├── .gitignore ├── README.md ├── Syllabus.pdf ├── lecture_10 ├── Lecture10_geneticmanipulationsPart2.pdf ├── desktop.ini ├── lecture_10.txt ├── lecture_10_screenshot_01.PNG ├── lecture_10_screenshot_02.PNG ├── lecture_10_screenshot_03.PNG ├── lecture_10_screenshot_04.PNG ├── lecture_10_screenshot_05.PNG └── pcr origin_KBMullisSciAm.pdf ├── lecture_11 ├── Lecture11_Highthroughputmicroscopy.pdf ├── desktop.ini ├── lecture_11.txt ├── lecture_11_screenshot_01.PNG ├── lecture_11_screenshot_02.PNG ├── lecture_11_screenshot_03.PNG ├── lecture_11_screenshot_04.PNG └── lecture_11_screenshot_05.PNG ├── lecture_12 ├── Lecture12_experimentaldesign.pdf └── lecture_12_screenshot_01.PNG ├── lecture_3 ├── CH13-annotated.PDF ├── delgado_wireless_chimp_recordings.pdf ├── lecture_03.txt ├── lecture_03_screenshot1.png ├── lecture_03_screenshot2.png ├── lecture_3.pdf └── lecture_3.pptx ├── lecture_4 ├── lecture_04_screenshot1.png ├── lecture_04_screenshot2.png ├── lecture_04_screenshot3.png └── lecture_4.txt ├── lecture_5 ├── Sjulson et al. 2016 - Cell-specific targeting of genetically encoded tools for neuroscience.pdf ├── lecture_5.pdf ├── lecture_5.pptx ├── lecture_5.txt ├── lecture_5_screenshot0.PNG ├── lecture_5_screenshot1.PNG ├── lecture_5_screenshot2.PNG ├── lecture_5_screenshot3.PNG ├── lecture_5_screenshot4.PNG ├── readme_before.txt └── sabatini_optical_reporters.pdf ├── lecture_6 ├── lecture_6.txt ├── lecture_6_screenshot1.PNG ├── lecture_6_screenshot2.PNG ├── lecture_6_screenshot3.PNG ├── lecture_6_screenshot4.PNG ├── lecture_6_screenshot5.PNG ├── lecture_6_screenshot6.PNG ├── lecture_6_screenshot7.PNG └── lecture_6_screenshot8.PNG ├── lecture_7 ├── lecture_7.txt ├── lecture_7_screenshot_01.PNG ├── lecture_7_screenshot_02.PNG ├── lecture_7_screenshot_03.PNG ├── lecture_7_screenshot_04.PNG ├── lecture_7_screenshot_05.PNG ├── lecture_7_screenshot_06.PNG └── lecture_7_screenshot_07.PNG ├── lecture_8 ├── Lecture8_Anatomy.pdf ├── lecture_8.txt ├── lecture_8_screenshot_01.PNG ├── lecture_8_screenshot_02.PNG ├── lecture_8_screenshot_03.PNG ├── lecture_8_screenshot_04.PNG └── lecture_8_screenshot_05.PNG ├── lecture_9 ├── Lecture9_geneticmanipulationpart1.pdf ├── lecture_9.txt ├── lecture_9_screenshot_01.PNG ├── lecture_9_screenshot_02.PNG ├── lecture_9_screenshot_03.PNG ├── lecture_9_screenshot_04.PNG └── lecture_9_screenshot_05.PNG ├── lectures_1-2 ├── lecture_01.txt ├── lecture_01_screenshot.png ├── lecture_02.txt ├── lecture_02_screenshot1.png ├── lecture_02_screenshot2.png ├── lecture_2_powerpoint │ ├── amplifier_analogin_auxiliary_int16.dat │ ├── data_formats1.m │ ├── desktop.ini │ ├── fermat.m │ ├── methods_lecture_2.pdf │ └── methods_lecture_2.pptx └── readings_lecture_1-2 │ ├── CH2-annotated.PDF │ ├── CH3-annotated.PDF │ ├── CH4-annotated.PDF │ ├── CH5-annotated.PDF │ ├── CH6-annotated.PDF │ └── readme.txt └── other_stuff ├── Final_methodscourse_04232020.docx ├── Final_methodscourse_04232020.pdf └── Quiz questions_methodscourse04232020.pdf /.gitignore: -------------------------------------------------------------------------------- 1 | # pycharm 2 | .idea 3 | 4 | # temporary folder 5 | temp/ 6 | 7 | # matlab stuff 8 | # Windows default autosave extension 9 | *.asv 10 | 11 | # OSX / *nix default autosave extension 12 | *.m~ 13 | 14 | # python stuff 15 | __pycache* 16 | 17 | # Compiled MEX binaries (all platforms) 18 | *.mex* 19 | 20 | # Windows image file caches 21 | Thumbs.db 22 | ehthumbs.db 23 | 24 | # Folder config file 25 | Desktop.ini 26 | 27 | # Recycle Bin used on file shares 28 | $RECYCLE.BIN/ 29 | 30 | # Windows Installer files 31 | *.cab 32 | *.msi 33 | *.msm 34 | *.msp 35 | 36 | # Windows shortcuts 37 | *.lnk 38 | 39 | # ========================= 40 | # Operating System Files 41 | # ========================= 42 | 43 | # OSX 44 | # ========================= 45 | 46 | .DS_Store 47 | .AppleDouble 48 | .LSOverride 49 | 50 | # Thumbnails 51 | ._* 52 | 53 | # Files that might appear in the root of a volume 54 | .DocumentRevisions-V100 55 | .fseventsd 56 | .Spotlight-V100 57 | .TemporaryItems 58 | .Trashes 59 | .VolumeIcon.icns 60 | 61 | # Directories potentially created on remote AFP share 62 | .AppleDB 63 | .AppleDesktop 64 | Network Trash Folder 65 | Temporary Items 66 | .apdisk 67 | 68 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # methods_class 2 | Approaches to Study Neural Circuits 3 | 4 | The class is now finished. All 12 lectures are recorded and available 5 | to watch. All course materials, including assigned readings and 6 | lecture slides, are under the "code" tab, or in the "View code" folder 7 | if you're on a mobile device. 8 | 9 | We have done our best to ensure all of the course material is accurate, 10 | but any necessary corrections will be in each lecture folder. If there 11 | are any questions or problems, or if you note any inaccuracies or 12 | important omissions, email luke@sjulsonlab.org 13 | 14 | Lecture 1: Signals and data acquisition hardware 15 | (note: Lecture 1 is a little rough, but the subsequent ones are more 16 | polished) 17 | https://www.youtube.com/watch?v=3mldM94od3g 18 | 19 | Lecture 2: Sampling, filtering, convolution, digital data formats 20 | https://www.youtube.com/watch?v=9MAQtmK0b14 21 | 22 | Lecture 3: Electrophysiology 1 (the basics) 23 | https://www.youtube.com/watch?v=Z-SOnQ9v6M8 24 | 25 | Lecture 4: Electrophysiology 2 (data preprocessing and spike sorting) 26 | https://www.youtube.com/watch?v=0iukrKY34y4 27 | 28 | Lecture 5: Fluorescent proteins; genetically encoded sensors and 29 | actuators (e.g. GCaMP, optogenetics, chemogenetics) 30 | https://www.youtube.com/watch?v=ebC5FL1kY1w 31 | 32 | Lecture 6: In vivo imaging from photometry to miniscopes 33 | https://www.youtube.com/watch?v=YG6w5lV0Lwg 34 | 35 | Lecture 7: In vivo imaging: from images to data 36 | https://www.youtube.com/watch?v=9juDmbkAUmY 37 | 38 | Lecture 8: Anatomical tracing techniques 39 | https://www.youtube.com/watch?v=HXJGraPHS6g 40 | 41 | Lecture 9: Lesions, pharmacology, and genetic manipulations 42 | https://www.youtube.com/watch?v=rqWcUTQFOR0 43 | 44 | Lecture 10: Genetic manipulations part 2; sequencing and analyses of gene expression, scRNA-seq 45 | https://www.youtube.com/watch?v=yOQ3vf7iaaQ 46 | 47 | Lecture 11: High throughput microscopy and brain clearing 48 | https://www.youtube.com/watch?v=37hkOQP2zZQ 49 | 50 | Lecture 12: Experimental design (new lecture added in 2024) 51 | https://www.youtube.com/watch?v=0VhXJMyT4Ik 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | -------------------------------------------------------------------------------- /Syllabus.pdf: -------------------------------------------------------------------------------- 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to recorded lecture: 2 | https://einsteinmed.zoom.us/rec/share/5vVPPp_S8GNIWbPx63DQdZR4EKG0X6a8hCMdr_AOnkqLwTsrNKpz2KwwUlSgK86l 3 | -------------------------------------------------------------------------------- /lecture_10/lecture_10_screenshot_01.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_10/lecture_10_screenshot_01.PNG -------------------------------------------------------------------------------- /lecture_10/lecture_10_screenshot_02.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_10/lecture_10_screenshot_02.PNG -------------------------------------------------------------------------------- /lecture_10/lecture_10_screenshot_03.PNG: 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-------------------------------------------------------------------------------- /lecture_11/lecture_11.txt: -------------------------------------------------------------------------------- 1 | Link to the recorded lecture: 2 | 3 | Topic: methods class 11 4 | Date: Apr 30, 2020 10:25 AM Eastern Time (US and Canada) 5 | 6 | Meeting Recording: 7 | https://einsteinmed.zoom.us/rec/share/6-dRD5zv7mRIRZ3yynv1Ao8eF7nJaaa8gyQcrKcEmE-CFx-8km5ET0Qu3ki4Iy_x 8 | -------------------------------------------------------------------------------- /lecture_11/lecture_11_screenshot_01.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_11/lecture_11_screenshot_01.PNG -------------------------------------------------------------------------------- /lecture_11/lecture_11_screenshot_02.PNG: 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https://einsteinmed.zoom.us/rec/share/y5AkC-zL2V1IXYGRuWrWGbZiPYK_T6a80CMd_vAEnkzlo4dcbw3CQrJVG_edQlVw 5 | 6 | Additional notes for lecture 3 (i.e. things I forgot to mention): 7 | 8 | - one of the big limitations of almost all electrode-based ephys 9 | approaches is that they are only stable for a limited period of time. 10 | For intracellular recordings, a couple of hours at best. For 11 | extracellular recordings, they could be stable for much longer 12 | than that, but unless you record continuously 24 hrs/day, it is 13 | impossible to know whether the units you see on Tuesday were the 14 | same ones you saw on Monday. So one major advantage of calcium 15 | imaging is the possibility of tracking the same cells longitudinally 16 | over time, which is useful for studying learning, memory, drug 17 | addiction, etc. 18 | 19 | - I forgot to talk about this, but the newest electrode technology 20 | for extracellular recordings is to make electrodes printed on 21 | flexible plastic coils. You wrap the flexible coils around a thin 22 | needle and attach them with water-soluble nontoxic glue. Then you 23 | insert the needle into the brain, allow the glue to dissolve, and 24 | pull the needle out. The flexibility of the electrodes approximately 25 | matches the mechanical properties of the brain, so they flex and 26 | move with the brain tissue. In some studies, the electrodes were 27 | still working perfectly after six months of recording, and it is 28 | possible they would be stable for years. It is worth pointing out 29 | that previous studies have found that the main cause of gliosis 30 | and cell death around electrode sites is the chronic motion of 31 | the electrode back and forth, mechanically traumatizing the tissue. 32 | 33 | - I am also including the PDF of the Delgado paper from 1970 34 | showing wireless recordings in a freely moving chimpanzee. 35 | 36 | 37 | 38 | -------------------------------------------------------------------------------- /lecture_3/lecture_03_screenshot1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_3/lecture_03_screenshot1.png -------------------------------------------------------------------------------- /lecture_3/lecture_03_screenshot2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_3/lecture_03_screenshot2.png -------------------------------------------------------------------------------- /lecture_3/lecture_3.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_3/lecture_3.pdf -------------------------------------------------------------------------------- /lecture_3/lecture_3.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_3/lecture_3.pptx -------------------------------------------------------------------------------- /lecture_4/lecture_04_screenshot1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_4/lecture_04_screenshot1.png -------------------------------------------------------------------------------- /lecture_4/lecture_04_screenshot2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_4/lecture_04_screenshot2.png -------------------------------------------------------------------------------- /lecture_4/lecture_04_screenshot3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_4/lecture_04_screenshot3.png -------------------------------------------------------------------------------- /lecture_4/lecture_4.txt: -------------------------------------------------------------------------------- 1 | Lecture 4: extracellular electrophysiology demo 2 | 3 | The link for the recorded lecture is here: 4 | https://einsteinmed.zoom.us/rec/share/5eF_NpHL7yBOXaPd51vkfJMkBN34eaa8hCAcrvdYnUmHx2R23FV6Vz9l_BmDQ_Kv -------------------------------------------------------------------------------- /lecture_5/Sjulson et al. 2016 - Cell-specific targeting of genetically encoded tools for neuroscience.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/Sjulson et al. 2016 - Cell-specific targeting of genetically encoded tools for neuroscience.pdf -------------------------------------------------------------------------------- /lecture_5/lecture_5.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5.pdf -------------------------------------------------------------------------------- /lecture_5/lecture_5.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5.pptx -------------------------------------------------------------------------------- /lecture_5/lecture_5.txt: -------------------------------------------------------------------------------- 1 | Link for recording of lecture 5: 2 | 3 | https://einsteinmed.zoom.us/rec/share/u-BxP7bU9kFJAbPB0nnRRIIaJqWieaa8hCAcrqVbxBuCsxTZl1bM9YEksKURmIel 4 | 5 | Tiago's notes: 6 | - many FPs have significant pH sensitivity (e.g. Citrine) 7 | - FPs can show "blinking" behavior, where their light output goes up and down 8 | (interesting biophysics but not relevant in most neuroscience applications 9 | - DsRed and some red FP's start off green and slowly mature into the red state. 10 | Most modern RFP's don't have this issue. 11 | - another important factor complicating analysis of GCaMP data is when there is 12 | heterogeneous GCaMP expression across the cell population, e.g. if you 13 | use AAV. 14 | 15 | -------------------------------------------------------------------------------- /lecture_5/lecture_5_screenshot0.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5_screenshot0.PNG -------------------------------------------------------------------------------- /lecture_5/lecture_5_screenshot1.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5_screenshot1.PNG -------------------------------------------------------------------------------- /lecture_5/lecture_5_screenshot2.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5_screenshot2.PNG -------------------------------------------------------------------------------- /lecture_5/lecture_5_screenshot3.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5_screenshot3.PNG -------------------------------------------------------------------------------- /lecture_5/lecture_5_screenshot4.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/lecture_5_screenshot4.PNG -------------------------------------------------------------------------------- /lecture_5/readme_before.txt: -------------------------------------------------------------------------------- 1 | hi everyone, 2 | 3 | The Sabatini paper discusses the influence of reporter kinetics on interpretation 4 | of imaging experiments, including a discussion of a controversial high-profile 5 | result about dopamine that he argues may be artifactual. Everything he says 6 | applies to optogenetic experiments as well. 7 | 8 | The review paper that I wrote focuses on the topic of how to target transgenes 9 | to specific neurons of interest and the various pitfalls you have to watch for. 10 | I wrote this review because people ask me questions about this all the time, 11 | and I wanted there to be a guide that collects all the information in one place. 12 | It is up to date, with a few exceptions: 1) since then, people have had 13 | success with transsynaptic anterograde transduction of cells using AAV-1 expressing 14 | Cre or Flp. Flp is better because high-level Cre expression is toxic, and you 15 | frequently get toxicity at the injection site. 2) AAVs with mutant capsids that 16 | transduce axon terminals with higher efficiency now exist ("retroAAV"). These 17 | work well in some cell types but not others. 3) Ben Deverman has developed 18 | the PHP capsids for AAV, which are mutant AAV9 capsids that were selected for 19 | their ability to access neurons from the bloodstream. People now routinely 20 | inject those AAVs intravenously in mice and can get fairly uniform labeling of 21 | neurons in the entire brain (with low copy numbers of viral genomes/cell). 22 | 4) Several different groups are making progress by finding short distal 23 | enhancer elements in the genome that can be used in AAVs to target specific 24 | cell types. Jordane Dimidschstein is the one who pioneered this, and he and Ben 25 | are collaborating now. Combining those technologies successfully would 26 | reduce our dependence on transgenic animals substantially and enable these 27 | technologies to be used in a wider range of animals (including primates). 28 | We will not discuss the topic of transgene targeting in class, but I 29 | recommend that you read through the paper. There are far too many serious 30 | mistakes that people have made because they did not understand these principles. 31 | 32 | Luke 33 | 34 | 35 | 36 | -------------------------------------------------------------------------------- /lecture_5/sabatini_optical_reporters.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_5/sabatini_optical_reporters.pdf -------------------------------------------------------------------------------- /lecture_6/lecture_6.txt: -------------------------------------------------------------------------------- 1 | Lecture 6: in vivo imaging 2 | 3 | Link to recorded lecture: 4 | https://einsteinmed.zoom.us/rec/share/uOJ-M6_77V9OGqvz9VHzY68YD9znT6a81yMXq_EPzBygw3qVocY-OqB9iX4TfjND -------------------------------------------------------------------------------- /lecture_6/lecture_6_screenshot1.PNG: 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-------------------------------------------------------------------------------- /lecture_8/lecture_8.txt: -------------------------------------------------------------------------------- 1 | Here is the zoom link for the recorded lecture: 2 | 3 | https://einsteinmed.zoom.us/rec/share/_ehsBKr6_DNJfI331m3cce0GEILBeaa8hihP_6AFzMqvfHf_UnyfEU1IpE1PGmA -------------------------------------------------------------------------------- /lecture_8/lecture_8_screenshot_01.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lecture_8/lecture_8_screenshot_01.PNG -------------------------------------------------------------------------------- /lecture_8/lecture_8_screenshot_02.PNG: -------------------------------------------------------------------------------- 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https://einsteinmed.zoom.us/rec/share/wspaJaivyjlLeK_M5BvPRah9Lp__X6a8g3NI-vRfyB57suy8-fvnhCOQO-JeZbVc 5 | 6 | An important practical point that separates the novices 7 | from the experts: 8 | 9 | Never place anything electrical on the floor. Labs flood 10 | routinely. Buy platforms to elevate your equipment 11 | by 10 cm off the floor. -------------------------------------------------------------------------------- /lectures_1-2/lecture_01_screenshot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_01_screenshot.png -------------------------------------------------------------------------------- /lectures_1-2/lecture_02.txt: -------------------------------------------------------------------------------- 1 | Lecture 2: sampling, filtering, convolution, and digital data formats 2 | 3 | Additional notes from lecture 2: 4 | 5 | - if you copy large data files, especially over the network, use 6 | robocopy on windows or rsync on mac/linux. These programs copy 7 | your files and verify that they were copied without errors. The 8 | regular copy-by-dragging-folder method corrupts files surprisingly 9 | often. 10 | 11 | - It is worth repeating: the failure rate of hard drives is 100%. 12 | 13 | 14 | Link to recording of lecture 2: 15 | https://einsteinmed.zoom.us/rec/share/vMlEP57NyEJIWNbT-EGCBKgwNavKX6a8hnUYqaBfnR6xpWNanEnSAMQaEg2E7Ovo -------------------------------------------------------------------------------- /lectures_1-2/lecture_02_screenshot1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_02_screenshot1.png -------------------------------------------------------------------------------- /lectures_1-2/lecture_02_screenshot2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_02_screenshot2.png -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/amplifier_analogin_auxiliary_int16.dat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_2_powerpoint/amplifier_analogin_auxiliary_int16.dat -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/data_formats1.m: -------------------------------------------------------------------------------- 1 | % looking at data formats 2 | 3 | clear all 4 | close all 5 | clc 6 | 7 | %% load in Intan data 8 | cd('G:\My Drive\lab-private\lab-teaching\2020_techniques\lecture_2'); 9 | 10 | fid = fopen('amplifier_analogin_auxiliary_int16.dat', 'rb'); 11 | raw_data = int16(fread(fid, Inf, 'int16')); % the reason I have to put int16 there is because matlab automatically converts to doubles 12 | fclose(fid); 13 | 14 | % reshape into matrix reflecting the number of channels 15 | nChan = 7; % 7 channels 16 | reshaped_data = reshape(raw_data, nChan, length(raw_data)/nChan)'; 17 | 18 | 19 | %% convert to double - we need to do this if we're going to do any math 20 | reshaped_data_double = double(reshaped_data); 21 | 22 | 23 | %% plotting 24 | Fs = 20000; % 20 kHz sampling 25 | timevec = 1/Fs:1/Fs:size(reshaped_data_double, 1)/Fs; 26 | 27 | p1 = plot(timevec, reshaped_data_double); 28 | x1 = xlabel('Time (seconds)'); -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | ConfirmFileOp=0 3 | IconResource=C:\Program Files\Google\Drive File Stream\37.0.8.0\GoogleDriveFS.exe,21 4 | -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/fermat.m: -------------------------------------------------------------------------------- 1 | %% did Homer Simpson disprove Fermat's Last Theorem? 2 | % It states that there are no positive integer solutions to 3 | % 4 | % x^n + y^n = z^n 5 | % for any n > 2. 6 | % 7 | % However, Homer is shown writing this on a blackboard: 8 | % 9 | % 3987^12 + 4365^12 = 4472^12 10 | % 11 | % is he right? 12 | 13 | clear all 14 | clc 15 | format long % this is to print all the decimal places 16 | 17 | %% set variables 18 | disp('Fermat''s Theorem state: there are no positive integer solutions for'); 19 | disp('x^n + y^n = z^n, where n > 2'); 20 | disp(' '); 21 | disp('Homer wrote: 3987^12 + 4365^12 = 4472^12'); 22 | % disp(' '); 23 | % disp([]); 24 | 25 | x = 3987 26 | y = 4365 27 | z = 4472 28 | 29 | whos 30 | 31 | %% show answer 32 | disp('The answer is:'); 33 | disp(' '); 34 | disp(['x^12 + y^12 = ' num2str(x^12 + y^12)]) 35 | disp([' z^12 = ' num2str(z^12)]) 36 | disp(' ') 37 | 38 | %% calculate difference 39 | disp('Was Homer right? How big is the error?'); 40 | disp(['x^12 + y^12 - z^12 = ' num2str(x^12 + y^12 - z^12)]) 41 | disp(' '); 42 | -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/methods_lecture_2.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_2_powerpoint/methods_lecture_2.pdf -------------------------------------------------------------------------------- /lectures_1-2/lecture_2_powerpoint/methods_lecture_2.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/lecture_2_powerpoint/methods_lecture_2.pptx -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/CH2-annotated.PDF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/readings_lecture_1-2/CH2-annotated.PDF -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/CH3-annotated.PDF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/readings_lecture_1-2/CH3-annotated.PDF -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/CH4-annotated.PDF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/readings_lecture_1-2/CH4-annotated.PDF -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/CH5-annotated.PDF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/readings_lecture_1-2/CH5-annotated.PDF -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/CH6-annotated.PDF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/lectures_1-2/readings_lecture_1-2/CH6-annotated.PDF -------------------------------------------------------------------------------- /lectures_1-2/readings_lecture_1-2/readme.txt: -------------------------------------------------------------------------------- 1 | For Lecture 1: 2 | Smith Ch. 2, p. 11-26 (signals) 3 | Smith Ch. 3, p. 35-38 (DAQ) 4 | 5 | For Lecture 2: 6 | Smith Ch. 4, p. 67-76 (digital data formats) 7 | Smith Ch. 3, p. 39-44, 48-49, and 52-58 (sampling/filters/convolution) 8 | Smith Ch. 5 (linear systems) 9 | Smith Ch. 6 (convolution) 10 | -------------------------------------------------------------------------------- /other_stuff/Final_methodscourse_04232020.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/other_stuff/Final_methodscourse_04232020.docx -------------------------------------------------------------------------------- /other_stuff/Final_methodscourse_04232020.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/other_stuff/Final_methodscourse_04232020.pdf -------------------------------------------------------------------------------- /other_stuff/Quiz questions_methodscourse04232020.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SjulsonLab/methods_class/070fcb22ddfa8c5c40169b60de08945bed91831f/other_stuff/Quiz questions_methodscourse04232020.pdf --------------------------------------------------------------------------------