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Short-term memory trace in rapidly adapting synapses of inferior temporal cortex.

Sugase-Miyamoto Y, Liu Z, Wiener MC, Optican LM, Richmond BJ - PLoS Comput. Biol. (2008)

Bottom Line: We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval.Neurons in perirhinal cortex did not show this correlation.Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.

ABSTRACT
Visual short-term memory tasks depend upon both the inferior temporal cortex (ITC) and the prefrontal cortex (PFC). Activity in some neurons persists after the first (sample) stimulus is shown. This delay-period activity has been proposed as an important mechanism for working memory. In ITC neurons, intervening (nonmatching) stimuli wipe out the delay-period activity; hence, the role of ITC in memory must depend upon a different mechanism. Here, we look for a possible mechanism by contrasting memory effects in two architectonically different parts of ITC: area TE and the perirhinal cortex. We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval. During a sequential delayed matching-to-sample task (DMS), the noise in the neuronal response to the test image was correlated with the noise in the neuronal response to the sample image. Neurons in perirhinal cortex did not show this correlation. These results led us to hypothesize that area TE contributes to short-term memory by acting as a matched filter. When the sample image appears, each TE neuron captures a static copy of its inputs by rapidly adjusting its synaptic weights to match the strength of their individual inputs. Input signals from subsequent images are multiplied by those synaptic weights, thereby computing a measure of the correlation between the past and present inputs. The total activity in area TE is sufficient to quantify the similarity between the two images. This matched filter theory provides an explanation of what is remembered, where the trace is stored, and how comparison is done across time, all without requiring delay period activity. Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory.

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Example of matched filter output computation.The top row shows input images. The memory trace of the model is simulated with the discrete Fourier Transform of the input, plus noise (middle row). (Noise is not very noticeable, because of the logarithmic scaling). Bottom row shows the product of the memory trace and the match and nonmatch inputs. The output power is shown on the left.
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pcbi-1000073-g008: Example of matched filter output computation.The top row shows input images. The memory trace of the model is simulated with the discrete Fourier Transform of the input, plus noise (middle row). (Noise is not very noticeable, because of the logarithmic scaling). Bottom row shows the product of the memory trace and the match and nonmatch inputs. The output power is shown on the left.

Mentions: Above, predicted responses were computed from the average responses of the experimental data. To simulate the DMS task with a matched filter model with noise on a trial-by-trial basis, we need to generate an encoder output. For simplicity, we chose the discrete Fourier transform (DFT) to represent the encoder. Each 8×8 stimulus was placed on a 16×16 gray background. The stimuli (Figure 8, top row) were first converted to their 16×16 DFTs (Figure 8, middle row). Each DFT image thus represents activity in 256 encoder cells (represented as a vector of length 256). The output of the model is just the dot product of the sample and test responses (Figure 8, bottom row. NB: the luminance levels in the figure are a poor indicator of their importance, because of the log transformation used in plotting). The average output power (calculated using root-sum-of-squares of population activity, with the brightest pixel across all stimulus pairs normalized to 1.0) across the entire population is given on the left (0.452 for the match, and 0.149 for the nonmatch case).


Short-term memory trace in rapidly adapting synapses of inferior temporal cortex.

Sugase-Miyamoto Y, Liu Z, Wiener MC, Optican LM, Richmond BJ - PLoS Comput. Biol. (2008)

Example of matched filter output computation.The top row shows input images. The memory trace of the model is simulated with the discrete Fourier Transform of the input, plus noise (middle row). (Noise is not very noticeable, because of the logarithmic scaling). Bottom row shows the product of the memory trace and the match and nonmatch inputs. The output power is shown on the left.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2366068&req=5

pcbi-1000073-g008: Example of matched filter output computation.The top row shows input images. The memory trace of the model is simulated with the discrete Fourier Transform of the input, plus noise (middle row). (Noise is not very noticeable, because of the logarithmic scaling). Bottom row shows the product of the memory trace and the match and nonmatch inputs. The output power is shown on the left.
Mentions: Above, predicted responses were computed from the average responses of the experimental data. To simulate the DMS task with a matched filter model with noise on a trial-by-trial basis, we need to generate an encoder output. For simplicity, we chose the discrete Fourier transform (DFT) to represent the encoder. Each 8×8 stimulus was placed on a 16×16 gray background. The stimuli (Figure 8, top row) were first converted to their 16×16 DFTs (Figure 8, middle row). Each DFT image thus represents activity in 256 encoder cells (represented as a vector of length 256). The output of the model is just the dot product of the sample and test responses (Figure 8, bottom row. NB: the luminance levels in the figure are a poor indicator of their importance, because of the log transformation used in plotting). The average output power (calculated using root-sum-of-squares of population activity, with the brightest pixel across all stimulus pairs normalized to 1.0) across the entire population is given on the left (0.452 for the match, and 0.149 for the nonmatch case).

Bottom Line: We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval.Neurons in perirhinal cortex did not show this correlation.Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.

ABSTRACT
Visual short-term memory tasks depend upon both the inferior temporal cortex (ITC) and the prefrontal cortex (PFC). Activity in some neurons persists after the first (sample) stimulus is shown. This delay-period activity has been proposed as an important mechanism for working memory. In ITC neurons, intervening (nonmatching) stimuli wipe out the delay-period activity; hence, the role of ITC in memory must depend upon a different mechanism. Here, we look for a possible mechanism by contrasting memory effects in two architectonically different parts of ITC: area TE and the perirhinal cortex. We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval. During a sequential delayed matching-to-sample task (DMS), the noise in the neuronal response to the test image was correlated with the noise in the neuronal response to the sample image. Neurons in perirhinal cortex did not show this correlation. These results led us to hypothesize that area TE contributes to short-term memory by acting as a matched filter. When the sample image appears, each TE neuron captures a static copy of its inputs by rapidly adjusting its synaptic weights to match the strength of their individual inputs. Input signals from subsequent images are multiplied by those synaptic weights, thereby computing a measure of the correlation between the past and present inputs. The total activity in area TE is sufficient to quantify the similarity between the two images. This matched filter theory provides an explanation of what is remembered, where the trace is stored, and how comparison is done across time, all without requiring delay period activity. Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory.

Show MeSH
Related in: MedlinePlus