papers fixed

Author: rgs2151

_data/papers.yml

@@ -30,7 +30,6 @@
   bib: "/assets/bibs/Nuttida_2023.txt"
   doi: "https://doi.org/10.1073/pnas.2316745122"
 
-
 - year: 2024
   title: "Disinhibitory signaling enables flexible coding of top-down information"
   authors: "Aquino TG*, Kim R*, Rungratsameetaweemana N."
@@ -39,10 +38,9 @@
   bib: "/assets/bibs/Aquino_2023.txt"
   doi: "https://doi.org/10.1101/2023.10.17.562828"
 
-
 - year: 2022
   title: "Brain network dynamics codify heterogeneity in seizure evolution"
-  authors: "Rungratsameetaweemana N, Lainscsek C, Cash SS, Garcia JO, Sejnowski TJ*, Bansal K*.""
+  authors: "Rungratsameetaweemana N, Lainscsek C, Cash SS, Garcia JO, Sejnowski TJ*, Bansal K*."
   venue: "Brain Communications"
   pdf: "/assets/papers/Nuttida_2022.pdf"
   bib: "/assets/bibs/Nuttida_2022.txt"
@@ -102,7 +100,7 @@
   venue: "bioRxiv: 10.1101/420430v1, 2018"
   pdf: "/assets/papers/Nelli_2018.pdf"
   bib: "/assets/bibs/Nelli_2018.txt"
-  doi: ""
+  doi: "https://doi.org/10.1101/420430 "
 
 - year: 2018
   title: "Expectations do not alter early sensory processing during perceptual decision-making"

_site/404.html

@@ -6,21 +6,21 @@
 
   <title></title>
   <link rel="shortcut icon" type="image/x-icon" href="//favicon.ico" ><!-- Begin Jekyll SEO tag v2.8.0 -->
-<title>Rudramani Singha | Hey there! I’m a researcher based in New York City. I build probabilistic models and reverse engineer the brain.</title>
+<title>NuttidaLab | We develop experimental and computational frameworks to investigate the neural computations that underlie complex cognitive functions in health and disease.</title>
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-<meta property="og:title" content="Rudramani Singha" />
-<meta name="author" content="Rudramani Singha" />
+<meta property="og:title" content="NuttidaLab" />
+<meta name="author" content="NuttidaLab" />
 <meta property="og:locale" content="en_US" />
-<meta name="description" content="Hey there! I’m a researcher based in New York City. I build probabilistic models and reverse engineer the brain." />
-<meta property="og:description" content="Hey there! I’m a researcher based in New York City. I build probabilistic models and reverse engineer the brain." />
+<meta name="description" content="We develop experimental and computational frameworks to investigate the neural computations that underlie complex cognitive functions in health and disease." />
+<meta property="og:description" content="We develop experimental and computational frameworks to investigate the neural computations that underlie complex cognitive functions in health and disease." />
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_site/assets/bibs/Katlowitz_2025.txt

@@ -0,0 +1,12 @@
+@article {Katlowitz2025.04.09.648012,
+	author = {Katlowitz, Kalman A. and Shah, Shraddha and Franch, Melissa C. and Adkinson, Joshua and Belanger, James L. and Mathura, Raissa K. and Mesz{\'e}na, Domokos and Mickiewicz, Elizabeth A. and McGinley, Matthew and Mu{\~n}oz, William and Banks, Garrett P. and Cash, Sydney S. and Hsu, Chih-Wei and Paulk, Angelique C. and Provenza, Nicole R. and Watrous, Andrew and Williams, Ziv and Heilbronner, Sarah R. and Kim, Robert and Rungratsameetaweemana, Nuttida and Hayden, Benjamin Y. and Sheth, Sameer A.},
+	title = {Learning and language in the unconscious human hippocampus},
+	elocation-id = {2025.04.09.648012},
+	year = {2025},
+	doi = {10.1101/2025.04.09.648012},
+	publisher = {Cold Spring Harbor Laboratory},
+	abstract = {Consciousness is a fundamental component of cognition,1 but the degree to which higher-order perception relies on it remains disputed.2,3 Here we demonstrate the persistence of learning, semantic processing, and online prediction in individuals under general anesthesia-induced loss of consciousness.4,5 Using high-density Neuropixels microelectrodes6 to record neural activity in the human hippocampus while playing a series of tones to anesthetized patients, we found that hippocampal neurons could reliably detect oddball tones. This effect size grew over the course of the experiment (\~{}10 minutes), consistent with learning effects. A biologically plausible recurrent neural network model showed that learning and oddball representation are an emergent property of flexible tone discrimination. Last, when we played language stimuli, single units and ensembles carried information about the semantic and grammatical features of natural speech, even predicting semantic information about upcoming words. Together these results indicate that in the hippocampus, which is anatomically and functionally distant from primary sensory cortices,7 complex processing of sensory stimuli occurs even in the unconscious state.Competing Interest StatementThe authors have declared no competing interest.},
+	URL = {https://www.biorxiv.org/content/early/2025/04/09/2025.04.09.648012},
+	eprint = {https://www.biorxiv.org/content/early/2025/04/09/2025.04.09.648012.full.pdf},
+	journal = {bioRxiv}
+}

_site/assets/bibs/Nett_2025.txt

@@ -0,0 +1,12 @@
+@article {Nett2025.01.17.633375,
+	author = {Nett, Laura and Guth, Tim A. and B{\"u}chel, Philipp K. and Rungratsameetaweemana, Nuttida and Kunz, Lukas},
+	title = {Behavioral investigation of allocentric and egocentric cognitive maps in human spatial memory},
+	elocation-id = {2025.01.17.633375},
+	year = {2025},
+	doi = {10.1101/2025.01.17.633375},
+	publisher = {Cold Spring Harbor Laboratory},
+	abstract = {Spatial memory is a fundamental cognitive function that enables humans and other species to encode and recall the locations of items in their environments. Humans employ diverse strategies to support spatial memory, including the use of cognitive maps. Cognitive maps are mental representations of the environment that organize its content along two or more continuous dimensions. In allocentric cognitive maps, these dimensions form a Cartesian coordinate system referenced to the environment. In egocentric cognitive maps, the dimensions form a polar coordinate system centered on the subject. To better understand how humans employ allocentric and egocentric cognitive maps for spatial memory, we performed a behavioral study with a novel task designed to directly and explicitly assess both types of cognitive maps. During encoding periods, participants navigated through a virtual environment and encountered objects at different locations. During recall periods, participants aimed at remembering these locations in abstract allocentric and egocentric coordinate systems. Our results show that relationships between the objects and the environment, such as their distance to boundaries and corners, were associated with allocentric memory performance. Relationships between the objects and the participant, including their distance and orientation to the participant{\textquoteright}s starting position, were linked to egocentric memory performance. Spatial feedback during recall supported performance within allocentric and egocentric domains, but not across domains. These findings are compatible with the notion that allocentric and egocentric cognitive maps operate as (partially) independent systems for spatial memory, each specialized in processing specific types of spatial relationships.Competing Interest StatementThe authors have declared no competing interest.},
+	URL = {https://www.biorxiv.org/content/early/2025/01/17/2025.01.17.633375},
+	eprint = {https://www.biorxiv.org/content/early/2025/01/17/2025.01.17.633375.full.pdf},
+	journal = {bioRxiv}
+}

_site/assets/papers/Katlowitz_2025.pdf

@@ -1,4 +1,4 @@
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+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.3.4">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2025-05-01T00:13:09-04:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">NuttidaLab</title><subtitle>We develop experimental and computational frameworks to investigate the neural computations that underlie complex cognitive functions in health and disease.</subtitle><author><name>NuttidaLab</name></author><entry><title type="html">Hypothesis Testing vs Bayesian Modeling</title><link href="http://localhost:4000/posts/hypothesis/" rel="alternate" type="text/html" title="Hypothesis Testing vs Bayesian Modeling" /><published>2025-03-12T21:27:20-04:00</published><updated>2025-03-12T21:27:20-04:00</updated><id>http://localhost:4000/posts/hypothesis</id><content type="html" xml:base="http://localhost:4000/posts/hypothesis/"><![CDATA[<h2 id="hypothesis-testing">Hypothesis Testing</h2>
 <p>Hypothesis testing is a statistical method used to make inferences about a population based on a sample. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), and then using statistical tests to determine whether to reject or fail to reject the null hypothesis.</p>
 
 \[H_0: \mu = \mu_0 \\
@@ -53,7 +53,7 @@ y \sim P(y|\theta) \\
 <ul>
   <li>\(\theta\) is the parameter of interest</li>
   <li>\(y\) is the observed data</li>
-</ul>]]></content><author><name>Rudramani Singha</name></author><summary type="html"><![CDATA[Hypothesis Testing Hypothesis testing is a statistical method used to make inferences about a population based on a sample. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), and then using statistical tests to determine whether to reject or fail to reject the null hypothesis.]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://localhost:4000/assets/images/posts/hangouts/6flags.jpeg" /><media:content medium="image" url="http://localhost:4000/assets/images/posts/hangouts/6flags.jpeg" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Announcement only</title><link href="http://localhost:4000/posts/only-announce/" rel="alternate" type="text/html" title="Announcement only" /><published>2024-08-12T21:27:20-04:00</published><updated>2024-08-12T21:27:20-04:00</updated><id>http://localhost:4000/posts/only-announce</id><content type="html" xml:base="http://localhost:4000/posts/only-announce/"><![CDATA[<h1 id="hypothesis-testing-vs-bayesian-modeling">Hypothesis Testing vs Bayesian Modeling</h1>
+</ul>]]></content><author><name>NuttidaLab</name></author><summary type="html"><![CDATA[Hypothesis Testing Hypothesis testing is a statistical method used to make inferences about a population based on a sample. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), and then using statistical tests to determine whether to reject or fail to reject the null hypothesis.]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://localhost:4000/assets/images/posts/hangouts/6flags.jpeg" /><media:content medium="image" url="http://localhost:4000/assets/images/posts/hangouts/6flags.jpeg" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Announcement only</title><link href="http://localhost:4000/posts/only-announce/" rel="alternate" type="text/html" title="Announcement only" /><published>2024-08-12T21:27:20-04:00</published><updated>2024-08-12T21:27:20-04:00</updated><id>http://localhost:4000/posts/only-announce</id><content type="html" xml:base="http://localhost:4000/posts/only-announce/"><![CDATA[<h1 id="hypothesis-testing-vs-bayesian-modeling">Hypothesis Testing vs Bayesian Modeling</h1>
 
 <h2 id="hypothesis-testing">Hypothesis Testing</h2>
 <p>Hypothesis testing is a statistical method used to make inferences about a population based on a sample. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), and then using statistical tests to determine whether to reject or fail to reject the null hypothesis.</p>
@@ -110,4 +110,4 @@ y \sim P(y|\theta) \\
 <ul>
   <li>\(\theta\) is the parameter of interest</li>
   <li>\(y\) is the observed data</li>
-</ul>]]></content><author><name>Rudramani Singha</name></author><summary type="html"><![CDATA[Hypothesis Testing vs Bayesian Modeling]]></summary></entry><entry><title type="html">Hangout with Herbert Wu Lab</title><link href="http://localhost:4000/posts/herbert-wu-lab/" rel="alternate" type="text/html" title="Hangout with Herbert Wu Lab" /><published>2023-05-06T13:00:00-04:00</published><updated>2023-05-06T13:00:00-04:00</updated><id>http://localhost:4000/posts/herbert-wu-lab</id><content type="html" xml:base="http://localhost:4000/posts/herbert-wu-lab/"><![CDATA[]]></content><author><name>Rudramani Singha</name></author><summary type="html"><![CDATA[]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://localhost:4000/assets/images/posts/lab_outing/lab_outing.jpg" /><media:content medium="image" url="http://localhost:4000/assets/images/posts/lab_outing/lab_outing.jpg" xmlns:media="http://search.yahoo.com/mrss/" /></entry></feed>
+</ul>]]></content><author><name>NuttidaLab</name></author><summary type="html"><![CDATA[Hypothesis Testing vs Bayesian Modeling]]></summary></entry><entry><title type="html">Hangout with Herbert Wu Lab</title><link href="http://localhost:4000/posts/herbert-wu-lab/" rel="alternate" type="text/html" title="Hangout with Herbert Wu Lab" /><published>2023-05-06T13:00:00-04:00</published><updated>2023-05-06T13:00:00-04:00</updated><id>http://localhost:4000/posts/herbert-wu-lab</id><content type="html" xml:base="http://localhost:4000/posts/herbert-wu-lab/"><![CDATA[]]></content><author><name>NuttidaLab</name></author><summary type="html"><![CDATA[]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://localhost:4000/assets/images/posts/lab_outing/lab_outing.jpg" /><media:content medium="image" url="http://localhost:4000/assets/images/posts/lab_outing/lab_outing.jpg" xmlns:media="http://search.yahoo.com/mrss/" /></entry></feed>

_site/assets/papers/Nett_2025.pdf

@@ -6,21 +6,21 @@
 
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+<title>Gallery | NuttidaLab</title>
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