The Organization of Behavior

Risk stratification and pathological mechanisms in preterm delivery

Lockwood, C. J., & Kuczynski, E. (2001) · Paediatric and Perinatal Epidemiology · doi:10.1046/j.1365-3016.2001.00010.x · Cited by 179

Semantic Associations between Signs and Numerical Categories in the Prefrontal Cortex

Diester, I., & Nieder, A. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050294 · Cited by 186

Object recognition contributions to figure-ground organization: Operations on outlines and subjective contours

Peterson, M. A., & Gibson, B. S. (1994) · Perception & Psychophysics · doi:10.3758/bf03206951 · Cited by 178

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition

Zhang, Y., Li, P., Jin, Y., & Choe, Y. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2388544 · Cited by 178

Neuroscience insights improve neurorehabilitation of poststroke aphasia

Berthier, M. L., & Friedemann Pulvermüller, A. (2011) · Nature Reviews Neurology · doi:10.1038/nrneurol.2010.201 · Cited by 191

Theory and Simulation in Neuroscience

Wulfram Gerstner, B., Sprekeler, H., & Deco, G. (2012) · Science · doi:10.1126/science.1227356 · Cited by 185

What can we learn from synaptic weight distributions?

Barbour, B., Brunel, N., Hakim, V., & Nadal, J. (2007) · Trends in Neurosciences · doi:10.1016/j.tins.2007.09.005 · Cited by 183

Physiological interpretationm of the self-organizing map algorithm

Kohonen, T. (1993) · Neural Networks · doi:10.1016/s0893-6080(05)90000-2 · Cited by 178

To discard or not to discard: the neural basis of hoarding symptoms in obsessive-compulsive disorder

An, S. K., Mataix‐Cols, D., Lawrence, N., Wooderson, S. C., Giampietro, V., Speckens, A. E. M., Brammer, M. J., & Phillips, M. L. (2008) · Molecular Psychiatry · doi:10.1038/sj.mp.4002129 · Cited by 177

Singular Perturbation Analysis of Competitive Neural Networks with Different Time Scales

Meyer‐Baese, A., Ohl, F. W., & Scheich, H. (1996) · Neural Computation · doi:10.1162/neco.1996.8.8.1731 · Cited by 177

Receptive-Field Modification in Rat Visual Cortex Induced by Paired Visual Stimulation and Single-Cell Spiking

Meliza, C. D., & Dan, Y. (2006) · Neuron · doi:10.1016/j.neuron.2005.12.009 · Cited by 177

Inhibitory Modulation of Cortical Up States

Sanchez-Vives, M. V., Mattia, M., Compte, A., Pérez‐Zabalza, M., Winograd, M., Descalzo, V. F., & Reig, R. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00178.2010 · Cited by 177

Spontaneous synchronous synaptic calcium transients in cultured cortical neurons

Murphy, T. H., Blatter, L., Wier, W. G., & Baraban, J. M. (1992) · Journal of Neuroscience · doi:10.1523/jneurosci.12-12-04834.1992 · Cited by 177

Regulation of motor neuron dendrite growth by NMDA receptor activation

Kalb, R. G. (1994) · Development · doi:10.1242/dev.120.11.3063 · Cited by 177

Human Development: Biological and Genetic Processes

Gottesman, I. I., & Hanson, D. R. (2004) · Annual Review of Psychology · doi:10.1146/annurev.psych.56.091103.070208 · Cited by 180

Methodologies for studying human knowledge

Anderson, J. R. (1987) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00023554 · Cited by 177

Quantum Hopfield neural network

Rebentrost, P., Bromley, T. R., Weedbrook, C., & Lloyd, S. (2018) · Physical Review A · doi:10.1103/physreva.98.042308 · Cited by 187

Mechanical tension contributes to clustering of neurotransmitter vesicles at presynaptic terminals

Siechen, S., Yang, S., Chiba, A., & Saif, M. T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901867106 · Cited by 176

Comparative analysis of failure prediction methods: the Finnish case

Laitinen, T., & Kankaanpaa, M. (1999) · European Accounting Review · doi:10.1080/096381899336159 · Cited by 182

Habituation of exploratory activity in mice: A screening test for memory enhancing drugs

Platel, A., & Porsolt, R. D. (1982) · Psychopharmacology · doi:10.1007/bf00433739 · Cited by 176

Altered Cortical Ensembles in Mouse Models of Schizophrenia

Hamm, J. P., Peterka, D. S., Gogos, J. A., & Yuste, R. (2017) · Neuron · doi:10.1016/j.neuron.2017.03.019 · Cited by 175

Learning multidimensional signal processing

Knutsson, H. E., Borga, M., & Landelius, T. (2002) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.1998.711968 · Cited by 175

Mitochondrial Oxidative Phosphorylation System (OXPHOS) Deficits in Schizophrenia

Bergman, O., & Ben‐Shachar, D. (2016) · The Canadian Journal of Psychiatry · doi:10.1177/0706743716648290 · Cited by 180

Exploration and play: Resume and redirection.

Weisler, A., & McCall, R. R. (1976) · American Psychologist · doi:10.1037//0003-066x.31.7.492 · Cited by 175

Effects of experience and juvenile hormone on the organization of the mushroom bodies of honey bees

Withers, G. S., Fahrbach, S. E., & Robinson, G. E. (1995) · Journal of Neurobiology · doi:10.1002/neu.480260111 · Cited by 175

Biological constraints on neural network models of cognitive function

Friedemann Pulvermüller, A., Tomasello, R., Henningsen‐Schomers, M. R., & Wennekers, T. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00473-5 · Cited by 186

Evidence for synaptic potentiation in a cortical network during learning

Roman, F. S., Staubli, U. V., & LYNCH, G. S. (1987) · Brain Research · doi:10.1016/0006-8993(87)90089-8 · Cited by 174

THE ÆTIOLOGY OF RETROGRADE AMNESIA

Wolpaw, J. (1971) · The Lancet · doi:10.1016/s0140-6736(71)90068-7 · Cited by 174

Near-total loss of ‘learning’ and ‘memory’ as a result of combined cholinergic and serotonergic blockade in the rat

Vanderwolf, C. H. (1987) · Behavioural Brain Research · doi:10.1016/0166-4328(87)90241-5 · Cited by 174

What do we learn from binding features? Evidence for multilevel feature integration.

Colzato, L. S., Raffone, A., & Hommel, B. (2006) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.32.3.705 · Cited by 173

Logic programming on a neural network

Abdullah, W. A. T. W. (1992) · International Journal of Intelligent Systems · doi:10.1002/int.4550070604 · Cited by 177

Task Dynamic Coordination of the Speech Articulators: A Preliminary Model

Saltzman, E. L. (1986) · Springer eBooks · doi:10.1007/978-3-642-71476-4_10 · Cited by 173

The mnemon and its juices: neuromodulation of memory processes

Gold, P. E., & Zornetzer, S. F. (1983) · Behavioral and Neural Biology · doi:10.1016/s0163-1047(83)90170-x · Cited by 173

Plasticity and learning in a network of coupled phase oscillators

Seliger, P., Young, S. C., & Tsimring, L. S. (2002) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.65.041906 · Cited by 176

Turning On and Off with Excitation: The Role of Spike-Timing Asynchrony and Synchrony in Sustained Neural Activity

Gutkin, B. S., Laing, C. R., Colby, C. L., Chow, C. C., & Ermentrout, B. (2001) · Journal of Computational Neuroscience · doi:10.1023/a:1012837415096 · Cited by 176

Early-life handling stimulation and environmental enrichment

Fernández-Teruel, A., Giménez-Llort, L., Escorihuela, R. M., Gil, L., Aguilar, R., Steimer, T., & Tobeña, A. (2002) · Pharmacology Biochemistry and Behavior · doi:10.1016/s0091-3057(02)00787-6 · Cited by 171

Using genetic algorithms to select architecture of a feedforward artificial neural network

Arifovic, J., & Ramazan Gençay, A. (2001) · Physica A Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(00)00479-9 · Cited by 171

A review of artificial neural networks applications in microwave computer-aided design (invited article)

Burrascano, P., Fiori, S., & Mongiardo, M. (1999) · International Journal of RF and Microwave Computer-Aided Engineering · doi:10.1002/(sici)1099-047x(199905)9:3 · Cited by 172

Adaptive Principal component EXtraction (APEX) and applications

Kung, S., Diamantaras, K., & Taur, J. S. (1994) · IEEE Transactions on Signal Processing · doi:10.1109/78.295198 · Cited by 171

Distinct and Dynamic ON and OFF Neural Ensembles in the Prefrontal Cortex Code Social Exploration

Liang, B., Zhang, L., Barbera, G., Fang, W., Zhang, J., Chen, X., Chen, R., Li, Y., & Lin, D. (2018) · Neuron · doi:10.1016/j.neuron.2018.08.043 · Cited by 174

Posttraining Estrogen and Memory Modulation

Packard, M. G. (1998) · Hormones and Behavior · doi:10.1006/hbeh.1998.1464 · Cited by 172

Oscillatory Synchrony in the Monkey Temporal Lobe Correlates with Performance in a Visual Short-term Memory Task

Tallon‐Baudry, C. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh031 · Cited by 176

Unitization during category learning.

Goldstone, R. L. (2000) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.26.1.86 · Cited by 170

Facilitation of maze learning with posttrial injections of picrotoxin.

Breen, R. A., & McGaugh, J. L. (1961) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0046436 · Cited by 170

Co-evolution of Phases and Connection Strengths in a Network of Phase Oscillators

Aoki, T., & Aoyagi, T. (2009) · Physical Review Letters · doi:10.1103/physrevlett.102.034101 · Cited by 169

Toward a neurophenomenology as an account of generative passages: a first empirical case study

Antoine Lutz, A. (2002) · Phenomenology and the Cognitive Sciences · doi:10.1023/a:1020320221083 · Cited by 169

The role of hippocampus in memory: A hypothesis

Teyler, T. J., & DiScenna, P. G. (1985) · Neuroscience & Biobehavioral Reviews · doi:10.1016/0149-7634(85)90016-8 · Cited by 173

Low-frequency trains of paired stimuli induce long-term depression in area CA1 but not in dentate gyrus of the intact rat

Doy�re, V., Errington, M. L., Laroche, S., & Bliss, T. V. P. (1996) · Hippocampus · doi:10.1002/(sici)1098-1063(1996)6:1 · Cited by 79

Discerning the future of early childhood intervention.

Zigler, E., & Berman, W. (1983) · American Psychologist · doi:10.1037/0003-066x.38.8.894 · Cited by 171

Complex environment experience rescues impaired neurogenesis, enhances synaptic plasticity, and attenuates neuropathology in familial Alzheimer's disease‐linked APPswe/PS1ΔE9 mice

Hu, Y., Xu, P., Pigino, G. F., Brady, S. T., Larson, J., & Lazarov, O. (2010) · The FASEB Journal · doi:10.1096/fj.09-136945 · Cited by 176

Branch-Specific Plasticity Enables Self-Organization of Nonlinear Computation in Single Neurons

Legenstein, R. A., & Maass, W. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5684-10.2011 · Cited by 168

Effects of patterned electrical activity on neurite outgrowth from mouse sensory neurons

Fields, R. D., Neale, E. A., & Nelson, P. G. (1990) · Journal of Neuroscience · doi:10.1523/jneurosci.10-09-02950.1990 · Cited by 168

Development of feature detectors by self-organization

Rubner, J., & Schulten, K. (1990) · Biological Cybernetics · doi:10.1007/bf00198094 · Cited by 169

Social recovery of monkeys isolated for the first year of life: I. Rehabilitation and therapy.

Novak, M. A., & Harlow, H. F. (1975) · Developmental Psychology · doi:10.1037/h0076661 · Cited by 168

“Minding the Gap”: Imagination, Creativity and Human Cognition

Pelaprat, E., & Cole, M. (2011) · Integrative Psychological and Behavioral Science · doi:10.1007/s12124-011-9176-5 · Cited by 167

The time course of action and action-word comprehension in the human brain as revealed by neurophysiology

Hauk, O., Юрьевич, Ш. Ю., & Friedemann Pulvermüller, A. (2008) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2008.03.013 · Cited by 179

A Unified Approach to Building and Controlling Spiking Attractor Networks

Eliasmith, C. (2005) · Neural Computation · doi:10.1162/0899766053630332 · Cited by 177

Dynamics of neural structures

Anninos, P. A., Beek, B., Csermely, T. J., Harth, E. M., & Pertile, G. (1970) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(70)80036-4 · Cited by 167

Insights into activity‐dependent map formation from the retinotectal system: A middle‐of‐the‐brain perspective

Ruthazer, E. S., & Cline, H. T. (2004) · Journal of Neurobiology · doi:10.1002/neu.10344 · Cited by 170

Stimulus generalization of fear responses: effects of auditory cortex lesions in a computational model and in rats

Armony, J. L. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.2.157 · Cited by 167

Tonic heart rate: Experiments on the effects of collative variables lead to a hypothesis about its motivational significance.

Rogers, E. (1969) · Journal of Personality and Social Psychology · doi:10.1037/h0027630 · Cited by 167

Ecological Task Analysis: Translating Movement Behavior Theory into Practice

Davis, W. E., & Burton, A. W. (1991) · Adapted Physical Activity Quarterly · doi:10.1123/apaq.8.2.154 · Cited by 166

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

Kempter, R., Wulfram Gerstner, B., & van Hemmen, J. L. (2001) · Neural Computation · doi:10.1162/089976601317098501 · Cited by 173

Some developmental and attentional biases in the contrast enhancement and short term memory of recurrent neural networks

Grossberg, S., & Levine, D. S. (1975) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(75)80009-9 · Cited by 166

Effect of environmental complexity on cortical synapses of rats: Preliminary results

West, R. W., & Greenough, W. T. (1972) · Behavioral Biology · doi:10.1016/s0091-6773(72)80207-4 · Cited by 168

Deformation‐Driven Shape Correspondence

Zhang, H., Sheffer, A., Cohen‐Or, D., Zhou, Q., van Kaick, O. M., & Tagliasacchi, A. (2008) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2008.01283.x · Cited by 165

Encoding a motor memory in the older adult by action observation

Celnik, P. A., Stefan, K., Hummel, F. C., Duqué, J., Claßen, J., & Cohen, L. G. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.07.039 · Cited by 169

Automated interictal EEG spike detection using artificial neural networks

Gabor, A. J., & Seyal, M. (1992) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(92)90086-w · Cited by 165

Learning from mistakes

Chialvo, D. R., & Bak, P. (1999) · Neuroscience · doi:10.1016/s0306-4522(98)00472-2 · Cited by 167

Spatially selective firing properties of hippocampal formation neurons in rodents and primates

O’Mara, S. M. (1995) · Progress in Neurobiology · doi:10.1016/0301-0082(94)00050-r · Cited by 168

Organizing principles of real-time memory encoding: neural clique assemblies and universal neural codes

Lin, L., Osan, R. M., & Tsien, J. Z. (2005) · Trends in Neurosciences · doi:10.1016/j.tins.2005.11.004 · Cited by 166

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Yan, X., Qian, J. H., Sangwan, V. K., & Hersam, M. C. (2021) · Advanced Materials · doi:10.1002/adma.202108025 · Cited by 172

Why Seeing Is Believing: Merging Auditory and Visual Worlds

Witten, I. B., & Knudsen, E. I. (2005) · Neuron · doi:10.1016/j.neuron.2005.10.020 · Cited by 178

Hebbian LTP in feed-forward inhibitory interneurons and the temporal fidelity of input discrimination

Lamsa, K., Heeroma, J. H., & Kullmann, D. M. (2005) · Nature Neuroscience · doi:10.1038/nn1486 · Cited by 158

Knowledge acquisition, accessibility, and use in person perception and stereotyping: Simulation with a recurrent connectionist network.

Smith, E. R., & DeCoster, J. (1998) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.74.1.21 · Cited by 163

Synaptic plasticity in human cortical circuits: cellular mechanisms of learning and memory in the human brain?

Mansvelder, H. D., Verhoog, M. B., & Goriounova, N. A. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.06.013 · Cited by 170

A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks

Wu, J., Chua, Y., Zhang, M., Li, G., Li, H., & Tan, K. C. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3095724 · Cited by 169

Philosophy of Technology: An Introduction

Dusek, V. (2006) · Cited by 163

Synaptic Dysfunction in the Hippocampus Accompanies Learning and Memory Deficits in Human Immunodeficiency Virus Type-1 Tat Transgenic Mice

Fitting, S., Ignatowska-Jankowska, B. M., Bull, C., Skoff, R. P., Lichtman, A. H., Wise, L. E., Fox, M. A., Su, J., Medina, A. E., Krahe, T. E., et al. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.09.026 · Cited by 168

Structure of boredom.

Geiwitz, P. J. (1966) · Journal of Personality and Social Psychology · doi:10.1037/h0023202 · Cited by 162

A ventral CA1 to nucleus accumbens core engram circuit mediates conditioned place preference for cocaine

Zhou, Y., Zhu, H., Liu, Z., Chen, X., Su, X., Ma, C., Tian, Z. F., Huang, B. Y., Yan, E., Liu, X., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0524-y · Cited by 169

Striving for coherence

Singer, W. (1999) · Nature · doi:10.1038/17021 · Cited by 162

A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency

Brockett, P. L., Cooper, W. W., Golden, L. L., & Pitaktong, U. (1994) · Journal of Risk & Insurance · doi:10.2307/253568 · Cited by 166

A Protein Synthesis–Dependent Late Phase of Cerebellar Long-Term Depression

Linden, D. J. (1996) · Neuron · doi:10.1016/s0896-6273(00)80180-4 · Cited by 163

Spontaneous fixation tendencies for visual forms

Kaufman, L., & Richards, W. A. (1969) · Perception & Psychophysics · doi:10.3758/bf03210527 · Cited by 162

Different forms of post-training memory processing

Izquierdo, I. (1989) · Behavioral and Neural Biology · doi:10.1016/s0163-1047(89)90812-1 · Cited by 162

Imprinting, learning and development: from behaviour to brain and back

Bolhuis, J. J., & Honey, R. C. (1998) · Trends in Neurosciences · doi:10.1016/s0166-2236(98)01258-2 · Cited by 161

Beyond reduction: mechanisms, multifield integration and the unity of neuroscience

Craver, C. F. (2005) · Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences · doi:10.1016/j.shpsc.2005.03.008 · Cited by 167

Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review

Nath, D., Ankit, Neog, D. R., & Gautam, S. S. (2024) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-024-10063-0 · Cited by 167

Aging, spatial learning, and total synapse number in the rat CA1 stratum radiatum

Geinisman, Y., Ganeshina, O., Yoshida, R., Berry, R. W., Disterhoft, J. F., & Gallagher, M. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.12.001 · Cited by 166

Lyapunov function for the Kuramoto model of nonlinearly coupled oscillators

van Hemmen, J. L., & Wreszinski, W. F. (1993) · Journal of Statistical Physics · doi:10.1007/bf01048044 · Cited by 161

Face sensorimotor cortex and its neuroplasticity related to orofacial sensorimotor functions

Avivi‐Arber, L., Martin, R. E., Lee, J., & Sessle, B. J. (2011) · Archives of Oral Biology · doi:10.1016/j.archoralbio.2011.04.005 · Cited by 160

The nature and role of learning in the orientation and migratory behavior of fishes

Dodson, J. J. (1988) · Environmental Biology of Fishes · doi:10.1007/bf00004908 · Cited by 160

Probabilistic functionalism: A conception of research method.

Petrinovich, L. F. (1979) · American Psychologist · doi:10.1037//0003-066x.34.5.373 · Cited by 163

Repetitive paired-pulse TMS at I-wave periodicity markedly increases corticospinal excitability: A new technique for modulating synaptic plasticity

Thickbroom, G. W., Byrnes, M. L., Edwards, D. J., & Mastaglia, F. L. (2005) · Clinical Neurophysiology · doi:10.1016/j.clinph.2005.09.010 · Cited by 159

Supervised Learning in Multilayer Spiking Neural Networks

Sporea, I., & Grüning, A. (2012) · Neural Computation · doi:10.1162/neco_a_00396 · Cited by 159

Principles of Neuroplasticity-Based Rehabilitation

Nahum, M., Lee, H., & Merzenich, M. M. (2013) · Progress in Brain Research · doi:10.1016/b978-0-444-63327-9.00009-6 · Cited by 158

The neuroscience of memory: implications for the courtroom

Lacy, J. W., & Stark, C. E. L. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3563 · Cited by 155

Computational connectionism within neurons: A model of cytoskeletal automata subserving neural networks.

Rasmussen, S., Karampurwala, H., Vaidyanath, R., Jensen, K. S., & Hameroff, S. (1990) · Physica D Nonlinear Phenomena · doi:10.1016/0167-2789(90)90093-5 · Cited by 153

Social Attitudes and Other Acquired Behavioral Dispositions.

Campbell, D. T. (1963) · Psychology: A study of a science. Study II. Empirical substructure and relations with other sciences. Volume 6. Investigations of man as socius: Their place in psychology and the social sciences. · doi:10.1037/10590-003 · Cited by 514

Donald O. Hebb and the Organization of Behavior: 17 years in the writing

Brown, R. E. (2020) · Molecular Brain · doi:10.1186/s13041-020-00567-8 · Cited by 63

The Book of Hebb

B, T. J. S. A. (1999) · Neuron · doi:10.1016/s0896-6273(00)81025-9 · Cited by 108

The Organization of behavior : a neuropsychological theory / D.O. Hebb

Hebb, D. O. (1949) · Cited by 5

Donald Olding Hebb (1904–1985)

Wickens, A. P. (2018) · Routledge eBooks · doi:10.4324/9781351271042-11

Hebb, D. O. Organization of behavior. New York: Wiley, 1949, pp. 335, $4.00

(1950) · Journal of Clinical Psychology · doi:10.1002/1097-4679(195007)6:3 · Cited by 12