Disruption in the Inhibitory Architecture of the Cell Minicolumn: Implications for Autisim

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2003 9: 496NeuroscientistManuel F. Casanova, Daniel Buxhoeveden and Juan Gomez

Disruption in the Inhibitory Architecture of the Cell Minicolumn: Implications for Autisim

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496 THE NEUROSCIENTIST Lateral Inhibition in AutismCopyright © 2003 Sage PublicationsISSN 1073-8584

Notwithstanding the major classes of neurons, identify-ing and classifying inhibitory interneurons has provenvery difficult. Lund and Lewis (1993) reported 13 sepa-rate classes of local circuit neurons in monkey prefrontalcortex, only 5 of which resembled those found inhumans. The potentially large variety for different celltypes has negated the concept that “the” neuron repre-sents an element of the brain in the same way that hepa-tocytes or myocytes characterize their respective organs.In other parts of the body, specific cells unequivocallymanifest the particular function of that organ. However,the same cannot be said of the cerebral cortex whereindividual neurons seem incapable of producingthoughts or complex behaviors. Furthermore, the largevariety of neuronal cell types questions the wisdom ofthose studies that focus on single-cell pathology in com-plex behavioral disorders such as autism or schizophre-nia. Mental function requires a multitude of neuronalnetworks working together in temporal synchrony. Inthis regard, a focus on the columnar organization of theneocortex rather than on individual cells may better

show how the mind works under normal conditions andpathological states.

A system exists when the properties of the whole aregreater than the sum of its functionally related parts—that is to say, when the examination of its constituentelements results in unexpected consequences. The pres-ence of systems within an organ implies a graded cytoar-chitectural organization. In the primate brain, embryo-genic systems composed of vertical columns of cortexare called “modules.” In these arrangements, connectiv-ity within modules is stronger than between them.Modules embody a second property: their constituentcells share similar stimulus/response properties. Thesmallest neocortical module capable of information pro-cessing is the minicolumn (Mountcastle 1998).

Strict biological reductionism would require that thefunction and differentiation of the minicolumn be com-pletely explained in terms of its component neurons.However, minicolumns have emergent properties thatare not proper to the individual neurons (Fig. 1). Theseproperties are mediated by the relationship among theneurons and their connections (i.e., cortical afferent,efferent, and interneuronal). It is noteworthy that signalprocessing by minicolumns may become self-reinforcing,that is, reveal a tendency to magnify small effects underappropriate conditions. In neurophysiology, this effect ismediated through positive feedback. This phenomenonis well known in neurosurgery, which employs subpialtransection rather than cortical ablation for cases inwhich focal seizures involve the primary cortices or thelanguage regions of the brain (e.g., Landau-Kleffnersyndrome). This surgical procedure is intended to tran-sect those horizontal connections of minicolumns impli-cated in the kindling of an ictal event. Because affected

Disruption in the Inhibitory Architecture of the Cell Minicolumn: Implications for AutisimMANUEL F. CASANOVA, DANIEL BUXHOEVEDEN, and JUAN GOMEZ

The modular arrangement of the neocortex is based on the cell minicolumn: a self-contained ecosystem ofneurons and their afferent, efferent, and interneuronal connections. The authors’ preliminary studies indi-cate that minicolumns in the brains of autistic patients are narrower, with an altered internal organization.More specifically, their minicolumns reveal less peripheral neuropil space and increased spacing amongtheir constituent cells. The peripheral neuropil space of the minicolumn is the conduit, among other things,for inhibitory local circuit projections. A defect in these GABAergic fibers may correlate with the increasedprevalence of seizures among autistic patients. This article expands on our initial findings by arguing for thespecificity of GABAergic inhibition in the neocortex as being focused around its mini- and macrocolumnarorganization. The authors conclude that GABAergic interneurons are vital to proper minicolumnar differen-tiation and signal processing (e.g., filtering capacity of the neocortex), thus providing a putative correlate toautistic symptomatology. NEUROSCIENTIST 9(6):496–507, 2003. DOI: 10.1177/1073858403253552

KEY WORDS: Autistic disorder, Cerebral cortex/pathology, Computer simulation

This study was funded by grants from the Stanley Medical ResearchFoundation, the VA Merit Review Board, and the National Institutes ofMental Health (grants MH61606 and MH62654).

Department of Psychiatry and Department of Neurology, Pathology,Anatomy and Cell Biology; Medical College of Georgia (MFC).Department of Psychiatry, Medical College of Georgia (DB, JG).

Address correspondence to: Manuel F. Casanova, Gottfried andGisela Kolb Endowed Chair, Department of Psychiatry andBehavioral Science, University of Louisville, Health SciencesCenter, 500 South Preston St., Bldg A, Louisville, KY 40292 (e-mail:[email protected]).

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Volume 9, Number 6, 2003 THE NEUROSCIENTIST 497

patients are not born with seizures but develop them dur-ing infancy, the minicolumn in this instance exhibits aperversion of Hebbian learning.

Minicolumns are reiterative elements of the neocortex(Fig. 2). They are defined anatomically by the positionof bundles: those composed of apical dendrites, myeli-nated axons, and double-bouquet axons. In Nissl-stainedsections, these components are integrated into single-cell radial structures spanning layers II through VI (Fig.3). The total content of cells per minicolumn varies from60 to 100. Certain areas, such as koniocortex (i.e., stri-ate cortex), show a two- to threefold increase in num-bers. The genesis of this structure appears early in gesta-tion. A series of symmetrical divisions of periventricularprecursor cells first define the total number of mini-columns. Then, a subsequent wave of asymmetrical divi-sions determines the total number of cells within theminicolumns. Although the radial path of minicolumnarprecursor cells is well known, some interneurons maypursue a longer tangential approach to the cortex(Corbin and others 2001).

Recent reports have suggested that autism may resultfrom a minicolumnopathy (Casanova and others 2002b,2002c). More specifically, minicolumns in the brains ofautistic patients were both more numerous and narrowerthan normal. Furthermore, their constituent neuronswere more dispersed than in controls, accounting for anormal cellular density. Similar results have now beenreported in high-functioning autism or Asperger’s syn-drome (Casanova and others 2002a). In both autism andAsperger’s syndrome, narrowing of the minicolumnswas most prominent for the peripheral neuropil com-partment. Because this compartment encases theunmyelinated projections of some interneurons,researchers have postulated a deficit of inhibition inautism (Casanova and others 2002b, 2002c). This wouldprovide a pathological correlate to some autistic symp-tomatology, for example, the expression of seizures andamelioration of certain behavioral traits with anticonvul-sants (Casanova, Buxhoeveden, and Brown 2002). Thisarticle will focus on deficits of inhibition as they pertainto the organization of cortical minicolumns. It will alsosuggest how such a deficit may contribute to dysfunctionin autism.

Minicolumns and Macrocolumns

The somas of cortical neurons are not randomly distrib-uted in space; they are organized in both layers and dif-ferent-sized columns or modules. Similarly, some den-dritic and axonal ramifications that begin or end in thesesomas are wired in parallel groups of fibers. This repet-itive pattern of connections and cellular bodies, a puta-tive “crystalline structure of the cortex,” is the key tounderstanding the huge processing capacity of the brainand its modular arrangement (see Box 1).

The modular organization of the brain may be said tospan four hierarchical levels: 1) the individual minicol-umn, 2) the engagement of multiple minicolumns instructures less than a single macrocolumn, 3) an entiremacrocolumn, and 4) large-scale networks of macro-columns. This hierarchical model does not include alevel composed of multiple adjacent macrocolumns. Inbarrel field cortex, blocking GABA-mediated synapticinhibition causes a lateral spread of excitation for layersII/III and V that is restricted to the barrel of origin(Petersen and Sakmann 2001).1 It thus appears that neu-rons from a particular macrocolumn do not communi-cate with neighboring barrels. Rather, outputs from indi-vidual barrels are preferentially directed toward neuronsof the parent column (Laaris and Keller 2002).

The highest level of modularity within the brain is anetwork of macrocolumns. These networks are geo-graphically noncontiguous and widely distributedthroughout the neocortex. Although these networks holdthe promise of unraveling global cognitive processes,this article will not deal with them. Alternatively, thelowest level of neocortical modularity is the minicol-umn. The minicolumn is the unit of anatomy that reiter-ates itself throughout the neocortex while its functionsimultaneously reflects the holistic properties of thebrain: afferent, efferent, and central processing(Buxhoeveden and Casanova 2002a, 2002b). Reelin, aglycoprotein produced and secreted by Cajal-Retziuscells, appears to be involved in the development of thesevertical structures (Nishikawa and others 2002).Discussions of minicolumns usually focus on their com-ponent neurons and connections. However, astrocyteswith interlaminar processes may provide an essential

A 2 E Y 7 C

Fig. 1. Recurrence or reentry is an essential feature within theorganization of minicolumnar assemblies. An increase in thenumber of minicolumns is accompanied by a still larger increasein their connective infrastructure. Those minicolumns that tendto discharge together will be selected and their synapsesstrengthened. Slight modifications in the connectivity of involvedminicolumns can generate novel representations that are notreducible to inputs of the original minicolumns. It is through theproliferation and apposition of supernumerary minicolumns thatnew cortical areas may be formed in the course of evolution. Inthis illustration, the two interconnected minicolumns are notblank slates but have developed a stimuli history with other, notnecessarily adjacent, minicolumns.




498 THE NEUROSCIENTIST Lateral Inhibition in Autism

role by maintaining the spatial definition of mini-columns and isolating them from neighboring units(Colombo and others 2000; Colombo 2001). Thick,Nissl-stained sections allow the visualization of mini-columns as central cellular cores surrounded by cell-poor areas. Cell-poor areas (the peripheral neuropilspace of the minicolumn) are rich in unmyelinated(inhibitory) axon fibers, dendritic arborizations, andsynapses (Buxhoeveden and Casanova 2002a, 2002b).Multiple minicolumns aggregate into hexagonal-likearrangements called macrocolumns (Fig. 4).

The cells of macrocolumns respond to similar but notidentical features (Tanaka 1997). The subtle variations inresponse properties seem to be a function of individualminicolumns within the larger module. Estimates for thenumber of minicolumns occupying a macrocolumnrange between 60 and 80 (Favorov and Kelly 1994a,1994b; Calvin 1998). Macrocolumns have been theobject of greater scientific inquiry than have the mini-columns that constitute them. Examples of macro-columns include barrels in rodent somatosensory cortex,segregates in cat and monkey somatosensory cortex, andhypercolumns in visual cortex. Macrocolumns havebeen studied by electrophysiological means, immunocy-

A B

C D

Fig. 2. Minicolumns during development. (A) Ontogenetic cell columns at 18 weeks of gestation. (B) Ontogenetic cell columns at 28weeks of gestation. Note onset of lamination with increased lateral and vertical spacing between cells in layer III. (C) Cell columns(pyramidal cell arrays) in a 4-year-old. (D) Pyramidal cell arrays in a 50-year-old. Layer III is in the center and layer IV at the bottom.(Nissl-stain, (A) at 200X magnification, (B), (C), and (D) at 100X magnification.)

Box 1: Lashley Revisited

The function of minicolumns lends itself to com-parisons with logic gates and even to microproces-sors. In the simpler example, minicolumns as bio-logical gates have the advantage of small size, lowpower consumption, and reliability. The white mat-ter provides for the connectivity of the logic gate(minicolumn), making the thalamocortical, associ-ation, and commissural connections the circuit dia-grams of the brain. Minicolumns throughout theneocortex may follow the same anatomical andphysiological template; that is, they may act as asingle logic gate. The fact that all minicolumns maystem from a primordial template is exemplified bythe unvarying use of layers II and III for association(e.g., corticocortical integration), layer IV forreception, and layers V and VI for efferent connec-tivity. It is therefore noteworthy that combinationsof single logic gates (i.e., NOR) can provide forhigher-level functions capable of implementing anycomputer program.





tochemistry, and optical imaging. Physiologically,macrocolumns may exist as “topographic entities due inlarge part to the operations of the spiny-stellate cells oflayer IV and the double-bouquet cells of the superficiallayers” (Favorov and Kelly 1994a; Favorov and Kelly1994b, p 408). Anatomically, dendritic branching andaxonal patches (intrinsic and extrinsic) are used todefine the size of macrocolumns. In somatosensory cor-tex, the anatomical basis of a macrocolumn is the termi-nation of thalamic afferents that occur in focal clustersmeasuring hundreds of microns in width (Mountcastle1997). Research has found that axonal terminal patchestypically match the size of dendritic arbors (Elston andRosa 2000; Lubke and others 2000). This fact suggests apredetermined (not coincidental) structure for theiraggregate fields. Thalamic activity is relayed in the ver-tical direction and limited in the horizontal direction byan input cluster. This activity engages all neuronal typesacross all horizontal lamina. The bundling of afferent

axons also includes association and commissural sys-tems. Thus, the widths of the terminal fields of callosalafferents equal those of the thalamic bundles with whichthey interdigitate or, under certain circumstance, becomeconvergent (i.e., pyramidal cells in layer IIIb can bothemit callosal fibers and receive direct input from thala-mic afferents) (Mountcastle 1997).

Minicolumns and Inhibitory Circuits

The neocortex, with its minicolumnar organization, pre-sents a specific type of inhibitory circuit. Minicolumnsuse at least two basic forms of inhibition: lateral (or sur-round) and intrinsic. Lateral inhibition sharpens the bor-ders of minicolumns and increases their definition(Marin-Padilla 1970; Szentagothai 1978; DeFelipe andothers 1990; Favorov and Kelly 1994a, 1994b; DeFelipe1999). The primary source for this inhibitory effect maybe derived from axon bundles of double-bouquet cells

Fig. 3. Vertical components in the cortex. The following elements contribute to the anatomical vertical orientation, as well as to phys-iological vertical bias of the neocortex: (A) Pyramidal cell arrays. Pyramidal cell somas of layers III, V, and VI are vertically oriented(Schlaug and others 1995). (B) Interneurons. Studies have shown that GABAergic cells tend to be vertically aligned within the cortex(DeFelipe and Jones 1985; Somogyi and Soltesz 1986). Marin-Padilla (1970) reported a vertical alignment of basket cells in humanmotor cortex. (C) Axons. Each minicolumn contains one myelinated efferent bundle extending from layers II/III to layer VI (Peters andSethares 1996) and at least one double-bouquet axon bundle (DeFelipe and others 1990; Peters and Sethares 1997). Layer IV stellatecells send axons vertically to supragranular layers. (D) Dendrites. Layers V/VI pyramidal cells have bundles of vertically oriented den-drites that extend upward within a column (Peters and Sethares 1991). Dendrites of nonpyramidal cells also have strong vertical ori-entation (Jin and others 2001; Kozloski and others 2001). (E) Overlay. The previously mentioned components are grouped togetherwithin the confines of a minicolumn.





(DeFelipe and others 1990; Favorov and Kelly 1994a)and basket cells (Marin-Padilla 1970) (Fig. 5). Theaxons of double-bouquet cells arrange themselves inessentially repeatable patterns varying between 15 and30 µm wide, depending on the cortical area examined(DeFelipe and others 1990; DeFelipe 1999), and areconsidered by some to be the source of lateral inhibi-tion of neighboring minicolumns. The synaptic patternsof double-bouquet axons are complex, apparently con-tacting a variety of cell types including pyramidal, spinystellate cells, and nonpyramidal cells. All of the contactsare dendritic of which approximately 60% are found onsmall to medium dendritic shafts (1-2 µm) and theremainder on distal spines. Among the possible func-tions that have been postulated for double-bouquet cellsare that 1) they inhibit inhibitory interneurons (disinhi-bition) within a column so as to allow the unopposedflow of vertical excitation from spiny stellates withinthat minicolumn, and 2) the vertical descent of axonsacross the lamina inhibits dendritic terminals belongingto excitatory cells in neighboring minicolumns.However, the implication that double-bouquet axon bun-dles are the source for a powerful surround inhibition(Favorov and Kelly 1994a) has not been demonstrated.

The study by DeFelipe and others (1986) in monkeysensory-motor cortex also suggests that basket cells haveseveral functions regarding columnar organization. Amajority of the horizontal axonal connections remainswithin a macro-size column, whereas a small number ofthese extend beyond this to encompass two or moremacrocolumns. Most dendritic fields of basket cells arecontained within a more narrow area averaging about800 by 500 µm and vertically crossing at least three lay-ers. The long-range (horizontal) myelinated axons crossthe equivalent of two or more macrocolumns, with someextending as far as 2 mm. However, these long-range con-

nections are said to represent only a minority of the col-laterals from basket cells. Therefore, although basket cellsreceive input that is restricted to one macrocolumn, someare capable of influencing signals in neighboring units.The basket cell dendrite appears well suited for unificationof a macrocolumns size unit, whereas that double-bouquetcell is clearly suited for minicolumn size control.

Intrinsic inhibition, on the other hand, regulates theflow of information within a minicolumn. One functionof intrinsic inhibition is the transfer of informationbetween horizontal layers within a narrow vertical corti-cal field. Already during development, excitatory thala-mic inputs establish connections with minicolumns.These inputs are disseminated via spiny stellate cells(and apical dendrites of lamina V) radially to supra- andinfragranular layers to establish a vertical organizationbased on shared excitation. In addition, thalamocorticalafferents participate in a feedforward pathway toinhibitory interneurons in layer IV. After an initial volleyof excitatory input, thalamic connections excite inhibito-ry interneurons, which then fire on short latency. Theaxons of layer IV interneurons are anatomically alignedvertically. This suggests that after a thalamic volley, inhi-bition flows upward to the supragranular layers, in thesame way as excitation from the stellate and pyramidalcells. Interestingly, excitatory interneurons in layers IIIband IV are responsible for projecting information verti-cally in narrow bundles 100 to 200 µm wide. Becausethis is larger than a typical minicolumn but smaller thana macrocolumn, it raises the possibility that dynamiccolumnar units comprise multiple minicolumns withinthe confines of a “parent” macrocolumn (level 2 of themodular organization, vide supra). Intrinsic inhibitionwould be capable of subdividing them, whereas disinhi-bition would serve to merge them.

A B

A B Fig. 4. Vertical compartments within minicolumns. (A)Schematic representation of the major vertical compo-nents of cell columns viewed from a horizontal perspec-tive (blue circles: myelinated bundles; green circles: apicaldendrite bundles; red circles: double-bouquet axonbundles). The illustration represents a tangential sliceat the upper level of layer IV in striate cortex. Peripheralneuropil space is labeled “A”; core area is labeled “B.”The core space comprises 90% of the neurons in acolumn. The relationship between core area and theperipheral neuropil space varies. In human area Tpt,the core generally occupies between 50% and 60% ofthe total area. The three fiber bundles depicted here arefound in each minicolumn and are a regularly spaced,common feature of the primate neocortex (Peters andSethares 1997). Different projections are segregatedinto separate parallel channels. This configurationallows for parallel processing among neighboring mini-columns. (B) Minicolumn input and output. Schematictwo-dimensional representation of major minicolumnpathways and circuits. Information is received and sentin all dimensions of the column: on top via layer I fibers;at the bottom via the major thalamic, association, andcommissural pathways; and within the column (graymatter) via horizontal connectivity.





The excitation-inhibition interface is vital to neuro-logical function because it determines the filtering prop-erties2 of the tissue and the ultimate fate of an incomingsignal. Inhibition and excitation act not in opposition butas part of a synchronized whole. Exploiting temporalstimulus parameters requires precise timing of sensorypathways (Grothe and Klump 2000). Temporal dynamicsin the brain are generated by propagation delays of neu-ral pathways, synaptic delays, membrane time constants,

and the interaction of excitatory and inhibitory factors incellular compartments and ionic channels. Recently,GABAergic inputs have been seen as crucial to phaselocking and for precise coincidence detection over awide range of stimulus intensities (Grothe and Klump2000). In motor cortex, intrinsic cortical circuits pro-mote temporal coordination of cortical modules in theexecution of complex movement patterns (Keller 1993).In the spinal cord, sensory-motor processing is provided

DB

CH

BC

BD

AD

AX

ON

DBBarrel Column

ActivatedInhibited

A B

C

Fig. 5. Inhibitory cells. (A) Double-bouquet cell: the axon bundlesof these cells contact small to medium dendritic shafts and distalspines of apical and basal dendrites. The double-bouquet cellsends long vertical axons in tight bundles hundreds of micronsinto the cortex, beginning deep in layer II and extending to layer V,although this varies with cortical area. Chandelier cell: thisinterneuron synapses directly onto the axon hillock of pyramidalcells. Basket cell: this inhibitory cell contacts the dendritic initialsegment and cell soma thereby modulating the input phase to thepyramidal cell. Budd and Kisvarday (2001) reported peak connec-tions of clutch cell axons (axon terminals) within a 30 to 45 µmradius of the cell (i.e., the size of the minicolumn). (B) This figurepostulates how inhibitory interneurons can create smaller inhibito-ry domains within larger units of function. Red lines indicate exci-tatory input. In section A, afferents first contact strong inhibitoryinterneurons, whereas in section B they converge first onto theexcitatory cells. The result is a biphasic response within a singlemacrocolumn. The inhibitory neurons in section B would either beinhibited or activated after the excitatory phase in section A hasbeen initiated. Porter and others (2001) showed that in mouse bar-rel cortex, only a subset of inhibitory interneurons is activated bythalamocortical inputs and that the afferents preferentially excitethe inhibitory interneurons. Inhibitory interneurons respondedmore vigorously at lower thresholds and shorter latencies thanexcitatory ones did. In barrel columns, as in minicolumns, inhibito-ry neurons enhance spatial contrast. In this instance, it occursbetween principal and adjacent whiskers (Shimegi and others1999). It does so by differentiating small versus large magnituderesponses (Brumberg and others 1996). Basket and chandeliercells participate in surround inhibition in barrel cortex. (C)Mountcastle (1997) referred to a “vertical stream of inhibition” pro-vided by the axon bundles of double-bouquet cells. In this dia-gram, minicolumn 2 receives a strong stimulus and is immediate-ly able to inhibit its neighboring columns. This creates the contrastneeded to enhance somatosensory discrimination. The exact roleof the double-bouquet cell is far from understood, and otherinterneurons such as basket and chandelier cells may be involvedin the lateral inhibition of minicolumns.





by tightly knit circuits containing a variety of inhibitorycell types such as the Renshaw cell (recurrent inhibition)and the Ia inhibitory interneuron (reciprocal inhibition).

The excitatory convergence model of Hubel andWiesel has been the dominant paradigm for approxi-mately 40 years (1962). However, an increased role forlocal inhibitory circuits is being proposed for the visualcortex—in this regard, a model for other cortical areas.Some recent articles have discussed emerging modelsfor the functioning of orientation columns in the visualcortex. These studies propose that intracortical inhibito-ry systems are heavily implicated for selectivity of ori-entation (Vidyasagar and others 1996; Sompolinsky andShapley 1997). The theory of cross-orientation inhibi-tion (Somers and others 1995; Vidyasagar and others1996) suggests that intracortical inhibition, rather thanexcitatory input from the thalamus, creates orientationselectivity.

Based on these facts, we conclude that whereas thespread of excitation indicates the capacity of the mini-column to fuse and form bigger units, the spread of inhi-bition determines the capacity of a module to subdivideinto smaller units. The presence of inhibitory synapses inkey topographical locations indicates the potential of themodule for self-division. The dynamic competitionbetween inhibition and excitation determines whether aregion of interest exhibits discontinuity (modular limit)or continuity (modular fusion). In this context, complexmental pathology can result from a disruption in thiscompetition. Although Hussman (2001), for instance,suggested that autism might be caused by an array ofdefects in relatively independent systems, some haveargued that it could be reduced to a single dysfunction,that is, cortical inhibitory defect (Table 1). Among thereasons given as support for the hypothesis is thatpathology relating to GABA receptors is a common fea-ture in several suspected etiologies of autism. Both dis-inhibition of GABAergic influence and excessive stimu-lation of non-NMDA glutamate receptors generate pathol-ogy similar to autism. Furthermore, the most prevalentgenetic or environmental factor found among the first100 cases in the South Carolina autism project is an abnor-mality of the chromosome 15q that has three GABAreceptor subunit genes. Last, computer models that alterexcitation and inhibition levels provide for representa-tions of core autistic symptoms. Some of these modelshave critically tied the fundamental shaping of themacrocolumn during development to the correct balanceof excitation and inhibition of individual minicolumns.

Computer Models of Excitation and Inhibition

The model proposed by Favorov and Kelly (1994a,1994b) closely parallels physiological studies, differenti-ates between mini- and macrocolumns, and uses themain types of cells responsible for excitation and inhibi-tion. In this regard, their study may be more biologicallyaccurate than others discussed below. Favorov and Kelly(1994a, 1994b) ran computer models of segregate for-mation (macrocolumns) in primary somatosensory cor-

tex based on studies in rodent and monkey cortex. Theystudied segregates according to the effects of 1) excita-tory thalamocortical input, 2) thalamic input plus lateralexcitation, 3) the latter two plus the addition of inhibi-tion, and 4) the effects of varying the synaptic weights ofinhibition and excitation. Their model used three kindsof cells, those representing thalamic input (spiny stel-late), lateral excitation (pyramidal cell), and inhibition(double-bouquet cell). They argued that during perinataldevelopment, minicolumns play an important role in theselection of thalamic connections to neighboring mini-columns. The thalamic connections to individual mini-columns are shaped by the primary interaction of mini-columns with those neighbors belonging to the samesegregate. In other words, within-segregate self-organization of minicolumns induces an orderly patternof afferent connections. Lateral inhibition provides theminicolumn with diverse receptive fields arranged in ashuffled, yet orderly manner. Favorov and Kelly (1994a,1994b) found that in the presence of too much inhibi-tion, minicolumns within a segregate became highly dis-ordered. On the other hand, with a diminution of lateralinhibition, the segregates tended to merge. That is, exci-tatory lateral connections caused interconnected mini-columns to act more alike.

In a normal segregate, not all minicolumns are acti-vated at the same time but respond to different thalamicinputs. Inhibition provided by GABAergic cells, like thedouble-bouquet neurons, accounts for some of the sys-tem’s plasticity. An example in somatosensory cortexconcerns directional selectivity. A stimulus for a partic-ular direction will initially activate a single minicolumn(“x”) that in turn inhibits its immediate neighbors (“y”and “z”). The neighbor neurons (“y” and “z”) are thusinhibited from responding when the stimulus arrives attheir own receptive fields. The first minicolumn receiveslittle inhibition during most of its stimulus period.However, a stimulus moving in another direction wouldfirst activate the opposing minicolumn “y” with thesame sequence of events, thereby inhibiting “x” and pre-venting inhibition of “y” during most of the stimulus

Table 1. GABAergic Abnormalities in Autism

• Alterations in platelet, plasma, and urine GABA levels• Abnormalities in the gene coding for reelina as well

as in its tissue levels• Abnormalities in the long arm of chromosome 15

(near a cluster of genes coding for GABA receptor subunits)

• A paradoxical effect of benzodiazepines on autistic individuals

• Reduced GABAergic receptor binding in the hippocampus

• Increased incidence of seizures

The table is a summary of evidence from Dhossche and oth-ers (2002).a A glycoprotein involved in the regulation of GABAergic trans-mission.





period. This permits individual minicolumns to responddifferently to different stimuli such as point location,directional motion detection, and pressure (Box 2).According to Favorov and Kelly (1994b), thalamic con-nections to minicolumns are not prescribed according tosome preconceived idea (e.g., the mapping relationshipbetween skin and cortex) but are selected by the modelitself. The interaction between thalamus and mini-columns is therefore determined by its history of senso-ry stimulation.

Gustafsson (1997) has proposed another model basedon a neural circuit theory of autism referred to as “inad-equate cortical feature maps.” This model is based onKohonen’s “physiological self-organizing map” withHebbian learning,3 which has a columnar structure as anessential feature. He proposed that proper self-organizationof feature maps does not take place in autism. Featuresare defined as “characteristics of classes of objects thatare useful for distinguishing the objects within a class.”Gustafsson claimed that too much lateral inhibition nar-rows the range of information for a column. A given col-umn will be active (i.e., the output of neurons within itwill be simultaneously high) when a particular set of fea-tures is present in the input. During development,columnar structures develop and become ordered so thatobjects with similar features activate columns that are inclose proximity to each other (Kohonen 1988; Favorovand Kelly 1994a). The simplest lateral interactionbetween neurons is described according to a Mexicanhat function (Fig. 6) in which neighboring neurons coop-erate and distant neurons compete. This connectivitygives capacities to detect spatial differences in neuralactivity, and the network behaves as a generalized edgeor boundary detector. Edge detectors enhance contrastand ignore irrelevant details. Defects of this mechanismat higher levels, according to Gustafsson, cause an insis-tence on sameness and attention to irrelevant data.

A column does not distribute synaptic weights evenlyamong neurons. This allows for variability in the pro-cessing of the objects that activate the column.According to Gustafsson (1997), a wide column thatcontains many neurons has a wider spread of synapticweights than a narrow one has. Narrow columns withfewer cells facilitate “discrimination,” whereas widercolumns facilitate “generalization.” Our studies have

shown similar results: narrow columns (discrimination)in the brains of autistic individuals and broader ones(generalization) in dyslexia (Casanova and others 2002b,2002c; Casanova, Buxhoeveden, Cohen, and others2002). This has suggested “that minicolumns exist with-in a phenotypic spectrum that intertwines the inhibitory/excitatory flow of neocortical information with a tweak-ing of the signal-to-noise ratio relevant to feature extrac-tion” (Casanova, Buxhoeveden, Cohen, and others 2002,p 110).

Cohen (1994) created another computer model ofautism using artificial neural networks. The author test-ed the effects of having too many or too few neuronsoffering connections. The study revealed that too manyconnections produced excellent discrimination but infe-rior generalization because of an overemphasis ondetails unique to the training set. Although this studyused neurons as opposed to cell columns, it represents asimilar theme. An alteration in the balance between exci-tation and inhibition may account for some aspect ofautistic behavior. This study suggests a loss of the abili-ty to correctly oscillate between discrimination (inhibi-tion) and generalization (excitation). Unfortunately, thismodel does not take into account the effects of inhibi-tion, it is not a self-organizing model (which we prefer),nor does it speculate where such increases or decreasesin numbers of neurons occur within the modular organi-zation of the brain, whether in minicolumns or in macro-columns. It is fair to say that when this study was per-

Fig. 6. Lateral excitation and inhibition are modeled by bell-shaped functions with radial profiles shown (left). Each function is multi-plied by some positive constant representing its absolute strength, then inhibition is subtracted from excitation to yield the Mexicanhat model. In a module of normal minicolumns (center) with Mexican hat lateral connections, the active column in red has a net exci-tatory effect on its immediate neighbors shown pink, a net inhibitory effect on more distant minicolumns shown blue, and no signifi-cant effect on distant minicolumns. In a module in which the minicolumns are narrower, corresponding to a 50% reduction in inhibi-tion, lateral excitation dominates (right).

Box 2: Video Game Technology

We may think of minicolumns as a space bar in avideo game. In one game, the space bar is used tofire a cannon at invading aliens. Implementinganother software may cause a different function forthe space bar, for example, rotating a space ship orcausing a character to jump. The potentially limit-less number by which minicolumns may be used orcombined provides a mathematical explanation tothe vast number of operations entailed in complexcognitive processes.





formed, no clear evidence existed for cortical abnormal-ities in autism.

Because it is obvious that either too much excitationor inhibition can result in a breakdown in the processingof information, the question is which one of the afore-mentioned models best represents what is seen inautism. We agree with Gustafsson (1997) in the use ofthe columnar model and the role of inhibition but ques-tion his conclusions for the following reasons: 1) It failsto account for the predilection of epilepsy-seizure activ-ity seen in autism. Seizures are facilitated by a moveaway from discreteness toward a synchronization of sig-nals. If the pathophysiology of autism involved too muchlateral inhibition, it would not explain their increasedsusceptibility to seizures. A further difficulty is trying tocorrelate the autistic symptomatology of hypersensitivi-ties and increased discriminatory abilities (which wouldrequire narrow fields of inhibitory control) with seizures(which suggest a loss of inhibition). If minicolumns losetheir lateral inhibition to the extent that they cannotmaintain their individuality, a merging between themoccurs with a resultant diffusion of the afferent input(feature extraction) spread among several columns (Fig.6). 2) Narrow columns by themselves do not produceabnormal behavior. Humans and nonhuman primateshave much smaller minicolumns in visual cortex com-pared to those of other mammals. In this instance, thesmaller columns allow for more interconnections andresult in greater complexity required for primate vision(Peters and Yilmaz 1993). Similarly, the fact that mini-columns are also smaller in V1 than in other regions ofthe human cortex does not imply pathology. Last, thebrains of nonhuman primates contain smaller mini-columns than those of autistic patients without manifest-ing autistic-like behavior. The uniqueness of the mini-column in autism is that they are smaller relative to thenorm for the human condition. This suggests that theyare abnormal, either in their internal configuration, theirinterconnections, or both. 3) In addition to lateral mod-els of inhibition such as portrayed by the Mexican hatmodel, critical inhibitory defects can occur within a col-umn. One example is the temporal balance betweenfeedforward excitation and inhibition among thalamicafferents to layer IV stellate cells that regulate the inflowof thalamic information into the minicolumn. 4) TheMexican hat model (Fig. 6) used by the author may beincomplete. The Mexican hat model states that lateralexcitatory connections drive neighbors to develop simi-lar afferent connections, whereas minicolumns fartheraway are driven to develop dissimilar afferent connec-tions by inhibitory actions.4 Physiological data (Favorovand Kelly 1994a, 1994b) show that the receptive fieldsof individual minicolumns are not strictly topographicalin organization. An adjacent column may be responsiveto a very different part of the larger receptive fieldencountered in the segregate.5 Although the segregatewill exhibit the same feature extraction, the responseproperties of individual minicolumns within that segre-gate vary. In this regard, a more general function can be

used, for instance, a Gabor function (Pollen and Ronner1983; Field and Tolhurst 1986).

The Gabor function (Field and Tolhurst 1986) hasbeen useful in explaining edge detection and contrastenhancement for the visual system. It seems that theseproperties are diminished by a disruption of the normalbalance between excitation and inhibition. In Figure 6,for instance, we represent the lateral extension of excita-tion by a bell-shaped function, a cubic spline, whichpeaks at the center of a minicolumn. The lateral exten-sion of inhibition, on the other hand, is represented byanother bell-shaped function with a lower peak but ofgreater extent. In this way, the subtraction between exci-tation and inhibition, estimated for instance in terms ofsynaptic density, synaptic weight, or membrane poten-tial, can represent a good approximation of the Mexicanhat function (Wilson and Bergen 1979). It can be seenthat the alternation of dominance between the distribu-tion of excitation and inhibition can produce the lateralinhibition effects and its spatial filtering capacities. Themore fragile factor in this configuration appears to bethe inhibition around the periphery of the minicolumn,where a deficit of inhibitory fibers in autism has beensuggested (Casanova and others 2002b). The result ofsuch a defect is the disruption of the flow of informationbetween minicolumns.

One may conclude from these models that if we rep-resent the lateral extension of inhibition or excitation bybell-shaped functions of different peaks and widths, thenet balance between both determines the computationalabilities (filtering properties) of the model. Modelsbased on the Mexican hat function can explore the gen-eral properties of the spatial distribution of inhibitionand excitation, but only to a limited extent. The Mexicanhat function implies that interactions between units aresymmetrical and singular, whereas cortical lateral inter-actions are asymmetric, anisotropic, and usually withmany other columns.

Autism and Inhibition

Based on the descriptions given thus far, one may rea-sonably suspect a disruption of the normal balancebetween excitation and inhibition in the columnar organ-ization of autistic patients. Computer modeling suggeststhat such an imbalance biases the information-processingsystem toward more signal or discrimination. This biasmay explain some of the more publicized features of theautistic condition: highly focused savant skills (e.g., cal-endar calculators), hypersensitivities of all sensorymodalities (e.g., flickering of fluorescent lights), andsome eccentricities (e.g., eating the same food, wearingthe same clothes). In this regard, a series of noteworthystudies report that both children and adults with autismwere superior to a control group in their ability to dis-criminate novel, highly similar stimuli (Plaisted and oth-ers 1998). Autistic children also have superior ability todiscriminate display items in visual search tasks(O’Riordan and Plaisted 2001; O’Riordan and others





2001). O’Riordan (2000) stated that enhanced discrimi-nation in autism results from low-level perceptual pro-cessing of incoming stimuli, or what is called the bottom-up approach. This supports a model in which altered pro-cessing of sensory input occurs in the neocortex (e.g., adeficiency in the dampening of filtered information). Ifthis were the case, the enhancement of improper dis-crimination would likely operate at the level of the mini-or macrocolumn.

Another salient feature of autism is that by puberty,one-third of affected individuals will have suffered atleast two unprovoked seizures (Volkmar and Nelson1995). Interneurons both help define minicolumnarorganization and play a crucial role in epilepsy. DeFelipe(1999) proposed that a genetically determined decreasein the presence of a class of inhibitory interneurons(chandelier cells) can make the brains of individualsmore susceptible to seizure disorders. He argued that theconsiderable variability in human brain size and num-bers of GABA interneurons suggest significant dissimi-larities of internal connectivity. Furthermore, networksof inhibitory interneurons acting as GABA-gated pace-makers are critically involved in gamma oscillations(Bragin and others 1995; Traub and others 1996; Grotheand Klump 2000; Bartos and others 2002; Porjesz andothers 2002). Abnormalities in these mechanisms havebeen associated with binding problems (the coactivationof neural assemblies), which may be present in bothautism and schizophrenia (Shergill and others 2000;Grice and others 2001; Brock and others 2002; Lee andothers 2003).

The genesis of the minicolumn is defined early in ges-tation by a series of divisions of primordial cells liningthe anterodorsal aspect of the embryonic ventricles. Thefirst phase of symmetrical divisions defines the totalnumber of minicolumns. In primate species, both humanand nonhuman, this process usually transpires during thefirst 40 days of gestation. The increased number of mini-columns reported in autism (Casanova and others 2002b,2002c) therefore suggests a disruption during the earlierstages of gestation. The proposed timing correlates wellwith the observation of a high incidence of pervasivedevelopmental disorders in children with prenatal expo-sure to thalidomide (Rodier and others 1996, 1997) andthe concurrence of structural and functional brainstemabnormalities in autistic children (Hashimoto and others1992). This early insult may well interfere with some ofthe unfolding capabilities of the developing brain of anautistic patient.

A normal neonate does not come to the world as ablank slate. Rather, it demonstrates a number of behav-iors and potential capabilities that appear to be hardwired during gestation. Among these capabilities are theneonate’s preference for the mother’s complex vocaliza-tions, a temperament style, the capacity for object recog-nition, an internal grammatical structure, an ability toparse elements of spoken sounds, and even taste prefer-ence or aversion. An additional process that begins inutero is attachment in which the baby co-constructs with

his or her mother an inkling of who he or she is going tobe. This effort, if successful, provides scaffolding forfuture social constructs that will affect both early andadult relationships. Correlational data support the role oflack of attachment in the development of avoidantbehavior, problems at school, and a proclivity towardmood disorders. Interference with an internal workingmodel of relationships (i.e., the initial parental model)may provide for disturbances in proximity, reciprocity,and commitment when dealing with other people. Thiswill in turn require a greater investment from other peo-ple for an affective bond to develop. Furthermore, aminicolumnar abnormality may translate difficulties inthe integration of information (e.g., accommodation,assimilation) into a delay in language acquisition. In all,minicolumnar abnormalities may incapacitate a patientas a social being by distorting elements of the child’sbiopsychological experience. Williams James’s famousportrayal of the internal world of infants as “one greatblooming, buzzing confusion” may better serve todescribe the potential shimmering kaleidoscope of per-ceptual abnormalities caused by minicolumnopathies.

Notes

1. Nonetheless, cortical plasticity is present in rodent representa-tional maps and may be due to the extension of a small fraction of thal-amocortical input beyond the parent barrel (Arnold and others 2001).

2. Filtering refers to the capacity to accept or reject frequencychanges from a given stimulus.

3. The rules for Hebbian learning are the following: 1) the neuronresponding most strongly to an input pattern has its synapses modifiedsuch that it becomes more sensitive to that input, and 2) any two cellsor systems of cells that are repeatedly active at the same time will tendto become associated.

4. Recent studies using high spatiotemporal resolution BOLDfMRI have reported signal in the submillimeter range that may be com-patible with macrocolumnar activation following a Mexican hat func-tion (Kim and others 2000). These studies offer hope for discerning thespatial resolution of the macrocolumn under different challenges andbehavioral states.

5. From the “normal” Kohonen (1988) maps, it is well known thateven though there is a strong similarity property in these maps, therewill still be “ravines” (Kohonen’s wording) where neighboring neuronshave distinctly different (synaptic) weight vectors.

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Disruption in the Inhibitory Architecture of the Cell Minicolumn: Implications for Autisim