Revealing voxel correlation cliques by functional holography analysis of fMRI

Jacob, Yael; Rapson, Amir; Kafri, Michal; Baruchi, Itay; Hendler, Talma; Jacob, Eshel Ben

doi:10.1016/j.jneumeth.2010.06.007

Cited by 5 publications

(6 citation statements)

References 46 publications

(58 reference statements)

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“…Although fewer examples of application to the latter are and further investigation of the method on different (viz. event-related) designs is needed, the proposed method shows great potential even for fMRI data in differentiating experimental conditions particularly when the corresponding signals are separated (Jacob et al, 2010). Since the outcome of the analysis is a holographic presentation in an abstract reduced space, it represents an ideal tool for multi-modal analysis of data from experiments combining EEG´s temporal precision with fMRI´s spatial one.…”

Section: Resultsmentioning

confidence: 99%

“…When applied to fMRI data, FH is an effective clustering method, capable of capturing system level networks using voxel-voxel correlation matrices (Jacob et al, 2010). Here we show how the algorithm using a dendrogram clustering method combined with a standard deviation (STD) filter can effectively be used to identify and extract voxel clusters.…”

Section: Analyzing Fmri Recorded Human Brain Activitymentioning

confidence: 99%

See 1 more Smart Citation

Functional Holography and Cliques in Brain Activation Patterns

Jacob¹,

Papo²,

Hendler³

et al. 2012

Advances in Brain Imaging

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Section: Resultsmentioning

confidence: 99%

Section: Analyzing Fmri Recorded Human Brain Activitymentioning

confidence: 99%

Functional Holography and Cliques in Brain Activation Patterns

Jacob¹,

Papo²,

Hendler³

et al. 2012

Advances in Brain Imaging

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“…The rest angle of each piezoelectric device was carefully matched to the resting angle of each whisker. For a detailed description of the 24-whisker stimulator, see the original article ( 8 ). Four different types of stimulation were used in these experiments: POS W , VEL W , ACC W , and sparse noise (one whisker at a time ramp-hold-ramp stimuli).…”

Section: Methodsmentioning

confidence: 99%

“…More recently, improved stimulus control ( 7 , 8 ) across the entire mystacial pad enabled reverse correlation techniques that were developed in the visual and auditory fields ( 9 , 10 ) to be adapted to the whisker system. These approaches are geared toward anesthetized rodents, and rather than exploring the stimulus space one input parameter at a time, they are based on broadband stimulation of the whiskers and analysis of the spike-eliciting stimulus features in small prespike temporal windows.…”

Section: Introductionmentioning

confidence: 99%

An elaborate sweep-stick code in rat barrel cortex

et al. 2020

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In rat barrel cortex, feature encoding schemes uncovered during broadband whisker stimulation are hard to reconcile with the simple stick-slip code observed during natural tactile behaviors, and this has hindered the development of a generalized computational framework. By designing broadband artificial stimuli to sample the inputs encoded under natural conditions, we resolve this disparity while markedly increasing the percentage of deep layer neurons found to encode whisker movements, as well as the diversity of these encoded features. Deep layer neurons encode two main types of events, sticks and sweeps, corresponding to high angular velocity bumps and large angular displacements with high velocity, respectively. Neurons can exclusively encode sticks or sweeps, or they can encode both, with or without direction selectivity. Beyond unifying coding theories from naturalistic and artificial stimulation studies, these findings delineate a simple and generalizable set of whisker movement features that can support a range of perceptual processes.

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“…A data-driven analysis approach, on the other hand, based on clustering algorithms of each individual's brain responses, precludes such previous assumptions. This latter approach has been applied to functional magnetic resonance imaging (fMRI) fine voxel analysis for obtaining distinct brain activity states, which can later be used as regressors for external/behavior state inference (Dodel et al, 2002;Eguiluz et al, 2005;Jacob et al, 2010;Sporns et al, 2000Sporns et al, , 2007Stam and Reijneveld, 2007).…”

Section: Introductionmentioning

confidence: 99%

Functional Cliques in the Amygdala and Related Brain Networks Driven by Fear Assessment Acquired During Movie Viewing

Kinreich

Intrator²,

Hendler³

2011

Brain Connectivity

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One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

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Revealing voxel correlation cliques by functional holography analysis of fMRI

Cited by 5 publications

References 46 publications

Functional Holography and Cliques in Brain Activation Patterns

Functional Holography and Cliques in Brain Activation Patterns

An elaborate sweep-stick code in rat barrel cortex

Functional Cliques in the Amygdala and Related Brain Networks Driven by Fear Assessment Acquired During Movie Viewing

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