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Koje su razlike (ako ih ima) u moždanoj aktivnosti pri halucinaciji u odnosu na opažanje stvarnog objekta?

Koje su razlike (ako ih ima) u moždanoj aktivnosti pri halucinaciji u odnosu na opažanje stvarnog objekta?


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Pitao sam se postoji li razlika u moždanoj aktivnosti kada netko halucinira neki objekt, recimo žirafu u usporedbi s time da netko istinski promatra pravu žirafu?


Koja je razlika između prividnog kretanja i prividnog kretanja?

Definicija za prividno kretanje je:

Opažanje kretanja proizvedeno podražajima koji su nepomični, ali su prvo prikazani na jednom mjestu, a zatim u odgovarajućem vremenskom intervalu predstavljeni na drugom položaju.

I prividno kretanje definira se kao:

Kretanje se može otkriti čak i ako nema pravog kretanja

Sada na moju stvarnu pitanje: Znam da su ta dva oblika percepcije vrlo bliska, pa koja je stvarna razlika između ta dva? Postoji li čista definicija razlike? Smatram da su i prividno kretanje i prividno kretanje prema Gleitmanu i sur. (2010) prilično su isti i mogli bi se primijeniti na obje vrste primjera. Dakle, ako im se predstavi podražaj/iluzija, kako bi im se pristupilo da razaznaju koji je koji?


Znanost o halucinacijama

Govorimo o halucinacijama, od unutarnjeg vida do stvari za koje se čini da se tijekom noći dešavaju. Osim toga, kao i obično, pridružuju nam se naši lokalni stručnjaci kako bismo probali neke od najnovijih vijesti iz neuroznanosti.

U ovoj epizodi

01:13 - Čitanje emocija kroz maske za lice

Čitanje emocija kroz maske za lice Helen Keyes, ARU Duncan Astle, Sveučilište Cambridge

Ovog je mjeseca Helen Keyes pogledala članak koji proučava implikacije odraslih koji nose maske za lice na dječju sposobnost tumačenja emocija.

Helen - Ova se studija usredotočila na 81 dijete u dobi od 7 do 13 godina. To je ključna dob u kojoj se djeca počinju oslanjati na oči za tumačenje emocionalnog izraza. Ova djeca su vidjela mnogo slika lica i lica su imala različite izraze lica - tugu, bijes i strah. Slike bi počele doista mutne i postajale bi sve jasnije. A djeca bi govorila koja se emocija izražava u licu. Očito kako je lice postajalo jasnije, ovaj je zadatak postajao lakši. Lica su ili predstavljena u cjelini ili su prekrivena licem, samo kirurškom maskom za lice, ili su predstavljena kao sunčane naočale. I kao što se očekivalo, djeca su bila najpreciznija u prepoznavanju emocija lica kad uopće nije bilo pokrića za lice. Dakle, bez maske za lice i bez sunčanih naočala, to ne čudi.

Međutim, taj je utjecaj bio relativno mali. Uistinu, kad pogledamo pojedinačne emocije, djeca su i dalje imala znatno više uspjeha od prepoznavanja emocija za tužna lica. Čak i ako lice nosi masku ili nosi sunčane naočale, djeca su ipak bila uspješnija. Još su mogli vidjeti da je lice tužno. Kad pogledamo ljuta lica, ponovno nošenje maske za lice nije imalo toliko učinka - u smislu djece i dalje su bili bolji od šanse u prepoznavanju ljutite emocije, dok su sunčane naočale to doista umanjile. A onda je stvarno tek kada je lice izražavalo strah da je uvođenje bilo koje vrste prekrivača lica, poput maske za lice ili sunčanih naočala, djeci doista otežalo tumačenje te emocije. Bilo im je vrlo teško zaključiti izražava li lice strah ili iznenađenje kada imate taj pogled gotovo razrogačenih očiju, nose li masku za lice ili sunčane naočale.

Dakle, ovdje ima dosta nade, iako se očito bolje snalazimo bez prekrivanja lica, djeca bi i dalje mogla uvelike tumačiti emocije koje su se prenijele.

Katie - Što mislite o varijaciji u tome koliko su djeca bila sposobna pokupiti različite emocije?

Helen - Za očekivati ​​je. Dakle, znamo da je strah i iznenađenje doista teško razlikovati u smislu stvarnih glavnih ključnih emocija. Često se ljutnja i tuga pomiješaju. Pa sam pomislio da je doista zanimljivo da djeca mogu jasno razlikovati tugu i ljutnju.

Ovdje govorimo o nepokretnim slikama lica. Sada na ulici, ako ste nekoga sreli, a on je bio tužan ili ljut, ima još mnogo znakova na koje biste se oslonili osim njihovog lica. Dakle, njihov govor tijela, ono što govore ili viču, tu vrstu stvari, možete jasno razlikovati. No, samo gledajući te slike, može biti zaista teško razlikovati tugu i ljutnju. I zaista je lijep nalaz vidjeti da su djeca još uvijek mogla razaznati te emocije.

Katie - Koliko je raznolika bila skupina djece. Zanima me samo razlikuju li se takve stvari ovisno o pojedincu ili možda o podrijetlu ili kulturi?

Helen - Dakle, bilo je jako lijepog širenja djece. Često u ovoj vrsti istraživanja može postojati tendencija da se usredotočimo na jednu podgrupu, većinu, podskupinu djece, ali ova je imala zaista lijepu ravnotežu među različitim etničkim grupama u djece. I prilično dobra spolna ravnoteža među djecom. I tamo nije bilo velikih otkrića osim što su dječaci bili nešto brži u prepoznavanju gnjeva nego djevojčice.

Katie - Ljudi, lica, to su bili stranci, zar ne? Samo slike na ekranu.

Helen - Svi su bili stranci. Da. Preuzeto iz baze podataka koja se doista često koristi, gdje smo zaista utvrdili da su to sve tužna lica i ljudi su potvrdili da izgledaju kao tužna lica ili ljuta lica, i tako dalje.

Katie - Sumnjate li da bi se to moglo promijeniti na bilo koji način, ovisno o odnosu prema odrasloj osobi? Recimo, to su tvoji roditelji ili tvoj učitelj, znate, te ključne interakcije.

Helen - To je jako dobro. Pa da, definitivno ćemo se poboljšati ako je to poznato lice, jednostavno zato što smo puno bolje upoznati s tim kako ta lica izgledaju pod različitim uvjetima. I tu ideju nečijeg lica u mnogo različitih uvjeta možemo asimilirati u lijep predložak njihovog lica. I tada nam je jako lako upotrijebiti vrlo malo znakova s ​​ljudima koje poznajemo kako bismo zaključili tu emociju.

No u stvarnosti ljudi koje će ta djeca vidjeti s maskama za lice neće pretežno biti njihovi roditelji ili njihovi učitelji. Na ulici će uglavnom biti stranci.

Katie - Što je s djecom kojoj bi emocionalna komunikacija ionako mogla biti teška? Recimo možda djeca koja su autistična.

Helen - To je dobro pitanje jer autistična djeca i odrasli autisti nemaju toliko jaku sklonost kao ljudi koji nisu autistični, nemaju toliko jaku sklonost gledati u oči i usredotočiti se te se zadržati na području oko očiju. Dakle, postoje neki dokazi koji ukazuju na to da autistični ljudi radije gledaju značajke, poput područja usta kako bi dobili svoje emocionalne znakove. Dakle, nije bilo puno istraživanja o tome u smislu nošenja ili uporabe maski za lice, ali očekivali bismo, da, da će to biti dodatno narušeno, ako ne želite gledati područje oko očiju, već koristiti usta za vaše znakove emocija. Da, očekivali bismo da će to biti značajnije umanjenje vrijednosti.

Katie - Kao što ste ranije rekli, očito su emocije prilično nijansirane. Znate, postoji izraz lica, govor tijela treba uzeti u obzir. Koliko mislite da je općenito značajna ova studija?

Helen - Mislim da to nije od velike važnosti u smislu mogu li djeca ikada protumačiti emocije u svijetu ili njihov društveni razvoj. Mislim da doista ono što čini smiruje neke brige koje su u ovom trenutku jako rasprostranjene jer su svi roditelji toliko zabrinuti za društveni razvoj svoje djece. I lijepo je imati zaista mali komad utjehe koji kaže, vidi, pa, jedna stvar oko koje se ne trebaš brinuti je: "O moj Bože, moja djeca ne unose dovoljno emocija lica i odlaze doživotno zakržljati! " Dakle, to je lijepo, vrlo malo, ali smisleno uvjerenje za roditelje koji su već prilično zabrinuti.

Duncan - Dakle, znamo da su djeca u ovom laboratorijskom okruženju, koje je prilično dobro kontrolirano ovim standardnim podražajima za lice, bolja od slučajnosti. Pitao sam se mislimo li da će se to odigrati u stvarnom svijetu, koji je nekako zauzet i puno se događa? Bi li ta izvedba veća od šanse bila dovoljna da djeca pouzdano prepoznaju emocije u stvarnom svijetu?

Helen - Mislim da je to stvarno dobro pitanje. A da želimo ovo učiniti realnijim, naravno bismo uveli mnogo korisnijih društvenih znakova, kao i mnogo više zaposlenosti u vizualnom okruženju. Dakle, da, iako u stvarnom svijetu ne znamo bi li djeca još uvijek mogla prepoznati te emocije kroz maske, imala bi daleko više informacija u smislu nečijeg govora tijela i onoga što su prenijeli na druge načine, osim od njihovih izraza lica. Stoga bi bilo jako teško razdvojiti to dvoje, zbog čega je lijepo imati ovo u izolaciji, govoreći nam samo o tumačenju emocija lica.

Duncan Astle pogledao je pregled koji je istražio koliko učitelja vjeruje u koncept stilova učenja, kolika je vjerojatnost da će ih primijeniti u učionici, smanjuje li se to uvjerenje s vremenom i djeluje li intervencija za suprotstavljanje tom uvjerenju.

Duncan - Stilovi učenja koncept su da svaka osoba ima suptilno drugačiji način učenja. Stoga bi neki ljudi više voljeli da informacije dolaze u vizualnom obliku, neki mogu biti u slušnom formatu, neki bi radije naučili radeći nešto sami, takozvani kinestetički učenik. Ideja je da ako možete uskladiti nečiji stil učenja s načinom na koji dostavljate informacije u učionici, tada ćete stvoriti optimalno okruženje za učenje. S vremenom ćete potaknuti njihovo učenje.

Katie - Koji dokazi postoje u prilog ovoj ideji o tome kako ljudi uče?

Duncan - Bojim se da nema mnogo dokaza. Zapravo, podaci pokazuju da će vam djeca sigurno reći da imaju preferirani stil. Prebrzo će vam reći koji im je stil draži. Međutim, podaci pokazuju da u svom preferiranom stilu nisu ništa bolji od bilo kojeg drugog. Naravno, svatko ima prednost, ali čini se da to uopće ne odgovara učenju. I zapravo mogu postojati neke opasnosti od promicanja ideje o stilovima učenja, jer na primjer, ako vam kažem da ste kinestetički učenik, kad pokušavam iznijeti nešto na satu u auditivnom ili vizualnom formatu, u čemu je smisao obraćaš pažnju? Uostalom, ovo nije vaš omiljeni stil. Dakle, dokazi da to radi su ništavni. Nema ih. I zapravo se sve više shvaća da promicanje ove ideje može imati neke negativne posljedice.

Katie - Dakle, ako nema dokaza da to funkcionira, odakle onda ideja?

Duncan - Pa, izvorna ideja dolazi od svojevrsnog savjetovanja o menadžmentu, ali razlog zašto je ušla u nastavu je taj što - kao što ćemo kasnije doći - još uvijek postoji u obrazovanju učitelja. I još uvijek se nalazi u brojnim čak i novijim udžbenicima za obuku učitelja. I tako je to ušlo u učionicu.

Katie - Što je recenzija tada otkrila?

Duncan - Pa, ono što su htjeli ustanoviti je vjeruju li učitelji i dalje u stilove učenja ili ne, a način na koji su to činili bio je napraviti sustavni pregled. Stoga su imali vrlo pažljive kriterije za odabir različitih objavljenih studija. To je rezultiralo u 33 različite studije koje su pokrivale stavove više od 15 000 učitelja, anketiranih između 2009. i 2020. Dakle, u rasponu od 10 godina. A od tih učitelja, više od 89% vjeruje u stilove učenja da ćete, ako uskladite stil učenja s izvođenjem, poboljšati njihovo učenje. I gotovo svi oni koji vjeruju u to namjeravaju ga koristiti u nastavi.

Katie - Što je pregled pronašao u smislu trendova? Vjeruje li više ili manje ljudi u to?

Duncan - Pa, sigurno ne ide na bolje. Dakle, ono što biste mogli očekivati ​​vidjeti je ako sve manje ljudi vjeruje u stilove učenja, a kako vrijeme odmiče - od 2009. do 2020. - postupno će manje učitelja reći da vjeruje u to. Ali to nije istina. Nema značajne veze s vremenom. I zapravo, ako to podijelite između učitelja pripravnika i etabliranih učitelja, zapravo će učitelji vježbači vjerojatnije vjerovati u stilove učenja, iako su to oni koji su nedavno završili obrazovanje učitelja. Dakle, nema dokaza da s vremenom postaje sve bolje. Čini se da sugerira da je u osnovi prilično konstantan u ovom desetogodišnjem razdoblju.

Katie - Ako nema dokaza da ovo funkcionira, čini li čin komuniciranja koji čini razliku?

Duncan - Da. Dakle, samo su četiri studije pokušale intervenirati, ali sve pokazuju da je to prilično učinkovito. Dakle, ako izvodite neku vrstu kampanje kako biste objasnili učiteljima da je to besmislica, onda njihovo vjerovanje u to ide sa oko 78% na 37%. Tako da stvarno možete promijeniti perspektive. Mislim, pitam se što se događa u onih 37% koji vjerojatno ne vjeruju u intervenciju, ali to pokazuje da je prilično učinkovita.

Katie - Što nam znanost govori o najboljim načinima učenja? Je li raznolikost u metodama učenja i poučavanja korisna?

Duncan - Da, ali ne iz razloga za koje stilovi učenja kažu da bi trebalo biti. Dakle, znamo da ako dostavljate informacije iz više različitih perspektiva, tada ćete dobiti ono što se zove duboka obrada. Dakle, razlog zašto je dobro učiti informacije iz mnogo različitih perspektiva je taj što postavljate trajnija dugoročna sjećanja povezana s tim, a ne neku vrstu plitkog traga.

Katie - Iz različitih perspektiva, govorite li o tome da čitate nešto, naspram slušanja učitelja, nasuprot tome da nešto radite?

Duncan - Upravo tako. Ideja je zato što svaki put kad ponovno naiđete na informacije u drugom formatu, na neki način rekonstruirate tragove od prvog puta. I sa svakom rekonstrukcijom, nagib raspada memorije činite plićim. I tako s vremenom postaje sve izdržljiviji.

Ali to nije zato što na ovaj ili onaj način tjerate djecu na učenje. To je samo općenito načelo da veća raznolikost u načinu na koji se informacije isporučuju teži trajnijim sjećanjima.

Katie - Oh, vidim. Dakle, čak i ako više volim učiti putem nekoga tko razgovara sa mnom, zapravo je raditi sve te stvari vjerojatno dobro za moje učenje. To govoriš?

Duncan - Da, točno. Također stvarate ono što se naziva kontekstualno neovisna memorija. Postoji stvarno snažan učinak, a to je da recimo da učite stvari u jednom formatu u jednoj prostoriji. Vjerojatnije je da ćete ga se sjetiti kada morate biti u toj prostoriji u istom formatu. Dok ako imate različitost u stilu i mjestima prezentacije, tada ćete dobiti uspomene koje su trajnije u različitim kontekstima i u različitim formatima.

Katie - Što je revizija učinila stvarnom kvalitetom dokaza koje su gledali?

Duncan - Velika upozorenja. Doista je teško doći do stvarno nepristrane mjere vjerovanja ljudi u nešto koristeći prigodni uzorak, što je velika većina ovih studija. A to je zato što ljudi koji se bave takvim stvarima možda nisu vaš tipični učitelj. I gotovo uvijek su ta pitanja o stilovima učenja i vjerovanjima u stilove učenja ugrađena uz mnoga druga neuro-mitska pitanja i stvari koje se mogu činiti mnogo manje vjerojatnima. Stoga bi moglo doći do pristranosti u tome što kad naiđu na pitanja o stilovima učenja misle: "pa, to se čini mnogo vjerojatnijim od besmislica koje sam upravo pročitao". Stoga će svi ti čimbenici doista utjecati na to koliko vjeru u vjeru u stilove učenja doista možete postići.

Katie - U redu. Dakle, općenito, što mislite da možemo izvući iz ovog pregleda o stanju vjerovanja u stilove učenja?

Duncan - Govorim o stilovima učenja u školama oko 10 godina. Rekao bih da je i dalje slučaj da ljudi većinu puta to spominju. Pa bih rekao da je njihova brojka od 80 do 90%, vjerojatno je malo visoka za Veliku Britaniju, ali nije daleko.

Razlog tome je taj što, pa, postoji zakon koji se zove Brandolinijev zakon, koji neću doslovno citirati, ali to je ideja da je energija potrebna za pobijanje besmislica za red veličine veća od one koja je potrebna za njeno stvaranje. Ako pogledate na primjer, u prvoj velikoj studiji koja pokazuje da stilovi učenja imaju veliki učinak, to je citirano više od 600 puta.

A dvije godine kasnije, izašlo je još jedno istraživanje koje je pokazalo da je izvorna studija besmislena i da uopće nema učinka. Ta druga studija citirana je samo 60 puta. Kad dobijete ideju, vrlo lako stekne snagu. A za vraćanje duha u bocu potrebno je strahovito više energije.


Što uzrokuje hipnopompične halucinacije?

Točni uzroci hipnopompičnih halucinacija općenito su podložni značajnim individualnim varijacijama. Drugim riječima, jedna osoba ih može doživjeti kao posljedicu poremećaja spavanja, dok ih druga može doživjeti kao posljedicu unosa psihoaktivne droge prije nego što zaspi. Dodatno, ono što pojedinac vidi može biti povezano s jedinstvenim kolektivnim podsvjesnim materijalom i načinom na koji se percipira može biti povezano s psihološkim stanjem osobe.

Aktiviranje mozga : Postoje dokazi da regionalna aktivacija mozga ili deaktiviranje određenih regija može biti odgovorna za stvaranje hipnopompičnih halucinacija. Točnije, neki istraživači vjeruju da prednji režanj mozga postaje depresivan što dovodi do smanjenja vremena reakcije i kratkotrajnog pamćenja. Također se pretpostavlja da bi aktivacija određenih regija kao posljedica aktivnosti slične REM-u, aktivnosti nalik napadajima ili iritacije korteksa mogla uzrokovati ove hipnopompične halucinacije.

Istraživanja su pokazala da izravna stimulacija mozga određenih regija može dovesti do halucinacija, čak i među onima koji nikada prije nisu imali halucinacijsko iskustvo. Ako stimulirate različite vizualne centre, možete stvoriti jednostavne ili složene halucinacije. Ako stimulirate slušne centre, osoba može čuti glasove ili druge zvukove.

Ako stimulirate oboje, mogli biste dobiti i vizualne i zvučne efekte. Moguće je da naleti aktivnosti slične REM-u stimuliraju određene regije u hipnopompičnom stanju, što rezultira hipnopompičnim halucinacijama. Trajanje i stupanj do kojeg se stimuliraju mogu predvidjeti percipiranu duljinu i složenost halucinacija.

Struktura mozga : Osobe sa strukturnim abnormalnostima mozga mogu biti sklonije halucinacijama, osobito vizualne (npr. Vidjeti stvari). Struktura osobe može biti abnormalna od rođenja, ili može biti abnormalna kao posljedica neke ozbiljne ozljede mozga. U mnogim slučajevima otkriveno je da lezije na određenim dijelovima mozga mogu uzrokovati i poremećaje spavanja i halucinacije povezane sa spavanjem (npr. Hipopompične).

Moždani valovi : Smatra se da se moždani valovi mijenjaju tijekom hipnopompičnih halucinacija. Uzorak moždanog vala može uključivati ​​kombinaciju theta vala i/ili alfa valova, zajedno s povremenim naletima beta. Smatra se da je to stanje pretežno sporih valova, ali koncentracije tih valova mogu ovisiti o stupnju hipnopompičnog prijelaza iz sna u budnost.

Netko tko doživi hipnopompičnu halucinaciju bliže točki buđenja može biti svjesniji tog iskustva, ali može podnijeti samo vrlo suptilnu halucinaciju. Netko tko je bliže spektru hipnopompije spavanju mogao bi doživjeti življe halucinacije nalik snu, ali nije svjestan tog iskustva. Potpisi moždanog vala za hipnopompične halucinacije također mogu biti pod utjecajem REM -a ili prikrivenog REM -a.

Svijest : Tijekom hipnopompičnog stanja svijesti, misli se da smo u emocionalnom stanju svijesti nalik snu. Tijekom ovog stanja nalik snu, naš mozak pokušava logički osmisliti iskustvo, što rezultira vlastitim subjektivnim tumačenjima. Hipnopompična halucinacija može biti povezana s nečim što vam je nedavno bilo na umu (svjesno) ili je nešto što ste već davno zaboravili (podsvijest).

Nezakonite droge : Oni koji koriste zabranjene droge mogu doživjeti čudne snove, kao i hipnagogične i/ili hipnopompične halucinacije. Među ovisnicima o drogama poznato je da se kola mogu promijeniti u mozgu tijekom vremena, što potencijalno može dovesti do oštećenja i smrti moždanih stanica. Promjene u funkcioniranju mozga zbog upotrebe ili zlouporabe nedopuštenih droga mogu dovesti do poremećaja sna i manifestacija hipnopompičnih halucinacija.

Poznato je da pojedinci koji dožive psihozu uzrokovanu lijekovima pokazuju abnormalnu neurotransmisiju i aktivaciju mozga kao posljedicu primjene lijeka. Moguće je da pojedinac zaspi nakon uporabe lijeka, samo da prijeđe iz sna u budnost s hipnopompičnom halucinacijom. Ove halucinacije mogu biti posljedica kombinacije aktivnosti REM -a i mehanizma djelovanja lijeka.

Meditacija : Oni koji su napredni u praksi meditacije mogu prenijeti čudna osjetilna iskustva nakon prijelaza u stanje budnosti. To je zbog činjenice da meditacija s vremenom mijenja mozak, općenito na bolje (Pročitajte: Znanstvene prednosti meditacije). Većina vrsta meditacije omogućuje pojedincima da ostanu svjesni tijekom pojave sporijih moždanih valova (npr. Alfa i theta).

Netko tko je meditirao duže vrijeme može ostati polu-potpuno svjestan tijekom prolazne (hipnopompične) faze i biti svjestan bilo kakvih halucinacija koje se često javljaju kao posljedica REM-a (brzo kretanje očiju) ili aktivnosti slične REM-u . Valja napomenuti da različite vrste meditacije na jedinstven način utječu na mozak. Neke meditativne prakse mogu dovesti do povećanja hipnopompičnih halucinacija.

Neurotransmisija : Važno je razmotriti ulogu neurotransmisije u pojavi hipnopompičnih halucinacija. Kad se umjetno povećaju (kao posljedica lijekova ili dodataka), različiti neurotransmiteri mogu utjecati na san i/ili izazvati halucinacije. Na primjer, poznato je da povećana razina serotonina može utjecati na san.

Dodatno povećanje razine dopamina moglo bi rezultirati halucinacijama. Gustoća receptora za neurotransmitere također može imati ulogu u utjecaju na hipnopompične halucinacije. Ako određeni neurotransmiteri nisu adekvatno obrađeni receptorima (npr. Polimorfizmi dopaminskih receptora), to može dovesti do manifestacije halucinacija, od kojih bi se neke mogle pojaviti tijekom hipnopompičnog stanja.

Farmaceutski lijekovi : Postoje značajni dokazi koji podupiru ideju da bi farmaceutski lijekovi, osobito oni koji utječu na neurotransmisiju, mogli uzrokovati hipnopompične halucinacije. Izvješće objavljeno 2000. godine dokumentiralo je slučajeve pojedinaca koji su doživjeli hipnopompične halucinacije nakon primjene Donpezila, lijeka koji se koristi za liječenje simptoma Alzheimerove bolesti.

Lijek djeluje kao inhibitor acetilholinesteraze, čime se povećava koncentracija acetilkolina u nastojanju da se poboljša kognitivna funkcija. Nažalost, ovaj mehanizam djelovanja mijenja REM (brzo kretanje oka) i povećava vjerojatnost hipnopompičnih halucinacija. U starijim izvješćima iz osamdesetih godina prošlog stoljeća zabilježene su hipnopompične halucinacije među onima koji su uzimali triciklične antidepresive.

Smatra se da lijek Amitriptilin mijenja obrasce spavanja i većina pacijenata koji uzimaju lijekove mogu shvatiti da halucinacije nisu psihotične. No, liječnici bi ipak trebali upozoriti pacijente koji uzimaju ove lijekove kako ne bi paničili ili vjerovali da je to simptom psihoze. Treba nagađati da bi različiti psihijatrijski lijekovi mogli izazvati hipnopompične halucinacije.

Psihodinamika : Neki nagađaju da se tijekom hipnopompije svjesnom može otkriti nesvjesni ili podsvjesni materijal, što može pridonijeti halucinacijama. Neki vjeruju da su halucinacije manifestacije kumulativnog nesvjesnog i/ili podsvjesnog materijala. Drugi nagađaju da su halucinacije pripremljene kao rezultat ponavljajućeg materijala svjesnosti (npr. Tetris efekt).

Treća psihodinamička teorija je da su oni kombinacija svjesnog i podsvjesnog. Također je moguće da vlastito ožičenje mozga može izazvati halucinacije neovisno o cijelom svjesnom i podsvjesnom materijalu.

REM aktivnost : Moguće je da REM (brzo kretanje oka) ili naleti slični REM-u u određenim regijama mozga dovode do hipnopompičnih pojava. U hipnopompičnom stanju, smatra se da ljudi doživljavaju neku aktivnost brzog kretanja očiju (REM), a istovremeno postaju polusvjesni. Tijekom ovog REM stanja, ljudi mogu izvijestiti o živopisnim slikama koje bi mogle nastati kao izravna posljedica brzog kretanja očiju.

Slike iz REM -a mogu se privremeno zadržati, što rezultira izvješćima o hipnopompičnim vizualnim halucinacijama -#8211 najčešćoj vrsti. Važno je uzeti u obzir i činjenicu da brzo kretanje očiju može dovesti do percepcije zvukova i drugih osjeta (npr. Dodira) osim isključivo vizualnih pojava.

Osjetna oskudica : Postoje dokazi da senzorna deprivacija može dovesti do halucinacija tijekom hipnagogičkog i hipnopompičnog stanja. Ako se često bavite osjetilnom deprivacijom, vaš mozak shvaća da ne prima zvučne, vizualne ili druge podatke. Mozak neprestano skenira okoliš u potrazi za tim glavnim osjetilnim inputima koji su povezani s ljudskom evolucijom i preživljavanjem.

Budući da mozak nije u stanju pronaći bilo kakve okolišne inpute, popunjava praznine u osjetilnim informacijama generirajući halucinacije. To može biti zvuk, prizor ili kombinacija obojega. U slučaju da se uključite u senzornu deprivaciju prije spavanja, možete povećati izglede za hipnagogične ili hipnopompične halucinacije.

Nedostatak sna : Postoje dokazi da bi nedostatak i ograničavanje sna mogli uzrokovati hipnopompične halucinacije. Nedostatak sna mijenja moždanu aktivnost, hormone i neurotransmisiju – sve faktore koji mogu utjecati na hipnopompične pojave. Kronično nedostatak sna može povećati vjerojatnost halucinacijskih iskustava nakon buđenja iz stanja spavanja.


Spoznaja i percepcija: Postoji li doista razlika?

Što ako svaki uvodni udžbenik psihologije nije u redu s ulogom najosnovnijih i temeljnih sastavnica psihološke znanosti? Desetljećima su udžbenici učili da postoji jasna granica između percepcije-kako vidimo, čujemo, dodirujemo, okusimo i mirišemo-i kognitivnih procesa na višoj razini koji nam omogućuju da integriramo i interpretiramo svoja osjetila. Ipak, nova interdisciplinarna istraživanja pokazuju da razgraničenje između percepcije i spoznaje može biti mnogo zamagljenije nego što se ranije mislilo. Čini se da kognitivni procesi odozgo prema dolje utječu čak i na najosnovnije komponente percepcije, utječući na to kako i što vidimo. Nova otkrića također pokazuju da naši takozvani procesi percepcije na niskoj razini, poput mirisa, zapravo mogu biti mnogo pametniji nego što se prije mislilo. Razlučivanje onog što je odozgo prema dolje ili odozdo prema gore moglo bi biti daleko složenije nego što su znanstvenici nekad vjerovali.

Neuroimaging Mixing Bowl

Novi napredak u tehnologiji neuroslikovanja omogućuje istraživačima da promatraju percepcijske procese poput vida i dodira u stvarnom vremenu dok subjekti gledaju slike, slušaju zvuk ili prelaze prstima po taktilnim objektima.

Funkcionalna MRI (fMRI) mjeri promjene u protoku krvi u mozgu, dopuštajući istraživačima da promatraju određene regije i strukture mozga koje su aktivne tijekom zadatka. Međutim, fMRI radi na vremenskoj skali koja je daleko sporija od brzine mozga u milisekundama po milisekundama. Druga tehnologija snimanja, magnetoencefalografija (MEG), koristi senzore oko tjemena sudionika za mjerenje aktivnosti u mozgu. MEG omogućuje snimanje iznimno brze moždane aktivnosti gotovo u stvarnom vremenu, ali nedostaje preciznost fMRI za određivanje koje su strukture u mozgu aktivne.

Suradnica na APS-u Aude Oliva, viša znanstvena znanstvenica u području računalnog vida, neuroznanosti i interakcije čovjek-računalo u Laboratoriju za računalne znanosti i umjetnu inteligenciju MIT-a, radi na obećavajućoj novoj metodi kombiniranja podataka fMRI i MEG kako bi istraživači mogli promatrati i kada i gdje se u mozgu javlja vizualna percepcija. Glavni problem kombiniranja fMRI i MEG, objasnila je Oliva, jest da dvije metode pružaju različite vrste podataka s različitih vrsta senzora.

"Trenutne [neinvazivne] tehnike snimanja mozga izolirano ne mogu riješiti prostorno-vremensku dinamiku mozga jer pružaju ili visoku prostornu ili vremensku rezoluciju, ali ne oboje", rekli su Oliva i kolege Radoslaw Martin Cichy (Freie Universitat Berlin) i Dimitrios Pantazis (Institut Massachusetts tehnologije) napisao je u članku objavljenom 2016 Moždana kora.

Znanstvena znanstvenica s MIT -a Aude Oliva radi na novoj metodi kombiniranja funkcionalnih MRI i magnetoencefalografskih podataka koja istraživačima omogućuje promatranje i kada i gdje se vizualna percepcija javlja u mozgu. Fotografija: Benjamin Lahner

Nova metoda na koju se Oliva poziva pruža istraživačima mogućnost promatranja vizualne obrade brzinom milisekundi i razlučivosti milimetra.

U jednoj studiji, Oliva i kolege stvorili su masivnu bazu podataka o vizualnoj percepciji, snimivši tako da je 16 sudionika izvršilo identične zadatke i na fMRI i na MEG aparatu. Ovaj jedinstveni skup podataka omogućio je istraživačkom timu da izgradi matricu koja uspoređuje prostorne podatke iz fMRI i vremenske podatke iz MEG -a.

"Koristimo reprezentacijsku geometriju, a to je pojam gledanja na to koliko su slična dva ili više podražaja u prostoru vaših podataka", objasnila je Oliva.

Nalazi ove studije pružaju nove spoznaje o tome kako najosnovnije komponente vizualne percepcije, poput oblika ili boje, vode do kognitivnih procesa više razine vezanih uz kategorizaciju i pamćenje. U članku objavljenom 2014 Neuroznanost prirode, Oliva i kolege otkrili su da se tok moždane aktivnosti od viđenja objekta do prepoznavanja i klasifikacije kao biljke ili životinje dogodio velikom brzinom - samo 160 milisekundi.

Iako je Oliva primijetila da se u tim pokusima ne može razlikovati obrada odozdo prema gore i odozgo prema dolje, bilo je iznenađujućih nalaza. Neka područja mozga za koja se očekuje da će postati aktivna relativno kasno u prepoznavanju vizualnih objekata postala su aktivna mnogo ranije nego što se očekivalo.

This novel neuroimaging approach allows researchers to create spatio-temporal maps of the human brain that also include the duration of neural representations that can help to guide theory and model architecture, Oliva noted.

Distinguishing Between Seeing and Thinking

Recently, a large body of published research has shown that our “higher order” cognitive processes such as beliefs, desires, and motivations can exert significant top-down influences on basic perceptual processes, altering our basic visual perception. However, Yale University psychology professor and APS Fellow Brian Scholl insists that perception can proceed without any direct influence from cognition.

Scholl leads the Yale Perception and Cognition Laboratory, where he explores questions about how perception, memory, and learning interact to produce our experience of the world. In a bold 2016 paper coauthored with Chaz Firestone (John Hopkins University), he wrote: “None of these hundreds of studies — either individually or collectively — provides compelling evidence for true top-down effects on perception.” Scholl and Firestone said that basic visual perception is in fact much smarter than most researchers believe.

“We try to demonstrate how this is not just a matter of semantics, but these are straightforward empirical questions,” Scholl said at an Integrative Science Symposium at the 2019 International Convention of Psychological Science.

According to Scholl, causal history is just one example of a phenomenon that is widely considered paradigmatic of higher-level thinking but that really has a basis in low-level visual perception. For example, if you see a cookie with a bite taken out of it, you implicitly understand that the original shape of the cookie has been altered by events in the past, he said.

U studiji objavljenoj u Psihološka znanost, Scholl and lead author Yi-Chia Chen (Yale University) used an elegantly simple series of animations of square shapes that had “bites” taken out of them. When the initial square had missing pieces that inferred a causal history, like a cookie missing a bite shape rather
than missing a triangle, participants perceived the change in shape as gradual even when the animation showed an instantaneous change.

“When we draw the distinction between seeing and thinking, we can realize that perhaps the roots of this kind of representation may lie in low-level visual perception,” Scholl explained.

In another series of experiments, Scholl and Firestone used intuitive physics to show that people could tell within just 100 milliseconds whether a tower of blocks was unstable and about to fall over.

“When you look at a phenomenon, at a stimulus like this, I find that I see physics seemingly in an instant. You just have a visceral sense that doesn’t seem to require much thought, for example, for how stable that pile of plates is, whether it’s going to fall, perhaps how quickly it’s going to fall, what direction it’s going to fall,” Scholl said.

A Joint in Nature

New research on the top-down influence of cognition on perception has led to new questions from scientists about whether there truly is a “joint in nature” between cognition and perception.

“Now in philosophy, just as in psychology, there is a long history of regarding cognition and perception as basically the same thing,” said Ned Block, a professor of philosophy, psychology, and neural science at New York University.

Block pointed to evidence from perceptual science that supports a distinct joint between perception and cognition. The solitary wasp, a species of wasp that does not live in hives, is one example of evidence for pure perception in biology, he said. Though the wasps have excellent visual perception abilities, that perception is noncognitive and nonconscious.

When it comes to the question of defining where perception ends and cognition begins in humans, Block points to the work of Anna Franklin, a professor of visual perception and cognition at the University of Sussex. Franklin has conducted extensive research on infants’ color perception.

Although the colors of the rainbow are a continuous band of wavelengths, humans perceive color categorically — we break the continuous spectrum up into blocks of distinctive color groups. Using studies of eye movement and gaze, Franklin and colleagues found that infants can perceive color categories by the age of 4 to 6 months. Yet a body of research suggests that infants don’t begin to develop concepts of color until they’re around a year old.

Block cited a 1980 child speech and language study from APS Fellow Mabel Rice (University of Kansas) in which children as old as 3 took more than 1,000 learning trials over several weeks to learn the words “red” and “green.”

Yale psychology professor Brian Scholl says causal history is an example of a phenomenon based in low-level visual perception, rather than the higher-level thinking widely attributed to it.

Even Charles Darwin noted that children seem to have a difficult time learning words for color: “[I] was startled by observing that they seemed quite incapable of affixing the right names to the colours in coloured engravings, although I tried repeatedly to teach them. I distinctly remember declaring that they were colour blind,” Darwin wrote about his children in 1877.

“The idea is that 6- to 11-month-old infants have color perception without color concepts and this shows that color perception can be nonconceptual,” Block said. “And I think the simplest view is that all perception
is nonconceptual.”

Smart Sensory Neurons

John McGann’s work uses cutting-edge optical techniques to explore the neurobiology of sensory cognition in smell. McGann, a professor of psychology at Rutgers University, uses the olfactory system as a model to investigate neural processing of sensory stimuli.

In a recent series of experiments, McGann was interested in looking at cognitive processing at the earliest stages of perception — at the level of sensory neurons themselves.

For this research, McGann’s lab used genetically engineered mice. A little window was implanted in each mouse’s skull over the olfactory bulb where the brain processes scent, allowing researchers to see the mouse’s brain light up in reaction to odors.

“Not metaphorically light up they literally light up and you can see it through the microscope,” McGann explained.

The genetically engineered mice were exposed to a specific smell at the same time they experienced a painful shock. Not only did mice start showing typical fear-response behaviors after getting a whiff of the shock-associated odor, but the pattern of activation in olfactory bulb neurons was visible exposure to the fear-associated odor led to substantially more neurotransmitters being released from the olfactory sensory neurons compared with baseline levels before exposure to the painful shocks.

NYU professor Ned Block: “I think the simplest view is that all perception is nonconceptual.”

“So essentially, it was like the information coming into the brain from the nose already had the memory of bad things incorporated into it,” McGann said in a Znanost podcast interview.

In another experiment, mice were exposed to about a dozen rounds of a series of lights and audio tones before an odor. On trials in which researchers skipped over the anticipated audio tone, olfactory sensory nerves’ response to the odor was much smaller. This was unexpected because olfactory sensory neurons activate so early in sensory processing — they are physically contacting the odor as it enters the nasal mucosa, McGann explained.

“So how could the olfactory sensory neurons know all this stuff about shocks and lights and tones?” upitao.

These axons are surrounded by a population of interneurons at the location where they enter the brain, theoretically connecting these regions to many other areas of the brain. So even though the central nucleus of the amygdala doesn’t connect to the olfactory system, McGann and colleague Cynthia Fast (APOPO, a nonprofit in Tanzania) found that the amygdala is still part of a circuit where the nerve terminals in the nasal mucosa are connected through a series of interneurons.

“This means that maybe there’s no such thing as a purely ‘bottom-up’ odor representation in the mouse brain because this is the entry to the mouse brain,” McGann elaborated.

Learning What to Ignore

Thoughts of learning and decision-making tasks may conjure images of a rat learning whether to push a lever on the basis of a light turning on or off. But this is not at all what decision-making in the real world actually looks like, according to Yael Niv, a professor at the Princeton Neuroscience Institute at Princeton University. Just think about a mundane real-world task such as crossing the street. There are oncoming cars, parked cars, other pedestrians, crosswalks, and the countdown of a streetlight.

If our task is to cross the street, we might attend to the speed and distance of oncoming cars while ignoring their colors. Alternatively, if we’re trying to hail a taxi in New York City, we need to pay attention to spot the telltale yellow used by taxis. But how do we learn how to sort out the factors that are relevant or irrelevant in such a cluttered scene?

“All of learning is generalization because you never actually cross the same street twice in the same exact configuration, so no two events are ever exactly the same,” Niv explained. “The question that we ask in my lab is ‘how do we learn a representation of the environment for each task that will support efficient learning and efficient decision-making?’”

In order to better understand how we learn what to ignore, Niv’s lab has used a task called the dimensions task. Participants in an fMRI scanner are shown sets of stimuli with different dimensions (i.e., color, shape, texture). To earn a reward, they must learn which item to select out of the set. Features from only one relevant dimension — assigned by the researchers — determine the probability of reward. The rub is that participants are not told ahead of time what dimension is relevant and what target feature will get them the reward.

“So this is kind of like crossing the street in the sense that you can ignore a bunch of stuff and concentrate only on one dimension — either color, or shape, or texture. The question is how does the human brain learn this,” Niv explained.

Niv then uses this trial-by-trial choice data to develop computational models that reflect participants’ learning and decision-making strategies. In 10 years of working with this task, the Niv lab has determined that participants don’t appear to be using simple reinforcement learning, Bayesian inference, or simple hypothesis testing, she said. Instead, the best model uses what they call feature reinforcement learning plus decay: After each trial, the value of each of the chosen features is updated and adjusted to reflect any prediction errors, while all other values are decayed toward zero, to mimic less attention to those.

“What I’m trying to understand is how cognition shapes what we attend to and how we decide what to attend to,” Niv explained. “What we have shown so far is that attention constrains what we learn about, and we consider this a feature, not a bug by constraining learning to only the dimensions that are relevant to the task, we can learn to cross the street in 10 trials and not in 10,000 trials.”

This article is based in part on an Integrative Science Symposium at the 2019 International Convention of Psychological Science (ICPS) in Paris. Learn about ICPS 2021 in Brussels.


Materijali i metode

Sudionici

This study reports findings from five late-onset blind/visually-impaired individuals diagnosed with CBS (age 47 ± 8.9, two females, two left handed, one ambidextrous), 11 late-onset blind individuals not experiencing visual hallucinations (blind control group, age 40.54 ± 11, four females, two left handed, one ambidextrous) and 13 sighted individuals with normal or corrected-to-normal vision (sighted control group, age 43.85 ± 7.4, 10 females, two left handed). Experimental groups did not differ in age, gender or handedness (all P-values > 0.27, Fisher’s exact test). Participants had no history of psychiatric illness or cognitive impairments, and were not taking any psychoactive medications. Recruitment of participants was carried out with the assistance of a neuro-ophthalmologist, and through standard advertisements. All participants provided written informed consent before participating, in accordance with the Declaration of Helsinki, and were paid for their participation in the study. All procedures were approved by the Tel-Aviv Sourasky Medical Center, IRB ethics committee. Table 1 presents demographic, clinical and hallucination phenomenology information of the CBS participants (see also Supplementary material , ‘Hallucination phenomenology’ section).

Phenomenology of hallucinations in participants with CBS

. CBS 1 . CBS 2 . CBS 3 . CBS 4 . CBS 5 .
Dob 48 48 59 34 46
Spol Female Female Muški Muški Muški
Handedness Ambidextrous Pravo Lijevo Lijevo Pravo
Visual acuity No light perception No light perception Light perception 6/120 No light perception
Time since deterioration of vision, years 15 22 16 3 2.5
Dijagnoza Retinitis pigmentosa Retinitis pigmentosa Retinitis pigmentosa Cone-rod dystrophy Glaukom
VVIQ score a 70 103 61 99 124
Hallucinatory content Continuous stream of still images, including humans, animals, objects, houses, and patterns Face of a man who is unfamiliar to the participant. The face can appear and disappear and can rotate or move across the visual field Unfamiliar and distorted black and white faces, rotating objects, patterns and flashes of light Very rapid flashes of light spanning the entire visual field Continuous and rapidly changing shapes and colours that resemble kaleidoscope patterns
Frequency of hallucinations Konstantno Weekly Every few months Konstantno Konstantno
Number of alternations in hallucinations per 8-min scan, mean ± SD 123.6 ± 50.5 (four verbal and four manual report scans) 13.7 ± 4.9 (two verbal and one manual report scans) 17.5 ± 12 (one verbal and one manual report scans) Continuous Continuous
Frequency of alternations in hallucinatory content Seconds Minutes Seconds–minutes Fractions of a second Fractions of a second
Do hallucinations move with gaze? Ne Da Da Da Da
. CBS 1 . CBS 2 . CBS 3 . CBS 4 . CBS 5 .
Dob 48 48 59 34 46
Spol Female Female Muški Muški Muški
Handedness Ambidextrous Pravo Lijevo Lijevo Pravo
Visual acuity No light perception No light perception Light perception 6/120 No light perception
Time since deterioration of vision, years 15 22 16 3 2.5
Dijagnoza Retinitis pigmentosa Retinitis pigmentosa Retinitis pigmentosa Cone-rod dystrophy Glaukom
VVIQ score a 70 103 61 99 124
Hallucinatory content Continuous stream of still images, including humans, animals, objects, houses, and patterns Face of a man who is unfamiliar to the participant. The face can appear and disappear and can rotate or move across the visual field Unfamiliar and distorted black and white faces, rotating objects, patterns and flashes of light Very rapid flashes of light spanning the entire visual field Continuous and rapidly changing shapes and colours that resemble kaleidoscope patterns
Frequency of hallucinations Konstantno Weekly Every few months Konstantno Konstantno
Number of alternations in hallucinations per 8-min scan, mean ± SD 123.6 ± 50.5 (four verbal and four manual report scans) 13.7 ± 4.9 (two verbal and one manual report scans) 17.5 ± 12 (one verbal and one manual report scans) Continuous Continuous
Frequency of alternations in hallucinatory content Seconds Minutes Seconds–minutes Fractions of a second Fractions of a second
Do hallucinations move with gaze? Ne Da Da Da Da

The possible range of the scores in the Vividness of Visual Imagery Questionnaire (VVIQ) across two administrations is 32–160, where low scores indicate higher imagery abilities.

Phenomenology of hallucinations in participants with CBS

. CBS 1 . CBS 2 . CBS 3 . CBS 4 . CBS 5 .
Dob 48 48 59 34 46
Spol Female Female Muški Muški Muški
Handedness Ambidextrous Pravo Lijevo Lijevo Pravo
Visual acuity No light perception No light perception Light perception 6/120 No light perception
Time since deterioration of vision, years 15 22 16 3 2.5
Dijagnoza Retinitis pigmentosa Retinitis pigmentosa Retinitis pigmentosa Cone-rod dystrophy Glaukom
VVIQ score a 70 103 61 99 124
Hallucinatory content Continuous stream of still images, including humans, animals, objects, houses, and patterns Face of a man who is unfamiliar to the participant. The face can appear and disappear and can rotate or move across the visual field Unfamiliar and distorted black and white faces, rotating objects, patterns and flashes of light Very rapid flashes of light spanning the entire visual field Continuous and rapidly changing shapes and colours that resemble kaleidoscope patterns
Frequency of hallucinations Konstantno Weekly Every few months Konstantno Konstantno
Number of alternations in hallucinations per 8-min scan, mean ± SD 123.6 ± 50.5 (four verbal and four manual report scans) 13.7 ± 4.9 (two verbal and one manual report scans) 17.5 ± 12 (one verbal and one manual report scans) Continuous Continuous
Frequency of alternations in hallucinatory content Seconds Minutes Seconds–minutes Fractions of a second Fractions of a second
Do hallucinations move with gaze? Ne Da Da Da Da
. CBS 1 . CBS 2 . CBS 3 . CBS 4 . CBS 5 .
Dob 48 48 59 34 46
Spol Female Female Muški Muški Muški
Handedness Ambidextrous Pravo Lijevo Lijevo Pravo
Visual acuity No light perception No light perception Light perception 6/120 No light perception
Time since deterioration of vision, years 15 22 16 3 2.5
Dijagnoza Retinitis pigmentosa Retinitis pigmentosa Retinitis pigmentosa Cone-rod dystrophy Glaukom
VVIQ score a 70 103 61 99 124
Hallucinatory content Continuous stream of still images, including humans, animals, objects, houses, and patterns Face of a man who is unfamiliar to the participant. The face can appear and disappear and can rotate or move across the visual field Unfamiliar and distorted black and white faces, rotating objects, patterns and flashes of light Very rapid flashes of light spanning the entire visual field Continuous and rapidly changing shapes and colours that resemble kaleidoscope patterns
Frequency of hallucinations Konstantno Weekly Every few months Konstantno Konstantno
Number of alternations in hallucinations per 8-min scan, mean ± SD 123.6 ± 50.5 (four verbal and four manual report scans) 13.7 ± 4.9 (two verbal and one manual report scans) 17.5 ± 12 (one verbal and one manual report scans) Continuous Continuous
Frequency of alternations in hallucinatory content Seconds Minutes Seconds–minutes Fractions of a second Fractions of a second
Do hallucinations move with gaze? Ne Da Da Da Da

The possible range of the scores in the Vividness of Visual Imagery Questionnaire (VVIQ) across two administrations is 32–160, where low scores indicate higher imagery abilities.

Experimental design

We aimed to study hallucinations (unprompted perceptual events) in CBS as a model for unprompted behaviours. To isolate the unprompted component of hallucinations, we compared hallucinations in CBS to cued veridical vision in sighted controls who were presented with visual simulations of these hallucinations. However, while the unprompted nature of visual hallucinations differentiates them from veridical vision, another difference is that hallucinations are internally generated while veridical vision is evoked by external stimulation. To control for this difference, we further compared hallucinations to cued visual imagery, as both of these conditions are internally generated, but only hallucinations are unprompted. Finally, to ensure that hallucination-related brain activations are not the product of mere verbal/manual report, we used a control condition consisting of verbal and manual tasks that were unrelated to the onsets of hallucinations.

The experimental procedures included the administration of questionnaires, and between one and three functional MRI sessions per participant. Session times ranged between 45 min and 120 min. In aggregate, these sessions included one resting-state scan (all groups), one to two imagery scans (all groups), an anatomical scan (all groups), a verbal-manual control condition (CBS participants/blind controls), and one visual localizer scan (sighted controls). We also conducted two to four hallucination scans reported verbally or using button-presses for each CBS participant, and for sighted controls, we conducted six simulated hallucination scans (as elaborated below). The order of scans was counterbalanced across participants with the exception that the first session always began with a resting-state run. Analyses of the visual localizer and resting state scans will not be reported here. Experimental software is detailed in the Supplementary material .

Upitnici

Questionnaires were used to collect demographic and clinical details. Additionally, the Vividness of Visual Imagery Questionnaire (VVIQ Marks, 1973) was administered to assess how vividly participants imagined different scenes and situations. This questionnaire was administered twice, with participants' eyes being open/shut, and the scores across the two administrations were summed per participant.

Hallucination report

During prescanning simulations, Participants CBS1–3 stated that they could report their hallucination as easily and promptly as they could identify visual stimuli before their vision deteriorated. Participants CBS4 and CBS5 said they were unable to report their hallucinations, and were therefore excluded from the report condition and subsequent analyses (but were included in all other conditions and analyses). The report condition consisted of several 8-min scans (number of scans depended on the availability/stamina of participants Table 1), in which participants provided reports of their hallucinations either verbally, or via button presses. Because some CBS participants had some, albeit minimal, residual vision, participants were instructed to close their eyes during the entire scanning procedure. Participants were trained to speak without moving their heads, both outside and inside the scanner.

In-scanner verbal reports of hallucinations were recorded, and played back to the participants outside the scanner at the end of each session, asking them to give details of these hallucinatory events. Because the visual acuity of all CBS participants deteriorated at a relatively late stage of life, their description of the hallucinations was based on their prior visual experiences.

During the button-press runs, Participant CBS1 pressed a button using her index finger whenever an image appeared (note that hallucinatory images were constantly replaced by other images with no interval between them). Participants CBS2 and CBS3 pressed a button with the index finger whenever a face appeared and pressed a second button using the middle finger when the face disappeared.

Simulated hallucinations

The temporal structure of the in-scanner verbal reports made by the CBS participants, along with the post hoc details regarding the hallucinations’ content, were used to create movies simulating these hallucinatory streams. Three such movies were created, one corresponding to each of the reporting CBS participants. The simulated hallucinations of Participant CBS1 consisted of images of humans, animals, body parts, objects, houses and patterns, presented in different sizes and positions on a grey background. The simulated hallucinations of Participant CBS2 consisted of a video recording of a male face, made small enough to move around the grey screen. The simulated hallucinations of Participant CBS3 consisted of various pictures and of video recordings of faces/patterns, all presented on a grey background. To account for the possible latency between the true onset of hallucinations and the actual reports made by CBS participants, all simulated stimuli were presented 1 s prior to their real temporal position, as reported by the CBS participants ( Ben-Yakov and Henson, 2018).

Sighted control participants watched these simulated hallucination streams in an order that was counterbalanced across participants. Each simulated hallucination stream was watched twice, with instructions to report the hallucinatory content verbally or using button presses, as the CBS participants did. Participants were trained to speak without moving their heads. Two sighted control participants only completed the verbal-report runs, and additional four participants had one to three of their six scans excluded from further analyses because of excessive head motion. Nevertheless, all participants had at least one valid scan for each simulated hallucination stream.

Visual imagery

All participants were asked to imagine faces, houses, objects and patterns. Before the scan, participants were given examples of items from each category. This 8-min run comprised 12-s blocks, each beginning with an auditory cue signalling a category name. These blocks ended with the auditory instruction ‘rest’, which was followed by an 8-s resting period. Block order was pseudo-randomized across participants. All participants closed their eyes during this experiment. CBS and all blind control participants completed two separate runs of this experiment (except for two blind controls, who completed only one run), and sighted controls completed one run. Data from one blind control were excluded from further analyses due to excessive head motion.

At the end of each run, participants assessed their success level in imagining each visual category on an increasing success scale of 1–5. These ratings were summed per participant.

Verbal-manual control condition

To test whether verbal or manual reports alone evoke activity in the visual system, CBS and blind control participants performed a tone discrimination task. During this 8 min 6 s scan, participants heard a second-long tone of either 440 Hz or 460 Hz, interleaved with silent periods of 3–5 s. Stimulus order was pseudo-randomized across participants. Participants spoke/pressed a button when presented with the higher/lower frequency tone, respectively. Participants were trained to differentiate between the two tones before being scanned. Data from one blind control were excluded from further analyses due to excessive head motion.

See the Supplementary material for MRI data acquisition and preprocessing description.

Statistička analiza

Upitnici

Given the small sample size of participants, here and in all similar analyses, scores were compared between experimental groups using non-parametric permutation tests ( Holmes et al., 1996 Nichols and Holmes, 2002). Here, each test statistic was set to the difference between the group means. Under the null hypothesis of no group difference in imagery capabilities, participants’ group labels were shuffled to create two random groups of participants, and the difference between these groups’ means was calculated. This procedure was repeated for all possible permutations of participants between the two groups to construct the full null distribution, which was used to derive a two-tailed P-value for the true (unshuffled) test statistic.

Whole-brain analyses

To create task-based statistical parametric maps, we applied a voxel-based general linear model (GLM) as implemented in FSL’s FEAT, using a double-gamma haemodynamic response function convolved with the experimental model, as well as the resulting regressors' temporal derivatives. The six motion parameters and their derivatives, scrubbed volumes ( Power et al., 2012), and ventricle and white matter time courses for each participant ( Fox et al., 2009) were used as nuisance regressors. In addition, in the simulated hallucinations data, the first/last five repetition times (TRs) of each scan were included in the GLM model as nuisance variables, to remove the contribution of arousal-related effects. See the Supplementary material for a detailed description of all GLM designs.

As the sample size of the CBS group was small, whole-brain comparisons between the CBS group and any of the control groups were carried out using non-parametric randomization tests, as implemented in FSL’s randomize ( Winkler et al., 2014), including threshold free cluster enhancement correction for multiple comparisons. However, because of the inherent differences between the hallucination and the simulated hallucinations conditions (as it is impossible to simulate hallucinations with full precision), we refrained from directly contrasting activation strengths between these conditions, as any effects could be equally attributed to differences between hallucinations and veridical vision, or to differences in the visual stimuli.

Parametric activation maps were projected onto a template of a flattened cortical surface using the Connectome Workbench.

Quantifying the similarity between visual activations

Our hypothesis that hallucination-related activations would be similar to activations evoked by other visual experiences was tested in the posterior part of the brain (25 876 grey matter voxels corresponding to y < 44 in MNI space Gilaie-Dotan et al., 2013.). CBS hallucination activations (group beta values) were correlated with imagery/simulated-hallucinations beta values of each sighted control and with imagery/verbal-manual control condition beta values in each blind control. This calculation was performed twice for sighted controls in the simulated-hallucination condition: once modelled using the CBS report protocol, and once using a protocol locked to the sighted controls' own manual report. In both cases, for each sighted control participant, analysis was carried out using beta-value maps resulting from an FFX analysis of all three simulated-hallucinations data (corresponding to simulations of the three CBS participants’ hallucinations). Resulting correlation coefficients of the participants in each group and experimental condition were tested using a two-tailed one-sample Wilcoxon test.

Note that we refrained from statistically testing the posterior brain correlations of CBS participants across the different experimental conditions, because: (i) any significant similarities between the activations evoked by the imagery/control condition to those evoked by hallucinations may be confounded by the fact that CBS participants hallucinated during all conditions and (ii) any absence of statistical significance could be due to the lack of statistical power in testing very small samples (specifically, the largest possible effect size in a sample of n = 5 in a Wilcoxon test would correspond with a P-value of 0.03. Any smaller effect size would be non-significant under an alpha level of 0.05). Nevertheless, we assume that since CBS participants originate from the blind population, any effects found in blind controls during the imagery/verbal-manual control conditions should be representative of similar effects in CBS participants.

See the Supplementary material for a description of a bootstrap analysis testing whether the measured correlations were driven by noise.

Evaluation of temporal dynamics

To assess differences in the temporal dynamics of blood oxygenation level-dependent (BOLD) activity between the experimental groups, we extracted signals from an early/intermediate visual and a fusiform face area (FFA) regions of interest. Sensorimotor lip/hand regions of interest were also used as control regions for the verbal/manual report scans, respectively (see the Supplementary material for region of interest definitions and testing of activation in early/intermediate visual regions of interest).

Single participant’s signals were extracted from each region of interest, z-score normalized and subjected to an event related averaging analysis, within a time window of 3 TRs prior to stimulus onset to 7 TRs after stimulus onset. These signals were later averaged across participants of the same experimental group and for each experimental condition.

The BOLD signal typically rises shortly after stimulus presentation, but due to noise factors (e.g. slight asynchronies between scanner and experimental protocol, inconsistencies in participants’ attentiveness across trials, etc.) the event-related signals for individual participants may show slight random jitter (±1 TR) around the true event timings. Here, however, we had a clear prediction that the BOLD signal in visual regions across all CBS participants should consistently precede the reported onset of hallucinations, unlike in other experimental conditions or in the control groups. To test this prediction statistically, a canonical haemodynamic response function (HRF) was fitted to the event-related data of each individual participant (this was done automatically without the possibility of adjustment). This HRF was fitted to the data five times, each time with a different lag, ranging between 3 TRs prior to the modelled neural event (hallucination/imagery/vision) to 1 TR after the modelled neural event. The HRF lag that produced the best fit between the HRF and data was identified in each participant. These ‘optimal lags’ of the HRF in each region of interest were then compared between the CBS group and each of the sighted/blind control groups separately, using a permutation test ( Supplementary material ).

All sighted controls' simulated-hallucinations data (verbal and button-press scans) were analysed using a protocol locked to the hallucination report of CBS participants, and button-press scans were further analysed using a protocol locked to the individual button presses of each sighted control participant. The analysis of the sensorimotor lips/hand regions of interest made use of scans involving verbal/button-press reports, respectively.

Quantifying BOLD temporal dynamics across the visual hierarchy

To assess differences in the onset of the BOLD responses across regions of the visual system, all regions of interest of a probabilistic atlas ( Wang et al., 2015) were ranked based on their position in the visual hierarchy ( Supplementary Table 1 ). The optimal HRF lag was calculated for each CBS participant and region of interest in the hallucination and imagery conditions, as explained earlier. Then, Spearman’s correlation was calculated between the rank of all regions of interest and the group-averaged optimal lags in these regions of interest. The resulting correlation coefficients were tested using a permutation test, under the null hypothesis of no correlation between ranks across the visual hierarchy and optimal lags. region of interest ranks across the visual hierarchy were therefore shuffled 10 000 times, and, each time, the correlation coefficient between the random ranks and optimal lags was computed. Two-tailed P-values were derived based on this null distribution.

Dostupnost podataka

Statistical data and experimental materials are available upon request.


The Differences between Sensation and Perception

Do these two major processes make more sense to you now? Have a look at the table below to see all the main differences between perception and sensation.

Osjećaj

Percepcija

  • The sensation is the first stage of a complex process that allows us to understand and interact with our world.
  • Perception is the second stage of said process.
  • The sensation is more physical. It entails the simple awareness of various stimuli.
  • Perception gives meaning to what we sense and can be said it is a mix of sensations with ideas, past experience, and connections with objects or concepts.
  • Sensation does not involve any organization , combination or selection of stimuli.
  • Perception entails organization, combination, and selection to form stimuli into a pattern.

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Attention and Expectation

Selective attention occurs when the brain finds some parts of a scene more relevant or important and these are selected for special processing. Expectation often is the reason for the selective attention. Looking for a lost object (a missing car key) the brain focuses on the usual places for it. It is difficult to think of looking in the unusual locations where the lost object is hiding in plain sight.

Along with the impossible to define word “consciousness”, attention is, also, not definable, except in context. Therefore, the specific brain regions involved in each are not really defined. Definitions of “attention” and “consciousness” and “expectation” are logical definitions in a system of thought, rather than an inherent biological fact. For this discussion, expectation focuses on those aspects of the scene likely to be present. Selective attention further focuses the brain’s search to understand the scene by choosing those sensory inputs that are deemed to be more important.

Some research teases out those modulations that occur on the probably of specific sensory input occurring versus the importance that the observer places on them.

When data is vague, then probability operates more. When data is very specific and strong, then the fact that something is meaningful increases the decision-making. Attention naturally ignores very unexpected or extremely vague information. But, also, attention makes the prediction occur more rapidly.

Attention and expectation interact in many ways. Expectations can be about specific parts of the scene and attention decides how important it is. Errors occur in predictions and these are constantly being altered and updated. Attention can alter the amount of errors. Attention affects whether there is more needed information. Expectations and their probabilities are more important for determination of the response. Attention makes more details apparent. Both can increase and alter the perceptual decision.

In one study expectation limited sensory information and reactions when there was little attention. With attention, the opposite occurs and there is more data and reaction. Attention changes the ability of the top-downneurons from suppressing expectations by focusing on errors. Attention makes errors more available for analysis. Research shows that attention strongly affects errors in prediction.

Repetition of a scene shows movement and change and is highly related to expectation and attention. The default of repetition is stability, not change.

When a neuron fires repetitively, the sensory signal decreases. This could be nerve fatigue. Or it could be the suppression of expectation. When the repetitions are more expected, the signals are greater. Repetition supression begins at 50 ms and expectation suppression at 100 ms.


Bleeding in the Brain

Sometimes an injury damages blood vessels inside your brain. The trapped blood pools and forms a bump called a hematoma. It can lessen or cut off blood flow to your brain. This is a medical emergency. Some signs of a hematoma include:

  • Glavobolje
  • Povraćanje
  • Trouble with balance
  • Slabost
  • Napadi
  • Problems speaking


Coping

An important aspect of helping a loved one who is experiencing hallucinations is reassuring them that treatment is available. Here are a few more practical steps for helping your loved one cope with hallucinations.

Pay Attention the Environment

The environment can play an important role in misperceptions and worsening of hallucinations for example, a poorly lit room and loud, chaotic setting may increase the likelihood of a hallucination.

Ostani miran

Although it can be frightening and uncomfortable when a loved one experiences a hallucination, it’s important to do your best to respond in a calm, supportive manner. For example, you might say “I know this is scary for you” or “Don’t worry I’m here.”

Use Distraction

Depending on the severity of the hallucination, gently touching or patting your loved one may help serve as a distraction and reduce the hallucination. Other possible distractions include conversation, music, or a move to another room.

Be Honest

While you don’t want to upset your loved one or engage in an argument, you do want to be honest and assure them that you're not dismissing their concerns. If they ask: "Did you hear that?" Consider saying: "I know you heard something, but I didn’t hear it."

Maintain Routines

Keeping normal and reliable day-to-day routines can make it less likely that your loved one will stray from reality and experience hallucinations. Consider keeping a record of when hallucinations occur and under what circumstances.

If you or a loved one are struggling with hallucinations, contact the Substance Abuse and Mental Health Services Administration (SAMHSA) National Helpline at 1-800-662-4357 for information on support and treatment facilities in your area.


Gledaj video: Potresi mozga kod odraslih i dece - KAKO lečiti i koji su to simptomi na koje treba obratiti pažnju (Lipanj 2022).


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