Acquisition of Neural Learning in Cerebellum and Cerebral Cortex for Smooth Pursuit Eye Movements
Li, Medina, Frank, Lisberger, 2011
We evaluated the emergence of neural learning in the frontal eye fields (FEFSEM) [note: this is an area of the frontal cortex] and the floccular complex of the cerebellum while monkeys learned a precisely timed change in the direction of pursuit eye movement. For each neuron, we measured the time course of changes in neural response across a learning session that comprised at least 100 repetitions of an instructive change in target direction. In both areas, the average population learning curves tracked the behavioral changes with high fidelity, consistent with possible roles in driving learning. However,the learning curves of individual neurons sometimes bore little relation to the smooth, monotonic progression of behavioral learning. In the FEFSEM, neural learning was episodic. For individual neurons, learning appeared at different times during the learning session and sometimes disappeared by the end of the session. Different FEFSEM neurons expressed maximal learning at different times relative to the acquisition of behavioral learning. In the floccular complex, many Purkinje cells acquired learned simple spike responses according to the same time course as behavioral learning and retained their learned responses throughout the learning session. A minority of Purkinje cells acquired learned responses late in the learning session, after behavioral learning had reached an asymptote.We conclude that learning in single neurons can follow a very different time course from behavioral learning. Both the FEFSEM and the floccular complex contain representations of multiple temporal components of learning, with different neurons contributing to learning at different times during the acquisition of a learned movement.
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Neurons Are Recruited to a Memory Trace Based on Relative Neuronal Excitability Immediately before Training
Adelaide P. Yiu, Valentina Mercaldo, Chen Yan, Blake Richards, Asim J. Rashid,
Hwa-Lin Liz Hsiang, Jessica Pressey, Vivek Mahadevan, Matthew M. Tran, Steven A. Kushner,
Melanie A. Woodin, Paul W. Frankland, and Sheena A. Josselyn (2014)
http://dx.doi.org/10.1016/j.neuron.2014.07.017Video Summary by the Authors:
https://www.cell.com/neuron/fulltext/S0896-6273(14)00628-XAbstract
Memories are thought to be sparsely encoded in
neuronal networks, but little is known about why a
given neuron is recruited or allocated to a particular
memory trace. Previous research shows that in
the lateral amygdala (LA), neurons with increased
CREB are selectively recruited to a fear memory
trace. CREB is a ubiquitous transcription factor im-
plicated in many cellular processes. Which process
mediates neuronal memory allocation? One hypoth-
esis is that CREB increases neuronal excitability to
bias neuronal recruitment, although this has not
been shown experimentally. Here we use several
methods to increase neuronal excitability and show
this both biases recruitment into the memory trace
and enhances memory formation. Moreover, artificial
activation of these neurons alone is a sufficient
retrieval cue for fear memory expression, showing
that these neurons are critical components of the
memory trace. These results indicate that neuronal
memory allocation is based on relative neuronal
excitability immediately before training.
The role of intrinsic excitability in the evolution of memory: significance in memory allocation, consolidation, and updating
Lingxuan Chena, Kirstie A. Cummingsa, William Maua, Yosif Zakia, Zhe Donga, Sima
Rabinowitza, Roger L. Clema, Tristan Shumana, Denise J. Caia (2020)
https://doi.org/10.1016/j.nlm.2020.107266
Free Copy: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429265/Abstract
Memory is a dynamic process that is continuously regulated by both synaptic and intrinsic neural
mechanisms. While numerous studies have shown that synaptic plasticity is important in various
types and phases of learning and memory, neuronal intrinsic excitability has received relatively
less attention, especially regarding the dynamic nature of memory. In this review, we present
evidence demonstrating the importance of intrinsic excitability in memory allocation,
consolidation, and updating. We also consider the intricate interaction between intrinsic
excitability and synaptic plasticity in shaping memory, supporting both memory stability and
flexibility.