Temporal dynamics of binocular integration in primary visual cortex

Maier

Schall

2020

eNeuro

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Visual search performance varies with stimulus and response history. Priming of pop-out refers to increased accuracy and reduced response time with repeated presentation of particular singleton and distractor features (e.g., a red target among green distractor stimuli), which are abruptly impaired when singleton and distractor features swap (e.g., green target among red distractors). Meanwhile, inhibition of return refers to slowing of response time when target location repeats. Neurophysiological correlates of both these phenomena have been reported in the frontal eye field (FEF), an area in the frontal lobe contributing to attentional selection and eye movement planning. To understand the mechanistic origin of these adaptive behaviors, we investigated visual cortical area V4, an area providing input to and receiving feedback from FEF, during feature-based priming of popout and location-based inhibition of return. Performing a color pop-out task, monkeys exhibited pronounced priming of pop-out and inhibition of return. Neural spiking from V4 revealed earlier target selection associated with priming of pop-out and delayed selection associated with inhibition of return. These results demonstrate substantial involvement of extrastriate visual cortex in behavioral priming and inhibition of return. Significance Statement Mid-level attention and visual processing is influenced by recent history of visual stimuli and gaze behavior. Using priming of pop-out visual search, we discovered that neural spiking in extrastriate visual area V4 shows speeded attentional selection when target and distractor features repeat and delayed selection when target location repeats. These neural processes paralleled but did not account for the magnitude of visual search performance changes with stimulus and response history. These new results improve our understanding of how recent experience influences attention and performance.

Section: Experimental Design and Behaviormentioning

confidence: 99%

Priming of Attentional Selection in Macaque Visual Cortex: Feature-Based Facilitation and Location-Based Inhibition of Return

Maier

Schall

2020

eNeuro

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“…Orthogonal array penetrations were confirmed online through a reverse-correlation RF mapping procedure (Nandy et al, 2017;Westerberg et al, 2019;Cox et al, 2019aCox et al, , 2019bDougherty et al, 2019) (Figure S6A). RFs were found to represent portions of visual space consistent with previous reports of V4 (Gattass et al, 1988) (Figure S6D).…”

Section: Laminar Alignmentmentioning

confidence: 96%

Laminar microcircuitry of visual cortex producing attention-associated electric fields

Schall

Maier

et al. 2021

Preprint

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Cognitive 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.

“…Supplementary Figure 2 demonstrates the reliability of these functional markers following alignment of all sessions. Both extracranial to intracranial and gray matter to white matter boundaries were determined by finding the pair of recording electrodes where no multiunit response to visual stimuli was observed on one channel and a significant response was observed on the other (Cox et al, 2019b;Westerberg et al, 2019). Recording channels positioned between these pairs all showed significant responses.…”

Section: Laminar Alignmentmentioning

confidence: 99%

“…That is, we found no instances of a lack of response on a channel determined to be within the gray matter. The L2/3-L4 boundary was set to 0.5 mm above the L4-L5 boundary as we do not have a reliable functional marker and that distance is consistent with histological studies of V1 laminar structure (see Cox et al, 2019b;Westerberg et al, 2019 for details).…”

Section: Laminar Alignmentmentioning

confidence: 99%

“…A long-standing hypothesis is that the eye-specific inputs in the middle layers are merged to a combined (binocular) response in the layers above, even though most V1 neurons maintain preference for one eye over the other (Hubel and Wiesel, 1972;Ohzawa and Freeman, 1986;Prince et al, 2002;Read and Cumming, 2004). Neurons in the uppermost layers of V1 project to neurons in V1's lower layers, so if the upper layers form a combined binocular signal, this signal should be present in the lower layers as well (Hubel and Wiesel, 1972;Cox et al, 2019b;Dougherty et al, 2019a). However, based on several other pieces of empirical evidence, an alternative hypothesis postulates that the two eyes' signals are interacting at or before LGN responses arrive in the middle layers of V1 (see Dougherty et al, 2019b for review).…”

Section: Stimulus Feature-specific Information Within Neural Activatimentioning

confidence: 99%

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Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis

Tovar

Cox

et al. 2020

Front. Syst. Neurosci.

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Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.