Till startsida
To content Read more about how we use cookies on gu.se

Stephen Grossberg

Two talk titles

1. Paradigms, Methods, and Objects

Brain paradigms and research methods for understanding
object attention, conscious seeing, learning, invariant recognition, and search

2. Space and Time

Spatial navigation, cognitive working memory, and conscious speech perception

The first part of lecture 1 provides an overview to ground the listeners for what will follow. I will then discuss recent models of object attention, conscious seeing, learning, invariant recognition, and search. This should be of interest to both biologists and technologists. Along the way, I explain a lot of data and make experimental predictions.

The second lecture complements the first. It explains how entorhinal grid and place cells can be learned and uses the same model to simulate a lot of challenging psychological and neurobiological data about spatial navigation. Then it switches gears to discuss how sequences of events are stored temporarily in working memory while being unitized, or chunked, into familiar words, plans, or skills. Then it describes recent modeling of conscious speech perception using this foundation.


Stephen Grossberg is Wang Professor of Cognitive and Neural Systems; He is a principal founder and current research leader in computational neuroscience, connectionist cognitive science, and neuromorphic technology. In 1957-58, Grossberg introduced the paradigm of using nonlinear systems of differential equations, including widely used equations for short-term memory (STM), or neuronal activation; medium-term memory (MTM), or activity-dependent habituation; and long-term memory (LTM), or neuronal learning. His work focuses upon how individuals adapt autonomously in real-time to unexpected environmental challenges, and includes models of vision and visual cognition; object, scene, and event recognition; audition, speech and language; development; cognitive information processing; reinforcement learning and cognitive-emotional interactions; navigation; social cognition; sensory-motor control and planning; mental disorders; and neuromorphic technology. Grossberg founded key infrastructure of the field of neural networks, including the International Neural Network Society and the journal Neural Networks. He is a fellow of AERA, APA, APS, IEEE, INNS, MDRS, and SEP. He has published 17 books or journal special issues, over 500 research articles, and has 7 patents. He was most recently awarded the 2015 Lifetime Achievement Award of the Society of Experimental Psychologists.

See the following web pages for further information:

Suggested readings

See http://cns.bu.edu/~steve for other research articles, editorials, lectures, and videos.

Review Articles

Grossberg, S. (2013). Adaptive resonance theory. Scholarpedia:

Grossberg, S. (2013). Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world. Neural Networks, 37, 1-47.

Grossberg, S. (2014). From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.Brain Research, doi: 10.1016/j.brainres.2014.11.018

Object and Scene Learning, Invariant Recognition, and Attentive Search Articles

SMART: Grossberg, S. and Versace, M. (2008). Spikes, synchrony, and attentive learning by laminar thalamocortical circuits. Brain Research,1218, 278-312.

ARTSCAN: Fazl, A., Grossberg, S., and Mingolla, E. (2009). View-invariant object category learning, recognition, and search: How spatial and object attention are coordinated using surface-based attentional shrouds. Cognitive Psychology, 58, 1-48.

ARTSCENE: Grossberg, S., & Huang, T.-R. (2009). ARTSCENE: A neural system for natural scene classification. Journal of Vision, 9(4):6, 1-19,http://journalofvision.org/9/4/6/, doi:10.1167/ 9.4.6.

ARTSCENE Search: Huang, T.-R., and Grossberg, S. (2010). Cortical dynamics of contextually cued attentive visual learning and search: Spatial and object evidence accumulation. Psychological Review, 117(4), 1080-1112.

CRIB: Grossberg, S., and Vladusich, T. (2010). How do children learn to follow gaze, share joint attention, imitate their teachers, and use tools during social interactions? Neural Networks, 23, 940-965.

pARTSCAN: Cao, Y., Grossberg, S., and Markowitz, J. (2011). How does the brain rapidly learn and reorganize view- and positionally-invariant object representations in inferior temporal cortex? Neural Networks, 24, 1050-1061.

More pARTSCAN: Grossberg, S., Markowitz, J., and Cao, Y. (2011). On the road to invariant recognition: Explaining tradeoff and morph properties of cells in inferotemporal cortex using multiple-scale task-sensitive attentive learning. Neural Networks, 24, 1036-1049.

dARTSCAN: Foley, N.C., Grossberg, S. and Mingolla, E. (2012). Neural dynamics of object-based multifocal visual spatial attention and priming: Object cueing, useful-field-of-view, and crowding. Cognitive Psychology, 65, 77-117.

3D ARTSCAN: Grossberg, S., Srinivasan, K., and Yazdanbakhsh, A. (2014). Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements. Frontiers in Psychology: Perception Science, doi: 10.3389/fpsyg.2014.01457

ARTSCAN Search: Chang, H.-C., Grossberg, S., and Cao, Y. (2014) Where's Waldo? How perceptual cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene. Frontiers in Integrative Neuroscience, doi: 10.3389/fnint.2014.0043:

Spatial Navigation Articles

Pilly, P.K., and Grossberg, S. (2013). How reduction of theta rhythm by medial septum inactivation may covary with disruption of entorhinal grid cell responses due to reduced cholinergic transmission. Frontiers in Neural Circuits, doi: 10.3389/fncir.2013.00173:

Pilly, P.K., and Grossberg, S. (2013). Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells. PLOS ONE:

Grossberg, S., and Pilly, P. K. (2014) Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention, and oscillations. Philosophical Transactions of the Royal Society B., 369, 20120524:

Pilly, P.K., and Grossberg, S. (2014) How does the modular organization of entorhinal grid cells develop? Frontiers in Human Neuroscience, doi:10.3389/fnhum.2014.0037:

Working Memory, Chunking, and Conscious Speech Perception Articles

Grossberg, S. (2003). Resonant neural dynamics of speech perception. Journal of Phonetics, 31, 423-445.

Grossberg, S. and Pearson, L. (2008). Laminar cortical dynamics of cognitive and motor working memory, sequence learning and performance: Toward a unified theory of how the cerebral cortex works.Psychological Review, 115, 677-732.

Grossberg, S. and Kazerounian, S. (2011). Laminar cortical dynamics of conscious speech perception: A neural model of phonemic restoration using subsequent context in noise. Journal of the Acoustical Society of America, 130, 440-460.

Kazerounian, S., and Grossberg, S. (2014). Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory. Frontiers in Psychology: Language Sciences, doi: 10.3389/fpsyg.2014.01053.

Page Manager: Daniel Ruhe|Last update: 8/3/2015

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?