In Vivo Two-Photon Imaging Reveals a Role of Arc in Enhancing Orientation Specificity in Visual Cortex

Wang, Kuan Hong; Majewska, Ania K.; Schummers, James; Farley, Brandon J.; Hu, Chengcheng; Sur, Mriganka; Tonegawa, Susumu

doi:10.1016/j.cell.2006.06.038

Cited by 215 publications

(233 citation statements)

References 39 publications

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“…6 A, cells 33 and 58). This random arrangement of receptive-field orientation and position is consistent with the arrangement of orientation preference measured with grating stimuli (Ohki et al, 2005;Wang et al, 2006;Sohya et al, 2007;Kerlin et al, 2010), and with the scatter of ON and OFF receptive-field subregions of nearby neurons measured with sparse noise (Smith and Häusser, 2010).…”

Section: Local Receptive-field Populations: Diversity and Organizationmentioning

confidence: 49%

“…In cat visual cortex, receptive fields of neighboring neurons measured from the same electrodes were rarely found to be similar (DeAngelis et al, 1999;Hetherington and Swindale, 1999). Diversity has best been demonstrated using cellular imaging (Stosiek et al, 2003;Ohki et al, 2005) in local regions of the visual cortex of the mouse (Wang et al, 2006;Mrsic-Flogel et al, 2007;Sohya et al, 2007;Kerlin et al, 2010), where neurons with diverse properties are intermingled. Key to studying this diversity is the development of tools to measure the detailed receptive fields of comprehensive populations (Smith and Häusser, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex

Bonin

Histed²,

Yurgenson³

et al. 2011

J. Neurosci.

238

217

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Many thousands of cortical neurons are activated by any single sensory stimulus, but the organization of these populations is poorly understood. For example, are neurons in mouse visual cortex-whose preferred orientations are arranged randomly-organized with respect to other response properties? Using high-speed in vivo two-photon calcium imaging, we characterized the receptive fields of up to 100 excitatory and inhibitory neurons in a 200 m imaged plane. Inhibitory neurons had nonlinearly summating, complex-like receptive fields and were weakly tuned for orientation. Excitatory neurons had linear, simple receptive fields that can be studied with noise stimuli and system identification methods. We developed a wavelet stimulus that evoked rich population responses and yielded the detailed spatial receptive fields of most excitatory neurons in a plane. Receptive fields and visual responses were locally highly diverse, with nearby neurons having largely dissimilar receptive fields and response time courses. Receptive-field diversity was consistent with a nearly random sampling of orientation, spatial phase, and retinotopic position. Retinotopic positions varied locally on average by approximately half the receptive-field size. Nonetheless, the retinotopic progression across the cortex could be demonstrated at the scale of 100 m, with a magnification of ϳ10 m/°. Receptive-field and response similarity were in register, decreasing by 50% over a distance of 200 m. Together, the results indicate considerable randomness in local populations of mouse visual cortical neurons, with retinotopy as the principal source of organization at the scale of hundreds of micrometers.

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Section: Local Receptive-field Populations: Diversity and Organizationmentioning

confidence: 49%

Section: Introductionmentioning

confidence: 99%

Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex

Bonin

Histed²,

Yurgenson³

et al. 2011

J. Neurosci.

238

217

View full text Add to dashboard Cite

show abstract

“…Multiphoton microscopy has several advantages over traditional confocal microscopy, providing high-resolution images at increased imaging depths, minimal out-of-plane absorption, and inherent optical sectioning. With a tunable near-IR laser source, multiphoton microscopy also provides simultaneous endogenous contrast through cellular two-photon excited fluorescence (2PEF) and extracellular second harmonic generation (SHG) contrast of collagen fibrils (15,19) as well as exogenous contrast with 2PEF of contrast agents such as green fluorescent protein (20) or SHG of styryl dyes (21).…”

Section: Introductionmentioning

confidence: 99%

Endogenous Optical Biomarkers of Ovarian Cancer Evaluated with Multiphoton Microscopy

Kirkpatrick

Brewer

Utzinger

2007

Cancer Epidemiology, Biomarkers &Amp; Prevention

131

132

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Purpose: Among gynecologic cancers, ovarian cancer is the second most common and has the highest mortality. Currently, there is no accurate early diagnostic technique for ovarian cancer. Furthermore, little is understood regarding the early progression of this disease. We have imaged multiphoton interactions of endogenous tissue constituents from normal and abnormal ovarian biopsies that were kept viable during transport from the operating room and microscopy. Experimental Design: The ovarian surface and underlying stroma were assessed with two-photon excited fluorescence (2PEF) and second harmonic generation (SHG). High-resolution, optically sectioned images were analyzed for epithelial morphology based on 2PEF and collagen density and structural integrity based on SHG. Additionally, multiwavelength 2PEF provided an estimation of the cellular redox ratio of epithelial cells.

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“…This conclusion contrasts with activity-dependent models. Although memory consolidation requires expression of immediate early genes like Arc (10,(13)(14)(15), it is unknown if Arc is required for plasticity in cortical regions that lack stimulus-induced activity. Although Arc expression has been observed with high levels of neuronal activity (16)(17)(18)(19)(20)(21), such activity is not always sufficient (22)(23)(24).…”

mentioning

confidence: 99%

Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

Carpenter-Hyland

Plummer

Vazdarjanova

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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Models of learning-dependent sensory cortex plasticity require local activity and reinforcement. An alternative proposes that neural activity involved in anticipation of a sensory stimulus, or the preparatory set, can direct plasticity so that changes could occur in regions of sensory cortex lacking activity. To test the necessity of target-induced activity for initial sensory learning, we trained rats to detect a low-frequency sound. After learning, Arc expression and physiologically measured neuroplasticity were strong in a high-frequency auditory cortex region with very weak target-induced activity in control animals. After 14 sessions, Arc and neuroplasticity were aligned with target-induced activity. The temporal and topographic correspondence between Arc and neuroplasticity suggests Arc may be intrinsic to the neuroplasticity underlying perceptual learning. Furthermore, not all neuroplasticity could be explained by activity-dependent models but can be explained if the neural activity involved in the preparatory set directs plasticity.rat | instrumental learning | neurophysiology T he brain's ability to modify its own structure and function is currently used in diverse therapies involving remediation of language-learning impairment, reversing age-related cognitive decline, stroke rehabilitation, and others. These powers of neuroplasticity stem from the mammalian brain's ability to reorganize in response to experience (1-4). In sensory cortex, plasticity induced by sensory tasks optimizes the brain's capacity for future performance through amplifying activity that is most informative about reinforcement (4-6). Dominant models of this plasticity are activity-dependent (2,7,8), and associated learning is presumed to be a function of endogenous processes reliant on gene activation, because long-term plasticity and long-term memory require protein synthesis (9) following expression of immediate-early genes such as Arc (10, 11). Although models of sensory cortex plasticity are dependent on activity, these models fail to account for plasticity and behavioral phenomena observed shortly after learning.A prediction of activity-dependent models is that the strongest and most selective population responses to a target stimulus should grow the most. However, in contrast to this prediction, cortical patterns of activity early after learning enter a weakly selective and highly responsive state that is subsequently refined into a highly selective and less responsive state (3). The same phenomenon is reflected behaviorally. If auditory stimuli are paired with nucleus basalis stimulation, acoustically induced changes in respiratory rate can initially be induced by a wide range of sound frequencies, and these induced respiratory changes become more frequency-specific with time (12). These findings suggest that cortical regions representing sensory stimuli other than the learned sensory stimulus may be recruited in brain plasticity shortly after learning. This conclusion contrasts with activity-dependent models. Although memor...

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In Vivo Two-Photon Imaging Reveals a Role of Arc in Enhancing Orientation Specificity in Visual Cortex

Cited by 215 publications

References 39 publications

Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex

Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex

Endogenous Optical Biomarkers of Ovarian Cancer Evaluated with Multiphoton Microscopy

Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

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