scholarly journals Layer 4 in Primary Visual Cortex of the Awake Rabbit: Contrasting Properties of Simple Cells and Putative Feedforward Inhibitory Interneurons

2013 ◽  
Vol 33 (28) ◽  
pp. 11372-11389 ◽  
Author(s):  
J. Zhuang ◽  
C. R. Stoelzel ◽  
Y. Bereshpolova ◽  
J. M. Huff ◽  
X. Hei ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Inhibitory Interneurons ◽  
Simple Cells ◽  
Layer 4

Map of the synapses onto layer 4 basket cells of the primary visual cortex of the cat

1997 ◽  
Vol 380 (2) ◽  
pp. 230-242 ◽  
Author(s):  
Bashir Ahmed ◽  
John C. Anderson ◽  
Kevan A.C. Martin ◽  
J. Charmaine Nelson
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Basket Cells ◽  
Layer 4

Man's Triune Conscious Mind: Part III

1995 ◽  
Vol 81 (2) ◽  
pp. 463-466
Author(s):  
Carl G. Aurell
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Conscious Mind ◽  
Perceptual Model ◽  
Cortex Area ◽  
Layer 4

The perceptual model, discussed previously in Part II, is applied to the organization of the visual cortex in a search for “consciousness neurons,” i.e., sources of sensations, images, and percepts. It is hypothesized that these three conscious phenomena emerge in the primary visual cortex, Area VI, possibly from neurons in its Layer 4.

scholarly journals Reward Timing and Its Expression by Inhibitory Interneurons in the Mouse Primary Visual Cortex

2020 ◽  
Vol 30 (8) ◽  
pp. 4662-4676
Author(s):  
Kevin J Monk ◽  
Simon Allard ◽  
Marshall G Hussain Shuler
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Network Architecture ◽  
Sensory Cortex ◽  
Inhibitory Interneurons ◽  
In Vivo Electrophysiology ◽  
Timing Information ◽  
Primary Sensory Cortex ◽  
A Site

Abstract The primary sensory cortex has historically been studied as a low-level feature detector, but has more recently been implicated in many higher-level cognitive functions. For instance, after an animal learns that a light predicts water at a fixed delay, neurons in the primary visual cortex (V1) can produce “reward timing activity” (i.e., spike modulation of various forms that relate the interval between the visual stimulus and expected reward). Local manipulations to V1 implicate it as a site of learning reward timing activity (as opposed to simply reporting timing information from another region via feedback input). However, the manner by which V1 then produces these representations is unknown. Here, we combine behavior, in vivo electrophysiology, and optogenetics to investigate the characteristics of and circuit mechanisms underlying V1 reward timing in the head-fixed mouse. We find that reward timing activity is present in mouse V1, that inhibitory interneurons participate in reward timing, and that these representations are consistent with a theorized network architecture. Together, these results deepen our understanding of V1 reward timing and the manner by which it is produced.

scholarly journals Spatial integration in mouse primary visual cortex

2013 ◽  
Vol 110 (4) ◽  
pp. 964-972 ◽  
Author(s):  
Agne Vaiceliunaite ◽  
Sinem Erisken ◽  
Florian Franzen ◽  
Steffen Katzner ◽  
Laura Busse
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Neural Circuits ◽  
Temporal Dynamics ◽  
Visual Saliency ◽  
Brain State ◽  
Inhibitory Interneurons ◽  
Spatial Integration ◽  
V1 Neurons ◽  
Contrast Normalization

Responses of many neurons in primary visual cortex (V1) are suppressed by stimuli exceeding the classical receptive field (RF), an important property that might underlie the computation of visual saliency. Traditionally, it has proven difficult to disentangle the underlying neural circuits, including feedforward, horizontal intracortical, and feedback connectivity. Since circuit-level analysis is particularly feasible in the mouse, we asked whether neural signatures of spatial integration in mouse V1 are similar to those of higher-order mammals and investigated the role of parvalbumin-expressing (PV+) inhibitory interneurons. Analogous to what is known from primates and carnivores, we demonstrate that, in awake mice, surround suppression is present in the majority of V1 neurons and is strongest in superficial cortical layers. Anesthesia with isoflurane-urethane, however, profoundly affects spatial integration: it reduces the laminar dependency, decreases overall suppression strength, and alters the temporal dynamics of responses. We show that these effects of brain state can be parsimoniously explained by assuming that anesthesia affects contrast normalization. Hence, the full impact of suppressive influences in mouse V1 cannot be studied under anesthesia with isoflurane-urethane. To assess the neural circuits of spatial integration, we targeted PV+ interneurons using optogenetics. Optogenetic depolarization of PV+ interneurons was associated with increased RF size and decreased suppression in the recorded population, similar to effects of lowering stimulus contrast, suggesting that PV+ interneurons contribute to spatial integration by affecting overall stimulus drive. We conclude that the mouse is a promising model for circuit-level mechanisms of spatial integration, which relies on the combined activity of different types of inhibitory interneurons.

scholarly journals Vision reconstructs the cellular composition of binocular circuitry during the critical period

2020 ◽  
Author(s):  
Liming Tan ◽  
Elaine Tring ◽  
Dario L. Ringach ◽  
S. Lawrence Zipursky ◽  
Joshua T. Trachtenberg
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Critical Period ◽  
Cellular Composition ◽  
Feature Detectors ◽  
Layer 2 ◽  
Layer 4 ◽  
High Acuity ◽  
Longitudinal Imaging

AbstractHigh acuity binocularity is established in primary visual cortex during an early postnatal critical period. In contrast to current models for the developmental of binocular neurons, we find that the binocular network present at the onset of the critical period is dismantled and remade. Using longitudinal imaging of receptive field tuning (e.g. orientation selectivity) of thousands of layer 2/3 neurons through development, we show most binocular neurons present at critical-period onset are poorly tuned and rendered monocular. These are replenished by newly formed binocular neurons that are established by a vision-dependent recruitment of well-tuned ipsilateral inputs to contralateral monocular neurons with matched tuning properties. The binocular network in layer 4 is equally unstable but does not improve. Thus, vision instructs a new and more sharply tuned binocular network in layer 2/3 by exchanging one population of neurons for another and not by refining an extant network.One Sentence SummaryUnstable binocular circuitry is transformed by vision into a network of highly tuned complex feature detectors in the cortex.

Sign in / Sign up

Export Citation Format

Share Document