Statistical learning of visual transitions in monkey inferotemporal cortex
By T. Meyer, Carl Olson. 2011
298 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Jorie Koster-Hale
- Peter Kok
- Rebecca Saxe
- F. D. de Lange
- Floris P. de Lange
- Ana Todorovic
- Christopher Summerfield
- Micha Heilbron
Citations in the corpus
- Theory of Mind: A Neural Prediction Problem (2013, positive): “Error neurons are similarly distributed throughout the cortex and respond to specific stimulus features (Meyer and Olson, 2011; den Ouden et al., 2012), rather than, for example, a single ‘‘error region’’ signaling the overall amount of error or degree to which the observed stimulus is unpredicted (”
- Predictive Processing: A Canonical Cortical Computation (2018, unknown): “This is indeed the case when stimuli become predictable either as the result of a learned association with a preceding stimulus (Egner et al., 2010; Meyer and Olson, 2011), or after frequent presentation of the same stimulus, in which case the suppression is often described as sensory adaptation (Ul”
- How Do Expectations Shape Perception? (2018, methodology): “Such studies showed for instance that expectation suppression in macaque IT was associated with decreased decoding performance [66]; that BOLD responses in posterior superior temporal sulcus (pSTS) to expected words were weaker and contained less information, as quantified by representational simila”
- How Prediction Errors Shape Perception, Attention, and Motivation (2012, background): “…a transitional surprise effect in inferotemporal cortex, the terminus of the ventral stream, where object-selective neurons exhibited a much stronger response to unpredicted than predicted images after image transitions were learned by associative pairing (Meyer and Olson, 2011, Figure 1B).”
- The Visual System's Internal Model of the World (2015, background): “Recently, neurophysiological results have found that neurons in IT experienced more significant suppression when an incoming event is predicted than when such event is not predicted [94], [95].”
- Canonical microcircuits for predictive coding. (2012, unknown): “Furthermore, neurons in monkey inferotemporal cortex respond significantly less to a predicted sequence of natural images, compared to an unpredicted sequence (Meyer and Olson, 2011).”
- Concurrent Repetition Enhancement and Suppression Responses in Extrastriate Visual Cortex (2012, background): “Cerebral Cortex September 2013, V 23 N 9 2241”
- Less Is More: Expectation Sharpens Representations in the Primary Visual Cortex (2012, unknown): “This is in line with recent neurophysiological studies in monkeys and humans, highlighting that valid expectations lead to a reduction in spiking activity (Meyer and Olson, 2011) as well as gamma-band oscillatory activity (Todorovic et al., 2011).”
- Neural networks and neuroscience-inspired computer vision. (2014, background): “showed that responses of inferotemporal neurons to particular stimuli could be nearly completely suppressed if the animal learned to expect their appearance in a particular ordered sequence; these same stimuli evoked strong responses when seen out of the learned order [90].”
- Repetition Suppression and Expectation Suppression Are Dissociable in Time in Early Auditory Evoked Fields (2012, background): “Although this chicken-or-egg problem seems hard to resolve, a recent study (Meyer and Olson, 2011) suggests that ES may be a cause of, rather than consequence of, attentional capture.”
- A Hierarchy of Responses to Auditory Regularities in the Macaque Brain (2014, unknown): “In humans, many brain areas show a reduced activation to predictable sequences and an increased response to unexpected stimuli, thought to reflect a prediction error (Friston, 2005; Meyer and Olson, 2011; Wacongne et al., 2011, 2012; Sanmiguel et al., 2013).”