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:10.1016/j.neuron.2020.12.013

Cited by 40 publications

(33 citation statements)

References 75 publications

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“…We hypothesized that heterogeneous changes in noise correlations arise from the modulation of On-Off dynamics propagating locally across columns. 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. 1 b).…”

Section: Introductionmentioning

confidence: 98%

“…1 b). The On and Off phases of population activity persist on the timescale of ~100 ms with exponentially distributed durations 22 , 23 and correlate with large fluctuations in neurons’ membrane potentials 24 , 25 , which are signatures of bistable dynamics 26 . 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 .…”

Section: Introductionmentioning

confidence: 99%

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Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex

et al. 2022

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Correlated activity fluctuations in the neocortex influence sensory responses and behavior. Neural correlations reflect anatomical connectivity but also change dynamically with cognitive states such as attention. Yet, the network mechanisms defining the population structure of correlations remain unknown. We measured correlations within columns in the visual cortex. We show that the magnitude of correlations, their attentional modulation, and dependence on lateral distance are explained by columnar On-Off dynamics, which are synchronous activity fluctuations reflecting cortical state. We developed a network model in which the On-Off dynamics propagate across nearby columns generating spatial correlations with the extent controlled by attentional inputs. This mechanism, unlike previous proposals, predicts spatially non-uniform changes in correlations during attention. We confirm this prediction in our columnar recordings by showing that in superficial layers the largest changes in correlations occur at intermediate lateral distances. Our results reveal how spatially structured patterns of correlated variability emerge through interactions of cortical state dynamics, anatomical connectivity, and attention.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex

et al. 2022

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“…To understand how information within and between areas is conveyed as a function of cognitive task, we performed simultaneous laminar recordings in areas V1 and V4 using 16-contact laminar probes while macaque monkeys performed a feature-based spatial attention task (22). We quantified communication between laminae and areas by measuring Granger causality (GC) using locally referenced LFP signals.…”

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confidence: 99%

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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“…The main task and stimuli have been described previously (Ferro et al, 2021;Thiele et al, 2016;van Kempen et al, 2021). In brief, the monkey initiated a trial by holding a lever and fixating a white fixation spot (0.1°) displayed on a grey background (1.41 cd/m 2 ).…”

Section: Behavioral Paradigmsmentioning

confidence: 99%

Dopamine influences attentional rate modulation in Macaque posterior parietal cortex

Kempen

Brandt

Distler

et al. 2020

Preprint

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Selective attention facilitates the prioritization of task-relevant sensory inputs over those which are irrelevant. Although cognitive neuroscience has made great strides in understanding the neural substrates of attention, our understanding of its neuropharmacology is incomplete. Cholinergic and glutamatergic contributions have been demonstrated, but emerging evidence also suggests an important influence of dopamine (DA). DA has historically been investigated in the context of frontal/prefrontal function arguing that dopaminergic receptor density in the posterior/parietal cortex is sparse. However, this notion was derived from rodent data, whereas in primates DA innervation in parietal cortex matches that of many prefrontal areas. We recorded single- and multi-unit activity whilst iontophoretically administering dopaminergic agonists and antagonists to posterior parietal cortex of rhesus macaques engaged in a spatial attention task. Out of 88 neurons, 50 showed modulation of activity induced by drug administration. Dopamine inhibited firing rates across the population according to an inverted-U shaped dose-response curve. D1 receptor antagonists diminished firing rates in broad-spiking units according to a monotonically increasing function. Additionally, dopamine modulated attentional signals in broad, but not narrow-spiking cells. Finally, both drugs modulated the pupil light reflex. These data show that dopamine plays an important role in shaping neuronal responses and modulates attentional processing in macaque parietal cortex.Significance statementDopamine is critically involved in high-level cognitive functions, and dopaminergic dysfunctions pertain to ageing and neurological and psychiatric disorders. Most previous studies focused on dopaminergic effects on prefrontal activity or its role in basal ganglia circuitry. The effects of dopamine in other brain areas such as parietal cortex, despite its well-established role in cognition and cognitive dysfunction, have largely been overlooked. This study is the first to show dopaminergic modulation of parietal activity in general, and specific to spatial attention in the non-human primate, revealing cell-type specific effects of dopamine on attentional modulation.

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Top-down coordination of local cortical state during selective attention

Cited by 40 publications

References 75 publications

Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex

Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex

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

Dopamine influences attentional rate modulation in Macaque posterior parietal cortex

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