<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Hi Nenad<div><br><div><div>On 30 Aug 2012, at 10:33, Nenad Polomac wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div>I am analyzing data obtained on CTF MEG 275 system. However, 4 sensors are broken and data ended up with 271 sensor. So, my question is should I interpolate the missing sensors with <span style="background-color:rgb(247,249,250);color:rgb(51,51,51);font-family:Consolas,'Andale Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap"> </span><font color="green" style="font-family:Consolas,'Andale Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap;padding:0px;margin:0px;color:rgb(51,51,51)"><a href="http://fieldtrip.fcdonders.nl/reference/ft_channelrepair" title="" style="font-family:Consolas,'Andale Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap;padding:0px;margin:0px;color:rgb(51,51,51)">FT_CHANNELREPAI</a><u>R</u>? </font>In the case I leave data with 271 sensor, will those missing sensors influence neighbors configuration in the statistic and the source localisation analysis?</div>
</blockquote><br></div><div>If the channels are consistently broken in all your subjects, you should better not interpolate them. If the channels are only missing in some, but not all subjects, interpolating will be of use for the channel-level statistics. </div><div><br></div><div>For source reconstruction you should not interpolate the broken channels. Group statistics on source-level data is also not affected by having slight differences in the working channels over subjects.</div><div><br></div><div>best regards</div><div>Robert</div><div><br></div><div><br></div><div><br></div><div><br></div><br></div></body></html>