[14C]2-Deoxyglucose demonstration of the organization of ocular dominance in areas 17 and 18 of the normal cat

Tieman, Suzannah Bliss; Tumosa, Nina

doi:10.1016/0006-8993(83)91037-5

Cited by 25 publications

(31 citation statements)

References 36 publications

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“…These observations are in accordance with previous anatomical and electrophysiological results (e.g. Hubel & Wiesel, 1962;Blakemore & Pettigrew, 1970;Albus, 1975;Shatz & Stryker, 1978;Tieman & Tumosa, 1983;Löwel, 1994), indicating that the contralateral eye tends to occupy more cortical territory than the ipsilateral eye. This was the case irrespective of whether the contralateral eye was the deviated (operated) or non-deviated eye (compare Figs 3A,B and 4A,B).…”

Section: Layout Of Ocular Dominance Columnssupporting

confidence: 93%

The layout of orientation and ocular dominance domains in area 17 of strabismic cats

Löwel¹,

Schmidt²,

Kim³

et al. 1998

Eur J Neurosci

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In the primary visual cortex of strabismic cats, the elimination of correlated activity between the two eyes enhances the segregation of the geniculocortical afferents into alternating ocular dominance domains. In addition, both tangential intracortical fibres and neuronal synchronization are severely reduced between neurons activated by different eyes. Consequently, ocular dominance columns belonging to different eyes are functionally rather independent. We wondered whether this would also affect the organization of orientation preference maps. To this end, we visualized the functional architecture of area 17 of strabismic cats with both optical imaging based on intrinsic signals and double labelling of orientation and ocular dominance columns with [ 14 C]2-deoxyglucose and [ 3 H]proline. As expected, monocular iso-orientation domains had a patchy appearance and differed for the two eyes, leading to a clear segregation of the ocular dominance domains. Comparison of 'angle maps' revealed that orientation domains exhibit a pinwheel organization as in normally reared cats. Interestingly, the map of orientation preferences did not show any breaks at the borders between ocular dominance columns: iso-orientation domains were continuous across these borders. In addition, iso-orientation contours tended to cross the borders of adjacent ocular dominance columns at right angles. These data suggest that the basic relations between the layout of orientation maps and ocular dominance columns are not disturbed by artificial decorrelation of binocular input. Therefore in cat area 17, the orientation map does not seem to be modified by experience-dependent changes of thalamic input connections. This suggests the possibility that usedependent rearrangement of geniculocortical afferents into ocular dominance columns is due to Hebbian modifications whereby postsynaptic responsivity is constrained by the scaffold of the orientation map.

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Section: Layout Of Ocular Dominance Columnssupporting

confidence: 93%

The layout of orientation and ocular dominance domains in area 17 of strabismic cats

Löwel¹,

Schmidt²,

Kim³

et al. 1998

Eur J Neurosci

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“…A well-established layer model of the cat visual cortex was employed to examine whether functional T 1 ρ changes are localized to the most active sites, as suggested by Magnotta et al (Magnotta et al, 2012). The middle cortical layer (layer IV) is known to have the highest change in neuronal activities and in metabolic rate during stimulation (Price, 1983; Tieman and Tumosa, 1983) and can be visualized as a slightly bright band (indicated by arrows) in the cat visual cortex (outlined by green contours) in T 1 -weighted inversion recovery echo-planar images (Fig. 2A) (Jin and Kim, 2008c; Kim and Kim, 2011).…”

Section: Resultsmentioning

confidence: 99%

Characterization of non-hemodynamic functional signal measured by spin-lock fMRI

Jin¹,

Kim²

2013

NeuroImage

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Current functional MRI techniques measure hemodynamic changes induced by neural activity. Alternative measurement of signals originated from tissue is desirable and may be achieved using T1ρ, the spin-lattice relaxation time in the rotating-frame, which is measured by spin-lock MRI. Functional T1ρ changes in the brain can have contributions from vascular dilation, tissue acidosis, and potentially other contributions. When the blood contributions were suppressed with a contrast agent at 9.4 T, a small tissue-originated T1ρ change was consistently observed at the middle cortical layers of cat visual cortex during visual stimulation, which had different dynamic characteristics compared to hemodynamic fMRI such as a faster response and no post-stimulus undershoot. Functional tissue T1ρ is highly dependent on the magnetic field strength and experimental parameters such as the power of the spin-locking pulse. With a 500 Hz spin-locking pulse, the tissue T1ρ without the blood contribution increased during visual stimulation, but decreased during acidosis-inducing hypercapnia and global ischemia, indicating different signal origins. Phantom studies suggest that it may have contribution from concentration decrease in metabolites. Even though the sensitivity is much weaker than BOLD and its exact interpretation needs further investigation, our results show that non-hemodynamic functional signal can be consistently observed by spin-lock fMRI.

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“…This should be detectable at the spatial resolution of our method for those RF properties that have map-like distributions, including visuotopy (Hubel and Wiesel, 1962;Tusa et al, 1978Tusa et al, , 1979, direction preference (Shmuel and Grinvald, 1996), ocular dominance (Tieman and Tumosa, 1983;Hü bener et al, 1997), and spatial frequency (Tootell et al, 1981;Hü bener et al, 1997;Sirovich and Uglesich, 2004). A detailed knowledge of the relevant maps would potentially allow modeling their effects on anatomical connectivity, but only at the cost of a radical increase in the number of model parameters.…”

Section: Simple Tuning Model Explains Populationlevel Connectivitymentioning

confidence: 99%

Model‐based analysis of excitatory lateral connections in the visual cortex

Buzás

Kovács

Ferecskó

et al. 2006

J of Comparative Neurology

103

151

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Excitatory lateral connections within the primary visual cortex are thought to link neurons with similar receptive field properties. Here we studied whether this rule can predict the distribution of excitatory connections in relation to cortical location and orientation preference in the cat visual cortex. To this end, we obtained orientation maps of areas 17 or 18 using optical imaging and injected anatomical tracers into these regions. The distribution of labeled axonal boutons originating from large populations of excitatory neurons was then analyzed and compared with that of individual pyramidal or spiny stellate cells. We demonstrate that the connection patterns of populations of nearby neurons can be reasonably predicted by Gaussian and von Mises distributions as a function of cortical location and orientation, respectively. The connections were best described by superposition of two components: a spatially extended, orientation-specific and a local, orientation-invariant component. We then fitted the same model to the connections of single cells. The composite pattern of nine excitatory neurons (obtained from seven different animals) was consistent with the assumptions of the model. However, model fits to single cell axonal connections were often poorer and their estimated spatial and orientation tuning functions were highly variable. We conclude that the intrinsic excitatory network is biased to similar cortical locations and orientations but it is composed of neurons showing significant deviations from the population connectivity rule.

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[14C]2-Deoxyglucose demonstration of the organization of ocular dominance in areas 17 and 18 of the normal cat

Cited by 25 publications

References 36 publications

The layout of orientation and ocular dominance domains in area 17 of strabismic cats

The layout of orientation and ocular dominance domains in area 17 of strabismic cats

Characterization of non-hemodynamic functional signal measured by spin-lock fMRI

Model‐based analysis of excitatory lateral connections in the visual cortex

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