On the Viability of FIB Tomography for Generating 3-D Orientation Maps in Deformed and Annealed Metals

Author(s):  
M. Ferry ◽  
W. Xu ◽  
N. Mateescu ◽  
J.M. Cairney ◽  
F. John Humphreys
Keyword(s):  
2007 ◽  
Vol 97 (5) ◽  
pp. 3781-3789 ◽  
Author(s):  
Ian Nauhaus ◽  
Dario L. Ringach

Recent theoretical models of primary visual cortex predict a relationship between receptive field properties and the location of the neuron within the orientation maps. Testing these predictions requires the development of new methods that allow the recording of single units at various locations across the orientation map. Here we present a novel technique for the precise alignment of functional maps and array recordings. Our strategy consists of first measuring the orientation maps in V1 using intrinsic optical imaging. A micromachined electrode array is subsequently implanted in the same patch of cortex for electrophysiological recordings, including the measurement of orientation tuning curves. The location of the array within the map is obtained by finding the position that maximizes the agreement between the preferred orientations measured electrically and optically. Experimental results of the alignment procedure from two implementations in monkey V1 are presented. The estimated accuracy of the procedure is evaluated using computer simulations. The methodology should prove useful in studying how signals from the local neighborhood of a neuron, thought to provide a dominant feedback signal, shape the receptive field properties in V1.


Author(s):  
Hubertus Axer ◽  
Jan Jantzen ◽  
David Gräßel ◽  
Matthias Leunert ◽  
Malte Mürköster ◽  
...  

Neuroscience ◽  
2018 ◽  
Vol 374 ◽  
pp. 49-60 ◽  
Author(s):  
S.I. Shumikhina ◽  
I.V. Bondar ◽  
M.M. Svinov

2000 ◽  
Vol 20 (3) ◽  
pp. 1119-1128 ◽  
Author(s):  
Harel Z. Shouval ◽  
David H. Goldberg ◽  
Judson P. Jones ◽  
Martin Beckerman ◽  
Leon N. Cooper
Keyword(s):  

2001 ◽  
Vol 56 (5-6) ◽  
pp. 464-478 ◽  
Author(s):  
Thomas Burger ◽  
Wolfgang Lang

A nonlinear, recurrent neural network model of the visual cortex is presented. Orientation maps emerge from adaptable afferent as well as plastic local intracortical circuits driven by random input stimuli. Lateral coupling structures self-organize into DOG profiles under the influence of pronounced emerging cortical activity blobs. The model’s simplified architecture and features are modeled to largely mimik neurobiological findings.


Sign in / Sign up

Export Citation Format

Share Document