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  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>International Journal of Global Mental Health, Innovation, Policy, Action, Culture &amp; Transformation</journal-title>
        <abbrev-journal-title abbrev-type="publisher">IMPACT</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">3107-8311</issn>
      <publisher>
        <publisher-name>Dr. Aashna Narula</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.61113/impact.V2I1.1239</article-id>
      <article-id pub-id-type="publisher-id">impact-00001219</article-id>
      <title-group>
        <article-title>The Cognitive Cost of Artificial Intelligence: A Neurocognitive Review</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Gumber</surname>
            <given-names>Namika</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date pub-type="epub" iso-8601-date="2026">
        <year>2026</year>
      </pub-date>
      <volume>2</volume>
      <issue>1</issue>
      <abstract>
        <p>
Artificial Intelligence was originally conceived as a tool for human ease, intended to enhance productivity and streamline complex tasks. However, recent trends suggest a shift from augmentation to a total &quot;cognitive offloading,&quot; where humans increasingly outsource critical thinking and memory to AI. This review paper explores the hypothesis that this dependency is contributing to a reversal of the Flynn Effect. After reviewing neuroimaging data from fMRI and EEG studies, the paper identifies significant alterations in neuroplasticity and neural activity. A primary concern is the observed decline in hippocampal volume among individuals who over-rely on AI for routine and complex cognitive tasks. Because the brain follows a &quot;use it or lose it&quot; paradigm, bypassing &quot;desirable difficulties&quot; during information processing leads to a lack of deep memory encoding and weakened retention skills. This phenomenon, often termed &quot;Digital Amnesia,&quot; suggests that our neural architecture is physically adapting to a state of passive retrieval rather than active synthesis. The paper concludes that while AI offers immense efficiency, we must develop a balanced Human-AI interaction model. By treating AI as a collaborative partner rather than a cognitive substitute, we can leverage technological speed while preserving the biological integrity and intellectual capacity of the human brain.</p>
      </abstract>
    </article-meta>
  </front>
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