The organization of behavior: A neuropsychological theory

By J. Knott. 1951

Subfields: Neuroscience, Cognitive Science & Psychology

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Citations in the corpus

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation (2016, positive): “Instead we propose a more biologically plausible mechanism: Hebb-like learning [21] at the level of simple cells (see Equation (2)).”
Critical Learning Periods in Deep Neural Networks (2017, background): “They are thus more relevant to the network, since it has to pay a price in order to maintain them, and can be compared to strengthened synaptic connections in biological system (36).”
The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “More than half a century ago, Donald Hebb [1] laid down an enticing framework for the neurobiological basis of learning, which can be succinctly summarized in the well-known mantra, “neurons that fire together wire together” [2].”
Neural plasticity across the lifespan (2016, background): “Perhaps the most famous form of plasticity is Hebbian plasticity, so named because it was the cornerstone of Donald Hebb’s theory of cognition and learning developed in the 1940s.(2) Hebb proposed that organized activity within a brain circuit could be sustained, and, importantly, re-implemented in ”
Active Long Term Memory Networks (2016, background): “In humans the dyadic interaction between Hippocampus and Neocortex [2] is thought to mitigate the problem of CI by carefully balancing the sensitivity-stability [20] trade-off such that new experiences can be integrated without exposing the system to risk of abrupt phase transitions.”
Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks (2017, background): “In contrast, learning algorithms such as Hebbian learning [42], neuromodulation [43], and backpropagation [10–12] enable ANNs to continuously learn during their lifetime.”
About sleep's role in memory. (2013, background): “Encoding induces synaptic long-term potentiation (LTP) or long-term depression (LTD) as major forms of learning-induced synaptic plasticity (222, 527, 616, 629, 1209).”
Differentiable plasticity: training plastic neural networks with backpropagation (2018, background): “While multiple forms of synaptic plasticity exist, many of them follow the general principle known as Hebb’s rule: if a neuron repeatedly takes part in making another neuron fire, the connection between them is strengthened (often roughly summarized as “neurons that fire together, wire together”) (H”
A metaplasticity view of the interaction between homeostatic and Hebbian plasticity (2017, background): “Proposed by Donald Hebb in the 1940s, Hebb’s rule is pithily summarized by the now well-worn mantra, ‘neurons that fire together, wire together’ [1].”
Merging chrominance and luminance in early, medium, and late fusion using Convolutional Neural Networks (2015, background): “After the second World War, in 1949, Donald Olding Hebb17 inspired by Ramón 1949 y Cajal and Lashley18 published the book “The Organization of Behavior” [Hebb, 1949].”
Abnormal neural oscillations and synchrony in schizophrenia (2010, background): “Modification of synaptic contacts is dependent on the precise temporal coordination of neural activit”
Temporal encoding of place sequences by hippocampal cell assemblies. (2006, background): “This organization implies temporally coordinated activity within and between anatomically distributed groups of sequential cell assemblies (Hebb’s ‘‘phase sequence’’) (Hebb, 1949).”
Learning hierarchical spatio-temporal pattern for human activity prediction (2016, background): “The Canadian Psychologist Donald Hebb [11] speculated in 1949 that ‘‘When neuron A repeatedly and persistently takes part in exciting neuron B, the synaptic connection from A to B will be strengthened.””
Canonical microcircuits for predictive coding. (2012, unknown): “Donald Hebb proposed that neurons distributed over several cortical areas could form a functional computational unit called a neural assembly (Hebb, 1949).”