Autism Spectrum Disorders: Linking Neuropathological Findings to Treatment with Transcranial...

Online Proofing System Instructions

The Wiley Online Proofing System allows authors and proof reviewers to review PDF proofs, mark corrections, respond to queries, upload replacement figures, and submit these changes directly from the PDF proof from the locally saved file or while viewing it in your web browser.

1. For the best experience reviewing your proof in the Wiley Online Proofing System please ensure you are connected to the internet. This will allow the PDF proof to connect to the central Wiley Online Proofing System server. If you are connected to the Wiley Online Proofing System server you should see the icon with a green check mark above in the yellow banner.

2. Please review the article proof on the following pages and mark any corrections, changes, and query responses using the Annotation Tools outlined on the next 2 pages.

3. To save your proof corrections, click the “Publish Comments” button appearing above in the yellow banner. Publishing your comments saves your corrections to the Wiley Online Proofing System server. Corrections don’t have to be marked in one sitting, you can publish corrections and log back in at a later time to add more before you click the “Complete Proof Review” button below.

4. If you need to supply additional or replacement files bigger than 5 Megabytes (MB) do not attach them directly to the PDF Proof, please click the “Upload Files” button to upload files:

5. When your proof review is complete and you are ready to submit corrections to the publisher, please click the “Complete Proof Review” button below:

IMPORTANT: Do not click the “Complete Proof Review” button without replying to all author queries found on the last page of your proof. Incomplete proof reviews will cause a delay in publication.

IMPORTANT: Once you click “Complete Proof Review” you will not be able to publish further corrections.

Online Proofing System Instructions

Connected Disconnected

USING e-ANNOTATION TOOLS FOR ELECTRONIC PROOF CORRECTION

Once you have Acrobat Reader open on your computer, click on the Comment tab at the right of the toolbar:

This will open up a panel down the right side of the document. The majority of

tools you will use for annotating your proof will be in the Annotations section,

pictured opposite. We’ve picked out some of these tools below:

1. Replace (Ins) Tool – for replacing text.

Strikes a line through text and opens up a text

box where replacement text can be entered.

How to use it

x Highlight a word or sentence.

x Click on the Replace (Ins) icon in the Annotations

section.

x Type the replacement text into the blue box that appears.

2. Strikethrough (Del) Tool – for deleting text.

Strikes a red line through text that is to be

deleted.

How to use it

x Highlight a word or sentence.

x Click on the Strikethrough (Del) icon in the

Annotations section.

3. Add note to text Tool – for highlighting a section

to be changed to bold or italic.

Highlights text in yellow and opens up a text

box where comments can be entered.

How to use it

x Highlight the relevant section of text.

x Click on the Add note to text icon in the


x Type instruction on what should be changed

regarding the text into the yellow box that

appears.

4. Add sticky note Tool – for making notes at

specific points in the text.

Marks a point in the proof where a comment

needs to be highlighted.

How to use it

x Click on the Add sticky note icon in the


x Click at the point in the proof where the comment

should be inserted.

x Type the comment into the yellow box that

appears.

USING e-ANNOTATION TOOLS FOR ELECTRONIC PROOF CORRECTION

5. Attach File Tool – for inserting large amounts of

text or replacement figures.

Inserts an icon linking to the attached file in the

appropriate place in the text.

How to use it

x Click on the Attach File icon in the Annotations

section.

x Click on the proof to where you’d like the attached

file to be linked.

x Select the file to be attached from your computer

or network.

x Select the colour and type of icon that will appear

in the proof. Click OK.

6. Drawing Markups Tools – for drawing

shapes, lines and freeform annotations on

proofs and commenting on these marks.Allows shapes, lines and freeform annotations to be

drawn on proofs and for comment to be made on

these marks.

How to use it

�� Click on one of the shapes in the Drawing Markups

section.

�� Click on the proof at the relevant point and draw the

selected shape with the cursor.

�� To add a comment to the drawn shape, move the

cursor over the shape until an arrowhead appears.

�� Double click on the shape and type any text in the

red box that appears.

REVIEW ARTICLE

Autism spectrum disorders: linking neuropathological findings to treatmentwith transcranial magnetic stimulationManuel F. Casanova ([email protected])1, Estate Sokhadze1, Ioan Opris2, Yao Wang1,3, Xiaoli Li31

1.Department of Psychiatry, University of Louisville, Louisville, KA, USA2.Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NA, USA3.State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China2

Keywords

Autism spectrum disorder, Cerebral cortex,Minicolumn, Transcranial magnetic stimulation

CorrespondenceM F Casanova, MD, Gottfried and Gisela KolbEndowed Chair in Psychiatry, Department ofPsychiatry, University of Louisville, 500 SouthPreston Street, Bldg A, Rm 217, Louisville, KY40202, USATel.: xxxx |Fax: xxxx |3

Email: [email protected]

Received10 December 2014; revised 15 January 2015;accepted 20 January 2015.

DOI:10.1111/apa.12943

ABSTRACTPostmortem studies in autism spectrum disorder (ASD) individuals indicate the presenceof abnormalities within the peripheral neuropil space (PNS) of cortical minicolumns. Thegeometrical orientation of inhibitory elements within the PNS suggests using repetitivetranscranial magnetic stimulation (rTMS) to up-regulate their activity. Several rTMS trials inASD have shown marked improvements in motor symptomatology, attention andperceptual binding.Conclusion: rTMS is the first therapeutic attempt at ASD aimed at correcting some of itscore pathology.

INTRODUCTION

Bauman and Kemper’s pioneering histoanatomic studiesbriefly described the presence of cerebral cortex pathologywithin their series of autism spectrum disorder (ASD)individuals. Described changes included an indistinct lam-inar pattern and minor cortical malformations or dysplasias(1). Nevertheless, the first group to emphasise the role ofthe cerebral cortex in the neuropathology of ASD was thatof Bailey et al. (2). Since then many studies have underlinedindividual aspects of this pathology including changes inneuronal size and density (3), abnormalities of minicolum-nar morphometry (4,5), heterotopias (6), the presence ofsupernumerary cells in both the molecular layer and thesubplate region (7) and dysplasias (8). The prominence andprevalence of cortical pathology along with reports ofwidespread heterotopias has prompted some researchers tosuggest that, in some cases, ASD results from the hetero-chronic divisions of germinal cells (periventricular and

rhombic lip) giving rise to the desynchronisation in matu-ration between radially derived pyramidal cells and tan-gentially derived interneurons (9). This abnormality ofgerminal cell division and later migration appears to explainmany of the reported neuropathological and clinical aspectsof both idiopathic and syndromic autism. In this regard,autism can be considered a neurodevelopmental disorder asit impairs the growth and development of the brain.

The cerebral cortex provides the mainboard of crucialcircuitry that allows for the emergence of higher cognitivefunctions such as attention, memory, judgment, languageand empathy. Impairments of corticogenesis usuallymanifest themselves early in life as varying degrees ofcognitive dysfunction for which they are traditionallylabelled as neurodevelopmental disorders. Understanding

Abbreviations

ASD, Autism spectrum disorder; DLPC, Dorsolateral prefrontalcortex; EEG, Electroencephalography; ERP, Event-related poten-tial; GABA, Gamma-aminobutyric acid; HF, High frequency;HRV, Heart rate variability; kA, Kilo-amps; LF, Low frequency;M1, Primary motor cortex; MRCP, Movement related corticalpotential; PNS, Peripheral neuropil space; rTMS, RepetitiveTranscranial Magnetic Stimulation; S1, Primary somatosensorycortex; SCL, Skin conductance level; SMA, Supplementarymotor area; TMS, Transcranial Magnetic Stimulation.

Key notes

! The presence of heterotopias and dysplasias in thebrains of autistic individuals clearly frame the conditionas a neurodevelopmental disorder.

! The smallest unit of information processing within themodular organisation of the cerebral cortex is theminicolumn.

! The presence of neuronomorphometric abnormalitieswithin the periphery of minicolumns in the brains ofautistic individuals suggests using low frequency repet-itive transcranial magnetic stimulation (rTMS) as apossible treatment intervention.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

©2015 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd 1

Acta Pædiatrica ISSN 0803-5253

AP

A12943

Dispa

tch:

3.2.15

CE:Se

linAar

thi

Journ

alCode

ManuscriptNo.

No.

ofpa

ges:

10PE:T

hang

araj

the mechanisms for the development of the cerebral cortexis therefore of major importance when discussing thepathogenesis of autism.

In this article, we will summarise recent findings regard-ing the organisation of the cerebral cortex, its ontogeneticorigin and related neuropathological findings in the brainsof ASD individuals. Subsequently, we will describe how thetopographical specificity of these abnormalities, beingprimarily within the periphery of minicolums, is amenableto treatment with repetitive transcranial magnetic stimula-tion (rTMS). We finalise the article by summarising theresults of different clinical trials using rTMS in ASD.

CORTICAL MODULARITY

The cerebral cortex is organised into different areas thatprocess information in a hierarchical feedforward manner.Although it would be profitable to differentiate these areasin a quantitative and unbiased manner this endeavour hasbeen fraught with difficulties. At present, techniques forvisualising cell morphometry can only poorly demarcatelarge portions of the cortex. About two-thirds of thecerebral cortex lies buried in folds under the surface ofthe brain. The curvature and repositioning of cellularelements in these abstruse areas has confounded research-ers to such an extent that their existence has been ignoredin different neuroanatomical treatises. Indeed, the limita-tion of cytoarchitectural techniques led neuroanatomists toconclude that attempts at subdividing the cerebral cortex byhistological methods would prove unprofitable, if notimpossible. For many decades it has thus been recom-mended to complement cytoarchitectural surveys withother techniques, notably those based on fibre connectivity.Indeed the lack of ‘cookie cutter borders’ between cytoar-chitecturally defined parcellations of the cerebral cortex hasled to an alternate affiliation system based on functionalconnections.

Attempts at parsing the cerebral cortex by means offunctional connections have yielded a limited number ofdiscrete areas (10–12) where Information travels in astereotyped manner going from the extrapersonal space toidiotypic cortex (primary sensory and motor areas) andfrom there to homotypical (unimodal and heteromodal),paralimbic and limbic cortices. As there is an infinitenumber and variety of inputs the proposed computationsystem begs the question as to how intrinsic cortical circuitsare adapted to so many different tasks. According toCreutzeldt (13) the cerebral cortex overcomes this obstacleby instantiating a canonical circuit that provides for similartransformations throughout the cerebral cortex (Fig. 1).This view upholds that functional differences among brainregions depend on variations in input sources, outputtargets, interconnectivity and the modulatory effect ofinhibitory influences.

Common patterns in the organisation of nerve cells andtheir connections (i.e. microcircuits) have been described inthe cerebral cortex of all examined mammalian species.Lorente de N!o was the first to discuss the physiological role

of ‘vertical cylinders’ of cells when he famously said: ‘All theelements of the cortex are represented in it, and therefore itmay be called an elementary unit, in which, theoretically,the whole process of transmission of impulses from theafferent fibre to the efferent axon may be accomplished’(14). Later on electrophysiological studies by Mountcastlehelped define a minicolumnar organisation of neurons thatencoded similar features and shared nearly identical termi-nal fields (15). Over the years it has become clear that therepetitive and ‘on-demand’ event-based nature of theproposed canonical circuit is an enabler of neuroplasticitythat allows different areas of the cerebral cortex to processinformation stemming from varied sources, including somethat are artificial in nature.

In recent years, Opris et al. (16) have implemented theuse of custom-designed conformal (i.e. following the longi-tudinal contour of the cortex) multielectrode recordingarrays to describe the coding of interlaminar circuitrywithin and between minicolumns (Fig. 2). Their group hasfound that substituting firing patterns of layer 5 neuronswith electrical stimulation during minicolumnar transmis-sion from layers 2/3 improved task performance (targetselection) in primates (17). More importantly, when micro-electrode stimulation was applied following the pharmaco-logical ablation of a cortical region, the researchersobserved recovery of performance (18). This finding, based

Figure 1 Schematic display of principal cell types and their interconnectionsfound in the minicolumn, the canonical microcircuit of six-layered cerebralcortex (neocortex). Ch: chandelier cell; DB: double bouquet cell; LB: large basketcell; SB: small basket cell; SS: spiny stellate cell.

2 ©2015 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd

Autism and TMS Casanova et al.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

on encoding the pattern of signals of individual minicol-umns, is the first reported intervention where a neuropros-thesis has been used to successfully restore diminishedcognitive function (19).

Construct validity for the minicolumn, and the appropri-ateness of inferences based on their existence, is derivedfrom multiple sources. Population analysis of neuronswithin the same receptive field in primary somatosensorycortex (SI) shows that diversity within segregates is attrib-utable to variability among minicolumns rather than withinminicolumns (20,21). Metabolic studies (2-deoxyglucose) ofthe receptive fields of monkey’s SI evoked by skin stimulishow column-shaped patches of label comprised of activeminicolumns interspersed with less active minicolumns(22). Two-photon imaging of calcium influxes evidences anorganisation of cortical response fields comprised of col-umns 1–2 cell wide (23). Similarly, studies using labelledretroviruses and multiple cell recordings illustrate a pro-pensity for pyramidal cells to develop connections withsister cells rather than to neighbouring non-siblings (24).This affinity may be the result of the close apposition ofneuroblasts as they migrate radially towards the corticalplate. Indeed, early during brain development these cells areconnected to each other via gap junctions thus procreatinga suitable scenario for Hebbian reciprocity. Minicolumnsare therefore highly integrated structures where connec-tions within the modules far exceed those between modules.In this regard, minicolumns are modules within a hierar-chical system whose parts are interconnected by anatomicaland physiological relationships fulfilling the function of aninformation-processing unit.

It is important to note that although different minicol-umns appear to convey the same canonical circuit that theyare not clonal elements. Anatomical studies have foundsignificant minicolumnar variability within and across areasin individual brains as well as between mammalian species.This variability (e.g. number of neurons and synapticelements) between minicolumns may be an adaptive featurethat is responsible for both fault tolerances within largernetworks (e.g. macrocolumns) as well as for the competi-tion among modules that is necessary for circuit optimisa-tion (25).

CORTICOGENESIS AND AUTISM

During corticogenesis germinal cells surrounding the ven-tricles divide and migrate to the cortical plate to form aconsecutive series of strata one on top of another followingan inside–out configuration (Fig. 3). Neuroblasts derivedfrom periventricular germinal cells migrate radially towardsthe cortical plate using a glia projection as a scaffold.Computerised image analysis of the radial translaminararrays of pyramidal cells has shown a chronologicalcontinuity from early on in gestation (i.e. the ontogeneticminicolumn) through postnatal maturation and ageing (26).These neurons mature in synchrony with cells that arethemselves derived from a tangential migratory streamstemming primarily from the ganglionic eminences. Theradially migrating cells (future pyramidal cells) and tangen-tially derived neurons (future interneurons) provide forfunctional units called dyads, e.g. pyramidal-double bou-quet cell dyads, pyramidal-basket cell dyads. Deficits of

Figure 2 Interlaminar recording and MIMO stimulation model: (left panel) rasters and peri-event histograms depict the activity of supra-granular (blue) and infra-granular (red) cell layers. Overlay cross-correlograms show inter-laminar firing increase following the presentation of targets compared to pre-target epoch. Recordingarray with the MIMO model for recording in layer 2/3 and stimulation in layer 5. Stimulation effect (on the right panel) compares the cumulative effect in single sessionand population tuning for MIMO stimulation (red) vs. layer 5 prefrontal cortical activity (dark blue dotted line). Overall MIMO stimulation effect (red) is significantlygreater than no-stimulation and the chance level. Asterisks **p < 0.001, ANOVA.

COLOR


Casanova et al. Autism and TMS

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

neuronal migration are likely to impair the formation ofthese dyads thus promoting an excitatory/inhibitory biascapable of explaining the high prevalence of epilepsy amongneurodevelopmental disorders.

Some abnormalities of the cerebral cortex pinpoint to adevelopmental malformation deficit. Occasional brainsexhibit an excessive number of small convolutions (gyri)and, in others, sulci have been noted to run in an abnormaldirection (27). Microscopic examination has revealedindistinct or disordered lamination, small neurons andchanges in cell-packing density (2,28). Bailey et al. notedthe presence of increased number of neurons in both Layer1 and the subcortical white matter (2). These findings,indicative of a migrational disorder, have been reproducedby Avino and Hutsler in a study using computerised imageanalysis and in a qualitative study that surveyed whole brainserial sections by Wegiel et al. (7,8). More recently, thepresence of focal cortical dysplasias was quantitated inserial sections of ASD individuals as compared to neuro-typicals (29). Morphometric analysis of neurons withininvolved patches suggested a reduction in the overallnumber of interneurons and a reduction in size of remain-ing pyramidal cells.

Several studies have used unbiased semiautomated imag-ing methods to analyse minicolumnar morphometry in

ASD. In one study, photomicrographs from Brodmannareas 9, 21 and 22 were decomposed according to a grey-scale distribution and subsequently thresholded to definecellular kernels in nine ASD individuals and an equalnumber of neurotypicals (4). The least square method wasused to fit a radial axis through the clusters of Nissl stainedelements in order to define a mean tangential axis-to-axisdistance, i.e. minicolumnar width. The results showedsignificant narrowing (p = 0.034) of minicolumns in ASDwith the greatest decrease found in the PNS compartment.Thinning within the PNS of minicolumns in ASD wasobserved across layers (i.e. supragranular, granular, infra-granular) suggesting involvement of a common anatomicalelement throughout the cortical width of ASD individuals.The findings were latter corroborated using the samepatient population but with a different parcellation tech-nique: the grey level index (GLI) (3).

Neuropathological findings regarding a minicolumnopa-thy in ASD was reproduced in an independent populationwith investigators blind to diagnoses (5). An algorithmbased on the Delaunay triangulation was used to define thedistribution of edges between image kernels (Fig. 4). Theresults were fitted to a bimodal distribution of interneuronaldistances within and between core cell columns. Thefindings indicated that in ASD the number and arrange-ment of pyramidal cells within a minicolumn was preservedbut minicolumnar width was reduced. The researchers alsoreported a small but significant reduction in the size ofpyramidal cell perikarya that would serve to bias brain

Figure 3 Coronal section of the human brain during embryonic development.The clear arrowheads illustrate the tangential migratory pathway of cells (futureinterneurons) from the lateral and medial ganglionic eminences (LGE and MGE,respectively) to the cortical plate. Interneurons may also originate from theretrobulbar neuroepithelium of the lateral ventricle and from the cortex itself.Those interneurons fated for the cortex acquire a superficial and deeperpathway in order to avoid the embryonic striatum. A set of dark arrowheadsillustrates how neuroblasts migrate out of the ventricular zone and into thecortical plate (future pyramidal cells) following a radial pathway. An excitatory/inhibitory imbalance may result from desynchronisation of cells as theyundertake their radial and tangential migrations. Because interneurons aregenerated at such distant sites their migration may be susceptible to disruptionfrom a large variety of sources. Reprinted from Medical hypotheses, volume 83,Casanova et al., ‘Autism as a sequence’, pp. 32–38, copyright 2012, withpermission from Elsevier.

Figure 4 Minicolumnar fragments visible in a 35 lm thick section fromBrodmann area 22 of a 98-year-old male. These were identified by ourautomatic image analysis methods (5). The highlighted fragment spans laminasIII and IV (from top to bottom).



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

connectivity in favour of short corticocortical projections atthe expense of longer ones.

Studies of minicolumnar morphometry in autism indicatea relative preservation in the size of the core compartmentalongside a significant reduction of the peripheral neuropilspace. The periphery of the minicolumn is the site thatprovides for lateral or surround inhibition (30). Mountcas-tle described this compartment as conferring a strong flowof vertical inhibition to the minicolumn (15). Szent!agothaistressed the anatomical role of this peripheral compartmentby calling it a ‘shower curtain of inhibition’ (31). Both EEGand tactile processing studies corroborate the presence ofan abnormality of lateral inhibition in the cerebral cortex ofindividuals with ASD (32,33). Flutter stimuli capable ofdifferentiating between active and inactive inhibitory sur-rounds are now being used as potential biomarkers in thediagnosis of autism (33).

CLINICAL SIGNIFICANCE OF NEUROPATHOLOGICAL FINDINGS

The inhibitory defect in the cerebral cortex of ASDindividuals focuses around its minicolumnar organisation(30). Positive feedback without inhibitory modulationserves to drive a system harder towards signal saturationand deformation. For most intelligent systems it is desirableto control the gain of a signal through negative feedbackrather than allowing it go towards its extremes. A defect oflateral inhibition would enable individual minicolumns tocoalesce into islands of excitatory activity. The inhibitorydeficit procreated by the minicolumnopathy, alongside greymatter heterotopias, offers a suitable clinicopathologicalcorrelate with both the cognitive deficits and seizuresobserved in many autistic individuals. A similar imbalancein the excitatory/inhibitory bias (i.e. stochastic resonance)may account for abnormalities in multiple sensory domains(see below) (34).

Stochastic resonance is a phenomenon where a weaksignal, normally below levels of detection, can be recogni-sed by adding noise to the system. In the case of ASD thenoise (i.e. signals that add to the ‘intelligent’ input) isinherent to the system in the form of a hyperexcitablecerebral cortex (Fig. 5). Under an optimal noise level smallperturbations increase the sensitivity of the system. On theother hand, non-optimal noise levels decrease its sensitivity,blurring signal from noise (e.g. the background ‘hiss’ incommunication systems). This mechanism, already demon-strated and applied in neurophysiology (36,37), could helpexplain features of concurrent hypo- and hypersensitivity inASD, e.g. heightened apprehension to external stimuli anddecreased registration of internal body stimuli.

The interpretation of many of the clinical findings in ASDappears related to the previously described minicolumnarpathology (see above). This core pathological feature ofautism is amenable to intervention when considering thenature of the anatomical elements involved, their location,and their geometrical orientation in regards to the cerebralcortex. Some inhibitory elements within the PNS stand atdirect angle to the pial surface. Axons of double bouquet

cells transverse the width of the cerebral cortex formingtightly interwoven horsetail-like bundles. The regular spac-ing of double bouquet cells serves to frame the minicolumnin an inhibitory surround. The large number of axonsstemming from each cell, their length, as well as theirgeometrical orientation within the cerebral cortex suggeststheir susceptibility to low frequency TMS stimulation(Fig. 6). The axonal ramifications of these cells wouldprovide an additive effect to their overall diameter thusdecreasing their resistance and facilitating their proclivitytowards being induced by an external magnetic field.

0 50 100 150 200!100

!50

0

50

100

Time (msec)

Mem

bra

ne

po

ten

tial

(m

V)

0 50 100 150 200!100

!50

0

50

100

Time (msec)M

embra

ne

po

ten

tial

(m

V)

0 50 100 150 200!100

!50

0

50

100

Time (msec)

Mem

bra

ne

po

ten

tial

(m

V)

A

B

C

Figure 5 Stochastic resonance illustrated in a model neuron, SRM0 (35). Themodel was stimulated with a combination of subthreshold pulses at 25 msintervals or 40 Hz, within the gamma band, and a background of randompostsynaptic potentials (PSP) distributed as a Poisson process. In the absence ofbackground, the subthreshold pulses fail to produce action potentials in themodel neuron. When noise is present at a rate of 500 PSP per second (A), theneuron spikes occasionally with the gamma-band pulses. At a higher noise rateof 1000 PSP per second (B), the neuron fires in synchrony with the 40 Hz inputsignal. At still greater noise, 2000 PSP per second (C), random firing drowns outthe signal. Vertical bars in each panel indicate the timing of the input pulses.



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

However, despite the apparent susceptibility of certain cellsto TMS, especially at lower frequencies, it seems possiblethat stimulation results in a compound action potentialcomprised of individual pulses in many different types ofaxons.

TRANSCRANIAL MAGNETIC STIMULATION

Whenever current flows through a conductor a magneticfield is generated. For a straight wire the resultant magneticfield has no polarity and the field strength tends to be smalland of little practical use. Twisting the wire into a loopforces the flux lines closer together and adds polarity to themagnetic field. Sliding a bar of a ferromagnetic materialthrough the coil changes the core’s permeability to flux linesthus greatly increasing the strength of the magnetic fieldproduced. A coil with a ferromagnetic core is called anelectromagnet. In contrast with a permanent magnet thefield around the coil or electromagnet exists only whencurrent flows through the loops of wire. The strength of themagnetic field thus produced depends on the number ofturns of the coil and the amount of current flowing throughthe same. The conformation of the electromagnet serves todirect the magnetic field lines to a particular foci therebyincreasing flux density and strength but decreasing orlimiting its penetration. For this reason many machinesuse an air core with their coiled inductor. Current researchis being directed towards testing new cores and variedshaped coils that may induce stronger magnetic fields whileimproving penetration. At present, depth of penetration ofthe induced magnetic field is approximately 30 mms. Sincethe surface of the cerebral cortex lies about 20 mms belowthe skin, brain stimulation with TMS targets primarily thecrest of gyri.

In transcranial magnetic stimulation (TMS) a bank ofsuper- or ultracapacitors discharge stored current across an

inductor coil. As the capacitors discharge, a current of highmagnitude, usually several kA, passes through the stimu-lating coil causing at first a magnetic field to rapidly expandand then to collapse. For practical purposes stimulation oftissue elements (alterations in membrane potential) with asingle pulse of TMS is thought to occur during the risingedge of the applied magnetic field. The resultant magneticfield is on the order of 1 T, which is approximately 20 000times the Earth’s magnetic field.

Electromagnetic induction is the process of producing anelectromotive force (voltage) through a conductor by eithermoving the same through a stationary magnetic field or byleaving the conductor still and changing the magnetic field.In TMS the process of relative motion is caused by theexpanding magnetic field, otherwise the anatomical ele-ments acting as conductors remain stationary. The inducedvoltage is influenced by the strength of the magnetic fieldapplied, the speed of the relative motion between theconductor and magnetic field, the length of the conductorand the angle at which the conductor cuts the magneticfield. The maximum induced voltage occurs in thoseconductors standing at ninety degrees to the magnetic field.

Low frequency (<1 Hz) is considered to have an inhib-itory effect on the cerebral cortex, for the most part (38), asit suppresses the excitability of the motor or visual cortexfor motor or phosphene thresholds. Depending on the pre-existing baseline excitability level, higher frequencies (con-sidered as 5 Hz and greater) are considered excitatory. Atdifferent frequencies TMS alters the expression of immedi-ate early gene proteins and GABAergic neurotransmission(39,40). It has therefore been hypothesised that slow rTMSincreases the activation of inhibitory circuits. Indeed, slowrTMS significantly increases high frequency oscillations andhave no effect on somatosensory evoked potentials over theprimary somatosensory cortex. These oscillations are areflection of the activity of intracortical inhibitory neurons(41). The results suggest that slow rTMS affects corticalexcitability by stimulating interneurons, an effect whichlasts beyond the time of stimulation (42,43). Hoffman andCavus in their review of the literature regarding slow rTMSproposed long-term depression and long-term depotentia-tion for its mechanisms of action (44). Changes accrued tothese mechanisms appear to accumulate in additive fashionover repeated sessions.

TRANSCRANIAL MAGNETIC STIMULATION AND AUTISM

Several studies have examined the effects of low frequency(0.5 Hz–1.0 Hz) rTMS on behavioural, EEG and ERPoutcome measures in children with ASD (45,46). Thestudies have been performed as outpatient proceduresusually lasting 20–30 min. Since there may be a risk forinducing seizures, especially in patients with a hyperexcit-able cortex, our group and others have excluded partici-pants with seizures or a family history of the same. As anadditional precaution in rTMS studies we have adjusted thestimulation intensity (energy of the pulses) below thepatient’s motor threshold. Given the susceptibility of metal

B

j

B

Poor

lateral

inhibition

Enhanced

lateral

inhibition

Poor

lateral

inhibition

Enhanced

lateral

inhibition

Figure 6 The principle of rTMS is that a magnetic field (B), varying in strengthover time, induces electric currents (j) parallel to the direction of B. The greatesteffect will be seen in superficial layers of the cortex and outside of sulci, since Bloses strength rapidly with increasing distance from the scalp. This part of thecerebral cortex includes double bouquet cells, whose long, straight axon bundlessynapse on the basal dendrites of pyramidal cells, creating the inhibitorysurround that isolates a particular minicolumn from its neighbours. Reprintedfrom Cutting-edge therapies for autism 2010–2011 by permission of SkyhorsePublishing, Inc.



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

objects to the effects of a magnetic field, individuals whouse intracranial metallic pieces, pacemakers and/or otherimplantable devices have been excluded from participatingin the studies.

Our studies have focused on stimulating the dorsolateralprefrontal cortex (DLPC) for 6, 12 and 18 weeks. Thetremendous output territory of the DLPC makes it aconnection hub within the small-world network of corti-cocortical connectivity. It was thought that modulating theoutput of the DLPC would procreate a beneficial cascadingto the many areas connected to the same. The age range ofparticipants in the various studies was 8–27 with a mean of14 years. In our first study (n = 8 children with ASD, n = 5wait-list participants, n = 13 age-matched controls) wemeasured the EEG gamma band during a visual attentiontask (i.e. recognising a Kanizsa stimuli as either an illusoryfigure or not) and then measured the EEG gamma bandafter six sessions of rTMS treatment (47–49). Binding ofwidely distributed cell assemblies by these high frequencyoscillations or gamma frequencies (30 Hz–80 Hz) has beenassociated with top-down attentional processing and objectperception. In this study, gamma activity in our controlgroup was found to increase during the presentation oftarget-stimuli as compared to non-target stimuli. The powerof the gamma oscillations was higher in the ASD group andhad a shorter latency as compared to controls. After sixsessions of slow rTMS the power of gamma oscillationsdecreased over the frontal and parietal locations (on thesame side of the stimulation), and the difference betweengamma responses to target and non-target stimuli signifi-cantly increased (Fig. 7). Clinical assessments revealedsignificant improvements in repetitive and stereotypedbehaviours.

Gamma band activity has been investigated after 12sessions of bilateral slow rTMS to the dorsolateral pre-frontal cortex (50). In these studies, 16 ASD patients andnine age-matched controls were assessed while usingKanizsa illusory figures. Following rTMS treatment ASDindividuals showed significant improvements between rel-evant and irrelevant visual stimuli. Other studies have

followed using independent populations showing thatrTMS significantly improves ERP indices of selectiveattention, motor response errors, error detection andcorrection, and both repetitive behaviours and irritability(50–53). Evidence from our trials of compromised errormonitoring was deemed of importance as it may underlie animpairment of self-monitoring which is part of the super-visory attentional system that reviews when and how to usespecific strategies and adjust the same according to envi-ronmental changes and task demands (51,52). Individualswith error monitoring dysfunction may thus show impair-ments in set shifting abilities and inflexibility in theircapacity to change goals. In schizophrenia, an impairmentin error monitoring predicts poor executive function astested with the Penn Conditional Exclusion test (PCET)(54). TMS may therefore prove to be an intervention thatimproves executive functions in addition to behaviouralperformance in ASD.

The effects of rTMS have been investigated after 18weekly session of bilateral DLPC stimulation. This studyused two groups of children with autism (TMS and wait listgroup, n = 27 per group) (55). Following the study sessionsthere was a significant decrease in amplitude and prolongedlatency in the frontal and fronto-central N100, N200 andP3a ERP components to non-targets in the TMS group ascompared to the wait-list group. These changes along withan increase in P2d, centro-parietal P100 and P3b suggest agreater efficiency of information processing after TMStreatment.

Bilateral prefrontal rTMS has been used to examine theeffects on evoked and induced EEG gamma phase coher-ence between frontal and parietal sites during performanceon a Kanizsa illusory figures oddball task (56). The studyconsisted of 18 sessions with 32 participants (TMS and waitlist, 16 individuals per group). Results indicated that TMShad its most significant effect on induced gamma in thefrontal region as suggested by a significant increase aftertreatment in frontal gamma coherence in response totarget stimuli compared to the coherence observed in thewait list group. TMS also increased induced gamma phase

50 100 150 200–1.5

–1.0

–0.5

0

0.5

1.0

1.5

Time (msec)

Pre!rTMS

50 100 150 200–1.5

–1.0

–0.5

0

0.5

1.0

1.5

Time (msec)

Post!rTMSNon!targetTarget

Gam

ma

amp

litu

de

(µV

)

Gam

ma

amp

litu

de

(µV

)

Figure 7 rTMS modulates evoked EEG gamma frequency oscillations to target and non-target illusory figures at frontal site F7. Following a 12 session-long TMS course,early gamma response to non-target decreased, whereas gamma oscillation power to target illusory figures increased. Reprinted, with permission, from Frontiers inautism research, ed. Valerie W. Hu, copyright 2014 World Scientific Publishing.



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

coherence between ipsi- and contra-lateral frontal andparietal regions. The data shows that TMS does improvegamma coherence in autism, especially in the inducedgamma time frame.

The combined use of rTMS and EEG neurofeedback (i.e.the use of brain activity parameters as feedback to regulate afunction we want to control) has been used to operantlycondition post-TMS EEG changes (57). The underlyinghypothesis was that combined TMS and neurofeedbacktherapy would improve executive functions and behaviourin the treatment group (n = 20) as compared to the wait listgroup (n = 22). Results of the integrated neuromodulationtreatment supported the initial hypothesis by demonstratingsignificant improvements in the behavioural and ERPmeasures of executive functions, as well as significantchanges in EEG outcomes of neurofeedback training suchas frontal theta-to-beta ratio and an increased relativepower of gamma activity.

Heart rate variability and electrodermal activity havebeen used as noninvasive measures of autonomic nervoussystem activity during rTMS therapy in autism (58). Thestudy found that an accelerated heart rate in associationwith lower heart rate variability (HRV) indexed by lowfrequency (LF) to high frequency (HF) ratio (LF/HF ofHRV, so-called cardiac autonomic balance index) and lowstandard deviation of HR (SDHR) along with high electro-dermal activity (skin conductance level -SCL) were goodindicators of excessive sympathetic and reduced parasym-pathetic activation at the pre-treatment stage (58). Resultsof the study showed that, except for a reduction in LFpower of HRV, all dependent HRV variables changed in thepredicted way (decreased heart rate, increased standarddeviation of HR, increase of HF of HRV, decreased SCL).

Besides the DLPC other areas of the brain have beenstimulated with improved performance in behavioural tasksin ASD individuals. Fecteau and colleges applied a singlesession of rTMS (1 Hz) to the left and right pars triangularisand pars opercularis in 10 individuals with ASD and 10matched neurotypicals (59). Compared to the sham con-trols, all ASD individuals showed reduced latency to nameobjects on the Boston Naming test. A similar study using asingle session of 1 HZ rTMS was applied to the left primarymotor region (M1) and the supplementary motor area(SMA) in 11 individuals with ASD (60). Activation of thesensorimotor system while observing another person’sactions is referred to as interpersonal motor resonanceand is considered an index of mirror neuron activity. Thestudy reported significant improvements in late movementrelated cortical potential (MRCP) following stimulation ofM1 and of the early MCRP following stimulation of theSMA.

In summary, contrary with clinical interventions thattarget behavioural manifestations of ASD, TMS focuses onwhat may be considered a core pathology of the condition,that is, a minicolumnopathy that manifests marked deficitsof lateral inhibition. It is the only intervention for ASDthat has shown improvements in executive functions asevidenced by normalisation of ERP responses, reaction

time and accuracy during tests of executive function.Although applied primarily to the DLPC, the effects,according to behavioural performance and electrophysiol-ogy, are not limited to this region. Contrary with otherinterventions, repetitive pulse TMS is fairly safe and offersfew side effects to treatment, e.g. a transient tension typeheadache, discomfort due to the sound of the pulses. Manyclinical trials have been performed in children attestingto both its safety and efficacy. Future studies shouldaddress the long-term effectiveness of the technique andthe possible synergism when used in conjunction withbehavioural and pharmacological therapies in largersample sizes.

ACKNOWLEDGEMENTS

This article is based on several studies partially supportedby a grant from the National Institutes of Health(MH86784) awarded to Manuel F. Casanova.

References

1. Kemper TL, Bauman M. Neuropathology of infantile autism.J Neuropathol Exp Neurol 1998; 57: 645–52.

2. Bailey A, Luthert PJ, Dean AF, Harding B, Janota I,Montgomery M, et al. A clinicopathological study of autism.Brain 1998; 121: 889–905.

3. Casanova MF, Buxhoeveden DP, Switala AE, Roy E. Neuronaldensity and architecture (grey level index) in the brains of ASDpatient. J Child Neurol 2002; 17: 515–21.

4. Casanova MF, Buxhoeveden DP, Switala AE, Roy E.Minicolumnar pathology in autism. Neurology 2002; 58: 428–32.

5. Casanova MF, Van Kooten IAJ, Switala AE, Van Engeland H,Heinsen H, Steinbusch HWM, et al. Minicolumnarabnormalities in autism. Acta Neuropathol 2006; 112: 287–303.

6. Casanova MF. The neuropathology of autism. In: Volkmar FR,Rogers SJ, Paul R, Pephrey KA, editors. Handbook of pervasivedevelopmental disorders. 4th ed. New York: Wiley, 2014: 497–531.

7. Avino TA, Hutsler JJ. Abnormal cell patterning at the corticalgray-white matter boundary in autism spectrum disorders.Brain Res 2010; 1360: 138–46.

8. Wegiel J, Kuchna I, Nowicki K, Imaki H, Wegiel J, Marchi E,et al. The neuropathology of autism: defects of neurogenesisand neuronal migration, and dysplastic changes. ActaNeuropathol 2010; 119: 755–70.

9. Casanova MF. The minicolumnopathy of autism. In: BuxbaumJ, Hof P, editors. The neuroscience of autism spectrumdisorders. Oxford: Academic Press, 2013: 327–33.

10. Yakovlev PI. Pathoarchitectonic studies of cerebralmalformations. III. Arrhinencephalies (Holotelencephalies).J Neuropathol Exp Neurol 1959; 18: 22–55.

11. Sanides F. Functional architecture of motor and sensorycortices in primates in the light of a new concept ofneocortex evolution. In: Noback CR, Motagna W, editors.The primate brain. New York: Appleton-Century-Crofts,1970: 137–208.

12. Jones EG, Powell TP. An anatomical study of convergingsensory pathways within the cerebral cortex of the monkey.Brain 1970; 93: 793–820.

13. Creutzfeldt OD. The neocortical link: thoughts on thegenerality of structure and function in the neocortex. In:



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

Brazier M, Ptesche H, editors. Architectonics of the cerebralcortex. New York: Raven Press, 1978: 367–84.

14. Lorente de N!o R. The cerebral cortex: architecture,intracortical connections, and motor projections. In: Fulton JF,editor. Physiology of the nervous system. London: OxfordUniversity Press, 1938:291–339

15. Mountcastle VB. Perceptual neuroscience: the cerebral cortex.Cambridge: Harvard University Press, 1998.

16. Opris I, Fuqua JL, Huettl PF, Gerhardt GA, Berger TW,Hampson RE, et al. Closing the loop in the primate prefrontalcortex: inter-laminar processing. Front Neural Circuits 2012; 6:88.

17. Song D, Opris I, Chan RH, Marmarelis VZ, Hampson RE,Deadwyler SA, et al. Functional connectivity between layer 2/3and layer 5 neurons in prefrontal cortex of nonhuman primatesduring a delayed match-to-sample task. Proc Conf IEEE EngMed Biol Soc 2012; 34: 2555–84 .

18. Hampson RE, Gerhardt GA, Marmarelis V, Song D, Opris I,Santos L, et al. Facilitation and restoration of cognitivefunction in primate prefrontal cortex by a neuroprosthesis thatutilizes minicolumn-specific neural firing. J Neural Eng 2012;9: 056012.

19. Opris I, Hampson RE, Gerhardt GA, Berger TW, DeadwylerSA. Columnar processing in primate pFC: evidence forexecutive control microcircuits. J Cogn Neurosci 2012; 24:2334–7.

20. Favorov O, Whitsel BL. Spatial organization of the peripheralinput to area 1 cell columns: I. The detection of ‘segregates’.Brain Res Rev 1988; 13: 25–42.

21. Favorov OV, Diamond M. Demonstration of discrete place-defined columns, segregates, in cat SI. J Comp Neurol 1990;298: 97–112.

22. Tommerdahl M, Favorov OV, Whitsel BL, Nakhle B, GoncharYA. Minicolumnar activation patterns in cat and monkey SIcortex. Cereb Cortex 1993; 3: 399–411.

23. Ohki J, Chung S, Ch0ng YH, Kara P, Reid RC. Functionalimaging with cellular resolution reveals precisemicro-architecture in visual cortex. Nature 2005; 433: 597–603.

24. Yu YC, Bultje RS, Wang X, Shi SH. Specific synapses developpreferentially among sister excitatory neurons in the neocortex.Nature 2009; 458: 501–4.

25. Casanova MF. The significance of minicolumnar size variabilityin autism. In: Zimmerman AW, editor. Autism: current theoriesand evidence. Totowa: Humana Press, 2008: 349–60.

26. Casanova MF, Trippe J, Switala A. A temporal continuity to thevertical organization of the human neocortex. Cereb Cortex2006; 17: 130–7.

27. Weidenheim KM, Goodman L, Dickson DW, Gillberg C,Rastman M, Rapin I. Etiology and pathophysiology ofautistic behavior: clues from two cases with an unusualvariant of neuroaxonal dystrophy. J Child Neurol 2001; 16:809–19.

28. Bauman ML, Kemper TL. Neuroanatomic observations of thebrain in autism. In: Bauman ML, Kemper TL, editors. Theneurobiology of autism. Baltimore: Johns Hopkins UniversityPress, 1994: 119–45.

29. Casanova MF, El-Baz AS, Kamat SS, Dombroski BA, KhalifaE, Elnakib A, et al. Focal cortical displasias in autism spectrumdisorders. Acta Neuropathol Commun 2013; 1: 67.

30. Casanova MF, Buxhoeveden D, Gomez J. Disruption in theinhibitory architecture of the cell minicolumn: Implications forautism. Neuroscientist 2003; 9: 496–507.

31. Szent!agothai J, Arbib MA. Conceptual models of neuralorganization. Cambridge: MIT Press, 1975.

32. Keita L, Mottron L, Dawson M, Bertrone A. Atypical lateralconnectivity: a neural basis for altered visuospatial processingin autism. Biol Psychiatry 2011; 79: 806–11.

33. Puts NAJ, Wodka EL, Tommerdahl M, Mostofsky SH, EddenRAE. Impaired tactile processing in children with autismspectrum disorder. J Neurophysiol 2014; 111: 1803–11.

34. Davis G, Plaisted-Grant K. Low endogenous neural noise inautism. Autism 2014; ???: ???–??? in press 5

35. Gerstner W, Kistler W. Spiking neuron models: single neurons,populations, plasticity. Cambridge: Cambridge UniversityPress, 2002.

36. Douglass JK, Wilkens L, Pantazelou E, Moss F. Noiseenhancement of information transfer in crayfishmechanoreceptors by stochastic resonance. Nature 1993; 365:337–40.

37. Levin JE, Miller JP. Broadband neural encoding in the cricketcercal sensory system enhanced by stochastic resonance.Nature 1996; 380: 165–8.

38. Caparelli EC, Backus W, Telang F, Wang GJ, Maloney T,Goldstein RZ, et al. Is 1 Hz rTMS always inhibitory in healthyindividuals? Open Neuroimag 2012; 6: 69–74 6.

39. Aydin-Abidin S, Trippe J, Funke K, Eysel UT, Benali A. High-and low-frequency repetitive transcranial magnetic stimulationdifferentially activates c-Fos and zif268 protein expression inthe rat brain. Exp Brain Res 2008; 188: 249–61.

40. Trippe J, Mix A, Aydin-abidin S, Funke K, Benali A. Theta burstand conventional low-frequency rTMS differentially affectGABAergic neurotransmission in the rat cortex. Exp Brain Res2009; 199: 411–21.

41. Ogawa A, Ukai S, Shinosaki K, Yamamoto M, Kawaguchi S,Ishii R, et al. Slow repetitive transcranial magnetic stimulationincreases somatosensory high-frequency oscillations inhumans. Neurosci Lett 2004; 358: 193–6.

42. Filipovi!c SR, Rothwell JC, Bhatia K. Slow (1 Hz) repetitivetranscranial magnetic stimulation (rTMS) induces a sustainedchange in cortical excitability in patients with Parkinson’sdisease. Clin Neurophysiol 2010; 121: 1129–37.

43. Casula EP, Tarantino V, Basso D, Arcara G, Marino G, ToffoloGM, et al. Low-frequency rTMS inhibitory effects in theprimary motor cortex: insights from TMS-evoked potentials.NeuroImage 2014; 98: 225–32.

44. Hoffman RE, Cavus I. Slow transcranial magnetic stimulation,long-term depotentiation, and brain hyperexcitabilitydisorders. Am J Psychiatry 2002; 159: 1093–102.

45. Casanova MF, Sokhadze EM. Transcranial magneticstimulation: application in autism treatment. In: Hu VW,editor. Frontiers in autism research: new horizons fordiagnosis and treatment. Hackensack: World Scientific,2014: 583–606.

46. Oberman L, Rotenberg A, Pascual-Leone A. Use of transcranialmagnetic stimulation in autism spectrum disorders. J AutismDev Disord 2013; ???: ???–????. doi:10.1007/s10803-013-1960-2. 7

47. Sokhadze E, El-Baz A, Baruth J, Mathai G, Sears L, CasanovaMF. Effects of low frequency repetitive transcranial magneticstimulation (rTMS) on gamma frequency oscillations andevent-related potentials during processing of illusory figures inautism. J Autism Dev Disord 2009; 39: 619–34.

48. Basar E. A review of gamma oscillations in healthy subjects andin cognitive impairment. Int J Psychophysiol 2013; 90: 99–117.

49. Casanova MF, Baruth J, El-Baz AS, Sokhadze GE, Hensley M,Sokhadze ES. Evoked and induced gamma frequencyoscillations in autism. In: Casanova MF, El-Baz AS, Suri JS,editors. Imaging the brain in autism. New York: Springer,2013: 87–106.



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

http://dx.doi.org/10.1007/s10803-013-1960-2

http://dx.doi.org/10.1007/s10803-013-1960-2

50. Casanova MF, Baruth JM, El-Baz A, Tasman A, Sears L,Sokhadze E. Repetitive transcranial magnetic stimulation(rTMS) modulates event-related potential (ERP) indices ofattention in autism. Transl Neurosci 2012; 3: 170–80.

51. Sokhadze E, Baruth J, Tasman A, Sears L, Mathai G, El-Baz A,et al. Event-related potential study of novelty processingabnormalities in autism. Appl Psychophysiol Biofeedback2009; 34: 37–51.

52. Sokhadze E, Baruth J, El-Baz A, Horrell T, Sokhadze G,Carroll T, et al. Impaired error monitoring and correctionfunction in autism. J Neurother 2010; 14: 79–95.

53. Sokhadze EM, Baruth JM, Sears L, Sokhadze GE, El-Baz AS,Casanova MF. Prefrontal neuromodulation using rTMSimproves error monitoring and correction function in autism.Appl Psychophysiol Biofeedback 2012; 37: 91–102.

54. Silver H, Goodman C. Impairment in error monitoring predictspoor executive function in schizophrenia patients. SchizophrRes 2007; 94: 156–63.

55. Sokahdze EM, El-Baz AS, Sears LL, Opris I, Casanova MF.rTMS neuromodulation improves electrocortical functionalmeasures of information processing and behavioral responsesin autism. Front Syst Neurosci 2014; 8: 134.

56. Hensley MK, El-Baz AS, Sokhadze E, Sears L, Casanova MF.Effects of 18 session TMS therapy on gamma coherence inautism. Psychophysiology 2014; 51: S16.

57. Sokhadze EM, El-Baz AS, Tasman A, Sears LL, Wang Y,Lamina EV. Neuromodulation integrating rTMS andneurofeedback for the treatment of autism spectrum disorder:an exploratory study. Appl Psychophysiol Biofeedback 2014;39: 237–57.

58. Casanova MF, Hensley MK, Sokhadze EM, El-Baz AS, WangY, Li X, et al. Effects of rTMS on autonomic functions inautism spectrum disorder. Front Hum Neurosci 2014; 8: 851.

59. Fecteau S, Agosta S, Oberman L, Pascual-Leone A. Brainstimulation over Broca’s area differentially modulates namingskills in neurotypical adults and individuals with Asperger’ssyndrome. Eur J Neurosci 2011; 34: 158–64.

60. Enticott PG, Rinehart NJ, Tonge BJ, Bradshaw JL, FitzgeraldPB. Repetitive transcranial magnetic stimulation (rTMS)improves movement-related cortical potentials in autismspectrum disorders. Brain Stimul 2012; 5: 30–7.



1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

Author Query Form

Journal: APAArticle: 12943

Dear Author,During the copy-editing of your paper, the following queries arose. Please respond to these by marking up yourproofs with the necessary changes/additions. Please write your answers on the query sheet if there isinsufficient space on the page proofs. Please write clearly and follow the conventions shown on the attachedcorrections sheet. If returning the proof by fax do not write too close to the paper’s edge. Please remember thatillegible mark-ups may delay publication.Many thanks for your assistance.

Query reference Query Remarks

1 AUTHOR: Please confirm that given names (red) and surnames/family names(green) have been identified correctly.

2 AUTHOR: Please check affiliations are correctly presented.

3 AUTHOR: Please provide tel and fax numbers for corresponding author.

4 AUTHOR: Please check journal title for reference [17].

5 AUTHOR: Please provide the volume number, page range for reference [34].

6 AUTHOR: Please check journal title for reference [38].

7 AUTHOR: Please provide the volume number, page range for reference [46].

Autism Spectrum Disorders: Linking Neuropathological Findings to Treatment with Transcranial...

Documents

Transcript of Autism Spectrum Disorders: Linking Neuropathological Findings to Treatment with Transcranial...