Cognitive phase transitions in the cerebral cortex - enhancing the neuron doctrine by modeling neura

Page 1


Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields 1st Edition Robert Kozma

Visit to download the full and correct content document: https://textbookfull.com/product/cognitive-phase-transitions-in-the-cerebral-cortex-enh ancing-the-neuron-doctrine-by-modeling-neural-fields-1st-edition-robert-kozma/

More products digital (pdf, epub, mobi) instant download maybe you interests ...

Cerebral Cortex: Principles of Operation 1st Edition

Edmund T. Rolls

https://textbookfull.com/product/cerebral-cortex-principles-ofoperation-1st-edition-edmund-t-rolls/

Artificial Intelligence in the Age of Neural Networks and Brain Computing 1st Edition Robert Kozma Cesare Alippi Yoonsuck Choe Francesco Morabito

https://textbookfull.com/product/artificial-intelligence-in-theage-of-neural-networks-and-brain-computing-1st-edition-robertkozma-cesare-alippi-yoonsuck-choe-francesco-morabito/

Phase Transitions in Foods Second Edition Drusch

https://textbookfull.com/product/phase-transitions-in-foodssecond-edition-drusch/

Phase Transitions in Materials 2nd Edition Brent Fultz

https://textbookfull.com/product/phase-transitions-inmaterials-2nd-edition-brent-fultz/

Introduction to Neural and Cognitive Modeling 3rd Edition

https://textbookfull.com/product/introduction-to-neural-andcognitive-modeling-3rd-edition-daniel-s-levine/

Cognitive neuroscience of aging linking cognitive and cerebral aging Second Edition Cabeza

https://textbookfull.com/product/cognitive-neuroscience-of-aginglinking-cognitive-and-cerebral-aging-second-edition-cabeza/

Brain Evolution

by

Design From Neural Origin to Cognitive Architecture 1st Edition Shuichi Shigeno

https://textbookfull.com/product/brain-evolution-by-design-fromneural-origin-to-cognitive-architecture-1st-edition-shuichishigeno/

First Order Phase Transitions of Magnetic Materials: Broad and Interrupted Transitions First Edition Praveen Chaddah

https://textbookfull.com/product/first-order-phase-transitionsof-magnetic-materials-broad-and-interrupted-transitions-firstedition-praveen-chaddah/

Theoretical Modeling of Vibrational Spectra in the Liquid Phase 1st Edition Martin Thomas (Auth.)

https://textbookfull.com/product/theoretical-modeling-ofvibrational-spectra-in-the-liquid-phase-1st-edition-martinthomas-auth/

Robert Kozma

Walter J. Freeman

Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields

StudiesinSystems,DecisionandControl

Volume39

Serieseditor

JanuszKacprzyk,PolishAcademyofSciences,Warsaw,Poland e-mail:kacprzyk@ibspan.waw.pl

Theseries “StudiesinSystems,DecisionandControl” (SSDC)coversbothnew developmentsandadvances,aswellasthestateoftheart,inthevariousareasof broadlyperceivedsystems,decisionmakingandcontrol-quickly,uptodateand withahighquality.Theintentistocoverthetheory,applications,andperspectives onthestateoftheartandfuturedevelopmentsrelevanttosystems,decision making,control,complexprocessesandrelatedareas,asembeddedinthe fieldsof engineering,computerscience,physics,economics,socialandlifesciences,aswell astheparadigmsandmethodologiesbehindthem.Theseriescontainsmonographs, textbooks,lecturenotesandeditedvolumesinsystems,decisionmakingand controlspanningtheareasofCyber-PhysicalSystems,AutonomousSystems, SensorNetworks,ControlSystems,EnergySystems,AutomotiveSystems, BiologicalSystems,VehicularNetworkingandConnectedVehicles,Aerospace Systems,Automation,Manufacturing,SmartGrids,NonlinearSystems,Power Systems,Robotics,SocialSystems,EconomicSystemsandother.Ofparticular valuetoboththecontributorsandthereadershiparetheshortpublicationtimeframe andtheworld-widedistributionandexposurewhichenablebothawideandrapid disseminationofresearchoutput.

Moreinformationaboutthisseriesathttp://www.springer.com/series/13304

CognitivePhaseTransitions intheCerebralCortexEnhancingtheNeuron DoctrinebyModeling NeuralFields

WithCommentariesby:KazuyukiAiharaandTimothy Leleu,BernardBaars,StevenBressler,RayBrownand MorrisHirsch,Péter ÉrdiandZoltánSomogyvári, HansLiljenström,FrankOhl,IchiroTsuda, GiuseppeVitiello,PaulWerbos,andJamesWright

RobertKozma

UniversityofMemphis

Memphis,TN USA

WalterJ.Freeman

UniversityofCaliforniaatBerkeley

Berkeley,CA USA

ISSN2198-4182

ISSN2198-4190(electronic) StudiesinSystems,DecisionandControl

ISBN978-3-319-24404-4ISBN978-3-319-24406-8(eBook) DOI10.1007/978-3-319-24406-8

LibraryofCongressControlNumber:2015950877

SpringerChamHeidelbergNewYorkDordrechtLondon © SpringerInternationalPublishingSwitzerland2016

Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart ofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations, recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped.

Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthis publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse.

Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthis bookarebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernorthe authorsortheeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinor foranyerrorsoromissionsthatmayhavebeenmade.

Printedonacid-freepaper

SpringerInternationalPublishingAGSwitzerlandispartofSpringerScience+BusinessMedia (www.springer.com)

Thisworkisdedicatedtoscientistswho persevereinquestioningprevailingdogma insearchofwisdominthefrontiers ofneuroscience

Preface

Everydaysubjectiveexperienceofthestreamofconsciousnesssuggestscontinuous cognitiveprocessingintime.Brainmonitoringtechniqueswithmarkedlyimproved spatiotemporalresolution,however,provideanevidenceofdiscontinuitiesbetween transientlystationarydynamicsinbrains.Weobservespatiotemporalcortical dynamicsasgivingsequencesofmetastablespatialpatternsofcoherentpopulation activity.Eachmetastablepatternmanifestsacorticalstate(correspondingtoa cinematicframe)thatcollapsesintransientdesynchronization(analogoustoa shutter),followedbytherapidemergenceofanewpattern.Thetemporalsequence ofmetastablespatialpatternsiscloselycorrelatedwithintentionalbehaviors.Each framemanifeststheaction–perceptioncycle[1]bywhichanimalsprobetheir environmentsandlearnaboutthembyaccommodatingtotheimpactoftheirown actionsontheirsensorysystems.

Patternsofmicroscopicpulsetrainsfromdepthrecordings,mesoscopicaction potentialsfromintracranialassemblies,macroscopicsurfaceelectrocorticograms (ECoG),scalpelectroencephalograms(EEG)andmagnetoencephalograms(MEG), andhigh-resolutionfunctionalmagneticresonanceimages(fMRI)revealahierarchyofbrainstatesacrosstemporalandspatialscales.Theobservedneuralprocesseshavesignificanthigh-frequencyspatiotemporalcomponents.The high-frequencyoscillatorycomponentsmeasuredbybrainmonitoringtechniques arewidelyviewedasnoiseand/orartifactsandeliminatedbyaveragingand band-pass filtering.However,theseeminglyerraticdynamicbehaviorofneural fieldpotentialscontainsrecognizablepatterns,whichhavebeenmeasuredafter appropriatedecompositionintowavelets[2].

Analysisofhigh-frequencyevokedpotentialsmeasuredbyhigh-resolutionbrain imagingtechniquespointtofrequenttransitionsbetweenperiodsoflarge-scale synchronizationandintermittentdesynchronizationatalpha-thetarates.These observationssupportthehypothesisaboutthecinematicmodelofcognitiveprocessing,accordingtowhichhighercognitioncanbeviewedasmultiplemovies superimposedintimeandspace.Themetastablespatialpatternsof fieldpotentials

manifesttheframes,andtherapidtransitionsprovidetheshutterfromeachpattern tothenextinmultiplestreamsofvarioussizes.

Thealternatingstatesofferastarkcontrastinorganizationofactivitybetweena low-energy,sparsely firingstatethatweanalogizetoagas-likephaseanda high-energyliquid-likephase,stillsparsely firingbutsynchronized.Weanalogize theonsetasaphasetransitionofcondensation,followedbyevaporationafter3to5 cyclesoftheoscillation[3].Thecortexholdsitselfinastateofcriticality,whichis manifestedinareadinesstoreorganizeitselffromrandomnoiseintosynchronizationofimmensepopulations.Thesynchronymaynotbeapparentinsinglecell recordings,partlybecausethecorticalneuronsaretime-multiplexingtodistribute thecomputationalloadoveralargenumberofparticipants,andpartlybecause manyoftheneuronsinapatternarebeingheldsilent,toldtoshutup,becauseevery patternrequiresbothlightanddark.

Whatthisanalysistellsusisthatthe fi ringofpulsesbyaxons(andbysome dendrites)isonlyapartofthestorybeingtoldbybrainactivity.Theotherpartis toldbythe flowsofioniccurrentfromdendritesthatdeterminethe firing.Thevalue ofthisotherpartisenhancedbythefactthatthediscoveryoflarge-scalesynchronization–desynchronizationtransitionsinbrainsopennewopportunitiestothe developmentofbraincomputerinterfaces(BCIs).Inclinicalsettings,BCIscanhelp todiagnose,predict,andtreatcognitivediseasesattheearlystage;theycanalso drasticallyimprovethequalityoflifeofdisabledpeople.Thepotentialbenefitsare enormous.Theimplementationscanbedividedintotwobroadgroups.Invasive techniquesinvolvetheplacementofimplantsonbrainsbyopeningtheskull.The implantscanhavesingleelectrodesormultiplearrays.Rapidtechnological developmentallowstoaccessinformationfromindividualneuronsandtoachieve thegoalofbreakingtheneuralcodeofthebraintobeabletozeroinonindividual neurons[4,5].Butthereisnoonecode,ifthereisanyatall,andifoneistobe acceptedforaxons,anothermustbeacceptedfordendrites.

Innoninvasivedevices,theelectrodesarelocatedonthescalpfarfromthe corticalneurons.Asaresult,therecordedsignalsandimageslackthehighresolutionobservedininvasivedevicesandcannotgiveusanaxonalcode.Noninvasive approachesgiveusaccesstodendriticcodes,astheyareapplicableineverydaylife. Asaresult,noninvasiveBCIsareincreasinglyaccessible,forexample,inthe entertainmentindustry,aswellasservingaspersonalassistantsinphysicaltraining andexercises.

BCIsareyoungandimmaturetechnologies,andtheyarestillattheveryearly stageoftheirdevelopment.Inspiteoftheadvanceswithnoninvasiveapproaches, extractingmeaningfulinformationfromthesignalsofremotelylocatedelectrodes mayseemdaunting.Indeed,significantexponentsoftheneurosciencecommunity considertheobstaclesimpenetrableandtherelatedactivitiesoutrightmeaningless. Thetaskofnoninvasivebrainmonitoringhasbeenridiculedbycomparingittothe assumed “impossibility” oftheassignmentofKeystoneCopstoeavesdropona singleconservationinastadiumfromoutside:

KeystoneCopsinacrowded stadium,illustratingthe allegedparadoxofbrain monitoringusingnoninvasive devices(Illustrationby VladimirTaytslin)

Externaldevices,suchasthebrainwave-readingskullcap marketedas “havingapplicationsforwellness,educationandentertainment,” havenoneoftheserisks.Butbecause theirsensorsaresofarremovedfromindividualneurons,theyarealsofarlesseffective. TheyarelikeKeystoneCopstryingtoeavesdroponasingleconversationfromoutsidea giantfootballstadium.[4].

Thismisguidedsimilebetraysthelackofawarenessoflarge-scalebrain dynamics.Topursuethesimile,the roarofthecrowdatafootballgame isnotthe sumofmanythousandsofconversations.Itisthecollectiveactionofspectators engagedinasocialritual,forwhichthestadiumwasbuiltatenormousexpense. Thecrowdhasconvenedwithextensiveplanninginadvancetoenjoyparticipation intherealizationofsocialsolidarity.Comparably,millionsofneuronsformcollectivesthattranscendpairwisesynapticexchanges.Thecollectivethattheyform hasthepowerofnumbersinsynchronizeddischargessweepingthroughthebasal gangliaandbrainstem.The firingsarefarbetterpositionedandorganizedthanthe spiketrainsofnetworksofafewtensofneuronsinanunknownnumberof networkswidelyspacedincortex.Undeniablytheremustbeprivateconversations amongneurons,buttheyarenotthewholestory.Collectiveactionstakeprecedence,andtheseareobservablewithoutneedforneurosurgeons.

Thealternationbetweensynchronizedanddesynchronizedstatesisbynomeans obviousincasualrecordingsofECoGorscalpEEG.Someformoftemporal filteringisrequired[2,6]usedthespatialgradientofthealphaamplitudeinthe scalpEEG.Brockmeier[7]usedICA;Ruizetal.[8]usedtheRicianstatisticsto specifyabandofbetaactivity.Zhangetal.[9]usedthephasecoherenceinthebeta andgammabands.Panagiotidesetal.[10]usedthespatialstandarddeviationofthe betaamplitudesasamarker.EachofthesemeasuresgaveaccesstotheAMpatterns thatprovidedtheneuralcorrelatesofperceptionofconditionedstimuliinthe severalmodalities.Thetechniquesalsoservedtoshowthatthelow-energygas-like supervenesinarestingstatethatwasobservedinanimalsandhumanswhenthey areplacedinmonotonousandunchangingenvironmentthatinducesawakerest. Thisenabledustodefinetherestingstateseenalsounderlightanesthesiaasa sustainedgroundstatewithasimple1=f α canonicalEEG/ECoGtemporalspectrum withnopeaksinthebetaorgammaranges,and2 α 4[11].

Theneurodynamicsoftherestingandactivestatesthusdefinedhavebeentested forstationarityandlinearity.Thiswasdonebyperturbingthecortexwithelectric impulsesmodeledwiththeDiracdeltafunctionandmeasuringtheimpulse responsesby fi ttingthemwithwaveletsconsistingofsumsoflinearbasisfunctions [12].Thebasisfunctionsyieldedthecharacteristicfrequenciesofthecorticesin theirnormaloperatingrange,whichwasdefinedbytherangeof 3standard deviationsoftheamplitudeoftherestingorworkingEEG/ECoG.Compliancewith superpositioninthesmallsignalrangethusdefinedmadeitpossibletomodelthe corticaldynamicswiththesolutionstoordinarydifferentialequations(ODEs).That inturnmadeitfeasibletomodelthestrengthsandsignsofsynapticcouplingswith adaptivecoefficientsandtoreplacethenonlineargaincurvewiththeslopeofthe tangenttothecurveattheestimatedoperatingpoint.

Bythesestepsitbecamepossibletomodelthedynamicsonbothsidesofthe phasetransition,therandomgroundphaseandthehigh-energyactivephase. However,theODEcouldnotmodelthephasetransitionbetweenthem.Two approacheshavebeenadopted.Themorespeculativeapproachistousethecontinuousequationsofmany-bodyphysicstomodeltheinteractionsofneuralpopulationsthataresufficientlylargetoenableustodefineactivitydensityfunctions foraxonalpulsesandpostsynapticpotentials(EPSPsandIPSPs)[13].

ThemoreadvancedapproachistouseRandomGraphTheory(RGT)[14,15]to deviseadiscretecalculusinwhichtheelementisnotaneuronbutafunctional elementcorrespondingtothecollectiveofneuronsthatparticipateintime-sharing. Bothapproachesdependonthebasicassumptionthattheneuropilhastheproperty tosustainpulsetrainsfrommanyifnotmostofitsneuronsbutalsothepropertyof ephapsis,whichoperatesinacontinuumacrossthesustainingneuralpopulation. Ephasiscanbemodeledbythediscreteparticlesrequiredfordigitalapproximations inbothODEandRGT.TheaimofthisbookistoestablishabranchofRGTthat supplementsandmayeventuallyreplaceODEwith neuropercolation asthebasis formodelingneuralpopulationdynamicsondigitalplatforms.

Inthecorrespondingmathematicaltheories,brainsareperceivedasopenthermodynamicsystems[3,16]convertingbroadly fluctuatingsensorydatainto meaningfulknowledge.Amongthewiderangeofapproachesaddressing discontinuitiesinbraindynamics,randomgraphshaveuniqueadvantagesby characterizingcorticalprocessesasphasetransitionsandtransientpercolation processesinprobabilisticcellularautomata(PCA).Thecorrespondingmodelis calledneuropercolation,whichusesresultsofRGTasarigorousmathematical approachtoformulatethefundamentalrelationshipbetweentransientneuralprocessesinthecortexandthestructureoftheembeddingbraingraph.RGThas distinctadvantagesascomparedtodifferentialequationswhendescribingdiscontinuitiesincorticaldynamics.Itpresentsaparadigmshiftfrommodelingofindividualneuronstomodelingthecollectivebehaviorofneuralpopulations.

Thecaricaturesprovidemetaphorstoillustratethisparadigmshiftandexpose thelimitationsofanalytictoolsfordescribingmicroscopicpulselogicand macroscopicwavedynamics.Justasitisimpossibletounderstandorevenconceive thecollectivedynamicsofthefootballstadiumbytryingtolistentotheindividual

conversationsintheaudience;itisafeebleattempttogaininsightintobrain dynamicsbylimitingthescopetoindividualneurons.Brainsarelarge-scalesystems,inwhichthecomponentsproduce fi eldeffectsasemergentphenomenon.Itis the fieldsthatprovidepromisetomonitorandunderstandbraindynamicsby attemptingtotakeitapartandthenlearnhowtheneuronsgeneratethepopulations andinturnhowtheneuronsareinfluencedandcontrolledbythepopulationsin circularcausality.

Ourpremiseisthattherepetitivesuddentransitionsobservedinthecortexare maintainedbyneuralpercolationprocessesinthebrainasalarge-scalerandom graphnearcriticality,whichisself-organizedincollectiveneuralpopulations formedbysynapticactivity.Neuropercolationaddressesthecomplementaryaspects ofneocortex,manifestingcomplexinformationprocessinginmicroscopicnetworks ofspecializedspatialmodules,anddevelopingmacroscopicpatternsevidencing thatbrainsareholistic,multi-taskingorgans.Thepresentvolumereviewsneurophysiologicalevidencesofcollectivebraindynamicsandproposesneuropercolationasamathematicalmodeltointerpretexperimental findings.Potentialbenefits tobraincomputerinterfacesareindicated,aswell.

Wearedelightedtopresentthisbook,whichwasbornoutofthemanydiscussionswehadinthepast10yearsabouttheroleofscale-freestructureand dynamicsinproducingintelligentbehaviorinbrains.Thediscussionsstartedto convergeduringtheSpring2006ofRobert’ssabbaticalvisitatWalter ’sLabatUC Berkeley.Clearly,thequestionofscale-freestructureandbehaviorisacontroversialandaverycontentiousissueintheliterature.Thiscontroversywasapparent inthefailedattemptstopublishsuchresultsinthejournalofBehavioralandBrain Science firstin2007byWalter,thenin2014asajointendeavorbytwoofus.It becameclearthatdifferentresearchgroupshadtheirvestedinterestsinoneor anotheraspectsoftheissueandwerenotinterestedinhearingorconsidering alternativepointsofviews.Asaresult,wehavereceivedfeedbacks,whichinour judgmenttranscendedtheboundariesexpectedincivilizedandscienti ficallysolid andjusti fiedconstructivedebates.

Followingextensivediscussionswithourcolleagues,wedecidedtoproducethis volume,whichhasasomewhatunorthodoxstructure.The fi rsthalf(PartIandII) summarizesourviewsontherelevantexperimentalandtheoretical findingsand methodologicalissuesonintermittentspatiotemporalneurodynamicsinthebrain andthekeyroleoflarge-scale,collectiveoscillationsinproducinghighercognition andconsciousness.Thesecondhalfofthebook(PartIII,IV,andV)includes commentariesbyleadingexpertsinthe fieldofneuroscience,cognitivescience,and theoretical/mathematicalmodelingoftherelationshipbetweenmicroscopicneural level(neurondoctrine)andmacroscopicbehaviorallevel(fieldtheories)ofbrain operation.

Wegreatlyappreciatethosewhosupportedourendeavorbycontributingtothis volumewiththeircommentaries,KazuyukiAiharaandTimothyLeleu,Bernard Baars,StevenBressler,RayBrownandMorrisHirsch,PeterErdiandZoltan Somogyvari,HansLiljenstrom,FrankOhl,IchiroTsuda,GiuseppeVitiello,Paul Werbos,andJamesWright.Withtheirhelpweareabletopresentabroadrangeof

views,extendingbeyondourownconstraintsandhelpingtostimulateproductive discussionsandfurtherbreakthroughsinunderstandingthecodesofthebrain.

WearethankfulforthehelpfulcommentsandcriticalinsightbyScottKelsoand JosePrincipe,andforencouragementandsupportfromourSpringereditorsJanusz KaczprzykandThomasDitzinger.

Thisvolumecouldnotberealizedwithoutthesupportduringthepastdecade fromsomanyofourcolleagues,collaborators,mentors,andstudents,including PaulBalister,BelaBollobas,MikeBreakspear,A.Brockmeier,GyuriBuzsaki, TianYuCao,AntonioCapolupo,JimCaul field,JoshuaDavis,ToshiFukuda,Grant Gillett,DerekHarter,MarkHolmes,SanqingHu,TerryHuntsberger,RomanIlin, GuangLi,C.T.Lin,RobertoLivi,VinodMenon,MarkMyers,MasashiObinata, SeanO’Nuallain,HeraclesPanagiotides,LeonidPerlovsky,SuePockett,Karl Pribram,MarkoPuljic,RodrigoQuian-Quirga,MishaRabinovich,CeonRamon, OliverRiordan,JoseRodriguez,YuselyRuiz,MiklosRuszinko,HavaSiegelmann, RodrigoSilva,YurySokolov,EddieTunstel,JunWang,AnneWarlamount, LudmillaWerbos,JianZhai,andmanymanymore.Theexcellentdrawingsby VladimirTaytslinandChrisGralappofEyeArtprovideverycompellingperspectivestoillustrateourmessages.

Theintendedaudienceofthisbookincludesresearchers,postdocs,andgraduate studentsworkingtowardsnovelapproachesinbrainscienceinordertobetter understandtheoperationofthisverypreciousanddelicateorganweareall equippedwith.Theresultscanbeusefultomaintainnormaloperationofourbrain, helptoimprovethequalityoflifeoftheelderly,anddevelopnoveltreatmentsand approachesforpeoplewithcognitiveormentaldisabilities.Inshort,helptofulfi ll thehumanpotentialtothehighestlevelandtosupportthesustainabledevelopment ofhumanity.

Acknowledgments

ThisworkhasbeensupportedinpartbyNSFCRCNSProgramDMS-13-11165, DARPAPhysicalIntelligenceProgramthroughHRLsubcontract,byAFOSRLab TaskintheMathematicsandCognitionProgramtoRK,andbygrantsfromthe NationalInstituteofMentalHealthNIMH(MH06686)toWJF.

Memphis RobertKozma Berkeley WalterJ.Freeman November2014

References

1.Merleau-PontyM(1945)Phnomnologiedelaperception.Gallimard,Paris

2.FreemanWJ,QuianQuirogaR(2013)ImagingbrainfunctionwithEEG:advancedtemporal andspatialanalysisofelectroencephalographicandelectrocorticographicsignals.Springer, NewYork

3.CapolupoA,FreemanWJ,VitielloG(2013)Dissipationof ‘darkenergy’ bycortexin knowledgeretrieval.PhysLifeRev,Online.doi:10.1016/j.plrev.2013.01.001

4.MarcusG,KochC(2014)Thefutureofbrainimplants.TheWallStreetJournal.DowJones andCo,S.Brunswick,NJ

5.SanchezJC,PrincipeJC(2007).Brain-machineinterfaceengineering(Vol17).Morganand ClaypoolPublishers,LaPorte,Colorado

6.LehmannWK,StrikB,HenggelerT,KoenigM,Koukkou(1998)Brainelectricmicrostates andmomentaryconsciousmindstatesasbuildingblocksofspontaneousthinking,I.Visual imageryandabstractthoughts.IntJPsychophysiol29:111

7.BrockmeierAJ,HazratiMK,FreemanWJ,LiL,PrncipeJC(2012)Locatingspatialpatterns ofwaveformsduringsensoryperceptioninscalpEEG.InEngineeringinMedicineand BiologySociety(EMBC),2012AnnualInternationalConferenceoftheIEEE(pp.2531–2534)

8.RuizY,PockettS,FreemanWJ,GonzalesE,GuangLi(2010)Amethodtostudyglobal spatialpatternsrelatedtosensoryperceptioninscalpEEG.JNeurosciMethods191:110–118

9.ZhangT,DaiL,FreemanWJ,LiG(2013)EEGspatiotemporalpatternclassificationofthe stimuliondifferent fingers.In:4thInternationalConferenceonCognitiveNeurodynamics (ICCN2013),Sweden,Springer,Germany

10.PanagiotidesH,FreemanWJ,HolmesM,PantazisD(2008)Behavioralstatesexhibitdistinct spatialEEGpatterns.In:Proceedingsofthe62ndAnnualMeeting,AmericanEpilepsy Society,Seattle,WA,2008

11.FreemanWJ,ZhaiJ(2009)Simulatedpowerspectraldensity(PSD)ofbackground electrocorticogram(ECoG).CognNeurodyn3(1):97–103

12.FreemanWJ(1975/2004)Massactioninthenervoussystem.Academic,NewYork. Electronicversion2004. http://sulcus.berkeley.edu/MANSWWW/MANSWWW.html

13.FreemanWJ,LiviR,ObinataM,VitielloG(2012)Corticalphasetransitions,nonequilibrium thermodynamicsandtime-dependentGinzburg-Landauequation.IntJModPhysB26 (06):1250035

14.AlbertR,BarabasiA-L(2002)Statisticalmechanicsofcomplexnetworks.RevModPhy 74:47–97

15.FreemanWJ,KozmaR,BollobasB,RiordanO(2009)Chapter7.Scale-freecorticalplanar network.In:BollobasB,KozmaR,MiklosD(eds)Handbookoflarge-scalerandom networks.Series:Bolyaimathematicalstudies,vol18.Springer,NewYork,pp.277–324

16.FreemanWJ,KozmaR,VitielloG(2012)AdaptationofthegeneralizedCarnotcycleto describethermodynamicsofcerebralcortex.In:The2012InternationalJointConferenceon NeuralNetworks(IJCNN).IEEE,pp1–8

Commentators

Prof.KazuyukiAihara InstituteofIndustrialScience UniversityofTokyo 4-6-1,Komaba,Meguro-ku Tokyo153-8505,Japan aihara@sat.t.u-tokyo.ac.jp

Dr.BernardJ.Baars,Ph.D.,CEO SocietyforMind-BrainSciences TheNeurosciencesInstitute LaJolla,CA,USA baarsbj@gmail.com http://www.MBScience.org

Prof.StevenL.Bressler,Ph.D. CenterforComplexSystemsandBrainSciences DepartmentofPsychology,777GladesRoad FloridaAtlanticUniversity BocaRaton,FL33431,USA bressler@fau.edu

Dr.RayBrown,President EEASI,2100Winrock,#64 Houston,TX77057,USA raybrown.easi@gmail.com

Prof.Péter Érdi,HenryR.Luce CenterforComplexSystemsStudies 1200AcademyStreet

KalamazooCollege Kalamazoo,MI49006,USA Peter.Erdi@kzoo.edu

Prof.MorrisW.Hirsch,EmeritusUCB 7926AlbeRoad CrossPlains,WI53528-9350,USA mwhirsch@chorus.net

Dr.TimothyLeleu InstituteofIndustrialScience UniversityofTokyo 4-6-1,Komaba,Meguro-ku Tokyo153-8505,Japan

Prof.HansLiljenström AgoraforBiosystems,Director DepartmentofEnergyandTechnology SLU,P.O.Box7032 75007Uppsala,Sweden Hans.Liljenstrom@slu.se

Prof.Dr.FrankW.Ohl

LeibnizInstituteforNeurobiology DepartmentofSystemsPhysiologyofLearning Brenneckestr.6 D-39118Magdeburg,Germany frank.ohl@ifn-magdeburg.de

Dr.ZoltanSomogyvari WignerResearchCenterforPhysics HungarianAcademyofSciences KonkolyiThegeM.ut29-33 H-1121Budapest,Hungary

Prof.IchiroTsuda ResearchInstituteforElectronicScience HokkaidoUniversity Kita12Nishi6,Kita-ku Sapporo060-0812,Japan Tsuda@math.sci.hokudai.ac.jp

Prof.GiuseppeVitiello,Ph.D. DepartmentofPhysics “E.R.Caianiello” UniversityofSalerno Baronissi(SA)84100,Italy vitiello@sa.infn.it

Prof.PaulJ.Werbos

DepartmentofMathematicalSciences UniversityofMemphis Memphis,TN38152,USA paul.werbos@gmail.com

Prof.JamesJ.Wright

DepartmentofPsychologicalMedicine UniversityofAucklandSchoolofMedicine Auckland,NewZealand jj.w@xtra.co.nz

PartIReviewofDynamicalBrainTheoriesandExperiments

1Introduction OntheLanguagesofBrains ..................3

1.1BrainsAreNotComputers..........................3

1.2SymbolicApproachestoBrains.......................4 1.3Connectionism..................................5

1.4BrainsasTransientDynamicalSystems.................7

1.5RandomGraphTheory(RGT)forBrainModels...........8

1.6NeuropercolationModelingParadigm..................9 References..........................................10

2ExperimentalInvestigationofHigh-ResolutionSpatio-Temporal Patterns ............................................15

2.1Method.......................................15

2.1.1ExperimentswithRabbits....................15

2.1.2HumanECoGExperiments...................16

2.1.3ScalpEEGDesignConsiderations...............17

2.2TemporalPatterns:TheCarrierWave..................18

2.3SpatialPatternsofAmplitudeModulation(AM)andPhase Modulation(PM).................................20

2.4Classi ficationofECoGandEEGAMPatterns............23

2.5CharacterizationofSynchronization-Desynchronization TransitionsintheCortex...........................25

2.6ExperimentalObservationofSingularity.................26

2.7TransmissionofMacroscopicOutputbyMicroscopic Pulses........................................28 References..........................................30

3InterpretationofExperimentalResultsAsCorticalPhase Transitions ..........................................35

3.1TheoreticalApproachestoNonlinearCorticalDynamics......35

3.2ScalesofRepresentation:Micro-,Meso-, andMacroscopicLevels............................37

3.3CinematicTheoryofCorticalPhaseTransitions...........38

3.4CharacterizationofPhaseTransitions...................41

3.4.1CriticalState.............................41

3.4.2SingularDynamics.........................41

4ShortandLongEdgesinRandomGraphsforNeuropil Modeling ...........................................47

4.1MotivationofUsingRandomGraphTheory forModelingCorticalProcesses......................47

4.2GlossaryofRandomGraphTerminology................48

4.3NeuropercolationBasics............................51

4.4CriticalBehaviorinNeuropercolationwithMean-Field, Local,andMixedModels...........................54

4.4.1Mean-FieldApproximation....................54

4.4.2MixedShortandLongConnections.............56

4.5FiniteSizeScalingTheoryofCriticalityinBrainModels....58

5CriticalBehaviorinHierarchicalNeuropercolationModels ofCognition .........................................63

5.1BasicPrinciplesofHierarchicalBrainModels.............63

5.2Narrow-BandOscillationsinLatticeswithInhibitory Feedback......................................64

5.3Broad-BandOscillationsinCoupledMultiple Excitatory-InhibitoryLayers.........................65

5.4ExponentiallyExpandingGraphModel.................66 References..........................................68

6ModelingCorticalPhaseTransitionsUsingRandomGraph Theory .............................................71

6.1DescribingBrainNetworksinTermsofGraphTheory.......71

6.1.1Synchronizationandthe ‘Aha’ Moment...........71

6.1.2PracticalConsiderationsonSynchrony...........72

6.1.3ResultsofSynchronizationMeasurements.........74

6.2EvolutionofCriticalBehavior intheNeuropil aHypothesis.......................74

6.3SingularityandSuddenTransitions Interpretation ofExperimentalFindings...........................77 References..........................................77

7SummaryofMainArguments ............................79

7.1BrainImagingCombiningStructuralandFunctional MRI,EEG,MEGandUnitRecordings.................79

7.2Signi ficanceofRGTforBrainModeling................79

7.2.1RelevancetoBrainDiseases...................80

7.2.2NeuropercolationasaNovelMathematicalTool.....81

7.3NeuromorphicNanoscaleHardwarePlatforms.............83 References..........................................84

PartIISupplementaryMaterialsonBrainStructureandDynamics

8SupplementI:MathematicalFramework ....................89

8.1ODEImplementationofFreemanKSets................89

8.1.1FoundationsofFreemanKSets................89

8.1.2HierarchyofFreemanKSets..................91

8.2Finite-SizeScalingTheoryforRandomGraphs............96 References..........................................98

9SupplementII:SignalProcessingTools .....................101

9.1DescriptionofECoGandEEGSignals.................101

9.2HilbertTransformandAnalyticalSignalConcept forPatternAnalysis...............................102

9.2.1BasicConceptsofAnalyticSignals..............102

9.2.2AmplitudeModulation(AM)Patterns............103

9.2.3FrequencyModulation(PM):Temporal ResolutionofFrequency.....................104 References..........................................105

10SupplementIII:NeuroanatomyConsiderations ...............107

10.1StructuralConnectivities:EmergenceofNeocortex fromAllocortex..................................107

10.2ConstancyofPropertiesofNeocortexAcrossSpecies.......109

10.3DiscussionofScale-FreeStructuralandFunctional Networks......................................111 References..........................................112

PartIIICommentariesonNeuroscienceExperimentsatCell andPopulationLevels

11CommentarybyB.Baars ...............................117 11.1Introduction....................................118

11.1.1DoestheCortex “know” or “intend”?............118

11.1.2CorticalIntentionProcessing..................119

11.1.3FreemanNeurodynamics.....................119

11.2BinocularRivalryinPrimates........................120

11.3DynamicGlobalWorkspaceTheory....................121

11.3.1DirectEvidenceforCorticalBinding andBroadcasting..........................122

11.4FreemanNeurodynamics...........................123 11.5AnIntegrativeHypothesis..........................124

11.5.1ReferenceNotes...........................124 References..........................................124

12CommentarybyStevenL.Bressler ........................127

12.1Introduction....................................127

12.2Neuron–NeuronInteractions.........................129

12.3Population–PopulationInteractions....................130

12.4Discussion.....................................131

13CommentarybyZoltánSomogyváriandPéter Érdi ............135 13.1ModelingPopulationofNeurons:TheThirdOption........135 13.2MesoscopicNeurodynamics.........................136

13.2.1StatisticalNeurodynamics:HistoricalRemarks......136 13.3ForwardandInverseModelingoftheNeuro-Electric Phenomena.....................................138

13.3.1Micro-ElectricImaging......................139

13.3.2SourceReconstructiononSingleNeurons.........140

13.3.3AnatomicalAreaandLayerDetermination: Micro-Electroanatomy.......................140

13.4Conclusions....................................143

14CommentarybyFrankOhl

14.2TraditionalConceptualizationsofAuditoryCortex..........148

14.3Learning-InducedPlasticityinAuditoryCortex andMultisensoryProcessing.........................149

14.4TowardsUnderstandingtheNeurodynamicsUnderlying PerceptionandCognition...........................150

14.5ExploitingCategoryFormationtoStudytheNeurodyamics Underlyingthe “CreationofMeaning” intheBrain.........150

14.6CoexistenceofPoint-LikeTopographicandField-Like HolographicRepresentationofInformation...............154

14.7ConclusionandOutlook............................157 References..........................................157

PartIVCommentariesonDifferentialEquationinCorticalModels

15CommentarybyJamesJ.Wright .........................163

15.1Introduction....................................163

15.2NeuralMean-FieldEquations........................164

15.3StochasticEquationsinODEForm....................166

15.4Cortical-SubcorticalInteractions......................167

15.5Pulse-BurstingandtheIntroductionofStoredInformation....168

15.6SynchronyastheGlobalAttractor.....................169

15.7Stimulus-Feature-Linking,PhaseCones,Phase-Transitions, andNull-Spikes..................................169

15.8InformationCapacity SynapsesandTheirDevelopmental Organization....................................170

15.9CorticalComputationandSynchronousFields............171

15.10Self-SupervisionofLearning.........................172

15.11InConclusion...................................173 References..........................................173

16CommentarybyHansLiljenström ........................177

16.1Introduction....................................177 16.2CorticalNetworkModels...........................178

16.2.1PaleocorticalModel.........................179

16.2.2NeocorticalModel..........................179 16.3SimulationResults................................180

16.3.1Bottom-Up:Noise-InducedStateTransitions.......180

16.3.2Top-Down:NetworkModulation ofNeuralActivity..........................181

16.4Discussion.....................................183 References..........................................185

17CommentarybyRayBrownandMorrisHirsch ..............187

17.1Introduction....................................187

17.2StretchingandFoldingProvideanAlternativeApproach totheLawsofPhysicsforModelingDynamics...........189

17.3InfinitesimalDiffeomorphismsFirstOriginated fromIntegralEquations............................191

17.4DerivingIDEsfortheKIIIModel.....................194

17.4.1TheLinearIDProvidesFundamentalInsights intotheDynamicsofStretchingandFolding Systems.................................195

17.4.2TheStandardKIIIModelCanBeReformulated asaSetofInfinitesimalDiffeomorphisms(ID)......196

17.5TheApplicationofIDstoK-NeurodynamicsMayResult inUsefulSimplificationsoftheODEsUsetoDescribe theKIIISystem..................................197

17.6TheKIII-IDModelCanProvideaReduction inComputationasWellasInsights intotheNeurodynamics............................199

17.7TheWave Ψ ðXÞ forAnyKModelMayArise fromPartialDifferentialEquationsthatMustBeDerived fromExperiment.................................202

17.8Summary......................................204 References..........................................204

18CommentarybyRayBrownonRealWorldApplications ........205

18.1Introduction....................................205

18.2ImplementationoftheKIIIModel.....................206

18.3SelectionofMesoscopicComponents..................206 18.4ExampleResults.................................209 18.5Summary......................................212 References..........................................213

PartVCommentariesonNewTheoriesofCorticalDynamics andCognition

19CommentarybyPaulJ.Werbos ..........................217

19.1Introduction....................................217

19.2TopDownVersusBottomupandtheNeuronDogma.......218

19.3AnApproachtoExplainingthe4–8HertzAbruptShifts inCortex......................................221

19.4CouldFieldEffectsBeImportanttoBrainandMind?.......223

19.4.1AssociateMemoryorQuantumEffectsInside theNeuron...............................223

19.4.2DendriticFieldProcessing....................224

19.4.3QuantumFieldsandQuantumMind.............225

19.5SummaryandConclusions..........................227 References..........................................228

20CommentarybyIchiroTsuda ............................229

20.1Self-organizationandFieldTheory....................229

20.2DifferentiationbyVariationalPrinciple..................230 References..........................................232

21CommentarybyKazuyukiAiharaandTimoth

22CommentarybyGiuseppeVitiello

ReviewofDynamicalBrainTheories andExperiments

Chapter1

Introduction—OntheLanguagesofBrains

1.1BrainsAreNotComputers

Theinventionofdigitalcomputersoverhalfacenturyagofascinatedscientistswith enormousopportunitiescreatedbythisnewresearchtool,whichpotentiallyparalleledthecapabilitiesofbrains.VonNeumannhasbeenoneofthepioneersofthis newdigitalcomputingera.Whileappreciatingpotentialofcomputers,hewarned aboutamechanisticparallelbetweenbrainsandcomputers.Inhislastworkabout therelationshipbetweencomputersandbrains,hepointedoutthattheoperationof brainscannotobeythepotentiallyveryhighprecisionofalgorithmspostulatedby Turingmachines[1],andthusitisabsolutelyimplausiblethatbrainswouldusesuch algorithmsintheiroperations.Athigherlevelsofabstraction,inthelastpagesof hisfinalwork,VonNeumanncontendsthatthelanguageofthebraincannotbe mathematicsasweknowit[2].Hecontinues:

Itisonlypropertorealizethatlanguageisalargelyhistoricalaccident.Thebasichuman languagesaretraditionallytransmittedtousinvariousforms,buttheirverymultiplicity provesthatthereisnothingabsoluteandnecessaryaboutthem.JustaslanguageslikeGreek andSanskritarehistoricalfactsandnotabsolutelogicalnecessities,itisonlyreasonableto assumethatlogicsandmathematicsaresimilarlyhistorical,accidentalformsofexpression. Theymayhaveessentialvariants,i.e.theymayexistinotherformsthantheonestowhichwe areaccustomed.Indeed,thenatureofthecentralnervoussystemandofthemessagesystems thatittransmits,indicatepositivelythatthisisso.Wehavenowaccumulatedsufficient evidencetoseethatwhateverlanguagethecentralnervoussystemisusing,itischaracterized bylesslogicalandarithmeticdepththanwhatwearenormallyusedto.(VonNeumann,1958)

Ifthelanguageofthebrainisnotmathematics,ifitisnotaprecisesequenceof well-definedlogicalstatementssuchasusedinmathematics,thenwhatisit?VonNeumannwasunabletoelaborateonthisquestionduetohisearlytragicdeath.Halfacenturyofresearchinvolvingartificiallyintelligentcomputerdesignscouldnotgivethe answereither.ThisispartlyduetothefactthatVonNeumann’swarningaboutprincipallimitationsoftheearlydesignsofdigitalcomputers,calledtoday‘VonNeumann

©SpringerInternationalPublishingSwitzerland2016

R.KozmaandW.J.Freeman, CognitivePhaseTransitionsintheCerebral Cortex–EnhancingtheNeuronDoctrinebyModelingNeuralFields, StudiesinSystems,DecisionandControl39,DOI10.1007/978-3-319-24406-8_1

41Introduction—OntheLanguagesofBrains

computerarchitectures,’fellondeafears.Biologicalandhumanintelligenceuses differentwaysofoperationsfromtheoneimplementedinsymbol-manipulatingdigitalcomputers.Nevertheless,researchersexcitedbyseeminglyunlimitedpowerof digitalcomputersembarkedonprojectsofbuildingincreasinglycomplexcomputer systemstoimitateandsurpasshumanintelligence,withoutimitatingnaturalintelligence.Theseprojectsgaveimpressiveresults,butnotoriouslyfellshortofproducing systemsapproachinghumanintelligence.

Thepasthalfcenturyproducedcrucialadvancesinbrainresearch,inpartdueto advancesinexperimentaltechniques.Animportantchallengehasbeentoreconcile theapparentcontradictionbetweentheabsenceofsymbolicrepresentationsinbrains asevidencedbyneurodynamicsandthesymbolicnatureofhigher-levelcognition andconsciousness.Inphilosophyofartificialintelligencethisisaddressedasthe symbolgroundingproblem.

Thedynamicalapproachtocognitionconsidersbrainasadynamicsystemmovingalongacomplexnon-convergenttrajectoryinfluencedbythesubject’spastand presentexperiencesandanticipatedfutureevents.Thetrajectorymayrestintermittently,forafractionofasecond,atagivenspatio-temporalpattern.Thispatternmay havesomemeaningtotheindividualbasedonpreviousexperiences.Inthissenseone maycallthispatternarepresentationofthemeaningofthegivensensoryinfluence inthecontextofthepresentinternalstate.However,thespatio-temporalpatternis unstable.Aswiftphasetransitiondestroysitandmovesthesystemalongthetrajectory.Inotherwords,thequasi-stablespatio-temporalpatternscanbeconsidered asthewords,andthephasetransitionsamongpatternsasthegrammarofthebrain codeduringtheneverendingcyclesofcognitiveprocessing.

Therestofthischapterdescribestheconceptualandphilosophicalchallenges towardhumanbrainsandintelligenceandtheirpossibleresolution.

1.2SymbolicApproachestoBrains

Theuseofsymbolicdynamicstostudyknowledgeandcognition,whichprovedto bearichsourceofpowerfulconceptsdominatingthefieldfromthe60sthrough the80s.Thephysicalsymbolsystemhypothesisillustrateskeycomponentsofthe symbolicapproach[3–5].Accordingtothishypothesis,aphysicalsymbolsystem hasthenecessaryandsufficientmeansforintelligentaction.Inpracticaltermsthis meansthatthetypesofsyntacticmanipulationofsymbolsfoundinformallogicand formallinguisticsystemstypifythisviewofcognition.Inthisviewpoint,external eventsandperceptionsaretransformedintoinnersymbolstorepresentthestateofthe world.Thisinnersymboliccodestoresandrepresentsallofthesystem’slong-term knowledge.Actionstakeplacethroughthelogicalmanipulationofthesesymbols. Thisway,solutionsarefoundforcurrentproblemspresentedbytheenvironment. Problemsolvingtakestheformofasearchthroughaproblemspaceofsymbols, andthesearchisperformedbylogicalmanipulationofsymbolsthroughpredefined operations(copying,conjoining,etc.).Thesesolutionsareimplementedbyforming

plansandsendingcommandstothemotorsystemtoexecutetheplanstosolvethe problem.Foranoverview,see[6].

Accordingtosymbolicviewpoint,intelligenceistypifiedbyandresidesatthelevel ofdeliberativethought.Modernexamplesofsystemsthatfallwithinthisparadigm includeSOAR[7]andACT-R[8].Thesymbolicapproachmodelscertainaspects ofcognition,andiscapableofprovidingmanyexamplesofintelligentbehavior. However,challengestothisviewpointofcognitionhaveappeared,bothaspractical criticismsoftheperformanceofsuchsystemsandmorephilosophicalchallengesto thephysical-symbolsystemhypothesis.Onthepracticalside,symbolicmodelsare notoriouslyinflexibleanddifficulttoscaleupfromsmallandconstrainedenvironmentstorealworldproblems.

Ifsymbolicsystemsarenecessaryandsufficientforintelligentbehavior,whydo wehavesuchproblemsinproducingtheflexibilityofbehaviorexhibitedbybiological organisms?

Onthephilosophicalside,Dreyfus’situatedintelligenceapproachisaprominent exampleofacriticismofsymbolism.Dreyfusascertains,followingHeidegger’s andMerleau-Ponty’straditions,thatintelligenceisdefinedinthecontextofthe environment,therefore,apresetandfixedsymbolsystemcannotgrasptheessence ofintelligence[9, 10].Pragmaticimplementationsofsituatedintelligencefindtheir successfulimplementationsinthefieldofembodiedintelligenceandrobotics[11]. Morerecently,Dreyfuspointsoutthat…“Brooks’animatesandallotherversionsof whatsomecallHeideggerianAIhavetheirownversionoftheframeproblem,viz. thattheprogramcannotupdaterelevance”[12].Heindicatesthatapproachesbased ondynamicalsystemstheorycanprovideanaccountofhowthebrainofanactive animalcandirectlypickupandupdatewhatcountsassignificantinitsworld.Itisthe hopeoftheauthorsofthisessaythatthedescribedneurodynamicalprinciplesand mathematicalmodelsgiveastimulationforthedevelopmentofpracticallyrelevant autonomousdevicesinthespiritofMerleau-PontyandHeidegger[13].

1.3Connectionism

Theconnectionistviewofcognitionprovidesanalternativetheoryofthemindtothe symbolicapproach.Connectionistmodelsemphasizeparallel-distributedprocessing,whilesymbolicsystemstendtoprocessinformationinaserialfashion.Connectionistapproachesrepresentadaptiveanddistributedstructures,whilesymbols arestaticlocalizedstructures.Connectionistmodelsoffermanyattractivefeatures whencomparedwithstandardsymbolicapproaches.Theyhavealevelofbiologicalplausibilityabsentinsymbolicmodelsthatallowsforeasiervisualizationofhow brainsmightprocessinformation.Parallel-distributedrepresentationsarerobust,and flexible.Theyallowforpatterncompletionandgeneralizationperformance.They arecapableofadaptivelearning.Inshort,connectionistmodelsprovideauseful modelofcognition,whichareinmanywayscomplementarytosymbolicapproaches.

Clark[14]categorizesmodernconnectionismintothreegenerations,aslistedbelow. Wealsoaddthefourthgenerationasthenewestdevelopmentinthefield:

• First-generationconnectionism:Itbeganwiththeperceptronandtheworkof thecyberneticistsinthe50s.Itinvolvessimpleneuralstructureswithlimited capabilities.Theirlimitationsdrawcriticismbyrepresentativesofthesymbolist AIschoolinthe60s,whichresultedinabandonmentofconnectionistprinciples bymainstreamresearchestablishmentfordecades.Theresistancetoconnectivist ideasisunderstandable;itisinfactarepetitionofmillennia-oldphilosophical shiftfromnominalismtorealism[15].Connectionismhasbeenrevivedinthemid ’80s,thankstotheactivitiesofthePDPresearchgroupswork(amongothers)on paralleldistributedprocessing[16].

• Second-generationconnectionism:Itgainedmomentumsincethe’80s.Itextends first-generationnetworkstodealeffectivelywithcomplexdynamicsofspatiotemporalevents.Itinvolvesadvancedrecurrentneuralnetworkarchitecturesanda rangeofadvancedadaptationandlearningalgorithms.Foranoverview,see[17].

• Third-generationconnectionism:Itistypifiedbyevenmorecomplexdynamicand timeinvolvingproperties[18].Thesemodelsusebiologicallyinspiredmodular architectures,alongwithvariousrecurrentandhard-codedconnections.Because oftheincreasingemphasisondynamicandtimeproperties,third-generationconnectionismhasalsobeencalleddynamicconnectionism.ThirdgenerationconnectionistmodelsincludeDARWIN[19],andtheDistributedAdaptiveControl (DAC)models[15, 20].

• Fourthgenerationconnectionism:Thenewestdevelopmentofneuralmodeling,representinganadditionalstepgoingbeyondClark’soriginalcategorization schema.Thisapproachinvolvesnonconvergent/chaoticsequencesofspatiotemporaloscillations[21, 22].ItisbasedonadvancesinEEGanalysis,which gavespatiotemporalamplitudemodulation(AM)patternsofunprecedentedclarity.TheK(Katchalsky)modelsareprominentexamplesofthiscategory,which arerootedinintuitiveideasfromthe70s[23]andgainedprominencesincethe turnofthecentury.

Ourfocusisnewdevelopmentsinfourthgenerationconnectionism.Akeyto thesemodelsisthemesoscopic-intermediate-rangeparadigm[24].Accordingly, intelligenceinbrainsisrootedinthedelicatebalancebetweenlocalfragmentation ofindividualcomponentsatthecellularlevel,andoveralldominanceofaunified globalcomponentatthebrain/hemispherelevel.Thisbalanceismanifestedthrough metastabledynamicbrainstatesundergoingfrequentstatetransitions.Phasetransitionsarecrucialcomponentsofthenewgenerationofconnectionistmodelsasthey providevehiclestoproducetheseamlesssequenceofspatio-temporaloscillation patternspunctuatedbycorticalphasetransitions.Thisisthemainfocusofthiswork. Traditionalapproachestoknowledgeextractionandontologygenerationin machinelearningandtrainedsystemshavefocusedonstaticsystems,extracting grammaticalrulesfromdynamicalsystemsorcreatingontologiesprimarilyfrom textornumericaldatadatabases[18].Theseapproachesareinherentlylimitedby

natureofextractedknowledgerepresentations,whicharestaticstructureswithno dynamics.Dynamicapproachtointelligencecreatestheopportunityofintegrating bottom–upandtop–downmethodsofintelligence.Itgoesbeyondbottom–upconnectionistapproachesbyextractingsymbolicknowledgefromsub-symbolicstructures manifestedintheformofspatio-temporalfluctuationsofbrainactivity.

1.4BrainsasTransientDynamicalSystems

Thereisarichliteratureaimingatbridgingthedifferenceinspatialandtemporal scalesbetweenmicroscopicpropertiesofsingleneuronsandmacroscopicproperties oflargepopulationsofneurons,includingcoarsegraining,mean-fieldapproaches, circularcausality[23, 25–27].However,thereisavastamountoftheoreticalissuesto beresolvedbeforeunderstandingtheoperationofbrainasaunifiedorgan.Interactive populationsofneuronsoperatingfarfromequilibriumcreatespatiotemporalpatterns ofactivitythatsustainintelligentbehaviors[28–30].Thesepatternsaredissipative structures,becausetheyrequireprodigiousquantitiesofmetabolicenergy,alsocalled darkenergy [31].

Measurementsofelectricalpotentialfieldsinbrainsdocumentthepresenceof spatialtexturesofactivitypatterns;theexperimentalmethodcanbeeitherinvasive usingelectrocorticogram(ECoG)electrodesonthecorticalsurface[32],ornoninvasiveelectroencephalogram(EEG)usingscalpelectrodes[33].Eachpatternhasa narrow-bandcarrierfrequencyofoscillationinthebeta-gammarange.Thepatterns areformedbythemodulationoftheamplitude(AM)andphase(PM)ofthecarrier wave.ThesizesofAMandPMpatternsvaryfromafewmmindiameter(ECoG) [34]totheentirescalp(EEG)[33].Thetemporalspectraarepower-law[35].The distributionsofthedurationsofthepatternsarepower-law[36].Thesefindingsimply thattheAM-PMpatternsarescale-freeinspaceandtimeacrossthebetaandgamma ranges[28, 37–39].TheAMandPMpatternsarerepresentedasn-dimensionalvectorsinthefeaturespace,wherenisthenumberofpixelsinthepatterns.Thevector frommultichannelECoGrecordingsservesasavectorialstatevariableinmodeling. Thesebasicconceptsprovidedthefoundationforchaoticbraindynamics,following thepioneeringworkby[40].

FollowingPrigogineandHakentheoryonemergentbehaviorinopenthermodynamicsystems[41, 42],brainshavebeenmodeledasadissipativethermodynamic systemthatbyhomeostasisholdsitselfnearacriticallevelofactivitythatisa non-equilibriummetastablestate.Principlesofself-organizationandmetastability havebeenintroducedtodescribebraindynamics[43, 44].Recently,theconcept ofself-organizedcriticality(SOC)hasbeenemployedinneurosciencetoprovide amodelframeworkfortheobservations[45, 46].Thereisempiricalevidenceof cortexconformingtotheself-stabilizednearcriticalstateduringtheexistenceof quasi-stablestates[47–49].Brainsexhibittransientswitchesbetweenthemeta-stable states.SOC,however,cannotproducethesequenceoftransientpatternsobserved

Another random document with no related content on Scribd:

In respect of the formation of rocks as precipitates from a state of vapor we have scarcely any illustrations excepting in volcanic regions. Rocky materials with which we are generally acquainted are practically non-volatile at the highest temperature which can be secured on the earth’s surface, but it is possible that in the interior of the earth the temperature may be so high as to maintain many substances in a state of vapor.

They may, in this case, become disassociated so that the compounds or elements exist distinctly in a vaporous condition. Such a vapor transported to regions of diminished temperature would first of all on cooling permit a union of the chemical elements forming new compounds less volatile, which, of course, would be at once precipitated.

The rocks and minerals formed in this way which are of some agricultural importance may be classified as follows:

Oxids, carbonates, silicates, sulfur, sulfids, sulfates, phosphates, chlorids, and hydrocarbon compounds, the most important from an agricultural point of view being the phosphates.

The second group of rocks, namely those formed as sedimentary deposits, differ from those just described in that they are comprised mainly of fragmental materials derived from the breaking down of preexisting rocks. The formation of fragmental rocks includes, therefore, the same processes as are active in the formation of arable soil. They are deposited from water, and are as a rule distinctly stratified.

Through the action of pressure and the heat thereby generated, or simply through the chemical action of percolating solutions, such rocks pass over into the crystalline sedimentary forms known as metamorphic. All metamorphic rocks, however, are not of a sedimentary origin. For instance, by pressure, heat, and the chemical changes thereby induced, granite may be changed into gneiss and the latter would then be a metamorphic rock.

This group of sedimentary rocks and of sedimentary material, either unchanged or metamorphosed, is of vast extent and includes materials of widely varying chemical and mineralogical nature. They form by far the greater portion of the present surface of the earth, even the mountain ranges being composed mainly of this sedimentary material. Indeed, in the whole of this country there is only a comparatively very small extent of igneous or irruptive rocks. They are of great importance from a purely scientific, as well as agricultural standpoint, since they

contain the fossil records of past geologic ages. From them it is possible to study the variations in climate, the meteorological conditions in circumstances and periods far remote, and thus form some idea of the process by which the crust of the earth has been modified by natural forces from its original form to the present time.

The sedimentary rocks may be divided, with sufficient accuracy for our purposes, into two great classes: First, rocks formed by mechanical agencies and mainly of inorganic materials. These are subdivided again as follows:

(a) The arenaceous group.

(b) The argillaceous group.

(c) The volcanic group.

The second class of sedimentary rocks is formed largely, or in part at least, by mechanical agencies, but is comprised chiefly of the débris of plant and animal life. It may be subdivided as follows:

(a) The siliceous group, such as infusorial earth.

(b) The calcareous group, fossiliferous formations, limestone, etc.

(c) The carbonaceous group, such as peat, lignite, coals, etc. The different classes of rock described above are distinguished by special qualities represented largely by the name. The first division, the arenaceous group, is composed mainly of the siliceous or coarsely granular materials derived from the disintegration of older crystalline rocks, which have been rearranged in beds of varying thickness through the mechanical agency of water. They are, in short, consolidated or unconsolidated beds of sand and gravel. In composition and texture they vary almost indefinitely. Many of them having suffered little during the process of disintegration and transportation are composed essentially of the same materials as the rocks from which they were derived.

The sandstones, which are the type of these rocks, vary greatly in structure as well as in composition, in some the grains being rounded while in others they are sharply angular.

The microscopic structure of sandstone is shown in figure 7.[24]

The material by which the individual grains of a sandstone are bound together is usually the material of some of the other classes. The calcareous, ferruginous, and siliceous cements being the chief ones. This cementing substance is deposited among the granules forming the sandstone by percolating water.

The colors of sandstone are dependent usually upon iron oxids. Especially is this true of the red, brown, and yellow colors. In some of the light grey varieties, the color is that of the minerals comprising the stone. Some of the darker colored sandstones contain organic matter.

F. 7.

Microscopic Structure of Sandstone.

The rocks of the argillaceous group are composed essentially of a hydrous silicate of alumina, which is the basis of common clay, and varying amounts of free silica, oxids of iron and manganese, carbonates of lime and magnesia, and small quantities of organic matter. They may have originated in situ from the decomposition of feldspars or as deposits of fine mud or silt at the bottom of large bodies of water. The older formations of these rocks are known as shales, argillites, and slates and the fissile structure which enables this to be split into thin sheets is probably due to the conditions under which they have been formed and not to any properties of the clays themselves.

One of the purest forms of this rock is kaolin, which is almost a pure hydrous silicate of alumina formed from the decomposition of feldspathic rocks from which the alkalies, iron oxids and other soluble constituents have been removed by water.

Under the volcanic group are included the materials ejected from volcanic vents in a more or less finely comminuted condition and which

through the drifting power of atmospheric currents may be scattered over many miles of territory. Various names are applied to such products, names dependent in large part upon their state of subdivision. Volcanic dust and sand, or ashes, includes the finer dust-like or sandlike materials, and lapilli, or rapilli the coarser. The general name tuff includes the more or less compacted and stratified beds of this material, while trass, peperino, and pozzuolano are local varietal names given to similar materials occurring in European volcanic regions.

The second division, namely sedimentary rocks composed of the débris of plant and animal life includes many forms of great agricultural importance.

The first subdivision of this group is the infusorial or diatomaceous earth. It forms a fine white or yellowish pulverulent rock composed mainly of minute shells, or tests of diatoms, and is often so soft and pliable as to crumble readily between the thumb and fingers. According to Whitney the beds are of comparatively limited extent and for this reason are of little agricultural value, although the weathering of this diatomaceous material gives rise to a light yellow clay forming very fertile agricultural lands.

The second subdivision of this group includes the rocks of a calcareous nature derived from animal life; that is to say, what are properly called limestones. They vary in color, structure, and texture almost indefinitely, and include all possible grades of materials from those which can be used only as a flux, or for lime burning, through ordinary building materials to the finest marbles. These rocks are world-wide in their distribution and limited to no one particular geologic horizon, but are found in stratified beds among rocks of all ages from the most ancient to the most recent.

Owing to the fact that their chief constituent, carbonate of lime, is soluble in ordinary meteoric waters, the rocks have undergone extensive decomposition, their lime being removed, while their less soluble constituents or impurities remain to form soil. A single ton of residual soil represents not infrequently a loss of 100 tons of original rock matter. As this mass of lime carbonate is removed by solution the residual soil settles, and as the limestone rocks are more soluble than the adjacent rock formations limestone formations usually form valley lands with ridges on either side. Caves are frequently found in such formations. Furthermore, as the lime is almost all in the form of the easily soluble lime carbonate it can be very completely removed and the fertile “limestone soils” are often very deficient in lime and respond

readily to an application of burnt lime, which, not infrequently, is quarried from the same field. From an agricultural standpoint this group is of very great interest and importance.

The third subdivision of this group, namely, that of vegetable origin, includes peat, lignite, coals, etc. Rocks of this group are made up of more or less fragmental remains of plants. In many of them, as the peats and lignites, the traces of plant structure are still apparent. In others, as the anthracite coals, these structures have been wholly obliterated by metamorphisms.

Plants when decomposing on the surface of the ground give off their carbon to the atmosphere in the shape of carbon dioxid gas leaving only the strictly inorganic or mineral matter behind. When, however, they are protected from the oxidizing influence of the air, by water or by other plant growth, decomposition is greatly retarded, and a large portion of the carbonaceous and volatile matters is retained, and by this means together with pressure from the overlying mass, the material becomes slowly converted into coal. When this process goes on near the surface of the earth, and without much pressure, peat or muck is the product.

The fourth subdivision of this group, the phosphatic, forms a class of rocks limited in extent but of the greatest economic importance. Guano, coprolites, and phosphatic rocks (the phosphorites) come under this head.

34. Aeolian Rocks.—This class of rocks is of less importance than the others, either geologically or agriculturally. It is formed from materials drifted by the winds and this material has various degrees of compactness. Usually the components of these drifts form rocks or deposits of a friable texture and of a fragmental nature. The very extensive deposits of loess in China, forming their most fertile lands, are admitted now to have been formed in this way, but it is now generally admitted that similar deposits in this country are of subaqueous origin.

Chief among these rocks, are the volcanic ashes which are often carried to a long distance by the wind before they are deposited and consolidated into rock masses. Many loose soils may be carried to great distances by the wind, the deposits forming new aggregates. This is particularly the case in arid regions.

35. Metamorphic Rocks.—This class of rocks includes all sedimentary or eruptive rocks, which, after their deposition and agglomeration, have been changed in their nature through the action of

heat, pressure, or by chemical means. Sometimes these changes are so complete that no indication of the character of the original rocks remains. At other times the changes may be found in all the stages of progress, so that they can be traced from the original fragmental or irruptive to the completely metamorphosed deposit. This is especially true of rocks containing large quantities of lime. In those containing silica, the changes are less readily traced.

8.

M C L.

(West Rutland, Vermont.)

The metamorphic rocks may be divided into two subclasses, namely, stratified or bedded, and foliated or schistose.

The rocks of the first class are represented by the crystalline limestones and dolomites. The microstructure of a crystalline limestone is shown in Fig. 8.[25] When lime and magnesia occur together in combination with carbon dioxid, the substance is known as dolomite. The chemical nature of these rocks and their soil-forming properties are the same as those of the ordinary, non-metamorphosed limestones and dolomites to which reference has already been made. The subject need not, therefore, be further dwelt upon here.

F.

F. 9.

M G.

(West Andover, Massachusetts.)

At a a are shown plagioclase crystals broken and rounded by the sheering force producing the foliation.

The second variety of metamorphic rocks is represented by the gneisses and crystalline schists. Gneiss has essentially the same composition as granite and can frequently hardly be distinguished from it, except by a microscopic study of its sections, and even thus it is sometimes difficult to determine. Frequently a number of new minerals is formed in the metamorphic changes. The microstructure of a gneiss is shown in Fig. 9.[26] The schists include an extremely variable class of rocks, of which quartz is the prevailing constituent, and which, as a rule, are deficient in potash and other important ingredients.

36. Rocks Formed Through Igneous Agencies, or Eruptive Rocks.

—This group includes all those rocks, which, having been at some time in a state of igneous fusion, have been solidified into their present form by a process of cooling. It may be stated, as a general principle, that the greater the pressure under which a rock solidifies and

the slower and more gradual the cooling the more perfect will be found the crystalline structure. Hence, it follows that the older and more deepseated rocks which are forced up in the form of dikes, bosses, or intrusive sheets, into the overlying masses, and which have become exposed only through erosion and removal of the overlying rocks, are the more highly crystalline.

The eruptive rocks are divided into two main groups, viz.:

(a) Intrusive or plutonic rocks, and (b) Effusive or volcanic rocks.

Among the more important of the first division of the plutonic form, from an agricultural point of view, are the granites. The essential constituents of granite are quartz, potash feldspar, and plagioclase. One or more minerals of the mica, amphibole or pyroxene groups are also commonly present, and in microscopic proportions apatite and particles of magnetic iron. The more valuable constituents, from an agricultural standpoint, are the minerals potash feldspar, and apatite, which furnish by their decomposition the essential potash and phosphoric acid.

In addition to the granites, which have already been mentioned, the group includes the syenites, the nepheline syenites, the diorites, the gabbros, the diabases, the theralites, the peridotites, and the pyroxenites.

The second group, the effusive or volcanic rocks, includes those igneous rocks, which, like the first group, have been forced up through the overlying rocks, but which were brought to the surface, flowing out as lavas. These, therefore, represent, in many cases, only the upper or surface portions of the first group, differing from them structurally, because they have cooled under little pressure more rapidly, and hence are not so distinctly crystalline. These comprise the following groups:

(a) Quartz porphyries. (b) Liparites. (c) Quartz-free porphyries. (d) Trachytes. (e) Phonolites. (f) Porphyrites. (g) Andesites. (h) Melaphyrs and augite porphyrites. (i) Basalts. (j) Tephrites and Basanites. (k) Picrite porphyrites. (l) Limburgites and augitites. (m) Leucite rocks. (n) Nepheline rocks. (o) Melilite rocks.

It is, in most cases, impossible to state which of the above classes is of most importance from an agricultural standpoint, since, in the process of soil formation, both chemical and physical processes are involved, whereby the character of the resultant soil is so modified as to but remotely resemble its parent rock. In most soils, the prevailing

constituent is but the least soluble one of the rock mass from which it was derived. Thus a limestone soil may contain upwards of ninety per cent of silica and alumina, while the original limestone itself may not have carried more than one or two per cent of these substances. Of course, if a rock mass contains none of the constituents essential to plant growth, its resultant soil must by itself alone be quite barren. It does not absolutely follow, however, that those rocks containing the highest percentages of valuable constituents will yield the most fertile soils, since much depends on the manner in which they have been formed, the amount of leaching, etc., they may have undergone. Nevertheless, the study of the composition of the rocks in their relation to soils, is an extremely interesting and by no means unimportant one.

A comparative table of rock compositions is here given. It will be observed that there is a considerable range of variation even among rocks of the same class, a fact due to the varying abundance of their mineral constituents. The figures given are not those of actual analyses on any one particular rock, but are selected from a number of comparatively typical cases; and, it is thought, fairly well represent the composition of the class of rocks indicated.

Peridotites

37. Origin of Soils.—The soils in which crops grow and which form the subject of the analytical processes to be hereinafter described have

been formed under the combined influences of rock decay and plant and organic growth. The mineral matters of soils have had their origin in the decay of rocks, while the humic and other organic constituents have been derived from living bodies. It is not the object of this treatise to discuss in detail the processes of soil formation, but only to give such general outlines as may bear particularly on the proper conceptions of the principles of soil investigation.

38. The Decay of Rocks.—The origin and composition of rocks are fully set forth in works on geology and mineralogy. Only a brief summary of those points of interest to agriculture has been given in the preceding pages. The soil analyst should be acquainted with these principles, but for practical purposes he has only to understand the chief factors active in securing the decay of rocks and in preparing the débris for plant growth.

The following outline is based on the generally accepted theories respecting the formation of soils.[7]

The forces ordinarily concerned in the decay of rocks are:

1. Changes of temperature, including the ordinary daily and monthly changes, and the conditions of freezing and thawing.

2. Moving water or ice.

3. Chemical action of water and air.

4. Influence of vegetable and animal life:

(a) Shades the rock or soil surface.

(b) Penetrates the rock or soil material with its roots, thus admitting air.

(c) Solvent action of roots.

(d) Chemical action of decaying organic matter.

5. Earth worms.

6. Bacteria.

39. The Action of Freezing and Thawing.—In those parts of a rock stratum exposed near the surface of the earth the processes of freezing and thawing have perhaps had considerable influence in rock decay. The expansive force of freezing water is well known. Ice occupies

a larger volume than the water from which it was formed. The force with which this expansion takes place is almost irresistible. The phenomenon of bursted water pipes which have been exposed to a freezing temperature is not an uncommon one. While the increase in volume is not large, yet it is entirely sufficient to produce serious results. The way in which freezing affects exposed rock is easily understood. The effect is unnoticeable if the rock be dry. If, on the other hand, it be saturated with water, the disintegrating effect of a freeze must be of considerable magnitude. This effect becomes more pronounced if the intervals of freezing and thawing be of short duration. The whole affected portion of the rock may thus become thoroughly decayed. But even in the most favorable conditions this form of disintegration must be confined to a thin superficial area. Even in very cold climates the frost only penetrates a few feet below the surface, and therefore the action of ice cannot in any way be connected with those changes at great depths, to which attention has already been called. Nevertheless, certain building stones seem very sensitive to this sort of weathering, and the crumbling of the stone in the Houses of Parliament is due chiefly to this cause.

On the whole it appears that the action of ice in producing rock decay has been somewhat overrated, although its power must not by any means be denied. But on the other hand a freeze extending over a long time tends to preserve the rocks, and it therefore appears that the entire absence of frost would promote the process of rock decay.

At best it must be admitted that frost has affected the earth’s crust only to an insignificant depth, but its influence in modifying the arable part of the soil is of the utmost importance to agriculture.

40. The Action of Glaciers.—The action of ice in soil formation is not confined alone to the processes just described. At a period not very remote geologically, a great part of our Northern States was covered with a vast field of moving ice. These seas of ice crept down upon us from more northern latitudes and swept before them every vestige of animal and vegetable life. In their movement they leveled and destroyed the crests of hills and filled the valleys with the débris. They crushed and comminuted the strata of rocks which opposed their flow and carried huge boulders of granite hundreds of miles from their homes. On melting they left vast moraines of rocks and pebbles which will mark for all time the termini of these empires of ice. When the ice of these vast glaciers finally melted the surface which they had leveled presented the appearance of an extended plain. No estimate can be made of the enormous quantities of rock material which were ground to finest

powder by these glaciers. This rock powder forms to-day no inconsiderable part of those fertile soils which are composed of glacial drift. The rich materials of these soils probably bear a more intimate relation to the rocks from which they were formed than of any other kinds of soil in the world. The rocks were literally ground into a fine powder, and this powder was intimately mixed with the soils which had already been formed in situ. The melting ice also left exposed to disintegrating forces large surfaces of unprotected rocks in which decay would go on much more rapidly than when covered with the débris which protected them before the advent of the ice. The area of glacial action extended over nearly all of New England and over the whole area of the northern tier of States. It extended southward almost to the Ohio river, and in some places crossed it. The effect of the ice age in producing and modifying our soil must never be forgotten in a study of soil genesis. It is not a part of our purpose here to study the causes which produced the age of ice. Even a brief reference to some of the more probable ones might be entirely out of place. Before the glacial period it is certain that a tropical climate extended almost, if not quite, to the North Pole. The fossil remains of tropical plants and animals which have been found in high northern latitudes are abundant proofs of this fact.

In the opinion of Sterry Hunt,[27] rock decay has taken place largely in preglacial and pretertiary times. The decay of crystalline rocks is a process of great antiquity. It is also a universal phenomenon. The fact that the rocks of the southern part of this country seem to be covered with a deeper débris than those further north is probably due to the mechanical translation of the eroded particles towards the south. The decay and softening of the material were processes necessarily preceding the erosion by aqueous and glacial action.

It is possible that a climate may have existed in the earlier geologic ages more favorable to the decay of rocks than that of the present time.

41. Progress of Decay as Affected by Latitude.—Extensive investigations carried on along the Atlantic side of the country show wide differences in the rate of decay in the same kind of rocks in different latitudes. In general, the progress of decay is more marked toward the south. The same fact is observed in the great interior valleys of the country; at least, everywhere except in the arid and semi-arid regions. Wherever there is a deficiency of water the processes of decay have been arrested. Where the rock strata have been displaced from a horizontal position the progress of decay has been more rapid. This is

easily understood. The percolation of water is more easy as the displacement approaches a vertical position.

A most remarkable example of this is seen in the rocks of North Carolina.[28] A kind of rock known as trap is found in layers called dikes in the Newark system of rocks in that State. These dikes have been so completely displaced from the horizontal position they at first occupied as to have an almost vertical dip. The edges thus exposed vary from a few feet to nearly 100 feet in thickness. The trap rock in those localities is composed almost exclusively of the mineral dolerite, which is so hard and elastic in a fresh state as to ring like a piece of metal when struck with a hammer. In building a railroad through this region these dikes were in some places uncovered to a depth of forty feet and more. At this depth they were found completely decomposed and with no indications of having reached the lower limit of disintegration. The original hard bluish dolerite has been transformed into a yellowish clay-like mass that can be molded in the fingers and cut like putty. Similar geologic formations in New Jersey and further North do not exhibit anything like so great a degree of decomposition, thus illustrating in a marked degree the fact that freezing weather for a part of the year is a protection against rock decay. The ice of winter at least protects the rocks from surface infiltration, although it can not stop the subterranean solution which must go on continuously.

Other things being equal, therefore, it appears that as the region of winter frost is passed the decay of the rocks has been more rapid than in the North, because the chief disintegrating forces act more constantly.

42. The Solvent Action of Water.—The water of springs and wells is not pure. It contains in solution mineral matters and often a trace of organic matter. The organic matter comes from contact with vegetable matter and other organic materials near the surface of the earth. The mineral matter is derived from the solvent action of the water and its contents on the soil and rocks.

The expressions “hard” and “soft” applied to water indicate that it has much or little mineral matter in suspension, as the case may be. When surface and spring waters are collected into streams and rivers they still contain in solution the greater part of the mineral matters which they at first carried.

When well or spring waters have more than forty grains of mineral matter per gallon they are not suitable for drinking waters. Mineral waters, so called, are those which carry large quantities of mineral

matter, or which contain certain comparatively rare mineral substances which are valued for their medicinal effects.

The analysis of spring, well, or river waters will always give some indication of the character of the rocks over which they have passed.[29] The vast quantities of mineral matters carried into oceans and seas are gradually deposited as the water is evaporated. If, however, these matters be very soluble, such as common salt, sulfate of magnesia, etc., they become concentrated, as is seen with common salt in sea waters. In small bodies of waters, such as inland seas, which have no outlet, this concentration may proceed to a much greater extent than in the ocean. As an instance of this, it may be noted that the waters of the Dead Sea and Great Salt Lake are impregnated to a far greater degree with soluble salts than the water of the ocean. The solvent action of water on rocks is greatly increased by the traces of organic or carbonic acids which it may contain. When surface water comes in contact with vegetable matter it may become partially charged with the organic acids which the growing vegetable may contain or decaying vegetable matter produce. Such acids coming in contact with limestone under pressure will set free carbon dioxid. Water charged with carbon dioxid acts vigorously on limestone and other mineral aggregates. If such solutions penetrate deeply below the surface of the earth their activity as solvents may be greatly increased by the higher temperature to which they are subjected. Hence, all these forces combine to disintegrate the rocks, and through such agencies vast deposits of original and secondary rocks have been completely decomposed.

The gradual passing of the firm rock into an arable soil is beautifully shown in Fig. 10, a print from a negative taken by Mr. Geo. P. Merrill, near Washington, D. C.

The fresh but badly decomposed granitic rock is shown passing upward into material more and more decomposed until it becomes sufficiently pulverulent and soluble to support plant life. The roots showing in the upper part of the picture formerly penetrated the decomposed rock, but have been exposed through quarrying operations. Photograph by George P. Merrill, 1891.

43. Action Of Vegetable Life.

—The preliminary condition to vegetation is the formation of soil, but once started, vegetation aids greatly in the decomposition of rocks. Some forms of vegetation, as the lichens, have apparently the faculty of growing on the bare surface of rocks, but the higher order requires at least a little soil. The vegetation acts by shading the surface and thus rendering the action of water more

F 10.
View on the Broad Branch of Rock Creek, Washington, D. C.

effective, by mechanically separating the rock particles by means of its penetrating roots and by the positive solvent action of the root juices. The rootlets of plants in contact with limestone or marble dissolve large portions of these substances, and while their action on more refractory rocks is slower, it must be of considerable importance. The organic matter introduced into the soil by vegetation also promotes decay still further both directly and by the formation of acids of the humic series. This matter also furnishes a considerable portion of carbon dioxid which is carried by the water to assist in its solvent action.

44. Action of Earth-Worms.—Of animal organisms those most active in the formation of soil are earth-worms. The work of earthworms has been exhaustively studied by Darwin.[30] The worms not only modify the soil by bringing to the surface portions of the subsoil, but also influence its physical state by making it more porous and pulverulent. According to Darwin the intestinal content of worms has an acid reaction, and this has an effect on those portions of the soil passing through their alimentary canal. The acids, which are formed in the upper part of the digestive canal are neutralized by the carbonate of lime secreted by the calciferous glands of the worms thus neutralizing the free acid and changing the reaction to alkaline in the lower part of the canal. There is a fair presumption that the acids of the worm are of a humic nature.

The worms further modify the composition of the soil by drawing leaves and other organic matter into their holes, and leaving therein a portion of such matter which is gradually converted into humus. Stockbridge[31] gives a striking illustration of this process due to an experiment by von Hensen. Darwin estimates that about eleven tons of organic matter per acre are annually added to the soil in regions where worms abound. A considerable portion of the ammonia in the soil at any given time may also be due to the action of worms, as much as 0.18 per cent of this substance having been found in their excrement. It is probable that nearly the whole of the vegetable matter in the soil passes sooner or later through the alimentary canals of these ceaseless soil builders, and is converted into the form of humus.

45. Action of Bacteria.—The intimate relations which have been found to subsist between certain minute organisms and the chemical reactions which take place in the soil is a sufficient excuse for noting the effect of other similar organisms in the formation of soils.

In addition to the usual forces active in decomposing rocks Müntz[32] has described the effects of a nitrifying bacillus contributing to the same

purpose.

According to him the bare rock usually furnishes a purely mineral environment where organisms cannot be developed unless they are able to draw their nourishment directly from the air. Some nitrifying organisms belong to this class. It has been shown that these bodies can be developed by absorbing from the ambient atmosphere carbonate of ammonia and vapors of alcohol, the presence of which has been determined in the air. According to the observations of Winogradsky, they assimilate even the carbon of the carbon dioxid just as vegetables do which contain chlorophyl. Thus even in the denuded rocks of high mountains the conditions for the development of all these inferior organisms exist. In examining the particles produced by attrition, it is easily established that they are uniformly covered by a layer of organic matter evidently formed by microscopic vegetations. Thus we see, in the very first products of attrition, appearing upon the rocky particles the characteristic element of vegetable soil, viz., humus, the proportion of which increases rapidly with the products of disaggregation collected at the foot of declivities until finally they become covered with chlorophyliferous plants.

In a similar manner the presence of nitrifying organisms has been noted upon rocky particles received in sterilized tubes, and cultivated in an appropriate environment where they soon produce nitrification. The naked rocks of the Alps, the Pyrenees, the Auvergnes and the Vosges, comprise mineralogical types of the most varied nature, viz., granite, porphyry, gneiss, micaschist volcanic rocks and limestones and all these have shown themselves to be covered with the nitrifying ferment. It is known that below a certain temperature these organisms are not active; their action upon the rock is, therefore, limited to the summer period. During the cold season their life is suspended but they do not perish, inasmuch as they have been found living and ready to resume all their activity after an indefinite sleep on the ice of the glaciers where the temperature is never elevated above zero.

The nitrifying ferment is exercised on a much larger scale in the normal conditions of the lower levels where the rock is covered with earth. This activity is not limited to the mass of rock but is continued upon the fragments of the most diverse size scattered through the soil and it gradually reduces them to a state of fine particles. It is therefore a phenomenon of the widest extension.

The action of these micro-organisms according to Müntz is not confined to the surface but extends to the most interior particles of the

rocky mass. Where, however, there is nothing of a nitrogenous nature, to nitrify such an organism must live in a state of suspended animation.

When the extreme minuteness of these phenomena is considered there may be a tendency to despise their importance, but their continuity and their generality in the opinion of Müntz place them among the geologic causes to which the crust of the earth owes a part of its actual physiognomy and which particularly have contributed to the formation of the deposits of the comminuted elements constituting arable soil.

The general action of nitrifying organisms in the soil, the nature of these bodies, and the method of isolating and identifying them will be fully discussed in another part of this work.

46. Action of the Air.—The air itself takes an active part in rock decay. Wherever rocks are exposed to decay, there air is found or, at least, the active principle of air, viz., oxygen. The air not only penetrates to a great depth in the earth, but is also carried to much greater depths by water which always holds a greater or less quantity of air in solution. The oxygen of the air is thus brought into intimate contact with the disintegrating materials and in a condition to assist wherever possible in the decomposing processes.

The oxygen acts vigorously on the lower oxids of iron, converting them into peroxids, and thus tends to produce decay.

There are other constituents of rocks which oxygen affects injuriously and thus helps to their final breaking up. It is true that, as a rule, the constituents of rocks are already oxidized to nearly as high a degree as possible, and on these constituents of course the air would have no effect. But on others, especially when helped by water with the other substances it carries in solution, the air may greatly help in the work of destruction.

In a general view, the action of the air in soil formation may be regarded as of secondary importance, and to depend chiefly on the oxidation of the lower to the higher basic forms. These processes, while they seem of little value, have, nevertheless, been of considerable importance in the production of that residue of rock disintegration which constitutes the soil.

47. Classification of Soils According to Deposition.—In regard to their deposition soils are divided into five classes:

1. Those which are formed from the decomposition of crystalline or sedimentary rocks or of unconsolidated sedimentary material in situ.

2. Those which have been moved by water from the place of their original formation and deposited by subsidence (bottom lands, alluvial soils, lacustrine deposits, etc.).

3. Those which have been deposited as débris from moving masses of ice (glacial drift).

4. Soils formed from volcanic ashes or from materials moved by the wind and deposited in low places or in hills or ridges.

5. Those formed chiefly from the decay of vegetable matter, (tule, peat, muck).

48. Qualities of Soils.—In respect of quality, soils have been arbitrarily divided into many kinds. Some of the more important of these divisions are as follows:

1. Sand. Soils consisting almost exclusively of sand.

2. Sandy Loams. Soils containing some humus and clay but an excess of sand.

3. Loams. Soils inclining neither to sand nor clay and containing some considerable portions of vegetable mold, being very pulverulent and easily broken up into loose and porous masses.

4. Clays. Stiff soils in which the silicate of alumina and other fine mineral particles are present in large quantity.

5. Marls. Deposits containing an unusual proportion of carbonate of lime, with often some potash or phosphoric acid resulting from the remains of sea-animals and plants.

6. Alkaline. Soils containing carbonate and sulfate of soda, or an excess of these alkaline and other soluble mineral substances.

7. Adobe. A fine grained porous earth of peculiar properties hereinafter described.

8. Vegetable. Soils containing much vegetable débris in an advanced state of decomposition. When such matter predominates or exists in large proportion in a soil the term tule, peat or muck is applied to it.

With the exception of numbers six, seven and eight these types of soil are so well-known as to require no further description for analytical purposes. The alkaline, adobe and vegetable soils on the contrary demand further study.

49. Alkaline Soils.—The importance of a more extended notice of this class of soils for analytical purposes is emphasized by their large extent in the United States.

Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.