scholarly journals Microsaccades mediate a bottom-up mechanism for cross-frequency coupling in early visual cortex (Commentary on Lowetet al.)

2016 ◽  
Vol 43 (10) ◽  
pp. 1284-1285 ◽  
Author(s):  
Leon Y. Deouell
2018 ◽  
Author(s):  
Christian D. Márton ◽  
Makoto Fukushima ◽  
Corrie R. Camalier ◽  
Simon R. Schultz ◽  
Bruno B. Averbeck

AbstractPredictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom up interactions in sensory processing. The theory has suggested that specific frequency bands relay bottom-up and top-down information (e.g. “γ up, β down”). But it remains unclear whether this notion generalizes to cross-frequency interactions. Furthermore, most of the evidence so far comes from visual pathways. Here we examined cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up made prominent use of low frequencies: low-to-low frequency (θ, α, β) and low frequency-to-high γ couplings were predominant top-down, while low frequency-to-low γ couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting they are a general feature of information processing in auditory cortex. Moreover, our findings showed that low-frequency PAC alternated between predominantly top-down or bottom-up over time. Altogether, this suggests sensory information need not be propagated along separate frequencies upwards and downwards. Rather, information can be unmixed by having low frequencies couple to distinct frequency ranges in the target region, and by alternating top-down and bottom-up processing over time.1SignificanceThe brain consists of highly interconnected cortical areas, yet the patterns in directional cortical communication are not fully understood, in particular with regards to interactions between different signal components across frequencies. We employed a a unified, computationally advantageous Granger-causal framework to examine bi-directional cross-frequency interactions across four sectors of the auditory cortical hierarchy in macaques. Our findings extend the view of cross-frequency interactions in auditory cortex, suggesting they also play a prominent role in top-down processing. Our findings also suggest information need not be propagated along separate channels up and down the cortical hierarchy, with important implications for theories of information processing in the brain such as predictive coding.


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.


eNeuro ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. ENEURO.0467-18.2019 ◽  
Author(s):  
Christian D. Márton ◽  
Makoto Fukushima ◽  
Corrie R. Camalier ◽  
Simon R. Schultz ◽  
Bruno B. Averbeck

2003 ◽  
Vol 15 (7) ◽  
pp. 925-934 ◽  
Author(s):  
Andrea Mechelli ◽  
Cathy J. Price ◽  
Uta Noppeney ◽  
Karl J. Friston

In this study, we combined functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate whether object category effects in the occipital and temporal cortex are mediated by inputs from early visual cortex or parietal regions. Resolving this issue may provide anatomical constraints on theories of category specificity— which make different assumptions about the underlying neurophysiology. The data were acquired by Ishai, Ungerleider, Martin, Schouten, and Haxby (1999, 2000) and provided by the National fMRI Data Center (http://www.fmridc.org). The original authors used a conventional analysis to estimate differential effects in the occipital and temporal cortex in response to pictures of chairs, faces, and houses. We extended this approach by estimating neuronal interactions that mediate category effects using DCM. DCM uses a Bayesian framework to estimate and make inferences about the influence that one region exerts over another and how this is affected by experimental changes. DCM differs from previous approaches to brain connectivity, such as multivariate autoregressive models and structural equation modeling, as it assumes that the observed hemodynamic responses are driven by experimental changes rather than endogenous noise. DCM therefore brings the analysis of brain connectivity much closer to the analysis of regionally specific effects usually applied to functional imaging data. We used DCM to estimate the influence that V3 and the superior/inferior parietal cortex exerted over category-responsive regions and how this was affected by the presentation of houses, faces, and chairs. We found that category effects in occipital and temporal cortex were mediated by inputs from early visual cortex. In contrast, the connectivity from the superior/inferior parietal area to the category-responsive areas was unaffected by the presentation of chairs, faces, or houses. These findings indicate that category effects in the occipital and temporal cortex can be mediated by bottom–up mechanisms—a finding that needs to be embraced by models of category specificity.


Science ◽  
2008 ◽  
Vol 321 (5887) ◽  
pp. 414-417 ◽  
Author(s):  
L. B. Ekstrom ◽  
P. R. Roelfsema ◽  
J. T. Arsenault ◽  
G. Bonmassar ◽  
W. Vanduffel

2020 ◽  
Author(s):  
Gokulraj T. Prabhakaran ◽  
Khaldoon O. Al-Nosairy ◽  
Claus Tempelmann ◽  
Markus Wagner ◽  
Hagen Thieme ◽  
...  

AbstractfMRI studies in macular degeneration (MD) and retinitis pigmentosa (RP) demonstrated that responses in the lesion projection zones (LPZ) of V1 are task related, indicating significant limits of bottom-up visual system plasticity in MD and RP. In advanced glaucoma (GL), a prevalent eye disease and leading cause of blindness, the scope of visual system plasticity is currently unknown. We performed 3T fMRI in patients with extensive visual field defects due to GL (n=5), RP (n=2) and healthy controls (n=7; with simulated defects). Participants viewed contrast patterns drifting in 8 directions alternating with uniform gray and performed 3 tasks: (1) passive viewing (PV), (2) one-back task (OBT) and (3) fixation-dot task (FDT). During PV, they passively viewed the stimulus with central fixation, during OBT they reported the succession of the same two motion directions, and during FDT a change in the fixation color. In GL, LPZ responses of the early visual cortex (V1, V2 and V3) shifted from negative during PV to positive for OBT [p (corrected): V1(0.006); V2(0.04); V3(0.008)], while they were negative in the controls’ simulated LPZ for all stimulation conditions. For RP a similar pattern as for GL was observed. Consequently, activity in the de-afferented visual cortex in glaucoma is, similar to MD and RP, task-related. In conclusion, the lack of bottom-up plasticity appears to be a general feature of the human visual system. These insights are of importance for the development of treatment and rehabilitation schemes in glaucoma.HighlightsFunctional dynamics of early visual cortex LPZ depend on task demands in glaucomaBrain activity in deprived visual cortex suggests absence of large-scale remappingLimited scope of bottom-up plasticity is a general feature of human visual systemVisual system stability and plasticity is of relevance for therapeutic advances


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.


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