Projections from the claustrum to the prelunate gyrus in the monkey

1997 ◽  
Vol 113 (3) ◽  
pp. 564-568 ◽  
Author(s):  
J. S. Baizer ◽  
T. M. Lock ◽  
M. Youakim
Keyword(s):  
2001 ◽  
Vol 136 (1) ◽  
pp. 108-113 ◽  
Author(s):  
Ivan N. Pigarev ◽  
Hans-Christoph Nothdurft ◽  
Sabine Kastner

1989 ◽  
Vol 496 (1-2) ◽  
pp. 307-313 ◽  
Author(s):  
Chao-yi Li ◽  
Masafumi Tanaka ◽  
O.D. Creutzfeldt
Keyword(s):  

Author(s):  
Estel Van Der Gucht ◽  
Michele Youakim ◽  
Lutgarde Arckens ◽  
Patrick R. Hof ◽  
Joan S. Baizer

2010 ◽  
Vol 20 (02) ◽  
pp. 95-108 ◽  
Author(s):  
NIKOLAY V. MANYAKOV ◽  
MARC M. VAN HULLE

We propose an invasive brain-machine interface (BMI) that decodes the orientation of a visual grating from spike train recordings made with a 96 microelectrodes array chronically implanted into the prelunate gyrus (area V4) of a rhesus monkey. The orientation is decoded irrespective of the grating's spatial frequency. Since pyramidal cells are less prominent in visual areas, compared to (pre)motor areas, the recordings contain spikes with smaller amplitudes, compared to the noise level. Hence, rather than performing spike decoding, feature selection algorithms are applied to extract the required information for the decoder. Two types of feature selection procedures are compared, filter and wrapper. The wrapper is combined with a linear discriminant analysis classifier, and the filter is followed by a radial-basis function support vector machine classifier. In addition, since we have a multiclass classification problen, different methods for combining pairwise classifiers are compared.


1984 ◽  
Vol 4 (7) ◽  
pp. 1690-1704 ◽  
Author(s):  
WM Maguire ◽  
JS Baizer

2021 ◽  
Author(s):  
Jacob A. Westerberg ◽  
Michelle S. Schall ◽  
Alexander Maier ◽  
Geoffrey F. Woodman ◽  
Jeffrey D. Schall

AbstractCognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the component neural circuitry giving rise to these signals remains unknown. Specifically, the functional architecture of cortical columns which results in attention-associated electric fields has not been explored. Here we detail the laminar cortical circuitry underlying an attention-associated electric field often measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Lastly, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field capable of being measured extracranially and the relative contribution of each column depends upon the underlying functional architecture.


1982 ◽  
Vol 47 (2) ◽  
pp. 193-213 ◽  
Author(s):  
S. J. Schein ◽  
R. T. Marrocco ◽  
F. M. de Monasterio

1. Recordings were made from neurons located within the central-field representation of the V4 area of extrastriate visual cortex using a semichronic, nitrous-oxide preparation; the properties of 174 cells were examined in sufficient detail to permit their classification. Cyto- and myeloarchitectural studies confirmed the identification of the area. 2. Color-selective cells with either color-biased or color-opponent properties represented about 20% of the examined population. Their incidence was not significantly different from that of similar cells encountered in penetrations into the central-field representation of area V2. 3. Most color-selective cells had color-biased properties, responding best to wave-lengths shorter than 460 nm, or longer than 580 n, or both. No examples of "green-biased" cells were found. Some color-biased cells responded to photopically matched white light, while others did not. Very few cells showed overt color-opponent responses. The spectral sensitivity of color-selective cells was not unusually narrow. 4. Cells lacking color selectivity and responding equally well to chromatic and achromatic lights of equal photopic luminosity, were the most commonly encountered cell type in penetrations of different parts of the V4 area (56%). Other than color, these cells showed stimulus preferences like those of color-selective cells. 5. One-fourth of V4 cells could not be systematically driven with the various stimuli used. This finding is consistent with recent results of recordings from the prelunate gyrus of the behaving monkey suggesting that some V4 cells receive extraretinal signals. 6. Our results do not support recent claims that V4 is specialized in the detailed analysis of color information.


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