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Cognitive neuroscienceThe Neural Mind
Contents and reading path

Chapter 2

Sensation, Perception and Action

  1. 2.1How does the world become an experience?
  2. 2.2From stimulation to nerve signals
  3. 2.3Vision and visual perception
  4. 2.4Hearing and the direction of sound
  5. 2.5When the senses work together
  6. 2.6The cup in a noisy café
  7. 2.7How does a movement take shape?
  8. 2.8Prediction, feedback and learning
  9. LabThe visual lab

Perception and motor learning – in preparation

Reading path
Coming chapters (planned content)
  1. 1. Introduction to Cognitive Neuroscience
  2. 3. Attention
  3. 4. Memory and Learning
  4. 5. Language
  5. 6. Thinking and Executive Functions
  6. 7. Decision-Making
  7. 8. Emotion and Motivation
  8. 9. Social Cognition
  9. 10. Metacognition and Consciousness

Chapter 2

Sources and figures

The book's explanations draw on neuroscience research and scientific reviews. The references below offer further reading on the mechanisms and experiments behind the text. Figures and models help explain the concepts but are not themselves research data.

Scientific references

  • Gauthier, J. L. et al. (2009). Receptive Fields in Primate Retina Are Coordinated to Sample Visual Space More Uniformly. PLoS Biology, 7(4), e1000063. Link ↗ (new tab)Recordings in isolated peripheral macaque retina, from ON/OFF midget and parasol populations. Supports collective spatial sampling and overlapping receptive fields, not a direct demonstration of human object recognition or the lab's exact subtraction.
  • Johansson, R. S. & Vallbo, A. B. (1980). Spatial properties of the population of mechanoreceptive units in the glabrous skin of the human hand. Brain Research, 184(2), 353–366. Link ↗ (new tab)Recordings of afferents from human glabrous hand skin and a population model. Supports the relationship of field size, density and coverage to tactile spatial information, not retinal centre–surround wiring in all skin afferents.
  • Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception & Psychophysics, 14, 201–211. DOI: 10.3758/BF03212378. Link ↗ (new tab)The original point-light study. The book's 15-point animation is an original schematic – not Johansson's recorded stimuli, motion capture or a psychophysical replication.
  • Atkinson, A. P., Dittrich, W. H., Gemmell, A. J. & Young, A. W. (2004). Emotion perception from dynamic and static body expressions in point-light and full-light displays. Perception, 33(6), 717–746. DOI: 10.1068/p5096. Link ↗ (new tab)Behavioural experiments with actors' portrayed emotions and covered faces, classified with forced choices. Not certain recognition of felt inner emotion, and no validation of the book's gait or speeds.
  • de Gelder, B., Snyder, J., Greve, D., Gerard, G. & Hadjikhani, N. (2004). Fear fosters flight: A mechanism for fear contagion when perceiving emotion expressed by a whole body. PNAS, 101(47), 16701–16706. DOI: 10.1073/pnas.0407042101. Link ↗ (new tab)Human fMRI with still whole-body images and blanked faces. Co-occurring activity in affect-, visual- and action-related regions – an association, not a directed chain or a single necessary region.
  • Aviezer, H., Trope, Y. & Todorov, A. (2012). Body cues, not facial expressions, discriminate between intense positive and negative emotions. Science, 338(6111), 1225–1229. DOI: 10.1126/science.1224313. Link ↗ (new tab)Behavioural experiments with intense facial expressions and face–body composites. The book's thought comparison with the same gait and different stories is not that paradigm.
  • Kuffler, S. W. (1953). Discharge patterns and functional organization of mammalian retina. Journal of Neurophysiology, 16(1), 37–68. DOI: 10.1152/jn.1953.16.1.37. Link ↗ (new tab)Classic physiological recordings from cat ganglion cells: antagonistic centre/surround regions and variable responses. Not evidence for the model's exact balanced subtraction or all human ganglion cells.
  • Ströh, S. et al. (2018). Eliminating Glutamatergic Input onto Horizontal Cells Changes the Dynamic Range and Receptive Field Organization of Mouse Retinal Ganglion Cells. Journal of Neuroscience. DOI: 10.1523/JNEUROSCI.0141-17.2018. Link ↗ (new tab)Primary mouse experiment: eliminating glutamate receptors on horizontal cells altered surround structure in transient OFF-alpha ganglion cells. Supports horizontal-circuit contributions alongside amacrine circuits, not a universal human circuit.
  • Courtiol, E. & Wilson, D. A. (2015). The olfactory thalamus: unanswered questions about the role of the mediodorsal thalamic nucleus in olfaction. Frontiers in Neural Circuits. Link ↗ (new tab)The early olfactory bulb–cortex pathway lacks an initial thalamic relay; the thalamus participates in later olfactory processing.
  • Guinan, J. J., Jr. (2010). Cochlear Efferent Innervation and Function. Current Opinion in Otolaryngology & Head and Neck Surgery. Link ↗ (new tab)Review of olivocochlear systems: MOC to outer hair cells, LOC to auditory nerve fibres near inner hair cells.
  • Chawla, D., Rees, G., & Friston, K. J. (1999). The physiological basis of attentional modulation in extrastriate visual areas. Nature Neuroscience, 2, 671–676. Link ↗ (new tab)Human fMRI: attention to colour and motion. The task figure contains no measured activity values.
  • McAlonan, K., Cavanaugh, J., & Wurtz, R. H. (2008). Guarding the gateway to cortex with attention in visual thalamus. Nature, 456, 391–394. Link ↗ (new tab)Attending macaques: modulation of magno- and parvocellular LGN responses, not control of human photoreceptors.
  • Erişir, A., Van Horn, S. C., & Sherman, S. M. (1997). Relative numbers of cortical and brainstem inputs to the lateral geniculate nucleus. PNAS, 94, 1517–1520. Link ↗ (new tab)Cat anatomy: distinguishes cortical and brainstem inputs. Synaptic contacts are not signal traffic.
  • Van Horn, S. C., Erişir, A., & Sherman, S. M. (2000). Relative distribution of synapses in the A-laminae of the lateral geniculate nucleus of the cat. Journal of Comparative Neurology, 416, 509–520. Link ↗ (new tab)Synapses in cat LGN. The RS category also includes brainstem inputs and must not be equated with cortex; read alongside Erişir et al.
  • Gastinger, M. J., O'Brien, J. J., Larsen, N. B., & Marshak, D. W. (1999). Histamine immunoreactive axons in the macaque retina. Investigative Ophthalmology & Visual Science, 40, 487–495. Link ↗ (new tab)Sparse brain-origin retinal fibres in macaques; does not demonstrate conscious cortical control of human photoreceptors.
  • Dragicevic, C. D., et al. (2015). The olivocochlear reflex strength and cochlear sensitivity are independently modulated by auditory cortex microstimulation. Journal of the Association for Research in Otolaryngology, 16, 223–240. Link ↗ (new tab)Cortical microstimulation in chinchillas: peripheral auditory influence through descending systems. MOC contacts outer hair cells; LOC auditory afferents. Not a measure of voluntary human attention.
  • Purves, D. et al. (eds., 2001). Neuroscience (2nd ed.). Neural Centers Responsible for Movement. Link ↗ (new tab)Interacting motor systems, descending influences and spinal circuits.
  • Purves, D. et al. (eds., 2001). Neuroscience (2nd ed.). The Motor Unit. Link ↗ (new tab)Alpha motor neurons and the skeletal muscle fibres they innervate.
  • Purves, D. et al. (eds., 2001). Neuroscience (2nd ed.). Mechanoreceptors Specialized for Proprioception. Link ↗ (new tab)Sensory information from muscles and tendons about the body.
  • Wolpert, D. M., Miall, R. C. & Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9), 338–347. DOI: 10.1016/S1364-6613(98)01221-2. Link ↗ (new tab)A model-based account of prediction and cerebellar contributions, not a direct anatomical map.
  • Shadmehr, R., Smith, M. A. & Krakauer, J. W. (2010). Error correction, sensory prediction, and adaptation in motor control. Annual Review of Neuroscience, 33, 89–108. DOI: 10.1146/annurev-neuro-060909-153135. Link ↗ (new tab)Review of feedback, sensory prediction and motor adaptation.
  • Tseng, Y.-W., Diedrichsen, J., Krakauer, J. W., Shadmehr, R. & Bastian, A. J. (2007). Sensory prediction errors drive cerebellum-dependent adaptation of reaching. Journal of Neurophysiology, 98(1), 54–62. DOI: 10.1152/jn.00266.2007. Link ↗ (new tab)Sensory prediction errors and cerebellum-dependent adaptation under visuomotor perturbations of reaching; not all forms of learning.
  • Bostan, A. C. & Strick, P. L. (2018). The basal ganglia and the cerebellum: nodes in an integrated network. Nature Reviews Neuroscience, 19(6), 338–350. DOI: 10.1038/s41583-018-0002-7. Link ↗ (new tab)An integrated-network perspective on basal ganglia, cerebellum and cortex; not an exhaustive atlas.
  • Funahashi, S., Bruce, C. J. & Goldman-Rakic, P. S. (1989). Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. Journal of Neurophysiology, 61(2), 331–349. DOI: 10.1152/jn.1989.61.2.331. Link ↗ (new tab)Macaque recordings in and around the principal sulcus: activity for a remembered location during a delay. Does not apply to every area 46 cell and shows no new connections.
  • Takada, M. et al. (2004). Organization of prefrontal outflow toward frontal motor-related areas in macaque monkeys. European Journal of Neuroscience, 19(12), 3328–3342. DOI: 10.1111/j.0953-816X.2004.03425.x. Link ↗ (new tab)Tracer study in Japanese macaques: area 46 reaches pre-SMA and the rostral cingulate motor area (CMAr) mainly indirectly via rostral dorsal and ventral premotor areas; direct projections to pre-SMA and CMAr are sparse. The study is used here to explain the continuation towards motor networks.
  • Suzuki, W. A. & Amaral, D. G. (1994). Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. Journal of Comparative Neurology, 350(4), 497–533. DOI: 10.1002/cne.903500402. Link ↗ (new tab)Macaque: TF and TH receive different mixtures of cortical input; TH receives very little from TE and TEO. No general new classification.
  • Suzuki, W. A. & Amaral, D. G. (1994). Topographic organization of the reciprocal connections between the monkey entorhinal cortex and the perirhinal and parahippocampal cortices. Journal of Neuroscience, 14(3 Pt 2), 1856–1877. DOI: 10.1523/JNEUROSCI.14-03-01856.1994. Link ↗ (new tab)Macaque tracer study: reciprocal connections between parahippocampal and entorhinal cortex at a regional level. The map's grouped areas are not subdivided here.
  • Witter, M. P. & Amaral, D. G. (1991). Entorhinal cortex of the monkey: V. Projections to the dentate gyrus, hippocampus, and subicular complex. Journal of Comparative Neurology, 307(3), 437–459. DOI: 10.1002/cne.903070308. Link ↗ (new tab)Macaque: projections from entorhinal cortex to the dentate gyrus, hippocampus and subicular complex.
  • Witter, M. P. & Amaral, D. G. (2021). The entorhinal cortex of the monkey: VI. Organization of projections from the hippocampus, subiculum, presubiculum, and parasubiculum. Journal of Comparative Neurology, 529(4), 828–852. DOI: 10.1002/cne.24983. Link ↗ (new tab)Macaque: return projections from the hippocampus and subicular areas to entorhinal cortex.
  • Derrington, A. M. & Lennie, P. (1984). Spatial and temporal contrast sensitivities of neurones in lateral geniculate nucleus of macaque. The Journal of Physiology, 357, 219–240. DOI: 10.1113/jphysiol.1984.sp015498. Link ↗ (new tab)Primary macaque recordings: relative spatial, temporal and contrast-related M/P properties; no universal numerical cutoffs.
  • Zhou, H., Friedman, H. S. & von der Heydt, R. (2000). Coding of border ownership in monkey visual cortex. Journal of Neuroscience, 20, 6594–6611. DOI: 10.1523/JNEUROSCI.20-17-06594.2000. Link ↗ (new tab)Primary macaque recordings: V2/V4 responses to which side of an edge belongs to a figure, depending on surrounding configuration.
  • Pasupathy, A. & Connor, C. E. (1999). Responses to contour features in macaque area V4. Journal of Neurophysiology, 82, 2490–2502. DOI: 10.1152/jn.1999.82.5.2490. Link ↗ (new tab)Primary macaque V4 recordings: selectivity for curvature and angles of contour features; not a solitary colour or shape centre.
  • Xu, X., Ichida, J. M., Allison, J. D., Boyd, J. D., Bonds, A. B. & Casagrande, V. A. (2001). A comparison of koniocellular, magnocellular and parvocellular receptive field properties in the lateral geniculate nucleus of the owl monkey (Aotus trivirgatus). The Journal of Physiology, 531, 203–218. DOI: 10.1111/j.1469-7793.2001.0203j.x. Link ↗ (new tab)Primary owl-monkey (Aotus trivirgatus) study: varied K properties compared with M/P. No universal human K profile; retinal inputs and V1 targets use Callaway’s primate review.
  • Callaway, E. M. (2005). Structure and function of parallel pathways in the primate early visual system. The Journal of Physiology, 566(1), 13–19. DOI: 10.1113/jphysiol.2005.088047. Link ↗ (new tab)Review of parvocellular, magnocellular and koniocellular pathways from retina via LGN to V1 (primate, review article).
  • Berman, R. A. & Wurtz, R. H. (2010). Functional identification of a pulvinar path from superior colliculus to cortical area MT. Journal of Neuroscience, 30(18), 6342–6354. Link ↗ (new tab)Macaque electrophysiology: the superior colliculus → inferior pulvinar → area MT pathway.
  • Purushothaman, G., Marion, R., Li, K. & Casagrande, V. A. (2012). Gating and control of primary visual cortex by pulvinar. Nature Neuroscience, 15, 905–912. DOI: 10.1038/nn.3106. Link ↗ (new tab)Study in galago (a prosimian primate): lateral pulvinar influences V1. Not directly shown in humans or macaques.
  • Saalmann, Y. B. et al. (2012). The pulvinar regulates information transmission between cortical areas based on attention demands. Science, 337(6095), 753–756. DOI: 10.1126/science.1223082. Link ↗ (new tab)Monkey recordings: the pulvinar participates in attention-dependent regulation between cortical areas.
  • Briggs, F. & Usrey, W. M. (2007). A fast, reciprocal pathway between the lateral geniculate nucleus and visual cortex in the macaque monkey. Journal of Neuroscience, 27(20), 5431–5436. Link ↗ (new tab)Macaque: a fast, reciprocal connection between LGN and cortex – the basis of corticogeniculate feedback.
  • Hupé, J. M. et al. (1998). Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons. Nature, 394, 784–787. DOI: 10.1038/29537. Link ↗ (new tab)Macaque: inactivating area V5 changed figure–background responses in V1–V3, an example of feedback's contribution.
  • Felleman, D. J. & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1(1), 1–47. DOI: 10.1093/cercor/1.1.1-a. Link ↗ (new tab)Synthesis of macaque cortical connectivity; a compilation of monkey data, not a human atlas.
  • Markov, N. T. et al. (2014). Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. Journal of Comparative Neurology, 522(1), 225–259. DOI: 10.1002/cne.23458. Link ↗ (new tab)Modern quantitative laminar mapping refining the classic hierarchy; a methodological note, not a basis for extra edges.
  • Winawer, J. & Witthoft, N. (2015). Human V4 and ventral occipital retinotopic maps. Visual Neuroscience, 32, E020. DOI: 10.1017/S0952523815000176. Link ↗ (new tab)Review: modern human parcellations (hV4, VO-1, VO-2) differ from the historical designation V8.
  • Hadjikhani, N. et al. (1998). Retinotopy and color sensitivity in human visual cortical area V8. Nature Neuroscience, 1, 235–241. DOI: 10.1038/681. Link ↗ (new tab)Human fMRI study that introduced the designation V8 for a ventral retinotopic map.
  • Pitzalis, S. et al. (2006). Wide-field retinotopy defines human cortical visual area V6. Journal of Neuroscience, 26(30), 7962–7973. Link ↗ (new tab)Human fMRI: area V6 with a wide-field representation in the medial parieto-occipital region.
  • Swisher, J. D. et al. (2007). Visual topography of human intraparietal sulcus. Journal of Neuroscience, 27(20), 5326–5337. DOI: 10.1523/JNEUROSCI.0991-07.2007. Link ↗ (new tab)Human fMRI: retinotopic maps in the intraparietal sulcus, including IPS0, often called V7.
  • Grossman, E. D., Battelli, L. & Pascual-Leone, A. (2005). Repetitive TMS over posterior STS disrupts perception of biological motion. Vision Research, 45(22), 2847–2853. DOI: 10.1016/j.visres.2005.05.027. Link ↗ (new tab)Human TMS study: posterior STS contributes to the perception of biological motion.
  • Kriegeskorte, N. et al. (2008). Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron, 60(6), 1126–1141. Link ↗ (new tab)Comparison of object representations in inferior temporal cortex in humans and monkeys.
  • Pitcher, D. & Ungerleider, L. G. (2021). Evidence for a third visual pathway specialized for social perception. Trends in Cognitive Sciences, 25(2), 100–110. DOI: 10.1016/j.tics.2020.11.006. Link ↗ (new tab)Review proposing a third, lateral visual pathway towards the STS for social perception. Draws on anatomical and functional evidence from several species; the route runs via intervening areas such as MST/FST and is not a proven direct human projection. Authors' full text: https://www-users.york.ac.uk/~dp859/Pitcher_Lab/Welcome_files/2021_Pitcher_Ungerleider.pdf
  • Pitcher, D. (2014). Facial Expression Recognition Takes Longer in the Posterior Superior Temporal Sulcus than in the Occipital Face Area. Journal of Neuroscience, 34(27), 9173–9177. DOI: 10.1523/JNEUROSCI.5038-13.2014. Link ↗ (new tab)Human TMS study: temporarily disrupting right pSTS impaired matching facial expressions in photographs, while the matched identity task was unaffected. The stimuli were still images.
  • Basil, R. A., Westwater, M. L., Wiener, M. & Thompson, J. C. (2017). A Causal Role of the Right Superior Temporal Sulcus in Emotion Recognition From Biological Motion. Open Mind, 2(1), 26–36. DOI: 10.1162/opmi_a_00015. Link ↗ (new tab)Primary human cTBS study with individual fMRI localisation of right pSTS: emotion recognition from point-light body movements was impaired, while a non-biological global-motion control was not.
  • Felleman, D. J. & Van Essen, D. C. (1987). Receptive field properties of neurons in area V3 of macaque monkey extrastriate cortex. Journal of Neurophysiology, 57(4), 889–920. DOI: 10.1152/jn.1987.57.4.889. Link ↗ (new tab)Primary recordings in anaesthetized macaques, dorsal V3 as defined then; orientation/direction/binocular-disparity selectivity (proportions do not transfer to humans or all V3 maps).
  • Gegenfurtner, K. R., Kiper, D. C. & Levitt, J. B. (1997). Functional properties of neurons in macaque area V3. Journal of Neurophysiology, 77(4), 1906–1923. DOI: 10.1152/jn.1997.77.4.1906. Link ↗ (new tab)Primary macaque recordings; overlap of chromatic and motion responses, including direction-sensitive responses to isoluminant gratings. Supports interacting feature processing, not independent M/P/K streams or a unique human V3 function.
  • McAdams, C. J. & Maunsell, J. H. R. (1999). Effects of attention on orientation-tuning functions of single neurons in macaque cortical area V4. Journal of Neuroscience, 19(1), 431–441. DOI: 10.1523/JNEUROSCI.19-01-00431.1999. Link ↗ (new tab)Attention to a stimulus in vs outside the receptive field modulated responses without systematically narrowing orientation tuning. It does not show that attention universally sharpens tuning, nor did this study compare attending to colour vs shape.
  • Ruff, C. C. et al. (2008). Distinct causal influences of parietal versus frontal areas on human visual cortex: evidence from concurrent TMS–fMRI. Cerebral Cortex, 18(4), 817–827. Link ↗ (new tab)Human TMS–fMRI, network influence: stimulating the IPS changes activity in V5/MT+ and V1–V4. Supports an influence through networks, not a monosynaptic tract.
  • Hubel, D. H. & Wiesel, T. N. (1974). Sequence regularity and geometry of orientation columns in the monkey striate cortex. Journal of Comparative Neurology, 158(3), 267–293. DOI: 10.1002/cne.901580304. Link ↗ (new tab)Macaque: how orientation preference changes across the cortical surface. A classical organisational description, not a regular grid or a map measured for this book.
  • Dougherty, K., Cox, M. A., Westerberg, J. A. & Maier, A. (2019). Binocular modulation of monocular V1 neurons. Current Biology, 29(3), 381–391.e4. DOI: 10.1016/j.cub.2018.12.004. Link ↗ (new tab)Macaque laminar recordings: even input-layer neurons driven by one eye can be binocularly modulated. No figures from the study are used here.
  • Pack, C. C., Livingstone, M. S., Duffy, K. R. & Born, R. T. (2003). End-stopping and the aperture problem: two-dimensional motion signals in macaque V1. Neuron, 39(4), 671–680. DOI: 10.1016/S0896-6273(03)00439-2. Link ↗ (new tab)Macaque V1: end-stopping and contour endpoints in motion processing. The static comparison does not simulate these experiments.
  • Yazdanbakhsh, A. & Livingstone, M. S. (2006). End stopping in V1 is sensitive to contrast. Nature Neuroscience, 9(5), 697–702. DOI: 10.1038/nn1693. Link ↗ (new tab)Macaque V1 complex cells: length sensitivity depends on relative end-zone contrast. End-stopping also occurs in simple cells.
  • Horton, J. C. & Hoyt, W. F. (1991). The representation of the visual field in human striate cortex. A revision of the classic Holmes map. Archives of Ophthalmology, 109, 816–824. DOI: 10.1001/archopht.1991.01080060080030. Link ↗ (new tab)Human map revised using visual-field defects and MRI-defined lesions. Supports retinotopy and central magnification, not universal V1 percentages.
  • Duncan, R. O. & Boynton, G. M. (2003). Cortical magnification within human primary visual cortex correlates with acuity thresholds. Neuron, 38, 659–671. DOI: 10.1016/S0896-6273(03)00265-4. Link ↗ (new tab)Same human observers: linear V1 magnification with fMRI and psychophysical acuity. A relationship, not evidence that V1 alone determines acuity; the measure is mm/degree.
  • Benson, N. C., Yoon, J. M. D., Forenzo, D., Engel, S. A., Kay, K. N. & Winawer, J. (2022). Variability of the Surface Area of the V1, V2, and V3 Maps in a Large Sample of Human Observers. Journal of Neuroscience, 42, 8629–8646. DOI: 10.1523/JNEUROSCI.0690-21.2022. Link ↗ (new tab)181 human observers: variability in V1–V3 map areas and relative central magnification. A limited retinotopically mapped region, not whole-V1 surface area; no universal exact shares inferred.
  • Hubel, D. H. & Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. Journal of Physiology, 160, 106–154. DOI: 10.1113/jphysiol.1962.sp006837. Link ↗ (new tab)Single cells in cat visual cortex: the description of simple and complex receptive fields. Not a universal human circuit.
  • Hubel, D. H. & Wiesel, T. N. (1968). Receptive fields and functional architecture of monkey striate cortex. Journal of Physiology, 195, 215–243. DOI: 10.1113/jphysiol.1968.sp008455. Link ↗ (new tab)Monkey physiology: orientation selectivity and columnar organisation. The authors note that a strict hierarchy may be an oversimplification.
  • Hubel, D. H. & Wiesel, T. N. (1974). Uniformity of monkey striate cortex: A parallel relationship between field size, scatter, and magnification factor. Journal of Comparative Neurology, 158, 295–305. DOI: 10.1002/cne.901580305. Link ↗ (new tab)Monkey: relationship between field size, scatter and cortical magnification. Used for the concept; no exact fractions.
  • Dumoulin, S. O. & Wandell, B. A. (2008). Population receptive field estimates in human visual cortex. NeuroImage, 39, 647–660. DOI: 10.1016/j.neuroimage.2007.09.034. Link ↗ (new tab)Human fMRI: retinotopic maps and population fields that grow with eccentricity. A voxel is not an individual neuron.
  • Adelson, E. H. & Bergen, J. R. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America A, 2(2), 284–299. Link ↗ (new tab)Computational model, not a physiological measurement. The lab's static spatial amplitude is a simplified adaptation of the model family, not their motion model.
  • Wheatstone, C. (1838). Contributions to the physiology of vision.—Part the first. On some remarkable, and hitherto unobserved, phenomena of binocular vision. Philosophical Transactions of the Royal Society of London, 128, 371–394. DOI: 10.1098/rstl.1838.0019. Link ↗ (new tab)Historical geometric experiments with binocular images; obsolete absolute physiological claims are not adopted here.
  • Julesz, B. (1964). Binocular depth perception without familiarity cues. Science, 145(3630), 356–362. DOI: 10.1126/science.145.3630.356. Link ↗ (new tab)Human random-dot psychophysics: disparity-based depth without prior recognition of familiar objects.
  • Cumming, B. G. & Parker, A. J. (2000). Local disparity not perceived depth is signaled by binocular neurons in cortical area V1 of the macaque. Journal of Neuroscience, 20(12), 4758–4767. DOI: 10.1523/JNEUROSCI.20-12-04758.2000. Link ↗ (new tab)Macaque V1 single-unit recordings with locally ambiguous gratings; distinguishes local disparity from perceived depth, not human neuronal recordings.
  • Hillis, J. M., Watt, S. J., Landy, M. S. & Banks, M. S. (2004). Slant from texture and disparity cues: optimal cue combination. Journal of Vision, 4(12), 967–992. DOI: 10.1167/4.12.1. Link ↗ (new tab)Human psychophysics: slant judgments and reliability-weighted texture/disparity combination under the study’s conditions, not universal optimality.
  • Gordon, J. & Shapley, R. (2006). Brightness contrast inhibits color induction: evidence for a new kind of color theory. Spatial Vision, 19(2–4), 133–146. DOI: 10.1163/156856806776923498. Link ↗ (new tab)Experiments with small achromatic targets against chromatic surrounds: colour induction depended on boundaries and was strongest at minimal brightness contrast. Our screen colours are not a calibrated reproduction or individually brightness-matched.
  • Land, E. H. & McCann, J. J. (1971). Lightness and Retinex Theory. JOSA, 61(1), 1–11. DOI: 10.1364/JOSA.61.000001. Link ↗ (new tab)Historical Retinex theory of lightness and comparisons across a scene. Not a complete established brain algorithm; the illustration does not reproduce the original experiments.
  • Linnell, K. J. & Foster, D. H. (2002). Scene articulation: dependence of illuminant estimates on number of surfaces. Perception, 31(2), 151–159. DOI: 10.1068/p03sp. Link ↗ (new tab)Human experiments on illuminant discrimination and estimation with different numbers of surfaces. More surfaces helped under certain conditions; not evidence that every extra contrast improves perceived colour constancy.
  • Stockman, A., Sharpe, L. T. & Fach, C. (1999). The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches. Vision Research, 39(17), 2901–2927. DOI: 10.1016/S0042-6989(98)00225-9. Link ↗ (new tab)Human S-cone estimates from thresholds and colour matches; supports the S-cone sensitivity curve, not the lab’s RGB model.
  • Stockman, A. & Sharpe, L. T. (2000). The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype. Vision Research, 40(13), 1711–1737. DOI: 10.1016/S0042-6989(00)00021-3. Link ↗ (new tab)Measurements of M- and L-cones in observers of known genotype; supports overlapping sensitivity of these classes, not the lab’s RGB model.
  • Conway, B. R. (2001). Spatial structure of cone inputs to color cells in alert macaque primary visual cortex (V-1). Journal of Neuroscience, 21(8), 2768–2783. DOI: 10.1523/JNEUROSCI.21-08-02768.2001. Link ↗ (new tab)Single-unit experiments in alert macaque V1: spatial and chromatic comparisons; not proof of a complete human perceptual model.
  • Brainard, D. H., Brunt, W. A. & Speigle, J. M. (1997). Color constancy in the nearly natural image. 1. Asymmetric matches. JOSA A, 14(9), 2091–2110. DOI: 10.1364/JOSAA.14.002091. Link ↗ (new tab)Human psychophysics in controlled room illumination: partial colour constancy in asymmetric matching.
  • Kraft, J. M. & Brainard, D. H. (1999). Mechanisms of color constancy under nearly natural viewing. PNAS, 96(1), 307–312. DOI: 10.1073/pnas.96.1.307. Link ↗ (new tab)Human experiments varying illumination and surface collection: local surround, spatial mean or brightest region alone is insufficient; does not rule out adaptation contributing.
  • Rust, N. C. & DiCarlo, J. J. (2010). Selectivity and tolerance (“invariance”) both increase as visual information propagates from cortical area V4 to IT. Journal of Neuroscience, 30(39), 12978–12995. DOI: 10.1523/JNEUROSCI.0179-10.2010. Link ↗ (new tab)Macaque: V4 and IT neuronal population comparisons under tested image transformations. Limited tolerance, not perfect single-neuron invariance. Journal version: https://www.jneurosci.org/content/30/39/12978
  • Cavina-Pratesi, C., Kentridge, R. W., Heywood, C. A. & Milner, A. D. (2010). Separate channels for processing form, texture, and color: evidence from fMRI adaptation and visual object agnosia. Cerebral Cortex, 20(10), 2319–2332. DOI: 10.1093/cercor/bhp298. Link ↗ (new tab)Humans: discrimination tasks and fMRI adaptation, including two object-agnosic patients. Partly distinct occipitotemporal processing; not everything converges on one IT node.
  • Davenport, J. L. & Potter, M. C. (2004). Scene consistency in object and background perception. Psychological Science, 15(8), 559–564. DOI: 10.1111/j.0956-7976.2004.00719.x. Link ↗ (new tab)Humans: briefly presented, masked photographs (80 ms) in consistent or inconsistent settings. Behaviour, not localisation to IT; does not show that a background always helps compared with isolated objects.
  • Scharli, H., Harman, A. M. & Hogben, J. H. (1999). Blindsight in subjects with homonymous visual field defects. Journal of Cognitive Neuroscience, 11(1), 52–66. DOI: 10.1162/089892999563247. Link ↗ (new tab)Human lesion study separating forced-choice performance from reported awareness. Not a universal prevalence.
  • Ajina, S., Pestilli, F., Rokem, A., Kennard, C. & Bridge, H. (2015). Human blindsight is mediated by an intact geniculo-extrastriate pathway. eLife, 4, e08935. DOI: 10.7554/eLife.08935. Link ↗ (new tab)Human psychophysics and tractography; an LGN–hMT+ association, not causal proof or a universal route.
  • Schmid, M. C. et al. (2010). Blindsight depends on the lateral geniculate nucleus. Nature, 466, 373–377. DOI: 10.1038/nature09179. Link ↗ (new tab)Macaques with V1 lesions; reversible LGN inactivation abolished detection and extrastriate responses. Not a measurement of human consciousness.
  • Zeki, S. & ffytche, D. H. (1998). The Riddoch syndrome: insights into the neurobiology of conscious vision. Brain, 121, 25–45. DOI: 10.1093/brain/121.1.25. Link ↗ (new tab)The GY case: residual motion awareness after V1 lesion; distinguishes awareness from discrimination.
  • Bouvier, S. E. & Engel, S. A. (2006). Behavioral deficits and cortical damage loci in cerebral achromatopsia. Cerebral Cortex, 16(2), 183–191. DOI: 10.1093/cercor/bhi096. Link ↗ (new tab)Lesion-overlap analysis of 92 published cases; variable severity, coexisting spatial impairments, ventral occipital overlap. Not isolated V4 lesions or a pure colour-only module.
  • Kusunoki, M., Moutoussis, K. & Zeki, S. (2006). Effect of background colors on the tuning of color-selective cells in monkey area V4. Journal of Neurophysiology, 95(5), 3047–3059. DOI: 10.1152/jn.00597.2005. Link ↗ (new tab)Macaque ventral V4 recordings with background illumination changes, compared with psychophysics. Modulation related to colour induction/constancy; no claim that cells themselves perceive.
  • Goodale, M. A., Milner, A. D., Jakobson, L. S. & Carey, D. P. (1991). A neurological dissociation between perceiving objects and grasping them. Nature, 349, 154–156. DOI: 10.1038/349154a0. Link ↗ (new tab)The DF case: visual form agnosia and a perception–action dissociation in the tested tasks; not independent, universally spared streams.
  • Cohen, A. L., Soussand, L., Corrow, S. L., Martinaud, O., Barton, J. J. S. & Fox, M. D. (2019). Looking beyond the face area: lesion network mapping of prosopagnosia. Brain, 142(12), 3975–3990. DOI: 10.1093/brain/awz332. Link ↗ (new tab)Human lesion-network study; a network connected to right FFA, lesions need not overlap FFA. Normative connectivity, not monosynaptic anatomical wiring.
  • DeGutis, J. et al. (2023). What is the prevalence of developmental prosopagnosia? An empirical assessment of different diagnostic cutoffs. Cortex, 161, 51–64. DOI: 10.1016/j.cortex.2022.12.014. Link ↗ (new tab)Prevalence varies with definition and cutoffs; about 2% is not universal. The lifelong developmental form is distinguished from acquired injury.
  • Gaillard, R. et al. (2006). Direct intracranial, fMRI, and lesion evidence for the causal role of left inferotemporal cortex in reading. Neuron, 50(2), 191–204. DOI: 10.1016/j.neuron.2006.03.031. Link ↗ (new tab)Single human case before and after surgery with multiple methods; selective acquired reading deficit after resection of left word-responsive occipitotemporal cortex. Not all reading disorders arise from one locus.
  • Zihl, J., von Cramon, D. & Mai, N. (1983). Selective disturbance of movement vision after bilateral brain damage. Brain, 106, 313–340. DOI: 10.1093/brain/106.2.313. Link ↗ (new tab)The LM case: bilateral posterior damage, motion impairment with some remaining motion function. Lesion extent does not isolate MT alone.
  • Perenin, M. T. & Vighetto, A. (1988). Optic ataxia: a specific disruption in visuomotor mechanisms. I. Different aspects of the deficit in reaching for objects. Brain, 111, 643–674. DOI: 10.1093/brain/111.3.643. Link ↗ (new tab)Ten patients with unilateral parietal damage; reaching and hand-orientation errors that can dissociate from visuospatial perception. Not equivalent to akinetopsia or hemianopia.
  • Beauchamp, M. S., Nath, A. R. & Pasalar, S. (2010). fMRI-guided transcranial magnetic stimulation reveals that the superior temporal sulcus is a cortical locus of the McGurk effect. Journal of Neuroscience, 30(7), 2414–2417. DOI: 10.1523/JNEUROSCI.4865-09.2010. Link ↗ (new tab)fMRI-guided TMS of left STS with incongruent audiovisual speech; supports a contribution to the McGurk effect, not all audiovisual integration.
  • Pelphrey, K. A., Morris, J. P. & McCarthy, G. (2005). Neural basis of eye gaze processing deficits in autism. Brain, 128, 1038–1048. DOI: 10.1093/brain/awh404. Link ↗ (new tab)Human task-fMRI group comparison of context modulation during gaze shifts. An association, not causal focal-lesion evidence, a diagnostic biomarker or a universal feature of autistic people.
  • Campbell, F. W. & Green, D. G. (1965). Optical and retinal factors affecting visual resolution. Journal of Physiology, 181(3), 576–593. DOI: 10.1113/jphysiol.1965.sp007784. Link ↗ (new tab)Human measurements separating the eye's optical limits from those of the retina and further processing. Provides no exact threshold for the book's schematic figure.
  • Rossi, E. A. & Roorda, A. (2010). The relationship between visual resolution and cone spacing in the human fovea. Nature Neuroscience, 13, 156–157. DOI: 10.1038/nn.2465. Link ↗ (new tab)Human adaptive-optics measurements: cone spacing predicted resolution only at the centre of the fovea; just outside it, midget ganglion-cell sampling fitted better. Cones alone do not set the limit everywhere.
  • Hecht, S., Shlaer, S. & Pirenne, M. H. (1942). Energy, quanta, and vision. Journal of General Physiology, 25(6), 819–840. DOI: 10.1085/jgp.25.6.819. Link ↗ (new tab)Classic human experiments on detecting brief, dim flashes under carefully controlled conditions. Supports the distinction between detection and detail vision, not a universal photon threshold or astronomical measurements.
  • Kelly, D. H. (1961). Visual responses to time-dependent stimuli. I. Amplitude sensitivity measurements. Journal of the Optical Society of America, 51(4), 422–429. DOI: 10.1364/JOSA.51.000422. Link ↗ (new tab)Human sensitivity to flicker depends on frequency and adaptation level. Supports that there is no fixed frame rate for all of vision.
  • Burr, D. C. & Morgan, M. J. (1997). Motion deblurring in human vision. Proceedings of the Royal Society B, 264(1380), 431–436. DOI: 10.1098/rspb.1997.0061. Link ↗ (new tab)Perceived sharpness and the ability to discriminate blur in moving patterns can dissociate; subjective deblurring did not improve discrimination. No evidence for complete neural restoration of the image.
  • Angelaki, D. E., Shaikh, A. G., Green, A. M., & Dickman, J. D. (2004). Neurons compute internal models of the physical laws of motion. Nature, 430, 560–564. Link ↗ (new tab)Recordings in macaque brainstem and cerebellum show how canal and otolith signals are combined to distinguish tilt from linear translation. Not direct evidence about every human percept.
  • Kok, P., Jehee, J. F. M., & de Lange, F. P. (2012). Less is more: expectation sharpens representations in the primary visual cortex. Neuron, 75(2), 265–270. Link ↗ (new tab)Human fMRI: expectation affected responses and representations in primary visual cortex. Supports a role for expectation but is not a complete or universal theory of perception or consciousness.
  • McGurk, H. & MacDonald, J. (1976). Hearing lips and seeing voices. Nature, 264, 746–748. Link ↗ (new tab)Visual influences on speech perception and the McGurk example.
  • Ernst, M. O. & Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature, 415, 429–433. Link ↗ (new tab)Combining vision and haptics in the study's task; not a claim that all senses are always integrated optimally.
  • Saunders, J. A. & Knill, D. C. (2003). Humans use continuous visual feedback from the hand to control fast reaching movements. Experimental Brain Research, 152(3), 341–352. DOI: 10.1007/s00221-003-1525-2. Link ↗ (new tab)Visual feedback from the hand during fast reaching movements.
  • Purves, D. et al. (2001). Neuroscience (2nd ed.). The Retina. Link ↗ (new tab)The retina's layers, cell types and the direction of light in the visual lab.
  • Masland, R. H. (2012). The Neuronal Organization of the Retina. Link ↗ (new tab)The diversity and organisation of the cells; the tissue sketch shows only a selection.
  • Farsaii, M. & Connaughton, V. P. AII Amacrine Cells. Webvision. Link ↗ (new tab)Rod bipolar and AII amacrine cells in the rods' main pathway in dim light.
  • Purves, D. et al. (2001). Neuroscience (2nd ed.). Phototransduction. Link ↗ (new tab)Light leads to hyperpolarisation of photoreceptors.
  • Purves, D. et al. (2001). Neuroscience (2nd ed.). The Auditory System – Summary. Link ↗ (new tab)Tonotopy in the cochlea and auditory pathways.
  • Purves, D. et al. (2001). Neuroscience (2nd ed.). Integrating Information from the Two Ears. Link ↗ (new tab)Interaural time and level differences.
  • Schiller, P. H. (1986). The functions of the ON and OFF channels of the visual system. Link ↗ (new tab)
  • Sinha, P. et al. (2020). Mechanisms underlying simultaneous brightness contrast: Early and innate. Vision Research, 173, 41–49. Link ↗ (new tab)
  • Economou, E., Zdravković, S. & Gilchrist, A. (2007). Anchoring versus spatial filtering accounts of simultaneous lightness contrast. Journal of Vision, 7(12), 2. Link ↗ (new tab)

Authoritative background

  • Konica Minolta. Light Measurement: Spectroradiometers. Link ↗ (new tab)Manufacturer explanation of wavelength-resolved measurement of arriving light. Background for the instrument analogy, not evidence for the simulated spectrum or the accuracy of a particular instrument.
  • W3C. Web Content Accessibility Guidelines (WCAG) 2.2: Relative luminance. Link ↗ (new tab)Definition and sRGB conversion for relative luminance derived from image RGB values. Not evidence for physical reflectance, spectra or the figure’s model curves.
  • CIE. e-ILV 17-24-064: reflectance. Link ↗ (new tab)Authoritative definition: reflected divided by incident radiant flux. Background for spectral reflectance, not the figure’s authored curves.
  • Konica Minolta. Precise Color Communication: Spectrophotometers. Link ↗ (new tab)Manufacturer explanation of wavelength-resolved spectrophotometry versus a three-filter colorimeter. Instrument principle only, not a brand recommendation or measurements of the image.
  • NASA Science. Wave Behaviors. Link ↗ (new tab)Authoritative background on reflection, transmission and absorption: absorbed energy can increase molecular motion in a material and contribute to warming. Not measured fractions for the cup figure; the page's simplified colour examples are not used.
  • NASA Science. Interactions Between Light and Matter. Link ↗ (new tab)Authoritative overview distinguishing absorption, emission, transmission and reflection. Background for the text, not reused artwork or a description of the cup's exact material properties.
  • OpenStax. College Physics 2e, 25.2 The Law of Reflection. Link ↗ (new tab)Authoritative textbook background on diffuse reflection from rough surfaces and why they can be seen from different positions. Not evidence for absorption details or the figure's chosen angles.
  • NASA Science. Visible Light. Link ↗ (new tab)Authoritative background: visible light and the approximate 380–700 nm range.
  • NASA Science. Introduction to the Electromagnetic Spectrum. Link ↗ (new tab)Authoritative background: electromagnetic waves, wavelength and frequency.
  • CERN. The Standard Model. Link ↗ (new tab)Background on fundamental interactions; the Standard Model does not include gravity.
  • NIDCD. How Do We Hear? Link ↗ (new tab)Authoritative background on mechanical sound transmission and hearing; the book distinguishes receptor potentials from nerve signalling.
  • NIDCD. Balance Disorders. Link ↗ (new tab)Authoritative background on the otolith organs, otoconia, hair cells and the multisensory basis of balance; not used for diagnostic or treatment claims.

New pedagogical figures

The book combines AI-generated illustrations of an everyday scene and reconstructions of the eye and retina with separately authored interactive annotations and explanations, alongside authored editable scientific drawings. The images are not photographs or micrographs. Neither the illustrations nor the schematic maps are validated anatomical maps or measured research data.

The retina's layers and cell types are described with reference to Purves, Masland and the Webvision chapter on AII amacrine cells. The figure shows a selection of layers, not all ten histological layers; the signal trace is a simplified cone pathway, not complete connectivity.

Teaching models

The visual lab's receptive fields use a balanced model, R_ON = (centre − surround) / 100 and R_OFF = −R_ON. The output is a relative contrast response between −1 and 1, not firing rates or measured data.

The V1 model shows simplified contrast and orientation responses. The depth model calculates binocular geometry; the colour lab compares lighting, surfaces and surrounds. The point-light walk is synthetic movement, not a recording. The cup exploration shows available information, not a calculated movement. The network map represents historically reported macaque connections, not a validated human atlas. Assumptions and limits are explained beside each exploration.