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        Saira Jameela Hübenette
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        Doctoral Research Fellow
          -
        <a href="https://www.sv.uio.no/psi/english?vrtx=unit-view&amp;areacode=170595">RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion (PSI)</a>
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                  <span class="vrtx-address-line">澳门皇冠体育,皇冠足球比分sv. 3A</span>
                
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              <h2>Academic interests</h2><p>I am interested in understanding the neural basis of temporal prediction of time and space, and how we process sounds in motion. I also study?patients with prefrontal lesions; are they impaired in generating predictions of sounds in motion, and do they struggle with creating cognitive maps of task space (which I also investigate through sounds in motion), compared with healthy controls.?I?use scalp EEG and eyetracking in combination with auditory cognitive tasks.</p><h2>Teaching</h2><h4><i>Spring 2026</i></h4><p>- PSYC2230 Kognitiv Nevrovitenskap<br/>- Seminars PSY4340 Internship</p><h4><i>Seminar leader autumn 2025</i></h4><p>- PSYC2230 Kognitiv Nevrovitenskap<br/>- PSY1050?Psykologi: Teori og praksis</p><h2>Background</h2><p><i>Education</i></p><p>2012-2015 BSc Psychology, University of Essex</p><p>2015-2016 MSc Advanced Psychology, University of Essex</p><p>2018-2020 Master in Cognitive Neuroscience, University of Oslo</p><p>?</p>
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      <h2>Publications</h2>



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            <li><a href="#vrtx-publication-tab-1" name="vrtx-publication-tab-1">Scientific articles and book chapters</a></li>
            <li><a href="#vrtx-publication-tab-2" name="vrtx-publication-tab-2">Other</a></li>
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    <div id="vrtx-publication-tab-1">
  <ul class="vrtx-external-publications">

      <li id="vrtx-external-publication-10315582" class="vrtx-external-publication">
        <div id="vrtx-publication-10315582">
            <span class="vrtx-contributors" id="vrtx-publication-contributors-10315582">
                Hope, Sigrun; Lin, Aihua; R?devand, Linn; Hübenette, Saira Jameela; Quintana, Daniel &amp; S?nderby, Ida Elken
                    <a href="javascript:void(0);" title="Get all contributors" onclick="addContributor('https://api.cristin.no/v2/nvaresults/10315582/contributors', 'vrtx-publication-contributors-10315582')">
                    [Show all&nbsp;17&nbsp;contributors for this article]</a>
            </span>(2025).
                <span class="vrtx-title title-articlesAndBookChapters">
                    <!-- For readability. Too many underlined characters when both present -->
                        Shared genetic architecture between autism spectrum disorder, loneliness, and social isolation reveals novel genetic loci.
                </span>
                <span class="vrtx-publisher publisher-articlesAndBookChapters publisher-category-ARTICLE">
                        Psychiatric Genetics.
                </span>
                <span class="vrtx-issn">ISSN 0955-8829.</span>
                            
            doi: <a href="https://doi.org/10.1097/ypg.0000000000000406">10.1097/ypg.0000000000000406</a>.
            <a href="https://hdl.handle.net/11250/5343718">Full text in Research Archive</a>
                <span class="vrtx-publication-summary">
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                            <p class="vrtx-publication-summary" style="display:none">Objective: Deficits in social communication and social interaction are core features of autism spectrum disorder (ASD), and studies suggest that loneliness and social isolation are common. ASD has a strong genetic basis, but the genetic architecture and overlap with social phenotypes are not clear. 
Methods: We analyzed summary statistics from genome-wide association studies on ASD (46 350), loneliness (452 302), and social isolation (288 950), using linkage disequilibrium score regression, local analysis of covariant annotation (LAVA), bivariate causal mixture model (MiXeR), and the conditional/conjunctional false discovery rate (cond/conjFDR). 
Results: For ASD and social isolation, we found nonsignificant global genetic correlation ( r g = 0.02, P ?=?0.8), but LAVA identified 72 genomic regions with bidirectional correlations, and MiXeR estimated that 8.7 k of 13.1 k variants (81%) were shared, of which 53% had concordant effect directions. For ASD and loneliness, we found a positive genetic correlation ( r g = 0.26, P ?=?2e-10), LAVA identified 80 genomic regions with bidirectional genetic correlations, and MiXeR suggested that at least 3.8 k variants were shared. We identified nine specific shared genetic loci between ASD and loneliness and eight between ASD and social isolation (conjFDR?&lt;?0.05). Of these, 12 loci were novel for ASD. Genes mapped to these loci are involved in γ-aminobutyric acid (GABA), glutamate, calcium, and stress hormone signaling, cerebral glucose transport, TAU-accumulation, and immune function. 
Conclusion: We found extensive overlap in genetic architecture between ASD, loneliness, and social isolation, with bidirectional effects. By leveraging data for ASD and social traits, we identified 12 novel ASD related genetic loci implicating several genes, thereby elucidating potential pathways underlying their shared genetic architecture.</p>
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      <li id="vrtx-external-publication-2178576" class="vrtx-external-publication">
        <div id="vrtx-publication-2178576">
            <span class="vrtx-contributors" id="vrtx-publication-contributors-2178576">
                Hope, Sigrun; Shadrin, Alexey; Lin, Aihua; Bahrami, Shahram; R?devand, Linn &amp; Frei, Oleksandr
                    <a href="javascript:void(0);" title="Get all contributors" onclick="addContributor('https://api.cristin.no/v2/nvaresults/2178576/contributors', 'vrtx-publication-contributors-2178576')">
                    [Show all&nbsp;17&nbsp;contributors for this article]</a>
            </span>(2023).
                <span class="vrtx-title title-articlesAndBookChapters">
                    <!-- For readability. Too many underlined characters when both present -->
                        Bidirectional genetic overlap between autism spectrum disorder and cognitive traits.
                </span>
                <span class="vrtx-publisher publisher-articlesAndBookChapters publisher-category-ARTICLE">
                        Translational Psychiatry.
                </span>
                            13(1),
                <span class="vrtx-pages">p. 1–9.</span>
            doi: <a href="https://doi.org/10.1038/s41398-023-02563-7">10.1038/s41398-023-02563-7</a>.
            <a href="https://hdl.handle.net/11250/3097822">Full text in Research Archive</a>
                <span class="vrtx-publication-summary">
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                            <p class="vrtx-publication-summary" style="display:none">Autism spectrum disorder (ASD) is a highly heritable condition with a large variation in cognitive function. Here we investigated the shared genetic architecture between cognitive traits (intelligence (INT) and educational attainment (EDU)), and risk loci jointly associated with ASD and the cognitive traits. We analyzed data from genome-wide association studies (GWAS) of INT (n?=?269,867), EDU (n?=?766,345) and ASD (cases n?=?18,381, controls n?=?27,969). We used the bivariate causal mixture model (MiXeR) to estimate the total number of shared genetic variants, local analysis of co-variant annotation (LAVA) to estimate local genetic correlations, conditional false discovery rate (cond/conjFDR) to identify specific overlapping loci. The MiXeR analyses showed that 12.7k genetic variants are associated with ASD, of which 12.0k variants are shared with EDU, and 11.1k are shared with INT with both positive and negative relationships within overlapping variants. The majority (59–68%) of estimated shared loci have concordant effect directions, with a positive, albeit modest, genetic correlation between ASD and EDU (rg?=?0.21, p?=?2e?13) and INT (rg?=?0.22, p?=?4e?12). We discovered 43 loci jointly associated with ASD and cognitive traits (conjFDR&lt;0.05), of which 27 were novel for ASD. Functional analysis revealed significant differential expression of candidate genes in the cerebellum and frontal cortex. To conclude, we quantified the genetic architecture shared between ASD and cognitive traits, demonstrated mixed effect directions, and identified the associated genetic loci and molecular pathways. The findings suggest that common genetic risk factors for ASD can underlie both better and worse cognitive functioning across the ASD spectrum, with different underlying biology.</p>
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      <p class="vrtx-more-external-publications"><a href="https://nva.sikt.no/research-profile/1285029">View all works in NVA</a></p>
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      <li id="vrtx-external-publication-10253718" class="vrtx-external-publication">
        <div id="vrtx-publication-10253718">
            <span class="vrtx-contributors" id="vrtx-publication-contributors-10253718">
                Hübenette, Saira Jameela
            </span>(2025).
                <span class="vrtx-title title-other">
                    <!-- For readability. Too many underlined characters when both present -->
                        Spatial and temporal processing of auditory stimuli.
                </span>
                            
            
            <a href="https://hdl.handle.net/11250/4435443">Full text in Research Archive</a>
                <span class="vrtx-publication-summary">
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                            <p class="vrtx-publication-summary" style="display:none">Tracking a moving sound in space requires continuous prediction of its next location. This implies that we must combine information about the time and location of the sound, to accurately predict its trajectory. Using EEG, auditory motion processing has previously been found in frontal, central, and parietal areas of the brain.
Prior studies have suggested that space and time for auditory stimuli are processed separately in the brain. Despite the seemingly distinct processing pathways of spatial and temporal sound information, they must integrate at some stage to enable the prediction of movement. It remains unknown if these processes are initially working in parallel and then converging at some point, or if there are several instances of convergence throughout.
The goal of this study is to delineate the neural correlates of spatial and temporal processing of moving sounds, and to assess how and when they converge to aid in the tracking of the sound movement.
</p>
                </span>
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    </li>
      <li id="vrtx-external-publication-10253599" class="vrtx-external-publication">
        <div id="vrtx-publication-10253599">
            <span class="vrtx-contributors" id="vrtx-publication-contributors-10253599">
                Hübenette, Saira Jameela; Solbakk, Anne-Kristin; Danielsen, Anne; Endestad, Tor &amp; Blenkmann, Alejandro Omar
            </span>(2025).
                <span class="vrtx-title title-other">
                    <!-- For readability. Too many underlined characters when both present -->
                        Hearing in motion: Spatial and temporal processing of auditory stimuli.
                </span>
                            
            doi: <a href="https://doi.org/https:/www.dropbox.com/scl/fi/ijya3kj1w1dl2e7vyjo5y/ICAC25-poster.pdf?rlkey=2516eohjz9vyx3g7qj7rjsedc&amp;st=wm335i35&amp;dl=0">https:/www.dropbox.com/scl/fi/ijya3kj1w1dl2e7vyjo5y/ICAC25-poster.pdf?rlkey=2516eohjz9vyx3g7qj7rjsedc&amp;st=wm335i35&amp;dl=0</a>.
            <a href="https://hdl.handle.net/11250/4600761">Full text in Research Archive</a>
                <span class="vrtx-publication-summary">
                            <a href="#" aria-expanded="false" aria-label="Show summary" class="vrtx-publication-summary">Show summary</a>
                            <p class="vrtx-publication-summary" style="display:none">Tracking a moving sound in space requires continuous prediction of its next location. This implies that we must combine information about the time and location of the sound, to accurately predict its trajectory. Using EEG, auditory motion processing has previously been found in frontal, central, and parietal areas of the brain. Prior studies have suggested that space and time for auditory stimuli are processed separately in the brain. Despite the seemingly distinct processing pathways of spatial and temporal sound information, they must integrate at some stage to enable the prediction of movement. It remains unknown if these processes are initially working in parallel and then converging at some point, or if there are several instances of convergence throughout.
The goal of this study was to delineate the neural correlates of spatial and temporal processing of moving sounds, and to assess how and when they converge to aid in the tracking of the sound movement.</p>
                </span>
        </div>
    </li>
      <li id="vrtx-external-publication-2345935" class="vrtx-external-publication">
        <div id="vrtx-publication-2345935">
            <span class="vrtx-contributors" id="vrtx-publication-contributors-2345935">
                Pieschnik, Sophia; Golla, Archana; Reiten, Ingrid; Schlegel, Ulrike; Hennestad, Eivind &amp; Hübenette, Saira Jameela
                    <a href="javascript:void(0);" title="Get all contributors" onclick="addContributor('https://api.cristin.no/v2/nvaresults/2345935/contributors', 'vrtx-publication-contributors-2345935')">
                    [Show all&nbsp;20&nbsp;contributors for this article]</a>
            </span>(2023).
                <span class="vrtx-title title-other">
                    <!-- For readability. Too many underlined characters when both present -->
                        Pioneering open neuroscience - the role of the curation services.
                </span>
                            
            
            <a href="https://hdl.handle.net/11250/4911892">Full text in Research Archive</a>
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      <p class="vrtx-more-external-publications"><a href="https://nva.sikt.no/research-profile/1285029">View all works in NVA</a></p>
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