Attentional Modulation of fMRI Responses in Human V1 Is Consistent with Distinct Spatial Maps for Chromatically Defined Orientation and Contrast

Song, Joo‐Hyun; Rowland, Jess; McPeek, Robert M.; Wade, Alex R.

doi:10.1523/jneurosci.0580-11.2011

Cited by 7 publications

(4 citation statements)

References 50 publications

(67 reference statements)

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“…The ratio between the response amplitude to the luminance (L) and chromatic (C) components of the compound grating was unimodally distributed and pronouncedly biased towards luminance (mean L/C = 4.31 in V1 linear cells), indicating that V1 responds ∼4 times more robustly to the luminance than to chromatic contrast (∼2 times if the luminance contrast is equalized to the chromatic cone contrast). The luminance/color preference of V1 linear neurons was correlated with their OS, a finding that adds a novel perspective to an ongoing discussion on the neuronal encoding of color and orientation in the primary visual cortex (Livingstone and Hubel 1984;Johnson et al 2001Johnson et al , 2008Gegenfurtner 2003;Economides et al 2011;Song et al 2011). We also demonstrate that V1 cells associated with positive LFPs in deep cortical layers (the subcortical output of area V1) show stronger combined responses to luminance and color than other V1 cells.…”

Section: Discussionsupporting

confidence: 59%

Mixing of Chromatic and Luminance Retinal Signals in Primate Area V1

Chen

Lashgari

et al. 2014

Cerebral Cortex

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Vision emerges from activation of chromatic and achromatic retinal channels whose interaction in visual cortex is still poorly understood. To investigate this interaction, we recorded neuronal activity from retinal ganglion cells and V1 cortical cells in macaques and measured their visual responses to grating stimuli that had either luminance contrast (luminance grating), chromatic contrast (chromatic grating), or a combination of the two (compound grating). As with parvocellular or koniocellular retinal ganglion cells, some V1 cells responded mostly to the chromatic contrast of the compound grating. As with magnocellular retinal ganglion cells, other V1 cells responded mostly to the luminance contrast and generated a frequency-doubled response to equiluminant chromatic gratings. Unlike magnocellular and parvocellular retinal ganglion cells, V1 cells formed a unimodal distribution for luminance/color preference with a 2- to 4-fold bias toward luminance. V1 cells associated with positive local field potentials in deep layers showed the strongest combined responses to color and luminance and, as a population, V1 cells encoded a diverse combination of luminance/color edges that matched edge distributions of natural scenes. Taken together, these results suggest that the primary visual cortex combines magnocellular and parvocellular retinal inputs to increase cortical receptive field diversity and to optimize visual processing of our natural environment.

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Section: Discussionsupporting

confidence: 59%

Mixing of Chromatic and Luminance Retinal Signals in Primate Area V1

Chen

Lashgari

et al. 2014

Cerebral Cortex

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“…Second, in posterior brain areas, the target region of attentional control, attention to some specific stimulus dimension increases the level of baseline activity in the corresponding sensory region, even when visual stimulation is kept constant (Martinez-Trujillo & Treue, 2004; Serences, Saproo, Scolari, Ho, & Muftuler, 2009; Song, Rowland, McPeek, & Wade, 2011). …”

Section: Identifying General Principles Underlying Conscious and Uncomentioning

confidence: 99%

“…Neuroimaging studies in human participants showed that perceiving a cue that indicates what will be the relevant dimension of the target is associated first with increased activity in prefrontal areas ( Bode & Haynes, 2008 ; Hopfinger, Buonocore, & Mangun, 2000 ; Hopfinger, Woldorff, Fletcher, & Mangun, 2001 ). Second, in posterior brain areas, the target region of attentional control, attention to some specific stimulus dimension increases the level of baseline activity in the corresponding sensory region, even when visual stimulation is kept constant ( Martinez-Trujillo & Treue, 2004 ; Serences, Saproo, Scolari, Ho, & Muftuler, 2009 ; Song, Rowland, McPeek, & Wade, 2011 ).…”

Section: Identifying General Principles Underlying Conscious and Uncomentioning

confidence: 99%

Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

Kiefer¹,

Ansorge²,

Haynes³

et al. 2011

Advances in Cognitive Psychology

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Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research.

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“…Even within a particular age group, there is remarkable inter-individual variability in anatomy both at the level of whole tissue volume/thickness and cortical morphology. For example, brain volume across 30 individuals aged (18–35) was found to vary by as much as 40% (Song et al, 2011). Cortical gyri-sulci morphology (contours, folding patterns, functional localization) are complex and are characterized by high inter-individual variability (Mangin et al, 2004; Derrfuss et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Inter-Individual Variation during Transcranial Direct Current Stimulation and Normalization of Dose Using MRI-Derived Computational Models

Datta¹,

Truong²,

Minhas³

et al. 2012

Front. Psychiatry

378

324

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Background: Transcranial Direct Current Stimulation (tDCS) is a non-invasive, versatile, and safe neuromodulation technology under investigation for the treatment of neuropsychiatric disorders, adjunct to rehabilitation, and cognitive enhancement in healthy adults. Despite promising results, there is variability in responsiveness. One potential source of variability is the intensity of current delivered to the brain which is a function of both the operator controlled tDCS dose (electrode montage and total applied current) and subject specific anatomy. We are interested in both the scale of this variability across anatomical typical adults and methods to normalize inter-individual variation by customizing tDCS dose. Computational FEM simulations are a standard technique to predict brain current flow during tDCS and can be based on subject specific anatomical MRI. Objective: To investigate this variability, we modeled multiple tDCS montages across three adults (ages 34–41, one female). Results: Conventional pad stimulation led to diffuse modulation with maximum current flow between the pads across all subjects. There was high current flow directly under the pad for one subject while the location of peak induced cortical current flow was variable. The High-Definition tDCS montage led to current flow restricted to within the ring perimeter across all subjects. The current flow profile across all subjects and montages was influenced by details in cortical gyri/sulci. Conclusion: This data suggests that subject specific modeling can facilitate consistent and more efficacious tDCS.

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Attentional Modulation of fMRI Responses in Human V1 Is Consistent with Distinct Spatial Maps for Chromatically Defined Orientation and Contrast

Cited by 7 publications

References 50 publications

Mixing of Chromatic and Luminance Retinal Signals in Primate Area V1

Mixing of Chromatic and Luminance Retinal Signals in Primate Area V1

Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

Inter-Individual Variation during Transcranial Direct Current Stimulation and Normalization of Dose Using MRI-Derived Computational Models

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