Recent behavioral studies showed that prior knowledge can directly influence visual perception. I... more Recent behavioral studies showed that prior knowledge can directly influence visual perception. In the current work, we offer an explanation of the observed findings based on the adaptive resonance theory (ART). The ART neural network was designed to solve the problem of catastrophic forgetting during learning in non-stationary environment. In the ART, stability of learning is achieved by matching bottom-up sensory signals with top-down expectations. Resonant state that corresponds with conscious perception develops in the network when the bottom-up and top-down signals are closely aligned. On the other hand, mismatch produces global reset signal that clears the traces of erroneous top-down expectations. Therefore, prior knowledge can influence conscious perception only when it already closely matches with sensory signals. We performed computer simulations with real-time implementation of the ART circuit that confirm our analysis. Simulations also showed how observed behavioral find...
Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijsk... more Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijske pravednosti. Nastojalo se provjeriti faktorsku strukturu Skale orijentacije na pravdu i utvrditi doprinos faktora orijentacije na pravdu objašnjenju percepcije organizacijske pravednosti. Istraživanje je provedeno na prigodnom uzorku od 673 sudionika zaposlenih u 32 hijerarhijski strukturirane organizacije različitih djelatnosti s područja grada Osijeka, Rijeke, Valpova, Pule, Donjeg Miholjca i Našica. Od instrumenata korištena je Skala orijentacije na pravdu za mjerenje orijentacije na pravdu te Upitnik percepcije organizacijske pravednosti za mjerenje percepcije organizacijske pravednosti. Tvrdnje su procjenjivane na ljestvicama Likertova tipa od pet stupnjeva, a od sudionika se tražilo da zaokruže stupanj u kojem se slažu ili ne slažu s nekom od navedenih tvrdnji. Rezultati faktorske i hijerarhijskih regresijskih analiza sugeriraju da bi se mogle prihvatiti obje istraživačke hipotez...
Emocionalna inteligencija (EI) relativno je nov i nedovoljno istražen pojam, a sve se ucestalije ... more Emocionalna inteligencija (EI) relativno je nov i nedovoljno istražen pojam, a sve se ucestalije spominje kao ona pomocu koje je moguce predvidjeti razlicite poslovne i životne ishode (Bachman, Stein i Campbell, 2000; Bar-On, 1997; Boyatzis, Goleman i Rhee, 2000). Za njezinu pojavu odgovorni su znanstveni, socijalni, ali i prakticni razlozi, a njihov kombinirani utjecaj doveo je do brojnih kontroverzi oko definiranja, mjerenja i valjanosti EI. Cilj ovoga rada jest operacionalizacija te prikaz metoda mjerenja EI. Iz razloga sto postoje brojne definicije EI koje se grupiraju ovisno o teoretskim modelima važno je njihova mjerenja interpretirati odvojeno. Dva najzastupljenija modela su modeli mentalnih sposobnosti mjereni testovima ucinka i modeli samoprocjene EI koji ukljucuju dvije podvrste: „mijesane modele“ i skale samoprocjene sposobnosti EI po revidiranom modelu Mayera i Saloveya. Valjanost se, eksplicitno ili implicitno, smatra jednom od najvažnijih metrijskih karakteristika mjernog instrumenta. Unatoc tome sto postoje brojni nacini provjere mjeri li zaista test ono sto bi trebao, u slucaju EI najcesce se radi o diskriminantnoj valjanosti. Stoga, kako bi se ispitala konstruktna valjanost, nužno je usporediti razlicite mjere u terminima konvergentne i diskriminantne valjanosti. U svrhu pružanja prikladne mjere takav konstrukt morao bi demonstrirati prediktivnu moc izvan kognitivne inteligencije i petofaktorskog modela. To bi zapravo znacilo da nova varijabla ne bi trebala prejako korelirati s IQ-om ili petofaktorskim modelom, ali, s druge strane, visoko korelirati sa sposobnostima (izvedbom). Prema empirijskim pokazateljima testovi operacionalizirani kao testovi ucinka EI imaju zadovoljavajucu konvergentno-divergentnu valjanost u odnosu na druge mjere inteligencije. Međutim smatra se da samo MSCEIT (Mayer, Salovey, Caruso Emotional Intelligence Tests) mjeri EI u skladu s postavkama konstrukta inteligencije.
Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijsk... more Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijske pravednosti. Nastojalo se provjeriti faktorsku str
U radu su prikazani teorijski argumenti i empirijske potvrde za ideju i protiv ideje da kognitivn... more U radu su prikazani teorijski argumenti i empirijske potvrde za ideju i protiv ideje da kognitivni procesi (mišljenje, rezoniranje, očekivanje i vjerovanje) ili emocije i motivacija mogu izravno utjecati na i mijenjati sadržaj vida. Prema hipotezi o modularnosti uma i Marrovoj računalnoj teoriji vid je informacijski zatvoren modul s fiksnom, urođenom arhitekturom. Ona se temelji na specifičnim načelima koja su bitno drugačija od općega kognitivnog funkcioniranja. Vid mora biti kognitivno inpenetrabilan zato jer mora stvoriti točnu mentalnu reprezentaciju vanjskog svijeta i time omogućiti jedinki uspješno snalaženje u njemu. Suprotno tome, prema modelu prediktivnog kodiranja, kao suvremenog oblika zagovaranja penetrabilnosti vida, mozak stalno generira predikcije koje olakšavaju i usmjeravaju procesiranje osjetnih informacija i posljedično mijenjaju ono što vidimo. U novije vrijeme mnoga bihevioralna i neuroznanstvena istraživanja pokazuju da se vid doista mijenja pod utjecajem naučenih asocijacija i konteksta kao i socijalne kognicije, motivacije i emocija, što upućuje na zaključak da je vid kognitivno penetrabilan. Međutim, u navedenim su istraživanjima identificirane brojne metodološke i interpretacijske poteškoće iz kojih proizlazi suprotan zaključak. Na kraju, opisani su mogući smjerovi za daljnja teorijska i empirijska istraživanja koja bi nas trebala približiti razrješenju ovoga složenog pitanja.
Incremental grouping is a process entailing serial binding of distal image elements into a unifie... more Incremental grouping is a process entailing serial binding of distal image elements into a unified object representation. At the neural level, incremental grouping involves propagation of the enhanced firing rate among feature-tuned neurons in the early visual cortex. Here, we developed a multi-resolution neural model of incremental grouping. In the model, propagation of the enhanced firing rate is achieved by computing the activity difference between two sets of units: attentional or A-units, whose firing rate is modulated by their horizontal collaterals, and non-attentional or N-units that receive only feedforward input. The activity difference is computed on dendrites that act as independent computational subunits. The proposed model employs multiple spatial scales to account for a variable speed of incremental grouping. In addition, the model incorporates the Ljunction detection network that enables incremental grouping over L-junctions. Computer simulations show that the timing of attentional modulations in the model is comparable with neurophysiological measurements in monkey primary visual cortex.
Incremental grouping is a process entailing serial binding of distal image elements into a unifie... more Incremental grouping is a process entailing serial binding of distal image elements into a unified object representation. At the neural level, incremental grouping involves propagation of the enhanced firing rate among feature-tuned neurons in the early visual cortex. Here, we developed a multi-resolution neural model of incremental grouping. In the model, propagation of the enhanced firing rate is achieved by computing the activity difference between two sets of units: attentional or A-units, whose firing rate is modulated by their horizontal collaterals, and non-attentional or N-units that receive only feedforward input. The activity difference is computed on dendrites that act as independent computational subunits. The proposed model employs multiple spatial scales to account for a variable speed of incremental grouping. In addition, the model incorporates the Ljunction detection network that enables incremental grouping over L-junctions. Computer simulations show that the timing of attentional modulations in the model is comparable with neurophysiological measurements in monkey primary visual cortex.
Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial... more Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial representation, which is termed a Boolean map. It partitions the visual scene into two distinct and complementary regions: selected and not selected. Here, we developed a model of a recurrent competitive network that is capable of state-dependent computation. It selects multiple winning locations based on a joint top-down cue. We augmented a model of the WTA circuit that is based on linear-threshold units with two computational elements: dendritic non-linearity that acts on the excitatory units and activity-dependent modulation of synaptic transmission between excitatory and inhibitory units. Computer simulations showed that the proposed model could create a Boolean map in response to a featured cue and elaborate it using the logical operations of intersection and union. In addition, it was shown that in the absence of top-down guidance, the model is sensitive to bottom-up cues such as saliency and abrupt visual onset.
Recent behavioral studies showed that prior knowledge can directly influence visual perception. I... more Recent behavioral studies showed that prior knowledge can directly influence visual perception. In the current work, we offer an explanation of the observed findings based on the adaptive resonance theory (ART). The ART neural network was designed to solve the problem of catastrophic forgetting during learning in non-stationary environment. In the ART, stability of learning is achieved by matching bottom-up sensory signals with top-down expectations. Resonant state that corresponds with conscious perception develops in the network when the bottom-up and top-down signals are closely aligned. On the other hand, mismatch produces global reset signal that clears the traces of erroneous top-down expectations. Therefore, prior knowledge can influence conscious perception only when it already closely matches with sensory signals. We performed computer simulations with real-time implementation of the ART circuit that confirm our analysis. Simulations also showed how observed behavioral find...
Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijsk... more Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijske pravednosti. Nastojalo se provjeriti faktorsku strukturu Skale orijentacije na pravdu i utvrditi doprinos faktora orijentacije na pravdu objašnjenju percepcije organizacijske pravednosti. Istraživanje je provedeno na prigodnom uzorku od 673 sudionika zaposlenih u 32 hijerarhijski strukturirane organizacije različitih djelatnosti s područja grada Osijeka, Rijeke, Valpova, Pule, Donjeg Miholjca i Našica. Od instrumenata korištena je Skala orijentacije na pravdu za mjerenje orijentacije na pravdu te Upitnik percepcije organizacijske pravednosti za mjerenje percepcije organizacijske pravednosti. Tvrdnje su procjenjivane na ljestvicama Likertova tipa od pet stupnjeva, a od sudionika se tražilo da zaokruže stupanj u kojem se slažu ili ne slažu s nekom od navedenih tvrdnji. Rezultati faktorske i hijerarhijskih regresijskih analiza sugeriraju da bi se mogle prihvatiti obje istraživačke hipotez...
Emocionalna inteligencija (EI) relativno je nov i nedovoljno istražen pojam, a sve se ucestalije ... more Emocionalna inteligencija (EI) relativno je nov i nedovoljno istražen pojam, a sve se ucestalije spominje kao ona pomocu koje je moguce predvidjeti razlicite poslovne i životne ishode (Bachman, Stein i Campbell, 2000; Bar-On, 1997; Boyatzis, Goleman i Rhee, 2000). Za njezinu pojavu odgovorni su znanstveni, socijalni, ali i prakticni razlozi, a njihov kombinirani utjecaj doveo je do brojnih kontroverzi oko definiranja, mjerenja i valjanosti EI. Cilj ovoga rada jest operacionalizacija te prikaz metoda mjerenja EI. Iz razloga sto postoje brojne definicije EI koje se grupiraju ovisno o teoretskim modelima važno je njihova mjerenja interpretirati odvojeno. Dva najzastupljenija modela su modeli mentalnih sposobnosti mjereni testovima ucinka i modeli samoprocjene EI koji ukljucuju dvije podvrste: „mijesane modele“ i skale samoprocjene sposobnosti EI po revidiranom modelu Mayera i Saloveya. Valjanost se, eksplicitno ili implicitno, smatra jednom od najvažnijih metrijskih karakteristika mjernog instrumenta. Unatoc tome sto postoje brojni nacini provjere mjeri li zaista test ono sto bi trebao, u slucaju EI najcesce se radi o diskriminantnoj valjanosti. Stoga, kako bi se ispitala konstruktna valjanost, nužno je usporediti razlicite mjere u terminima konvergentne i diskriminantne valjanosti. U svrhu pružanja prikladne mjere takav konstrukt morao bi demonstrirati prediktivnu moc izvan kognitivne inteligencije i petofaktorskog modela. To bi zapravo znacilo da nova varijabla ne bi trebala prejako korelirati s IQ-om ili petofaktorskim modelom, ali, s druge strane, visoko korelirati sa sposobnostima (izvedbom). Prema empirijskim pokazateljima testovi operacionalizirani kao testovi ucinka EI imaju zadovoljavajucu konvergentno-divergentnu valjanost u odnosu na druge mjere inteligencije. Međutim smatra se da samo MSCEIT (Mayer, Salovey, Caruso Emotional Intelligence Tests) mjeri EI u skladu s postavkama konstrukta inteligencije.
Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijsk... more Cilj ovoga istraživanja bio je provjeriti odnos orijentacije na pravdu i percepcije organizacijske pravednosti. Nastojalo se provjeriti faktorsku str
U radu su prikazani teorijski argumenti i empirijske potvrde za ideju i protiv ideje da kognitivn... more U radu su prikazani teorijski argumenti i empirijske potvrde za ideju i protiv ideje da kognitivni procesi (mišljenje, rezoniranje, očekivanje i vjerovanje) ili emocije i motivacija mogu izravno utjecati na i mijenjati sadržaj vida. Prema hipotezi o modularnosti uma i Marrovoj računalnoj teoriji vid je informacijski zatvoren modul s fiksnom, urođenom arhitekturom. Ona se temelji na specifičnim načelima koja su bitno drugačija od općega kognitivnog funkcioniranja. Vid mora biti kognitivno inpenetrabilan zato jer mora stvoriti točnu mentalnu reprezentaciju vanjskog svijeta i time omogućiti jedinki uspješno snalaženje u njemu. Suprotno tome, prema modelu prediktivnog kodiranja, kao suvremenog oblika zagovaranja penetrabilnosti vida, mozak stalno generira predikcije koje olakšavaju i usmjeravaju procesiranje osjetnih informacija i posljedično mijenjaju ono što vidimo. U novije vrijeme mnoga bihevioralna i neuroznanstvena istraživanja pokazuju da se vid doista mijenja pod utjecajem naučenih asocijacija i konteksta kao i socijalne kognicije, motivacije i emocija, što upućuje na zaključak da je vid kognitivno penetrabilan. Međutim, u navedenim su istraživanjima identificirane brojne metodološke i interpretacijske poteškoće iz kojih proizlazi suprotan zaključak. Na kraju, opisani su mogući smjerovi za daljnja teorijska i empirijska istraživanja koja bi nas trebala približiti razrješenju ovoga složenog pitanja.
Incremental grouping is a process entailing serial binding of distal image elements into a unifie... more Incremental grouping is a process entailing serial binding of distal image elements into a unified object representation. At the neural level, incremental grouping involves propagation of the enhanced firing rate among feature-tuned neurons in the early visual cortex. Here, we developed a multi-resolution neural model of incremental grouping. In the model, propagation of the enhanced firing rate is achieved by computing the activity difference between two sets of units: attentional or A-units, whose firing rate is modulated by their horizontal collaterals, and non-attentional or N-units that receive only feedforward input. The activity difference is computed on dendrites that act as independent computational subunits. The proposed model employs multiple spatial scales to account for a variable speed of incremental grouping. In addition, the model incorporates the Ljunction detection network that enables incremental grouping over L-junctions. Computer simulations show that the timing of attentional modulations in the model is comparable with neurophysiological measurements in monkey primary visual cortex.
Incremental grouping is a process entailing serial binding of distal image elements into a unifie... more Incremental grouping is a process entailing serial binding of distal image elements into a unified object representation. At the neural level, incremental grouping involves propagation of the enhanced firing rate among feature-tuned neurons in the early visual cortex. Here, we developed a multi-resolution neural model of incremental grouping. In the model, propagation of the enhanced firing rate is achieved by computing the activity difference between two sets of units: attentional or A-units, whose firing rate is modulated by their horizontal collaterals, and non-attentional or N-units that receive only feedforward input. The activity difference is computed on dendrites that act as independent computational subunits. The proposed model employs multiple spatial scales to account for a variable speed of incremental grouping. In addition, the model incorporates the Ljunction detection network that enables incremental grouping over L-junctions. Computer simulations show that the timing of attentional modulations in the model is comparable with neurophysiological measurements in monkey primary visual cortex.
Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial... more Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial representation, which is termed a Boolean map. It partitions the visual scene into two distinct and complementary regions: selected and not selected. Here, we developed a model of a recurrent competitive network that is capable of state-dependent computation. It selects multiple winning locations based on a joint top-down cue. We augmented a model of the WTA circuit that is based on linear-threshold units with two computational elements: dendritic non-linearity that acts on the excitatory units and activity-dependent modulation of synaptic transmission between excitatory and inhibitory units. Computer simulations showed that the proposed model could create a Boolean map in response to a featured cue and elaborate it using the logical operations of intersection and union. In addition, it was shown that in the absence of top-down guidance, the model is sensitive to bottom-up cues such as saliency and abrupt visual onset.
Neurodynamic Models of Top-Down Effects on Visual Perception, 2022
This doctoral thesis aims to develop new neural network models that will explore how feedback pro... more This doctoral thesis aims to develop new neural network models that will explore how feedback projections in the visual cortex contribute to top-down modulations of visual perception. Two types of top-down effects are considered: 1) Selective visual attention and 2) prior expectations. The models represent modifications and extensions of previously published models of lateral inhibition and adaptive resonance theory. The proposed models are thoroughly evaluated using computer simulations implemented in MATLAB. The models’ outputs are compared with behavioral and neural data. The first part of this thesis develops a model of the recurrent competitive network with the ability to flexibly orient attention in a spatial map to either a single location in space, all locations occupied by an object, or all locations occupied by the feature value. To achieve this property, the network was augmented by biophysically plausible mechanisms emulating properties of synaptic and dendritic computation. The proposed network can simulate object-based attention and implement visual routines, such as mental contour tracing, when further embedded in a more extensive multi-scale neural architecture for boundary detection. The second part of this thesis develops a neural network for color perception based on adaptive resonance theory. The model explains how feedback projections contribute to the stable learning of color codes and conscious experience of colors. The model demonstrates that the same mechanisms that assure learning stability are also responsible for constraining the effect of top-down expectations on color perception. In general, the model indicates that top-down predictions, to a large extent, do not alter the content of conscious visual perception.
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Papers by Mateja Marić
The first part of this thesis develops a model of the recurrent competitive network with the ability to flexibly orient attention in a spatial map to either a single location in space, all locations occupied by an object, or all locations occupied by the feature value. To achieve this property, the network was augmented by biophysically plausible mechanisms emulating properties of synaptic and dendritic computation. The proposed network can simulate object-based attention and implement visual routines, such as mental contour tracing, when further embedded in a more extensive multi-scale neural architecture for boundary detection.
The second part of this thesis develops a neural network for color perception based on adaptive resonance theory. The model explains how feedback projections contribute to the stable learning of color codes and conscious experience of colors. The model demonstrates that the same mechanisms that assure learning stability are also responsible for constraining the effect of top-down expectations on color perception. In general, the model indicates that top-down predictions, to a large extent, do not alter the content of conscious visual perception.