Gamma band plasticity in sensory cortex is a signature of the strongest memory rather than memory of the training stimulus

Abstract

Gamma oscillations (~30–120 Hz) are considered to be a reflection of coordinated neuronal activity, linked to processes underlying synaptic integration and plasticity. Increases in gamma power within the cerebral cortex have been found during many cognitive processes such as attention, learning, memory and problem solving in both humans and animals. However, the specificity of gamma to the detailed contents of memory remains largely unknown. We investigated the relationship between learning-induced increased gamma power in the primary auditory cortex (A1) and the strength of memory for acoustic frequency. Adult male rats (n = 16) received three days (200 trials each) of pairing a tone (3.66 kHz) with stimulation of the nucleus basalis, which implanted a memory for acoustic frequency as assessed by associatively-induced disruption of ongoing behavior, viz., respiration. Post-training frequency generalization gradients (FGGs) revealed peaks at non-CS frequencies in 11/16 cases, likely reflecting normal variation in pre-training acoustic experiences. A stronger relationship was found between increased gamma power and the frequency with the strongest memory (peak of the difference between individual post- and pre-training FGGs) vs. behavioral responses to the CS training frequency. No such relationship was found for the theta/alpha band (4–15 Hz). These findings indicate that the strength of specific increased neuronal synchronization within primary sensory cortical fields can determine the specific contents of memory.

Learning strategy refinement reverses early sensory cortical map expansion but not behavior: Support for a theory of directed cortical substrates of learning and memory

“…The complete CONCERTO model posits both system level and circuit-cell-molecule levels of explanation, aspects of which have been published elsewhere: e.g., neuromodulators/muscarinic receptors (Bieszczad et al, 2013; McLin et al, 2002; Miasnikov, Chen, & Weinberger, 2008; Weinberger et al, 2006; see also Edeline, 2012; Edeline, Manunta, & Hennevin, 2011), and neuronal synchrony and gamma band activity (Headley & Weinberger, 2011, 2013; Weinberger, Miasnikov, Bieszczad, & Chen, 2013). We are able to present here only major elements of its system level formulation.…”

Associative learning and sensory neuroplasticity: how does it happen and what is it good for?

“…Reductions in firing rate or in the number of neurons responding to a stimulus (Gdalyahu et al 2012;Kass et al 2013b) may thus reflect an optimization of stimulus representations according to metabolic constraints, while changes in spike timing or synchrony (Bao et al 2004;Weinberger et al 2013;Kay 2015) or increases in neural response to one stimulus balanced by decreased response to other stimuli (Froemke et al 2013) present potentially metabolically neutral mechanisms for encoding stimulus importance. In this light the large increases in stimulus-evoked synaptic activity (Kass et al 2013d) and action potential firing rates (Bakin and Weinberger 1990;Polley et al 2004) after conditioning constitute an investment of significant resources that presumably serves an important purpose.…”

Volume transmission signalling via astrocytes

“…Neuronal activity is temporally coordinated in gamma rhythms by NBM stimulation and this synchronization could be a prevailing mechanism of augmented synaptic plasticity [77]. However, the deficiency of NBM-associated cortical plasticity in IP 3 R2-KO mice strongly supports a role of astrocytic Ca 2+ signalling in the synaptic plasticity.…”