From d10d67b0398794a266f2057d6a0d6efe87be0239 Mon Sep 17 00:00:00 2001 From: Jan Benda Date: Tue, 24 Jan 2017 09:40:00 +0100 Subject: [PATCH] final fixes --- projects/disclaimer.tex | 30 +++++++++---------- .../populationvector.tex | 24 ++++++++++----- 2 files changed, 32 insertions(+), 22 deletions(-) diff --git a/projects/disclaimer.tex b/projects/disclaimer.tex index 4d63ac7..7d0d834 100644 --- a/projects/disclaimer.tex +++ b/projects/disclaimer.tex @@ -8,21 +8,21 @@ \vspace{1ex} The {\bf code} and the {\bf presentation} should be uploaded to - ILIAS at latest on Wednesday, February 8th, 23:59h. We will + ILIAS at latest on Thursday, February 9th, 12:59h. We will store all presentations on one computer to allow fast - transitions between talks. The presentations start on - Thursday 9:00h. Please hand in your presentation as a pdf file. Bundle - everything (the pdf, the code, and the data) into a {\em - single} zip-file. + transitions between talks. The presentations start on Thursday, + February 9th at 1:00h c.t.. Please hand in your presentation as + a pdf file. Bundle everything (the pdf, the code, and the data) + into a {\em single} zip-file. \vspace{1ex} - The {\bf code} should be exectuable without any further - adjustments from our side. A single {\em main} script should + The {\bf code} should be executable without any further + adjustments from our side. A single \texttt{main.m} script should coordinate the analysis by calling functions and sub-scripts and should produce the {\em same} figures that you use in your slides. The code should be properly commented and comprehensible - by a third persons (use proper and consistent variable and + by a third person (use proper and consistent variable and function names). \vspace{1ex} @@ -34,11 +34,11 @@ The {\bf presentation} should be {\em at most} 10min long and be held in English. In the presentation you should (i) briefly - describe the problem, (ii) explain how you solved it - algorithmically (don't show your entire code), and (iii) present - figures showing your results. All data-related figures you show - in the presentation should be produced by your program. It is - always a good idea to illustrate the problem with basic plots of - the raw-data. - + describe the problem, (ii) present figures introducing, showing, + and discussing your results, and (iii) explain how you solved + the problem algorithmically (don't show your entire code). All + data-related figures you show in the presentation should be + produced by your program. It is always a good idea to illustrate + the problem with basic plots of the raw-data. Make sure the axis + labels are large enough! }} diff --git a/projects/project_populationvector/populationvector.tex b/projects/project_populationvector/populationvector.tex index 5cd87df..44c1b62 100644 --- a/projects/project_populationvector/populationvector.tex +++ b/projects/project_populationvector/populationvector.tex @@ -36,10 +36,10 @@ respond to bars in dependence on their orientation. How is the orientation of a bar encoded by the activity of a - population of orientation sensisitive neurons? + population of orientation sensitive neurons? In an electrophysiological experiment, 6 neurons have been recorded - simultaneously. First, the tuning of these neurons was characteried + simultaneously. First, the tuning of these neurons was characterized by presenting them bars in a range of 12 orientation angles. Each orientation was presented 50 times. Each of the \texttt{unit*.mat} files contains the responses of one of the neurons. In there, @@ -76,14 +76,24 @@ gain factor that sets the maximum firing rate. \part How can the orientation angle of the presented bar be read - out from the population activity of the 6 neurons? One is the so - called ``population vector''. Think of another (simpler) method. + out from one trial of the population activity of the 6 neurons? + One is the so called ``population vector'' where unit vectors + pointing into the direction of the maximum response of each neuron + are weighted by their firing rate. The stimulus orientation is + then the direction of the averaged vectors. - Load one of the \texttt{population*.mat} files, illustrate the data, - and estimate the orientation angle of the bar by two different methods. + Think of another (simpler) method how the orientation of the bar + may be approximately read out from the population. + + Load one of the \texttt{population*.mat} files, illustrate the + data, and estimate the orientation angle of the bar by the two + different methods. \part Compare, illustrate and discuss the performance of your two - decoding methods. + decoding methods by using all of the recorded responses (all + \texttt{population*.mat} files). How exactly is the orientation of + the bar encoded? How robust is the estimate of the orientation + from trial to trial? \end{parts} \end{questions}