Enhanced mental imagery and intact perceptual organization in schizotypal personality disorder

Maróthi, Rebeka; Kéri, Szabolcs

doi:10.1016/j.psychres.2017.11.015

Cited by 15 publications

(14 citation statements)

References 40 publications

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“…The imagery condition was matched to the perception condition in task structure and general difficulty, and we made sure during the practice block that individuals with ASC understood the task correctly. Moreover, in our previous study, individuals with schizotypal personality disorder, who often find testing situations very challenging due to their decreased motivation, distractibility, and suspiciousness, exhibited enhanced (more effective) mental imagery relative to control participants, which is against the possibility that the imagery task is more difficult to understand or motivationally more demanding than the perceptual task (Maróthi and Kéri, 2018). Finally, a rating scale for fatigue and motivation did not indicate significant differences between individuals with ASC and healthy control participants.…”

Section: Discussionmentioning

confidence: 90%

“…The procedure was identical to that used in our previous studies (Kéri, 2015; Maróthi and Kéri, 2018), and here we only describe a short summary (Figure 1). We measured contrast threshold for a target Gabor patch when it was flanked by two lateral collinear masks with different target-to-mask distances (perception condition) or when the masks were not physically present, but the participant was instructed to imagine them (imagery condition).…”

Section: Methodsmentioning

confidence: 99%

“…The gamma function of the screen was linearized by using a lookup table. We selected the spatial frequency of the stimuli because it provided a reliable masking effect in our previous studies (Kéri, 2015; Maróthi and Kéri, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…The lateral masking task provides a unique opportunity for the behavioral assessment of bottom-up perception and top-down imagery at the level of the V1 (Ishai and Sagi, 1995; Kéri, 2015; Maróthi and Kéri, 2018; Figure 1). In the perceptual part of the task, participants detect a central low-contrast target (Gabor patch) vertically flanked by two high-contrast masks.…”

Section: Introductionmentioning

confidence: 99%

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Early-Stage Vision and Perceptual Imagery in Autism Spectrum Conditions

Maróthi

Csigó

Kéri

2019

Front. Hum. Neurosci.

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Autism spectrum conditions (ASC) are characterized by multifaceted alterations in visual perception and mental imagery. However, the interaction between early-stage visual perception and imagery has not been explored. We recruited 40 individuals with ASC and 20 neurotypical control volunteers to participate in a lateral masking task. Participants detected a luminance-contrast target pattern (Gabor patch) flanked by two collinear masks. The flanking masks inhibit target detection at small target-mask distances and facilitate target detection at intermediate target-mask distances. In the perceptual task, the masks appeared adjacent to the target. In the imagery task, participants imagined the masks immediately after seeing them. Results revealed that individuals with ASC characterized by exceptional visuoconstructional abilities (enhanced Block Design performance; n = 20) showed weaker inhibition at small target-mask distances and stronger facilitation at intermediate target-mask distances relative to the controls. Visual imagery was markedly dampened in ASC regardless of the visuoconstructional abilities. At the behavioral level, these results indicate increased facilitation via lateral connections in the primary visual cortex (V1) of individuals with ASC who exhibit exceptional visuoconstructional abilities, together with less efficient mental imagery.

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Section: Discussionmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Early-Stage Vision and Perceptual Imagery in Autism Spectrum Conditions

Maróthi

Csigó

Kéri

2019

Front. Hum. Neurosci.

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“…Mental imagery involves modality-specific regions and modalityindependent top-down inputs (38,42,(47)(48)(49)(50)71). It has a multifaceted relation to psychiatric disorders related to patient abilities, symptoms and treatments (3,(36)(37)(38)72). For this study, we used complexity analysis to examine neural oscillations that occur during mental imagery.…”

Section: Discussionmentioning

confidence: 99%

Neural Decoding of Multi-Modal Imagery Behavior Focusing on Temporal Complexity

et al. 2020

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Mental imagery behaviors of various modalities include visual, auditory, and motor behaviors. Their alterations are pathologically involved in various psychiatric disorders. Results of earlier studies suggest that imagery behaviors are correlated with the modulated activities of the respective modality-specific regions and the additional activities of supramodal imagery-related regions. Additionally, despite the availability of complexity analysis in the neuroimaging field, it has not been used for neural decoding approaches. Therefore, we sought to characterize neural oscillation related to multimodal imagery through complexity-based neural decoding. For this study, we modified existing complexity measures to characterize the time evolution of temporal complexity. We took magnetoencephalography (MEG) data of eight healthy subjects as they performed multimodal imagery and non-imagery tasks. The MEG data were decomposed into amplitude and phase of sub-band frequencies by Hilbert-Huang transform. Subsequently, we calculated the complexity values of each reconstructed time series, along with raw data and band power for comparison, and applied these results as inputs to decode visual perception (VP), visual imagery (VI), motor execution (ME), and motor imagery (MI) functions. Consequently, intra-subject decoding with the complexity yielded a characteristic sensitivity map for each task with high decoding accuracy. The map is inverted in the occipital regions between VP and VI and in the central regions between ME and MI. Additionally, replacement of the labels into two classes as imagery and nonimagery also yielded better classification performance and characteristic sensitivity with the complexity. It is particularly interesting that some subjects showed characteristic sensitivities not only in modality-specific regions, but also in supramodal regions. These analyses indicate that two-class and four-class classifications each provided better performance when using complexity than when using raw data or band power as input. When inter-subject decoding was used with the same model, characteristic sensitivity maps were also obtained, although their decoding performance was lower. Results of this study underscore the availability of complexity measures in neural decoding

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