Predictive coding of natural images by V1 firing rates and rhythmic synchronization

Uran, Cem; Peter, Alina; Lazar, Andreea; Barnes, William; Klon-Lipok, Johanna; Shapcott, Katharine A; Roese, Rasmus; Fries, Pascal; Singer, Wolf; Vinck, Martin

doi:10.1016/j.neuron.2022.01.002

Cited by 35 publications

(41 citation statements)

References 143 publications

(249 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This consistent set of findings from Shirhatti and colleagues [ 2 ] provides critical support for the center-surround prediction theory of gamma genesis [ 5 ], which was also recently tested for uniform color stimuli [ 7 ] and complex images [ 8 ]. These findings prompt us to reconsider prior theories, such that visual gamma’s primary function may not be that of a general mechanism for coordinating visual circuit interactions, but rather, a contextually specific mechanism for the efficient processing of redundant (i.e., predictable) feature configurations in the visual world [ 5 ].…”

supporting

confidence: 74%

“…These findings prompt us to reconsider prior theories, such that visual gamma’s primary function may not be that of a general mechanism for coordinating visual circuit interactions, but rather, a contextually specific mechanism for the efficient processing of redundant (i.e., predictable) feature configurations in the visual world [ 5 ]. Together, there is now a growing consensus for the types of stimulus configurations optimal for gamma genesis in visual cortex, allowing for impressive prediction of observed gamma amplitude based on knowledge of the stimulus input and RF [ 8 , 9 ]. A critical next step will be examining the occurrence of such stimulus configurations within natural scene statistics and the resulting implications for the functional role of gamma oscillations in natural vision.…”

mentioning

confidence: 99%

“…(C) Grating center-surround manipulations performed by Shirhatti and colleagues (2). Even if grating stimuli fall upon both RF center and surround, small spatial ( 5), orientation (6), phase (7) or contrast (8) discontinuities between the center-surround greatly attenuate gamma amplitude (B; lower) from levels observed for contiguous gratings of the same size (3). RF, receptive field.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Aligning evidence for the genesis of visual gamma oscillations

Foster

Bartoli

2022

PLoS Biol

View full text Add to dashboard Cite

show abstract

supporting

confidence: 74%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Aligning evidence for the genesis of visual gamma oscillations

Foster

Bartoli

2022

PLoS Biol

View full text Add to dashboard Cite

show abstract

“…Previous work has shown that extraclassical surround effects in V1 due to natural images can emerge from predictive feedback signals from higher to lower cortical areas [ 41 ]. In this context, it has also been suggested that gamma and firing rates play complimentary roles as predictive signals for lower and higher order image features respectively [ 42 ]. However, it is not clear how image predictability varies across the discontinuities used in our experiments, and whether it aligns with the observed nonlinear effects on gamma and spiking responses.…”

Section: Discussionmentioning

confidence: 99%

Gamma oscillations in primate primary visual cortex are severely attenuated by small stimulus discontinuities

2022

View full text Add to dashboard Cite

Gamma oscillations (30 to 80 Hz) have been hypothesized to play an important role in feature binding, based on the observation that continuous long bars induce stronger gamma in the visual cortex than bars with a small gap. Recently, many studies have shown that natural images, which have discontinuities in several low-level features, do not induce strong gamma oscillations, questioning their role in feature binding. However, the effect of different discontinuities on gamma has not been well studied. To address this, we recorded spikes and local field potential from 2 monkeys while they were shown gratings with discontinuities in 4 attributes: space, orientation, phase, or contrast. We found that while these discontinuities only had a modest effect on spiking activity, gamma power drastically reduced in all cases, suggesting that gamma could be a resonant phenomenon. An excitatory–inhibitory population model with stimulus-tuned recurrent inputs showed such resonant properties. Therefore, gamma could be a signature of excitation–inhibition balance, which gets disrupted due to discontinuities.

show abstract

“…Detrending amounts to highpass filtering because the Fourier amplitudes of a ramp decay as 1/ω 2 , and therefore introduces spurious spectral peaks (Figure 1-2). Instead of detrending in the time-domain, fitting AR(1)s or 1/ f a models and detecting peaks on normalized spectra is preferable (e.g., similar to (Peter et al, 2019;Uran et al, 2022;Hermes et al, 2015;Donoghue et al, 2020;Wen and Liu, 2016)).…”

Section: Technical Note On Analyzing Spectramentioning

confidence: 99%

Aperiodic processes explaining rhythms in behavior: A matter of false detection or definition?

Vinck¹,

Uran²,

Schneider³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

Behavioral studies suggest attention-related performancefluctuates at a 3-8Hz rhythm (Landau and Fries, 2012;Fiebelkorn et al., 2013). Brookshire (2022) argues that theseprevious studies failed to distinguish periodic from aperiodicprocesses, which led to the spurious detection of rhythms. Theargument is based on simulations of accuracy time courses(ATCs) by autoregressive models of order 1 (AR(1)), which is aknown aperiodic process. Brookshire shows that for this aperi-odic process, conventional methods often detect spurious peaksin the 3-8Hz range. Here, we argue that stationary stochasticAR(1) processes are invalid models of ATCs in general as ATCsare deterministic, non-stationary signals. When AR(1) realiza-tions are taken as models for deterministic signals, they do notconstitute per definition aperiodic processes. It is therefore notclear whether previous methods indeed detected rhythms spuri-ously. Furthermore, we show that because Brookshire’s methodrelies on AR(1) model fits, it can have very low sensitivity whennon-rhythmic signals are superimposed onto rhythmic signals.Here, we argue that an appropriate model of an ATCs is a de-terministic signal (akin to an impulse response or event-relatedpotential) with additive white noise due to random sampling ofhits and misses. Such a deterministic ATC can be either peri-odic or aperiodic. We show that when the deterministic ATC istruly aperiodic, detrending and random sampling lead to spu-rious rhythm detection. This supports the general point thatprevious studies did not adequately distinguish periodic fromaperiodic processes. Our analysis naturally suggests an effec-tive alternative method based on cross-validation which avoidsthe use of AR(1) models.

show abstract

Predictive coding of natural images by V1 firing rates and rhythmic synchronization

Cited by 35 publications

References 143 publications

Aligning evidence for the genesis of visual gamma oscillations

Aligning evidence for the genesis of visual gamma oscillations

Gamma oscillations in primate primary visual cortex are severely attenuated by small stimulus discontinuities

Aperiodic processes explaining rhythms in behavior: A matter of false detection or definition?

Contact Info

Product

Resources

About