scholarly journals Self-organization of cortical areas in the development and evolution of neocortex: a network growth model

2020 ◽  
Author(s):  
Nabil Imam ◽  
Barbara Finlay
Keyword(s):  
Growth Model ◽  
Activity Patterns ◽  
Basic Mechanism ◽  
Physical Parameters ◽  
Network Growth ◽  
Cortical Areas ◽  
Mirror Reversal ◽  
Correlated Activity ◽  
The Matrix ◽  
Characteristic Features

AbstractWhile the mechanisms generating the topographic organization of primary sensory areas in the neocortex are well-studied, what generates secondary cortical areas is virtually unknown. Using physical parameters representing primary and secondary visual areas as they vary from monkey to mouse, we derived a growth model to explore if characteristic features of secondary areas could be produced from correlated activity patterns arising from V1 alone. We found that V1 seeded variable numbers of secondary areas based on activity-driven wiring and wiring density limits within the cortical surface. These secondary areas exhibited the typical mirror-reversal of map topography on cortical area boundaries and progressive reduction of the area and spatial resolution of each new map on the caudorostral axis. Activity-based map formation may be the basic mechanism that establishes the matrix of topographically-organized cortical areas available for later computational specialization.

scholarly journals Self-organization of cortical areas in the development and evolution of neocortex

2020 ◽  
Vol 117 (46) ◽  
pp. 29212-29220 ◽  
Author(s):  
Nabil Imam ◽  
Barbara L. Finlay
Keyword(s):  
Activity Patterns ◽  
Basic Mechanism ◽  
Physical Parameters ◽  
Network Growth ◽  
Cortical Areas ◽  
Mirror Reversal ◽  
Correlated Activity ◽  
The Matrix ◽  
Characteristic Features ◽  
Development And Evolution

While the mechanisms generating the topographic organization of primary sensory areas in the neocortex are well studied, what generates secondary cortical areas is virtually unknown. Using physical parameters representing primary and secondary visual areas as they vary from monkey to mouse, we derived a network growth model to explore if characteristic features of secondary areas could be produced from correlated activity patterns arising from V1 alone. We found that V1 seeded variable numbers of secondary areas based on activity-driven wiring and wiring-density limits within the cortical surface. These secondary areas exhibited the typical mirror-reversal of map topography on cortical area boundaries and progressive reduction of the area and spatial resolution of each new map on the caudorostral axis. Activity-based map formation may be the basic mechanism that establishes the matrix of topographically organized cortical areas available for later computational specialization.

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 Representational drift in the mouse visual cortex

2020 ◽  
Author(s):  
Daniel Deitch ◽  
Alon Rubin ◽  
Yaniv Ziv
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Population Level ◽  
Population Activity ◽  
Cortical Areas ◽  
Electrophysiological Recordings ◽  
The Face ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Over Time

AbstractNeuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.

scholarly journals Intrinsic functional connectivity resembles cortical architecture at various levels of isoflurane anesthesia

2016 ◽  
Author(s):  
Felix Fischer ◽  
Florian Pieper ◽  
Edgar Galindo-Leon ◽  
Gerhard Engler ◽  
Claus C. Hilgetag ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Occipital Cortex ◽  
Amplitude Envelope ◽  
Cortical Areas ◽  
Temporal Properties ◽  
Connectivity Patterns ◽  
Different Depths ◽  
Amplitude Correlation

AbstractCortical activity patterns change in different depths of general anesthesia. Here we investigate the associated network level changes of functional connectivity. We recorded ongoing electrocorticographic (ECoG) activity from the ferret temporo-parieto-occipital cortex under various levels of isoflurane and determined the functional connectivity by computing amplitude envelope correlations. Through hierarchical clustering, we derived typical connectivity patterns corresponding to light, intermediate and deep anesthesia. Generally, amplitude correlation strength increased strongly with depth of anesthesia across all cortical areas and frequency bands. This was accompanied by the emergence of burstsuppression activity in the ECoG signal and a change of the spectrum of the amplitude envelope. Normalizing the functional connectivity patterns showed that the topographical structure remained similar across depths of anesthesia, resembling the functional association of the underlying cortical areas. Thus, while strength and temporal properties of amplitude co-modulation vary depending on the activity of local neural circuits, their network-level interaction pattern is presumably most strongly determined by the underlying structural connectivity.

scholarly journals Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Dominik Freche ◽  
Jodie Naim-Feil ◽  
Shmuel Hess ◽  
Avraham Peled ◽  
Alexander Grinshpoon ◽  
...  
Keyword(s):  
Resting State ◽  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Activity Patterns ◽  
Neuronal Populations ◽  
Correlated Activity ◽  
Amplitude Fluctuations ◽  
Phase Amplitude ◽  
External Stimuli

Abstract The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

scholarly journals Magnetic Activity of Two Similar Subgiants in Binaries with Very Different Mass Ratios: EI Eri and V711 Tau

2011 ◽  
Vol 7 (S282) ◽  
pp. 478-479 ◽  
Author(s):  
Katalin Oláh ◽  
Zsolt Kővári ◽  
Krisztián Vida ◽  
Klaus G. Strassmeier
Keyword(s):  
Differential Rotation ◽  
Activity Patterns ◽  
Magnetic Activity ◽  
Light Curves ◽  
Physical Parameters ◽  
Remarkable Difference ◽  
High Latitudes ◽  
Solar Type ◽  
Low Mass ◽  
Fast Rotating

AbstractWe use more than three decades-long photometry to study the activity patterns on the two fast-rotating subgiant components in EI Eri (G5IV) and V711 Tau (K1IV). From yearly mean rotational periods from the light curves, we find that EI Eri, with well-measured solar-type differential rotation, always has spots from the equator to high latitudes. The measured differential rotation of V711 Tau is controversial, and in any case is very small. The spots on the K1IV star in V711 Tau seem to be tidally locked. The physical parameters of the two systems are similar, with one remarkable difference: EI Eri has a low mass M4-5 dwarf companion, whereas V711 Tau has a G5V star in the system, thus their mass centers are in very different positions. This may modify the whole internal structure of the active stars, causing marked differences in their surface features.

scholarly journals Network growth model with intrinsic vertex fitness

2013 ◽  
Vol 88 (1) ◽  
Author(s):  
I. E. Smolyarenko ◽  
K. Hoppe ◽  
G. J. Rodgers
Keyword(s):  
Growth Model ◽  
Network Growth

Micro-Blogging Based Network Growth Model of Semantic Link Network

2014 ◽  
Vol 513-517 ◽  
pp. 2211-2214 ◽  
Author(s):  
Wei Ren ◽  
Yu Hui Qiu
Keyword(s):  
Social Network ◽  
Network Model ◽  
Growth Model ◽  
Real Life ◽  
Network Growth ◽  
Sina Weibo ◽  
Close Analogy ◽  
Interactive Network ◽  
Semantic Link ◽  
Semantic Link Network

This paper studies the network model in SLN by applying the methodology of social network to a widely accepted, real-life user interactive network scenario. The data and experiments are based on micro-blogging (Sina Weibo). Results show that the statistic properties of SLN are in close analogy with that of social network. Contrary to our normal understanding, some nodes with too much semantics (especially under one category) are in decreased chances of having links from newly added nodes.

Subdiffusive Dynamics of Bump Attractors: Mechanisms and Functional Roles

2015 ◽  
Vol 27 (2) ◽  
pp. 255-280 ◽  
Author(s):  
Yang Qi ◽  
Michael Breakspear ◽  
Pulin Gong
Keyword(s):  
Neural Coding ◽  
Spatial Working Memory ◽  
Activity Patterns ◽  
Stimulus Presentation ◽  
Generalized Langevin Equation ◽  
Spatial Correlations ◽  
Temporal Correlations ◽  
Normal Diffusion ◽  
Characteristic Features ◽  
Noisy Inputs

Bump attractors are localized activity patterns that can self-sustain after stimulus presentation, and they are regarded as the neural substrate for a host of perceptual and cognitive processes. One of the characteristic features of bump attractors is that they are neutrally stable, so that noisy inputs cause them to drift away from their initial locations, severely impairing the accuracy of bump location-dependent neural coding. Previous modeling studies of such noise-induced drifting activity of bump attractors have focused on normal diffusive dynamics, often with an assumption that noisy inputs are uncorrelated. Here we show that long-range temporal correlations and spatial correlations in neural inputs generated by multiple interacting bumps cause them to drift in an anomalous subdiffusive way. This mechanism for generating subdiffusive dynamics of bump attractors is further analyzed based on a generalized Langevin equation. We demonstrate that subdiffusive dynamics can significantly improve the coding accuracy of bump attractors, since the variance of the bump displacement increases sublinearly over time and is much smaller than that of normal diffusion. Furthermore, we reanalyze existing psychophysical data concerning the spread of recalled cue position in spatial working memory tasks and show that its variance increases sublinearly with time, consistent with subdiffusive dynamics of bump attractors. Based on the probability density function of bump position, we also show that the subdiffusive dynamics result in a long-tailed decay of firing rate, greatly extending the duration of persistent activity.

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