Enhanced mental imagery and intact perceptual organization in schizotypal personality disorder

Predicting the subjective intensity of imagined experiences from electrophysiological measures of oscillatory brain activity

Most people can conjure images and sounds that they experience in their minds. There are, however, marked individual differences. Some people report that they cannot generate imagined sensory experiences at all (aphantasics) and others report that they have unusually intense imagined experiences (hyper-phantasics). These individual differences have been linked to activity in sensory brain regions, driven by feedback. We would therefore expect imagined experiences to be associated with specific frequencies of oscillatory brain activity, as these can be a hallmark of neural interactions within and across regions of the brain. Replicating a number of other studies, relative to a Resting-State we find that the act of engaging in auditory or in visual imagery is linked to reductions in the power of oscillatory brain activity across a broad range of frequencies, with prominent peaks in the alpha band (8-12 Hz). This oscillatory activity, however, did not predict individual differences in the subjective intensity of imagined experiences. For audio imagery, these were rather predicted by reductions within the theta (6-9 Hz) and gamma (33-38 Hz) bands, and by increases in beta (15-17 Hz) band activity. For visual imagery these were predicted by reductions in lower (14-16 Hz) and upper (29-32 Hz) beta band activity, and by an increase in mid-beta band (24-26 Hz) activity. Our data suggest that there is sufficient ground truth in the subjective reports people use to describe the intensity of their imagined sensory experiences to allow these to be linked to the power of distinct rhythms of brain activity. In future, we hope to combine this approach with better measures of the subjective intensity of imagined sensory experiences to provide a clearer picture of individual differences in the subjective intensity of imagined experiences, and of why these eventuate.

A generative adversarial model of intrusive imagery in the human brain

The mechanisms underlying the subjective experiences of mental disorders remain poorly understood. This is partly due to long-standing over-emphasis on behavioral and physiological symptoms and a de-emphasis of the patient's subjective experiences when searching for treatments. Here, we provide a new perspective on the subjective experience of mental disorders based on findings in neuroscience and artificial intelligence (AI). Specifically, we propose the subjective experience that occurs in visual imagination depends on mechanisms similar to generative adversarial networks that have recently been developed in AI. The basic idea is that a generator network fabricates a prediction of the world, and a discriminator network determines whether it is likely real or not. Given that similar adversarial interactions occur in the two major visual pathways of perception in people, we explored whether we could leverage this AI-inspired approach to better understand the intrusive imagery experiences of patients suffering from mental illnesses such as post-traumatic stress disorder (PTSD) and acute stress disorder. In our model, a nonconscious visual pathway generates predictions of the environment that influence the parallel but interacting conscious pathway. We propose that in some patients, an imbalance in these adversarial interactions leads to an overrepresentation of disturbing content relative to current reality, and results in debilitating flashbacks. By situating the subjective experience of intrusive visual imagery in the adversarial interaction of these visual pathways, we propose testable hypotheses on novel mechanisms and clinical applications for controlling and possibly preventing symptoms resulting from intrusive imagery.

Definition and attributes of the emotional memory images underlying psychophysiological dis-ease

BACKGROUND

Previously, we proposed a "Split-second Unlearning" model to explain how emotional memories could be preventing clients from adapting to the stressors of daily living, thus forming a barrier to learning, health and well-being. We suggested that these emotional memories were mental images stored inside the mind as 'emotional memory images' (EMIs).

OBJECTIVE

To elaborate on the nature of these emotional memory images within the context of split-second learning and unlearning and the broader field of psychoanalysis, to initiate a conversation among scholars concerning the path that future healthcare research, practice, and policy should take.

METHOD

A narrative review of the attributes of EMIs utilizing relevant and contentious research and/or scholarly publications on the topic, facilitated by observations and approaches used in clinical practice. Results: We propose a refined definition of EMIs as Trauma induced, non-conscious, contiguously formed multimodal mental imagery, which triggers an amnesic, anachronistic, stress response within a split-second. The systematic appraisal of each attribute of an EMI supports the idea that the EMI is distinct from similar entities described in literature, enabling further sophistication of our Split-second Unlearning model of psychophysiological dis-ease.

CONCLUSION

Exploration of the concept of EMIs provides further insight on mechanisms associated with psychophysiological dis-ease and opportunities for therapeutic approaches.

Why do imagery and perception look and feel so different?

Despite the past few decades of research providing convincing evidence of the similarities in function and neural mechanisms between imagery and perception, for most of us, the experience of the two are undeniably different, why? Here, we review and discuss the differences between imagery and perception and the possible underlying causes of these differences, from function to neural mechanisms. Specifically, we discuss the directional flow of information (top-down versus bottom-up), the differences in targeted cortical layers in primary visual cortex and possible different neural mechanisms of modulation versus excitation. For the first time in history, neuroscience is beginning to shed light on this long-held mystery of why imagery and perception look and feel so different. This article is part of the theme issue 'Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.

Aphantasia: The science of visual imagery extremes

Visual imagery allows us to revisit the appearance of things in their absence and to test out virtual combinations of sensory experience. Visual imagery has been linked to many cognitive processes, such as autobiographical and visual working memory. Imagery also plays symptomatic and mechanistic roles in neurologic and mental disorders and is utilized in treatment. A large network of brain activity spanning frontal, parietal, temporal, and visual cortex is involved in generating and maintain images in mind. The ability to visualize has extreme variations, ranging from completely absent (aphantasia) to photo-like (hyperphantasia). The anatomy and functionality of visual cortex, including primary visual cortex, have been associated with individual differences in visual imagery ability, pointing to a potential correlate for both aphantasia and hyperphantasia. Preliminary evidence suggests that lifelong aphantasia is associated with prosopagnosia and reduction in autobiographical memory; hyperphantasia is associated with synesthesia. Aphantasic individuals can also be highly imaginative and are able to complete many tasks that were previously thought to rely on visual imagery, demonstrating that visualization is only one of many ways of representing things in their absence. The study of extreme imagination reminds us how easily invisible differences can escape detection.

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

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 non-imagery 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 approaches and suggest the possibility of a modality-independent imagery-related mechanism. The use of time evolution of temporal complexity in neural decoding might extend our knowledge of the neural bases of hierarchical functions in the human brain.

Early-Stage Vision and Perceptual Imagery in Autism Spectrum Conditions

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.