map adjustment in the deep superior colliculus. The adaptation is based on activity dependent axon developing which is instructed by an inhibitory network. In the inhibitory network, the strength of the inhibition is adjusted by spike timing dependent plasticity(STDP). The simulation results are in line with the biological experiment and support the idea that the STDP is involved in the alignment of sensory maps. The system of the model provides a new mechanism capable of eliminating the disparity in visual and auditory map integration.

The role of membrane threshold and rate in STDP silicon neuron circuit simulation

Spike-timing dependent synaptic plasticity (STDP) circuitry is designed in 0.35µm CMOS VLSI. By setting different circuit parameters and generating diverse spike inputs, we got different steady weight distributions. Through analysing these simulation results, we show the effect of membrane threshold and input rate in STDP adaptation.

The adaptation of visual and auditory integration in the barn owl superior colliculus with Spike Timing Dependent Plasticity

To localize a seen object, the superior colliculus of the barn owl integrates the visual and auditory localization cues which are accessed from the sensory system of the brain. These cues are formed as visual and auditory maps. The alignment between visual and auditory maps is very important for accurate localization in prey behavior. Blindness or prism wearing may interfere this alignment. The juvenile barn owl could adapt its auditory map to this mismatch after several weeks training. Here we investigate this process by building a computational model of auditory and visual integration in deep Superior Colliculus (SC). The adaptation of the map alignment is based on activity dependent axon developing in Inferior Colliculus (IC). This axon growing process is instructed by an inhibitory network in SC while the strength of the inhibition is adjusted by Spike Timing Dependent Plasticity (STDP). The simulation results of this model are in line with the biological experiment and support the idea that STDP is involved in the alignment of sensory maps. This model also provides a new spiking neuron based mechanism capable of eliminating the disparity in visual and auditory map integration.

Adaptive Visual and Auditory Map Alignment in Barn Owl Superior Colliculus and Its Neuromorphic Implementation

Adaptation is one of the most important phenomena in biology. A young barn owl can adapt to imposed environmental changes, such as artificial visual distortion caused by wearing a prism. This adjustment process has been modeled mathematically and the model replicates the sensory map realignment of barn owl superior colliculus (SC) through axonogenesis and synaptogenesis. This allows the biological mechanism to be transferred to an artificial computing system and thereby imbue it with a new form of adaptability to the environment. The model is demonstrated in a real-time robot environment. Results of the experiments are compared with and without prism distortion of vision, and show improved adaptability for the robot. However, the computation speed of the embedded system in the robot is slow. A digital and analog mixed signal very-large-scale integration (VLSI) circuit has been fabricated to implement adaptive sensory pathway changes derived from the SC model at higher speed. VLSI experimental results are consistent with simulation results.

CYP-nsSNP: A specialized database focused on effect of non-synonymous SNPs on function of CYPs

The cytochrome P450 (CYP) enzymes play the central role in synthesis of endogenous substances and metabolism of xenobiotics. The substitution of single amino acid caused by non-synonymous single nucleotide polymorphism (nsSNP) will lead to the change in enzymatic activity of CYP isozymes, especially the drugmetabolizing ability. CYP-nsSNP is a specialized database focused on the effect of nsSNPs on enzymatic activity of CYPs. Its unique feature lies in providing the qualitative and quantitative description of the CYP variants in terms of enzymatic activity. In addition, the database also offers the general information about nsSNP and compounds that are involved in corresponding enzymatic reaction. The current CYP-nsSNP can be accessible at http://cypdatabase.sjtu.edu.cn/ and includes more than 300 genetic variants of 12 CYP isozymes together with about 100 compounds. In order to keep the accuracy of information within database, all experimental data were collected from the scientific literatures, and the users who conducted research to identify the novel CYP variants are encouraged to contribute their data. Therefore, CYP-nsSNP can be considered as a valuable source for experimental and computational studies of impact of genetic polymorphism on the function of CYPs.

Silicon superior colliculus for the integration of visual and auditory information with adaptive axon connection

Visual and auditory map alignment in the superior colliculus (SC) of the barn owl is important for its accurate localization of prey. The visual map, and hence the alignment, may be purposefully disturbed in a juvenile barn owl by fitting it with ocular prisms, and it is found that it can adapt its auditory map to this mismatch after several weeks training. In our previous SC model, the axon growing process is instructed by an inhibitory network, the strength of which is adjusted using the neural structures involved in spatial localization. Based on this model, a mixed signal integrated circuit of the SC has been designed, and simulation results are consistent with those found by biological experiment. This new model makes possible artificial networks capable of eliminating the disparity between the visual and auditory maps.

Modeling visual and auditory integration of barn owl superior colliculus with STDP

The visual and auditory map alignment in the superior colliculus of barn owl is important for its accurate localization in prey behavior. This alignment may be disturbed by the blindness or prism wearing, the juvenile barn owl could adapt its auditory map to this mismatch after several weeks training. It is believed in literature that auditory map with the plasticity shifts in terms of the visual map change. In this paper, a model is built to explain this mechanism. The activity dependent axonogenesis during the auditory map shift is guided by the visual instructive spikes whereas the visual instructive spikes are modulated by an inhibitory network based on spike timing dependent plasticity(STDP). The simulation results are consistent with the biological experiment and would open a way towards artificial networks capable of eliminating the disparity in visual and auditory map integration.

Sensor-driven neuromorphic walking leg control

We present a simple neuromorphic central pattern generators (CPG) circuit module, which is essentially a pair of coupled oscillators, to actuate a joint on a leg. This novel, reconfigurable CPG module is able to generate different motor patterns of different frequencies or duty cycles, simply by changing a few of circuit parameters. Three CPG modules, corresponding to three joints, can make an arthropod leg of three degrees of freedom (DOFs). With appropriate circuit parameter settings, and thus suitable phase lags among joints, the leg is expected to walk on a complex terrain with adaptive steps. The adaptation is associated with the circuit parameters mediated by external commands or sensory signals. Simulation results for the circuitry, designed using a 0.35µm process, are reported.

Deterministic Coincidence Detection and Adaptation Via Delayed Inputs

A model of one integrate-and-firing (IF) neuron with two afferent excitatory synapses is studied analytically. This is to discuss the influence of different model parameters, i.e., synaptic efficacies, synaptic and membrane time constants, on the postsynaptic neuron activity. An activation window of the postsynaptic neuron, which is adjustable through spike-timing dependent synaptic adaptation rule, is shown to be associated with the coincidence level of the excitatory postsynaptic potentials (EPSPs) under several restrictions. This simplified model, which is intrinsically the deterministic coincidence detector, is hence capable of detecting the synchrony level between intercellular connections. A model based on the proposed coincidence detection is provided as an example to show its application on early vision processing.

VLSI Implementation of Barn Owl Superior Colliculus Network for Visual and Auditory Integration

A bio-inspired silicon Mixed Signal integrated circuit is designed in this paper to emulate the brain development in Superior Colliculus of barn owl. For the juvenile barn owl, it can adapt localization mismatch to prism wearing. Visual and auditory maps alignment in Superior Colliculus is adjusted. Visual and auditory input information can recover their registration after several weeks’ training. A mathematical model has been built previously to emulate this process. Based on the model, we designed a VLSI circuit in 0.35μm CMOS process which has been fabricated. In this paper we present the chip test results of a silicon superior colliculus and show a novel method for adaptive spiking neural information integration when disparity is caused by the environment.