scholarly journals Distinct effects of amyloid and tau deposition on eigenvector centrality during hippocampal down-regulation: a real-time fMRI virtual reality closed-loop neurofeedback study with CSF biomarkers

2019 ◽  
Author(s):  
Stavros Skouras ◽  
Jordi Torner ◽  
Patrik Andersson ◽  
Yury Koush ◽  
Carles Falcon ◽  
...  
Keyword(s):  
At Risk ◽  
Real Time ◽  
Somatosensory Cortex ◽  
Resting State ◽  
Closed Loop ◽  
Self Regulation ◽  
Primary Somatosensory Cortex ◽  
Csf Biomarkers ◽  
Eigenvector Centrality ◽  
Down Regulation

AbstractHippocampal down-regulation is associated with genetic predisposition to Alzheimer’s disease (AD), neurodevelopmental processes and disease symptoms. Resting state eigenvector centrality (EC) patterns resemble those of FDG-PET in AD, they can predict self-regulation performance and they are related to functional compensation across the pathophysiological continuum of AD. We acquired cerebrospinal fluid (CSF) biomarkers from a cognitively unimpaired sample at risk for AD (N=48), to investigate the effect of β- amyloid peptide 42 (Aβ42) and phosphorylated tau (p-Tau) levels on EC during the down-regulation of hippocampal subfield cornu ammonis 1, with real-time fMRI closed-loop neurofeedback. Controlling the effects of confounding variables (age, sex, number of APOE ε4 alleles, cognitive reserve, brain reserve and hippocampal down-regulation performance), CSF Aβ42 levels correlated positively with EC in the anterior cingulate cortex (BA24, BA32) and primary motor cortex (BA4). CSF p-Tau levels correlated with EC positively in the ACC (BA32, BA10) ventral striatum (caudate, nucleus accumbens, putamen) and left primary somatosensory cortex (BA2), as well as negatively in the posterior cingulate cortex, precuneus, cuneus and left frontal pole (BA9). Controlling for CSF biomarkers and other prognosis variables, age correlated negatively with EC in the midcingulate cortex, insula, primary somatosensory cortex (BA2) and inferior parietal lobule (BA40), as well as positively with EC in the inferior temporal gyri. Taken together, we identified patterns of functional connectomics in individuals at risk of AD during hippocampal down-regulation, which resemble those found during resting state at advanced AD stages. Moreover, we provide a standard paradigm to replicate and extend this work on a global level. This opens new avenues for further research applications, which quantify and monitor disease progression, by identifying early alterations in the self-regulation of brain function, with potential for non-invasive prognostic screening.HighlightsACC centrality decreases with early Aβ42ACC centrality increases with p-TauPCC centrality decreases with p-TauMCC centrality decreases in healthy aging

scholarly journals The effect of APOE genotype and streamline density volume, on hippocampal CA1 down-regulation: a real-time fMRI virtual reality neurofeedback study

2019 ◽  
Author(s):  
Stavros Skouras ◽  
Jordi Torner ◽  
Patrik Anderson ◽  
Yury Koush ◽  
Carles Falcon ◽  
...  
Keyword(s):  
At Risk ◽  
Virtual Reality ◽  
Real Time ◽  
Memory Performance ◽  
Self Regulation ◽  
Apoe Genotype ◽  
List Type ◽  
Down Regulation ◽  
Apoe Ε4 ◽  
Hippocampal Ca1

AbstractHippocampal hyperactivity is a precursor of Alzheimer’s disease and more prominent in APOE-ε4 carriers. It is therefore important to investigate the processes of hippocampal self-regulation, to monitor therapeutic efficacy of preclinical interventions. We have developed a closed-loop, virtual reality neurofeedback paradigm for real-time fMRI, that provides a standardized method for quantifying processes of hippocampal self-regulation. We acquired multi-modal neuroimaging data from a sample of 53 cognitively unimpaired subjects at risk for AD and applied standard methods of structural and functional connectomics. The analyses reveal significant negative associations between hippocampal CA1 down-regulation performance and APOE-ε4 alleles, as well as hippocampal streamline density volume. Better memory performance was associated with increased, bilateral hippocampal functional connectivity during the neurofeedback task. These are the first results to link neurofeedback performance to a genetic risk factor and structural connectivity. Further, these are the first evidence that functional cohesion between the hippocampi can reflect subtle differences in memory function, in cognitively unimpaired individuals at risk for AD. We provide a novel method to assess hippocampal function in preclinical AD, and propose it can be used to derive proxies for neural reserve.HighlightsAPOE-ε4 alleles impact hippocampal down-regulation neurofeedback performance.Hippocampal streamline density volume is associated with decreased hippocampal down-regulation performance.Bilaterally cohesive hippocampal activity is associated with better memory performance.We provide a novel paradigm to investigate self-regulation and brain function.

scholarly journals Palm-to-finger cortical functional interactions in primary somatosensory cortex: a 7T fMRI study

2020 ◽  
Author(s):  
Michel Akselrod ◽  
Roberto Martuzzi ◽  
Wietske van der Zwaag ◽  
Olaf Blanke ◽  
Andrea Serino
Keyword(s):  
Somatosensory Cortex ◽  
Resting State ◽  
Primary Somatosensory Cortex ◽  
Spatial Proximity ◽  
Single Subject ◽  
Functional Interactions ◽  
Somatotopic Organization ◽  
Pattern Similarity ◽  
Resting State Connectivity ◽  
7T Fmri

ABSTRACTMany studies focused on the cortical representations of fingers, while the palm is relatively neglected despite its importance for hand function. Here, we investigated palm representation (PR) and its interactions with finger representations (FRs) in primary somatosensory cortex (S1). Few studies in humans suggested that PR is located medially with respect to FRs in S1, yet to date, no study directly quantified the somatotopic organization of PR and the five FRs. Importantly, the relationship between the somatotopic organization and the cortical functional interactions between PR and FRs remains largely unexplored. Using 7T fMRI, we mapped PR and the five FRs at the single subject level. First, we analyzed the cortical distance between PR and FRs to determine their somatotopic organization. Results show that the PR was located medially with respect to D5. Second, we tested whether the observed cortical distances would predict palm-finger functional interactions. Using three complementary measures of functional interactions (co-activations, pattern similarity and resting-state connectivity), we show that palm-finger functional interactions were not determined by their somatotopic organization, that is, there was no gradient moving from D5 to D1, except for resting-state connectivity, which was predicted by the somatotopy. Instead, we show that the representational geometry of palm-finger functional interactions reflected the physical structure of the hand. Collectively, our findings suggest that the spatial proximity between topographically organized neuronal populations do not necessarily predicts their functional interactions, rather the structure of the sensory space (e.g. the hand shape) better predicts the observed functional interactions.

scholarly journals Cortical closed-loop brain-machine interface requires biomimetic sensory feedback

2019 ◽  
Author(s):  
A. Abbasi ◽  
L. Estebanez ◽  
D. Goueytes ◽  
H. Lassagne ◽  
D. E. Shulz ◽  
...  
Keyword(s):  
Somatosensory Cortex ◽  
Sensory Feedback ◽  
Closed Loop ◽  
The Body ◽  
Primary Somatosensory Cortex ◽  
Fine Motor ◽  
Brain Machine Interface ◽  
Motor Circuits ◽  
Machine Interface ◽  
The Rich

SummaryNew and improved neuroprosthetics offer great hope for motor-impaired human patients to regain autonomy. One obstacle facing current technologies is that fine motor control requires near-instantaneous somatosensory feedback. The way forward is to artificially recreate the rich, distributed feedback generated by natural movements. Here, we hypothesize that incoming sensory feedback needs to follow biomimetic rules in order to be efficiently integrated by motor circuits. We have developed a rodent closed-loop brain-machine interface where head-fixed mice were trained to control a virtual cursor by modulating the activity of motor cortex neurons. Artificial feedback consisting of precise optogenetic stimulation patterns in the primary somatosensory cortex coupled to the motor cortical activity was provided online to the animal. We found that learning occurred only when the feedback had a topographically biomimetic structure. Shuffling the spatiotemporal organization of the feedback prevented learning the task. These results suggest that the patterns of inputs that are structured by the body map present in the primary somatosensory cortex of all mammals are essential for sensorimotor processing and constitute a backbone that needs to be considered when optimizing artificial sensory feedback for fine neuroprosthetic control.

scholarly journals The effects of psychiatric history and age on self-regulation of the default mode network

2018 ◽  
Author(s):  
Stavros Skouras ◽  
Frank Scharnowski
Keyword(s):  
Real Time ◽  
Default Mode Network ◽  
Human Subjects ◽  
Brain Activity ◽  
Self Regulation ◽  
Control Group ◽  
Psychiatric History ◽  
Down Regulation ◽  
Default Mode ◽  
The Relationship

AbstractReal-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using open-access analyses and real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N=136), we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (na=74) and a healthy control group (nb=62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls.

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