Widespread temporal coding of cognitive control in the human prefrontal cortex

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Abstract

When making decisions we often face the need to adjudicate between conflicting strategies or courses of action. Our ability to understand the neuronal processes underlying conflict processing is limited on the one hand by the spatiotemporal resolution of functional MRI and, on the other hand, by imperfect cross-species homologies in animal model systems. Here we examine the responses of single neurons and local field potentials in human neurosurgical patients in two prefrontal regions critical to controlled decision-making, the dorsal anterior cingulate cortex (dACC) and dorsolateral prefrontal cortex (dlPFC). While we observe typical modest conflict-related firing rate effects, we find a widespread effect of conflict on spike-phase coupling in the dACC and on driving spike-field coherence in the dlPFC. These results support the hypothesis that a cross-areal rhythmic neuronal coordination is intrinsic to cognitive control in response to conflict, and provide new evidence to support the hypothesis that conflict processing involves modulation of the dlPFC by the dACC.

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Fig. 1: Recording configuration, task description, and behavioral performance.
Fig. 2: Rate coding of task-relevant variables in human dACC neurons.
Fig. 3: Robust phase coding in dACC neurons.
Fig. 4: dACC neuronal interactions within a broader control network.
Fig. 5: Temporal coding in human dlPFC neurons.
Fig. 6: Trial-to-trial encoding of conflict via population theta coherence.

Data availability

Data are available from the authors upon reasonable request and with permission of the Columbia University Medical Center Institutional Review Board.

Code availability

All analysis code is available online at http://www.github.com/elliothsmith/MSIT-analysis

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Acknowledgements

This work was supported by NIH R01 MH106700 (S.A.S.), NIH K12 NS080223 (S.A.S.), NIH S10 OD018211 (C.A.S.), NIH R01 NS084142 (C.A.S.), NIH R01 DA038615 (B.Y.H.), the Dana Foundation (S.A.S.), the McNair Foundation (S.A.S.), and a Young Investigator grant from the Brain & Behavior Research Foundation (E.H.S). Special thanks to C. Casadei, D. K. Peprah, and T. G. Dyster, all at Columbia University Medical Center, for coordination and data collection efforts.

Author information

S.A.S., C.B.M., M.J.Y., and E.H.S. designed the experiments. E.H.S., C.B.M., M.J.Y., Y.J.P., C.A.S., G.M.M., and S.A.S were involved with collecting the data. E.H.S., G.P.B., and G.H. analyzed the data. E.H.S., S.A.S., G.H., B.Y.H., M.M.B., and M.J.Y., wrote the manuscript. All authors provided edits to the manuscript.

Correspondence to Sameer A. Sheth.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks Tobias Egner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Integrated supplementary information

Supplementary Figure 1 Example dACC neurons.

Neurons that are selective for a, response identity, and b, feedback valence. Black dotted lines indicate the timing of the stimulus and colored dotted lines indicate the mean time of the response in a and time of feedback in b. Shaded regions indicate s.e.m over balanced numbers of trials (100 in each condition in a and 150 in each condition in b). c, example unit waveform recorded from the dACC (mean and standard error of 4278 spikes), and d, the corresponding inter-spike interval histogram. e, action potential waveform amplitude plotted against the threshold on the channel upon which the unit was recorded. This threshold corresponded to four times the RMS of the high-pass filtered data.

Supplementary Figure 2 Temporal coding of response identity and feedback valence in dACC neurons and dACC LFP.

Example spike field coherograms for feedback valence (a: valenced, b: neutral) and response identity (c: 1st button, d: 2nd button, e: 3rd button). Proportions of dACC neurons that exhibited phase coding (f) and SFC coding (g). h, Time course of linear discriminability of decision conflict among subgroups of phase-coding neurons (green: beta and blue: theta) and rate coding neurons (salmon). Permutation-based confidence interval is shown as a dotted line. Chance performance is 0.25.

Supplementary Figure 3 Decision conflict related LFP effects.

Colors in all figure panels represent conflict conditions and are color-coded in the same manner as in Fig. 1. a, example evoked potential from a dACC electrode averaged across trials within each conflict condition. b, example evoked potential from a dACC electrode averaged across trials within each conflict condition. c, spectrum of the electrode averaged across trials within each conflict condition. Dotted lines indicate the upper 95% confidence bound and the dashed lines indicate the lower confidence bounds (approximately 75 trials for each condition). d, same as c, for an electrode in dlPFC. Eight of the 29 examined ECoG contacts exhibited significant changes in LFP related to decision conflict (2-way ANOVA, F(3,5) > 2.68, all p < 0.05). All eight of these contacts exhibited conflict-related changes in the theta band, four of these contacts exhibited significant conflict related effects in the beta band, and two of these contacts exhibited changes in the gamma band (Tukey’s Range Tests, all p< 0.05). In dlPFC, three of the 29 examined ECoG contacts exhibited significant changes in LFP related to decision conflict (2-way ANOVA, F(3,5) > 2.76, all p < 0.05). Three of these contacts exhibited conflict-related changes in the theta band, and two of these contacts exhibited significant conflict related effects in the beta and gamma bands (Tukey’s Range Tests, all p< 0.05). Spectra from each contact averaged across trials are shown in e, for dACC and f, for dlPFC. (π±σ trials = 647.5±582.5) g, mean and s.e.m. coherence between dACC and dlPFC LFPs between stimulus and response for each patient and conflict condition, color coded as in Fig. 1.

Supplementary Figure 4 Electrode locations in patients from whom single units in dACC were recorded.

The top row of brains shows the distal tip of depth electrodes projected onto the medial surface of the MNI brain. The bottom row shows lateral most contact projected onto the lateral surface of the MNI brain. The left column shows all electrodes in the left hemisphere (L) and the right column shows all electrodes in the right hemisphere (R). Each color represents electrodes from an individual patient (legend above, center).

Supplementary Figure 5 stLFP for all classes of neuronal selectivity, as determined by the GLM.

a, Local stLFP between dACC neurons and dACC LFPs for the different classes of neuronal selectivity, as classified by the GLM. b, Distant stLFP between dACC neurons and dlPFC LFPs for the different classes of neuronal selectivity, as classified by the GLM. Same sample sizes as in Fig. 4. c, normalized stLFP amplitude distributions for dACC and dlPFC LFPs in black and gray, respectively. The mean trial by trial Pearson correlation between dACC and dlPFC LFPs are shown in green (π±σ trials = 647.5±582.5), indicating that changes in LFP correlations in both medial and lateral PFC do not underlie similarities in stLFP results. Box plot boxes indicate interquartile range, lines indicate medians, and ticks indicate data extrema.

Supplementary Figure 6 dACC phase coding relative to dlPFC LFPs.

a, Mean phase of SFC across 43 beta-coherent neurons. Shading indicates standard error. b, Schematic showing where the mean spikes fall for each conflict condition in beta-coherent neurons. c, Mean phase of SFC across 49 theta-coherent neurons. Shading indicates standard error. d, Schematic showing where the mean spikes fall for each conflict condition in theta-coherent neurons. e-f, For each neuron, the maximum F statistic from the firing rate GLM plotted against the maximum F statistic from the beta (i) or theta (j) phase code (LMM t-tests; t510 > 2.6 for beta and t510 > 2.1 for theta, both p < 0.05; colors as in Fig. 3; Spearman’s correlation coefficient for theta: ρ = −0.08; p = 0.33; correlation coefficient for beta: ρ = −0.01; p = 0.92; both-sided t-tests). g, Venn diagram for dACC-dlPFC rate and phase coding neurons selective for decision conflict (colors as in Fig. 3; significantly more temporal coding than rate coding: 70 vs 14 neurons; McNemar’s Test, χ2=13.6, p < 10−3).

Supplementary Figure 7 All reaction times across sessions and subjects.

a, Violin plots of RT distributions for the seventeen task sessions over six subjects in which dACC units were recorded. Each violin represents approximately 75 trials. Distributions are color coded as in Fig. 1, and the circles and bars show estimates of the mean and s.e.m. for each distribution. The effect of increasing RT with increasing level of conflict is evident at the individual subject level. b, Violin plots of RT distributions for the eleven task sessions over nine subjects in which dlPFC units were recorded. The conflict effect was also detected in these RTs (LMM t-test, RT ~ 1 + condition * session + (condition * session | subject), t3073 = 5.00, p = 6.17*10−7). Again, the conflict level-RT effect is evident at the individual subject level. There was no significant overall RT difference between groups of subjects (that is the groups of patients from which dACC units were recorded and the group of patients from which dlPFC units were recorded; Mann Whitney U test, w = 40, p = 0.25). Error rates were slightly higher in this sample (that is from which dlPFC units were recorded; 4.7%), yet were not significantly greater than in patients in which dACC units were recorded (two-sided Mann-Whitney U test, w = 90.5, p = 0.58). White circles and intersecting black lines indicate the means and standard errors for all violin plots.

Supplementary Figure 8 Example dlPFC neurons.

that are selective for a, response identity, and b, block valence. Black dotted lines indicate the timing of the stimulus and colored dotted lines indicate the mean time of the response in a and mean time of feedback in b. Shaded regions indicate s.e.m over balanced numbers of trials (100 in each condition in a and 150 in each condition in b). c, example unit waveform recorded from the dlPFC (mean and standard error of 6424 spikes), and d, the corresponding inter-spike interval histogram. e, action potential waveform amplitude plotted against the threshold on the channel upon which the unit was recorded. This threshold corresponded to four times the RMS of the high-pass filtered data.

Supplementary Figure 9 dlPFC local spike-field coding controls.

Examining the same measures for local spike field interactions in dlPFC yielded different results from dACC. a, mean stLFP waveforms averaged across dlPFC units that were selective for particular elements of the task (colors) or not (gray). The conflict selective stLFP comprises 11,596 spikes, the response selective stLFP comprises 10,348 spikes, the feedback selective stLFP comprises 6,130 spikes, and the non-rate-coding stLFP comprises 78,786 spikes. While an interesting voltage shift and temporal patterns of deflections in the theta range were observed in b, scatter plots of the stLFP amplitudes induced by different classes of neurons, as defined by the GLM, which were not significantly different among neuron classes (LMM, t78,182 < 1.27, p > 0.21). c, phase coding was not apparent in dlPFC. Rather dlPFC neural firing precessed slightly, from the trough of the LFP to slightly ahead of the trough (mean angle±s.d. = 0.38±0.12), in response to the stimulus, without a significant difference in phase among conflict conditions (LMM t-test, t886 = −1.71, p = 0.09). d, mean and s.e.m. stimulus-aligned evoked potentials from LFP averaged across 888 trials of dlPFC UMA (red) and overlying macrocontact (blue) data.

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Smith, E.H., Horga, G., Yates, M.J. et al. Widespread temporal coding of cognitive control in the human prefrontal cortex. Nat Neurosci 22, 1883–1891 (2019) doi:10.1038/s41593-019-0494-0

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