Norman M. Weinberger

Picture of Norman M. Weinberger
Fellow of the Center for the Neurobiology of Learning and Memory, Neurobiology and Behavior
School of Biological Sciences
Research Professor, Neurobiology and Behavior
School of Biological Sciences
Ph.D., Western Reserve University, 1961, Psychology
Phone: (949) 824-5512 (office), 824-5514 (lab)
Fax: (949) 824-4576
Email: nmweinbe@uci.edu
University of California, Irvine
309 Qureshey Research Laboratory
Center for the Neurobiology of Learning and Memory
Mail Code: 3800
Irvine, CA 92697
Research Interests
Academic Distinctions
Fellow, American Association for the Advancement of Science
Fellow, American Psychological Society
Research Abstract
Goals — Our goals are to understand the acquisition, retention and representation of information in the cerebral cortex that underlie behavioral memory. In contrast to traditional assumptions, primary sensory cortex is a substrate of memory rather than merely a sensory analyzer. Because primary sensory fields contain systematic “maps” of sensory parameters, they provide an opportune target for the study of representations. We focus on the primary auditory cortex (termed “A1”) due to the wealth of learning/memory studies that use acoustic stimuli. A1 contains a representationaltonotopic map” of acoustic frequency similar to the organization of a piano keyboard. Unlike a keyboard, A1 frequency representation is not fixed but is plastic, becoming “retuned” when a tone gains (or loses) behavioral importance during learning. We use a three-level attack.
• Identify a neurophysiological signature having the characteristics of memory
• Determine mechanisms of induction and expression of representational plasticity
• Determine and delineate Neural Memory Codes
Higher (Cortical) Associative Representational Plasticity (HARP) — Our lab pioneered the combined study of sensory physiology and learning/memory by findings that associative learning shifts cellular receptive fields (frequency tuning) to the frequency of a signal tone. Across the tonotopic map, the signal tone gains representational cortical area. Thus, HARP is revealed to be a systematic modification of cortical representations along a dimension, even during learning with a single stimuli. Representational plasticity develops in a wide variety of tasks, in all species tested (including humans) and has all the characteristics of major forms of memory: associativity, specificity, rapid acquisition, indefinite long-term retention (months) and consolidation (continued development over hours & days). Learning strategy (“how” a task is solved) can determine the formation of representational plasticity and in fact can trump the amount of training or the level of motivation.

Nucleus Basalis Induction of HARP and Implanted Behavioral Memory — A laboratory model hypothesized that the release of acetylcholine (ACh) in the cortex from activation of the nucleus basalis (NB) promotes the long-term storage of HARP as a substrate of memory. Indeed, pairing a tone with stimulation of the NB was found to induce muscarinic-dependent RF plasticity that has all the major attributes of associative memory. Remarkably, muscarinic-dependent specific behaviorally verified memories can be “implanted” in the rat by pairing a tone with NB stimulation. Furthermore, the degree of specificity of implanted memory can be determined by the amount of ACh released in the auditory cortex. Implanted memory also has the cardinal characteristics of “natural” memory. Also, activation of the basolateral amygdala (BLA), an established modulator of memory strength, can induce signal-specific tuning shifts in A1, perhaps via the NB, suggesting memory strength is linked to areal expansion.

Neural Memory Codes — We hypothesized that there are Memory Codes analogous to Sensory Codes for stimulus parameters. Studies of instrumental auditory tasks combined with mapping of A1 have found strong evidence for Memory Codes. For example, there appears to be a code for the acquired importance of stimuli —
The importance of the memory of a stimulus is a direct increasing function of the number of neurons that optimally process or become tuned to that stimulus.
As memories of greater behavioral importance should be stronger, we determined the relationship between memory strength (via resistance to extinction) and representational area. We found evidence for another Memory Code —
The strength of memory is proportional to the amount of expanded representational area for a signal: the greater the area, the stronger the memory.

Selected Publications:
Publications
Weinberger, N.M. (2015, in press). New perspectives on the auditory cortex: Learning and memory. In: G.G. Celesia and G. Hickok (Eds.), The Human Auditory System: Fundamental Organization and Clinical Disorders (Handbook of Clinical Neurology, chap. 8). New York: Elsevier. (ISBN: 978-0-444-62630-1) (Expected release April 12, 2015)

Headley, D.B. and Weinberger, N.M. (2014, in press). Relational associative learning induces cross-modal plasticity in early visual cortex. Cerebral Cortex.

Weinberger, N.M. (2014). Neuromusic research: Some benefits of incorporating basic research on the neurobiology of auditory learning and memory. Frontiers in Systems Neuroscience, 7(128), 1–2. PDF

Bieszczad, K.M., Miasnikov, A.A. and Weinberger, N.M. (2013). Remodeling sensory cortical maps implants specific behavioral memory. Neuroscience, 246, 40–51. PDF

Weinberger, N.M., Miasnikov, A.A., Bieszczad, K.M. and Chen, J.C. (2013). Gamma band plasticity in sensory cortex is a signature of the strongest memory rather than memory of the training stimulus. Neurobiology of Learning and Memory, 104, 49–63. PDF

Headley, D.B. and Weinberger, N.M. (2013). Fear conditioning enhances gamma oscillations and their entrainment of neurons representing the conditioned stimulus. Journal of Neuroscience, 33(13), 5705–5717. PDF

Chavez, C.M., McGaugh, J.L. and Weinberger, N.M. (2013). Activation of the basolateral amygdala induces long-term enhancement of specific memory representations in the cerebral cortex. Neurobiology of Learning and Memory, 101, 8–18. PDF

Chavez, C.M., McGaugh, J.L. and Weinberger, N.M. (2012). Amygdala strengthening of cortical memory representations. In: B. Ferry (Ed.), The Amygdala: A Discrete Multitasking Manager (chap. 7, pp. 171–202). New York: InTech. (ISBN: 978-953-51-0908-2) PDF

Miasnikov, A.A. and Weinberger, N.M. (2012). Detection of an inhibitory cortical gradient underlying peak shift in learning: a neural basis for a false memory. Neurobiology of Learning and Memory, 98(4), 368–379. PDF

Bieszczad, K.M., Kant, R., Constantinescu, C.C., Pandey, S.K., Kawai, H.D., Metherate, R., Weinberger, N.M. and Mukherjee, J. (2012). Nicotinic acetylcholine receptors in rat forebrain that bind 18F-nifene: Relating PET imaging, autoradiography, and behavior. Synapse, 66(5), 418–434. PDF

Weinberger, N.M. (2012). Plasticity in the primary auditory cortex, not what you think it is: Implications for basic and clinical auditory neuroscience. Otolaryngology, S3(002), 1–8. Published online Mar 12 at http://www.omicsonline.org/2161-119X/2161-119X-S3-002.pdf. (Special issue entitled Auditory Neuro-Plasticity) Link | PDF

Bieszczad, K.M. and Weinberger, N.M. (2012). Extinction reveals that primary sensory cortex predicts reinforcement outcome. European Journal of Neuroscience, 35(4), 598–613. PDF

Weinberger, N.M. (2012). Memory code. In: N.M. Seel (Ed.), Encyclopedia of the Sciences of Learning (pp. 2161–2163). New York: Springer. (ISBN: 978-1-4419-1427-9) PDF

Headley, D.B. and Weinberger, N.M. (2011). Gamma-band activation predicts both associative memory and cortical plasticity. Journal of Neuroscience, 31(36), 12748–12758. PDF

Weinberger, N.M. (2011). The medial geniculate, not the amygdala, as the root of auditory fear conditioning. Hearing Research, 274(1–2), 61–74. PDF

Weinberger, N.M. and Bieszczad, K.M. (2011). From traditional fixed cortical sensationism to contemporary plasticity of primary sensory cortical representations. In: J.A. Gottfried (Ed.), Neurobiology of Sensation and Reward (Frontiers in Neuroscience series, chap. 1, pp. 3–13). Boca Raton, FL: CRC Press.

Miasnikov, A.A., Chen, J.C. and Weinberger, N.M. (2011). Consolidation and long-term retention of an implanted behavioral memory. Neurobiology of Learning and Memory, 95(3), 286–295. PDF

Weinberger, N.M. (2011). Reconceptualizing the primary auditory cortex: Learning, memory and specific plasticity. In: J.A. Winer and C.E. Schreiner (Eds.), The Auditory Cortex (chap. 22, pp. 465–491). New York: Springer. PDF

Bieszczad, K.M. and Weinberger, N.M. (2010). Remodeling the cortex in memory: Increased use of a learning strategy increases the representational area of relevant acoustic cues. Neurobiology of Learning and Memory, 94(2), 127–144. PDF

Weinberger, N.M. (2010). The cognitive auditory cortex. In: A.R. Palmer and A. Rees (Eds.), The Oxford Handbook of Auditory Science: The Auditory Brain (chap. 18, pp. 439–475). New York: Oxford University Press.

Bieszczad, K.M. and Weinberger, N.M. (2010). Representational gain in cortical area underlies increase of memory strength. Proceedings of the National Academy of Sciences of the United States of America, 107(8), 3793–3798. PDF

Bieszczad, K.M. and Weinberger, N.M. (2010). Learning strategy trumps motivational level in determining learning-induced auditory cortical plasticity. Neurobiology of Learning and Memory, 93(2), 229–239. PDF

Hui, G.K., Wong, K.L., Chavez, C.M., Leon, M.I., Robin, K.M. and Weinberger, N.M. (2009). Conditioned tone control of brain reward behavior produces highly specific representational gain in the primary auditory cortex. Neurobiology of Learning and Memory, 92(1), 27–34. PDF

Chavez, C.M., McGaugh, J.L. and Weinberger, N.M. (2009). The basolateral amygdala modulates specific sensory memory representations in the cerebral cortex. Neurobiology of Learning and Memory, 91(4), 382–392. PDF

Berlau, K.M. and Weinberger, N.M. (2008). Learning strategy determines auditory cortical plasticity. Neurobiology of Learning and Memory, 89(2), 153–166. PDF

Weinberger, N.M. (2007). Auditory associative memory and representational plasticity in the primary auditory cortex. Hearing Research, 229(1–2), 54–68. PDF

Weinberger, N.M. (2007). Associative representational plasticity in the auditory cortex: A synthesis of two disciplines. Learning and Memory, 14(1–2), 1–16. PDF

Rutkowski, R.G. and Weinberger, N.M. (2005). Encoding of learned importance of sound by magnitude of representational area in primary auditory cortex. Proceedings of the National Academy of Sciences of the United States of America, 102(38), 13664–13669. PDF

Weinberger, N.M. (2004). Music and the brain. Scientific American, 291(5), 88–95. PDF

Weinberger, N.M. (2004). Specific long-term memory traces in primary auditory cortex. Nature Reviews Neuroscience, 5(4), 279–290. PDF

Weinberger, N.M. (2003). The nucleus basalis and memory codes: Auditory cortical plasticity and the induction of specific, associative behavioral memory. Neurobiology of Learning and Memory, 80(3), 268–284. PDF

McLin, D.E., 3rd, Miasnikov, A.A. and Weinberger, N.M. (2002). Induction of behavioral associative memory by stimulation of the nucleus basalis. Proceedings of the National Academy of Sciences of the United States of America, 99(6), 4002–4007. PDF

Galván, V.V. and Weinberger, N.M. (2002). Long-term consolidation and retention of learning-induced tuning plasticity in the auditory cortex of the guinea pig. Neurobiology of Learning and Memory, 77(1), 78–108. PDF

Cahill, L., McGaugh, J.L. and Weinberger, N.M. (2001). The neurobiology of learning and memory: Some reminders to remember. Trends in Neurosciences, 24(10), 578–581. PDF

Weinberger, N.M. (2001). Memory codes: New concept for old problem. In: P.E. Gold and W.T. Greenough (Eds.), Memory Consolidation: Essays in Honor of James L. McGaugh (chap. 16, pp. 321–342). Washington, DC: American Psychological Association.

Bakin, J.S. and Weinberger, N.M. (1996). Induction of a physiological memory in the cerebral cortex by stimulation of the nucleus basalis. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 11219–11224. PDF

Weinberger, N.M., Javid, R. and Lepan, B. (1993). Long-term retention of learning-induced receptive-field plasticity in the auditory cortex. Proceedings of the National Academy of Sciences of the United States of America, 90(6), 2394–2398. PDF

Edeline, J.-M. and Weinberger, N.M. (1993). Receptive field plasticity in the auditory cortex during frequency discrimination training: Selective retuning independent of task difficulty. Behavioral Neuroscience, 107(1), 82–103. PDF

Bakin, J.S. and Weinberger, N.M. (1990). Classical conditioning induces CS-specific receptive field plasticity in the auditory cortex of the guinea pig. Brain Research, 536(1–2), 271–286. PDF
Professional Societies
<font color="#000000">American Association for the Advancement of Science</font>
<font color="#000000">Association for Psychological Science</font>
<font color="#000000">Association for Research in Otolaryngology</font>
<font color="#000000">Cognitive Neuroscience Society</font>
<font color="#000000">Foundation for Biomedical Research</font>
<font color="#000000">International Brain Research Organization</font>
<font color="#000000">National Society for Medical Research</font>
<font color="#000000">Pavlovian Society of America</font>
<font color="#000000">Society for Music Perception and Cognition</font>
<font color="#000000">Society for Neuroscience</font>
Graduate Programs
Neurobiology and Behavior
Research Centers
Center for the Neurobiology of Learning and Memory
Last updated
04/15/2014