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• W2034139708 abstract "While we know that the neocortex occupies 85% of our brains and that its circuits allow an enormous flexibility and repertoire of behavior (not to mention unexplained phenomena like consciousness), a century after Cajal we have very little knowledge of the details of the cortical circuits or their mode of function. One simplifying hypothesis that has existed since Cajal is that the neocortex consists of repeated copies of the same fundamental circuit. However, finding that fundamental circuit has proved elusive, although partial drafts of a “canonical circuit” appear in many different guises of structure and function. Here, we review some critical stages in the history of this quest. In doing so, we consider the style of cortical computation in relation to the neuronal machinery that supports it. We conclude that the structure and function of cortex honors two major computational principles: “just-enough” and “just-in-time.” While we know that the neocortex occupies 85% of our brains and that its circuits allow an enormous flexibility and repertoire of behavior (not to mention unexplained phenomena like consciousness), a century after Cajal we have very little knowledge of the details of the cortical circuits or their mode of function. One simplifying hypothesis that has existed since Cajal is that the neocortex consists of repeated copies of the same fundamental circuit. However, finding that fundamental circuit has proved elusive, although partial drafts of a “canonical circuit” appear in many different guises of structure and function. Here, we review some critical stages in the history of this quest. In doing so, we consider the style of cortical computation in relation to the neuronal machinery that supports it. We conclude that the structure and function of cortex honors two major computational principles: “just-enough” and “just-in-time.” Maps are comforting. They reveal to us the fixed points of the known world and alert us to the regions that are “terra incognita.” However, maps themselves also map the changes in our perception of what is the “known world”—and these reveal our perceptions to be unstable. One famous example is the island of Buss (Figure 1), which was first “discovered” in 1578 somewhere between Ireland and Frisland and appeared on nautical charts from then on until it finally sank from consciousness after it last appeared on a chart in 1856. The island of Madya was the longest survivor of these phantoms. It first appeared on maps in about 1400, positioned in the north Atlantic to the southwest of Ireland. Over the centuries it moved more westward, so that by 1566 it was located near Newfoundland, and then took a turn south, and was last seen on a Rand McNally map of 1906 at the level of the West Indies. Claude Levi-Strauss (in contrast to William of Occam: “No more things should be presumed to exist than are absolutely necessary”) argued that every culture has a need for certain concepts and expressions to absorb any excess of existence that has not yet had a word coined for it. James Hamilton Paterson, 1993Hamilton Paterson J. Seven-Tenths: The Sea and Its Thresholds. Vintage, London1993Google Scholar suggests that these phantom islands operated as Levi-Straus's “floating signifiers” to provide comfort and points of reference within the void of ignorance—the terra incognita. The neocortex is one of the most elaborate maps we have. Not only does it contain many different areas, but these areas also contain within themselves multiple maps, which may reflect directly the sensory periphery or may appear as more abstract “cognitive maps.” The neocortex has its own floating signifiers, with words like “column,” “module,” “neural representation,” “cortical code,” and “consciousness,” which have been coined to absorb the enormous functional and structural excess of existence that is evident in every material record of the brain and, most particularly, in the cortical circuits about whose mode of organization and operation we are still greatly ignorant. One fundamental question is whether the neocortex is a unitary structure with a grammar and a logic of construction and operation that can be understood in terms of the physical circuits and their physiology, or whether it is a collective of very many separate modules with their own specialist “trick” circuitry? To begin at the beginning: like the syntax of human languages, the structure of the neocortex appears equally complex in all land mammals. Just as there is no simple or prototype version of a human language in existence, a simple or primitive form of neocortex does not exist. Yet, it is as evident that, like different languages, the neocortex consists of different areas as defined by histological or with physiological methods. But just as with languages, we will claim here, the neocortical areas are also essentially the same and, like languages, can be translated, one into the other. Thus, in understanding one area, we can expect to understand another. It is this sameness that we have called a “canonical” property of cortical circuits (Douglas et al., 1989Douglas R.J. Martin K.A.C. Whitteridge D. A canonical microcircuit for neocortex.Neural Comput. 1989; 1: 480-488Crossref Google Scholar). The immediate challenge is the question, what defines “neocortex”? The usual answer is structural: that, unlike allocortex, which has fewer layers and is phylogenetically older, the neocortex possesses six layers. The number of layers would, of course, seem a rather fragile means of defining a structure that varies over five orders of magnitude in volume from shrew to whale, that supports the processing of input from an unlikely range of sensory systems allowing detection of electromagnetic radiation, vibration, temperature, sound, and chemicals, and that then provides output to an equally unlikely range of motor structures, allowing an animal to fly, swim, walk, jump, and run. In fact, the “six-layered” neocortex is something of a unicorn, for the number of layers that can be distinguished varies greatly between areas and the histological stains used to reveal the layers. Yet, somehow, neocortex is so instantly distinguishable from other laminated structures, such as the hippocampus or superior colliculus, that early anatomists referred to it as “isocortex.” Although it is now clear that language comprehension and production involves much more of the brain than just the well-known regions first discovered by Broca and Wernicke, their 19th century idea of a compartmentalization of specific functions has reappeared in modern times, most prominently in evolutionary biology. The best known claim is captured by the “Swiss army knife” metaphor for the functional organization of cortex (Barkow et al., 1992Barkow J.H. Cosmides L. Tooby J. The Adapted Mind: Evolutionary Psychology and the Generation of Culture. Oxford University Press, New York1992Google Scholar). In this view, the brain has evolved a series of special-purpose modules, which, like the Swiss army knife, consist of individual components that have a specific function and are not designed to work together like the components of a machine. For humans, the language module is the most obvious of these special-purpose modules, but strong claims have been made that such specialized modules are the means by which the neocortex is organized and works (Fodor, 1983Fodor J.A. The Modularity of Mind. MIT Press, Cambridge, MA1983Crossref Google Scholar, Zeki, 1993Zeki S. A Vision of the Brain. Blackwell Scientific Publications, Oxford1993Google Scholar). Implicit in this is the notion that the neural pathways in the brain subserving these areas are highly segregated and that there is no general-purpose architecture that carries out the neocortical part of the computations. The era of microcircuit analysis was launched by Camillo Golgi's discovery of “la reazione nera,” which allowed individual neurons to be visualized, and by Santiago Ramon y Cajal's law of dynamic polarization, which provided the critical algorithm for identifying the input and output regions of individual neurons. Put together, these two advances made it possible for the first time to show the probable route of impulses from input to output for a given structure. As he recorded in his autobiography, the extraordinary claim that Cajal made was that even the highest center of the brain, the neocortex, was built of stereotyped circuits like those he had discovered in the retina, cerebellum, hippocampus, spinal cord, and other parts of the central nervous system (Cajal, 1937Cajal S.R. Recollections of My Life. American Philosophical Society, Philadelphia, PA1937Google Scholar). Despite intense efforts on his part, however, he was unable to define the basic cortical circuit, but until the end of his life he nevertheless remained convinced that it existed. When Cajal applied Golgi's stain to neonatal brain, he was able to map, mostly correctly, significant circuits in the spinal cord, retina, and visual pathways, cerebellum, hippocampus, olfactory bulb, auditory nuclei, and others. From this he developed the notion of the “neural avalanche,” which was essentially the inverse of Sherrington's “final common path.” It stated that the number of neurons involved in conducting impulses from a sensory receptor increases progressively from the periphery to the cortex (Cajal, 1937Cajal S.R. Recollections of My Life. American Philosophical Society, Philadelphia, PA1937Google Scholar). De Kock et al., 2007De Kock C.P. Bruno R.M. Spors H. Sakmann B. Layer- and cell-type-specific suprathreshold stimulus representation in rat primary somatosensory cortex.J. Physiol. 2007; 581: 139-154Crossref PubMed Scopus (241) Google Scholar have calculated the neural avalanche in the rat barrel cortex, and they estimate that a single whisker deflection generates about 4000 impulses in the cortex. This avalanche grows further through the associated cortical areas, before it is funneled down the final common path to the motoneuron, but even with his great skills of preparation, observation, and imagination, Cajal was unable to trace the route from input to the cortex to its output. However, his efforts were not without reward, for he provided a comprehensive description of the different cell types that inhabit the neocortex of different animals and incorporated the earlier descriptions of cortical cell types of Retzius, Meynert, Betz, and others. Lorente de Nó, 1949Lorente de Nó R. The cerebral cortex: architecture, intracortical connections, motor projections.in: Physiology of the Nervous System. Oxford University Press, New York1949: 288-330Google Scholar pursued Cajal's dream, also with Golgi's stain, and suggested that the functional unit of cortex consisted of a specific thalamocortical fiber and a cylindrical group of cells surrounding the fiber, some of which formed synapses with the thalamocortical fiber. With succeeding generations, however, this confidence in a basic circuit became less secure, and there was even a return, in the 1930s, to the idea that the neocortex was an equipotential network (Lashley, 1930Lashley K.S. Basic neural mechanisms in behavior.Psychol. Rev. 1930; 37: 1-24Crossref Scopus (167) Google Scholar), an idea demolished by Sperry (Sperry, 1947Sperry R.W. Cerebral regulation of motor coordination in monkeys following multiple transection of sensorimotor cortex.J. Neurophysiol. 1947; 10: 275-294PubMed Google Scholar, Sperry et al., 1955Sperry R.W. Miner N. Myers R.E. Visual pattern perception following subpial slicing and tantalum wire implantations in the visual cortex.J. Compar Physiol. Psych. 1955; 48: 50-58Crossref PubMed Scopus (56) Google Scholar), or that the connections between cortical neurons were not at all specific, but perhaps statistical (Sholl, 1956Sholl D.A. The Organization of the Cerebral Cortex. Methuen, London1956Google Scholar) or semirandom (Szentágothai, 1978Szentágothai J. Specificity versus (quasi-) randomness in cortical connectivity.in: Braizier M.A.B. Petsche H. Architectonics of the Cerebral Cortex. Raven Press, New York1978: 77-97Google Scholar) or even random (Braitenberg and Schüz, 1991Braitenberg V. Schüz A. Anatomy of the Cortex. Springer-Verlag, Berlin1991Crossref Google Scholar). Thus, proposals that the local circuit of barrel cortex begins its life as a “tabula rasa” to be written on by experience (Jeanmonod et al., 1981Jeanmonod D. Rice F.L. Van der Loos H. Mouse somatosensory cortex: alterations in the barrelfield following receptor injury at different early postnatal ages.Neuroscience. 1981; 6: 1503-1535Crossref PubMed Scopus (166) Google Scholar, Le Be and Markram, 2006Le Be J.V. Markram H. Spontaneous and evoked synaptic rewiring in the neonatal neocortex.Proc. Natl. Acad. Sci. USA. 2006; 103: 13214-13219Crossref PubMed Scopus (115) Google Scholar, Kalisman et al., 2005Kalisman N. Silberberg G. Markram H. The neocortical microcircuit as a tabula rasa.Proc. Natl. Acad. Sci. USA. 2005; 102: 880-885Crossref PubMed Scopus (149) Google Scholar) are simply a continuance of a surprisingly long-lived hypothesis that the cortex really wants to be a randomly connected neural network. In the face of such enormous numbers of possible circuits that could potentially arise from such random neural networks, to pursue the concept that all of neocortex has a uniform basic structure and performs some basic uniform operations would seem to be setting oneself up for yet another instance of Thomas Huxley's great tragedy of Science—“the slaying of a beautiful hypothesis by an ugly fact.” Yet, the decade that began in a trough with Karl Lashley's despairing account of his search for the engram (Lashley, 1950Lashley K.S. In search of the engram.Symp. Soc. Exp. Biol. 1950; 4: 454-482Google Scholar) ended on a much more positive peak for the neocortex, with seminal studies of the physiology of sensory cortex (Mountcastle, 1957Mountcastle V. Modality and topographic properties of single neurons of cat somatosensory cortex.J. Neurophysiol. 1957; 20: 408-434PubMed Google Scholar, Hubel and Wiesel, 1959Hubel D.H. Wiesel T.N. Receptive fields of single neurones in the cat's striate cortex.J. Physiol. 1959; 148: 574-591PubMed Google Scholar). The long hoped for evidence that neocortex had a specific architecture did not come from anatomists, but from physiologists working in vivo, who provided the major new insights into cortical organization. Mountcastle, 1957Mountcastle V. Modality and topographic properties of single neurons of cat somatosensory cortex.J. Neurophysiol. 1957; 20: 408-434PubMed Google Scholar recorded from the somatosensory cortex of cats and monkeys and found that neurons with common functional properties lay in a radial column of cells, extending from white matter to cortical surface. With this discovery, the anatomists were once again brought into play. Powell, working at Mountcastle's side, suggested that the vertical palisades of cells he saw in stained sections of sensory cortex were the elementary units that formed of the functional columns (Powell and Mountcastle, 1959Powell T.P. Mountcastle V.B. Some aspects of the functional organization of the cortex of the postcentral gyrus of the monkey: a correlation of findings obtained in a single unit analysis with cytoarchitecture.Bull. Johns Hopkins Hosp. 1959; 105: 133-162PubMed Google Scholar). This concept of a functional column was not lost on their neighbors at John's Hopkins, who were just then plotting their first receptive fields of visual cortical neurons on bed sheets hung from the ceiling. Hubel and Wiesel's ice-cube diagram (Hubel and Wiesel, 1972Hubel D.H. Wiesel T.N. Laminar and columnar distribution of geniculo-cortical ibvers in the macaque monkey.J. Comp. Neurol. 1972; 146: 421-450Crossref PubMed Scopus (626) Google Scholar, Hubel and Wiesel, 1977Hubel D.H. Wiesel T.N. Ferrier lecture. Functional architecture of macaque monkey visual cortex.Proc. R. Soc. Lond. B. Biol. Sci. 1977; 198: 1-59Crossref PubMed Google Scholar) summarized their basic findings about the functional architecture of area 17. What had first seemed to them irregularly shaped “columns,” sometimes ordered, sometimes not, sometimes continuous, sometimes not (Hubel and Wiesel, 1963Hubel D.H. Wiesel T.N. Shape and arrangement of columns in cat's striate cortex.J. Physiol. 1963; 165: 559-568Crossref PubMed Scopus (460) Google Scholar, Hubel and Wiesel, 1968Hubel D.H. Wiesel T.N. Receptive fields and functional architecture of monkey striate cortex.J. Physiol. 1968; 195: 215-243PubMed Google Scholar), were now schematized as parallel slabs, with the thin orientation slabs cutting the coarser ocular dominance columns at right angles. Since orientation selectivity is a property of single cells, it is inevitably discretized, but trivially so, for in all other respects the map of orientation space appears to be continuous. In the case of monkey visual cortex, Hubel and Wiesel, 1974bHubel D.H. Wiesel T.N. Sequence regularity and geometry of orientation columns in the monkey striate cortex.J. Comp. Neurol. 1974; 158: 267-293Crossref PubMed Scopus (664) Google Scholar found that movements of the microelectrode as small as 25–50 μm could produce just-detectable shifts in orientation preference (10°) in monkey V1. From this they reckoned that the orientation slabs were not discrete, or if they were, they had a width of less than 25 μm, i.e., the diameter of a large cell soma. To Hubel and Wiesel this indicated that there was no correlation between the fine-grain of the physiological slabs and the coarser grain offered by the orders of magnitudes larger dimensions of the soma, dendrite, and axon. The recent two-photon imaging of the neurons that form the orientation map in the cat (Ohki et al., 2005Ohki K. Chung S. Ch'ng Y.H. Kara P. Reid R.C. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex.Nature. 2005; 433: 597-603Crossref PubMed Scopus (815) Google Scholar, Ohki et al., 2006Ohki K. Chung S. Kara P. Hubener M. Bonhoeffer T. Reid R.C. Highly ordered arrangement of single neurons in orientation pinwheels.Nature. 2006; 442: 925-928Crossref PubMed Scopus (228) Google Scholar) confirms in 2D the precision of the progression in orientation preference seen with the microelectrode and confronts us again with the puzzle of how this comes about, given what we now know about the underlying anatomy. The anatomical basis of these functional domains was baffling to Hubel and Wiesel, since the radial fascicles seen in the light microscope seemed too ubiquitous and orderly to account for the picture they saw through their microelectrode (Hubel and Wiesel, 1968Hubel D.H. Wiesel T.N. Receptive fields and functional architecture of monkey striate cortex.J. Physiol. 1968; 195: 215-243PubMed Google Scholar). Yet the causal relation between the two is undeniable: the neurons create the functional architecture, the functional architecture has regularities, and so how do the underlying circuits do it? The iso-orientation slabs were about 30 μm wide, but the ocular dominance slabs were 500 μm wide. For other cortical areas, the picture was even less clear. With respect to the whisker representation in rodents, Hubel and Wiesel stated, “Whether they [barrels] should be considered columns seems a matter of taste and semantics” (Hubel and Wiesel, 1974bHubel D.H. Wiesel T.N. Sequence regularity and geometry of orientation columns in the monkey striate cortex.J. Comp. Neurol. 1974; 158: 267-293Crossref PubMed Scopus (664) Google Scholar). The whisker map in rodents is similar to retinotopic or tonotopic representations in other sensory cortices, but this map is not the same as higher-order maps of properties like orientation selectivity, whose topography is not predictable at the periphery. Nevertheless, the concept that neocortex consists of vertical arrangements of cells that are interconnected and have functional properties in common is almost universal. With the enormous success of the cortical physiologists in defining a basic architecture of cortex, the ball was back in the anatomists' court to explain the underlying structure. Although Golgi's stain had provided generations of anatomists with a powerful tool, it also had a major limitation, which Cajal had recognized and used to his advantage: it worked best in immature material. Because multiple cells were impregnated, it was virtually impossible to trace the same axon from one section to the next. Thus, the cell structures illustrated were obtained from reconstructions of single sections of perhaps 100 μm thick. A hint that this picture of the cortical axons was very incomplete came from degeneration studies in which small lesions had been made within the cortical gray matter. When the resulting degeneration was traced, it was clear that intracortical axons of pyramidal cells could extend over several mm (Fisken et al., 1975Fisken R.A. Garey L.J. Powell T.P.S. The intrinsic, association and commissural connections of area 17 of the visual cortex.Philos. Trans. R. Soc. Lond. B. Biol. Sci. 1975; 272: 487-536Crossref PubMed Scopus (204) Google Scholar, Gatter and Powell, 1978Gatter K.C. Powell T.P.S. The intrinsic connections of the cortex area 4 of the monkey.Brain. 1978; 101: 513-541Crossref PubMed Scopus (67) Google Scholar, Creutzfeldt et al., 1977Creutzfeldt O.D. Garey L.J. Kuroda R. Wolff J.-R. The distribution of degenerating axons after small lesions in the intact and isolated visual cortex of the cat.Exp. Brain Res. 1977; 27: 419-440PubMed Google Scholar). What is most surprising was how similar the pattern of fiber degeneration was across different species and different areas. Figure 2 shows the close similarities between the striate visual cortex and the primary motor cortex of monkey cortex, which, in cytoarchitectonic and functional respects, differ the most. It was evidence like this that encouraged Powell to pursue the concept of cortical uniformity. Later, bulk injections of tracers like horseradish peroxidase into the cortex confirmed this pattern of spread (Blasdel et al., 1985Blasdel G.G. Lund J.S. Fitzpatrick D. Intrinsic connections of macaque striate cortex: axonal projections of cells outside lamina 4C.J. Neurosci. 1985; 5: 3350-3369PubMed Google Scholar) and also revealed the existence of widespread lateral connections of pyramidal cells that formed dense patches of boutons (Rockland and Lund, 1982Rockland K.S. Lund J.S. Widespread periodic intrinsic connections in the tree shrew visual cortex.Science. 1982; 215: 1532-1534Crossref PubMed Scopus (224) Google Scholar). The lateral fibers detected in the degeneration studies and the first complete picture of mature cortical neurons came from studies where single neurons had been injected intracellularly with horseradish peroxidase (HRP; Gilbert and Wiesel, 1979Gilbert C.D. Wiesel T.N. Morphology and intracortical projections of functionally characterised neurones in the cat visual cortex.Nature. 1979; 280: 120-125Crossref PubMed Scopus (703) Google Scholar, Gilbert and Wiesel, 1983Gilbert C.D. Wiesel T.N. Clustered intrinsic connections in cat visual cortex.J. Neurosci. 1983; 3: 1116-1133PubMed Google Scholar, Martin and Whitteridge, 1984Martin K.A.C. Whitteridge D. Form, function and intracortical projections of spiny neurones in the striate visual cortex of the cat.J. Physiol. 1984; 353: 463-504PubMed Google Scholar). These pictures were a revelation (Figure 3). It was as if the Golgi stain had been given growth hormone, for the black spindly trees had now extended their branches and sprouted bushy terminal thickets. It was evident that even the “projection neurons” were substantial players in the local cortical circuits. However, what constituted a local circuit was now even less clear. What was the elementary unit of structure that formed the vertical functional column? The palisades of cell bodies still formed their neat columns, but not only did the dendrites originating from these cell bodies spread well beyond these elementary columns, so did their axonal arbors. It became impossible on anatomical grounds to define the columnar structure of a given area, let alone explain how the visible structure gave rise to the functional phenomenon of columns. The difficulty of defining the column has also generated the opinion that the concept has failed as a unifying principle for cerebral cortex (Purves et al., 1992Purves D. Riddle D.R. LaMantia A.S. Iterated patterns of brain circuitry (or how the cortex gets its spots).Trends Neurosci. 1992; 10: 362-368Abstract Full Text PDF Scopus (121) Google Scholar, Swindale, 1998Swindale N.V. Cortical organization: modules, polymaps and mosaics.Curr. Biol. 1998; 8: R270-R273Abstract Full Text Full Text PDF PubMed Google Scholar, Horton and Adams, 2005Horton J.C. Adams D.L. The cortical column: a structure without a function.Philos. Trans. R. Soc. Lond. B Biol. Sci. 2005; 360: 837-862Crossref PubMed Scopus (342) Google Scholar). However, the idea of elementary modules that could, by repetition, generate an entire cortex, could not so easily be quashed by these brutal facts. Critics of the column concept have to deal with the reality that the very long history of microelectrode recordings from the primary visual cortex seemed to give the same results, regardless of where exactly the electrode was placed. If it were not so, progress would have been achingly slow, and the visual cortex would never have become the model system it has. This reliable repetitiveness could only be a result of an underlying uniformity. The case is most convincingly made for the many areas that contain topographic maps of the sensory periphery. Here, the cortical area represents in 2D a map of audible frequencies, or a whisker, or one patch of visual field, and the actual shape of the cortical surface is determined by this primary map (Daniel and Whitteridge, 1961Daniel P.M. Whitteridge D. The representation of the visual field on the cerebral cortex in monkeys.J. Physiol. 1961; 159: 203-221PubMed Google Scholar). Within this map is the machinery studied so intensively by recording from single neurons and analyzing the receptive field properties. This realization that within the topographic map there was another dimension, the vertical distance between pial surface and white matter, prompted the deep thought that “the machinery may be roughly uniform over the whole striate cortex, the difference being in the inputs. A given region of cortex simply digests what is brought to it, and the process is the same everywhere…. It may be that there is a great developmental advantage in designing such machinery once only, and repeating it over and over monotonously, like a crystal” (Hubel and Wiesel, 1974aHubel D. Wiesel T. Uniformity of monkey striate cortex: A parallel relationship between field size, scatter, and magnification factor.J. Comp. Neurol. 1974; 158: 295-306Crossref PubMed Scopus (600) Google Scholar, in the paper that they considered their most important after their 1962 paper). Contrariwise, Hübener et al., 1997Hübener M. Shoham D. Grinvald A. Bonhoeffer T. Spatial relationships among three columnar systems in cat area 17.J. Neurosci. 1997; 17: 9270-9284PubMed Google Scholar, on the basis of 2D optical imaging of the intrinsic signal evoked by various stimuli, suggested instead that the cortex “could not be considered a crystalline structure built from identical modules, but rather it is composed of ‘mosaics’ of functional domains for the different properties.” This latter view of functional mosaics, however, does not capture the fact that all recording methods show that there is continuity in many of the maps and that each neuron expresses not just one property, but a number of properties. These multidimensional receptive fields of single neurons means that different properties that map onto a given cortical surface can never be simply segregated into separate “modules.” However, the same multidimensionality is represented in orderly 3D mappings, forcing us back to the central conundrum of how this multidimensionality is generated in the physical circuits. Although the concept of an identifiable “minicolumn” has a wide currency (Mountcastle, 1997Mountcastle V.B. The columnar organization of the neocortex.Brain. 1997; 120: 701-722Crossref PubMed Scopus (1420) Google Scholar, Peters and Yilmaz, 1993Peters A. Yilmaz E. Neuronal organization in area 17 of cat visual cortex.Cereb. Cortex. 1993; 3: 49-68Crossref PubMed Scopus (102) Google Scholar, Rockland and Ichinohe, 2004Rockland K.S. Ichinohe N. Some thoughts on cortical minicolumns.Exp. Brain Res. 2004; 158: 265-277Crossref PubMed Scopus (85) Google Scholar), to suppose that there is some acreage of gray matter that sensible scientists will agree contains an essence of their “cortical column” seems doubtful. There is simply a mismatch between the anatomy and the functional maps. The notion of the minicolumn or module does not properly capture the granularity or the vertical and lateral interdigitation of component neurons that seems to be the essence of the cortical circuit. This means that even in a highly specialized “column” such as those evident in the rodent barrel cortex, one cannot simply clip out a cylinder of tissue that contains the whole local circuit, for later reconstruction “in silico” (Markram, 2006Markram H. The blue brain project.Nat. Rev. Neurosci. 2006; 7: 153-160Crossref PubMed Scopus (758) Google Scholar, Helmstaedter et al., 2007Helmstaedter M. de Kock C.P. Feldmeyer D. Bruno R.M. Sakmann B. Reconstruction of an average cortical column in silico.Brain Res. Rev. 2007; 55: 193-203Crossref PubMed Scopus (69) Google Scholar). This is not to say that detailed “bottom-up” models should not" @default.
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• W2034139708 date "2007-10-01" @default.
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• W2034139708 title "Mapping the Matrix: The Ways of Neocortex" @default.
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• W2034139708 doi "https://doi.org/10.1016/j.neuron.2007.10.017" @default.
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