Sparse Representation in the Human Medial Temporal Lobe

By Stephen Waydo, Alexander Kraskov, R. Quian Quiroga, Itzhak Fried, Christof Koch. 2006

184 citations recorded by the source corpus.

Recent experiments characterized individual neurons in the human medial temporal lobe with remarkably selective, invariant, and explicit responses to images of famous individuals or landmark buildings. Here, we used a probabilistic analysis to show that these data are consistent with a sparse code in which neurons respond in a selective manner to a small fraction of stimuli.

Subfields: Cognitive Neuroscience

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In Cognitive Neuroscience

Citations in the corpus

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect (2014, background): “In particular, sparse activity patterns [82] cannot be stored at a low connectivity, e.”
Neural Associative Memory with Optimal Bayesian Learning (2011, unknown): “This suggests that the linear covariance rule is not always optimal, in particular not for finite networks and sparse memory representations as found in the brain (Waydo, Kraskov, Quiroga, Fried, & Koch, 2006 ).”
The Operating Point of the Cortex: Neurons as Large Deviation Detectors (2007, background): “This may explain the remarkable finding that some cells in high visual areas of human cortex show surprisingly high sparseness and selectivity (Quiroga et al., 2005; Waydo et al., 2006).”
Grandmother cells and localist representations: a review of current thinking (2017, background): “As detailed by Gubian et al. (2016) and Page (2016), localist models can account for the levels of selectivity reported Waydo et al. (2006), and can explain the number of stimuli that can be represented and identified by a population of neurons.”
Sparse but not ‘ Grandmother-cell ’ coding in the medial temporal lobe (2008, unknown): “27 Waydo, S. et al. (2006) Sparse representation in the human medial temporal lobe.”
Optimal synaptic learning in non-linear associative memory (2010, background): “Only for linearly or non- sparse patterns performance drops to the capacity of the original Hopfield network (e.g., C = 0.14bps [30], [35] or rather C = 0.33bps for “hetero-associative” feed-forward networks considered here [44]).”
Locating object knowledge in the brain: comment on Bowers's (2009) attempt to revive the grandmother cell hypothesis. (2010, background): “Waydo et al.’s (2006) analysis derived a measure a defined to”
The Packet Switching Brain (2011, unknown): “6 Indeed, sparseness itself is thought to be required for metabolic and other efficiency-related reasons (Waydo, Kraskov, Quian Quiroga, Fried, & Koch, 2006; Lennie, 2003; Attwell & Laughlin, 2001).”
Explicit encoding of multimodal percepts by single neurons in the human brain. (2009, unknown): “Each concept must activate a population of MTL cells, because if out of perhaps a billion MTL cells we do find a neuron firing to Oprah Winfrey (for example), there should be more [9, 37, 38].”
Unsupervised Learning of Individuals and Categories from Images (2008, background): “Neurons have been identified in the human medial temporal lobe (MTL) that display a strong selectivity for only a few stimuli (such as familiar individuals or landmark buildings) out of perhaps 100 presented to epileptic patients (Quian Quiroga, Reddy, Kreiman, Koch, & Fried, 2005; Waydo, Kraskov, ”