Please provide some insight into how human neural networks learn and memorize tasks

Human neural networks learn and memorize tasks by changing the strength and wiring of connections between neurons (synaptic plasticity), and by routing different kinds of tasks into somewhat different memory systems.brainfacts+2

Core mechanism: synaptic change

When you learn, patterns of activity across neurons lead to durable changes at synapses, the junctions where neurons communicate. Some connections become stronger (long-term potentiation, LTP) and others weaker (long-term depression, LTD), which gradually shapes circuits that can reliably reproduce a learned response when triggered. This “synaptic plasticity and memory” hypothesis holds that such activity-dependent synaptic changes are both necessary and sufficient to store many types of memories in the circuits where they are observed.pmc.ncbi.nlm.nih+2

From short-term to consolidated memory

New experiences are initially encoded in rapidly changing circuits, especially in the hippocampus and related medial temporal lobe structures. Over time, especially during sleep and quiet wakeful rest, coordinated “replay” of recent activity helps consolidate these traces into more distributed cortical networks for longer-term storage. This consolidation appears to occur in multiple steps: hippocampal plasticity for context-specific encoding, followed by cortical plasticity (for example in anterior cingulate cortex) during subsequent sleep that stabilizes the memory.science+2

Different systems for different tasks

The brain uses at least two major long-term memory systems that support different ways of learning tasks.pmc.ncbi.nlm.nih+2

• Declarative memory (facts, events, “knowing that”) relies heavily on hippocampus and medial temporal lobe; it supports rapid, often one-shot learning that you can consciously recall and describe.pmc.ncbi.nlm.nih+1

• Procedural memory (skills, habits, “knowing how”) depends more on basal ganglia, cerebellum, and motor-related cortex, and is learned gradually through practice, becoming automatic and less accessible to verbal report.pmc.ncbi.nlm.nih+2

Skill learning and practice

When learning a new motor or cognitive skill, the brain explores many possible patterns of neural activity and gradually stabilizes the ones that lead to successful performance. Neurons in motor and associative areas refine their connectivity so that the correct sequence of activations reliably produces the desired output (for example, a tennis stroke or a typing pattern), while still preserving older skills by balancing plasticity with stability and noise in the circuits. Brief rest periods between practice bouts allow rapid replay of the just-performed task, and more frequent replay predicts greater gains on the next attempt, suggesting rest helps bind and strengthen the skill memory.nih+2

Network-level coordination

Learning does not happen at isolated synapses but across interacting networks involving sensory, motor, associative, and modulatory systems. Neuromodulators such as dopamine, acetylcholine, and others gate plasticity, tying synaptic change to reward, novelty, or attention so that only some patterns of activity are consolidated into long-term memory. Over days to years, additional structural changes such as growth and pruning of dendritic spines and alterations in myelination help fine-tune timing and connectivity, further stabilizing well-practiced tasks and making their execution faster and more reliable.qbi.uq.edu+4