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Representation of retrieval confidence by single neurons in the human medial temporal lobe

Nature Neuroscience volume 18, pages 1041–1050 (2015)Cite this article

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Abstract

Memory-based decisions are often accompanied by an assessment of choice certainty, but the mechanisms of such confidence judgments remain unknown. We studied the response of 1,065 individual neurons in the human hippocampus and amygdala while neurosurgical patients made memory retrieval decisions together with a confidence judgment. Combining behavioral, neuronal and computational analysis, we identified a population of memory-selective (MS) neurons whose activity signaled stimulus familiarity and confidence, as assessed by subjective report. In contrast, the activity of visually selective (VS) neurons was not sensitive to memory strength. The groups further differed in response latency, tuning and extracellular waveforms. The information provided by MS neurons was sufficient for a race model to decide stimulus familiarity and retrieval confidence. Together, our results indicate a trial-by-trial relationship between a specific group of neurons and declared memory strength in humans. We suggest that VS and MS neurons are a substrate for declarative memories.

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Figure 1: The recognition memory task and behavioral results.
Figure 2: MS neurons.
Figure 3: The response of MS neurons is modulated by subjective confidence.
Figure 4: VS neurons.
Figure 5: The ability of VS neurons to differentiate visual stimuli is not influenced by confidence judgment or novelty of the stimulus.
Figure 6: MS and VS neurons signal at different times and only MS neurons are sensitive to confidence.
Figure 7: Quantification of population-level information difference resulting from confidence.
Figure 8: Computational model to decide the familiarity and confidence of a stimulus.

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Acknowledgements

We thank J. Kaminski, R. Adolphs, C. Anastassiou, U. Maoz, J. Wertheimer and W. Einhaeuser for discussion, Z. Fu for spike sorting, C. Heller for performing some of the surgeries, the staff of the Epilepsy Monitoring Units at Huntington Memorial Hospital and Cedars-Sinai for invaluable assistance, particularly J. Schmidt. We thank K. Birch and H. Babu for assistance with patient care and surgery, and L. Philpott and M.-T. Le for neuropsychological testing. This work was supported by the Cedars-Sinai Medical Center Department of Neurosurgery (to U.R.), National Institute of Mental Health Conte Center at Caltech (P50 MH094258), and the Gustavus and Louise Pfeiffer Research Foundation (to U.R.).

Author information

Authors and Affiliations

  1. Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA

    Ueli Rutishauser, Shengxuan Ye, Matthieu Koroma & Adam N Mamelak

  2. Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA

    Ueli Rutishauser & Jeffrey M Chung

  3. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA

    Ueli Rutishauser

  4. Computation & Neural Systems Program, California Institute of Technology, Pasadena, California, USA

    Ueli Rutishauser, Shengxuan Ye & Oana Tudusciuc

  5. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA

    Ueli Rutishauser

  6. Departement de Biologie, Ecole Normale Superieure de Cachan, Cachan, France

    Matthieu Koroma

  7. Division of Humanities and Social Science, California Institute of Technology, Pasadena, California, USA

    Oana Tudusciuc

  8. Department of Neurosurgery, Huntington Memorial Hospital, Pasadena, California, USA

    Ian B Ross

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  1. Ueli Rutishauser
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Contributions

U.R. and A.N.M. designed the experiments. U.R. and O.T. performed experiments. U.R., M.K. and S.Y. performed analysis. A.N.M. and I.B.R. performed surgery. J.M.C. provided patient care. U.R. and A.N.M. wrote the paper. All of the authors discussed the results at all stages of the project.

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Correspondence to Ueli Rutishauser.

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Integrated supplementary information

Supplementary Figure 1 Spike sorting and recording quality assessment.

(a-e) Metrics quantifying individual clusters. (a) Histogram of proportion of inter-spike intervals (ISIs) which are shorter than 3ms. The large majority of clusters had less than 0.5% of such short ISIs. (b) Histogram of mean firing rates. (c) Histogram of the SNR of the mean waveform peak of each unit. (d) Histogram of the SNR of the entire waveform of all units. (e) Histogram of CV2 values of all units. (f) Pairwise distance between all possible pairs of units on all wires where more than 1 cluster was isolated. Distances are expressed in units of s.d. after normalizing the data such that the distribution of waveforms around their mean is equal to 1. (g) Isolation distance of all units for which this metric was defined (n = 746, median 35.0). There was no significant difference in isolation distance between VS and MS cells (p=0.59, two-sample Kolmogorov-Smirnov test). (h) Absence of correlation between isolation distance and response strength, as quantified by ω2 for visual category regressor, for all VS cells. R2 = 0.009, p = 0.37. (i) Absence of correlation between isolation distance and response strength, as quantified by ω2 for novel/familiar regressor, for all MS cells. R2 = 0.03, p = 0.25. (j) Histogram of how many units were identified on each active wire (only wires with at least one unit identified are counted). The average yield per wire with at least one unit was 2.4 (range 1-7).

Supplementary Figure 2 Bootstrap statistics for number of cells selected.

Estimate of chance values (null distribution) of number of cells observed compared to the actual number of cells found. The red line indicates the actual number of cells observed. The null distribution (blue) was estimated by re-running the identical selection procedure after first randomly permuting the order of the labels assigned to each trial. This permutation procedure destroys to association between the spiking response and trial identity, but keeps everything else intact (number of behavioral choices, number of times a stimulus was seen). The p-value is equal to the number of chance observations (blue) which are larger than that observed (red). In cases where no chance values exceeded those observed, we set p-values to 1/B with B the number of bootstrap runs (B = 1000). (a) Significance of the number of MS and VS cells we identified for behavioral group 1 (top, p = 0.001 and p = 0.001, respectively) and group 2 (bottom, p = 0.001 and p = 0.001, respectively). (b) Significance of the number of cells that qualified as both MS and VS cells in behavioral group 1 (top, p = 0.001) and group 2 (bottom, p = 0.001). While rare, the number of cells observed was well above chance.

Supplementary Figure 3 Confidence encoding by NS and MS neurons, shown separately for different brain areas and hemispheres.

Confidence encoding by NS and MS neurons in the hippocampus (HF, panels a-c), amygdala (AMY, d-f), left side (panels g-i), and right side (j-l). The result shown in Fig 3 held when considering MS neurons separately in the hippocampus (d-f; n = 34, p = 0.00015, p = 0.0014, and p = 0.024 for all, NS, and FS neurons, respectively), amygdala (a-c; n = 31, p = 0.0024, p = 0.024, p = 0.017 for all, NS, and FS neurons, respectively), left side (g-i, n = 26, p = 0.0032, p = 0.0033, and p = 0.056 for all, NS, and FS neurons, respectively), and right side (j-l, n = 39, p = 0.000069, p = 0.0015, and p = 0.011 for all, NS, and FS neurons, respectively). (m-o) Bootstrap estimate of the null distribution and significance of difference between AUC for high and low confidence trials. Observed values (red line) are identical to those shown in Fig 3c-e. The null distribution was estimated by randomly scrambling the trials between high and low confidence. We ran 1000 runs, for each of which the average difference in AUC across all cells was calculated in the same manner as in Fig 3. (p) Further example neuronal ROCs for MS neurons, shown for high-confidence trials only, compare to Fig 2. All errorbars are ±s.e. across neurons. All p-values are one-tailed paired t-tests comparing the AUC of high and low confidence trials.

Supplementary Figure 4 Example cell that qualifies as both a VS and MS cell.

(a) Raster of all trials, grouped into familiar (top) and novel (bottom) trials. Color indicates visual category. (b) PSTH of familiar (top) and novel (bottom) trials. (c) Mean response as a function of visual category (color) and familiarity and novelty. This cell increased its firing rate significantly only for familiar landscapes (pairwise tests novel vs familiar for each category, not corrected for multiple comparisons). Note that these cells were selected independently as MS and VS cells. The contrasts shown in this panel were not used to select cells.

Supplementary Figure 5 Comparison of ability of VS cells to distinguish between visual categories as a function of confidence and familiarity.

(a,b) Show identical analysis to Fig 5a,b, but only including neurons VS neurons with baseline firing rate >1Hz (n = 78). There was no significant difference (p = 0.91 and p = 0.43 using paired sign-test and p = 0.75 and p = 0.48 using bootstrap test for confidence and familiarity, respectively).

Supplementary Figure 6 Population effect size estimation using a 2-way model with interaction term.

No interaction between the two main factors category and familiarity was found. (a-c) shows effect size for both main factors (category, familiarity) as well as their interaction for all neurons (a), only MS neurons (b) and only VS neurons (c). Dashed horizontal lines indicate the 99% confidence intervals of the null distribution (200 bootstrap runs each) for each factor (color). Note that the interaction term (red) never becomes significantly positive.

Supplementary Figure 7 Properties of extracellular waveforms (EWs).

(a) Normalized EWs of a random subset of all recorded neurons (50 waveforms are shown). (b) Histogram of the trough-to-peak time d of all units (n = 1065). The distribution was significantly bimodal (Hartigan’s dip test, p<1e-5). (c) Scatter plot of firing rate vs trough-to-peak time. Notice how, at all firing rates, there appear at least two clusters with different trough-to-peak time. (d-f) Comparison of waveforms between MS neurons and VS neurons. (d) Histogram of trough-to-peak time for MS units only (top) and VS units only (bottom). Only the distribution for VS neurons was significantly bimodal (Hartigan’s dip test, p = 0.004 vs p = 0.34 for MS neurons). (e) Waveforms of all MS (left) and VS (right) units. Colors mark short (red) and long (blue) waveforms. (f) Quantification of proportion of short and long waveforms for MS and VS neurons, respectively. The proportion of short and long waveforms was significantly different only for MS neurons (χ2 comparison of proportions, p = 2.2e-5 vs p = 0.12 for MS and VS neurons, respectively).

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Rutishauser, U., Ye, S., Koroma, M. et al. Representation of retrieval confidence by single neurons in the human medial temporal lobe. Nat Neurosci 18, 1041–1050 (2015). https://doi.org/10.1038/nn.4041

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