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Volterra dendritic stimulus processors and biophysical spike generators with intrinsic noise sources.

ABSTRACT: We consider a class of neural circuit models with internal noise sources arising in sensory systems. The basic neuron model in these circuits consists of a dendritic stimulus processor (DSP) cascaded with a biophysical spike generator (BSG). The dendritic stimulus processor is modeled as a set of nonlinear operators that are assumed to have a Volterra series representation. Biophysical point neuron models, such as the Hodgkin-Huxley neuron, are used to model the spike generator. We address the question of how intrinsic noise sources affect the precision in encoding and decoding of sensory stimuli and the functional identification of its sensory circuits. We investigate two intrinsic noise sources arising (i) in the active dendritic trees underlying the DSPs, and (ii) in the ion channels of the BSGs. Noise in dendritic stimulus processing arises from a combined effect of variability in synaptic transmission and dendritic interactions. Channel noise arises in the BSGs due to the fluctuation of the number of the active ion channels. Using a stochastic differential equations formalism we show that encoding with a neuron model consisting of a nonlinear DSP cascaded with a BSG with intrinsic noise sources can be treated as generalized sampling with noisy measurements. For single-input multi-output neural circuit models with feedforward, feedback and cross-feedback DSPs cascaded with BSGs we theoretically analyze the effect of noise sources on stimulus decoding. Building on a key duality property, the effect of noise parameters on the precision of the functional identification of the complete neural circuit with DSP/BSG neuron models is given. We demonstrate through extensive simulations the effects of noise on encoding stimuli with circuits that include neuron models that are akin to those commonly seen in sensory systems, e.g., complex cells in V1.

SUBMITTER: Lazar AA

PROVIDER: S-EPMC4150400 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Volterra dendritic stimulus processors and biophysical spike generators with intrinsic noise sources.

Lazar Aurel A AA Zhou Yiyin Y

Frontiers in computational neuroscience 20140901

We consider a class of neural circuit models with internal noise sources arising in sensory systems. The basic neuron model in these circuits consists of a dendritic stimulus processor (DSP) cascaded with a biophysical spike generator (BSG). The dendritic stimulus processor is modeled as a set of nonlinear operators that are assumed to have a Volterra series representation. Biophysical point neuron models, such as the Hodgkin-Huxley neuron, are used to model the spike generator. We address the q ...[more]

PMID: 25225477

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Project description:In the low stimulus environment project, we aimed to reduce the levels of intrusive background noise on an older adult mental health ward, combining a very straightforward measure on decibel levels with a downstream measure of reduced distress and agitation as expressed in incidents of violence. This project on reducing background noise levels on older adult wards stemmed from work the team had done on reducing levels of violence and aggression. We approached the problem using quality improvement methods. Reducing harm to patients and staff is a strategic aim of our Trust and in our efforts we were supported by the Trust's extensive programme of quality improvement, including training and support provided by the Institute for Healthcare Improvement and the trust's own Quality Improvement team. Prior to the project we were running a weekly multi-disciplinary quality improvement group on the ward. We established from this a sub-group to address the specific problem of noise levels and invited carers of people with dementia on our ward to the group. The project was led by nursing staff. We used a noise meter app readily downloadable from the internet to monitor background noise levels on the ward and establish a baseline measure. As a group we used a driver diagram to identify an overall aim and a clear understanding of the major factors that would drive improvements. We also used a staff and carer survey to identify further areas to work on. Change ideas that came from staff and carers included the use of the noise meter to track and report back on noise levels, the use of posters to remind staff about noise levels, the introduction of a visual indication of current noise levels (the Yacker Tracker), the addition of relaxing background music, and adaptations to furniture and environment. We tested many of these over the course of nine months in 2015, using the iterative learning gained from multiple PDSA cycles. The specific aim was a decrease from above 60dB to below 50dB in background noise on the wards. Following our interventions, we have managed to decrease noise levels on the ward to 53dB on average. The success of this project to date has relied on the involvement of ward staff and carers - those most affected by the problem - in generating workable local solutions. As many of the change ideas amounted to harm free interventions it was easier for us to make a case to test them out in the real-life setting. Nevertheless we were surprised at how effective such seemingly simple ideas have been in improving the environment on the ward. We have incorporated the change ideas into routine practice and are advising other wards on similar projects.

Dataset Information

Volterra dendritic stimulus processors and biophysical spike generators with intrinsic noise sources.

Publications

Volterra dendritic stimulus processors and biophysical spike generators with intrinsic noise sources.

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