Nature Neuroscience: doi: /nn Supplementary Figure 1

Similar documents
Interpretive Report of WMS IV Testing

Scatter Plots with Error Bars

Interpretive Report of WAIS IV Testing. Test Administered WAIS-IV (9/1/2008) Age at Testing 40 years 8 months Retest? No

Analysing Questionnaires using Minitab (for SPSS queries contact -)

Advanced Clinical Solutions. Serial Assessment Case Studies

Conducting Geriatric Evaluations: Using Data from WAIS-IV, WMS-IV, and ACSW4W4 Gloria Maccow, Ph.D., Assessment Training Consultant

WMS III to WMS IV: Rationale for Change

Multivariate Analysis of Ecological Data

Efficacy Report WISC V. March 23, 2016

2 The Use of WAIS-III in HFA and Asperger Syndrome

Neuropsychology testing the brain

The child is given oral, "trivia"- style. general information questions. Scoring is pass/fail.

Estimate a WAIS Full Scale IQ with a score on the International Contest 2009

General Ability Index January 2005

INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA)

Connectivity theory of Autism: Using connectivity measures in the assessment and treatment of autistic disorders

Outline. Definitions Descriptive vs. Inferential Statistics The t-test - One-sample t-test

Statistics Review PSY379

How To Map Language With Magnetic Source Imaging

Diagrams and Graphs of Statistical Data

Linear Models in STATA and ANOVA

To Err is Human: Abnormal Neuropsychological Scores and Variability are Common in Healthy Adults

Mean = (sum of the values / the number of the value) if probabilities are equal

Epilepsy and Neuropsychology Dr. Sare Akdag, RPsych

Solutions to Homework 6 Statistics 302 Professor Larget

Table Key. RHD = right- hemisphere damage. LHD = left-hemisphere damage. PN = prenatal. + S = patients suffering from seizures

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

WISE Power Tutorial All Exercises

How To Run Statistical Tests in Excel

IBM SPSS Direct Marketing 23

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics

HMRC Tax Credits Error and Fraud Additional Capacity Trial. Customer Experience Survey Report on Findings. HM Revenue and Customs Research Report 306

Introducing the WAIS IV. Copyright 2008 Pearson Education, inc. or its affiliates. All rights reserved.

IBM SPSS Direct Marketing 22

1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96

Descriptive Statistics. Purpose of descriptive statistics Frequency distributions Measures of central tendency Measures of dispersion

Interpretive Report of WISC-IV and WIAT-II Testing - (United Kingdom)

WISC IV and Children s Memory Scale

CSU, Fresno - Institutional Research, Assessment and Planning - Dmitri Rogulkin

Using Excel for descriptive statistics

Essentials of WAIS-IV Assessment

Early Childhood Measurement and Evaluation Tool Review

EXAM #1 (Example) Instructor: Ela Jackiewicz. Relax and good luck!

More details on the inputs, functionality, and output can be found below.

EEG IN CHILDREN: NORMAL AND ABNORMAL. Warren T. Blume, MD,FRCPC EEG Course FSNC/CNSF JUNE 2007

Clinician Portal: Enabling a Continuity of Concussion Care

Basic Statistics and Data Analysis for Health Researchers from Foreign Countries

Environmental Remote Sensing GEOG 2021

Exploratory Data Analysis

ALLEN Mouse Brain Atlas

Deep profiling of multitube flow cytometry data Supplemental information

Projects Involving Statistics (& SPSS)

AP: LAB 8: THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics

Two-sample inference: Continuous data

Scientific Method. 2. Design Study. 1. Ask Question. Questionnaire. Descriptive Research Study. 6: Share Findings. 1: Ask Question.

Exercise. Rule #1 Exercise boosts brain power.

Using Excel for inferential statistics

Tutorial 3: Graphics and Exploratory Data Analysis in R Jason Pienaar and Tom Miller

CALCULATIONS & STATISTICS

sample median Sample quartiles sample deciles sample quantiles sample percentiles Exercise 1 five number summary # Create and view a sorted

Evaluation & Validation: Credibility: Evaluating what has been learned

Multivariate Analysis of Variance. The general purpose of multivariate analysis of variance (MANOVA) is to determine

II. DISTRIBUTIONS distribution normal distribution. standard scores

Appendix G STATISTICAL METHODS INFECTIOUS METHODS STATISTICAL ROADMAP. Prepared in Support of: CDC/NCEH Cross Sectional Assessment Study.

Chapter 2: Descriptive Statistics

Case 4:05-cv Document 26-1 Filed in TXSD on 09/12/08 Page 1 of 5. Exhibit A

Sample Entrance Test

MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification

Chapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing

Improving the Performance of Data Mining Models with Data Preparation Using SAS Enterprise Miner Ricardo Galante, SAS Institute Brasil, São Paulo, SP

Vertical Alignment Colorado Academic Standards 6 th - 7 th - 8 th

Getting Started with Statistics. Out of Control! ID: 10137

A Comparison of Low IQ Scores From the Reynolds Intellectual Assessment Scales and the Wechsler Adult Intelligence Scale Third Edition

Statistiek II. John Nerbonne. October 1, Dept of Information Science

FINDING SUBGROUPS OF ENHANCED TREATMENT EFFECT. Jeremy M G Taylor Jared Foster University of Michigan Steve Ruberg Eli Lilly

CLINICAL DETECTION OF INTELLECTUAL DETERIORATION ASSOCIATED WITH BRAIN DAMAGE. DAN0 A. LELI University of Alabama in Birmingham SUSAN B.

CRITICALLY APPRAISED PAPER (CAP)

Measuring and modeling attentional functions

c. Construct a boxplot for the data. Write a one sentence interpretation of your graph.

Rarefaction Method DRAFT 1/5/2016 Our data base combines taxonomic counts from 23 agencies. The number of organisms identified and counted per sample

NATIONAL GENETICS REFERENCE LABORATORY (Manchester)

Chapter 2: Supplementary Exercises

The WISC III Freedom From Distractibility Factor: Its Utility in Identifying Children With Attention Deficit Hyperactivity Disorder

Week 4: Standard Error and Confidence Intervals

Basic research methods. Basic research methods. Question: BRM.2. Question: BRM.1

5 Correlation and Data Exploration

A Picture Really Is Worth a Thousand Words

Summary of Formulas and Concepts. Descriptive Statistics (Ch. 1-4)

Parents Guide Cognitive Abilities Test (CogAT)

0 value2. 3. Assign labels to the proteins in each interval of the ranked list

Cecil R. Reynolds, PhD, and Randy W. Kamphaus, PhD. Additional Information

SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES

Measurement with Ratios

Introduction to Exploratory Data Analysis

Adaptive information source selection during hypothesis testing

Course on Functional Analysis. ::: Gene Set Enrichment Analysis - GSEA -

INCREASE YOUR PRODUCTIVITY WITH CELF 4 SOFTWARE! SAMPLE REPORTS. To order, call , or visit our Web site at

September Population analysis of the Retriever (Flat Coated) breed

Lean Six Sigma Black Belt Body of Knowledge

Transcription:

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 ω 2 for visual category regressor, for all VS cells. R 2 =0.009, p=0.37. (I) Absence of correlation between isolation distance and response strength, as quantified by ω 2 for novel/familiar regressor, for all MS cells. R 2 =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-topeak 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).

Supplementary Tables Supplementary Table 1: Patients. Demographics, pathology and neuropsychological evaluation. Abbreviations: Hand: Dominant handedness. Tests indicated with n/a were not performed for clinical reasons. WAIS-III: IQ scores from the Wechsler Adult Intelligence Scale: performance IQ (PIQ), verbal IQ (VIQ), full scale IQ (FSIQ), verbal comprehension index (VCI), perceptual organization index (POI). All WAIS-III scores are on average 100 with a s.d. of 15 in the normal population (69 and less falls in the clinically abnormal range, 70-79 borderline, 80-89 low average, 90-109 average, 110-119 high average, 120-129 superior, 130+ very superior). WMS-R and WMS-III are the Wechsler memory scale revised and version 3, respectively. Subtests are verbal paired associates (VPA), logical memory (LM) and visual reproduction (Vis). 1 and 2 are immediate and delayed, respectively. Scores are raw scores. ID Age Sex Hand Epilepsy Diagnosis WAIS-III / WAIS-IV (*) WMS-R / WMS-III (*) Dom PIQ VIQ VCI POI FSIQ VPA1 VPA2 LM1 LM2 Vis1 Vis2 H09 55 M R right temporal 97 98 100 103 98 18 7 22 14 31 25 H10 37 M R Left frontal 79 64 n/a n/a 68 n/a n/a n/a n/a n/a n/a H11 16 M L right lateral frontal 84 91 88 84 88 17 8 n/a n/a 31 29 H14 31 M L Bilateral indep. temporal n/a n/a 112 111 n/a 11 6 18 11 40 16 H15 45 M R Right mesial temporal 64 59 59 69 58 n/a n/a n/a n/a 30 13 H16 34 F R right frontal 84 68 68 89 74 8 5 16 10 n/a n/a H17 19 M R left inferior frontal 128 131 122 133 134 24 6 34 37 40 39 H18 40 M R Right temporal 69 n/a n/a n/a n/a n/a n/a n/a n/a 25 8 H19 34 M R Left frontal 81 74 76 80 86 n/a n/a 20 19 35 32 H21 20 M R Not localized n/a n/a 93 89 n/a 23 8 34 33 34 32 H23 35 M R Left temporal n/a n/a 74 86 n/a 11 3 13 4 34 32 H27 41 M R Bilateral indep. temporal 86 91 86 88 89 n/a n/a n/a n/a n/a n/a H28 23 M R Right mesial temporal 79 77 78 80 76 n/a n/a n/a n/a n/a n/a H29 18 F L Left deep insula 104 110 107 101 107 n/a n/a n/a n/a n/a n/a H31 30 M R Right temporal n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a H33 29 M R Left temporal 113 104 101 123 108 11 5 21 15 41 41 H41 19 M R Right posterior temporal 92 100 107 95 97 22 6 31 27 36 37 H42 29 M R Not localized 87 75 78 91 79 16 6 22 14 37 36 H43 27 F L Left temporal n/a n/a 84 86 n/a 19 8 18 17 30 24 H44 58 F L Right temporal 74 77 72 78 74 12 5 10 3 34 28 C24 47 F n/a Not localized n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a C25 36 F R Bilateral indep. temporal 107 105 107 105 107 19* 8* 29* 30* 38* 38* C26 56 F L Right temporal 107 92 96 109 99 15* 6* 26* 17* 35* 33* C27 45 M R Left temporal 79 61 57 80 66 n/a n/a n/a 1* 17* 11* C29 19 M R Left temporal neocortical 113 95 89 121 103 20* 8* 19* 19* 37* 38*

C31 31 M R Left temporal neocortical n/a n/a 72* 79* 69* 21* 10* n/a n/a n/a n/a C32 19 M R Not localized (generalized) n/a n/a 83* n/a 80* 22* 18* n/a n/a n/a n/a C33 44 F R Right temporal 99 76 80 103 85 19* 5* 20* 24* 35* 28* Supplementary Table 2: Electrophysiological properties of neurons. Abbreviations are: visually selective (VS), memory selective (MS). Firing rates are over the duration of the experiment (overall) or mean rates across all correct trials of a neuron (baseline period is 1s before stimulus onset, stimulus period is 1.5s long starting 200ms after stimulus onset). P-values (right column) specify the likelihood of observing this many selective cells by chance by repeating the same selection procedure after randomly permuting the order of trials (1000 runs). * = Bootstrap p-values are set to 1/N where N=number of runs if none of the bootstrap samples contained more cells that observed. Nr of neurons Overall firing rate ±sd (Range) [Hz] Baseline rate ±sd (Range) [Hz] Post-Stimulus rate ±sd (Range) [Hz] p-value bootstrap, nr significant cells All sessions (Group 0) 1065 1.84±2.66 (0.01-23.68) 1.79±2.66 (0-26.19) 1.93±2.80 (0-22.20) - Behavioral Group 1 954 1.72±2.40 (0.01-19.71) 1.68±2.39 (0-20.38) 1.81±2.57 (0-22.20) - Behavioral Group 2 664 1.69±2.47 (0.02-19.7) 1.65±2.48 (0-20.38) 1.76±2.63 (0-22.20) - VS Neurons in Group 0 186 2.28±2.90 (0.05-23.68) 2.22±2.94 (0.01-26.19) 2.40±3.00 (0.02-21.63) 0.001 MS Neurons in Group 0 87 2.35±3.09 (0.03-19.71) 2.35±3.15 (0.03-20.38) 2.40±3.14 (0.03-18.81) 0.003 VS Neurons in Group 1 168 2.14±2.28 (0.05-11.80) 2.07±2.20 (0.01-12.04) 2.26±2.53 (0.02-13.90) 0.001* MS Neurons in Group 1 81 2.44±3.18 (0.03-19.71) 2.44±3.24 (0.03-20.38) 2.48±3.24 (0.03-18.81) 0.001 VS Neurons in Group 2 128 1.95±2.09 (0.05-10.66) 1.90±2.00 (0.01-10.46) 2.06±2.35 (0.03-13.90) 0.001* MS Neurons in Group 2 65 2.36±3.30 (0.10-19.71) 2.37±3.36 (0.06-20.38) 2.38±3.31 (0.08-18.81) 0.001* Supplementary Table 3: Total number of neurons recorded in each area and hemisphere. Numbers show total number recorded in all sessions (Group 0). Numbers in brackets are those recorded from pathological tissue. Neurons were counted if the patient was diagnosed with uni-or bilateral temporal seizure onset, regardless of whether the focus was medial or lateral. Hippocampus Amygdala Left 207 (62) 304 (94) Right 212 (124) 342 (121) Total 419 646

Supplementary Table 4: Comparison of VS and MS neurons. Here, only the subgroup of MS and VS neurons used for the comparison of extracellular waveforms are used (see results). All errors are ±s.d. MS neurons VS neurons p-value Mean firing rate 2.00±2.51 Hz 1.87±2.09 Hz ns Proportion of small ISIs 0.25±0.37 0.20±0.35 ns CV2 0.95±0.13 vs 0.93±0.17 ns Peak SNR 5.80±4.46 6.90±5.43 ns Burst index 0.02±0.02 0.03±0.05 ns