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Rapid learning in visual cortical networks.

Wang Y, Dragoi V - Elife (2015)

Bottom Line: We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity.More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning.These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, United States.

ABSTRACT
Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

No MeSH data available.


Related in: MedlinePlus

Control experiment—Monkey 2 was passively exposed for 10 sessions to novel natural scenes (similar to those in Figure 1A) while the animal performed a color detection task (red–green task) in the contralateral hemifield.After 150 trials of passive (unattended) exposure to the image, the monkey was engaged in the rapid learning experiment described in the manuscript (Figure 1A). However, even though images themselves were familiar to the animal, the fact that the monkey did not practice the image orientation discrimination task led to behavioral effects similar to those reported in the manuscript. That is, we found a gradual improvement in discrimination threshold at the end of each session—the gradual learning curve looked similar to that obtained in the original experiments (asterisks indicate p < 0.05).DOI:http://dx.doi.org/10.7554/eLife.08417.004
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fig1s1: Control experiment—Monkey 2 was passively exposed for 10 sessions to novel natural scenes (similar to those in Figure 1A) while the animal performed a color detection task (red–green task) in the contralateral hemifield.After 150 trials of passive (unattended) exposure to the image, the monkey was engaged in the rapid learning experiment described in the manuscript (Figure 1A). However, even though images themselves were familiar to the animal, the fact that the monkey did not practice the image orientation discrimination task led to behavioral effects similar to those reported in the manuscript. That is, we found a gradual improvement in discrimination threshold at the end of each session—the gradual learning curve looked similar to that obtained in the original experiments (asterisks indicate p < 0.05).DOI:http://dx.doi.org/10.7554/eLife.08417.004

Mentions: In principle, it may be possible that the behavioral improvement in blocks 2, 3, and 4 could reflect a change in monkey's strategy to respond, for instance, by frequently holding the lever after block 1 until the end of the session, rather than learning to perform the image discrimination task. To rule out this possibility, we examined the block-by-block changes in behavioral performance in the match trials (these trials require a bar release response). If monkey's strategy was to keep holding the lever as the session progressed, performance in the match trials (randomly interleaved with the non-match trials) would significantly deteriorate. However, we did not find statistically significant changes in match (bar release) responses across blocks of trials (by analyzing all the sessions with an improvement in learning performance, p > 0.1; ANOVA test). Another possibility that could explain our behavioral results is that the poorer performance at the beginning of the session (in block 1) may be due to animals being distracted by the novelty of stimulus presentation. To rule out this concern, we performed additional behavioral experiments (Monkey 2, n = 10 sessions) in which the animal was passively exposed to a novel natural scene while he performed a color detection task (red–green task) in the contralateral hemifield (Figure 1—figure supplement 1). After 150 trials of passive (inattentive) exposure to the novel image, the monkey was switched to the image discrimination task (Figure 1A). As expected, as the monkey did not actually practice the image orientation discrimination task for the stimuli he was exposed to, we found a gradual improvement in behavioral discrimination threshold during the session (p < 0.01, ANOVA test; each of blocks 2–4 was characterized by a lower threshold than block 1, p < 0.05, post hoc multiple comparisons). This control was repeated with images that were fixated (without controlling attention), but the results were similar.


Rapid learning in visual cortical networks.

Wang Y, Dragoi V - Elife (2015)

Control experiment—Monkey 2 was passively exposed for 10 sessions to novel natural scenes (similar to those in Figure 1A) while the animal performed a color detection task (red–green task) in the contralateral hemifield.After 150 trials of passive (unattended) exposure to the image, the monkey was engaged in the rapid learning experiment described in the manuscript (Figure 1A). However, even though images themselves were familiar to the animal, the fact that the monkey did not practice the image orientation discrimination task led to behavioral effects similar to those reported in the manuscript. That is, we found a gradual improvement in discrimination threshold at the end of each session—the gradual learning curve looked similar to that obtained in the original experiments (asterisks indicate p < 0.05).DOI:http://dx.doi.org/10.7554/eLife.08417.004
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588715&req=5

fig1s1: Control experiment—Monkey 2 was passively exposed for 10 sessions to novel natural scenes (similar to those in Figure 1A) while the animal performed a color detection task (red–green task) in the contralateral hemifield.After 150 trials of passive (unattended) exposure to the image, the monkey was engaged in the rapid learning experiment described in the manuscript (Figure 1A). However, even though images themselves were familiar to the animal, the fact that the monkey did not practice the image orientation discrimination task led to behavioral effects similar to those reported in the manuscript. That is, we found a gradual improvement in discrimination threshold at the end of each session—the gradual learning curve looked similar to that obtained in the original experiments (asterisks indicate p < 0.05).DOI:http://dx.doi.org/10.7554/eLife.08417.004
Mentions: In principle, it may be possible that the behavioral improvement in blocks 2, 3, and 4 could reflect a change in monkey's strategy to respond, for instance, by frequently holding the lever after block 1 until the end of the session, rather than learning to perform the image discrimination task. To rule out this possibility, we examined the block-by-block changes in behavioral performance in the match trials (these trials require a bar release response). If monkey's strategy was to keep holding the lever as the session progressed, performance in the match trials (randomly interleaved with the non-match trials) would significantly deteriorate. However, we did not find statistically significant changes in match (bar release) responses across blocks of trials (by analyzing all the sessions with an improvement in learning performance, p > 0.1; ANOVA test). Another possibility that could explain our behavioral results is that the poorer performance at the beginning of the session (in block 1) may be due to animals being distracted by the novelty of stimulus presentation. To rule out this concern, we performed additional behavioral experiments (Monkey 2, n = 10 sessions) in which the animal was passively exposed to a novel natural scene while he performed a color detection task (red–green task) in the contralateral hemifield (Figure 1—figure supplement 1). After 150 trials of passive (inattentive) exposure to the novel image, the monkey was switched to the image discrimination task (Figure 1A). As expected, as the monkey did not actually practice the image orientation discrimination task for the stimuli he was exposed to, we found a gradual improvement in behavioral discrimination threshold during the session (p < 0.01, ANOVA test; each of blocks 2–4 was characterized by a lower threshold than block 1, p < 0.05, post hoc multiple comparisons). This control was repeated with images that were fixated (without controlling attention), but the results were similar.

Bottom Line: We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity.More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning.These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, United States.

ABSTRACT
Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

No MeSH data available.


Related in: MedlinePlus