scholarly journals Efficient population coding of naturalistic whisker motion in the ventro-posterior medial thalamus based on precise spike timing

Author(s):  
Michael R. Bale ◽  
Robin A. A. Ince ◽  
Greta Santagata ◽  
Rasmus S. Petersen
2016 ◽  
Vol 27 (02) ◽  
pp. 1650009 ◽  
Author(s):  
Fernando Montani ◽  
Andriy Oliynyk ◽  
Luciano Fadiga

Whether premotor/motor neurons encode information in terms of spiking frequency or by their relative time of firing, which may display synchronization, is still undetermined. To address this issue, we used an information theory approach to analyze neuronal responses recorded in the premotor (area F5) and primary motor (area F1) cortices of macaque monkeys under four different conditions of visual feedback during hand grasping. To evaluate the sensitivity of spike timing correlation between single neurons, we investigated the stimulus dependent synchronization in our population of pairs. We first investigated the degree of correlation of trial-to-trial fluctuations in response strength between neighboring neurons for each condition, and second estimated the stimulus dependent synchronization by means of an information theoretical approach. We compared the information conveyed by pairs of simultaneously recorded neurons with the sum of information provided by the respective individual cells. The information transmission across pairs of cells in the primary motor cortex seems largely independent, whereas information transmission across pairs of premotor neurons is summed superlinearly. The brain could take advantage of both the accuracy provided by the independency of F1 and the synergy allowed by the superlinear information population coding in F5, distinguishing thus the generalizing role of F5.


eNeuro ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. ENEURO.0244-19.2020
Author(s):  
M. V. Beckert ◽  
B. J. Fischer ◽  
J. L. Pena

2018 ◽  
Author(s):  
Dana H. Ballard ◽  
Ruohan Zhang

AbstractOne of the fundamental problems in understanding the brain, in particular the cerebral cortex, is that we only have a partial understanding of the basic communication protocols that underlie signal transmission. This makes it difficult to interpret the significance of particular phenomena such as basic firing patterns and oscillations at different frequencies. There are, of course, useful models. Motivated by single-cell recording technology, Poisson statistics of cortical action potentials have long been a basic component in models of signal representation in the cortex. However, it is increasingly difficult to integrate Poisson spiking with spike timing signals in the gamma frequency spectrum. A potential way forward is being sparked by new technologies that allow the exploration of very low-level communication strategies. Specifically, the voltage potential of a cell’s soma now can be recorded with very high fidelity in vivo, allowing correlation of its fine structure to be correlated with behaviors. To interpret this data, we have developed a unified model (gamma spike multiplexing, or GSM) wherein a cell’s somatic gamma frequencies can modulate the generation of action potentials. Such spikes can be seen as the basis for a general-purpose method of modulating fast communication in cortical networks. In particular, the model has several important advantages over traditional formalisms: 1) It allows multiple, independent processes to run in parallel, greatly increasing the processing capability of the cortex 2) Its processing speed is 102 to 103 times faster than population coding methods 3) Its processes are not bound to specific locations, but migrate across cortical cells as a function of time, facilitating the maintenance of cortical cell calibration.


2019 ◽  
Author(s):  
Tushar Chauhan ◽  
Timothée Masquelier ◽  
Benoit R. Cottereau

AbstractThe early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often viewed as an optimisation which enables the most efficient representation of visual input. However, measurements in monkey and cat suggest that receptive fields in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the receptive fields do not emerge through a global minimisation of the generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity. Using an orientation discrimination paradigm, we show that while sub-optimal, such models offer a much better description of biology at multiple levels: single-cell, population coding, and perception. Taken together, our results underline the need to carefully consider the distinction between information-theoretic and biological notions of optimality in early sensorial populations.


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