Advancing neural computation: experimental validation and optimization of dendritic learning in feedforward tree networks DOI
Seyed‐Ali Sadegh‐Zadeh,

Pooya Hazegh

American Journal of Neurodegenerative Disease, Journal Year: 2024, Volume and Issue: 13(5), P. 49 - 69

Published: Jan. 1, 2024

This study aims to explore the capabilities of dendritic learning within feedforward tree networks (FFTN) in comparison traditional synaptic plasticity models, particularly context digit recognition tasks using MNIST dataset. We employed FFTNs with nonlinear segment amplification and Hebbian rules enhance computational efficiency. The dataset, consisting 70,000 images handwritten digits, was used for training testing. Key performance metrics, including accuracy, precision, recall, F1-score, were analysed. models significantly outperformed plasticity-based across all metrics. Specifically, framework achieved a test accuracy 91%, compared 88% demonstrating superior classification. Dendritic offers more powerful by closely mimicking biological neural processes, providing enhanced efficiency scalability. These findings have important implications advancing both artificial intelligence systems neuroscience.

Language: Английский

Priors, Evidence, and Memory: Dynamics of Predictive Processing in a Hierarchical Visual System DOI
Lars Muckli

Neuroscience & Biobehavioral Reviews, Journal Year: 2025, Volume and Issue: unknown, P. 106134 - 106134

Published: April 1, 2025

Language: Английский

Citations

1
Unpacking the Complexities of Consciousness: Theories and Reflections DOI Creative Commons
Liad Mudrik, Mélanie Boly,

Stanislas Dehaene

et al.

Neuroscience & Biobehavioral Reviews, Journal Year: 2025, Volume and Issue: unknown, P. 106053 - 106053

Published: Feb. 1, 2025

As the field of consciousness science matures, research agenda has expanded from an initial focus on neural correlates consciousness, to developing and testing theories consciousness. Several have been put forward, each aiming elucidate relationship between brain function. However, there is ongoing, intense debate regarding whether these examine same phenomenon. And, despite ongoing efforts, it seems like so far failed converge around any single theory, instead exhibits significant polarization. To advance this discussion, proponents five prominent consciousness-Global Neuronal Workspace Theory (GNWT), Higher-Order Theories (HOT), Integrated Information (IIT), Recurrent Processing (RPT), Predictive (PP)-engaged in a public 2022, as part annual meeting Association for Scientific Study Consciousness (ASSC). They were invited clarify explananda their theories, articulate core mechanisms underpinning corresponding explanations, outline foundational premises. This was followed by open discussion that delved into testability potential evidence could refute them, areas consensus disagreement. Most importantly, demonstrated at stage, more controversy than agreement pertaining most basic questions what is, how identify conscious states, required theory Addressing crucial advancing towards deeper understanding comparison competing theories.

Language: Английский

Citations

0
Context‐Sensitive Conscious Interpretation and Layer‐5 Pyramidal Neurons in Multistable Perception DOI Creative Commons
Talis Bachmann

Brain and Behavior, Journal Year: 2025, Volume and Issue: 15(3)

Published: March 1, 2025

There appears to be a fundamental difference between the two ways of how an object becomes perceptually experienced. One occurs when preconscious object-specifying sensory data processing crosses certain threshold so that constituents depiction become consciously The other already experienced features interpreted as belonging visual category. Surprisingly, experimental facts about neural markers conscious access gathered far do not allow us distinguish mechanisms responsible for these varieties. A cortical multicompartment layer-5 pyramidal neuron-based generic model is presented in order conceptualize possible mechanistic solution explanatory cul-de-sac. To support argument, review pertinent research compiled associated with from studies where physically invariant perceptual stimuli have underwent alternative interpretation(s) by brain. Recent developments newly emerging field cellular psycho(physio)logy are introduced, offering hypothetical distinguishing subserving content experience and interpretation. single cell-based approach brain process correlates perception added value beyond traditional inter-areal connectivity-based theoretical stances.

Language: Английский

Citations

0
Advancing neural computation: experimental validation and optimization of dendritic learning in feedforward tree networks DOI
Seyed‐Ali Sadegh‐Zadeh,

Pooya Hazegh

American Journal of Neurodegenerative Disease, Journal Year: 2024, Volume and Issue: 13(5), P. 49 - 69

Published: Jan. 1, 2024

This study aims to explore the capabilities of dendritic learning within feedforward tree networks (FFTN) in comparison traditional synaptic plasticity models, particularly context digit recognition tasks using MNIST dataset. We employed FFTNs with nonlinear segment amplification and Hebbian rules enhance computational efficiency. The dataset, consisting 70,000 images handwritten digits, was used for training testing. Key performance metrics, including accuracy, precision, recall, F1-score, were analysed. models significantly outperformed plasticity-based across all metrics. Specifically, framework achieved a test accuracy 91%, compared 88% demonstrating superior classification. Dendritic offers more powerful by closely mimicking biological neural processes, providing enhanced efficiency scalability. These findings have important implications advancing both artificial intelligence systems neuroscience.

Language: Английский

Citations

0