Relative precision of top-down attentional modulations is lower in early visual cortex compared to mid- and high-level visual areas

Author(s):  
Sunyoung Park ◽  
John T. Serences

Top-down spatial attention enhances cortical representations of behaviorally relevant visual information and increases the precision of perceptual reports. However, little is known about the relative precision of top-down attentional modulations in different visual areas, especially compared to the highly precise stimulus-driven responses that are observed in early visual cortex. For example, the precision of attentional modulations in early visual areas may be limited by the relatively coarse spatial selectivity and the anatomical connectivity of the areas in prefrontal cortex that generate and relay the top-down signals. Here, we used fMRI and human participants to assess the precision of bottom-up spatial representations evoked by high contrast stimuli across the visual hierarchy. Then, we examined the relative precision of top-down attentional modulations in the absence of spatially-specific bottom-up drive. While V1 showed the largest relative difference between the precision of top-down attentional modulations and the precision of bottom-up modulations, mid-level areas such as V4 showed relatively smaller differences between the precision of top-down and bottom-up modulations. Overall, this interaction between visual areas (e.g. V1 vs V4) and the relative precision of top-down and bottom-up modulations suggests that the precision of top-down attentional modulations is limited by the representational fidelity of areas that generate and relay top-down feedback signals.

2021 ◽  
Vol 14 ◽  
Author(s):  
Huijun Pan ◽  
Shen Zhang ◽  
Deng Pan ◽  
Zheng Ye ◽  
Hao Yu ◽  
...  

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat’s high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II–III, IV, V, and VI, with a higher proportion in layer II–III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support “reverse hierarchy theory” or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.


2014 ◽  
Vol 26 (10) ◽  
pp. 2370-2384 ◽  
Author(s):  
Ramakrishna Chakravarthi ◽  
Thomas A. Carlson ◽  
Julie Chaffin ◽  
Jeremy Turret ◽  
Rufin VanRullen

Objects occupy space. How does the brain represent the spatial location of objects? Retinotopic early visual cortex has precise location information but can only segment simple objects. On the other hand, higher visual areas can resolve complex objects but only have coarse location information. Thus coarse location of complex objects might be represented by either (a) feedback from higher areas to early retinotopic areas or (b) coarse position encoding in higher areas. We tested these alternatives by presenting various kinds of first- (edge-defined) and second-order (texture) objects. We applied multivariate classifiers to the pattern of EEG amplitudes across the scalp at a range of time points to trace the temporal dynamics of coarse location representation. For edge-defined objects, peak classification performance was high and early and thus attributable to the retinotopic layout of early visual cortex. For texture objects, it was low and late. Crucially, despite these differences in peak performance and timing, training a classifier on one object and testing it on others revealed that the topography at peak performance was the same for both first- and second-order objects. That is, the same location information, encoded by early visual areas, was available for both edge-defined and texture objects at different time points. These results indicate that locations of complex objects such as textures, although not represented in the bottom–up sweep, are encoded later by neural patterns resembling the bottom–up ones. We conclude that feedback mechanisms play an important role in coarse location representation of complex objects.


eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Ying-Zi Xiong ◽  
Jun-Yun Zhang ◽  
Cong Yu

Perceptual learning is often orientation and location specific, which may indicate neuronal plasticity in early visual areas. However, learning specificity diminishes with additional exposure of the transfer orientation or location via irrelevant tasks, suggesting that the specificity is related to untrained conditions, likely because neurons representing untrained conditions are neither bottom-up stimulated nor top-down attended during training. To demonstrate these top-down and bottom-up contributions, we applied a “continuous flash suppression” technique to suppress the exposure stimulus into sub-consciousness, and with additional manipulations to achieve pure bottom-up stimulation or top-down attention with the transfer condition. We found that either bottom-up or top-down influences enabled significant transfer of orientation and Vernier discrimination learning. These results suggest that learning specificity may result from under-activations of untrained visual neurons due to insufficient bottom-up stimulation and/or top-down attention during training. High-level perceptual learning thus may not functionally connect to these neurons for learning transfer.


2018 ◽  
Author(s):  
Hyehyeon Kim ◽  
Gayoung Kim ◽  
Sue-Hyun Lee

AbstractTop-down signals can influence our visual perception by providing guidance on information processing. Especially, top-down control between two basic frameworks, “Individuation” and “grouping”, is critical for information processing during face perception. Individuation of faces supports identity recognition while grouping subserves higher category level face perception such as race or gender. However, it still remains elusive how top-down dependent control between individuation and grouping affects cortical representations during face perception. Here we performed an fMRI experiment to investigate whether representations across early and high-level visual areas can be altered by top-down control between individuation and grouping process during face perception. Focusing on neural response patterns across the early visual cortex (EVC) and the face-selective area (the fusiform face area (FFA)), we found that the discriminability of individual faces from the response patterns was strong in the FFA but weak in the EVC during the individuation task whereas the EVC but not the FFA showed significant face discrimination during the grouping tasks. Thus, these findings suggest that the representation of face information across the early and high-level visual cortex is flexible depending on the top-down control of the perceptual framework between individuation and grouping.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Domenica Veniero ◽  
Joachim Gross ◽  
Stephanie Morand ◽  
Felix Duecker ◽  
Alexander T. Sack ◽  
...  

AbstractVoluntary allocation of visual attention is controlled by top-down signals generated within the Frontal Eye Fields (FEFs) that can change the excitability of lower-level visual areas. However, the mechanism through which this control is achieved remains elusive. Here, we emulated the generation of an attentional signal using single-pulse transcranial magnetic stimulation to activate the FEFs and tracked its consequences over the visual cortex. First, we documented changes to brain oscillations using electroencephalography and found evidence for a phase reset over occipital sites at beta frequency. We then probed for perceptual consequences of this top-down triggered phase reset and assessed its anatomical specificity. We show that FEF activation leads to cyclic modulation of visual perception and extrastriate but not primary visual cortex excitability, again at beta frequency. We conclude that top-down signals originating in FEF causally shape visual cortex activity and perception through mechanisms of oscillatory realignment.


2010 ◽  
Vol 68 ◽  
pp. e380
Author(s):  
Tomoki Fukai ◽  
Nobuhiko Wagatsuma ◽  
Tobias C. Potjans ◽  
Markus Diesmann

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