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Grandmother cell

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the most selective face cells usually also discharge, if more weakly, to a variety of individual faces. Furthermore, face-selective cells often vary in their responsiveness to different aspects of faces. This suggests that cell responsiveness arises from the need of a monkey to differentiate among different individual faces rather than among other categories of stimuli such as bananas with their discrimination properties linked to the fact that different individual faces are much more similar to each other in their overall organization and fine detail than other kinds of stimuli. Moreover, it has been suggested that these cells might in fact be responding as specialized feature detector neurons that only function in the holistic context of a face construct.
146:, of Halle Berry", and would fire not only for images of Halle Berry, but also to the actual name "Halle Berry". However, there is no suggestion in that study that only the cell being monitored responded to that concept, nor was it suggested that no other actress would cause that cell to respond (although several other presented images of actresses did not cause it to respond). The researchers believe that they have found evidence for 84:
others published findings on what they would come to call the "Jennifer Aniston neuron". After operating on patients who experience epileptic seizures, the researchers showed photos of celebrities like Jennifer Aniston. The patients, who were fully conscious, often had a particular neuron fire, suggesting that the brain has Aniston-specific neurons.
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However most of the reported face-selective cells are not grandmother/gnostic cells since they do not represent a specific percept, that is, they are not cells narrowly selective in their activations for one face and only one face irrespective of transformations of size, orientation, and color. Even
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Further evidence for the theory that a small neural network provides facial recognition was found from analysis of cell recording studies of macaque monkeys. By formatting faces as points in a high-dimensional linear space, the scientists discovered that each face cell’s firing rate is proportional
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in 1890 proposed a related idea of a pontifical cell. The pontifical cell is defined as a putative, and implausible cell which had all our experiences. This is different from a concept specific cell in that it is the site of experience of sense data. James's 1890 pontifical cell was instead a cell
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of the monkey fire selectively to hands and faces. These cells are selective in that they do not fire for other visual objects important for monkeys such as fruit and genitalia. Research finds that some of these cells can be trained to show high specificity for arbitrary visual objects, and these
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observed that the term had "become a shorthand for invoking all of the overwhelming practical arguments against a one-to-one object coding scheme. No one wants to be accused of believing in grandmother cells." However, in that year UCLA neurosurgeons Itzhak Fried, mentee Rodrigo Quian Quiroga and
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Around 1969, Lettvin introduced the term "grandmother cell" in a course he was teaching at MIT, telling a fictitious anecdote about a neurosurgeon who had discovered a group of "mother cells" in the brain that "responded uniquely only to a mother... whether animate or stuffed, seen from before or
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described cells in a frog retina as "bug detectors", but the term did not gain wide usage. Several years later, Jerome (Jerry) Lettvin and others also studied these and other cells, eventually resulting in their widely known 1959 paper "What the frog’s eye tells the frog’s brain."
43:. Rather than serving as a serious hypothesis, the "grandmother cell" concept was initially largely used in jokes and came to be used as a "straw man or foil" for a discussion of ensemble theories in introductory textbooks. However, a similar concept, that of the 166:, and is not without critics. The opposite of the grandmother cell theory is the distributed representation theory, that states that a specific stimulus is coded by its unique pattern of activity over a large group of neurons widely distributed in the brain. 113:
One idea has been that such cells form ensembles for the coarse or distributed coding of faces rather than detectors for specific faces. Thus, a specific grandmother may be represented by a specialized ensemble of grandmother or near grandmother cells.
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Rather than becoming more and more specific as visual processing proceeds from retina through the different visual centres of the brain, the image is partially dissected into basic features such as vertical lines, colour, speed,
36:(or "coarse" coding), where the unique set of features characterizing the grandmother is detected as a particular activation pattern across an ensemble of neurons, rather than being detected by a specific "grandmother cell". 31:
that represents a complex but specific concept or object. It activates when a person "sees, hears, or otherwise sensibly discriminates" a specific entity, such as their grandmother. It contrasts with the concept of
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According to some theories, one would need thousands of cells for each face, as any given face must be recognised from many different angles – profile, 3/4 view, full frontal, from above,
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to the projection of an incoming face stimulus onto a single axis in this space, allowing a face cell ensemble of about 200 cells to encode the location of any face in the space.
184:, distributed in various modules separated by relatively large distances. How all these disparate features are re-integrated to form a seamless whole is known as the 239: 432: 68:
behind, upside down or on a diagonal or offered by caricature, photograph or abstraction". In Lettvin's story, the neurosurgeon went on to remove (
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that have highly selective responses to different categories of stimuli including highly selective responses to individual human faces.
201:"to which the rest of the brain provided a representation" of a grandmother. The experience of grandmother occurred in this cell. 696:
Kreiman, G; Koch, C; Fried, I (2000). "Category specific visual responses of single neurons in the human medial temporal lobe".
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Yamane, S; Kaji, S; Kawano, K (1988). "What facial features activate face neurons in the inferotemporal cortex of the monkey?".
451: 72:) all these "several thousand separate neurons" from the brain of Portnoy, the title character of Philip Roth's 1969 novel 102:
would seem to fit the requirements of gnostic/grandmother cells. In addition, evidence exists for cells in the human
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Neurons in the cortex of the temporal lobe and in the amygdala of the monkey with responses selective for faces.
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Quian Quiroga, R.; et al. (2008). "Sparse but not 'Grandmother-cell' coding in the medial temporal lobe".
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Perrett, DI; Rolls, ET; Caan, W (1982). "Visual neurons responsive to faces in the monkey temporal cortex".
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study found evidence of different cells that fire in response to particular people, such as
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Single neuron responses in humans during binocular rivalry and flash suppression
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The grandmother cell hypothesis, is an extreme version of the idea of
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Gross, CG (2000). "Coding for visual categories in the human brain".
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Logothetis, NK; Sheinberg, DL (1996). "Visual object recognition".
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Integrative activity of the brain; an interdisciplinary approach.
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James W. (1890). The principles of psychology. New York: Dover
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Brain, vision, memory: tales in the history of neuroscience.
433:"Neuroscientists Battle Furiously over Jennifer Aniston" 39:
The term was coined around 1969 by cognitive scientist
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Hypothetical neuron that responds to a single concept
951:"The Code for Facial Identity in the Primate Brain" 801:"A face feature space in the macaque temporal lobe" 1001: 142:, for example, might respond "to the concept, the 799:Freiwald, WA; Tsao, DY; Livingstone, MS (2009). 756:Jagadeesh, B (2009). "Recognizing grandmother". 335:"Summation and inhibition in the frog's retina" 169:The arguments against the sparseness include: 846: 844: 8: 452:"Searching for the Jennifer Aniston Neuron" 450:Quian Quiroga, Rodrigo (February 1, 2013). 47:, was introduced several years earlier by 976: 966: 824: 608: 404: 358: 158:Sparseness vs distributed representations 641:Inferotemporal cortex and object vision. 233: 851:Quian Quiroga, R.; et al. (2005). 299:. Oxford University Press. p. 43. 231: 229: 227: 225: 223: 221: 219: 217: 215: 213: 209: 240:""Genealogy of the "Grandmother Cell" 150:, rather than for grandmother cells. 118:Individual specific recognition cells 7: 426: 424: 382: 380: 378: 601:10.1146/annurev.ne.19.030196.003045 431:Krulwich, Robert (March 30, 2012). 738:Kreiman G, Fried I, Koch C. 2001. 14: 387:Connor, Charles (23 June 2005). 333:Barlow, Horace (January 1953). 610:11858/00-001M-0000-0013-EBB0-3 351:10.1113/jphysiol.1953.sp004829 1: 908:Trends in Cognitive Sciences 643:Annu Rev Neurosci 19:109–39. 27:neuron", is a hypothetical 1076: 968:10.1016/j.cell.2017.05.011 920:10.1016/j.tics.2007.12.003 389:"Friends and grandmothers" 99:inferior temporal cortex 23:, sometimes called the " 534:Hum Neurobiol 3:209–22. 259:10.1177/107385802237175 51:as a serious proposal. 1004:Cognitive Neuroscience 1000:Rugg, Michael (1997). 295:Clark, Austen (2000). 97:Visual neurons in the 297:A Theory of Sentience 949:Chang, Tsao (2017). 93:Face selective cells 877:10.1038/nature03687 869:2005Natur.435.1102Q 863:(7045): 1102–1107. 770:10.1038/nn0909-1083 456:Scientific American 399:(7045): 1036–1037. 74:Portnoy's Complaint 744:Abstr Soc Neurosci 558:10.1007/bf00279674 502:10.1007/bf00239352 319:Konorski J. 1967. 238:Gross, CG (2002). 1060:Cognitive science 1023:978-0-262-68094-3 589:Annu Rev Neurosci 475:Gross CG. 1998a. 306:978-0-19-823851-5 1067: 1037: 1034: 1028: 1027: 1007: 997: 991: 990: 980: 970: 961:(6): 1013–1028. 946: 940: 939: 903: 897: 896: 848: 839: 838: 828: 796: 790: 789: 753: 747: 736: 730: 729: 693: 687: 686: 650: 644: 639:Tanaka K. 1996. 637: 631: 630: 612: 584: 578: 577: 541: 535: 530:Rolls ET. 1984. 528: 522: 521: 485: 479: 473: 467: 466: 464: 462: 447: 441: 440: 428: 419: 418: 408: 406:10.1038/4351036a 384: 373: 372: 362: 330: 324: 317: 311: 310: 292: 286: 285: 283: 277:. Archived from 244: 235: 193:Pontifical cells 138:. A neuron for 136:Jennifer Aniston 25:Jennifer Aniston 21:grandmother cell 1075: 1074: 1070: 1069: 1068: 1066: 1065: 1064: 1045: 1044: 1042: 1040: 1035: 1031: 1024: 999: 998: 994: 948: 947: 943: 905: 904: 900: 850: 849: 842: 817:10.1038/nn.2363 798: 797: 793: 755: 754: 750: 737: 733: 695: 694: 690: 652: 651: 647: 638: 634: 586: 585: 581: 543: 542: 538: 529: 525: 487: 486: 482: 474: 470: 460: 458: 449: 448: 444: 430: 429: 422: 386: 385: 376: 332: 331: 327: 318: 314: 307: 294: 293: 289: 281: 242: 237: 236: 211: 207: 195: 186:binding problem 160: 144:abstract entity 120: 95: 90: 57: 34:ensemble coding 17: 12: 11: 5: 1073: 1071: 1063: 1062: 1057: 1047: 1046: 1039: 1038: 1029: 1022: 992: 941: 898: 840: 811:(9): 1187–96. 791: 748: 731: 688: 645: 632: 579: 536: 523: 480: 468: 442: 420: 374: 325: 312: 305: 287: 284:on 2012-02-08. 253:(5): 512–518. 247:Neuroscientist 208: 206: 203: 194: 191: 190: 189: 177: 159: 156: 119: 116: 94: 91: 89: 86: 56: 53: 49:Jerzy Konorski 45:gnostic neuron 15: 13: 10: 9: 6: 4: 3: 2: 1072: 1061: 1058: 1056: 1055:Neural coding 1053: 1052: 1050: 1043: 1033: 1030: 1025: 1019: 1015: 1011: 1006: 1005: 996: 993: 988: 984: 979: 974: 969: 964: 960: 956: 952: 945: 942: 937: 933: 929: 925: 921: 917: 913: 909: 902: 899: 894: 890: 886: 882: 878: 874: 870: 866: 862: 858: 854: 847: 845: 841: 836: 832: 827: 822: 818: 814: 810: 806: 802: 795: 792: 787: 783: 779: 775: 771: 767: 764:(9): 1083–5. 763: 759: 752: 749: 745: 741: 735: 732: 727: 723: 719: 715: 711: 710:10.1038/78868 707: 704:(9): 946–53. 703: 699: 692: 689: 684: 680: 676: 672: 668: 667:10.1038/78745 664: 660: 656: 649: 646: 642: 636: 633: 628: 624: 620: 616: 611: 606: 602: 598: 594: 590: 583: 580: 575: 571: 567: 563: 559: 555: 552:(1): 209–14. 551: 547: 546:Exp Brain Res 540: 537: 533: 527: 524: 519: 515: 511: 507: 503: 499: 496:(3): 329–42. 495: 491: 490:Exp Brain Res 484: 481: 478: 472: 469: 457: 453: 446: 443: 438: 434: 427: 425: 421: 416: 412: 407: 402: 398: 394: 390: 383: 381: 379: 375: 370: 366: 361: 356: 352: 348: 344: 340: 336: 329: 326: 322: 316: 313: 308: 302: 298: 291: 288: 280: 276: 272: 268: 264: 260: 256: 252: 248: 241: 234: 232: 230: 228: 226: 224: 222: 220: 218: 216: 214: 210: 204: 202: 199: 198:William James 192: 187: 183: 178: 176: 172: 171: 170: 167: 165: 157: 155: 151: 149: 145: 141: 137: 133: 129: 125: 117: 115: 111: 107: 105: 100: 92: 87: 85: 82: 77: 75: 71: 65: 62: 61:Horace Barlow 54: 52: 50: 46: 42: 41:Jerry Lettvin 37: 35: 30: 26: 22: 1041: 1032: 1003: 995: 958: 954: 944: 914:(3): 87–91. 911: 907: 901: 860: 856: 808: 805:Nat Neurosci 804: 794: 761: 758:Nat Neurosci 757: 751: 743: 739: 734: 701: 698:Nat Neurosci 697: 691: 661:(9): 855–6. 658: 655:Nat Neurosci 654: 648: 640: 635: 592: 588: 582: 549: 545: 539: 531: 526: 493: 489: 483: 476: 471: 459:. 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Index

Jennifer Aniston
neuron
ensemble coding
Jerry Lettvin
Jerzy Konorski
Horace Barlow
ablate
Portnoy's Complaint
Ed Connor
inferior temporal cortex
hippocampus
UCLA
Caltech
Bill Clinton
Jennifer Aniston
Halle Berry
abstract entity
sparseness
sparseness
binding problem
William James








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