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	<title>Neurobot &#187; Documentation</title>
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	<link>http://neurobot.bio.auth.gr</link>
	<description>A computational neuroscience and neuroinformatics blog</description>
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		<title>EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters</title>
		<link>http://neurobot.bio.auth.gr/2021/eegminer-discovering-interpretable-features-of-brain-activity-with-learnable-filters/</link>
		<comments>http://neurobot.bio.auth.gr/2021/eegminer-discovering-interpretable-features-of-brain-activity-with-learnable-filters/#comments</comments>
		<pubDate>Sat, 23 Oct 2021 17:53:25 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<category><![CDATA[EEG]]></category>
		<category><![CDATA[Interpretability]]></category>
		<category><![CDATA[Learnable Filters]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=4099</guid>
		<description><![CDATA[Patterns of brain activity are associated with different brain processes and can be used to identify different brain states and make behavioral predictions. However, the relevant features are not readily apparent and accessible. To mine informative latent representations from multichannel EEG recordings, we propose a novel differentiable EEG decoding pipeline consisting of learnable filters and [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2021/eegminer-discovering-interpretable-features-of-brain-activity-with-learnable-filters/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Music perception triggers brain rhythms multiplexing: EEG experimental evidence</title>
		<link>http://neurobot.bio.auth.gr/2018/music-perception-triggers-brain-rhythms-multiplexing-eeg-experimental-evidence/</link>
		<comments>http://neurobot.bio.auth.gr/2018/music-perception-triggers-brain-rhythms-multiplexing-eeg-experimental-evidence/#comments</comments>
		<pubDate>Mon, 05 Feb 2018 16:40:04 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[brain networks]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[community detection]]></category>
		<category><![CDATA[modularity]]></category>
		<category><![CDATA[multiplexing]]></category>
		<category><![CDATA[music]]></category>
		<category><![CDATA[music neuroscience]]></category>
		<category><![CDATA[music perception]]></category>
		<category><![CDATA[network neuroscience]]></category>
		<category><![CDATA[Neural Networks]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=4001</guid>
		<description><![CDATA[A new study reports for the first time functional interactions among brain rhythms in music perception using a novel, elegant, multiplex-aware approach based on a community detection algorithm. The approach was motivated by recent trends in Network Science that focus on the multi-scaled character of complex network systems. A novel, elegant, multiplex-aware framework is introduced, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2018/music-perception-triggers-brain-rhythms-multiplexing-eeg-experimental-evidence/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Musical NeuroPicks: a consumer-grade BCI for on-demand music streaming services</title>
		<link>http://neurobot.bio.auth.gr/2017/musical-neuropicks-a-consumer-grade-bci-for-on-demand-music-streaming-services/</link>
		<comments>http://neurobot.bio.auth.gr/2017/musical-neuropicks-a-consumer-grade-bci-for-on-demand-music-streaming-services/#comments</comments>
		<pubDate>Thu, 07 Sep 2017 11:19:34 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[music recommendation]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3959</guid>
		<description><![CDATA[We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener&#8217;s subjective experience of music into scores that can be used in popular on-demand music streaming services. Our study resulted into two variants, differing in terms of performance and execution time, and hence, subserving distinct applications in online [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2017/musical-neuropicks-a-consumer-grade-bci-for-on-demand-music-streaming-services/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Transcranial stimulation of the developing brain: a plea for extreme caution</title>
		<link>http://neurobot.bio.auth.gr/2014/transcranial-stimulation-of-the-developing-brain-a-plea-for-extreme-caution/</link>
		<comments>http://neurobot.bio.auth.gr/2014/transcranial-stimulation-of-the-developing-brain-a-plea-for-extreme-caution/#comments</comments>
		<pubDate>Thu, 07 Aug 2014 15:01:43 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[neuroethics]]></category>
		<category><![CDATA[tCS]]></category>
		<category><![CDATA[TMS]]></category>
		<category><![CDATA[transcranial direct current stimulation]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3584</guid>
		<description><![CDATA[An opinion study published in Frontiers in Human Neuroscience that focuses on the risk assessment of translating brain stimulation procedures to pediatric cases. By NJ Davis, Department of Psychology, Swansea University, Swansea, UK You may read the full article here Related work: “Non-invasive” brain stimulation is not non-invasive]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2014/transcranial-stimulation-of-the-developing-brain-a-plea-for-extreme-caution/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A non-parametric prototyping scheme for LFP dynamics and its application to detect changes in spontaneous UP-states due to cortical maturation and aging</title>
		<link>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/</link>
		<comments>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/#comments</comments>
		<pubDate>Thu, 26 Jun 2014 22:42:39 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[LFP]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Statistical Analysis]]></category>
		<category><![CDATA[Trajectories]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3577</guid>
		<description><![CDATA[Spontaneous network activity in the form of Up and Down states plays an important role in the function of neural circuits and reflects intrinsic connectivity. Such cortical dynamics are shaped by genes, experience and intrinsic cellular properties and form the substrate upon which external stimuli and neuromodulation will impinge to determine cortical responses. The scope [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Exploiting the temporal patterning of transient VEP signals: A statistical single-trial methodology with implications to brain–computer interfaces</title>
		<link>http://neurobot.bio.auth.gr/2014/exploiting-the-temporal-patterning-of-transient-vep-signals-a-statistical-single-trial-methodology-with-implications-to-brain%e2%80%93computer-interfaces/</link>
		<comments>http://neurobot.bio.auth.gr/2014/exploiting-the-temporal-patterning-of-transient-vep-signals-a-statistical-single-trial-methodology-with-implications-to-brain%e2%80%93computer-interfaces/#comments</comments>
		<pubDate>Thu, 26 Jun 2014 22:19:43 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3570</guid>
		<description><![CDATA[When visual evoked potentials (VEPs) are deployed in brain–computer interfaces (BCIs), the emphasis is put on stimulus design. In the case of transient VEPs (TVEPs) brain responses are never treated individually, i.e. on a single-trial (ST) basis, due to their poor signal quality. Therefore their main characteristic, which is the emergence during early latencies, remains [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2014/exploiting-the-temporal-patterning-of-transient-vep-signals-a-statistical-single-trial-methodology-with-implications-to-brain%e2%80%93computer-interfaces/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Clustering Algorithms in Biomedical Research: A Review</title>
		<link>http://neurobot.bio.auth.gr/2012/clustering-algorithms-in-biomedical-research-a-review/</link>
		<comments>http://neurobot.bio.auth.gr/2012/clustering-algorithms-in-biomedical-research-a-review/#comments</comments>
		<pubDate>Thu, 20 Sep 2012 08:56:43 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3283</guid>
		<description><![CDATA[Applications of clustering algorithms in biomedical research are ubiquitous. However, due to the diversity of cluster analysis, the diversity of critical elements underlying different clustering algorithms can be daunting. This paper presents an overview of the status quo of clustering algorithms and illustrates examples of biomedical applications based on cluster analysis. Access the review paper [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/clustering-algorithms-in-biomedical-research-a-review/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>In quest of the missing neuron: Spike sorting based on dominant-sets clustering</title>
		<link>http://neurobot.bio.auth.gr/2012/in-quest-of-the-missing-neuron-spike-sorting-based-on-dominant-sets-clustering/</link>
		<comments>http://neurobot.bio.auth.gr/2012/in-quest-of-the-missing-neuron-spike-sorting-based-on-dominant-sets-clustering/#comments</comments>
		<pubDate>Wed, 12 Sep 2012 11:18:51 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[neural recordings]]></category>
		<category><![CDATA[Sparse neurons]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3276</guid>
		<description><![CDATA[Spike sorting algorithms aim at decomposing complex extracellular signals to independent events from single neurons in the electrode&#8217;s vicinity. The decision about the actual number of active neurons is still an open issue, with sparsely firing neurons and background activity the most influencing factors. We introduce a graph-theoretical algorithmic procedure that successfully resolves this issue. Dimensionality [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/in-quest-of-the-missing-neuron-spike-sorting-based-on-dominant-sets-clustering/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Book chapter &#124; &#8216;Extracellular spikes and current-source density&#8217;</title>
		<link>http://neurobot.bio.auth.gr/2012/book-chapter-extracellular-spikes-and-current-source-density/</link>
		<comments>http://neurobot.bio.auth.gr/2012/book-chapter-extracellular-spikes-and-current-source-density/#comments</comments>
		<pubDate>Wed, 14 Mar 2012 15:51:37 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[LFP]]></category>
		<category><![CDATA[Modelling]]></category>
		<category><![CDATA[Neurophysiology]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3165</guid>
		<description><![CDATA[Preprint of the forthcoming book chapter &#8216;Extracellular spikes and current-source density&#8217; featuring the numerical framework biophysics for the calculation of extracellular potentials from transmembrane currents in multi-compartment neuron models, using the line-source method (Holt &#38; Koch, J Comp Neurosci 1999). The chapter is to appear on the forthcoming book: K.H. Pettersen, H. Linden, A.M. Dale and [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/book-chapter-extracellular-spikes-and-current-source-density/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Book: &#8216;The Elements of  Statistical Learning&#8217;</title>
		<link>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/</link>
		<comments>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/#comments</comments>
		<pubDate>Fri, 09 Mar 2012 20:49:59 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3148</guid>
		<description><![CDATA[The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Download the book PDF (corrected 5th printing) here: http://www-stat.stanford.edu/~tibs/ElemStatLearn/]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Towards reliable spike-train recordings from thousands of neurons with multielectrodes</title>
		<link>http://neurobot.bio.auth.gr/2012/towards-reliable-spike-train-recordings-from-thousands-of-neurons-with-multielectrodes/</link>
		<comments>http://neurobot.bio.auth.gr/2012/towards-reliable-spike-train-recordings-from-thousands-of-neurons-with-multielectrodes/#comments</comments>
		<pubDate>Tue, 24 Jan 2012 18:25:13 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3103</guid>
		<description><![CDATA[A review article describing challenges towards accurate multi-electrode automatic spike sorting. The article emphasizes the absence of ground truth and the need of realistic modeling in the validation step of spike-sorting algorithms. You may read the article here: Einevoll GT, Franke F, Hagen E, Pouzat C, Harris KD. Towards reliable spike-train recordings from thousands of [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/towards-reliable-spike-train-recordings-from-thousands-of-neurons-with-multielectrodes/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Online wiki release of &#8220;Computational Explorations in Cognitive Neuroscience&#8221; textbook</title>
		<link>http://neurobot.bio.auth.gr/2012/online-wiki-release-of-computational-explorations-in-cognitive-neuroscience-textbook/</link>
		<comments>http://neurobot.bio.auth.gr/2012/online-wiki-release-of-computational-explorations-in-cognitive-neuroscience-textbook/#comments</comments>
		<pubDate>Mon, 09 Jan 2012 10:11:36 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Book Reviews]]></category>
		<category><![CDATA[Documentation]]></category>
		<category><![CDATA[External announcements]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Modelling]]></category>
		<category><![CDATA[Neurophysiology]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3081</guid>
		<description><![CDATA[The 2nd Edition of &#8220;Computational Explorations in Cognitive Neuroscience&#8221; (O&#8217;Reilly &#38; Munakata, 2000) is available as a free wiki textbook. The book is available here: http://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Main From the same page, it can also be ordered as a hard-copy book, printed by PediaPress (see link at top of above page). A major component of the book [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/online-wiki-release-of-computational-explorations-in-cognitive-neuroscience-textbook/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Spike sorting based on noise-assisted semi-supervised learning methodologies</title>
		<link>http://neurobot.bio.auth.gr/2012/spike-sorting-based-on-noise-assisted-semi-supervised-learning-methodologies/</link>
		<comments>http://neurobot.bio.auth.gr/2012/spike-sorting-based-on-noise-assisted-semi-supervised-learning-methodologies/#comments</comments>
		<pubDate>Sun, 08 Jan 2012 15:23:11 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Noise]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3076</guid>
		<description><![CDATA[SAN 2011 abstract in Neuroscience Letters 2011, vol. 500(Suppl.), e32-33.- DOI: http://dx.doi.org/10.1016/j.neulet.2011.05.161 Also, see presentation in SAN 2011]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/spike-sorting-based-on-noise-assisted-semi-supervised-learning-methodologies/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Quality metrics to accompany spike sorting of extracellular signals</title>
		<link>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/</link>
		<comments>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/#comments</comments>
		<pubDate>Mon, 26 Dec 2011 10:46:17 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3069</guid>
		<description><![CDATA[A review on visualization schemes and quality metrics used to evaluate the success of spike sorting procedures, published in Journal of Neuroscience. You may read the article here: Hill DN, Mehta SB and Kleinfeld D. Quality metrics to accompany spike sorting of extracellular signals. J Neurosci (2011) vol. 31 (24) pp. 8699-705]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Spike Sorting: The First Step in Decoding the Brain</title>
		<link>http://neurobot.bio.auth.gr/2011/spike-sorting-the-first-step-in-decoding-the-brain/</link>
		<comments>http://neurobot.bio.auth.gr/2011/spike-sorting-the-first-step-in-decoding-the-brain/#comments</comments>
		<pubDate>Mon, 26 Dec 2011 10:19:14 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3061</guid>
		<description><![CDATA[An overview of the spike sorting problem and challenges in IEEE Signal Processing Magazine. You may read the article here: Gibson et al. Spike Sorting: The First Step in Decoding the Brain. Signal Processing Magazine, IEEE (2012) vol. 29 (1) pp. 124 &#8211; 143 For an extended review on available contemporary algorithms in the spike [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/spike-sorting-the-first-step-in-decoding-the-brain/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Performance comparison of extracellular spike sorting algorithms for single-channel recordings</title>
		<link>http://neurobot.bio.auth.gr/2011/performance-comparison-of-extracellular-spike-sorting-algorithms-for-single-channel-recordings/</link>
		<comments>http://neurobot.bio.auth.gr/2011/performance-comparison-of-extracellular-spike-sorting-algorithms-for-single-channel-recordings/#comments</comments>
		<pubDate>Wed, 07 Dec 2011 09:20:23 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3050</guid>
		<description><![CDATA[A review and comparative analysis paper of contemporary algorithms in the spike sorting domain, published in Journal of Neuroscience Methods. Wild J et al. “Performance comparison of extracellular spike sorting algorithms for single-channel recordings“. Journal of Neuroscience Methods, 2011, vol.203 (2), pp. 369-76; doi:10.1016/j.jneumeth.2011.10.013]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/performance-comparison-of-extracellular-spike-sorting-algorithms-for-single-channel-recordings/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>An introductory review of information theory in the context of computational neuroscience</title>
		<link>http://neurobot.bio.auth.gr/2011/an-introductory-review-of-information-theory-in-the-context-of-computational-neuroscience/</link>
		<comments>http://neurobot.bio.auth.gr/2011/an-introductory-review-of-information-theory-in-the-context-of-computational-neuroscience/#comments</comments>
		<pubDate>Thu, 22 Sep 2011 16:20:56 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3022</guid>
		<description><![CDATA[A nice review paper presenting introductory fundamental concepts of information theory, from engineering to neuroscience. The paper was published as: McDonnell MD, Ikeda S and Manton JH, &#8221;An introductory review of information theory in the context of computational neuroscience&#8220;, Biological Cybernetics 2011;105(1):55-70. Also available in PDF format here.]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/an-introductory-review-of-information-theory-in-the-context-of-computational-neuroscience/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Journal Impact Factors updated for 2010</title>
		<link>http://neurobot.bio.auth.gr/2011/journal-impact-factors-updated-for-2010/</link>
		<comments>http://neurobot.bio.auth.gr/2011/journal-impact-factors-updated-for-2010/#comments</comments>
		<pubDate>Tue, 26 Jul 2011 15:04:47 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3008</guid>
		<description><![CDATA[Please see the Scientific Journals Table]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/journal-impact-factors-updated-for-2010/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Enhancing BCIs through electrocorticography (ECoG)</title>
		<link>http://neurobot.bio.auth.gr/2011/enhancing-bcis-through-electrocorticography-ecog/</link>
		<comments>http://neurobot.bio.auth.gr/2011/enhancing-bcis-through-electrocorticography-ecog/#comments</comments>
		<pubDate>Tue, 28 Jun 2011 07:50:50 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Stories]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2991</guid>
		<description><![CDATA[Electrocorticography (ECoG) records the “high-gamma” (&#62;60 Hz) frequency profile of the cortex, featuring a temporal resolution of the order of milliseconds [1]. Coupled with a software interface, the use of ECoG was explored in a Brain Computer Interface study when participants were asked to either think or say different vowel sounds [2]. While the recorded [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/enhancing-bcis-through-electrocorticography-ecog/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Information theory methods in Neuroscience</title>
		<link>http://neurobot.bio.auth.gr/2011/information-theory-methods-in-neuroscience/</link>
		<comments>http://neurobot.bio.auth.gr/2011/information-theory-methods-in-neuroscience/#comments</comments>
		<pubDate>Wed, 27 Apr 2011 09:41:41 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>
		<category><![CDATA[Neurophysiology]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2913</guid>
		<description><![CDATA[Back in 1948, Shannon introduced Information Theory with his landmark paper &#8220;A mathematical theory of communication&#8221;[1]. Since then, Neuroscience has been treated by researchers as a major field of application of this new theory,  beyond its original scope. A recent special issue of the Journal of Computational Neuroscience on Methods of Information Theory in Neuroscience [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/information-theory-methods-in-neuroscience/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>NASS: an empirical approach to spike sorting with overlap resolution based on a hybrid noise-assisted methodology</title>
		<link>http://neurobot.bio.auth.gr/2011/nass-an-empirical-approach-to-spike-sorting-with-overlap-resolution-based-on-a-hybrid-noise-assisted-methodology/</link>
		<comments>http://neurobot.bio.auth.gr/2011/nass-an-empirical-approach-to-spike-sorting-with-overlap-resolution-based-on-a-hybrid-noise-assisted-methodology/#comments</comments>
		<pubDate>Sat, 26 Feb 2011 07:39:05 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Noise]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2881</guid>
		<description><![CDATA[Background noise and spike overlap pose problems in contemporary spike-sorting strategies. In this paper, both issues are addressed by a hybrid scheme that combines the robust representation of spike waveforms to facilitate the reliable identification of contributing neurons with efficient data learning to enable the precise decomposition of coactivations. A recently introduced manifold learning technique, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/nass-an-empirical-approach-to-spike-sorting-with-overlap-resolution-based-on-a-hybrid-noise-assisted-methodology/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A Global Geometric Framework for Nonlinear Dimensionality Reduction</title>
		<link>http://neurobot.bio.auth.gr/2010/a-global-geometric-framework-for-nonlinear-dimensionality-reduction/</link>
		<comments>http://neurobot.bio.auth.gr/2010/a-global-geometric-framework-for-nonlinear-dimensionality-reduction/#comments</comments>
		<pubDate>Thu, 16 Sep 2010 12:20:24 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2439</guid>
		<description><![CDATA[The classic Tenenbaum&#8216;s paper that introduces ISOMAP, a manifold learning approach featuring non-linear dimensionality reduction. J. B. Tenenbaum, V. De Silva and J. C. Langford (2000). Science 290 (5500), 2319-2323 You may access the full text of the document here, or visit the ISOMAP Homepage for further details, Matlab code and data sets.]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2010/a-global-geometric-framework-for-nonlinear-dimensionality-reduction/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Template matching methods for spike sorting</title>
		<link>http://neurobot.bio.auth.gr/2010/template-matching-methods-for-spike-sorting/</link>
		<comments>http://neurobot.bio.auth.gr/2010/template-matching-methods-for-spike-sorting/#comments</comments>
		<pubDate>Wed, 04 Aug 2010 08:31:25 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2438</guid>
		<description><![CDATA[Template matching is a popular method in spike sorting, mostly employed in the overlap resolution task. Several algorithms have been proposed during the last 5 years, some of them featuring online implementations. Selected publications follow: Zhang et al. Spike sorting based on automatic template reconstruction with a partial solution to the overlapping problem. J Neurosci [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2010/template-matching-methods-for-spike-sorting/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A Description of NeuroML in PLoS Computational Biology</title>
		<link>http://neurobot.bio.auth.gr/2010/a-description-of-neuroml-in-plos-computational-biology/</link>
		<comments>http://neurobot.bio.auth.gr/2010/a-description-of-neuroml-in-plos-computational-biology/#comments</comments>
		<pubDate>Tue, 27 Jul 2010 06:27:05 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Neural Networks]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2432</guid>
		<description><![CDATA[A description of NeuroML (http://www.neuroml.org) has been published in PLoS Computational Biology. Padraig Gleeson, Sharon Crook, Robert C. Cannon, Michael L. Hines, Guy O. Billings, Matteo Farinella, Thomas M. Morse, Andrew P. Davison, Subhasis Ray, Upinder S. Bhalla, Simon R. Barnes, Yoana D. Dimitrova, R. Angus Silver NeuroML: A Language for Describing Data Driven Models [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2010/a-description-of-neuroml-in-plos-computational-biology/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Classic neuroscience papers</title>
		<link>http://neurobot.bio.auth.gr/2009/classic-neuroscience-papers/</link>
		<comments>http://neurobot.bio.auth.gr/2009/classic-neuroscience-papers/#comments</comments>
		<pubDate>Wed, 03 Jun 2009 08:28:05 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Neurophysiology]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2329</guid>
		<description><![CDATA[Society for Neuroscience provides access to a sample of high impact classic papers addressing a range of neuroscience topics. To suggest a classic paper, e-mail jn(at)sfn(dot)org. Topics are: * Action potentials * Arousal * Attention * Electroencephalography * Emotion * Frontal lobe function * Hormones * Language * Learning and memory * Sprouting * Stress [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2009/classic-neuroscience-papers/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>An enhanced version of nev2lkit</title>
		<link>http://neurobot.bio.auth.gr/2008/an-enhanced-version-of-nev2lkit/</link>
		<comments>http://neurobot.bio.auth.gr/2008/an-enhanced-version-of-nev2lkit/#comments</comments>
		<pubDate>Tue, 23 Sep 2008 16:32:39 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2236</guid>
		<description><![CDATA[Extracellular recordings of spontaneous nerve activity is a common practice for a number of electrophysiological experiments providing valuable information concerning peripheral and central nervous system physiology of vertebrates and invertebrates. Extracellular electrodes record voltage potentials representing the activity of an unknown number of activated axons which may serve different functions. It is generally assumed that [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/an-enhanced-version-of-nev2lkit/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Performance evaluation of PCA-based spike sorting algorithms</title>
		<link>http://neurobot.bio.auth.gr/2008/performance-evaluation-of-pca-based-spike-sorting-algorithms/</link>
		<comments>http://neurobot.bio.auth.gr/2008/performance-evaluation-of-pca-based-spike-sorting-algorithms/#comments</comments>
		<pubDate>Tue, 09 Sep 2008 07:14:06 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2230</guid>
		<description><![CDATA[Adamos DA, Kosmidis EK and Theophilidis G Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/performance-evaluation-of-pca-based-spike-sorting-algorithms/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Review: Reliability, synchrony and noise</title>
		<link>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/</link>
		<comments>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/#comments</comments>
		<pubDate>Mon, 21 Jul 2008 08:28:52 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2214</guid>
		<description><![CDATA[This review describes a constructive role for noise in synchronizing populations of neurons. Trends Neurosci. 2008 Jul 4. [Epub ahead of print] Reliability, synchrony and noise. Ermentrout GB, Galán RF, Urban NN. The brain is noisy. Neurons receive tens of thousands of highly fluctuating inputs and generate spike trains that appear highly irregular. Much of [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Linear and non-linear methods for brain-computer interfaces</title>
		<link>http://neurobot.bio.auth.gr/2007/linear-and-non-linear-methods-for-brain-computer-interfaces/</link>
		<comments>http://neurobot.bio.auth.gr/2007/linear-and-non-linear-methods-for-brain-computer-interfaces/#comments</comments>
		<pubDate>Wed, 22 Aug 2007 20:15:05 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2065</guid>
		<description><![CDATA[This paper includes examples applying EEG data sets to linear and non-linear methods. Also an overview of the various pros and cons of each approach is summarised. The paper follows a formal debate that was held on the pros and cons of linear and non-linear methods in Brain Computer Interface research, at the Second International [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2007/linear-and-non-linear-methods-for-brain-computer-interfaces/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Brain–Computer Interface Technology: A Review of the First International Meeting</title>
		<link>http://neurobot.bio.auth.gr/2007/brain%e2%80%93computer-interface-technology-a-review-of-the-first-international-meeting/</link>
		<comments>http://neurobot.bio.auth.gr/2007/brain%e2%80%93computer-interface-technology-a-review-of-the-first-international-meeting/#comments</comments>
		<pubDate>Wed, 11 Jul 2007 08:23:27 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2055</guid>
		<description><![CDATA[&#8220;Over the past decade, many laboratories have begun to explore brain–computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods.BCI’s provide these users with communication channels that do not depend on peripheral nerves and muscles.&#8221; This article summarizes the first international [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2007/brain%e2%80%93computer-interface-technology-a-review-of-the-first-international-meeting/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals</title>
		<link>http://neurobot.bio.auth.gr/2007/a-survey-of-signal-processing-algorithms-in-brain%e2%80%93computer-interfaces-based-on-electrical-brain-signals/</link>
		<comments>http://neurobot.bio.auth.gr/2007/a-survey-of-signal-processing-algorithms-in-brain%e2%80%93computer-interfaces-based-on-electrical-brain-signals/#comments</comments>
		<pubDate>Fri, 25 May 2007 06:29:22 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2039</guid>
		<description><![CDATA[&#8220;Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals.&#8221; In the BCI literature, however, there is no [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2007/a-survey-of-signal-processing-algorithms-in-brain%e2%80%93computer-interfaces-based-on-electrical-brain-signals/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A review of classification algorithms for EEG-based brain–computer interfaces</title>
		<link>http://neurobot.bio.auth.gr/2007/a-review-of-classification-algorithms-for-eeg-based-brain%e2%80%93computer-interfaces/</link>
		<comments>http://neurobot.bio.auth.gr/2007/a-review-of-classification-algorithms-for-eeg-based-brain%e2%80%93computer-interfaces/#comments</comments>
		<pubDate>Fri, 25 May 2007 06:22:48 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2038</guid>
		<description><![CDATA[The authors review classification algorithms used to design brain–computer interface (BCI) systems based on electroencephalography (EEG). The authors briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, they compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI. You may [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2007/a-review-of-classification-algorithms-for-eeg-based-brain%e2%80%93computer-interfaces/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>How Behavioral Constraints May Determine Optimal Sensory Representations</title>
		<link>http://neurobot.bio.auth.gr/2007/how-behavioral-constraints-may-determine-optimal-sensory-representations/</link>
		<comments>http://neurobot.bio.auth.gr/2007/how-behavioral-constraints-may-determine-optimal-sensory-representations/#comments</comments>
		<pubDate>Fri, 16 Mar 2007 09:56:13 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2029</guid>
		<description><![CDATA[&#8220;The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the neuron&#8217;s average response as a function of a parameter that characterizes a physical stimulus. What determines the shapes of tuning curves in a neuronal population?&#8221; by Emilio Salinas Department of Neurobiology and Anatomy, Wake Forest University School [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2007/how-behavioral-constraints-may-determine-optimal-sensory-representations/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Neuronal ensemble control of prosthetic devices by a human with tetraplegia</title>
		<link>http://neurobot.bio.auth.gr/2006/neuronal-ensemble-control-of-prosthetic-devices-by-a-human-with-tetraplegia/</link>
		<comments>http://neurobot.bio.auth.gr/2006/neuronal-ensemble-control-of-prosthetic-devices-by-a-human-with-tetraplegia/#comments</comments>
		<pubDate>Tue, 07 Nov 2006 11:52:40 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>
		<category><![CDATA[Brain Research]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2018</guid>
		<description><![CDATA[&#8220;Neuromotor prostheses (NMPs) aim to replace or restore lost motor functions in paralysed humans by routeing movement-related signals from the brain, around damaged parts of the nervous system, to external effectors. To translate preclinical results from intact animals to a clinically useful NMP, movement signals must persist in cortex after spinal cord injury and be [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/neuronal-ensemble-control-of-prosthetic-devices-by-a-human-with-tetraplegia/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Towards adaptive classification for BCI</title>
		<link>http://neurobot.bio.auth.gr/2006/towards-adaptive-classification-for-bci/</link>
		<comments>http://neurobot.bio.auth.gr/2006/towards-adaptive-classification-for-bci/#comments</comments>
		<pubDate>Thu, 07 Sep 2006 06:54:09 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2016</guid>
		<description><![CDATA[&#8220;Non-stationarities are ubiquitous in EEG signals. They are especially apparent in the use of EEG-based brain-computer interfaces (BCIs): (a) in the differences between the initial calibration measurement and the online operation of a BCI, or (b) caused by changes in the subject&#8217;s brain processes during an experiment (e.g. due to fatigue, change of task involvement, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/towards-adaptive-classification-for-bci/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Membrane and Action Potential : Properties of Excitable Membranes</title>
		<link>http://neurobot.bio.auth.gr/2006/membrane-and-action-potential-properties-of-excitable-membranes/</link>
		<comments>http://neurobot.bio.auth.gr/2006/membrane-and-action-potential-properties-of-excitable-membranes/#comments</comments>
		<pubDate>Fri, 02 Jun 2006 21:59:09 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Neurophysiology]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2009</guid>
		<description><![CDATA[Neurophysiology is a study of neurons, nerves, and nervous systems, what they do and how they do it. A neuron is a cell that is specialized in two of the fundamental properties of living matter, namely excitability and conductivity. Excitability is the ability to respond to changes in the environment. By Michael D. Mann, Ph.D., [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/membrane-and-action-potential-properties-of-excitable-membranes/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Decoding neuronal firing and modeling neural networks</title>
		<link>http://neurobot.bio.auth.gr/2006/decoding-neuronal-firing-and-modeling-neural-networks/</link>
		<comments>http://neurobot.bio.auth.gr/2006/decoding-neuronal-firing-and-modeling-neural-networks/#comments</comments>
		<pubDate>Mon, 08 May 2006 18:45:37 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Neural Networks]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2007</guid>
		<description><![CDATA[Biological neural networks are large systems of complex elements interacting through a complex array of connections. How do we describe and interpret the activity of a large population of neurons and how do we model neural circuits when: o individual neurons are such complex elements and o our knowledge of the synaptic connections is so [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/decoding-neuronal-firing-and-modeling-neural-networks/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Information theory and neural coding</title>
		<link>http://neurobot.bio.auth.gr/2006/information-theory-and-neural-coding/</link>
		<comments>http://neurobot.bio.auth.gr/2006/information-theory-and-neural-coding/#comments</comments>
		<pubDate>Wed, 26 Apr 2006 13:04:27 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2006</guid>
		<description><![CDATA[Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. The authors review information-theory basics before demonstrating its [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/information-theory-and-neural-coding/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Entropy and Information in Neural Spike Trains</title>
		<link>http://neurobot.bio.auth.gr/2006/entropy-and-information-in-neural-spike-trains/</link>
		<comments>http://neurobot.bio.auth.gr/2006/entropy-and-information-in-neural-spike-trains/#comments</comments>
		<pubDate>Thu, 23 Mar 2006 20:04:51 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2003</guid>
		<description><![CDATA[The nervous system represents time-dependent signals in sequences of discrete action potentials or spikes, all spikes are identical so that information is carried only in the spike arrival times. A scientific paper by Steven P. Strong, Roland Koberle, Rob R. de Ruyter van Steveninck, and William Bialek -NEC Research Institute, Princeton, New Jersey -Department of [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/entropy-and-information-in-neural-spike-trains/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Quantifying the information transmitted in a single stimulus</title>
		<link>http://neurobot.bio.auth.gr/2006/quantifying-the-information-transmitted-in-a-single-stimulus/</link>
		<comments>http://neurobot.bio.auth.gr/2006/quantifying-the-information-transmitted-in-a-single-stimulus/#comments</comments>
		<pubDate>Sun, 19 Mar 2006 17:51:14 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Information Theory]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2002</guid>
		<description><![CDATA[Shannon mutual information provides a measure of how much information is, on average, contained in a set of neural activities about a set of stimuli. It has been extensively used to study neural coding in different brain areas. To apply a similar approach to investigate single stimulus encoding, the authors need to introduce a quantity [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/quantifying-the-information-transmitted-in-a-single-stimulus/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Expectation Maximization Theory</title>
		<link>http://neurobot.bio.auth.gr/2006/expectation-maximization-theory/</link>
		<comments>http://neurobot.bio.auth.gr/2006/expectation-maximization-theory/#comments</comments>
		<pubDate>Fri, 10 Mar 2006 13:15:02 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2001</guid>
		<description><![CDATA[An article on Expectation Maximization Theory, taken from the book &#8220;Biometric Authentication: A Machine Learning Approach&#8221;. The article/book-chapter addresses a data-clustering algorithm, called the expectation-maximization (EM) algorithm, when complete or partial information of observed data is made available. The book is written by M.W. Mak, S.Y. Kung, S.H. Lin. and the sample chapter is provided [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/expectation-maximization-theory/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Multiple neural spike train data analysis: state-of-the-art and future challenges</title>
		<link>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/</link>
		<comments>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/#comments</comments>
		<pubDate>Thu, 23 Feb 2006 00:17:38 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1999</guid>
		<description><![CDATA[Multiple electrodes are now a standard tool in neuroscience research that make it possible to study the simultaneous activity of several neurons in a given brain region or across different regions. The data from multi-electrode studies present important analysis challenges that must be resolved for optimal use of these neurophysiological measurements to answer questions about [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Networks of Spiking Neurons: A New Generation of Neural Network Models</title>
		<link>http://neurobot.bio.auth.gr/2005/networks-of-spiking-neurons-a-new-generation-of-neural-network-models/</link>
		<comments>http://neurobot.bio.auth.gr/2005/networks-of-spiking-neurons-a-new-generation-of-neural-network-models/#comments</comments>
		<pubDate>Tue, 14 Jun 2005 10:23:19 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Neural Networks]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1988</guid>
		<description><![CDATA[A nice article trying to give the reader an intuition what computer scientists can contribute to the question how the brain works. Access the article here by Thomas NatschlÃ¤ger Institute for Theoretical Computer Science at the Technical University of Graz.]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/networks-of-spiking-neurons-a-new-generation-of-neural-network-models/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Pulsed Neural Networks and their Application</title>
		<link>http://neurobot.bio.auth.gr/2005/pulsed-neural-networks-and-their-application/</link>
		<comments>http://neurobot.bio.auth.gr/2005/pulsed-neural-networks-and-their-application/#comments</comments>
		<pubDate>Tue, 14 Jun 2005 10:18:47 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Neural Networks]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1987</guid>
		<description><![CDATA[Pulsed neural networks are networks of spiking neurons, which represent an entirely new class of artificial neurons. The paper presents an overview of pulsed neural networks, including the structure, function and available training mechanisms for networks of spiking neurons. This paper highlights differences between this model,âfirst generationâ threshold gates, and âsecond generationâ sigmoid activation gates, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/pulsed-neural-networks-and-their-application/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Accuracy of Tetrode Spike Separation as Determined by Simultaneous Intracellular and Extracellular Measurements</title>
		<link>http://neurobot.bio.auth.gr/2005/accuracy-of-tetrode-spike-separation-as-determined-by-simultaneous-intracellular-and-extracellular-measurements/</link>
		<comments>http://neurobot.bio.auth.gr/2005/accuracy-of-tetrode-spike-separation-as-determined-by-simultaneous-intracellular-and-extracellular-measurements/#comments</comments>
		<pubDate>Wed, 01 Jun 2005 13:40:05 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1978</guid>
		<description><![CDATA[This Paper by K.D.Harris provides an excellent walkthrough to the understanding of the spike-sorting procedure. KENNETH D. HARRIS, DARRELL A. HENZE, JOZSEF CSICSVARI, HAJIME HIRASE, AND GY ORGY BUZS AKI Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey 07102 Download here(pdf): View this publication]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/accuracy-of-tetrode-spike-separation-as-determined-by-simultaneous-intracellular-and-extracellular-measurements/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Brain-computer interfaces for communication and control</title>
		<link>http://neurobot.bio.auth.gr/2005/brain-computer-interfaces-for-communication-and-control/</link>
		<comments>http://neurobot.bio.auth.gr/2005/brain-computer-interfaces-for-communication-and-control/#comments</comments>
		<pubDate>Mon, 02 May 2005 20:25:09 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Interfaces]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1976</guid>
		<description><![CDATA[Invited review This paper is a review on Brain-computer interfaces for communication and control. By Jonathan R. Wolpawa(a,b)*, Niels Birbaumer(c,d), Dennis J. McFarland(a),Gert Pfurtscheller(e), Theresa M. Vaughan (a) For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/brain-computer-interfaces-for-communication-and-control/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Spike sorting in the frequency domain</title>
		<link>http://neurobot.bio.auth.gr/2005/spike-sorting-in-the-frequency-domain/</link>
		<comments>http://neurobot.bio.auth.gr/2005/spike-sorting-in-the-frequency-domain/#comments</comments>
		<pubDate>Thu, 03 Feb 2005 12:40:55 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1969</guid>
		<description><![CDATA[This paper deals with the problem of extracting the activity of individual neurons from multi-electrode recordings. Dima Rinberg William Bialek Hanan Davidowitz Naftali Tishby NEC Research Institute, 4 Independence Way, Princeton, NJ 08540. This paper deals with the problem of extracting the activity of individual neurons from multi-electrode recordings. Important aspects of this work are: [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/spike-sorting-in-the-frequency-domain/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>How Many Clusters? Which Clustering Method?</title>
		<link>http://neurobot.bio.auth.gr/2005/how-many-clusters-which-clustering-method/</link>
		<comments>http://neurobot.bio.auth.gr/2005/how-many-clusters-which-clustering-method/#comments</comments>
		<pubDate>Tue, 01 Feb 2005 09:19:59 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Clustering]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1968</guid>
		<description><![CDATA[How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis. C. Fraley and A. E. Raftery Technical Report No. 329 Department of Statistics University of Washington Box 354322 Seattle, WA 98195-4322 USA We consider the problem of determining the structure of clustered data, without prior knowledge of the number of clusters or any other [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/how-many-clusters-which-clustering-method/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Test of spike sorting algorithms on the basis of simulated network data</title>
		<link>http://neurobot.bio.auth.gr/2005/test-of-spike-sorting-algorithms-on-the-basis-of-simulated-network-data/</link>
		<comments>http://neurobot.bio.auth.gr/2005/test-of-spike-sorting-algorithms-on-the-basis-of-simulated-network-data/#comments</comments>
		<pubDate>Mon, 31 Jan 2005 22:30:29 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1967</guid>
		<description><![CDATA[A comparison of spike sorting algorithms agains physiological extracellular potential data by a realistic cortical network simulation. Kerstin M.L. Menne*1, Andre Folkers*1, Thomas Malina*1, Reinoud Maex*2, Ulrich G. Hofmann*1 *1 Medical University of Lbeck, Institute for Signal Processing, Seelandstr. 1a, D-23569 Lbeck, Germany [menne, folkers, malina, hofmann]@ isip.mu-luebeck.de *2 Born-Bunge Foundation, University of Antwerp, B-2610 [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/test-of-spike-sorting-algorithms-on-the-basis-of-simulated-network-data/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A review of methods for spike sorting</title>
		<link>http://neurobot.bio.auth.gr/2005/a-review-of-methods-for-spike-sorting/</link>
		<comments>http://neurobot.bio.auth.gr/2005/a-review-of-methods-for-spike-sorting/#comments</comments>
		<pubDate>Mon, 31 Jan 2005 22:18:52 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1966</guid>
		<description><![CDATA[A review of methods for spike sorting: the detection and classification of neural action potentials. Michael S Lewickiy Howard Hughes Medical Institute, Computational Neurobiology Laboratory, The Salk Institute, 10010 N Torrey Pines Road, La Jolla, CA 92037, USA Received 31 July 1998 The detection of neural spike activity is a technical challenge that is a [...]]]></description>
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		<slash:comments>0</slash:comments>
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