WTAINCNS

Winner-Take-All readout mechanisms in the Central Nervous System

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 Obiettivo del progetto (Objective)

'How is information about external stimuli or planned motor commands coded and communicated between different brain regions? This question is one of the most fundamental open questions in neuroscience, and addressing it is likely to revolutionize the field of neural-prosthetic devices. In particular, it will significantly improve the quality of life of the many thousands in need of cochlear implants. Furthermore, the creation of effective motor brain-machine interfaces relies heavily on advances in this field. One hypothesis for the neural code is the Winner-Take-All (WTA) readout, in which activity of single cells, rather than large populations of neurons, shapes behavior. It has been suggested that WTA is used in several brain regions, in particular the middle-temporal (MT) cortex, in which the activity of single cells can account for the observed behavior. However, the computational capabilities of WTA have received little theoretical attention. Therefore, it remains unclear to what extent WTA can account for the observed activity in the brain, particularly in the MT region. I propose to conduct extensive theoretical study of WTA. I will quantify the accuracy of WTA and study the effects of the network architecture, empirically observed noise-correlations, inherent neuronal heterogeneity and different coding strategies, all of which have been shown to considerably affect the accuracy of other readout hypotheses. In addition to studying the conventional WTA, I will construct a novel temporal-code generalization of WTA that can take into account the fine temporal structure of neural responses. My preliminary results show that this readout is superior to the conventional WTA in both accuracy and speed of computation. The primary goal of this research is to obtain quantitative estimates of the accuracy of WTA that will enable us to test its feasibility as readout utilized by the central nervous system by comparing it to the psychophysical accuracy.'

Introduzione (Teaser)

The brain is responsible for receiving and transmitting neuronal signals from and to the entire body. Understanding how large neuronal populations communicate to transmit information is central to our ability to build an effective brain-machine interface.

Descrizione progetto (Article)

Sensory stimuli are received, processed and transformed into motor commands.

How these commands are coded and communicated in such brief response times and with such accuracy still remains unclear.One of the theories proposed to explain neuronal information transmission is based on the Winner-Take-All (WTA) approach.

It is theorised that spiking neurons are trained to respond to repeated sequences of sensory cues.

As a result, they induce ordered patterns of neuronal activity that consist of a brief steady state followed by sharp neuronal transitions.

The EU-funded ?Winner-Take-All readout mechanisms in the central nervous system? (WTAINCNS) project set out to study the accuracy of a temporal WTA framework for the neural response to a stimulus.

Researchers suggested a latency-based competitive mechanism to explain transmission of the external stimulus based on the identity of the neuron that fired the first spike in the population.To this end, they used a mathematical model to analyse important parameters in neural transmission and determine how they affect WTA accuracy.

Their theoretical investigation was combined with experimental data from different systems.

In particular, the model was used to study the early visual system in the fish and the monkey, as well as determine sound source localisation in the guinea pig.

Results showed that cells responsible for sound source localisation achieve interaural time delay (ITD) by regulating the rate at which they fire the particular signal.

ITD is the difference in sound arrival time between the two ears.

The mechanism they use essentially takes into account the total number of spikes fired by the cell in the entire neural response to the auditory stimulus. The WTAINCNS computational approach provides a useful tool for studying neuronal responses and deciphering the response latency observed in both the auditory and visual systems.

In the long run, this information could be exploited in brain-computer interface neuroprosthetics' applications that aim to restore damaged hearing, sight and movement.