scholarly journals The Functional Network of the Visual Cortex Is Altered in Migraine

Vision ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 57
Author(s):  
Jie Huang ◽  
Arnold Wilkins
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Neural Activity ◽  
Neurological Disorder ◽  
Migraine Headache ◽  
Visual Stimulation ◽  
Data Driven ◽  
Functional Network ◽  
Healthy Control ◽  
Patients Experience

Migraine is a common neurological disorder characterized by recurrent episodes of headache, frequently accompanied by various reversible neurological disturbances. Some migraine patients experience visually triggered migraine headache, and most attacks of migraine with aura are associated with the disturbance of vision and photophobia, suggesting an abnormal neural activity in the visual cortex. Numerous studies have shown a large cortical hemodynamic response to visual stimulation and an altered intrinsic visual functional connectivity network in patients with migraine. In this interictal study, we applied a novel data-driven method with fMRI to identify the functional network in the visual cortex evoked by visual stimulation and investigated the effect of migraine on this network. We found that the distribution of the functional network along both the ventral and dorsal visual pathways differed between migraine patients and non-headache healthy control participants, providing evidence that the functional network was altered in migraine between headaches. The functional network was bilateral in the control participants but substantially lateralized in the migraine patients. The results also indicated different effects of colored lenses on the functional network for both participant groups.

scholarly journals Induced cortical oscillations in turtle cortex are coherent at the mesoscale of population activity, but not at the microscale of the membrane potential of neurons

2017 ◽  
Vol 118 (5) ◽  
pp. 2579-2591 ◽  
Author(s):  
Mahmood S. Hoseini ◽  
Jeff Pobst ◽  
Nathaniel Wright ◽  
Wesley Clawson ◽  
Woodrow Shew ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Membrane Potential ◽  
Neural Activity ◽  
Visual Stimulation ◽  
Field Potential ◽  
Brain Regions ◽  
Large Trial ◽  
Population Activity ◽  
Potential Oscillations ◽  
Time Frequency

Bursts of oscillatory neural activity have been hypothesized to be a core mechanism by which remote brain regions can communicate. Such a hypothesis raises the question to what extent oscillations are coherent across spatially distant neural populations. To address this question, we obtained local field potential (LFP) and membrane potential recordings from the visual cortex of turtle in response to visual stimulation of the retina. The time-frequency analysis of these recordings revealed pronounced bursts of oscillatory neural activity and a large trial-to-trial variability in the spectral and temporal properties of the observed oscillations. First, local bursts of oscillations varied from trial to trial in both burst duration and peak frequency. Second, oscillations of a given recording site were not autocoherent; i.e., the phase did not progress linearly in time. Third, LFP oscillations at spatially separate locations within the visual cortex were more phase coherent in the presence of visual stimulation than during ongoing activity. In contrast, the membrane potential oscillations from pairs of simultaneously recorded pyramidal neurons showed smaller phase coherence, which did not change when switching from black screen to visual stimulation. In conclusion, neuronal oscillations at distant locations in visual cortex are coherent at the mesoscale of population activity, but coherence is largely absent at the microscale of the membrane potential of neurons. NEW & NOTEWORTHY Coherent oscillatory neural activity has long been hypothesized as a potential mechanism for communication across locations in the brain. In this study we confirm the existence of coherent oscillations at the mesoscale of integrated cortical population activity. However, at the microscopic level of neurons, we find no evidence for coherence among oscillatory membrane potential fluctuations. These results raise questions about the applicability of the communication through coherence hypothesis to the level of the membrane potential.

scholarly journals Clustering of Multiple Psychiatric Disorders Using Functional Connectivity in the Data-Driven Brain Subnetwork

2021 ◽  
Vol 12 ◽  
Author(s):  
Tomoki Tokuda ◽  
Okito Yamashita ◽  
Yuki Sakai ◽  
Junichiro Yoshimoto
Keyword(s):  
Functional Connectivity ◽  
Psychiatric Disorders ◽  
Autism Spectrum ◽  
Data Driven ◽  
New Paradigm ◽  
Resting State Functional Connectivity ◽  
Major Depressive ◽  
Label Information ◽  
Healthy Control ◽  
Diagnostic Label

Recently, the dimensional approach has attracted much attention, bringing a paradigm shift to a continuum of understanding of different psychiatric disorders. In line with this new paradigm, we examined whether there was common functional connectivity related to various psychiatric disorders in an unsupervised manner without explicitly using diagnostic label information. To this end, we uniquely applied a newly developed network-based multiple clustering method to resting-state functional connectivity data, which allowed us to identify pairs of relevant brain subnetworks and subject cluster solutions accordingly. Thus, we identified four subject clusters, which were characterized as major depressive disorder (MDD), young healthy control (young HC), schizophrenia (SCZ)/bipolar disorder (BD), and autism spectrum disorder (ASD), respectively, with the relevant brain subnetwork represented by the cerebellum-thalamus-pallidum-temporal circuit. The clustering results were validated using independent datasets. This study is the first cross-disorder analysis in the framework of unsupervised learning of functional connectivity based on a data-driven brain subnetwork.

scholarly journals Naturalistic Spike Trains Drive State-Dependent Homeostatic Plasticity in Superficial Layers of Visual Cortex

2021 ◽  
Vol 13 ◽  
Author(s):  
Varun Chokshi ◽  
Bryce D. Grier ◽  
Andrew Dykman ◽  
Crystal L. Lantz ◽  
Ernst Niebur ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Neural Activity ◽  
Visual Stimulation ◽  
Average Frequency ◽  
Spike Trains ◽  
Homeostatic Plasticity ◽  
Excitatory Synapses ◽  
Rapid Reduction ◽  
History Of

The history of neural activity determines the synaptic plasticity mechanisms employed in the brain. Previous studies report a rapid reduction in the strength of excitatory synapses onto layer 2/3 (L2/3) pyramidal neurons of the primary visual cortex (V1) following two days of dark exposure and subsequent re-exposure to light. The abrupt increase in visually driven activity is predicted to drive homeostatic plasticity, however, the parameters of neural activity that trigger these changes are unknown. To determine this, we first recorded spike trains in vivo from V1 layer 4 (L4) of dark exposed (DE) mice of both sexes that were re-exposed to light through homogeneous or patterned visual stimulation. We found that delivering the spike patterns recorded in vivo to L4 of V1 slices was sufficient to reduce the amplitude of miniature excitatory postsynaptic currents (mEPSCs) of V1 L2/3 neurons in DE mice, but not in slices obtained from normal reared (NR) controls. Unexpectedly, the same stimulation pattern produced an up-regulation of mEPSC amplitudes in V1 L2/3 neurons from mice that received 2 h of light re-exposure (LE). A Poisson spike train exhibiting the same average frequency as the patterns recorded in vivo was equally effective at depressing mEPSC amplitudes in L2/3 neurons in V1 slices prepared from DE mice. Collectively, our results suggest that the history of visual experience modifies the responses of V1 neurons to stimulation and that rapid homeostatic depression of excitatory synapses can be driven by non-patterned input activity.

Antidromic latency of magnocellular, parvocellular, and koniocellular (Blue-ON) geniculocortical relay cells in marmosets

2014 ◽  
Vol 31 (3) ◽  
pp. 263-273 ◽  
Author(s):  
SOON KEEN CHEONG ◽  
ALEXANDER NICOLAAS JOHANNES PIETERSEN
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Primary Visual Cortex ◽  
Visual Stimulation ◽  
Blue Color ◽  
High Contrast ◽  
Response Latencies ◽  
Bon Cells ◽  
P Cells ◽  
Parallel Visual Pathways

AbstractWe studied the functional connectivity of cells in the lateral geniculate nucleus (LGN) with the primary visual cortex (V1) in anesthetized marmosets (Callithrix jacchus). The LGN sends signals to V1 along parallel visual pathways called parvocellular (P), magnocellular (M), and koniocellular (K). To better understand how these pathways provide inputs to V1, we antidromically activated relay cells in the LGN by electrically stimulating V1 and measuring the conduction latencies of P (n = 7), M (n = 14), and the “Blue-ON” (n = 5) subgroup of K cells (K-BON cells). We found that the antidromic latencies of K-BON cells were similar to those of P cells. We also measured the response latencies to high contrast visual stimuli for a subset of cells. We found the LGN cells that have the shortest latency of response to visual stimulation also have the shortest antidromic latencies. We conclude that Blue color signals are transmitted directly to V1 from the LGN by K-BON cells.

Data-Driven Approaches to Understanding Visual Neuron Activity

2019 ◽  
Vol 5 (1) ◽  
pp. 451-477 ◽  
Author(s):  
Daniel A. Butts
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Visual Stimulation ◽  
Visual Pathway ◽  
Data Driven ◽  
Visual Features ◽  
Neuron Activity ◽  
Visual Neurons ◽  
Neural Selectivity ◽  
Visual Neuron

With modern neurophysiological methods able to record neural activity throughout the visual pathway in the context of arbitrarily complex visual stimulation, our understanding of visual system function is becoming limited by the available models of visual neurons that can be directly related to such data. Different forms of statistical models are now being used to probe the cellular and circuit mechanisms shaping neural activity, understand how neural selectivity to complex visual features is computed, and derive the ways in which neurons contribute to systems-level visual processing. However, models that are able to more accurately reproduce observed neural activity often defy simple interpretations. As a result, rather than being used solely to connect with existing theories of visual processing, statistical modeling will increasingly drive the evolution of more sophisticated theories.

EEG-based functional networks evoked by acupuncture at ST 36: A data-driven thresholding study

2017 ◽  
Vol 31 (26) ◽  
pp. 1750187 ◽  
Author(s):  
Huiyan Li ◽  
Jiang Wang ◽  
Guosheng Yi ◽  
Bin Deng ◽  
Hexi Zhou
Keyword(s):  
Functional Connectivity ◽  
Network Connectivity ◽  
Data Driven ◽  
Functional Network ◽  
Eeg Signals ◽  
Long Distance ◽  
Alternative Approach ◽  
Connected Set ◽  
Data Driven Approach ◽  
The Brain

This paper investigates how acupuncture at ST 36 modulates the brain functional network. 20 channel EEG signals from 15 healthy subjects are respectively recorded before, during and after acupuncture. The correlation between two EEG channels is calculated by using Pearson’s coefficient. A data-driven approach is applied to determine the threshold, which is performed by considering the connected set, connected edge and network connectivity. Based on such thresholding approach, the functional network in each acupuncture period is built with graph theory, and the associated functional connectivity is determined. We show that acupuncturing at ST 36 increases the connectivity of the EEG-based functional network, especially for the long distance ones between two hemispheres. The properties of the functional network in five EEG sub-bands are also characterized. It is found that the delta and gamma bands are affected more obviously by acupuncture than the other sub-bands. These findings highlight the modulatory effects of acupuncture on the EEG-based functional connectivity, which is helpful for us to understand how it participates in the cortical or subcortical activities. Further, the data-driven threshold provides an alternative approach to infer the functional connectivity under other physiological conditions.

Widespread functional connectivity and fMRI fluctuations in human visual cortex in the absence of visual stimulation

NeuroImage ◽  
2006 ◽  
Vol 30 (4) ◽  
pp. 1313-1324 ◽  
Author(s):  
Yuval Nir ◽  
Uri Hasson ◽  
Ifat Levy ◽  
Yehezkel Yeshurun ◽  
Rafael Malach
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Visual Stimulation ◽  
Human Visual Cortex

scholarly journals Alzheimer’s Disease Progressively Reduces Visual Functional Network Connectivity

2021 ◽  
pp. 1-14
Author(s):  
Jie Huang ◽  
Paul Beach ◽  
Andrea Bozoki ◽  
David C. Zhu
Keyword(s):  
Visual Cortex ◽  
Lower Order ◽  
Resting State ◽  
Visual Processing ◽  
Network Connectivity ◽  
Higher Order ◽  
Functional Network ◽  
Functional Networks ◽  
The Face ◽  
Processing Network

Background: Postmortem studies of brains with Alzheimer’s disease (AD) not only find amyloid-beta (Aβ) and neurofibrillary tangles (NFT) in the visual cortex, but also reveal temporally sequential changes in AD pathology from higher-order association areas to lower-order areas and then primary visual area (V1) with disease progression. Objective: This study investigated the effect of AD severity on visual functional network. Methods: Eight severe AD (SAD) patients, 11 mild/moderate AD (MAD), and 26 healthy senior (HS) controls undertook a resting-state fMRI (rs-fMRI) and a task fMRI of viewing face photos. A resting-state visual functional connectivity (FC) network and a face-evoked visual-processing network were identified for each group. Results: For the HS, the identified group-mean face-evoked visual-processing network in the ventral pathway started from V1 and ended within the fusiform gyrus. In contrast, the resting-state visual FC network was mainly confined within the visual cortex. AD disrupted these two functional networks in a similar severity dependent manner: the more severe the cognitive impairment, the greater reduction in network connectivity. For the face-evoked visual-processing network, MAD disrupted and reduced activation mainly in the higher-order visual association areas, with SAD further disrupting and reducing activation in the lower-order areas. Conclusion: These findings provide a functional corollary to the canonical view of the temporally sequential advancement of AD pathology through visual cortical areas. The association of the disruption of functional networks, especially the face-evoked visual-processing network, with AD severity suggests a potential predictor or biomarker of AD progression.

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