scholarly journals Dynamic compartmentalization in neurons enables branch-specific learning

2018 ◽  
Author(s):  
Willem A.M. Wybo ◽  
Benjamin Torben-Nielsen ◽  
Marc-Oliver Gewaltig
Keyword(s):  
Information Processing ◽  
Electrical Properties ◽  
Mathematical Formalism ◽  
Tree Graph ◽  
Dendritic Trees ◽  
Shunting Inhibition ◽  
Structural And Electrical Properties ◽  
Stimulus Features ◽  
The Brain ◽  
Specific Learning

AbstractThe dendritic trees of neurons play an important role in the information processing in the brain. While it is tacitly assumed that dendrites require independent compartments to perform most of their computational functions, it is still not understood how they compartmentalize into functional subunits. Here we show how these subunits can be deduced from the structural and electrical properties of dendrites. We devised a mathematical formalism that links the dendritic arborization to an impedance-based tree-graph and show how the topology of this tree-graph reveals independent dendritic compartments. This analysis reveals that coopera-tivity between synapses decreases less than depolarization with increasing electrical separation, and thus that surprisingly few independent subunits coexist on dendritic trees. We nevertheless find that balanced inputs or shunting inhibition can modify this topology and increase the number and size of compartments in a context-dependent, temporal manner. We also find that this dynamic recompartmentalization can enable branch-specific learning of stimulus features.

scholarly journals Attention Promotes the Neural Encoding of Prediction Errors

2019 ◽  
Author(s):  
Cooper A. Smout ◽  
Matthew F. Tang ◽  
Marta I. Garrido ◽  
Jason B. Mattingley
Keyword(s):  
Information Processing ◽  
Coding Theory ◽  
Predictive Coding ◽  
Sensory Information ◽  
Neural Response ◽  
Prediction Errors ◽  
Feature Information ◽  
The Difference ◽  
Stimulus Features ◽  
The Brain

AbstractThe human brain is thought to optimise the encoding of incoming sensory information through two principal mechanisms: prediction uses stored information to guide the interpretation of forthcoming sensory events, and attention prioritizes these events according to their behavioural relevance. Despite the ubiquitous contributions of attention and prediction to various aspects of perception and cognition, it remains unknown how they interact to modulate information processing in the brain. A recent extension of predictive coding theory suggests that attention optimises the expected precision of predictions by modulating the synaptic gain of prediction error units. Since prediction errors code for the difference between predictions and sensory signals, this model would suggest that attention increases the selectivity for mismatch information in the neural response to a surprising stimulus. Alternative predictive coding models proposes that attention increases the activity of prediction (or ‘representation’) neurons, and would therefore suggest that attention and prediction synergistically modulate selectivity for feature information in the brain. Here we applied multivariate forward encoding techniques to neural activity recorded via electroencephalography (EEG) as human observers performed a simple visual task, to test for the effect of attention on both mismatch and feature information in the neural response to surprising stimuli. Participants attended or ignored a periodic stream of gratings, the orientations of which could be either predictable, surprising, or unpredictable. We found that surprising stimuli evoked neural responses that were encoded according to the difference between predicted and observed stimulus features, and that attention facilitated the encoding of this type of information in the brain. These findings advance our understanding of how attention and prediction modulate information processing in the brain, and support the theory that attention optimises precision expectations during hierarchical inference by increasing the gain of prediction errors.

Structural and Electrical Properties of Thermally Evaporated SnxSe1-x Thin Films

2011 ◽  
Vol 3 (10) ◽  
pp. 1-4 ◽  
Author(s):  
Bushra A Hasan ◽  
◽  
Ghuson H Mohamed ◽  
Amer A Ramadhan
Keyword(s):  
Thin Films ◽  
Electrical Properties ◽  
Structural And Electrical Properties

Fabrication and study the effect of the laser on the properties of the compound Tl2-xHgxBa2-ySryCa2Cu3O10+δ superconductor

2018 ◽  
pp. 168
Author(s):  
A. Kareem Dahash Ali ◽  
Nihad Ali Shafeek
Keyword(s):  
Transition Temperature ◽  
Solid State ◽  
Hydrostatic Pressure ◽  
Electrical Properties ◽  
Co2 Laser ◽  
Temperature Shift ◽  
Unit Cell ◽  
X Ray Diffraction ◽  
X Ray ◽  
Structural And Electrical Properties

This study included the fabrication of    compound (Tl2-xHgxBa2-ySryCa2Cu3O10+δ) in a manner solid state and under hydrostatic pressure ( 8 ton/cm2) and temperature annealing(850°C), and determine the effect of the laser on the structural and electrical properties elements in the compound, and various concentrations of x where (x= 0.1,0.2,0.3 ). Observed by testing the XRD The best ratio of compensation for x is 0.2 as the value of a = b = 5.3899 (A °), c = 36.21 (A °) show that the installation of four-wheel-based type and that the best temperature shift is TC= 142 K  .When you shine a CO2 laser on the models in order to recognize the effect of the laser on these models showed the study of X-ray diffraction of these samples when preparing models with different concentrations of the values ​​of x, the best ratio of compensation is 0.2 which showed an increase in the values ​​of the dimensions of the unit cell a=b = 5.3929 (A °), c = 36.238 (A°). And the best transition temperature after shedding laser is TC=144 K. 

scholarly journals Influence of the crystallization thermal treatment on the structural and electrical properties of PZT thin films

2004 ◽  
Vol 7 (2) ◽  
pp. 363-367 ◽  
Author(s):  
Antonio Leondino Bacichetti Junior ◽  
Manuel Henrique Lente ◽  
Ricardo Gonçalves Mendes ◽  
Pedro Iris Paulin Filho ◽  
José Antonio Eiras
Keyword(s):  
Thin Films ◽  
Electrical Properties ◽  
Thermal Treatment ◽  
Pzt Thin Films ◽  
Structural And Electrical Properties

Structural and electrical properties of sol–gel grown nanostructured ZnO and LaMnO3 particle-based nanocomposites

2021 ◽  
Vol 127 (2) ◽  
Author(s):  
Naisargi Kanabar ◽  
Keval Gadani ◽  
V. G. Shrimali ◽  
Khushal Sagapariya ◽  
K. N. Rathod ◽  
...  
Keyword(s):  
Electrical Properties ◽  
Sol Gel ◽  
Structural And Electrical Properties
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