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	<title>metabolic constraints &#8211; BIOENGINEER.ORG</title>
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		<title>Hebbian Learning Shows How Brains Could Spend Their Synaptic Budget Wisely</title>
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		<pubDate>Fri, 16 Oct 2026 18:37:18 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Technology]]></category>
		<category><![CDATA[audiovisual learning]]></category>
		<category><![CDATA[Computational neuroscience]]></category>
		<category><![CDATA[Dale's law]]></category>
		<category><![CDATA[Hebbian learning]]></category>
		<category><![CDATA[information bottleneck]]></category>
		<category><![CDATA[metabolic constraints]]></category>
		<category><![CDATA[neural efficiency]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Oja's rule]]></category>
		<category><![CDATA[representational cost]]></category>
		<category><![CDATA[sparsity]]></category>
		<category><![CDATA[synaptic plasticity]]></category>
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					<description><![CDATA[A new computational study shows that a constrained Hebbian learning rule achieves lower representational cost than backpropagation and target propagation under biologically motivated sparsity constraints, reframing local plasticity as a mechanism for efficient synaptic resource allocation.]]></description>
		
		
		
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