https://crcns.org These are the search results for the query, showing results 571 to 585. https://crcns.org/forum/using-datasets/593514207/39214342 I had a similar problem of the one from the post 'hc-3 ec016.234', but not exactly the same.   If i run: data.namepattern = '~/hc3/ec013.15/ec013.157/ec013.157 ' [timestamp,clus_id,map,Par]=LoadCluRes(data.namepattern,5);   i get the following map. map =      1     5     2      2     5     3      3     5     4      4     5     5      5     5     6   Therefore, I would expect five clusters in shank 5 in session 'ec013.157'. However, when I checked the hc3.cell table, I could not find any cluster 6 in shank 5 (clusters list from 2 to 5, as shown below).   (...) 'ec013.15'    'ec013'    4    15    'EC5' 'ec013.15'    'ec013'    5    2    'CA1' 'ec013.15'    'ec013'    5    3    'CA1' 'ec013.15'    'ec013'    5    4    'CA1' 'ec013.15'    'ec013'    5    5    'CA1' 'ec013.15'    'ec013'    6    2    'CA1' (...)   Further, cluster 6 from shank 5 has 4011 spikes only in session 'ec013.157'. Thus this cannot be explained as it was in the post  'hc-3 ec016.234' (neurons with less than 50 spikes are not listed). Probably there is another exclusion criterion to the neurons be included in the hc3.cell list. Maybe a measure of cluster quality? I would like to be sure I understand what is going on since I want to use the information of cell type in the hc3 table.   Thanks a lot for the help. Vítor     No publisher vtlsantos 2015-06-30T20:02:05Z Comment https://crcns.org/forum/using-datasets/826607086/520754812 Greetings, The answers are below. Please let me know if anything is unclear. Cheers, Natalia Bilenko, Gallant Lab. Previously Junxing Shi wrote: Three questions: 1. How can I project the fMRI data to surface as shown in the paper: Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies?   We used FreeSurfer (http://freesurfer.net/) to create the brain surface from the anatomical files included in the dataset. We then aligned the functional data manually using Pycortex (http://pycortex.org/), our lab's surface visualization software. The data can also be aligned using other fMRI analysis software, including FreeSurfer.   2. Some regions of inter, ex: FFA, were not provided in the indexing file. Is it because these areas were not included?   Yes, since the scanning volume was limited mostly to the occipital lobe, FFA was not spanned by the scanning volume in some of the subjects.   3. Are the three subjects' dataset in the MNI space? Because when I check the files, it seems like they were not aligned consistently.   No, all data are in the native anatomical space for all subjects. FreeSurfer can be used to remap the data from native to MNI space.   Thank you very much!   Junxing Shi   No publisher nbilenko 2015-06-09T21:07:58Z Comment https://crcns.org/forum/using-datasets/725145405/647209525 Thanks for this question. In response, the data contributor provided an update to the data description document.  The updates are shown below in bold: ... the data set contains simultaneous imaging with loose-seal cell-attached recording in GCaMP expressing neurons in the mouse visual cortex. The data are described in: Akerboom, et al JNS 2012 (http://www.ncbi.nlm.nih.gov/pubmed/23035093; figure 9). Chen, et al Nature 2013 (http://www.ncbi.nlm.nih.gov/pubmed/23868258; figure 3). No publisher jteeters 2015-05-13T15:23:06Z Comment https://crcns.org/forum/using-datasets/452032349/991647656 Based on information provided by Kenji Mizuseki (Research Assistant Professor in the Buzsaki lab), Robson compiled a document giving the relative depths (superficial vs. deep) of the channels in each shank.  This document (crcns-hc2-shank-maps.pdf) is now available from the " About page " for the hc-2 data set.  Thanks Robson. Kenji, Anton and Gautam!   No publisher jteeters 2012-03-09T01:17:05Z Comment https://crcns.org/forum/using-datasets/527189381/754794665 Hi, I have solved the questions 1 and 3 except for the difference of the amplification. Please reply about the 2nd question and the  amplification , thanks!   No publisher lizhaohui 2012-03-05T23:51:10Z Comment https://crcns.org/forum/using-datasets/931502130/753317628 Hi,   A paper (Y Dan 2005) that goes with the pvc-2 data mentions there are 36 complex and 14 simple neurons.  How do we distinguish the neurons in the .log files?  By 'distinguish' I mean not only simple/complex but other characteristics as well, like perhaps recording location, depth, etc.   Thanks! No publisher markrogersjr 2011-06-01T20:47:20Z Comment https://crcns.org/forum/using-datasets/931502129/749905768 The data is in the format of spk, how can I transform it to mat? No publisher lizhaohui 2011-05-31T14:19:15Z Comment https://crcns.org/forum/using-datasets/276820825/489456539 Thanks, I can now see this information in both locations you specified.  If I then calculated Tsec = T/32552 and compute the position in the same way, I find that the positionSampling vector is still 5.7 minutes longer than the last spike time in Tsec.  Would it make sense that the electrophysiology recordings were stopped this long before the position recording? No publisher DFetterhoff 2016-04-19T10:38:32Z Comment https://crcns.org/forum/using-datasets/16756230/812788889 Hi, I have downloaded the data recorded from cat. There are 10 neurons in the dataset, I want to know where thses neurons are located. Thanks! No publisher lizhaohui 2013-11-15T03:21:26Z Comment https://crcns.org/forum/using-datasets/305828919/94388003 Hi, I have almost the same problems. Regarding above numbers, however, I am not agree with Ayub. There are 260 trash data and the first 3 rows give information regardless of fixations/saccade. So, the first frame has to start at row 264. Also the display rate is 240/31.185 = 7.696 samples per frame   Thanks No publisher skhatoon 2013-10-08T20:48:14Z Comment https://crcns.org/forum/using-datasets/115877553/16687489 Hi Jeff, It seems that there are still some missing files in these datasets. Where can I find the .whl files in gor01 or vvp01 folders?    Thanks, Bryan No publisher bryancsouza 2015-01-05T22:52:15Z Comment https://crcns.org/forum/using-datasets/444349776/922258501 I could not find any information if during recording monkeys were fixate or not? The data contain spike wave form or LFP is available too? No publisher fjahromy 2015-01-04T20:09:29Z Comment https://crcns.org/forum/using-datasets/931502130/536525010 Mark, Unfortunately you can't distinguish between simple and complex in the log file. One of the papers associated with this data (Touryan, 2005) uses the below criterion. However, the CRCNS data does not include the drifting gratings component. Since the distinction is somewhat arbitrary, there are other was to distinguish simple from complex cells (including number of significant eigenvectors in spike-triggered covariance matrix). The log file only contains information about the stimulus configuration.    "Cells were classified as simple if their RFs had clear ON and OFF subregions (Hubel and Wiesel, 1962) and if the ratio of the first harmonic to the DC component of the response to an optimally oriented drifting grating was >1 (Skottun et al., 1991). All cells included in this study were complex cells." (Touryan, 2005)   - Jon Touryan Previously Mark Rogers wrote: Hi,   A paper (Y Dan 2005) that goes with the pvc-2 data mentions there are 36 complex and 14 simple neurons.  How do we distinguish the neurons in the .log files?  By 'distinguish' I mean not only simple/complex but other characteristics as well, like perhaps recording location, depth, etc.   Thanks!   No publisher touryan 2014-12-29T23:46:41Z Comment https://crcns.org/forum/using-datasets/601153056/298870837 Hello Michael, yes you are correct. While orientation tuning curves were measured (with sinusoidal gratings), this data was not included in the CRCNS dataset. I believe this was due to in the increased complexity of selecting, loading and processing the tuning curve data. Other datasets on CRCNS may be better suited for this type of analysis.  Sorry  - Jon Touryan     Previously Michael Oliver wrote: Hello, There doesn't seem to be the necessary data for generating the orientation and spatial frequency tuning plots for the cells recorded with the 2D stimuli. Based on Jon Touryan's paper it seems these tuning curves were measured, so I was hoping to get that data for comparison purposes. Thanks! Michael Oliver   No publisher touryan 2014-12-29T23:26:49Z Comment https://crcns.org/forum/using-datasets/996335119/40789487 Ilya, I have posted some answers to your questions below. This data was collected some time ago, so my recollections are limited. However, I have reviewed some of my data and notes and can hopefully shed some light on your questions:   1) I believe this is referring to the three classes of natural image sequences (Equalpower A/B/C). The differences between these classes are minimal but worth noting. The A sequences have lower RMS contrast. This was done to minimize the inevitable [0 255] clipping that can occur when image patches are re-scaled. The B sequences have higher RMS contrast and thus more clipping (I don't remember the fraction of pixels that were clipped, but it relatively small < 5% of pixels). The C sequences have the same contrast as B sequences with both uniform (i.e. spatial frequency = 0) and redundant frames (i.e. correlation coefficient between existing frames > 0.95) removed. This helps when inverting the stimulus auto-correlation matrix. The numbers simply indicate the order in which they were created.     2-3) File naming convention: YYMMDD.(experimental chamber [A,B]).(electrode penetration indicator [a-z])(cell number [00-99])(run number [a-z])(stimulus name, e.g. 'equalpower_B1').(file type, e.g. 'sa0')   030605.A.b02cequalpower_B3.sa0 = Spike file collected June 5, 2003; Chamber A; Penetration b, cell number 2, run number 3, using equalpower_B3 stimulus.   4) I'm not 100% sure of this, but basically the recording system could be configured for up to 60 channels of simultaneous recording. However, for this dataset we were primarily using one electrode (sa0). Typically, there was only one cells that reached threshold at a time/depth, however, occasionally there were multiple cells that we separated by clustering methods (sr0, sr2, ...).   Hope this helps.   - Jon Touryan   Previously Ilya Kuzovkin wrote: Hi community My name is Ilya, I am a PhD student at the Computational Neuroscience lab in University of Tartu and I have a few questions about the PVC-2 dataset. I am interested in the part of the dataset related to the natural images (<pre>crcns-pvc2/2D_noise_natural</pre> and I have a trouble understanding the structure of the data​: 1) In the articles it is mentioned that "three distinct natural ensembles were used in this study", but there are 8 <pre>Equalpower*</pre> files inside the <pre>Stimulus_Files</pre>. Why is that? What letters A,B,C and numbers 1,2,3 mean? Are these different sequences of images or same images but in different order? 2) Inside the <pre>Spike_and_Log_Files</pre> folder we have folders with names like <pre>030605.A.b02</pre>. What does the <pre>b02</pre> part mean? Is it the code for the test subject (cat)? Or it is an ID of a neuron? 3) Inside the folder <pre>030605.A.b02</pre> there are files with names <pre>030605.A.b02cequalpower_B3.sa0</pre>, <pre>030605.A.b02dequalpower_B3.sa0</pre>, <pre>030605.A.b02eequalpower_B3.sa0</pre>. What those letters <b>c, d, e</b> indicate? 4) The description of the data says that the data was recorded from 60 channels. But for every <pre>.sa0</pre> file when I load it using <pre>fget_hdr</pre> the <pre>hdr.DataInfo.Channel</pre> is always 0. What is the correct way to interpret this number?     No publisher touryan 2014-12-29T23:15:09Z Comment