Top-down coordination of local cortical state during selective attention

Kempen, Jochem van; Gieselmann, Marc Alwin; Boyd, Michael; Steinmetz, Nicholas A.; Moore, Tirin; Engel, Tatiana A.; Thiele, Alexander

doi:10.1101/2020.03.26.009365

Cited by 13 publications

(17 citation statements)

References 54 publications

(64 reference statements)

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“…The dynamics of individual units reproduce the On-Off transitions in single columns and their modulation during attention. As in the data from visual cortex 22,23 , the durations of On and Off episodes in the model are irregular and exponentially distributed (Fig. 2c).…”

Section: Resultssupporting

confidence: 56%

“…In our columnar recordings, we examined the relationship between the scale of ongoing On-Off dynamics and the magnitude of noise correlations. We quantified the On-Off dynamics by fitting a two-phase Hidden Markov Model (HMM) to the population spiking activity 22,23 (Fig. 1b, Methods).…”

Section: Resultsmentioning

confidence: 99%

“…The key mechanism generating correlated variability in our model is the stochastic On-Off dynamics of the population activity in single columns. In visual cortex of behaving monkeys, the durations of On and Off episodes are distributed exponentially with a timescale of about 100 ms 22,23 , which indicates that the On and Off phases are metastable with transitions driven by noise 27 . Accordingly, we model the dynamics of each unit in the network by a twodimensional dynamical system with two stable fixed points, corresponding to the On and Off phases (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…We hypothesized that heterogeneous changes in noise correlations arise from the modulation of On-Off dynamics propagating through spatially structured cortical connectivity. The On-Off dynamics are spontaneous transitions between phases of vigorous (On) and faint (Off) spiking that occur synchronously across layers of neocortex 20,21 , and are observed in visual cortex of behaving monkeys 22,23 (Fig. 1b).…”

mentioning

confidence: 98%

“…1b). The On-Off dynamics reflect the global cortical state associated with arousal and are also modulated locally within retinotopic maps during selective attention 22,23 . We analyzed spiking activity recorded from single columns in V4 and found that the scale of On-Off dynamics predicted the magnitude of noise correlations and their dependence on lateral distance.…”

mentioning

confidence: 99%

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Influence of On-Off dynamics and selective attention on the spatial pattern of correlated variability in neocortex

Shi

Steinmetz

Moore

et al. 2020

Preprint

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Correlated activity fluctuations in neocortex influence sensory responses and behavior. Neural correlations reflect anatomical connectivity and change dynamically with cognitive states, such as attention. Yet, how anatomical connectivity and cognitive states define the population structure of correlations is not known. We measured correlations in single cortical columns and found that the magnitude of correlations, their attentional modulation and dependence on lateral distance are predicted by On-Off dynamics, synchronous fluctuations in population activity across cortical layers. We developed a network model, in which spatial connectivity correlates the On-Off dynamics across nearby columns. We show that attentional inputs modulate the spatial extent of On-Off dynamics, resulting in spatially non-uniform changes in correlations. We confirm this prediction in our columnar recordings by showing that attentional modulation of correlations depends on lateral distance. Our results reveal how heterogeneous spatial patterns of correlations arise from the connectivity and network dynamics during attention.

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Section: Resultssupporting

confidence: 56%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 98%

mentioning

confidence: 99%

See 3 more Smart Citations

Influence of On-Off dynamics and selective attention on the spatial pattern of correlated variability in neocortex

Shi

Steinmetz

Moore

et al. 2020

Preprint

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Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

et al. 2023

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Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

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Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention

Ferro

Kempen

Boyd

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Achieving behavioral goals requires integration of sensory and cognitive information across cortical laminae and cortical regions. How this computation is performed remains unknown. Using local field potential recordings and spectrally resolved conditional Granger causality (cGC) analysis, we mapped visual information flow, and its attentional modulation, between cortical layers within and between macaque brain areas V1 and V4. Stimulus-induced interlaminar information flow within V1 dominated upwardly, channeling information toward supragranular corticocortical output layers. Within V4, information flow dominated from granular to supragranular layers, but interactions between supragranular and infragranular layers dominated downwardly. Low-frequency across-area communication was stronger from V4 to V1, with little layer specificity. Gamma-band communication was stronger in the feedforward V1-to-V4 direction. Attention to the receptive field of V1 decreased communication between all V1 layers, except for granular-to-supragranular layer interactions. Communication within V4, and from V1 to V4, increased with attention across all frequencies. While communication from V4 to V1 was stronger in lower-frequency bands (4 to 25 Hz), attention modulated cGCs from V4 to V1 across all investigated frequencies. Our data show that top-down cognitive processes result in reduced communication within cortical areas, increased feedforward communication across all frequency bands, and increased gamma-band feedback communication.

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Top-down coordination of local cortical state during selective attention

Cited by 13 publications

References 54 publications

Influence of On-Off dynamics and selective attention on the spatial pattern of correlated variability in neocortex

Influence of On-Off dynamics and selective attention on the spatial pattern of correlated variability in neocortex

Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention

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