Raposo et al., 2012 - Google Patents
Multisensory decision-making in rats and humansRaposo et al., 2012
View PDF- Document ID
- 7856757476256197599
- Author
- Raposo D
- Sheppard J
- Schrater P
- Churchland A
- Publication year
- Publication venue
- Journal of neuroscience
External Links
Snippet
We report a novel multisensory decision task designed to encourage subjects to combine information across both time and sensory modalities. We presented subjects, humans and rats, with multisensory event streams, consisting of a series of brief auditory and/or visual …
- 241000700159 Rattus 0 title abstract description 81
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Raposo et al. | Multisensory decision-making in rats and humans | |
| Schölvinck et al. | Cortical state determines global variability and correlations in visual cortex | |
| Downer et al. | Task engagement selectively modulates neural correlations in primary auditory cortex | |
| Konishi et al. | When attention wanders: Pupillometric signatures of fluctuations in external attention | |
| Farley et al. | Everyday attention and lecture retention: the effects of time, fidgeting, and mind wandering | |
| Abrams et al. | Auditory brainstem timing predicts cerebral asymmetry for speech | |
| Freedman et al. | Distinct encoding of spatial and nonspatial visual information in parietal cortex | |
| Swaminathan et al. | Preferential encoding of visual categories in parietal cortex compared with prefrontal cortex | |
| Werner et al. | Distinct functional contributions of primary sensory and association areas to audiovisual integration in object categorization | |
| Powers et al. | Perceptual training narrows the temporal window of multisensory binding | |
| Sugihara et al. | Integration of auditory and visual communication information in the primate ventrolateral prefrontal cortex | |
| Jahfari et al. | Responding with restraint: what are the neurocognitive mechanisms? | |
| Neil et al. | Development of multisensory spatial integration and perception in humans | |
| Rao et al. | Neural correlates of prior expectations of motion in the lateral intraparietal and middle temporal areas | |
| Havenith et al. | Synchrony makes neurons fire in sequence, and stimulus properties determine who is ahead | |
| Mills et al. | ADHD and attentional control: Impaired segregation of task positive and task negative brain networks | |
| Nath et al. | Neural correlates of interindividual differences in children's audiovisual speech perception | |
| Paavilainen et al. | Preattentive detection of nonsalient contingencies between auditory features | |
| Laurent et al. | Neural correlates of hypothalamic-pituitary-adrenal regulation of mothers with their infants | |
| Snyder et al. | Dynamics of excitatory and inhibitory networks are differentially altered by selective attention | |
| Deike et al. | The build-up of auditory stream segregation: a different perspective | |
| Wen et al. | Time course of dynamic range adaptation in the auditory nerve | |
| Deneux et al. | Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities | |
| Harris et al. | Accounting for taste: a multi-attribute neurocomputational model explains the neural dynamics of choices for self and others | |
| Tschentscher et al. | Fluid intelligence predicts novel rule implementation in a distributed frontoparietal control network |