Widespread temporal coding of cognitive control in the human prefrontal cortex

Smith, Elliot H.; Horga, Guillermo; Yates, Mark; Mikell, Charles B.; Banks, Garrett P.; Pathak, Yagna; Schevon, Catherine A.; McKhann, Guy M.; Hayden, Benjamin Y.; Botvinick, Matthew; Sheth, Sameer A.

doi:10.1038/s41593-019-0494-0

Cited by 97 publications

(82 citation statements)

References 63 publications

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“…This beta frequency is thus a powerful candidate for distributed information transfer, because spike output of many neurons is concentrated at the same phase and thus activate postsynaptic membranes at similar times. This scenario of beta rhythmic information exchange within fronto-striatal networks is supported by previous nonhuman primate studies that demonstrated 10-25 Hz beta rhythmic synchronization during active task processing states between ACC and LFPC (Smith et al, 2019;Voloh and Womelsdorf, 2017a;Womelsdorf et al, 2014a), between PFC and STR (Antzoulatos and Miller, 2014), between ACC and FEF (Babapoor-Farrokhran et al, 2017), between LPFC and FEF (Antzoulatos and Miller, 2016;Salazar et al, 2012), and between lateral PFC or FEF with posterior parietal cortex (Antzoulatos and Miller, 2016;Buschman and Miller, 2007;Buschman et al, 2012;Dean et al, 2012;Salazar et al, 2012).…”

Section: Distributed Encoding Of Learning Variables At a Shared Beta supporting

confidence: 78%

Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

Voloh

Oemisch

Womelsdorf

2019

Preprint

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KeywordsLearning; beta frequency oscillation; neuronal synchronization; prediction error phase code; anterior cingulate cortex; striatum; lateral prefrontal cortex; reward prediction error, reversal learning Highlights • Lateral prefrontal cortex, anterior cingulate cortex and striatum show phase-of-firing encoding for outcome, outcome history and reward prediction errors.• Neurons with phase-of-firing code synchronize long-range at 10-25 Hz.• Spike phases encoding reward prediction errors deviate from preferred synchronization phases.• Anterior cingulate cortex neurons show strongest long-range effects. AbstractThe prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected the network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that neurons encoding current choice outcomes, outcome prediction errors, and outcome history in their firing rates also carried significant information in their phase-of-firing at a 10-25 Hz beta frequency at which they synchronized across lateral prefrontal cortex, anterior cingulate cortex and striatum. The phase-of-firing code exceeded information that could be obtained from firing rates alone, was strong for inter-areal connections, and multiplexed Combined Manuscript File 2 information at three different phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document the multiplexing of three different types of information in the phase-of-firing at an interareally shared beta oscillation frequency during goal-directed behavior.

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Section: Distributed Encoding Of Learning Variables At a Shared Beta supporting

confidence: 78%

Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

Voloh

Oemisch

Womelsdorf

2019

Preprint

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“…We examined neuronal responses collected from 16 human subjects (dACC: n=7 patients, dlPFC: n=9 patients, see Methods ) performing the multi-source interference task (MSIT; Figure 1A-B ). This task and its close variants have been widely used to study conflict in humans in studies using both mass action measures and intracranial electrophysiology (Sheth et al, 2012; Smith et al, 2019; Widge et al, 2019a). These data were recorded in human dACC and dlPFC ( Figure 1C ).…”

Section: Resultsmentioning

confidence: 99%

“…These data were recorded in human dACC and dlPFC ( Figure 1C ). Some of these data come from a set used in a previous publication that focused on local field potentials, which are not relevant to our hypotheses and are not considered here (Smith et al, 2019). The data we study here do not overlap with those used in Sheth et al (2012), although the tasks are identical.…”

Section: Resultsmentioning

confidence: 99%

“…However, more recent studies have shown single neuron correlates of conflict in non-human animals (Ebitz and Platt, 2015; Bryden et al, 2018; Michelet et al, 2015). Most importantly, studies in human dACC – which lack translational uncertainties associated with model species – provide unambiguous correlates of conflict in both single units and in local field potentials (Sheth et al, 2012; Smith et al, 2019). These results confirm that conflict has direct and measurable neuronal effects but leave unresolved the computations underlying these effects.…”

Section: Introductionmentioning

confidence: 99%

“…The explicit hypothesis proposes that dACC neurons signal conflict abstractly, in the sense that conflict-related modulations serve the purpose of transmitting information about the presence of conflict – in general – to downstream conflict resolution structures, which implement its resolution. These downstream structures likely include the dorsolateral prefrontal cortex (dlPFC, Johnston et al, 2007; Ma et al, 2019; Smith et al, 2019; MacDonald et al, 2000; Shenhav et al, 2013). In this view, dACC contains either a dedicated, discrete set of neurons specialized for encoding conflict or else its neurons have a distinct population coding axis (sometimes referred to as a dimension , i.e.…”

Section: Introductionmentioning

confidence: 99%

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Human dorsal anterior cingulate neurons signal conflict by amplifying task-relevant information

Ebitz

Smith

Horga

et al. 2020

Preprint

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SUMMARYHemodynamic activity in dorsal anterior cingulate cortex (dACC) correlates with conflict, suggesting it contributes to conflict processing. This correlation could be explained by multiple neural processes that can be disambiguated by population firing rates patterns. We used targeted dimensionality reduction to characterize activity of populations of single dACC neurons as humans performed a task that manipulates two forms of conflict. Although conflict enhanced firing rates, this enhancement did not come from a discrete population of domain-general conflict-encoding neurons, nor from a distinct conflict-encoding response axis. Nor was it the epiphenomenal consequence of simultaneous coactivation of action plans. Instead, conflict amplified the task-relevant information encoded across the neuronal population. Effects of conflict were weaker and more heterogeneous in the dorsolateral prefrontal cortex (dlPFC), suggesting that dACC’s role in conflict processing may be somewhat specialized. Overall, these results support the theory that conflict biases competition between sensorimotor transformation processes occurring in dACC.

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A Multimodal Multi‐Shank Fluorescence Neural Probe for Cell‐Type‐Specific Electrophysiology in Multiple Regions across a Neural Circuit

et al. 2021

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Cell‐type‐specific, activity‐dependent electrophysiology can allow in‐depth analysis of functional connectivity inside complex neural circuits composed of various cell types. To date, optics‐based fluorescence recording devices enable monitoring cell‐type‐specific activities. However, the monitoring is typically limited to a single brain region, and the temporal resolution is significantly low. Herein, a multimodal multi‐shank fluorescence neural probe that allows cell‐type‐specific electrophysiology from multiple deep‐brain regions at a high spatiotemporal resolution is presented. A photodiode and an electrode‐array pair are monolithically integrated on each tip of a minimal‐form‐factor silicon device. Both fluorescence and electrical signals are successfully measured simultaneously in GCaMP6f expressing mice, and the cell type from sorted neural spikes is identified. The probe's capability of combined electro‐optical recordings for cell‐type‐specific electrophysiology at multiple brain regions within a neural circuit is demonstrated. The new experimental paradigm to enable the precise investigation of functional connectivity inside and across complex neural circuits composed of various cell types is expected.

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Widespread temporal coding of cognitive control in the human prefrontal cortex

Cited by 97 publications

References 63 publications

Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

Human dorsal anterior cingulate neurons signal conflict by amplifying task-relevant information

A Multimodal Multi‐Shank Fluorescence Neural Probe for Cell‐Type‐Specific Electrophysiology in Multiple Regions across a Neural Circuit

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