scholarly journals Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli

2019 ◽  
Author(s):  
DoHyun Kim ◽  
Tomer Livne ◽  
Nicholas V. Metcalf ◽  
Maurizio Corbetta ◽  
Gordon L. Shulman
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Spontaneous Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Visual Stimuli ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Stimulus Category ◽  
Human Visual Cortex

AbstractThe function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli and tasks. We compared in human visual cortex multi-vertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g. phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g. extra-striate body area for bodies), measured multi-vertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multi-vertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, i.e. both positive and negative, was significantly greater for the preferred stimulus category of an ROI (e.g. body category in body-preferring ROIs). The relationship between spontaneous and stimulus-evoked multi-vertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and patterns related to different categories fluctuated independently within their respective preferred ROIs (e.g. body- and scene-related multi-vertex patterns within body- and scene-preferring ROIs). These results support the general proposal that spontaneous multi-vertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.

Brain activity at rest: a multiscale hierarchical functional organization

2011 ◽  
Vol 105 (6) ◽  
pp. 2753-2763 ◽  
Author(s):  
Gaëlle Doucet ◽  
Mikaël Naveau ◽  
Laurent Petit ◽  
Nicolas Delcroix ◽  
Laure Zago ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Brain Activity ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Hierarchical Level ◽  
Spontaneous Brain Activity ◽  
Dorsal Attentional Network

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.

scholarly journals Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli

2020 ◽  
Vol 124 (5) ◽  
pp. 1343-1363
Author(s):  
DoHyun Kim ◽  
Tomer Livne ◽  
Nicholas V. Metcalf ◽  
Maurizio Corbetta ◽  
Gordon L. Shulman
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Spontaneous Activity ◽  
Spatial Patterns ◽  
Brain Activity ◽  
Spontaneous Brain Activity ◽  
Emerging Patterns ◽  
Early Visual Cortex ◽  
Functional Explanations ◽  
High Level

Spontaneous brain activity was once thought to reflect only noise, but evidence of strong spatiotemporal regularities has motivated a search for functional explanations. Here we show that the spatial pattern of spontaneous activity in human high-level and early visual cortex is related to the spatial patterns evoked by stimuli. Moreover, these patterns partly govern spontaneous spatiotemporal interactions between regions, so-called functional connectivity. These results support the hypothesis that spontaneous activity serves a representational function.

scholarly journals Perceptual grouping and inverse fMRI activity patterns in human visual cortex

10.1167/8.7.2 ◽  
2008 ◽  
Vol 8 (7) ◽  
pp. 2 ◽  
Author(s):  
Fang Fang ◽  
Daniel Kersten ◽  
Scott O. Murray
Keyword(s):  
Visual Cortex ◽  
Perceptual Grouping ◽  
Activity Patterns ◽  
Human Visual Cortex

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals Orientation and color tuning of the human visual gamma rhythm

2021 ◽  
Author(s):  
Ye Li ◽  
William Bosking ◽  
Michael S Beauchamp ◽  
Sameer A Sheth ◽  
Daniel Yoshor ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Brain Activity ◽  
Population Level ◽  
Gamma Oscillations ◽  
Cell Orientation ◽  
Population Activity ◽  
Color Tuning ◽  
Human Visual Cortex ◽  
Gamma Rhythm

Narrowband gamma oscillations (NBG: ~20-60Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. Consequently, the amplitude and frequency of induced NBG activity is highly sensitive to these stimulus features. For example, in the non-human primate, NBG displays biases in orientation and color tuning at the population level. Such biases may relate to recent reports describing the large-scale organization of single-cell orientation and color tuning in visual cortex, thus providing a potential bridge between measurements made at different scales. Similar biases in NBG population tuning have been predicted to exist in the human visual cortex, but this has yet to be fully examined. Using intracranial recordings from human visual cortex, we investigated the tuning of NBG to orientation and color, both independently and in conjunction. NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. These data both elaborate on the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases in visual cortex, adding to a growing set of stimulus dependencies associated with the genesis of NBG. Together, these two factors may provide a fruitful testing ground for examining multi-scale models of brain activity, and impose new constraints on the functional significance of the visual gamma rhythm.

scholarly journals The Effect of High-Level Illumination on Brain Activity in the Human Visual Cortex

2014 ◽  
Vol 98 (2) ◽  
pp. 87-91
Author(s):  
Yasuhiro Kawashima ◽  
Hiroyuki Yamashiro ◽  
Hiroki Yamamoto ◽  
Tomokazu Murase ◽  
Yoshikatsu Ichimura ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Brain Activity ◽  
Human Visual Cortex ◽  
High Level

scholarly journals Oxytocin shapes spontaneous activity patterns in the developing visual cortex by activating somatostatin interneurons

2019 ◽  
Author(s):  
Paloma P Maldonado ◽  
Alvaro Nuno-Perez ◽  
Jan Kirchner ◽  
Elizabeth Hammock ◽  
Julijana Gjorgjieva ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Sensory Processing ◽  
Activity Patterns ◽  
Network Activity ◽  
Synaptic Connections ◽  
Pairwise Correlations ◽  
Early Brain Development

SummarySpontaneous network activity shapes emerging neuronal circuits during early brain development, however how neuromodulation influences this activity is not fully understood. Here, we report that the neuromodulator oxytocin powerfully shapes spontaneous activity patterns. In vivo, oxytocin strongly decreased the frequency and pairwise correlations of spontaneous activity events in visual cortex (V1), but not in somatosensory cortex (S1). This differential effect was a consequence of oxytocin only increasing inhibition in V1 and increasing both inhibition and excitation in S1. The increase in inhibition was mediated by the depolarization and increase in excitability of somatostatin+ (SST) interneurons specifically. Accordingly, silencing SST+ neurons pharmacogenetically fully blocked oxytocin’s effect on inhibition in vitro as well its effect on spontaneous activity patterns in vivo. Thus, oxytocin decreases the excitatory/inhibitory ratio and modulates specific features of V1 spontaneous activity patterns that are crucial for refining developing synaptic connections and sensory processing later in life.

Magnetoencephalography in Alzheimer Disease

2020 ◽  
pp. 390-402
Author(s):  
David López-Sanz ◽  
Jaisalmer de Frutos-Lucas ◽  
Gianluca Susi ◽  
Fernando Maestú
Keyword(s):  
Alzheimer Disease ◽  
Spontaneous Activity ◽  
Brain Mapping ◽  
Brain Activity ◽  
Activity Patterns ◽  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Brain Signals ◽  
Epilepsy Localization ◽  
Monitoring Progress

There are two basic ways Magnetoencephalography (MEG) has been applied. The most typical way is recording brain signals related to specific stimuli and tasks or signals indicative of focal pathology as in presurgical brain mapping and epilepsy localization. The second way is recording patterns of spontaneous activity characteristic of particular states or traits. An example of the latter application is described in this chapter that details efforts of deriving brain activity patterns characteristic of Alzheimer’s dementia. The derivation of such patterns will be of great value in diagnosis, prognosis, as well as monitoring progress (or the process of amelioration) of diseases.

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