Dynamic causal modeling for calcium imaging data reveals differential effective connectivity for sensory processing in a barrel cortical column

AbstractMulti-photon calcium imaging (CaI) is an important tool to assess activity among neural populations within a column in the sensory cortex. However, the complex asymmetrical interactions among neural populations, termed effective connectivity, cannot be directly assessed by measuring the activity of each neuron using CaI but calls for computational modeling. To estimate effective connectivity among neural populations, we proposed a dynamic causal model (DCM) for CaI by combining a convolution-based dynamic neural state model and a dynamic calcium ion concentration model for CaI signals. After conducting a simulation study to evaluate DCM for CaI, we applied it to an experimental CaI data measured at the layer 2/3 of a barrel cortical column that differentially responds to hit and error whisking trails in mice. We first identified neural populations and constructed computational models with intrinsic connectivity of neural populations within the layer 2/3 of the barrel cortex and extrinsic connectivity with latent external modes. Bayesian model inversion and comparison shows that a top-down model with latent inhibitory and excitatory external modes explains the observed CaI signals during hit and error trials better than any other model, with a single external mode or without any latent modes. The best model also showed differential intrinsic and extrinsic effective connectivity between hit and error trials (corresponding to the bottom-up and top-down processes) in the functional hierarchical architecture. Both simulation and experimental results suggest the usefulness of DCM for CaI in terms of exploration of the hierarchical interactions among neural populations observed in CaI.

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Dynamic causal modeling for calcium imaging: Exploration of differential effective connectivity for sensory processing in a barrel cortical column

NeuroImage ◽

10.1016/j.neuroimage.2019.116008 ◽

2019 ◽

Vol 201 ◽

pp. 116008 ◽

Cited By ~ 1

Author(s):

Kyesam Jung ◽

Jiyoung Kang ◽

Seungsoo Chung ◽

Hae-Jeong Park

Keyword(s):

Sensory Processing ◽

Calcium Imaging ◽

Effective Connectivity ◽

Causal Modeling ◽

Cortical Column ◽

Dynamic Causal Modeling

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Looking from the top: enhanced top-down sensorimotor processing in somatic anxiety

10.1101/2021.12.02.471029 ◽

2021 ◽

Author(s):

Ismail Bouziane ◽

Moumita Das ◽

Cesar Caballero-Gaudes ◽

Dipanjan Ray

Keyword(s):

Empirical Bayes ◽

Hierarchical Modeling ◽

Functional Neuroimaging ◽

Effective Connectivity ◽

Causal Modeling ◽

Cortical Processing ◽

Top Down ◽

Somatic Anxiety ◽

Novel Approach ◽

Human Connectome Project

AbstractBackgroundFunctional neuroimaging research on anxiety has traditionally focused on brain networks associated with the complex psychological aspects of anxiety. In this study, instead, we target the somatic aspects of anxiety. Motivated by the growing recognition that top-down cortical processing plays crucial roles in perception and action, we investigate effective connectivity among hierarchically organized sensorimotor regions and its association with (trait) anxiety.MethodsWe selected 164 participants from the Human Connectome Project based on psychometric measures. We used their resting-state functional MRI data and Dynamic Causal Modeling (DCM) to assess effective connectivity within and between key regions in the exteroceptive, interoceptive, and motor hierarchy. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes we first established the architecture of effective connectivity in sensorimotor networks and investigated its association with fear somatic arousal (FSA) and fear affect (FA) scores. To probe the robustness of our results, we implemented a leave-one-out cross validation analysis.ResultsAt the group level, the top-down connections in exteroceptive cortices were inhibitory in nature whereas in interoceptive and motor cortices they were excitatory. With increasing FSA scores, the pattern of top-down effective connectivity was enhanced in all three networks: an observation that corroborates well with anxiety phenomenology. Anxiety associated changes in effective connectivity were of effect size sufficiently large to predict whether somebody has mild or severe somatic anxiety. Interestingly, the enhancement in top-down processing in sensorimotor cortices were associated with FSA but not FA scores, thus establishing the (relative) dissociation between somatic and cognitive dimensions of anxiety.ConclusionsOverall, enhanced top-down effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of trait somatic anxiety. These results pave the way for a novel approach into investigating the neural underpinnings of anxiety based on the recognition of anxiety as an embodied phenomenon and the emerging interest in top-down cortical processing.

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The Role of Unimodal Feedback Pathways in Gender Perception During Activation of Voice and Face Areas

Frontiers in Systems Neuroscience ◽

10.3389/fnsys.2021.669256 ◽

2021 ◽

Vol 15 ◽

Author(s):

Clement Abbatecola ◽

Peggy Gerardin ◽

Kim Beneyton ◽

Henry Kennedy ◽

Kenneth Knoblauch

Keyword(s):

Imaging Techniques ◽

Effective Connectivity ◽

Causal Modeling ◽

Conjoint Measurement ◽

Top Down ◽

Model Framework ◽

Face Area ◽

Gender Perception ◽

The Face ◽

Feedback Pathways

Cross-modal effects provide a model framework for investigating hierarchical inter-areal processing, particularly, under conditions where unimodal cortical areas receive contextual feedback from other modalities. Here, using complementary behavioral and brain imaging techniques, we investigated the functional networks participating in face and voice processing during gender perception, a high-level feature of voice and face perception. Within the framework of a signal detection decision model, Maximum likelihood conjoint measurement (MLCM) was used to estimate the contributions of the face and voice to gender comparisons between pairs of audio-visual stimuli in which the face and voice were independently modulated. Top–down contributions were varied by instructing participants to make judgments based on the gender of either the face, the voice or both modalities (N = 12 for each task). Estimated face and voice contributions to the judgments of the stimulus pairs were not independent; both contributed to all tasks, but their respective weights varied over a 40-fold range due to top–down influences. Models that best described the modal contributions required the inclusion of two different top–down interactions: (i) an interaction that depended on gender congruence across modalities (i.e., difference between face and voice modalities for each stimulus); (ii) an interaction that depended on the within modalities’ gender magnitude. The significance of these interactions was task dependent. Specifically, gender congruence interaction was significant for the face and voice tasks while the gender magnitude interaction was significant for the face and stimulus tasks. Subsequently, we used the same stimuli and related tasks in a functional magnetic resonance imaging (fMRI) paradigm (N = 12) to explore the neural correlates of these perceptual processes, analyzed with Dynamic Causal Modeling (DCM) and Bayesian Model Selection. Results revealed changes in effective connectivity between the unimodal Fusiform Face Area (FFA) and Temporal Voice Area (TVA) in a fashion that paralleled the face and voice behavioral interactions observed in the psychophysical data. These findings explore the role in perception of multiple unimodal parallel feedback pathways.

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Voice and Face Gender Perception engages multimodal integration via multiple feedback pathways

10.1101/2020.01.07.884668 ◽

2020 ◽

Author(s):

Clement Abbatecola ◽

Kim Beneyton ◽

Peggy Gerardin ◽

Henry Kennedy ◽

Kenneth Knoblauch

Keyword(s):

Effective Connectivity ◽

Causal Modeling ◽

Conjoint Measurement ◽

Auditory Modality ◽

Multimodal Integration ◽

Hierarchical Systems ◽

Top Down ◽

Face Area ◽

Gender Perception ◽

Gender Information

AbstractMultimodal integration provides an ideal framework for investigating top-down influences in perceptual integration. Here, we investigate mechanisms and functional networks participating in face-voice multimodal integration during gender perception by using complementary behavioral (Maximum Likelihood Conjoint Measurement) and brain imaging (Dynamic Causal Modeling of fMRI data) techniques. Thirty-six subjects were instructed to judge pairs of face-voice stimuli either according to the gender of the face (face task), the voice (voice task) or the stimulus (stimulus task; no specific modality instruction given). Face and voice contributions to the tasks were not independent, as both modalities significantly contributed to all tasks. The top-down influences in each task could be modeled as a differential weighting of the contributions of each modality with an asymmetry in favor of the auditory modality in terms of magnitude of the effect. Additionally, we observed two independent interaction effects in the decision process that reflect both the coherence of the gender information across modalities and the magnitude of the gender difference from neutral. In a second experiment we investigated with functional MRI the modulation of effective connectivity between the Fusiform Face Area (FFA) and the Temporal Voice Area (TVA), two cortical areas implicated in face and voice processing. Twelve participants were presented with multimodal face-voice stimuli and instructed to attend either to face, voice or any gender information. We found specific changes in effective connectivity between these areas in the same conditions that generated behavioral interactions. Taken together, we interpret these results as converging evidence supporting the existence of multiple parallel hierarchical systems in multi-modal integration.

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Effective connectivity decreases in specific brain networks with postparalysis facial synkinesis: a dynamic causal modeling study

Brain Imaging and Behavior ◽

10.1007/s11682-021-00547-z ◽

2021 ◽

Author(s):

Zhen-Zhen Ma ◽

Ye-Chen Lu ◽

Jia-Jia Wu ◽

Xu-Yun Hua ◽

Si-Si Li ◽

...

Keyword(s):

Effective Connectivity ◽

Brain Networks ◽

Causal Modeling ◽

Dynamic Causal Modeling ◽

Facial Synkinesis ◽

Modeling Study

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Altered Prefrontal–Basal Ganglia Effective Connectivity in Patients With Poststroke Cognitive Impairment

Frontiers in Neurology ◽

10.3389/fneur.2020.577482 ◽

2020 ◽

Vol 11 ◽

Author(s):

Jing Zhang ◽

Zixiao Li ◽

Xingxing Cao ◽

Lijun Zuo ◽

Wei Wen ◽

...

Keyword(s):

Cognitive Impairment ◽

Basal Ganglia ◽

Cognitive Decline ◽

Effective Connectivity ◽

Network Connectivity ◽

Brain Regions ◽

Neuronal Model ◽

Causal Modeling ◽

Healthy Controls

We investigated the association between poststroke cognitive impairment and a specific effective network connectivity in the prefrontal–basal ganglia circuit. The resting-state effective connectivity of this circuit was modeled by employing spectral dynamic causal modeling in 11 poststroke patients with cognitive impairment (PSCI), 8 poststroke patients without cognitive impairment (non-PSCI) at baseline and 3-month follow-up, and 28 healthy controls. Our results showed that different neuronal models of effective connectivity in the prefrontal–basal ganglia circuit were observed among healthy controls, non-PSCI, and PSCI patients. Additional connected paths (extra paths) appeared in the neuronal models of stroke patients compared with healthy controls. Moreover, changes were detected in the extra paths of non-PSCI between baseline and 3-month follow-up poststroke, indicating reorganization in the ipsilesional hemisphere and suggesting potential compensatory changes in the contralesional hemisphere. Furthermore, the connectivity strengths of the extra paths from the contralesional ventral anterior nucleus of thalamus to caudate correlated significantly with cognitive scores in non-PSCI and PSCI patients. These suggest that the neuronal model of effective connectivity of the prefrontal–basal ganglia circuit may be sensitive to stroke-induced cognitive decline, and it could be a biomarker for poststroke cognitive impairment 3 months poststroke. Importantly, contralesional brain regions may play an important role in functional compensation of cognitive decline.

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Fiber photometry does not reflect spiking activity in the striatum

10.1101/2021.01.20.427525 ◽

2021 ◽

Author(s):

Alex A. Legaria ◽

Julia A. Licholai ◽

Alexxai V. Kravitz

Keyword(s):

Neuronal Activity ◽

Calcium Imaging ◽

Brain Activity ◽

Neural Population ◽

Fluorescence Signal ◽

Calcium Signals ◽

Cellular Events ◽

Neural Populations ◽

Spiking Activity

AbstractFiber photometry recordings are commonly used as a proxy for neuronal activity, based on the assumption that increases in bulk calcium fluorescence reflect increases in spiking of the underlying neural population. However, this assumption has not been adequately tested. Here, using endoscopic calcium imaging in the striatum we report that the bulk fluorescence signal correlates weakly with somatic calcium signals, suggesting that this signal does not reflect spiking activity, but may instead reflect subthreshold changes in neuropil calcium. Consistent with this suggestion, the bulk fluorescence photometry signal correlated strongly with neuropil calcium signals extracted from these same endoscopic recordings. We further confirmed that photometry did not reflect striatal spiking activity with simultaneous in vivo extracellular electrophysiology and fiber photometry recordings in awake behaving mice. We conclude that the fiber photometry signal should not be considered a proxy for spiking activity in neural populations in the striatum.Significance statementFiber photometry is a technique for recording brain activity that has gained popularity in recent years due to it being an efficient and robust way to record the activity of genetically defined populations of neurons. However, it remains unclear what cellular events are reflected in the photometry signal. While it is often assumed that the photometry signal reflects changes in spiking of the underlying cell population, this has not been adequately tested. Here, we processed calcium imaging recordings to extract both somatic and non-somatic components of the imaging field, as well as a photometry signal from the whole field. Surprisingly, we found that the photometry signal correlated much more strongly with the non-somatic than the somatic signals. This suggests that the photometry signal most strongly reflects subthreshold changes in calcium, and not spiking. We confirmed this point with simultaneous fiber photometry and extracellular spiking recordings, again finding that photometry signals relate poorly to spiking in the striatum. Our results may change interpretations of studies that use fiber photometry as an index of spiking output of neural populations.

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Dynamic causal modeling of load-dependent modulation of effective connectivity within the verbal working memory network

Human Brain Mapping ◽

10.1002/hbm.22382 ◽

2013 ◽

Vol 35 (7) ◽

pp. 3025-3035 ◽

Cited By ~ 34

Author(s):

Danai Dima ◽

Jigar Jogia ◽

Sophia Frangou

Keyword(s):

Working Memory ◽

Effective Connectivity ◽

Verbal Working Memory ◽

Causal Modeling ◽

Dynamic Causal Modeling ◽

Memory Network

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Effective connectivity changes in LSD-induced altered states of consciousness in humans

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1815129116 ◽

2019 ◽

Vol 116 (7) ◽

pp. 2743-2748 ◽

Cited By ~ 32

Author(s):

Katrin H. Preller ◽

Adeel Razi ◽

Peter Zeidman ◽

Philipp Stämpfli ◽

Karl J. Friston ◽

...

Keyword(s):

Ventral Striatum ◽

Effective Connectivity ◽

Cingulate Cortex ◽

Receptor Activation ◽

Posterior Cingulate Cortex ◽

Causal Modeling ◽

Acute Administration ◽

Serotonin 2A Receptor ◽

Posterior Cingulate ◽

Serotonin 2A

Psychedelics exert unique effects on human consciousness. The thalamic filter model suggests that core effects of psychedelics may result from gating deficits, based on a disintegration of information processing within cortico–striato–thalamo-cortical (CSTC) feedback loops. To test this hypothesis, we characterized changes in directed (effective) connectivity between selected CTSC regions after acute administration of lysergic acid diethylamide (LSD), and after pretreatment with Ketanserin (a selective serotonin 2A receptor antagonist) plus LSD in a double-blind, randomized, placebo-controlled, cross-over study in 25 healthy participants. We used spectral dynamic causal modeling (DCM) for resting-state fMRI data. Fully connected DCM models were specified for each treatment condition to investigate the connectivity between the following areas: thalamus, ventral striatum, posterior cingulate cortex, and temporal cortex. Our results confirm major predictions proposed in the CSTC model and provide evidence that LSD alters effective connectivity within CSTC pathways that have been implicated in the gating of sensory and sensorimotor information to the cortex. In particular, LSD increased effective connectivity from the thalamus to the posterior cingulate cortex in a way that depended on serotonin 2A receptor activation, and decreased effective connectivity from the ventral striatum to the thalamus independently of serotonin 2A receptor activation. Together, these results advance our mechanistic understanding of the action of psychedelics in health and disease. This is important for the development of new pharmacological therapeutics and also increases our understanding of the mechanisms underlying the potential clinical efficacy of psychedelics.

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