{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Modeling the pupillometric signal\n", "\n", "**WARNING**: This functionality is **experimental**. Some of the provided algorithms are unpublished (or in the process of being published) and may not work well.\n", "\n", "The idea behind the algorithms is detailed in this notebook (slides from a symposium talk):\n", "\n", "- [Estimation of tonic and phasic pupillometric signals](symp_talk_uit2019.html)\n", "\n", "This notebooks also includes results from a simulation study showing the superiority of the algorithm to more traditional approaches." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n" ] } ], "source": [ "import sys\n", "sys.path.insert(0,\"..\") ## not necessary if pypillometry is installed on your system\n", "import pypillometry as pp\n", "import pylab as plt\n", "import numpy as np\n", "import scipy" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "It can sometimes be useful to think about the pupillometric signal as being composed of different components. One common assumption, based on the finding that the pupil reflects activity in the norepinephrinergic system, consists of slow, tonic (baseline) and faster, phasic (response) fluctuations. \n", "\n", "`pypillometry` comes with functions to create artificial data. These functions are built on such a model where stimulus- or event-induced responses are superimposed on a slow, baseline-like component:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "faked=pp.create_fake_pupildata(ntrials=20)\n", "plt.figure(figsize=(15,5))\n", "faked.plot()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The orange line is the tonic, baseline-component. At the timing of each event (grey lines), a scaled version of a \"response-kernel\" (Hoeks & Levelt, 1993) is added. Finally, random noise is added on top of the modeled data. The challenge is to extract both the size of the response as well as the baseline value at each stimulus when only using the raw pupillometric data (the blue line)." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Traditional approaches for disentangling tonic and phasic components\n", "\n", "One common way to solve this problem and analyse pupillometric data on the trial-by-trial level is therefore to extract the average pupillometric signal just before a stimulus (as a measure of the baseline signal) and just after the stimulus (as a measure of the pupil's response. In `pypillometry` this functionality is implemented by `PupilData.stat_per_event()` which allows to extract a summary of the signal relative to the events in the dataset.\n", "\n", "For example, the following code extracts\n", "- the average signal in the time-window from 200 ms before each event until the timing of the event itself (`0`) as baseline\n", "- the average signal in the time-window from 800 ms after each event until 1200 ms after the event as a measure of the response \n", "\n", "often, the baseline is subtracted from the response:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([5500.56515638, 5509.56503514, 5505.1305654 , 5505.58670786,\n", " 5532.68266103, 5511.59701815, 5525.41677883, 5503.82262254,\n", " 5522.53790134, 5513.09265628, 5505.33927185, 5514.86643245,\n", " 5512.1684625 , 5524.29129093, 5534.80567185, 5515.18542902,\n", " 5514.13734023, 5507.49263465, 5516.95359107, 5518.51300527,\n", " 5502.73976948, 5505.57378147, 5505.56045352, 5519.91456927,\n", " 5509.3941475 , 5512.94693075, 5502.59509483, 5509.74297856,\n", " 5518.75210639, 5503.21585722, 5512.47698792, 5522.8453116 ,\n", " 5521.46205695, 5525.64015504, 5509.74327272, 5506.72779301,\n", " 5512.27484191, 5517.6846295 , 5522.48397992, 5517.80347458]),\n", " array([ 9.98461655, -4.99864845, 0.42726416, 24.49363307,\n", " -19.41832247, 10.01091518, -20.29265814, 17.25116065,\n", " -7.60631407, -8.41636626, 10.76844416, -3.88367907,\n", " 10.23516969, 5.61337868, -19.53140635, -2.33528928,\n", " -5.38115079, 11.75266296, 1.34089933, -2.39554707,\n", " 6.02388672, 24.75995303, 24.94936076, -0.82832067,\n", " 16.80035467, -3.91412122, 18.91088326, 1.40832432,\n", " -3.60078712, 12.34610532, 10.43566863, 11.12587364,\n", " 13.2498906 , -11.73789482, 3.06054359, 6.10639128,\n", " 8.61800462, -0.06025906, -6.90040878, -6.85064879]))" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "baseline=faked.stat_per_event( (-200, 0 ) )\n", "response=faked.stat_per_event( ( 800, 1200) )-baseline\n", "baseline,response" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Note that `PupilData.stat_per_event()` supports selecting specific events, any summary-function (default is `numpy.mean`) and has functionality for handling missing data in the used time-windows, e.g.:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([5500.57469867, 5509.56155148, 5505.14088376, 5505.5962155 ,\n", " 5532.74450742, 5511.5497309 , 5525.53126847, 5503.84263458,\n", " 5522.51638809, 5513.12118851, 5505.3760257 , 5514.93968667,\n", " 5512.23951918, 5524.36564923, 5535.07116513, 5515.28880956,\n", " 5514.16906605, 5507.50759718, 5516.84940393, 5518.54110169,\n", " 5502.70723911, 5505.58973883, 5505.58973883, 5519.87836847,\n", " 5509.37193703, 5512.73641174, 5502.61046823, 5509.5477723 ,\n", " 5518.8241705 , 5503.16212078, 5512.51075884, 5523.16039138,\n", " 5521.92420769, 5525.61114133, 5509.62371445, 5506.67330874,\n", " 5512.29669153, 5517.6877734 , 5522.59228283, 5517.95132977]),\n", " array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", " 0., 0., 0., 0., 0., 0.]))" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "faked.stat_per_event( (-200,0), event_select=\"event\", statfct=np.median, return_missing=\"nmiss\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Advanced methods for tonic/phasic component estimation" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The simple method detailed above is appealing for its simplicity but has severe limitations. Most importantly, multiple overlapping pupillary responses can \"look like\" baseline-fluctuations when added together, thereby artificially inflating baseline-estimates particularly in cases where events are spaced closely in time (\"fast paradigms\"). For that reason, we developed specialized algorithms to disentangle tonic and phasic components of the pupillometric signal.\n", "\n", "This algorithm uses an iterative procedure to remove an initial estimate of the responses from the signal to continue to estimate the underlying baseline. Details about how this algorithm works and which parameters it supports are available in [this notebook](symp_talk_uit2019.html) and will be available in a forthcoming publication.\n", "\n", "In practice, the functionality is implemented in `PupilData.estimate_baseline()` and `PupilData.estimate_response()`. The response-estimation depends on the estimated baseline, hence the `estimate_baseline()` function should always be called first. In order to increase speed, we filter the data and downsample it to 50 Hz before running the baseline- and response-estimation functions" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "13:38:00 - cmdstanpy - INFO - compiling stan file /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.stan to exe file /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac\n", "13:38:11 - cmdstanpy - INFO - compiled model executable: /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac\n", "13:38:11 - cmdstanpy - WARNING - Stan compiler has produced 1 warnings:\n", "13:38:11 - cmdstanpy - WARNING - \n", "--- Translating Stan model to C++ code ---\n", "bin/stanc --o=/Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.hpp /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.stan\n", "Warning in '/Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.stan', line 25, column 2: Declaration\n", " of arrays by placing brackets after a variable name is deprecated and\n", " will be removed in Stan 2.33.0. Instead use the array keyword before the\n", " type. This can be changed automatically using the auto-format flag to\n", " stanc\n", "\n", "--- Compiling, linking C++ code ---\n", "clang++ -std=c++1y -Wno-unknown-warning-option -Wno-tautological-compare -Wno-sign-compare -D_REENTRANT -Wno-ignored-attributes -I stan/lib/stan_math/lib/tbb_2020.3/include -O3 -I src -I stan/src -I stan/lib/rapidjson_1.1.0/ -I lib/CLI11-1.9.1/ -I stan/lib/stan_math/ -I stan/lib/stan_math/lib/eigen_3.4.0 -I stan/lib/stan_math/lib/boost_1.78.0 -I stan/lib/stan_math/lib/sundials_6.1.1/include -I stan/lib/stan_math/lib/sundials_6.1.1/src/sundials -DBOOST_DISABLE_ASSERTS -c -include-pch stan/src/stan/model/model_header.hpp.gch -x c++ -o /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.o /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.hpp\n", "clang++ -std=c++1y -Wno-unknown-warning-option -Wno-tautological-compare -Wno-sign-compare -D_REENTRANT -Wno-ignored-attributes -I stan/lib/stan_math/lib/tbb_2020.3/include -O3 -I src -I stan/src -I stan/lib/rapidjson_1.1.0/ -I lib/CLI11-1.9.1/ -I stan/lib/stan_math/ -I stan/lib/stan_math/lib/eigen_3.4.0 -I stan/lib/stan_math/lib/boost_1.78.0 -I stan/lib/stan_math/lib/sundials_6.1.1/include -I stan/lib/stan_math/lib/sundials_6.1.1/src/sundials -DBOOST_DISABLE_ASSERTS -Wl,-L,\"/Users/mmi041/.cmdstan/cmdstan-2.32.2/stan/lib/stan_math/lib/tbb\" -Wl,-rpath,\"/Users/mmi041/.cmdstan/cmdstan-2.32.2/stan/lib/stan_math/lib/tbb\" /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.o src/cmdstan/main.o -Wl,-L,\"/Users/mmi041/.cmdstan/cmdstan-2.32.2/stan/lib/stan_math/lib/tbb\" -Wl,-rpath,\"/Users/mmi041/.cmdstan/cmdstan-2.32.2/stan/lib/stan_math/lib/tbb\" stan/lib/stan_math/lib/sundials_6.1.1/lib/libsundials_nvecserial.a stan/lib/stan_math/lib/sundials_6.1.1/lib/libsundials_cvodes.a stan/lib/stan_math/lib/sundials_6.1.1/lib/libsundials_idas.a stan/lib/stan_math/lib/sundials_6.1.1/lib/libsundials_kinsol.a stan/lib/stan_math/lib/tbb/libtbb.dylib stan/lib/stan_math/lib/tbb/libtbbmalloc.dylib stan/lib/stan_math/lib/tbb/libtbbmalloc_proxy.dylib -o /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac\n", "rm -f /Users/mmi041/miniconda3/envs/pypil/lib/python3.11/site-packages/pypillometry/stan/baseline_model_asym_laplac.o\n", "\n", "13:38:11 - cmdstanpy - INFO - Chain [1] start processing\n", "13:38:12 - cmdstanpy - INFO - Chain [1] done processing\n", "13:38:12 - cmdstanpy - INFO - Chain [1] start processing\n", "13:38:12 - cmdstanpy - INFO - Chain [1] done processing\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "MSG: optimizing both npar and tmax, might take a while...\n", "....RUNNING THE L-BFGS-B CODE\n", "\n", " * * *\n", "\n", "Machine precision = 2.220D-16\n", " N = 2 M = 10\n", "\n", "At X0 0 variables are exactly at the bounds\n", "\n", "At iterate 0 f= 5.02201D+03 |proj g|= 1.00000D+01\n", "......\n", "At iterate 1 f= 4.83098D+03 |proj g|= 1.14786D+01\n", "...\n", "At iterate 2 f= 4.82977D+03 |proj g|= 2.68592D+00\n", "....................................\n", "At iterate 3 f= 4.82861D+03 |proj g|= 1.12658D+01\n", "............................................................\n", "At iterate 4 f= 4.82860D+03 |proj g|= 1.12654D+01\n", ".........................................................\n", "At iterate 5 f= 4.82860D+03 |proj g|= 1.12654D+01\n", "...\n", "At iterate 6 f= 4.82766D+03 |proj g|= 3.16377D+00\n", "....................................\n", "At iterate 7 f= 4.82758D+03 |proj g|= 3.16486D+00\n", " ys=-1.257E-04 -gs= 3.597E-02 BFGS update SKIPPED\n", "...................................................\n", "At iterate 8 f= 4.82758D+03 |proj g|= 3.10292D+00\n", "........................................................................" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n", " Bad direction in the line search;\n", " refresh the lbfgs memory and restart the iteration.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "...............................................\n", " * * *\n", "\n", "Tit = total number of iterations\n", "Tnf = total number of function evaluations\n", "Tnint = total number of segments explored during Cauchy searches\n", "Skip = number of BFGS updates skipped\n", "Nact = number of active bounds at final generalized Cauchy point\n", "Projg = norm of the final projected gradient\n", "F = final function value\n", "\n", " * * *\n", "\n", " N Tit Tnf Tnint Skip Nact Projg F\n", " 2 9 128 11 1 0 3.103D+00 4.828D+03\n", " F = 4827.5801130770069 \n", "\n", "ABNORMAL_TERMINATION_IN_LNSRCH \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n", " Line search cannot locate an adequate point after MAXLS\n", " function and gradient evaluations.\n", " Previous x, f and g restored.\n", " Possible causes: 1 error in function or gradient evaluation;\n", " 2 rounding error dominate computation.\n" ] } ], "source": [ "d=faked.lowpass_filter(cutoff=5)\\\n", " .downsample(fsd=50)\\\n", " .estimate_baseline()\\\n", " .estimate_response()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Here, we allowed the two shape parameters `npar` and `tmax` to vary freely together with the amplitude of the responses. This allows an individualized shape of the pupillary response for each subject (which appears reasonable given the results in Hoeks & Levelt, 1993) but may also take a long time to optimize and potentially results in pathological solutions. In that case, one or both of the parameters can be fixed, for example to reasonable group-level values.\n", "\n", "After running these methods, the baseline is stored in the `PupilData.baseline` variable:\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([5506.60211363, 5506.59273533, 5506.5834325 , ..., 5485.23638076,\n", " 5484.3357519 , 5483.75875634])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.baseline" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "and the estimated response in `PupilData.response_pars`:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'npar': 12.133905825194027,\n", " 'npar_free': True,\n", " 'tmax': 898.7234873463632,\n", " 'tmax_free': True,\n", " 'coef': array([ 6.45214962, 7.60798074, 5.78462218, 28.48222728, 8.72415534,\n", " 1.63101216, 8.68602903, 3.46276526, 8.75802417, 3.99823936,\n", " 2.43358659, 6.28152258, 5.13713739, 5.93687642, 7.76130068,\n", " 9.48397437, 5.13520711, 3.96577155, 6.35544905, 4.47026992,\n", " 8.15474015, 7.52196319, 0. , 0.87014452, 7.6776929 ,\n", " 5.11455988, 6.19950358, 7.42388264, 0.84350501, 5.67189297,\n", " 4.80263714, 1.47131671, 0. , 10.11872253, 1.68426276,\n", " 0. , 5.86399889, 2.06501056, 0.46787953, 17.56992387]),\n", " 'bounds': {'npar': (1, 20), 'tmax': (100, 2000)}}" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.response_pars" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The resulting baseline-estimation and the estimated full model (baseline+response) can be plotted:\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15,5))\n", "d.plot()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The orange curve (estimated baseline) is still more wiggly than the real baseline (green) but give a considerable better estimate than a traditional method. The overall fit of the model (red) is excellent (which is to be expected, as this is simulated data). The misfit comes from randomly interspersed \"spurious\" events in the randomly generated data.\n", "\n", "We can quantify how well the novel baseline-estimation works relative to the traditional method by comparing it to the \"ground-truth\" which is available for artificial data." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We calculate the ground-truth and the traditional and novel estimates for each event-onset (=trial):" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "real_baseline=pp.stat_event_interval(d.tx, d.sim_baseline, d.event_onsets, [0,0])\n", "real_response=d.sim_response_coef\n", "\n", "traditional_baseline=d.stat_per_event( (-200,0) )\n", "traditional_response=d.stat_per_event( ( 800,1200) )-traditional_baseline\n", "\n", "novel_baseline=pp.stat_event_interval(d.tx, d.baseline, d.event_onsets, [0,0])\n", "novel_response=d.response_pars[\"coef\"]" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "And compare them by means of the correlation of the estimated and mean values:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Traditional method:\n", "Baseline: Corr(trad,real)= 0.4040649388855033\n", "Response: Corr(trad,real)= 0.24671355233788791\n", "\n", "\n", "Novel method:\n", "Baseline: Corr(nov, real)= 0.5735089277947327\n", "Response: Corr(nov, real)= 0.567976353827413\n" ] } ], "source": [ "print(\"Traditional method:\")\n", "print(\"Baseline: Corr(trad,real)=\",scipy.stats.pearsonr(traditional_baseline, real_baseline)[0])\n", "print(\"Response: Corr(trad,real)=\",scipy.stats.pearsonr(traditional_response, real_response)[0])\n", "print(\"\\n\")\n", "print(\"Novel method:\")\n", "print(\"Baseline: Corr(nov, real)=\",scipy.stats.pearsonr(novel_baseline, real_baseline)[0])\n", "print(\"Response: Corr(nov, real)=\",scipy.stats.pearsonr(novel_response, real_response)[0])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We see that the correlations are much higher for the novel method when compared to the traditional methods. More sophisticated simulation studies are reported in [this notebook](symp_talk_uit2019.html)." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "\n", "The parameters for the baseline-estimation function are described in the API-documentation for `pypillometry.baseline.baseline_envelope_iter_bspline()` and, in more detail, in [this notebook](symp_talk_uit2019.html).\n", "\n", "The parameters for the response-estimation function are described in the API-documentation for `pypillometry.pupil.pupil_response()`." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 4 }