(A) Task design. Subjects chose between a left and right option (green rectangles) using a manual joystick movement, after sequentially sampling 2, 3, or 4 cues that revealed reward probability and magnitude to the subject. Blue squares indicated locations available for information sampling. On attribute trials (left panels), cues 1 and 2 were on opposing options but the same attribute; on option trials (right panels), cues 1 and 2 were different attributes of the same option. (B) Choice behavior as function of cue 1 and 2 value. (i) Probability of choosing left option on attribute trials, as function of left-right picture rank difference (where 1 is lowest rank picture on each attribute, and 5 is highest rank picture). (ii) Probability of choosing option 1 on option trials, as function of first plus second picture value (relative to middle value picture 3). See also for additional analyses of choices.

(A) On attribute trials where a third cue was sampled, the probability of third saccade being directed diagonally back towards option 1, rather than vertically to remain on option 2, is high when Cue 1 is high value and Cue 2 is low value. (B) On option trials, the number of cues sampled is lowest when Cues 1 and 2 are high value, but surprisingly it is highest when Cues 1 and 2 are low value, even though this provides complete information about which option to choose.

(A) Strategy for reconstructing path of electrode tracks. Left: After surgery for chamber implantation, prior to craniotomy, subjects underwent MRI scan with a custom-built implant placed within the chamber. This contained the MRI contrast agent gadolinium along the trajectory of potential recording paths at regular 4mm intervals. Note the prominent susceptibility artifact due to titanium chambers does not affect gadolinium trajectories, which were intentionally located away from the chamber. Right: This scan could be co-registered to a pre-operative scan without susceptibility artifact (in orange; note that head appears smaller due to muscle growth between scans), to reliably reconstruct recording locations. This technique was further verified by identification of grey/white matter boundaries during lowering of electrodes along different trajectories. (B) Recording locations of orbitofrontal neurons (OFC), dorsolateral prefrontal neurons (DLPFC), and anterior cingulate neurons (ACC), shown on coronal sections. AP range denotes position anterior to interaural plane in stereotactic coordinates.

(A) OFC representaional similarity analysis between the 10 different cue identities – probability and magnitude, sorted from lowest (1) to highest (5) ranked picture – when presented on left and right options. For matrix element (i,j), color denotes Pearson’s correlation coefficient of Z-scored firing rate between condition i and condition j across the OFC neuronal population. Firing rate is averaged from 100ms to 500ms post-stimulus (see also ). Note this matrix collapses across top/bottom spatial position; see for 40x40 matrix, splitting conditions by spatial position. (B)/(C) As panel (A), but for DLPFC and ACC populations respectively. (D)-(H) Results from multiple linear regression of ‘templates’ onto RSA matrices. In each column, top subpanel shows template matrix, middle subpanel shows corresponding regression T-statistics for each region, and bottom subpanel shows coefficient of partial determination from sliding regression of templates onto RSA matrices, using sliding window of +/- 100ms. See for full description of template matrices, regression model and statistical inference via non-parametric permutation test. (D) ‘Spatial attention’ template (differentiating cues on left vs. right-hand option) was particularly prominent in DLPFC (DLPFC: T₃₉₉=35.782, p<1*10^-4), and significantly more so than other regions (one-way ANOVA F_2,1179 = 311.18, p<1*10^-4; post-hoc comparison for DLPFC>ACC: p<1*10^-4; post-hoc comparison for DLPFC>OFC: p<1*10^-4); (E) ‘stimulus identity’ template (responding similarly to the same cue irrespective of side) was particularly strong in OFC (T₃₉₉=15.3173, p<1*10^-4), again more so than other regions (F_2,1179 = 32.77, p<1*10^-4; post-hoc comparisons: OFC>ACC: p<1*10^-4; OFC>ACC: p<1*10^-4); (F) ‘Attended value’ template (representing cue 1 value irrespective of stimulus location or attribute) was prominent in OFC (T₃₉₉= 5.0697, p=0.0036), and significantly more so than in other regions (F_2,1179 = 6.73, p=0.0126; post-hoc comparisons: OFC>DLPFC: p=0.0017; OFC>ACC: p=0.0002); (G) ‘Left/right value’ template was prominent principally within ACC (T₃₉₉=5.5151, p=0.0096) and DLPFC (T₃₉₉=5.7156, p=0.0062), and significantly more so than in OFC (F_2,1179 = 9.08, p=0.011; post-hoc comparisons: ACC>OFC: p=0.0003; DLPFC>OFC: p=0.011); (H) ‘Accept/reject’ template (reflecting whether Cue 1 had high (rank 4 or 5) versus low value (rank 1 or 2)) was strongest in ACC (T₃₉₉=12.1217, p<1*10^-4) and significantly more so than other regions (F_2,1179 = 17.20, p=0.0006; post-hoc comparisons: ACC>OFC: p<1*10^-4; ACC>DLPFC: p=0.0004). In panels (D)-(F), * denotes p<0.05, ** denotes p<0.005, *** denotes p<0.0005. See also .

(A) Coefficient of partial determination for Cue 1 Value, Cue 2 Value and Cue 3 value, timelocked to each cue’s presentation using a sliding 200ms window. Lines denote mean +/- s.e.m. across neurons. (B) Positive relationship between T-statistics from regression of value of cue 1 when cue 1 is presented (ordinate), and value of cue 2 when cue 2 is presented (abscissa), implying a stable subspace reflecting the currently attended value. (C) When cue 2 is being attended on attribute trials, the online value subspace (ordinate) correlates negatively with the subspace reflecting the stored value of cue 1 (abscissa). (D)-(F) When cue 3 is being attended on option trials, the attended value subspace (ordinate of (D) and (E)) correlates negatively with the subspace for stored values of both cue 1 (abscissa of (D)) and cue 2 (abscissa of (E)). The two stored subspaces are positively correlated (F). (G)-(J) Cross-correlation matrices reflecting the time-varying relationship between different value subspaces on attribute trials (in (G)) and option trials (in (H)-(J)). Heat maps reflect the correlation coefficient between T-statistics from regression for each cue’s value across the OFC population. Superimposed letters refer back to the correlations that are plotted above, in panels (B)-(F). Black lines denote significant clusters (p<0.001, cluster-based permutation test, corrected for multiple comparisons). (K) Negative correlations in parts (C)-(E) are only present in OFC, and significantly stronger in OFC than in DLPFC (n=135 units) and ACC (n=189 units); bars show correlation coefficient +/- s.e. (*** = p<0.001, ** = p<0.01, * = p<0.05 (two-tailed), ‘+’ = p<0.05 (one-tailed), Fisher’s r-to-Z transform). Correlations in parts B-F and K are defined using a window of 150-350ms post-stimulus onset. All correlation coefficients are Pearson’s correlation. See also .

(A) Positive population correlations between four orthogonal regressors that reflect ‘belief confirmation’ at cue 2/cue 3 on both option and attribute trials (cf. ), and initial value population response at cue 1 (cf. ), demonstrating a stable belief confirmation subspace in ACC across multiple cues. The value inside each box denotes the Pearson correlation of parameter estimates across the neural population in each region; shading denotes significance. See for individual ACC correlations. (B) Formal comparison of correlations shown in part (A) using Fisher’s r-to-Z transformation against OFC (n=183 units) and DLPFC (n=135 units); left panels show the individual Z-scores/significance for each comparison (same layout as in part (A)), right panels show distribution of Z-scores. (C)/(D) Projecting ACC population activity into belief confirmation subspace reveals ramping immediately prior to the commitment to joystick movement. In part (C), trials are sorted by response time and time-locked to cue 1 onset (blue bars above are box plots of cue onset times for other cues); in part (D), trials are time-locked to response onset. (E) An orthogonal subspace in ACC reflects the emergence of an action plan to choose the left or right option. Activity in this subspace progressively favors one action over the other across time. See for relationship between belief confirmation and action selection subspaces.

(A) Attention-guided value comparison can be defined using three separate epochs and sets of regressors (see text for details). All three definitions show a greater proportion on neurons significantly encoding attention-guided value comparison in OFC (n=183 units) than in DLPFC (n=135 units) or ACC (n=189 units). (B) This figure shows the percentage of neurons that encoded value attended minus value unattended across any of the three different epochs in part (A). (C) There are four separate ways of defining ‘belief confirmation’ (see text and for details). All four definitions show a greater proportion of neurons significantly encoding belief confirmation in ACC than in OFC or DLPFC.

(A) Fractions of ACC (n=189 units), DLPFC (n=135 units) and OFC (n=183 units) neurons significantly encoding cue value, action value (left minus right), attribute value (probability minus magnitude), and spatial value (top minus bottom) in firing rates 100-500ms post-Cue 1 onset. Significance denotes two-sided binomial test against chance encoding (5%) for each bar (Cue value: ACC p<1*10e^-5, DLPFC p<1*10e^-5, OFC p<1*10e^-5; Action value: ACC p<1*10e^-5, DLPFC p<1*10e^-5, OFC p=0.4139; Attribute value: ACC p=0.029, DLPFC p=0.0023, OFC p<1*10e^-5; Spatial value: ACC p=0.0572, DLPFC p<1*10e^-5, OFC p=0.0845), and pairwise Chi² tests for comparisons between regions; * denotes p<0.05, ** denotes p<0.01, *** denotes p<0.001. (B) Coefficient of partial determination estimated in sliding 200ms bins for cue, action, attribute and spatial value in each region (mean +/- s.e. across neurons (ACC, n=189 units; DLPFC, n=135 units; OFC, n=183 units)).