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\n RowBox[{\"#\", \"[\", \n RowBox[{\"[\", \"1\", \"]\"}], \"]\"}]}], \",\", \n RowBox[{\"\\\"\\<ClusterFilled\\>\\\"\", \"->\", \n RowBox[{\"#\", \"[\", \n RowBox[{\"[\", \"2\", \"]\"}], \"]\"}]}], \",\", \n RowBox[{\"\\\"\\<n\\>\\\"\", \"->\", \n RowBox[{\"#\", \"[\", \n RowBox[{\"[\", \"3\", \"]\"}], \"]\"}]}], \",\", \n RowBox[{\"\\\"\\<S\\>\\\"\", \"->\", \n RowBox[{\"#\", \"[\", \n"}}},{"rowIdx":548972,"cells":{"sha256":{"kind":"string","value":"12dc7071ac6847e29cc7e089ea2c30126cc0df479bb590ee295637f13a2d5804"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":63,"string":"63"},"lines":{"kind":"number","value":5,"string":"5"},"content":{"kind":"string","value":"//adding channels to the membrane\r\n\r\nforall{\r\n\tinsert pas \r\n}\r\n"}}},{"rowIdx":548973,"cells":{"sha256":{"kind":"string","value":"6b8e4431eb70869038674f825b0887335f99a9f3cf1be80c4368aae3c0b298b9"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":67,"string":"67"},"lines":{"kind":"number","value":3,"string":"3"},"content":{"kind":"string","value":"module github.com/replicate/cog/test-helpers/https-server\n\ngo 1.21\n"}}},{"rowIdx":548974,"cells":{"sha256":{"kind":"string","value":"dbf5459d1bfabe5fb6d225427cb7c70fe269e02b1e3e1bc03e1651a2c7cf2af8"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":81,"string":"81"},"lines":{"kind":"number","value":5,"string":"5"},"content":{"kind":"string","value":"create soma\ninsert hh\n\nsoma diam=10\n//gnabar_hh=0.12 gkbar_hh=0.036 gl_hh=0.0003\n"}}},{"rowIdx":548975,"cells":{"sha256":{"kind":"string","value":"18bf417c139f084267cf93e3d8992e11748c0332108878a99d74794a42a252b1"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":106,"string":"106"},"lines":{"kind":"number","value":6,"string":"6"},"content":{"kind":"string","value":"load_file(\"init.hoc\")\r\nload_file(\"Rm_fitting3_soma-dend.ses\")\r\n\r\nuser_e_pas = 0\r\nv_init = 0\r\nIC3_passive()"}}},{"rowIdx":548976,"cells":{"sha256":{"kind":"string","value":"6b30a8a9b39ea85f54567f06c1ce119d05fe280915d11b989fa756f8486e3aa6"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":114,"string":"114"},"lines":{"kind":"number","value":10,"string":"10"},"content":{"kind":"string","value":"create soma\nsoma diam=10\ninsert hh\n\nobjectvar stim\nstim = new IClamp(0.5)\n\nstim.del=200\nstim.dur=500\nstim.amp=0.2\n"}}},{"rowIdx":548977,"cells":{"sha256":{"kind":"string","value":"51d72ef55db34352f51d86b5a5f694ebb75350549dcfc7e42d7a0db0d753f71d"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":177,"string":"177"},"lines":{"kind":"number","value":17,"string":"17"},"content":{"kind":"string","value":"NEURON {\r\n SUFFIX vmax\r\n RANGE vm\r\n}\r\n\r\nASSIGNED {\r\n v (millivolt)\r\n vm (millivolt)\r\n}\r\n\r\nINITIAL {\r\n vm = v\r\n}\r\n\r\nBREAKPOINT { \r\n if (v>vm) { vm=v }\r\n}\r\n"}}},{"rowIdx":548978,"cells":{"sha256":{"kind":"string","value":"171dd73f4dcfe6e1ade91929ba1661b392a5e831a8a7b7619fad5f617a9ae83b"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":195,"string":"195"},"lines":{"kind":"number","value":13,"string":"13"},"content":{"kind":"string","value":"begintemplate ball_and_stick_template\npublic soma, dend \npublic all\nobjref all\nproc init() {\n all = new SectionList()\n}\n\ncreate soma[1], dend[1]\n\nendtemplate ball_and_stick_template\n\n\n"}}},{"rowIdx":548979,"cells":{"sha256":{"kind":"string","value":"d941933d1d98c3b9faf585212991286672c3baa5da562c3d13da1d6bc972ad08"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":206,"string":"206"},"lines":{"kind":"number","value":14,"string":"14"},"content":{"kind":"string","value":"begintemplate stick_template\npublic dend \npublic all, basal\nobjref all, basal\nproc init() {\n all = new SectionList()\n basal = new SectionList()\n}\n\ncreate dend[1]\n\nendtemplate stick_template\n\n\n"}}},{"rowIdx":548980,"cells":{"sha256":{"kind":"string","value":"48ac78ab21b87c984285cc96a543014855583717d88172d19a16c6f762670244"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":260,"string":"260"},"lines":{"kind":"number","value":9,"string":"9"},"content":{"kind":"string","value":"module gitlab.com/Grouumf/enhlinktools/matrix\n\ngo 1.15\n\nrequire (\n\tgithub.com/valyala/fastrand v1.1.0 // indirect\n\tgitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91 // indirect\n\tgonum.org/v1/gonum v0.14.0 // indirect\n)\n"}}},{"rowIdx":548981,"cells":{"sha256":{"kind":"string","value":"53b58e2e5eaae3801ead42465a0cb19b79fd3dd4714e25d2625a7e82ce1e06da"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":273,"string":"273"},"lines":{"kind":"number","value":12,"string":"12"},"content":{"kind":"string","value":"//Neuron files\r\n\r\nnrn_load_dll(\"./mods/nrnmech.dll\")\r\nload_file(\"subiter.hoc\")\r\n//load_file(\"nrngui.hoc\")\r\nload_file(\"stdrun.hoc\")\r\n\r\n//Custom files\r\n\r\nload_file(\"morphology2.hoc\")\r\nload_file(\"biophys_na_inhomo_minimal_model+KM+KA+KD.hoc\")\r\n//load_file(\"gui_shah_km.hoc\")\r\n"}}},{"rowIdx":548982,"cells":{"sha256":{"kind":"string","value":"699fc18268f9975c925f4232d3feb48863274c9664af457585fe984537359137"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":335,"string":"335"},"lines":{"kind":"number","value":27,"string":"27"},"content":{"kind":"string","value":"create soma \ninsert hh\n\naccess soma\n\nL = 17.84\ndiam = 17.84\n\nobjref ampasyn, ns, nc, vc\n\nampasyn = new Exp2Syn(0.5)\nampasyn.tau1 = 0.3\nampasyn.tau2 = 3\n\nns = new NetStim(0.5)\nns.start = 100\nns.interval = 100\n\nnc = new NetCon(ns, ampasyn)\nnc.weight = 0.01\nnc.delay = 2.0\n\nvc = new SEClamp(0.5)\nvc.rs = 0.01\nvc.dur1 = 1000\nvc.amp1= -70\n\n"}}},{"rowIdx":548983,"cells":{"sha256":{"kind":"string","value":"c7ae5edaee2d16290214853d9ec6faddbb8175c0a991f5eed4476f80778483de"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":342,"string":"342"},"lines":{"kind":"number","value":20,"string":"20"},"content":{"kind":"string","value":"proc negative_init() { local dtsav, temp\n\tfinitialize(v_init)\n\tt = -10\n\tdtsav = dt\n\tdt = 1\n\t// if cvode is on, turn it off to do a large fixed step\n\ttmp = cvode.active()\n\tif (temp!=0) { cvode.active(0) }\n\twhile (t<-1e9) {\n\t\tfadvance()\n\t}\n\tdt = dtsav\n\tt = 0\n\tif (cvode.active()) {\n\t\tcvode.re_init()\n\t}\telse {\n\t\tfcurrent()\n\t}\n\tfrecord_init()\n}\n"}}},{"rowIdx":548984,"cells":{"sha256":{"kind":"string","value":"038f5cd64f45ddd9556c89682afcd819349affa018c8b9f537aed08bd4f6b002"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":347,"string":"347"},"lines":{"kind":"number","value":27,"string":"27"},"content":{"kind":"string","value":"create soma \ninsert hh\n\naccess soma\n\nL = 17.84\ndiam = 17.84\n\nobjref ampasyn, ns, nc, vc\n\nampasyn = new Exp2Syn(0.5)\nampasyn.tau1 = 0.3\nampasyn.tau2 = 3\n\nns = new NetStim(0.5)\nns.start = 100\nns.interval = 100\n\nnc = new NetCon(ns, ampasyn)\nnc.weight = 0.01\nnc.delay = 2.0\n\n// vc = new SEClamp(0.5)\n// vc.rs = 0.01\n// vc.dur1 = 1000\n// vc.amp1= -70\n\n"}}},{"rowIdx":548985,"cells":{"sha256":{"kind":"string","value":"f70893a8382e72ccec982785a7ed15ffbd5176b1e4f9128cc68f44c526527150"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":376,"string":"376"},"lines":{"kind":"number","value":12,"string":"12"},"content":{"kind":"string","value":"/* -----------------------------------------------------------------------------\nBallAndStickTemplate.hoc\n----------------------------------------------------------------------------- */\nbegintemplate BallAndStickTemplate\npublic init, soma, apic \npublic all\nobjref all\nproc init() { all = new SectionList() }\ncreate soma[1], apic[1]\nendtemplate BallAndStickTemplate\n\n\n"}}},{"rowIdx":548986,"cells":{"sha256":{"kind":"string","value":"87fd6fbaf76598b80e613357e64324dbcc3072009178b9b10b60c3179db1f352"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":377,"string":"377"},"lines":{"kind":"number","value":11,"string":"11"},"content":{"kind":"string","value":"module gitlab.com/Grouumf/enhlinktools/enhlinkobject\n\ngo 1.15\n\nrequire (\n\tgithub.com/biogo/store v0.0.0-20201120204734-aad293a2328f\n\tgithub.com/valyala/fastrand v1.1.0\n\tgitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91\n\tgitlab.com/Grouumf/enhlinktools/matrix v0.0.0-20231204202714-1f1a9f51b6ff // indirect\n\tgonum.org/v1/gonum v0.14.0\n)\n"}}},{"rowIdx":548987,"cells":{"sha256":{"kind":"string","value":"48fedd9e9e8ce79e22d347dfc696999bfde2d38850374e6e3d167dd440444aa9"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":390,"string":"390"},"lines":{"kind":"number","value":10,"string":"10"},"content":{"kind":"string","value":"module gitlab.com/Grouumf/enhlinktools/enhtools\n\ngo 1.15\n\nrequire (\n\tgithub.com/biogo/store v0.0.0-20201120204734-aad293a2328f\n\tgitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91\n\tgitlab.com/Grouumf/enhlinktools/enhlinkobject v0.0.0-20240905014251-972a77ac315a // indirect\n\tgitlab.com/Grouumf/enhlinktools/matrix v0.0.0-20231204205650-2e84324fc3ab\n)\n"}}},{"rowIdx":548988,"cells":{"sha256":{"kind":"string","value":"2f49503b84bb6fbe1aca6b8f100b79dd8fc31faf330a7642089755b3c07c1f6d"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":398,"string":"398"},"lines":{"kind":"number","value":33,"string":"33"},"content":{"kind":"string","value":"proc celldef() {\n topol()\n subsets()\n geom()\n biophys()\n geom_nseg()\n}\n\ncreate dend\n\nproc topol() { local i\n basic_shape()\n}\nproc basic_shape() {\n dend {pt3dclear() pt3dadd(0, 0, 0, 2) pt3dadd(0, 0, 1000, 2)}\n}\n\nobjref all\nproc subsets() { local i\n objref all\n all = new SectionList()\n dend all.append()\n\n}\nproc geom() {\n}\nproc geom_nseg() {\n}\nproc biophys() {\n}\naccess dend\n\ncelldef()\n"}}},{"rowIdx":548989,"cells":{"sha256":{"kind":"string","value":"35e0414967b7e31f2ab1473e1b79fd55d65e95285ee7899aab953cd80e212a07"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":400,"string":"400"},"lines":{"kind":"number","value":17,"string":"17"},"content":{"kind":"string","value":"begintemplate LFPyCellTemplate\npublic soma, axon, dend, apic \npublic all, somatic, axonal, basal, apical \nobjref all, somatic, axonal, basal, apical\nproc init() {\n all = new SectionList()\n somatic = new SectionList()\n axonal = new SectionList()\n basal = new SectionList()\n apical = new SectionList()\n}\n\ncreate soma[1], axon[1], dend[1], apic[1]\n\nendtemplate LFPyCellTemplate\n\n\n"}}},{"rowIdx":548990,"cells":{"sha256":{"kind":"string","value":"edecbb66302d14038b01b7f80845c17c563f06ca066745aa83b9cedce8ddbf92"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":460,"string":"460"},"lines":{"kind":"number","value":13,"string":"13"},"content":{"kind":"string","value":"module gitlab.com/Grouumf/enhlinktools/enhgrid\n\ngo 1.15\n\n// replace gitlab.com/Grouumf/enhlinktools/matrix => ../matrix\n\n// replace gitlab.com/Grouumf/enhlinktools/enhlinkobject => ../enhlinkobject\n\nrequire (\n\tgitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91\n\tgitlab.com/Grouumf/enhlinktools/enhlinkobject v0.0.0-20240730164559-df9745395267\n\tgitlab.com/Grouumf/enhlinktools/matrix v0.0.0-20231204205650-2e84324fc3ab\n)\n"}}},{"rowIdx":548991,"cells":{"sha256":{"kind":"string","value":"06b12b3c773f82096da33b1ff96becce380739d75abfcf631f3a8383d6bfc22b"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":524,"string":"524"},"lines":{"kind":"number","value":40,"string":"40"},"content":{"kind":"string","value":"TITLE Gap junction current for parallel computation\n\nCOMMENT\nImplemented by Erin Munro, \ncopied largely from:\nThe NEURON Book by Nicholas T. Carnevale, Michael L. Hines\nonline at Google books\nENDCOMMENT\n\n\nUNITS { \n\t(mV) = (millivolt) \n\t(nA) = (nanoamp) \n (uS) = (microsiemens)\n} \n\n\nNEURON { \n POINT_PROCESS gapjunction\n POINTER vpre\n\t RANGE weight\n\t NONSPECIFIC_CURRENT i\n}\n\n\nPARAMETER { \n\t weight = 0.0 \t (uS)\n} \n\n\nASSIGNED {\n v (mV)\n vpre (mV)\n i (nA)\n}\n\n\nBREAKPOINT { \n\t i = weight * (v - vpre) \n} \n"}}},{"rowIdx":548992,"cells":{"sha256":{"kind":"string","value":"b6a12d34209f2f8e367db882cfabf004469787d41b9dce71d553fe8cdeaa8f19"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":533,"string":"533"},"lines":{"kind":"number","value":40,"string":"40"},"content":{"kind":"string","value":"TITLE Gap junction current for parallel computation\n\nCOMMENT\nImplemented by Erin Munro, \ncopied largely from:\nThe NEURON Book by Nicholas T. Carnevale, Michael L. Hines\nonline at Google books\nENDCOMMENT\n\n\nUNITS { \n\t(mV) = (millivolt) \n\t(nA) = (nanoamp) \n (uS) = (microsiemens)\n} \n\n\nNEURON { \n POINT_PROCESS gapjunction_advance\n\t RANGE weight, vpre\n RANGE i\n\t NONSPECIFIC_CURRENT i\n}\n\n\nPARAMETER { \n\t weight = 0.0 \t (uS)\n} \n\n\nASSIGNED {\n v (mV)\n vpre (mV)\n i (nA)\n}\n\n\nBREAKPOINT { \n\t i = weight * (v - vpre) \n} \n"}}},{"rowIdx":548993,"cells":{"sha256":{"kind":"string","value":"0a96ddbe839f09e83990ed106a81a17930178db5dc3c01aae086a4e625b8f15a"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":536,"string":"536"},"lines":{"kind":"number","value":41,"string":"41"},"content":{"kind":"string","value":"TITLE Gap junction current for parallel computation\n\nCOMMENT\nImplemented by Erin Munro, \ncopied largely from:\nThe NEURON Book by Nicholas T. Carnevale, Michael L. Hines\nonline at Google books\nENDCOMMENT\n\n\nUNITS { \n\t(mV) = (millivolt) \n\t(nA) = (nanoamp) \n (uS) = (microsiemens)\n} \n\n\nNEURON { \n POINT_PROCESS gapjunction\n POINTER vpre\n\t RANGE weight\n RANGE i\n\t NONSPECIFIC_CURRENT i\n}\n\n\nPARAMETER { \n\t weight = 0.0 \t (uS)\n} \n\n\nASSIGNED {\n v (mV)\n vpre (mV)\n i (nA)\n}\n\n\nBREAKPOINT { \n\t i = weight * (v - vpre) \n} \n"}}},{"rowIdx":548994,"cells":{"sha256":{"kind":"string","value":"532efed38d617ef2a92178476d904671bafe76fa1494ec387bd9f134b57db1c4"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":558,"string":"558"},"lines":{"kind":"number","value":18,"string":"18"},"content":{"kind":"string","value":"// Code Taken from Aberra et al, JNE 2018\n/*\n* $Id: setpointers.hoc,v 1.4 2008/12/02 22:19:41 ted Exp ted $\n* sets up the pointers after the sections have been created\n* 2018/05/20 Modified by Aman Aberra\n*/\n\nproc setpointers() { local done \n getSecRefs() // save coordinates, get section refs, and assign section types\n forall {\n if (ismembrane(\"xtra\") && ismembrane(\"extracellular\")) {\n\t\tfor (x, 0) {\t\t\n\t\t\tsetpointer ex_xtra(x), e_extracellular(x)\n\t\t}\n }\n }\n //print \"After any change to cell geometry or nseg, be sure to invoke setpointers()\"\n}\n"}}},{"rowIdx":548995,"cells":{"sha256":{"kind":"string","value":"be9735823bbcbf9cdc230a4c000c6a5df334afa1261d78ade8b0123610cfe0c2"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":610,"string":"610"},"lines":{"kind":"number","value":32,"string":"32"},"content":{"kind":"string","value":"/* -----------------------------------------------------------------------------\nBallAndStick.hoc\n----------------------------------------------------------------------------- */\n// Create sections:\ncreate soma[1]\ncreate apic[1]\n\n// Add 3D information:\nsoma[0] {\n pt3dadd(0, 0, -15, 30)\n pt3dadd(0, 0, 15, 30)\n}\napic[0] {\n pt3dadd(0, 0, 15, 3)\n pt3dadd(0, 0, 1015, 3)\n}\n\n// Connect section end points:\nconnect apic[0](0), soma[0](1)\n\n// Set biophysical parameters:\nforall {\n Ra = 100.\n cm = 1.\n all.append()\n}\nsoma { insert hh }\napic {\n insert pas\n g_pas = 0.0002\n e_pas = -65.\n}\n"}}},{"rowIdx":548996,"cells":{"sha256":{"kind":"string","value":"02b52e5d6dd3cd20a20b69087352a2ef7e6a28d9998e602949cc207503e342a5"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":614,"string":"614"},"lines":{"kind":"number","value":30,"string":"30"},"content":{"kind":"string","value":"// Code Taken from Aberra et al, JNE 2018\n/*\n* $Id: anatscale.hoc,v 1.2 2005/09/10 23:02:15 ted Exp $\n* set up xyz scale bars\n* 2018/05/20 Modified by Aman Aberra\n*/\n\ncreate xScale, yScale, zScale\nproc anatscale() {\n\tcreate xScale, yScale, zScale\n\tif ($4>0) { // if length arg is <= 0 then do nothing\n\t\txScale {\n\t\t\tpt3dclear()\n\t\t\tpt3dadd($1, $2, $3, 1)\n\t\t\tpt3dadd($1+$4, $2, $3, 1)\n\t\t}\n\t\tyScale {\n\t\t\tpt3dclear()\n\t\t\tpt3dadd($1, $2, $3, 1)\n\t\t\tpt3dadd($1, $2+$4, $3, 1)\n\t\t}\n\t\tzScale {\n\t\t\tpt3dclear()\n\t\t\tpt3dadd($1, $2, $3, 1)\n\t\t\tpt3dadd($1, $2, $3+$4, 1)\n\t\t}\n\t}\n}\n\n//anatscale(400,0,0,250) // origin xyz and length\n"}}},{"rowIdx":548997,"cells":{"sha256":{"kind":"string","value":"a98fd6abea66a6d655c147b0ff494c3d35783311da2ce1de5239c835a23ccaec"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":624,"string":"624"},"lines":{"kind":"number","value":41,"string":"41"},"content":{"kind":"string","value":"TITLE nca current for C. elegans neuron model\n\n\nCOMMENT\nchannel type: sodium passive currents\n\nmodel and parameters from:\nNicoletti, M., et al. (2019). \"Biophysical modeling of C. elegans neurons: Single ion currents and whole-cell dynamics of AWCon and RMD.\" PLoS One 14(7): e0218738.\nENDCOMMENT\n\n\nUNITS {\n (nS) = (nanosiemens)\n (mV) = (millivolt)\n (pA) = (picoamp)\n (um) = (micron)\n}\n\n\nNEURON {\n SUFFIX nca\n USEION na READ ena WRITE ina\n RANGE gbnca\n}\n\n\nPARAMETER {\n gbnca = 1 (nS/um2)\n}\n\n\nASSIGNED {\n v (mV)\n ena (mV)\n ina (pA/um2)\n}\n\n\nBREAKPOINT {\n ina = gbnca * (v - 30) :ena=30mV\n}"}}},{"rowIdx":548998,"cells":{"sha256":{"kind":"string","value":"99866817705f175ab1f6810c6018e8b23e0ea8de63845552ab887cf154a6b2bf"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":634,"string":"634"},"lines":{"kind":"number","value":32,"string":"32"},"content":{"kind":"string","value":"/* ----------------------------------------------------\nexample_morphology.hoc\n\nThis hoc file creates a neuron of the following shape:\n\n\n |\n |\n |\n O\n \nNote the conventions:\n - soma needs to be a list (soma[0], not soma),\n - use soma for the soma compartment,\n - use a name starting with dend for the dendrites.\n-----------------------------------------------------*/\n\n\ncreate soma[1]\ncreate dend[1]\n\nsoma[0] {\n pt3dadd(0, 0, 0, 20)\n pt3dadd(0, 0, 20, 20)\n}\n\ndend[0] {\n pt3dadd(0, 0, 20, 2)\n pt3dadd(0, 0, 200, 2)\n}\n\nconnect dend[0](0), soma[0](1)\n"}}},{"rowIdx":548999,"cells":{"sha256":{"kind":"string","value":"c8a30c9efcc6cd8481d096346b129d915f43b0e5195f8def823e239920b279db"},"language":{"kind":"string","value":"NEURON"},"size":{"kind":"number","value":680,"string":"680"},"lines":{"kind":"number","value":34,"string":"34"},"content":{"kind":"string","value":"/* ----------------------------------------------------\nsticks_not_connected_head_to_toe.hoc\nNote the conventions:\n - soma needs to be a list (soma[0], not soma),\n - use soma for the soma compartment,\n - use a name starting with dend for the dendrites.\n-----------------------------------------------------*/\n\n\ncreate soma, dend1, dend2, dend3\n\nsoma {\n pt3dadd(0, 0, -10, 10)\n pt3dadd(0, 0, 0, 10)\n}\n\ndend1 {\n pt3dadd(0, 0, 0, 5)\n pt3dadd(0, 0, 200, 5)\n}\n\ndend2 {\n pt3dadd(0, 0, 100, 2)\n pt3dadd(0, 20, 200, 2)\n}\n\ndend3 {\n pt3dadd(0, 0, 140, 2)\n pt3dadd(-10, -50, 200, 2)\n}\n\nconnect dend1(0), soma(1)\nconnect dend2(0), dend1(.5)\nconnect dend3(0), dend1(.7)"}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":5489,"numItemsPerPage":100,"numTotalItems":835100,"offset":548900,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sInJlcG9JZHMiOlsiNmFiODVhOGYzODBjYmQ4YzAzYWQ5MjY3Il0sImlhdCI6MTc5NDA1MDY3NCwianRpIjoiODg0MDM1ZDAtMmE4Yi00MDc3LWE3OTUtOGRkY2RmMmE3ZTViIiwic3ViIjoiL2RhdGFzZXRzL09wZW5TY2llbnRpZmljQ29kZVJlZ2lzdHJ5L0RhdGFiYXNlIiwiZXhwIjoxNzk0MDU0Mjc0LCJpc3MiOiJodHRwczovL2h1Z2dpbmdmYWNlLmNvIn0.2e6Mm4ok9rdB3mb7DnXfQKP8bPdFPY5ib5g7T-FvlQOzoVIPHuv20QhIU5o8BPXhZ58SZDTKHy187idYmIDNAA","displayUrls":true,"splitSizeSummaries":[{"config":"scripts","split":"train","numRows":835100,"numBytesParquet":1400428785}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
606d4b60735c2a97c6d42cce45ed5fdadf732d375f769b5567a887d43fb395e5 | MATLAB | 90,038 | 3,705 | function label = ft_senslabel(type, varargin)
% FT_SENSLABEL returns a list of predefined sensor labels given the
% EEG or MEG system type which can be used to detect the type of data.
%
% Use as
% label = ft_senslabel(type)
%
% The input sensor array type can be any of the following
% 'ant128'
% 'biosemi64'
% 'bi... |
ff9763ca61ad10eb469b632ffdcf299225c81782a0b4a1378f6b20a981ded405 | MATLAB | 90,215 | 2,177 | % AUTHORSHIP
% Software Developers: Rachel Finck,
% Connor Meehan <connor.gw.meehan@gmail.com>
% Stephen Meehan <swmeehan@stanford.edu>
%
% ORIGINAL PUBLICATION
% http://cgworkspace.cytogenie.org/GetDown2/demo/dbm.pdf
%
% PUBLICATION REVISIONS
% https://stat... |
f90362ae3c291f0b7f3a96f1829cd281b1b3b7839d37645d60a71e65e70cb25c | MATLAB | 90,307 | 2,183 | function varargout = findallofthem(varargin)
% FINDALLOFTHEM MATLAB code for findallofthem.fig
% FINDALLOFTHEM, by itself, creates a new FINDALLOFTHEM or raises the existing
% singleton*.
%
% H = FINDALLOFTHEM returns the handle to a new FINDALLOFTHEM or the handle to
% the existing singleton*.
%
% ... |
d276be60bd9b082babd49a49795d7574784ba80dbd020d6213fd8492ffa807f3 | MATLAB | 90,930 | 2,166 | classdef DLBackEndClass < handle
% APT Backends specify a physical machine/server where GPU code is run.
% This class is intended to abstract away details particular to one backend or
% another, so that calling code doesn't need to worry about such grubby
% details.
%
% Note that filesystem paths stored in ... |
d2ca6b8d88ed782a232f163eaeb34ab707a935c6d0540cce65305e3e10f9e552 | MATLAB | 91,449 | 2,693 | function prepro_plot(LAN)
% v.0.5
%
% GUI para realizar prepocesamiento de matrices segemnnatadas
% tambien sirve de visualizaci??n para datos continuos
%
% prepro_plot(LAN)
% See Also VOL_THR_LAN , LAN_INTERP , FFTAMP_THR_LAN
%
% Pablo Billeke
% 18.04.2022 (PB) Bug ICA visualiza... |
97320dc6521304cad9261dabd9612e03e71ede3e346a0e285cfba9e2355e2302 | MATLAB | 92,110 | 1,658 | %To Do
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
69ea822052a9772dd3ccfd6e94f09061b58fbeb3bcaf776de3c67f4b9f4bb254 | MATLAB | 92,293 | 2,803 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef Mat... |
6fd89dfb8b53fc72002a85bb05bb570dfbfdb2b7a97063da097a3dac36502ba8 | MATLAB | 93,051 | 2,481 | function varargout = DPABI_SFC(varargin)
% DPABI_SFC MATLAB code for DPABI_SFC.fig
% DPABI_SFC, by itself, creates a new DPABI_SFC or raises the existing
% singleton*.
%
% H = DPABI_SFC returns the handle to a new DPABI_SFC or the handle to
% the existing singleton*.
%
% DPABI_SFC('CALLBACK',hO... |
24376e461ce063d4cd1f63a4fe0069b2d3dc97d9fb6cf875827977ce9313a3cd | MATLAB | 93,894 | 1,194 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
47062d04d1ace1be71ec823a8e4b891535d3a4a4af555cdc34dbe209d04924bc | MATLAB | 94,169 | 1,338 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
90a22860f5181fbfd58827229d4a403769b5e95bec9ab4565ebf2c9ce6f2999d | MATLAB | 94,741 | 3,223 | function plotModelingFigs(plotInds)
%---------------------------- KEY FOR PLOTINDS ----------------------------%
%1: plotConnMat_Schematic % Fig 2A
%2: plotOptJE % Fig 2D
%3: plotEnergyHeatmaps % Fig 2E
%4: plotBumpTraj_driven ... |
18cf94d96a0711e714ead0ccaff45309cdda3b8447c41f8757e85c3e9cc66e47 | MATLAB | 94,793 | 2,321 | function [event] = ft_read_event(filename, varargin)
% FT_READ_EVENT reads all events from an EEG, MEG or other time series dataset and
% returns them in a common data-independent structure. The supported formats are
% listed in the accompanying FT_READ_HEADER function.
%
% Use as
% [event] = ft_read_event(filename,... |
84bf5a281b52c9db036a79d59bbc244e951aa62947caf55bd5e47dec4a4b46b8 | MATLAB | 95,183 | 2,164 | function [cfg] = ft_databrowser(cfg, data)
% FT_DATABROWSER can be used for visual inspection of data. Artifacts that were
% detected by artifact functions (see FT_ARTIFACT_xxx functions where xxx is the type
% of artifact) are marked. Additionally data pieces can be marked and unmarked as
% artifact by manual selecti... |
2b875bb86360f8259d995793d9eb359c623ac3d375cc51afb39e0d4ab84d3202 | MATLAB | 95,747 | 2,200 | function [cfg] = ft_databrowser(cfg, data)
% FT_DATABROWSER can be used for visual inspection of data. Artifacts that were
% detected by artifact functions (see FT_ARTIFACT_xxx functions where xxx is the type
% of artifact) are marked. Additionally data pieces can be marked and unmarked as
% artifact by manual selecti... |
f40e946b5c28cd01d71e1a2450e236f2a7f7c68eb59c6cdbedf0bf670d28fd23 | MATLAB | 97,328 | 2,926 | function laprint(figno,filename,varargin)
%LAPRINT prints a figure for inclusion in LaTeX documents.
% LaPrint creates an eps-file and a tex-file. The tex-file contains
% the annotation of the figure such as titles, labels and texts. The
% eps-file contains the non-text part of the figure as well as the
% position... |
ed3a42be307e29a12c2d72568c5a890ca1cea15cebe27778265f2c6f999dba72 | MATLAB | 97,689 | 2,730 | function [opts,plm] = palm_takeargs(varargin)
% Handle the inputs for PALM.
%
% _____________________________________
% Anderson M. Winkler
% FMRIB / University of Oxford
% Oct/2014
% http://brainder.org
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% PALM -- Permutation Analysis of Linear ... |
e4ab4bb6972e9943c070c77a423972de5e6e5da309f3d2982f95342ef73569a4 | MATLAB | 99,215 | 2,778 | %% TI_paper_mainFigs234_and_supplFigs123.mat %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Sara Caldas-Martinez
% Last checked 240720
% COMMENTS:
% -
clear all;
close all;
clc;
%% Fig1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Abstract pure and modulated sinusoids that we use in main Figures 1, 2,
% 3,... |
6267809371c72f7fae1d30b1a5ba09d08000582369b2c71fafc7ed914fe1a5b0 | MATLAB | 99,393 | 2,068 | function [data] = read_besa_besa(filename, header, begsample, endsample, chanindx)
% READ_BESA_BESA reads data and header information from a BESA file
% See formatting document <a href="matlab:web(http://www.besa.de/downloads/file-formats/)">here</a>
%
% Use as
% [header] = read_besa_besa(filename);
% where
% fi... |
01e650cfd60ee1be6a473ab4a6a319660b5cbf4f4590630894c60a9e0c4998d5 | MATLAB | 99,481 | 2,070 | function [data] = read_besa_besa(filename, header, begsample, endsample, chanindx)
% READ_BESA_BESA reads data and header information from a BESA file
% See formatting document <a href="matlab:web(http://www.besa.de/downloads/file-formats/)">here</a>
%
% Use as
% [header] = read_besa_besa(filename);
% where
% fi... |
1c944f4973def4821e7e6695ca0866dd36a45fffa60a73002c7bc38cd639766d | MATLAB | 99,497 | 2,070 | function [data] = read_besa_besa(filename, header, begsample, endsample, chanindx)
% READ_BESA_BESA reads data and header information from a BESA file
% See formatting document <a href="matlab:web(http://www.besa.de/downloads/file-formats/)">here</a>
%
% Use as
% [header] = read_besa_besa(filename);
% where
% fi... |
a6f5ebc02148b55ff69217bdb676e93ee9a6da4f7a0fa25003f47a202e3b9fa7 | MATLAB | 99,585 | 1,667 | function QuaSOR_Generalized_Map_Generation(StackSaveName,StackSaveNameSuffix,IbIs,myPool,...
QuaSOR_Gaussian_Filter_Sigmas,QuaSOR_Gaussian_Filter_SizeBuffer,QuaSOR_Gaussian_Filter_Sizes,...
QuaSOR_TemporalColorizations,QuaSOR_Overlay_FilterIndex,QuaSOR_Overlay_ContrastIndex,QuaSOR_Overlay_Color,...
OQA_G... |
146a30cbd40af83756d8b3a4f7772e5837a2e1d4453159045d7cb7066e46fcb2 | MATLAB | 103,651 | 2,632 | function [hdr orig] = ft_read_header(filename, varargin)
% FT_READ_HEADER reads header information from a variety of EEG, MEG and LFP
% files and represents the header information in a common data-independent
% format. The supported formats are listed below.
%
% Use as
% hdr = ft_read_header(filename, ...)
%
% Addit... |
b2928e637856280b2b3cc62b9fa1da56eea2f8e1190966519c9767dd8088b54b | MATLAB | 105,138 | 2,630 | function [Cfg, JobList] = y_MultiEchoICA_Tedana(Cfg,WorkingDir,SubjectListFile)
% function [Cfg, JobList] = y_MultiEchoICA_Tedana(Cfg,WorkingDir,SubjectListFile)
% Run tedana on fMRIPrep multi-echo outputs and organize denoised files for DPABI.
%
% This function is designed as the multi-echo counterpart of y_Organize_f... |
8fb546fd8361756899c3d87b3a5cb904b6c1ef598e21bf424611d90c865b8ffe | MATLAB | 105,501 | 1,526 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
fe6057f95bc15544321f884bb52baafc9e88bce3e2805d51440ac3142d3a2d05 | MATLAB | 106,450 | 2,634 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math/Statistics: Connor Meehan <connor.gw.meehan@gmail.com>
% Guenther Walther <gwalther@stanford.edu>
% Primary inventors: Wayne Moore <wmoore@stanford.edu>
% David Parks <drparks@stanford.edu... |
c3fe71b50e7c3caca24d59333c625af8e21c694aebda00a9f2843f2184e99be2 | MATLAB | 108,692 | 2,839 | % Class for building a dendrogram based on QF dissimilarity measurements
%
% AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Her... |
899b27c451690f9e5073f77fd7bd46970cd1765302ecffa8c9459aef58cf3a03 | MATLAB | 108,748 | 2,767 | function [hdr] = ft_read_header(filename, varargin)
% FT_READ_HEADER reads header information from a variety of EEG, MEG and other time
% series data files and represents the header information in a common
% data-independent structure. The supported formats are listed below.
%
% Use as
% hdr = ft_read_header(filenam... |
71fcf4bf1b152048e4cbc6ac68484cfd7473e17eee64f18ffe0a2c7deb29e84b | MATLAB | 109,019 | 1,446 | function [ QuaSOR_Parameters,...
QuaSOR_Map_Settings,....
PixelMax_Map_Settings,...
QuaSOR_LowRes_Map_Settings,...
QuaSOR_Auto_AZ_Settings,...
QuaSOR_Event_Extraction_Settings,...
ScaleBar_Upscale]=...
M... |
2649aa4745cf8c4ae124c2dfb08bb2832bf8853b62124a1f872b1f567e3c11c4 | MATLAB | 109,613 | 2,087 | %To DO
%BFReader release .tif for delete from scratch disk
% DataRegion/Stitch Mask
% CZI import
function [FileID,FileName,RawDataDir,ScratchDir,ImageArray,DataRegion,StackOrder,...
MetaData,Additional_MetaData,BasicFileData,Channel_Labels,Channel_Colors,Channel_Color_Codes]=Stack_Import(varargin)
% [FileID... |
f10dfe53156eca3f1adadb0da3a075856834b78313a01f64e7bf627c31fdb000 | MATLAB | 111,261 | 1,935 | function p = pathdef
%PATHDEF Search path defaults.
% PATHDEF returns a string that can be used as input to MATLABPATH
% in order to set the path.
% Copyright 1984-2016 The MathWorks, Inc.
% DO NOT MODIFY THIS FILE. IT IS AN AUTOGENERATED FILE.
% EDITING MAY CAUSE THE FILE TO BECOME UNREADABLE TO
% THE ... |
0f876677f64cbfab62e7fe01c4838160d3d3038394911eec96f6bf0f6e0478dc | MATLAB | 111,942 | 3,383 | classdef PostProcess < handle
properties
pts2run = []; % row vec into 1..npts, used when pts independent. use at own risk
end
properties (GetAccess=public,SetAccess=public)
algorithm = 'maxdensity';
jointsamples = true;
ncores = [];
% parameters for KDE
kde_sigma = 5;
... |
b5a761d7991db04a909b9a98f10d48fa959f894bde53d4899cec92771d027577 | MATLAB | 116,300 | 2,442 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef SuhR... |
c2c99d92810b1a02c22a73b9e2392fc732197a977c6fb382778404a7d5a025c6 | MATLAB | 117,529 | 2,992 | function varargout = y_spm_orthviews(action,varargin)
% Display orthogonal views of a set of images
% FORMAT H = y_spm_orthviews('Image',filename[,position])
% filename - name of image to display
% area - position of image {relative}
% [left, bottom, width, height]
% H - handle for orthogonal sect... |
745af916917e7b1acc16523e67e54a85ecca38b451f8b96cdce4cd69ff298d21 | MATLAB | 117,695 | 1,527 | function [ImageArrayReg_AllImages,ImageArrayReg_FirstImages]=Enhanced_Multi_Modality_Registration(myPool,dc,SaveName,StackSaveName,...
ScratchDir,CurrentScratchDir,FigureSaveDir,ImageArray,ImageArray_FirstImages,...
ReferenceImage,AllBoutonsRegion,AllBoutonsRegion_Orig,BorderLine_Orig,Crop_Props,SubBout... |
e009d9561fe1d7c7661f7c914cbf8e70d22a4a18c15846c3d942bcf0ca5d082a | MATLAB | 118,559 | 2,942 | %% Load Unit Data
datRoot = '/Volumes/LaCie/Farries recordings/';
load([datRoot 'unitDat_final_culled.mat'])
uName = arrayfun(@(u) strsplit(u.name), unit, 'UniformOutput', false);
uRat = cellfun(@(u) u{1}, uName, 'UniformOutput', false);
uSes = cellfun(@(u) u{2}, uName, 'UniformOutput', false);
uTrode = cellfun(@(u) ... |
26105b87c3c15d9902b5bda5cd82549f4f6af0a220d6ab446f267d68a78fb4f4 | MATLAB | 122,190 | 2,681 | classdef TempoController < handle
properties
figure
recordings = {}
reporters = {}
duration = 300
zoom = 1
splitterPanel
splitter
videosPanel
videoPanels = {}
videoIconAxes
timelinesPanel
... |
0b9ca664c75de9cf5c2209bf4c2ad6018784f290c71497ce84445d44c47a7f65 | MATLAB | 122,967 | 2,095 | function [Error, Cfg]=DPABIFiber_run(Cfg,WorkingDir,SubjectListFile)
% FORMAT [Error]=DPABISurf_run(Cfg,WorkingDir,SubjectListFile)
% Cfg - the parameters for auto data processing.
% WorkingDir - Define the working directory to replace the one defined in Cfg
% SubjectListFile - Define the subject list to rep... |
4971a475a9e5c539f0a03c88e681db18239e76a02347632b04922bc66a225409 | MATLAB | 124,947 | 1,599 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~isfield(Recording,'ModalitySuffixes')||~isfield(Recording,'IncludeSpont')||~isfield(Recording,'SplitHighFreqMod')
warning('Recording structure now requires three new fiel... |
1a266767aea8b91eac20f17651e4ada1b20335ca6a60e0c79b7786ab43d1775f | MATLAB | 126,353 | 2,703 | function out = cat_run_boneseg(opt)
%cat_run_boneseg. Extract bone measures based on SPM segmentation.
% ... DETAILED DESCRIPTION ...
%
% out = cat_run_boneseg(opt);
%
% opt .. structure of input values
% .files .. SPM m-files
% .method .. method used for evaluation (default=2):
% ... |
2951924e9214709446510eb627f08735b74bbdb15e86ebbf0386aaeb102771f3 | MATLAB | 127,763 | 3,766 | function main_figure = createLabelerMainFigure()
% Read assets from .mat file
assets_file_path = fullfile(APT.Root, 'matlab', 'createLabelerMainFigure_assets.mat') ;
assets = loadAnonymous(assets_file_path) ;
% Create the controls. Many, many controls.
main_figure = figure(...
'Position',[40 106 1534 1062],...
'Colo... |
10548f3a2bfdf35077669ecc1f57506299db8ebd588188709e8ea330e8751ec1 | MATLAB | 128,748 | 5,068 |
% Panel is an alternative to Matlab's "subplot" function.
%
% INSTALLATION. To install panel, place the file "panel.m"
% on your Matlab path.
%
% DOCUMENTATION. Scan the introductory information in the
% folder "docs". Learn to use panel by working through the
% demonstration scripts in the folder "demo". Reference
... |
7d779042bf42a105b4c3c099a458fa88809069c63447aedd1122a85278b43739 | MATLAB | 128,888 | 2,713 | classdef sdoParameterExplorer_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
UIFigure matlab.ui.Figure
GridLayout matlab.ui.container.GridLayout
PlotSDOCombinationLabel matlab.ui... |
20c67142388e0af6ca02edfd06574e0b363c932015bf5b6d0feb684b97cd81dd | MATLAB | 128,986 | 3,601 | % [EEG, cfg] = eeg_SASICA(EEG,cfg)
%
% Suggest components to reject from an EEG dataset with ICA decomposition.
%
% Inputs: EEG: EEGlab structure with ICA fields.
% cfg: structure describing which methods are to use for suggesting
% bad components (see structure called def, in the code below)... |
8c26d937387513658a4d5cc35c6837c9d7361c34e476a15820b56d658ffa0e68 | MATLAB | 132,403 | 1,691 | function [QuaSOR_Auto_AZ,QuaSOR_Auto_AZ_Settings]=...
Multi_Modality_QuaSOR_Auto_AZ(myPool,OS,dc,SaveName,StackSaveName,SaveDir,CurrentScratchDir,FigureScratchDir,...
ImagingInfo,QuaSOR_Auto_AZ_Settings,QuaSOR_Map_Settings,QuaSOR_Event_Extraction_Settings,QuaSOR_Maps,QuaSOR_Data,QuaSOR_Parameters,...
Sca... |
2bff48c496029fecd93307aef6ad1d5c191e516b90f2f0c3ac9a055ab37c261e | MATLAB | 139,876 | 1,592 | %Note to user:
%To alter image enhancements necessary for clean Demon tracking you can
%adjust the StretchLims. Lower the upper limit to increase contrast but it
%is a percentage of total pixels so you need to compensate when altering
%the DemonReg.Padding size
%Increase Accumulated Field Smoothing or the Demon... |
26c1c0002b5d15378be5a100c0228ab84c696fae9c4ae8ab4998dad620406428 | MATLAB | 151,152 | 4,186 | function h=boxplot(varargin)
%BOXPLOT Displays box plots of multiple data samples.
% BOXPLOT(X) produces a box plot of the data in X. If X is a matrix there
% is one box per column, and if X is a vector there is just one box. On
% each box, the central mark is the median, the edges of the box are the
% 25th an... |
4f8b6f357e8215faca074b00b754b9b82f0bc737d4fd922de7bb829eb6932e06 | MATLAB | 151,958 | 5,056 | % VIEW_NII: Create or update a 3-View (Front, Top, Side) of the
% brain data that is specified by nii structure
%
% Usage: status = view_nii([h], nii, [option]) or
% status = view_nii(h, [option])
%
% Where, h is the figure on which the 3-View will be plotted;
% nii is the brain data in NIFTI format;
% o... |
085b66411a5facd83e47030eef1c6a71a57d561052bc22568cc26c81dcaaa298 | MATLAB | 154,288 | 3,890 | % Class for Hi-D matching with merging of data subsets using
% QF match or F-measure or both
%
%
% QF Algorithm is described in
% https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586874/
% and
% https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818510/
%
% Primary Inventor: Darya Orlova <dyorlova@gmail... |
2a681225e24a56dcfddc34b88f3900216c66edc727de319b02931141e13485b5 | MATLAB | 159,793 | 3,087 | function varargout = plot2svg(param1,id,pixelfiletype)
% Matlab to SVG converter
% Prelinary version supporting 3D plots as well
%
% Usage: plot2svg(filename,graphic handle,pixelfiletype)
% optional optional optional
% or
%
% plot2svg(figuresize,graphic handle,pixelfi... |
236138800e3a34e57508cc77e76561a146be609a5c71bd42b6af9491cf0b44c4 | MATLAB | 159,845 | 4,411 | % =========================================================================
% *** FUNCTION matlab2tikz
% ***
% *** Convert figures to TikZ (using pgfplots) for inclusion in LaTeX
% *** documents.
% ***
% *** Workflow:
% *** 0.) Place this file in one of the MATLAB paths
% ** (for example the current director... |
49345b5e801117a9ff2d80dac07e9038577e6798d7a7127dc1d9e412bc4207cb | MATLAB | 162,773 | 2,797 | %To Do
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
ec16845f68f45f13a033eb7da4a9dcb0ed8aa25b4c958cc8fd7067c7e7b917a2 | MATLAB | 166,751 | 2,173 | function [QuaSOR_Maps,QuaSOR_Map_Settings,PixelMax_Maps,PixelMax_Map_Settings]=...
Multi_Modality_QuaSOR_Maps(myPool,OS,dc,SaveName,StackSaveName,SaveDir,CurrentScratchDir,FigureScratchDir,...
QuaSOR_Map_Settings,QuaSOR_Data,QuaSOR_Parameters,QuaSOR_Event_Extraction_Settings,QuaSOR_LowRes_Map_Settings,...
... |
6714b9610f5d409586b6a93bb8af6f84c7d0723642042f00eae8c3f6229d8873 | MATLAB | 166,938 | 4,148 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
%
% Description:
% A_MusculoskeletalSystem_SagittalPlane.m should be run first
% This script performs 2D and 3D visualization and analy... |
f4a89ab0446964be25357d8769967558663a7e127c4de1ed0444767150e34cfc | MATLAB | 169,151 | 3,384 | function varargout = plot2svg(param1,id,pixelfiletype)
% Matlab to SVG converter
% Prelinary version supporting 3D plots as well
%
% Usage: plot2svg(filename,graphic handle,pixelfiletype)
% optional optional optional
% or
%
% plot2svg(figuresize,graphic handle,pixelfiletype)
... |
f1930cac50b702b014658fd979e55263e73eb5af1e12b9e8bd41b202d18ad819 | MATLAB | 169,961 | 3,820 | function palm_core(varargin)
% This is the core PALM function.
%
% _____________________________________
% Anderson M. Winkler
% FMRIB / University of Oxford
% Oct/2014
% http://brainder.org
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% PALM -- Permutation Analysis of Linear Models
% Copy... |
61f188231a1e86e8f859823f48373dcd1799729f91ad5314de7e048eec3dd673 | MATLAB | 177,858 | 2,960 | % pipeline_gait_analysis.m
% Sarah West
% 7/3/23
% Uses extracted and behavior-segmented traces of paw/body part velocities from
% DeepLabCut to find locomotion strides. Then uses those strides to run
% gait analysis.
% NOTE: From DLC, positive x is RIGHT, positive y is DOWN
%% Initial Setup
% Put all needed param... |
00fc739cec4624ce6b380da964cd4a1fb3c727e7b1a2b3cde590e9ec80a82c2f | MATLAB | 200,000 | 3,333 | function varargout = DPABI_InputPreparer(varargin)
% DPABI_BIDS_Converter GUI by Bin Lu
%-----------------------------------------------------------
% Convert the output folder of DPABI_Dicomsorter or xnat-like system to DPARSFA/DPABISurf's input format.
% B108, CAS Key Laboratory of Behavioral Science, Institute of Ps... |
26d35dbef5ac14e430956d16a02a534b18e9d9b84b919cfa077dd317fda27474 | MATLAB | 200,000 | 3,087 | function [Error, Cfg]=DPABISurf_run(Cfg,WorkingDir,SubjectListFile,FunctionalSessionNumber)
% FORMAT [Error, Cfg]=DPABISurf_run(Cfg,WorkingDir,SubjectListFile,FunctionalSessionNumber)
% Cfg - the parameters for auto data processing.
% WorkingDir - Define the working directory to replace the one defined in Cfg
... |
3cdf9a0720409dda76e905fbc64f1cc23201b96b240045f51211f8a605ad95b8 | MATLAB | 200,000 | 3,056 | function AZ_Histogram_Figure(FigName,FigSaveDir,dc,ModBins,...
ProfileError,ProfileXTicks,ProfileXLabel,ProfileYLabel,CalculationLabel,...
NumMods,NumGroups,RemovalIndex,MatchedModMax,MatchProfileXIndices,MatchProfileXTicks,MatchProfileXLim,CenteredPlot,PlotMarkers,IncludeAligned,FlipHist)
%NumMods=3;N... |
496d99a405c57593404ec5e6612696ab46003587f3945d7a3fff4d05b0c42dba | MATLAB | 200,000 | 5,734 | % COLORCET - Perceptually uniform color maps
%
% Usage 1: Generate a colour map and apply it to the current figure.
% >> colorcet(name);
%
% Usage 2: Return a colour map and its description.
% >> [map, descriptorname, description] = colorcet(name);
%
% Usage 3: Get a list of all possible colour maps.
% >> c... |
51ce31bb2c5b10784e0394fd1bea61764f0614f18aaa82a0031161500c1e80e3 | MATLAB | 200,000 | 5,680 | %function StateEditorProBeta(baseName, inputData, supressGUI, makePortable)
% SIMPLE USAGE (NO INPUT VARIABLES, if run from dir with .xml and .eeg/lfp):
% Add StateEditor to your Matlab path. Within Matlab navigate to a folder
% containing '.xml' and '.eeg' (or '.lfp') files. Type in the name of this
% .m file and pre... |
613da735d35013ba0a7a306bcb5929ce9feebf5ad842ed5f965e190716b410cf | MATLAB | 200,000 | 3,001 | function [Error, AutoDataProcessParameter]=DPARSFA_run(AutoDataProcessParameter,WorkingDir,SubjectListFile,IsAllowGUI)
% FORMAT [Error, AutoDataProcessParameter]=DPARSFA_run(AutoDataProcessParameter,WorkingDir,SubjectListFile,IsAllowGUI)
% Input:
% AutoDataProcessParameter - the parameters for auto data processing... |
7985f861f548e88a61e4caf707b22d432312e9e67f7ca7a28a9f8b621f30186a | MATLAB | 200,000 | 5,643 | classdef Labeler < handle
% Bransonlab Animal Video Labeler/Tracker
properties (Constant, Hidden)
VERSION = '3.1'
DEFAULT_LBLFILENAME = '%s.lbl'
%DEFAULT_CFG_FILENAME = Labeler.defaultCfgFilePath()
MAX_MOVIENAME_LENGTH = 80
% non-config props
% KB 20190214 - replaced trackDLParams, prePro... |
8ce8add739e55720573c47d18e5b8274e1d8f7904d1ca6f15dc4c29d523fa857 | MATLAB | 200,000 | 2,418 |
warning('May want to consider adding QuaSOR_Parameters.GMM.Minimum_Peak_Amplitude_EpisodeDelta...')
warning('May want to consider adding QuaSOR_Parameters.GMM.Minimum_Peak_Amplitude_EpisodeDelta...')
warning('May want to consider adding QuaSOR_Parameters.GMM.Minimum_Peak_Amplitud... |
97f30b9a6867f80fd5bb79b6b9bbb0fe0a0138a89c2c68993a428c6e0e253807 | MATLAB | 200,000 | 2,985 | classdef ISpin_Quattrocento_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
UIFigure matlab.ui.Figure
tabs matlab.ui.control.DropDown
RecordingSettingsPanel matlab.ui.co... |
ab5c98dbf478e0352d342c1b537e98b469661ccee3eb25093bfb77f6074c894d | MATLAB | 200,000 | 5,613 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef Gui
... |
bb8d984775c2438972809d9c8155def834d6fae204684df70064f843376a5b2e | MATLAB | 200,000 | 5,059 | classdef LabelerController < handle
properties % private/protected by convention
labeler_ % the controlled Labeler object
mainFigure_ % the GH to the main figure
auxiliaryViewFigures_ = gobjects(1,0) % array: one per view beyond the main view. Will stay empty for single-view projects
listeners_... |
f0dda55aa637d43daebda85dcbafd09ee00c34925fbad6f9065a3b418bd2b48a | MATLAB | 200,000 | 2,284 | function [QuaSOR_Fitting_Struct,QuaSOR_Data,QuaSOR_Parameters,AllBoutonsRegion_Upscale,ScaleBar_Upscale,BorderLine_Upscale,AbortStatus]=...
Multi_Modality_QuaSOR(myPool,OS,dc,SaveName,StackSaveName,SaveDir,...
ScratchDir,CurrentScratchDir,ImagingInfo,QuaSOR_Parameters,QuaSOR_Event_Extraction_Settings,...
Sp... |
fc1759d4bf611483c784fea4f3ea4c8d74693cb976d47428f7108368459c2c58 | MATLAB | 200,000 | 3,922 | %TODO List
%Flag Frames add to traces
%depth color
%delete/Undo ROI Area MOD NOT WORKING
%export image
%autocontrast
%line profilesExpo
%Auto-Tag Localizations
%Add Localization Counts to Trace
%LogHistY Zero adjust
%profile max proj
%orthogoal projections
%orthognal profiles
%RGB Mask Overlay Transparency
% frame buff... |
fe0f564bf9bd4a982242faafff91a095206a9a79dee38b099bc294ef6dae9768 | MATLAB | 200,000 | 2,528 | %todo:
%import flagged episode list
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%... |
706447875c09d10fe33b0ed8def357f6775262681f15a7f9969b4d39134fa7d8 | Mathematica | 54,915 | 1,249 | (*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[ 0, 0]
NotebookDataLength[ 54914, 1248]
NotebookOptionsPosition[ 49221, 1172]
NotebookOutlinePosition[ 49711, 1190]
CellTagsIndexPosition[ 49668, ... |
67812d1b0500c8b83b321ab3f9a29472a0ea22f0a046af623497d599aaea64a4 | Mathematica | 200,000 | 4,651 | (* Content-type: application/vnd.wolfram.mathematica *)
(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)
(* CreatedBy='Mathematica 11.3' *)
(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[ 158, 7]
NotebookDataLengt... |
12dc7071ac6847e29cc7e089ea2c30126cc0df479bb590ee295637f13a2d5804 | NEURON | 63 | 5 | //adding channels to the membrane
forall{
insert pas
}
|
6b8e4431eb70869038674f825b0887335f99a9f3cf1be80c4368aae3c0b298b9 | NEURON | 67 | 3 | module github.com/replicate/cog/test-helpers/https-server
go 1.21
|
dbf5459d1bfabe5fb6d225427cb7c70fe269e02b1e3e1bc03e1651a2c7cf2af8 | NEURON | 81 | 5 | create soma
insert hh
soma diam=10
//gnabar_hh=0.12 gkbar_hh=0.036 gl_hh=0.0003
|
18bf417c139f084267cf93e3d8992e11748c0332108878a99d74794a42a252b1 | NEURON | 106 | 6 | load_file("init.hoc")
load_file("Rm_fitting3_soma-dend.ses")
user_e_pas = 0
v_init = 0
IC3_passive() |
6b30a8a9b39ea85f54567f06c1ce119d05fe280915d11b989fa756f8486e3aa6 | NEURON | 114 | 10 | create soma
soma diam=10
insert hh
objectvar stim
stim = new IClamp(0.5)
stim.del=200
stim.dur=500
stim.amp=0.2
|
51d72ef55db34352f51d86b5a5f694ebb75350549dcfc7e42d7a0db0d753f71d | NEURON | 177 | 17 | NEURON {
SUFFIX vmax
RANGE vm
}
ASSIGNED {
v (millivolt)
vm (millivolt)
}
INITIAL {
vm = v
}
BREAKPOINT {
if (v>vm) { vm=v }
}
|
171dd73f4dcfe6e1ade91929ba1661b392a5e831a8a7b7619fad5f617a9ae83b | NEURON | 195 | 13 | begintemplate ball_and_stick_template
public soma, dend
public all
objref all
proc init() {
all = new SectionList()
}
create soma[1], dend[1]
endtemplate ball_and_stick_template
|
d941933d1d98c3b9faf585212991286672c3baa5da562c3d13da1d6bc972ad08 | NEURON | 206 | 14 | begintemplate stick_template
public dend
public all, basal
objref all, basal
proc init() {
all = new SectionList()
basal = new SectionList()
}
create dend[1]
endtemplate stick_template
|
48ac78ab21b87c984285cc96a543014855583717d88172d19a16c6f762670244 | NEURON | 260 | 9 | module gitlab.com/Grouumf/enhlinktools/matrix
go 1.15
require (
github.com/valyala/fastrand v1.1.0 // indirect
gitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91 // indirect
gonum.org/v1/gonum v0.14.0 // indirect
)
|
53b58e2e5eaae3801ead42465a0cb19b79fd3dd4714e25d2625a7e82ce1e06da | NEURON | 273 | 12 | //Neuron files
nrn_load_dll("./mods/nrnmech.dll")
load_file("subiter.hoc")
//load_file("nrngui.hoc")
load_file("stdrun.hoc")
//Custom files
load_file("morphology2.hoc")
load_file("biophys_na_inhomo_minimal_model+KM+KA+KD.hoc")
//load_file("gui_shah_km.hoc")
|
699fc18268f9975c925f4232d3feb48863274c9664af457585fe984537359137 | NEURON | 335 | 27 | create soma
insert hh
access soma
L = 17.84
diam = 17.84
objref ampasyn, ns, nc, vc
ampasyn = new Exp2Syn(0.5)
ampasyn.tau1 = 0.3
ampasyn.tau2 = 3
ns = new NetStim(0.5)
ns.start = 100
ns.interval = 100
nc = new NetCon(ns, ampasyn)
nc.weight = 0.01
nc.delay = 2.0
vc = new SEClamp(0.5)
vc.rs = 0.01
vc.dur1 = 1000... |
c7ae5edaee2d16290214853d9ec6faddbb8175c0a991f5eed4476f80778483de | NEURON | 342 | 20 | proc negative_init() { local dtsav, temp
finitialize(v_init)
t = -10
dtsav = dt
dt = 1
// if cvode is on, turn it off to do a large fixed step
tmp = cvode.active()
if (temp!=0) { cvode.active(0) }
while (t<-1e9) {
fadvance()
}
dt = dtsav
t = 0
if (cvode.active()) {
cvode.re_init()
} else {
fcurrent()... |
038f5cd64f45ddd9556c89682afcd819349affa018c8b9f537aed08bd4f6b002 | NEURON | 347 | 27 | create soma
insert hh
access soma
L = 17.84
diam = 17.84
objref ampasyn, ns, nc, vc
ampasyn = new Exp2Syn(0.5)
ampasyn.tau1 = 0.3
ampasyn.tau2 = 3
ns = new NetStim(0.5)
ns.start = 100
ns.interval = 100
nc = new NetCon(ns, ampasyn)
nc.weight = 0.01
nc.delay = 2.0
// vc = new SEClamp(0.5)
// vc.rs = 0.01
// vc.du... |
f70893a8382e72ccec982785a7ed15ffbd5176b1e4f9128cc68f44c526527150 | NEURON | 376 | 12 | /* -----------------------------------------------------------------------------
BallAndStickTemplate.hoc
----------------------------------------------------------------------------- */
begintemplate BallAndStickTemplate
public init, soma, apic
public all
objref all
proc init() { all = new SectionList() }
cre... |
87fd6fbaf76598b80e613357e64324dbcc3072009178b9b10b60c3179db1f352 | NEURON | 377 | 11 | module gitlab.com/Grouumf/enhlinktools/enhlinkobject
go 1.15
require (
github.com/biogo/store v0.0.0-20201120204734-aad293a2328f
github.com/valyala/fastrand v1.1.0
gitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91
gitlab.com/Grouumf/enhlinktools/matrix v0.0.0-2023120420271... |
48fedd9e9e8ce79e22d347dfc696999bfde2d38850374e6e3d167dd440444aa9 | NEURON | 390 | 10 | module gitlab.com/Grouumf/enhlinktools/enhtools
go 1.15
require (
github.com/biogo/store v0.0.0-20201120204734-aad293a2328f
gitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91
gitlab.com/Grouumf/enhlinktools/enhlinkobject v0.0.0-20240905014251-972a77ac315a // indirect
gitlab... |
2f49503b84bb6fbe1aca6b8f100b79dd8fc31faf330a7642089755b3c07c1f6d | NEURON | 398 | 33 | proc celldef() {
topol()
subsets()
geom()
biophys()
geom_nseg()
}
create dend
proc topol() { local i
basic_shape()
}
proc basic_shape() {
dend {pt3dclear() pt3dadd(0, 0, 0, 2) pt3dadd(0, 0, 1000, 2)}
}
objref all
proc subsets() { local i
objref all
all = new SectionList()
dend all.append()
}
p... |
35e0414967b7e31f2ab1473e1b79fd55d65e95285ee7899aab953cd80e212a07 | NEURON | 400 | 17 | begintemplate LFPyCellTemplate
public soma, axon, dend, apic
public all, somatic, axonal, basal, apical
objref all, somatic, axonal, basal, apical
proc init() {
all = new SectionList()
somatic = new SectionList()
axonal = new SectionList()
basal = new SectionList()
apical = new SectionList... |
edecbb66302d14038b01b7f80845c17c563f06ca066745aa83b9cedce8ddbf92 | NEURON | 460 | 13 | module gitlab.com/Grouumf/enhlinktools/enhgrid
go 1.15
// replace gitlab.com/Grouumf/enhlinktools/matrix => ../matrix
// replace gitlab.com/Grouumf/enhlinktools/enhlinkobject => ../enhlinkobject
require (
gitlab.com/Grouumf/ATACdemultiplex/ATACdemultiplexUtils v0.0.0-20231204194046-760c57794d91
gitlab.com/Grouumf... |
06b12b3c773f82096da33b1ff96becce380739d75abfcf631f3a8383d6bfc22b | NEURON | 524 | 40 | TITLE Gap junction current for parallel computation
COMMENT
Implemented by Erin Munro,
copied largely from:
The NEURON Book by Nicholas T. Carnevale, Michael L. Hines
online at Google books
ENDCOMMENT
UNITS {
(mV) = (millivolt)
(nA) = (nanoamp)
(uS) = (microsiemens)
}
NEURON {
POINT_PROCESS gapjuncti... |
b6a12d34209f2f8e367db882cfabf004469787d41b9dce71d553fe8cdeaa8f19 | NEURON | 533 | 40 | TITLE Gap junction current for parallel computation
COMMENT
Implemented by Erin Munro,
copied largely from:
The NEURON Book by Nicholas T. Carnevale, Michael L. Hines
online at Google books
ENDCOMMENT
UNITS {
(mV) = (millivolt)
(nA) = (nanoamp)
(uS) = (microsiemens)
}
NEURON {
POINT_PROCESS gapjuncti... |
0a96ddbe839f09e83990ed106a81a17930178db5dc3c01aae086a4e625b8f15a | NEURON | 536 | 41 | TITLE Gap junction current for parallel computation
COMMENT
Implemented by Erin Munro,
copied largely from:
The NEURON Book by Nicholas T. Carnevale, Michael L. Hines
online at Google books
ENDCOMMENT
UNITS {
(mV) = (millivolt)
(nA) = (nanoamp)
(uS) = (microsiemens)
}
NEURON {
POINT_PROCESS gapjuncti... |
532efed38d617ef2a92178476d904671bafe76fa1494ec387bd9f134b57db1c4 | NEURON | 558 | 18 | // Code Taken from Aberra et al, JNE 2018
/*
* $Id: setpointers.hoc,v 1.4 2008/12/02 22:19:41 ted Exp ted $
* sets up the pointers after the sections have been created
* 2018/05/20 Modified by Aman Aberra
*/
proc setpointers() { local done
getSecRefs() // save coordinates, get section refs, and assign section types... |
be9735823bbcbf9cdc230a4c000c6a5df334afa1261d78ade8b0123610cfe0c2 | NEURON | 610 | 32 | /* -----------------------------------------------------------------------------
BallAndStick.hoc
----------------------------------------------------------------------------- */
// Create sections:
create soma[1]
create apic[1]
// Add 3D information:
soma[0] {
pt3dadd(0, 0, -15, 30)
pt3dadd(0, 0, 15, 30)
}
ap... |
02b52e5d6dd3cd20a20b69087352a2ef7e6a28d9998e602949cc207503e342a5 | NEURON | 614 | 30 | // Code Taken from Aberra et al, JNE 2018
/*
* $Id: anatscale.hoc,v 1.2 2005/09/10 23:02:15 ted Exp $
* set up xyz scale bars
* 2018/05/20 Modified by Aman Aberra
*/
create xScale, yScale, zScale
proc anatscale() {
create xScale, yScale, zScale
if ($4>0) { // if length arg is <= 0 then do nothing
xScale {
pt3d... |
a98fd6abea66a6d655c147b0ff494c3d35783311da2ce1de5239c835a23ccaec | NEURON | 624 | 41 | TITLE nca current for C. elegans neuron model
COMMENT
channel type: sodium passive currents
model and parameters from:
Nicoletti, M., et al. (2019). "Biophysical modeling of C. elegans neurons: Single ion currents and whole-cell dynamics of AWCon and RMD." PLoS One 14(7): e0218738.
ENDCOMMENT
UNITS {
(nS) = (n... |
99866817705f175ab1f6810c6018e8b23e0ea8de63845552ab887cf154a6b2bf | NEURON | 634 | 32 | /* ----------------------------------------------------
example_morphology.hoc
This hoc file creates a neuron of the following shape:
|
|
|
O
Note the conventions:
- soma needs to be a list (soma[0], not soma),
- use soma for the soma... |
c8a30c9efcc6cd8481d096346b129d915f43b0e5195f8def823e239920b279db | NEURON | 680 | 34 | /* ----------------------------------------------------
sticks_not_connected_head_to_toe.hoc
Note the conventions:
- soma needs to be a list (soma[0], not soma),
- use soma for the soma compartment,
- use a name starting with dend for the dendrites.
-----------------------------------------------------*/
create so... |
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