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The computational power of the human brain
1Institute of Psychopharmacology, Central Institute of Mental Health, Faculty of Medicine, University of Heidelberg, Mannheim, Germany.
Frontiers in Cellular Neuroscience
|August 23, 2023
Summary
The brain utilizes both analog and digital processes for computation, challenging the purely digital Turing machine model. This complex interplay, involving neurons, astrocytes, and epigenetic factors, underlies memory and advanced cognitive functions.
Area of Science:
- Computational Neuroscience
- Neurobiology
- Artificial Intelligence
Background:
- The 20th century saw digital systems largely replace analog ones in computing due to superior power.
- The brain's computational nature, whether analog or digital, remains a key question, with initial theories favoring digital models akin to Turing machines.
- Recent AI advancements integrate both digital and analog processes, prompting a re-evaluation of biological computation.
Purpose of the Study:
- To compare mathematical models of computation with the biological reality of brain computation.
- To highlight the presence and significance of both digital and analog processes within the Central Nervous System.
- To differentiate computational principles between artificial (in silico) and biological systems.
Main Methods:
- Identification and analysis of digital and analog processes in cellular and molecular interactions within the Central Nervous System.
- Examination of electrical synapses and gap junctions for analog information processing in neurons and astrocytes.
- Analysis of neuronal action potentials (spikes), synaptic transmission (including tripartite synapses), and synaptic plasticity (LTP/LTD) for computational characteristics.
- Inclusion of memory storage mechanisms (e.g., oscillations, engrams, astrocytic syncytium) and epigenetic influences.
Main Results:
- Analog processing occurs in electrical synapses and gap junctions, while neuronal action potentials (spikes) represent digital events.
- Spike variability in amplitude and width influences transmitter release, and synaptic transmission is modulated by astrocytes (tripartite synapse).
- Memory formation involves synaptic plasticity (LTP/LTD), epigenetic factors, gene transcription/translation, and diverse storage mechanisms.
Conclusions:
- Brain computation is not exclusively analog or digital but a complex combination of both, operating in parallel.
- Biological computation exhibits higher orders of complexity than current artificial systems.
- Understanding brain computation requires considering intricate interactions at molecular, cellular, and network levels.
Keywords:
analog-digital computationartificial and biological intelligencebifurcationscellular computationengramslearning and memorymolecular computationnetwork oscillationsMore Related Videos
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