scholarly journals Attention selectively gates afferent signal transmission to area V4

2015 ◽  
Author(s):  
Iris Grothe ◽  
David Rotermund ◽  
Simon D. Neitzel ◽  
Sunita Mandon ◽  
Udo A. Ernst ◽  
...  

Selective attention causes visual cortical neurons to act as if only one of multiple stimuli are within their receptive fields. This suggests that attention employs a, yet unknown, neuronal gating mechanism for transmitting only the information that is relevant for the current behavioral context. We introduce an experimental paradigm to causally investigate this putative gating and the mechanism underlying selective attention by determining the signal availability of two time-varying stimuli in local field potentials of V4 neurons. We find transmission of the low frequency (<20Hz) components only from the attended visual input signal and that the higher frequencies from both stimuli are attenuated. A minimal model implementing routing by synchrony replicates the attentional gating effect and explains the spectral transfer characteristics of the signals. It supports the proposal that selective gamma-band synchrony subserves signal routing in cortex and further substantiates our experimental finding that attention selectively gates signals already at the level of afferent synaptic input.

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Bram-Ernst Verhoef ◽  
John HR Maunsell

Shifting attention among visual stimuli at different locations modulates neuronal responses in heterogeneous ways, depending on where those stimuli lie within the receptive fields of neurons. Yet how attention interacts with the receptive-field structure of cortical neurons remains unclear. We measured neuronal responses in area V4 while monkeys shifted their attention among stimuli placed in different locations within and around neuronal receptive fields. We found that attention interacts uniformly with the spatially-varying excitation and suppression associated with the receptive field. This interaction explained the large variability in attention modulation across neurons, and a non-additive relationship among stimulus selectivity, stimulus-induced suppression and attention modulation that has not been previously described. A spatially-tuned normalization model precisely accounted for all observed attention modulations and for the spatial summation properties of neurons. These results provide a unified account of spatial summation and attention-related modulation across both the classical receptive field and the surround.


2009 ◽  
Vol 26 (4) ◽  
pp. 411-420 ◽  
Author(s):  
MICHAEL L. RISNER ◽  
TIMOTHY J. GAWNE

AbstractNeurons in visual cortical area V1 typically respond well to lines or edges of specific orientations. There have been many studies investigating how the responses of these neurons to an oriented edge are affected by changes in luminance contrast. However, in natural images, edges vary not only in contrast but also in the degree of blur, both because of changes in focus and also because shadows are not sharp. The effect of blur on the response dynamics of visual cortical neurons has not been explored. We presented luminance-defined single edges in the receptive fields of parafoveal (1–6 deg eccentric) V1 neurons of two macaque monkeys trained to fixate a spot of light. We varied the width of the blurred region of the edge stimuli up to 0.36 deg of visual angle. Even though the neurons responded robustly to stimuli that only contained high spatial frequencies and 0.36 deg is much larger than the limits of acuity at this eccentricity, changing the degree of blur had minimal effect on the responses of these neurons to the edge. Primates need to measure blur at the fovea to evaluate image quality and control accommodation, but this might only involve a specialist subpopulation of neurons. If visual cortical neurons in general responded differently to sharp and blurred stimuli, then this could provide a cue for form perception, for example, by helping to disambiguate the luminance edges created by real objects from those created by shadows. On the other hand, it might be important to avoid the distraction of changing blur as objects move in and out of the plane of fixation. Our results support the latter hypothesis: the responses of parafoveal V1 neurons are largely unaffected by changes in blur over a wide range.


eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Ye Wang ◽  
Valentin Dragoi

Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.


2002 ◽  
Vol 88 (3) ◽  
pp. 1128-1135 ◽  
Author(s):  
Timothy J. Gawne ◽  
Julie M. Martin

We report here results from 45 primate V4 visual cortical neurons to the preattentive presentations of seven different patterns located in two separate areas of the same receptive field and to combinations of the patterns in the two locations. For many neurons, we could not determine any clear relationship for the responses to two simultaneous stimuli. However, for a substantial fraction of the neurons we found that the firing rate was well modeled as the maximum firing rate of each stimulus presented separately. It has previously been proposed that taking the maximum of the inputs (“MAX” operator) could be a useful operation for neurons in visual cortex, although there has until now been little direct physiological evidence for this hypothesis. Our results here provide direct support for the hypothesis that the MAX operator plays a significant (although certainly not exclusive) role in generating the receptive field properties of visual cortical neurons.


Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 375-375
Author(s):  
K Suder ◽  
K Funke ◽  
F Woergoetter

Cells in the lateral geniculate nucleus (LGN) strongly change their behaviour covarying with different EEG states. During sleep and drowsiness (synchronised alpha, delta-wave EEG) short transient responses prevail whereas during a desynchronised ‘alert’ EEG (beta-waves) long-lasting tonic responses are observed. We propose that this is part of a mechanism used to restructure the spatial and temporal characteristics of the receptive fields in LGN and cortex reflecting changing states of selective attention. To this end we present a model of the primary visual pathway using integrate-and-fire neurons to simulate the afferent signal flow (retina, LGN, V1). The model also implements excitatory topographically arranged lateral intracortical and corticofugal connections which act as a positive feedback and trigger spatial winner-takes-all (WTA) mechanisms enhanced by lateral inhibition at both levels. Furthermore, the LGN membrane characteristic can switch from phasic (hyperpolarised) low-threshold Ca2+ bursting mode to tonic (depolarised) signal-transmission mode. Switching is triggered by feedback and amplified by intracellular intrinsic positive-feedback mechanisms in the model LGN. All positive-feedback mechanisms are subject to damping such that they remain ineffective below a certain threshold. Salient stimuli which ‘attract attention’ will push the system above threshold and a self-amplifying process is started which sharpens the cortical receptive fields spatially (by spatial WTA) and drives the winners in the LGN into signal transmission mode (by intrinsic intracellular mechanisms). These results predicted by the model are in accordance with LGN cell behaviour. In addition, the model predicts that cortical receptive fields should be wider during synchronised EEG than during desynchronised EEG.


1993 ◽  
Vol 70 (3) ◽  
pp. 909-919 ◽  
Author(s):  
B. C. Motter

1. The activity of single neurons was recorded in Macaca mulatta monkeys while they performed tasks requiring them to select a cued stimulus from an array of three to eight stimuli and report the orientation of that stimulus. Stimuli were presented in a circular array centered on the fixation target and scaled to place a single stimulus element within the receptive field of the neuron under study. The timing of the cuing event permitted the directing of visual attention to the spatial location of the correct stimulus before its presentation. 2. The effects of focal attention were examined in cortical visual areas V1, V2, and V4, where a total of 672 neurons were isolated with complete studies obtained for 94 V1, 74 V2, and 74 V4 neurons with receptive-field center eccentricities in the range 1.8-8 degrees. Under certain conditions, directed focal attention results in changes in the response of V1, V2, and V4 neurons to otherwise identical stimuli at spatially specific locations. 3. More than one-third of the neurons in each area displayed differential sensitivity when attention was directed toward versus away from the spatial location of the receptive field just before and during stimulus presentation. Both relative increases and decreases in neural activity were observed in association with attention directed at receptive-field stimuli. 4. The presence of multiple competing stimuli in the visual field was a major factor determining the presence or absence of differential sensitivity. About two-thirds of the neurons that were differentially sensitive to the attending condition in the presence of competing stimuli were not differentially sensitive when single stimuli were presented in control studies. For V1 and V2 neurons the presence of only a few (3-4) competing stimuli was sufficient for a majority of the neurons studied; a majority of the V4 neurons required six to eight stimuli in the array before significant differences between attending conditions occurred. 5. For V1 and V2 neurons the neuronal sensitivity differences between attending conditions were observed primarily at or near the peak of the orientation tuning sensitivity for each neuron; the differences were evident over a broader range of orientations in V4 neurons. 6. In conclusion, neural correlates of focal attentive processes can be observed in visual cortical processing in areas V1 and V2 as well as area V4 under conditions that require stimulus feature analysis and selective spatial processing within a field of competing stimuli.(ABSTRACT TRUNCATED AT 400 WORDS)


2011 ◽  
Vol 106 (4) ◽  
pp. 1923-1932 ◽  
Author(s):  
Tomokazu Ohshiro ◽  
Shaista Hussain ◽  
Michael Weliky

Visual cortical neurons are selective for the orientation of lines, and the full development of this selectivity requires natural visual experience after eye opening. Here we examined whether this selectivity develops without seeing lines and contours. Juvenile ferrets were reared in a dark room and visually trained by being shown a movie of flickering, sparse spots. We found that despite the lack of contour visual experience, the cortical neurons of these ferrets developed strong orientation selectivity and exhibited simple-cell receptive fields. This finding suggests that overt contour visual experience is unnecessary for the maturation of orientation selectivity and is inconsistent with the computational models that crucially require the visual inputs of lines and contours for the development of orientation selectivity. We propose that a correlation-based model supplemented with a constraint on synaptic strength dynamics is able to account for our experimental result.


1980 ◽  
Vol 12 (2) ◽  
pp. 77-84
Author(s):  
I. A. Shevelev ◽  
V. G. Marchenko ◽  
I. V. Maksimova

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