Rapid learning in cortical coding of visual scenes

Yao, Haishan; Shi, Lei; Han, Feng; Gao, Hongfeng; Dan, Yang

doi:10.1038/nn1895

Cited by 116 publications

(124 citation statements)

References 48 publications

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“…Previous studies using voltage-sensitive dye imaging (21, 42) and single-cell electrophysiology in cat V1 (20) have shown that ongoing activity resembles orientation map responses to grating stimuli (42) and natural movies (20), and it can exhibit a memory trace response immediately after the stimulus is extinguished (20). Furthermore, "recall" responses were recently found in visual cortical networks following conditioning with a moving dot stimulus upon presentation of the first dot in the sequence (22).…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, "recall" responses were recently found in visual cortical networks following conditioning with a moving dot stimulus upon presentation of the first dot in the sequence (22). However, most previous visual cortex reactivation studies have been performed in anesthetized V1 or during sleep, where the spatial similarity between ongoing activity and stimulus-evoked response was either independent of stimulus history (42) or was observed immediately after stimulus offset (20). In contrast, we found clear evidence for reactivation in the awake state in V4 networks at the expected time of stimulus onset while monkeys performed a fixation task.…”

Section: Discussionmentioning

confidence: 99%

“…Although reactivation had originally been reported in the hippocampus as a mechanism of memory consolidation (12)(13)(14), it may constitute a fundamental property of neural ensembles in many brain areas. Indeed, in addition to hippocampus, reactivation has been reported in rat prefrontal cortex (15)(16)(17), motor and somatosensory cortex during quiescent awake states (18), rat primary visual cortex (V1) during slow-wave sleep (19), and rat and cat V1 immediately after stimulus presentation during anesthesia (20)(21)(22).…”

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confidence: 99%

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Image sequence reactivation in awake V4 networks

Eagleman

Dragoi

2012

Proc. Natl. Acad. Sci. U.S.A.

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In the absence of sensory input, neuronal networks are far from being silent. Whether spontaneous changes in ongoing activity reflect previous sensory experience or stochastic fluctuations in brain activity is not well understood. Here we describe reactivation of stimulusevoked activity in awake visual cortical networks. We found that continuous exposure to randomly flashed image sequences induces reactivation in macaque V4 cortical networks in the absence of visual stimulation. This reactivation of previously evoked activity is stimulusspecific, occurs only in the same temporal order as the original response, and strengthens with increased stimulus exposures. Importantly, cells exhibiting significant reactivation carry more information about the stimulus than cells that do not reactivate. These results demonstrate a surprising degree of experience-dependent plasticity in visual cortical networks as a result of repeated exposure to unattended information. We suggest that awake reactivation in visual cortex may underlie perceptual learning by passive stimulus exposure.electrophysiology | monkey

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Image sequence reactivation in awake V4 networks

Eagleman

Dragoi

2012

Proc. Natl. Acad. Sci. U.S.A.

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“…First, electrophysiological studies indicate that the reli-ability of the response of a neuron can vary greatly depending on the stimulus. Upon repeated presentations, certain stimuli elicit spikes at predictable, repeatable times whereas others, although they may elicit a similar average firing rate, do not drive the neuron in a precisely predictable way (Mainen and Sejnowski, 1995;Mechler et al, 1998;Yao et al, 2007). Response reliability (reproducibility) therefore offers a measure of how effectively a stimulus is driving activity that is complementary to the more common measure of response amplitude.…”

Section: Introductionmentioning

confidence: 99%

A Hierarchy of Temporal Receptive Windows in Human Cortex

et al. 2008

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Real-world events unfold at different time scales and, therefore, cognitive and neuronal processes must likewise occur at different time scales. We present a novel procedure that identifies brain regions responsive to sensory information accumulated over different time scales. We measured functional magnetic resonance imaging activity while observers viewed silent films presented forward, backward, or piecewise-scrambled in time. Early visual areas (e.g., primary visual cortex and the motion-sensitive area MTϩ) exhibited high response reliability regardless of disruptions in temporal structure. In contrast, the reliability of responses in several higher brain areas, including the superior temporal sulcus (STS), precuneus, posterior lateral sulcus (LS), temporal parietal junction (TPJ), and frontal eye field (FEF), was affected by information accumulated over longer time scales. These regions showed highly reproducible responses for repeated forward, but not for backward or piecewise-scrambled presentations. Moreover, these regions exhibited marked differences in temporal characteristics, with LS, TPJ, and FEF responses depending on information accumulated over longer durations (ϳ36 s) than STS and precuneus (ϳ12 s). We conclude that, similar to the known cortical hierarchy of spatial receptive fields, there is a hierarchy of progressively longer temporal receptive windows in the human brain.

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“…Complementary, as shown in voltage-sensitive dye imaging experiments, spatiotemporal patterns of activity do not merely reflect stochastic network fluctuations or internal noise sources, but can also be affected by the recent history of sensory experience (Kenet et al 2003, Han et al 2008, Yao et al 2007). Similar results were obtained from human BOLD fMRI data, which showed a robust and specific learning-related modulation of spontaneous activity (Lewis et al 2009).…”

Section: Introductionmentioning

confidence: 91%

Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model

et al. 2012

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While the neuronal activity of the cerebral cortex is strongly modulated by sensory inputs, the cortex also exhibits rich spontaneous dynamics. Experimental evidence suggests that sensory stimulation may shape the spontaneous activity of the cortex, which in turn can influence its responses to further external stimulation. However, we still do not understand how sensory stimuli affect the underlying neural circuitry. Here we study whether spike-timing-dependent plasticity (STDP) can mediate sensory-induced modifications in the spontaneous dynamics of a new large-scale model of layers II, III and IV of the rodent barrel cortex. A central feature of our model is its level of physiological detail, including the types of neurons present, the probabilities and delays of connections, and the STDP profiles at each excitatory synapse. We stimulated the neuronal network with a protocol of repeated sensory inputs, resembling those generated by the protraction-retraction motion of whiskers when rodents explore their environment, and studied the changes in network dynamics. By applying dimensionality reduction techniques to the synaptic weight space, we show that the trajectories converge to an initial spontaneous attractor state, which is modified by each repetition of the stimulus. This reverberation of the sensory experience induces long-term modifications in the synaptic weight space. The post-stimulus spontaneous state encodes a unique memory of the stimulus presented, since a different dynamical response is observed when the network is presented with shuffled stim- uli. These results suggest that repeated exposure to the same sensory experience could induce long-term circuitry modifications via 'Hebbian' STDP plasticity.

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Rapid learning in cortical coding of visual scenes

Cited by 116 publications

References 48 publications

Image sequence reactivation in awake V4 networks

Image sequence reactivation in awake V4 networks

A Hierarchy of Temporal Receptive Windows in Human Cortex

Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model

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