Combined structural and functional imaging reveals cortical deactivations in grapheme-color synaesthesia

An internet-based survey of synesthesia in multiple sclerosis: Incidence, characteristics and implications

Objective Prior work raises the interesting possibility that both multiple sclerosis and synesthesia share a common etiology, that being immune system dysfunction, as well as neuroanatomical and neurochemical abnormalities, including those involving white matter and serotonergic pathways, respectively. Given these links between these two syndromes, we examined the possibility that prevalence of synesthesia would be elevated in a population of individuals with MS, relative to what is thought to be the prevalence in the neurotypical population. It was not known whether synesthesia might be a marker for subsequent development of MS, or if synesthesia might reflect neurological damage resulting from MS disease progression. Method Individuals with self- reported clinically definite MS were recruited online via the internet and social media using sites specifically relevant to the MS community. Data from 147 individuals who completed several questionnaires related to synesthesia were analyzed. Results Depending on criteria, between approximately 7 and 16% of individuals with MS reported synesthesia here. This is an estimated 1.57 to 3.55 times increased incidence of synesthesia here relative to previous findings in neurotypical samples. Limitations of the study include that this was an internet survey, and that synesthesia was not directly assessed in this sample. Conclusions Results suggest a link between the syndromes, primarily indicating that synesthesia may be a marker for subsequent MS development, and the implications and directions for future study are discussed.

Do synaesthesia and mental imagery tap into similar cross-modal processes?

Synaesthesia has previously been linked with imagery abilities, although an understanding of a causal role for mental imagery in broader synaesthetic experiences remains elusive. This can be partly attributed to our relatively poor understanding of imagery in sensory domains beyond vision. Investigations into the neural and behavioural underpinnings of mental imagery have nevertheless identified an important role for imagery in perception, particularly in mediating cross-modal interactions. However, the phenomenology of synaesthesia gives rise to the assumption that associated cross-modal interactions may be encapsulated and specific to synaesthesia. As such, evidence for a link between imagery and perception may not generalize to synaesthesia. Here, we present results that challenge this idea: first, we found enhanced somatosensory imagery evoked by visual stimuli of body parts in mirror-touch synaesthetes, relative to other synaesthetes or controls. Moreover, this enhanced imagery generalized to tactile object properties not directly linked to their synaesthetic associations. Second, we report evidence that concurrent experience evoked in grapheme-colour synaesthesia was sufficient to trigger visual-to-tactile correspondences that are common to all. Together, these findings show that enhanced mental imagery is a consistent hallmark of synaesthesia, and suggest the intriguing possibility that imagery may facilitate the cross-modal interactions that underpin synaesthesic experiences. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'.

Stochastic resonance model of synaesthesia

In synaesthesia, stimulation of one sensory modality evokes additional experiences in another modality (e.g. sounds evoking colours). Along with these cross-sensory experiences, there are several cognitive and perceptual differences between synaesthetes and non-synaesthetes. For example, synaesthetes demonstrate enhanced imagery, increased cortical excitability and greater perceptual sensitivity in the concurrent modality. Previous models suggest that synaesthesia results from increased connectivity between corresponding sensory regions or disinhibited feedback from higher cortical areas. While these models explain how one sense can evoke qualitative experiences in another, they fail to predict the broader phenotype of differences observed in synaesthetes. Here, we propose a novel model of synaesthesia based on the principles of stochastic resonance. Specifically, we hypothesize that synaesthetes have greater neural noise in sensory regions, which allows pre-existing multisensory pathways to elicit supra-threshold activation (i.e. synaesthetic experiences). The strengths of this model are (a) it predicts the broader cognitive and perceptual differences in synaesthetes, (b) it provides a unified framework linking developmental and induced synaesthesias, and (c) it explains why synaesthetic associations are inconsistent at onset but stabilize over time. We review research consistent with this model and propose future studies to test its limits. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'.

Cannabis-induced altered states of consciousness are associated with specific dynamic brain connectivity states

BACKGROUND

Cannabis, and specifically one of its active compounds delta-9-tetrahydrocannabinol in recreational doses, has a variety of effects on cognitive processes. Most studies employ resting state functional magnetic resonance imaging techniques to assess the stationary effects of cannabis and to-date one report addressed the impact of delta-9-tetrahydrocannabinol on the dynamics of whole-brain functional connectivity.

METHODS

Using a repeated-measures, within-subjects design, 19 healthy occasional cannabis users (smoking cannabis ⩽2 per week) underwent resting state functional magnetic resonance imaging scans. Each subject underwent two scans: in the intoxicated condition, shortly after smoking a cannabis cigarette, and in the non-intoxicated condition, with the subject being free from cannabinoids for at least one week before. All sessions were randomized and performed in a four-week interval. Data were analysed employing a standard independent component analysis approach with subsequent tracking of the functional connectivity dynamics, which allowed six connectivity clusters (states) to be individuated.

RESULTS

Using standard independent component analysis in resting state functional connectivity, a group effect was found in the precuneus connectivity. With a dynamic independent component analysis approach, we identified one transient connectivity state, characterized by high connectivity within and between auditory and somato-motor cortices and anti-correlation with subcortical structures and the cerebellum that was only found during the intoxicated condition. Behavioural measures of the subjective experiences of changed perceptions and tetrahydrocannabinol plasma levels during intoxication were associated with this state.

CONCLUSIONS

With the help of the dynamic connectivity approach we could elucidate neural correlates of the transitory perceptual changes induced by delta-9-tetrahydrocannabinol in cannabis users, and possibly identify a biomarker of cannabis intoxication.

MRI Characterizes the Progressive Course of AD and Predicts Conversion to Alzheimer's Dementia 24 Months Before Probable Diagnosis

There is no disease-modifying treatment currently available for AD, one of the more impacting neurodegenerative diseases affecting more than 47.5 million people worldwide. The definition of new approaches for the design of proper clinical trials is highly demanded in order to achieve non-confounding results and assess more effective treatment. In this study, a cohort of 200 subjects was obtained from the Alzheimer's Disease Neuroimaging Initiative. Subjects were followed-up for 24 months, and classified as AD (50), progressive-MCI to AD (50), stable-MCI (50), and cognitively normal (50). Structural T1-weighted MRI brain studies and neuropsychological measures of these subjects were used to train and optimize an artificial-intelligence classifier to distinguish mild-AD patients who need treatment (AD + pMCI) from subjects who do not need treatment (sMCI + CN). The classifier was able to distinguish between the two groups 24 months before AD definite diagnosis using a combination of MRI brain studies and specific neuropsychological measures, with 85% accuracy, 83% sensitivity, and 87% specificity. The combined-approach model outperformed the classification using MRI data alone (72% classification accuracy, 69% sensitivity, and 75% specificity). The patterns of morphological abnormalities localized in the temporal pole and medial-temporal cortex might be considered as biomarkers of clinical progression and evolution. These regions can be already observed 24 months before AD definite diagnosis. The best neuropsychological predictors mainly included measures of functional abilities, memory and learning, working memory, language, visuoconstructional reasoning, and complex attention, with a particular focus on some of the sub-scores of the FAQ and AVLT tests.

Magnetic resonance imaging does not reveal structural alterations in the brain of grapheme-color synesthetes

Several publications have reported structural changes in the brain of synesthetes compared to controls, either local differences or differences in connectivity. In the present study, we pursued this quest for structural brain differences that might support the subjective experience of synesthesia. In particular, for the first time in this field, we investigated brain folding in comparing 45 sulcal shapes in each hemisphere of control and grapheme-color synesthete populations. To overcome flaws relative to data interpretation based only on p-values, common in the synesthesia literature, we report confidence intervals of effect sizes. Moreover, our statistical maps are displayed without introducing the classical, but misleading, p-value level threshold. We adopt such a methodological procedure to facilitate appropriate data interpretation and promote the "New Statistics" approach. Based on structural or diffusion magnetic resonance imaging data, we did not find any strong cerebral anomaly, in sulci, tissue volume, tissue density or fiber organization that could support synesthetic color experience. Finally, by sharing our complete datasets, we strongly support the multi-center construction of a sufficient large dataset repository for detecting, if any, subtle brain differences that may help understanding how a subjective experience, such as synesthesia, is mentally constructed.

The Merit of Synesthesia for Consciousness Research

Synesthesia is a phenomenon in which additional perceptual experiences are elicited by sensory stimuli or cognitive concepts. Synesthetes possess a unique type of phenomenal experiences not directly triggered by sensory stimulation. Therefore, for better understanding of consciousness it is relevant to identify the mental and physiological processes that subserve synesthetic experience. In the present work we suggest several reasons why synesthesia has merit for research on consciousness. We first review the research on the dynamic and rapidly growing field of the studies of synesthesia. We particularly draw attention to the role of semantics in synesthesia, which is important for establishing synesthetic associations in the brain. We then propose that the interplay between semantics and sensory input in synesthesia can be helpful for the study of the neural correlates of consciousness, especially when making use of ambiguous stimuli for inducing synesthesia. Finally, synesthesia-related alterations of brain networks and functional connectivity can be of merit for the study of consciousness.

Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach

Determination of sensitive and specific markers of very early AD progression is intended to aid researchers and clinicians to develop new treatments and monitor their effectiveness, as well as to lessen the time and cost of clinical trials. Magnetic Resonance (MR)-related biomarkers have been recently identified by the use of machine learning methods for the in vivo differential diagnosis of AD. However, the vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will (MCIc) or not convert (MCInc) to AD. Morphological T1-weighted MRIs of 137 AD, 76 MCIc, 134 MCInc, and 162 healthy controls (CN) selected from the Alzheimer's disease neuroimaging initiative (ADNI) cohort, were used by an optimized machine learning algorithm. Voxels influencing the classification between these AD-related pre-clinical phases involved hippocampus, entorhinal cortex, basal ganglia, gyrus rectus, precuneus, and cerebellum, all critical regions known to be strongly involved in the pathophysiological mechanisms of AD. Classification accuracy was 76% AD vs. CN, 72% MCIc vs. CN, 66% MCIc vs. MCInc (nested 20-fold cross validation). Our data encourage the application of computer-based diagnosis in clinical practice of AD opening new prospective in the early management of AD patients.

A critical review of the neuroimaging literature on synesthesia

Synesthesia refers to additional sensations experienced by some people for specific stimulations, such as the systematic arbitrary association of colors to letters for the most studied type. Here, we review all the studies (based mostly on functional and structural magnetic resonance imaging) that have searched for the neural correlates of this subjective experience, as well as structural differences related to synesthesia. Most differences claimed for synesthetes are unsupported, due mainly to low statistical power, statistical errors, and methodological limitations. Our critical review therefore casts some doubts on whether any neural correlate of the synesthetic experience has been established yet. Rather than being a neurological condition (i.e., a structural or functional brain anomaly), synesthesia could be reconsidered as a special kind of childhood memory, whose signature in the brain may be out of reach with present brain imaging techniques.