scholarly journals Fine-scale computations for adaptive processing in the human brain

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Elisa Zamboni ◽  
Valentin G Kemper ◽  
Nuno Reis Goncalves ◽  
Ke Jia ◽  
Vasilis M Karlaftis ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Brain Plasticity ◽  
Sensory Information ◽  
Adaptive Processing ◽  
Fine Scale ◽  
Brain Responses ◽  
Efficient Information ◽  
High Field Imaging ◽  
Higher Visual Areas

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

scholarly journals Fine-scale computations for adaptive processing in the human brain

2020 ◽  
Author(s):  
E Zamboni ◽  
VG Kemper ◽  
NR Goncalves ◽  
K Jia ◽  
VM Karlaftis ◽  
...  
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Human Brain ◽  
Visual Processing ◽  
Brain Plasticity ◽  
Sensory Information ◽  
Adaptive Processing ◽  
Fine Scale ◽  
Efficient Information ◽  
High Field Imaging

AbstractAdapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalize on the sub-millimetre resolution afforded by ultra-high field imaging to examine BOLD-fMRI signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive visual processing. We demonstrate suppressive recurrent processing within visual cortex, as indicated by stronger BOLD decrease in superficial than middle and deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show dissociable connectivity mechanisms for adaptive processing: enhanced feedforward connectivity within visual cortex, while feedback occipito-parietal connectivity, reflecting top-down influences on visual processing. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

scholarly journals Consistency in macroscopic human brain responses to noisy time-varying visual inputs

2019 ◽  
Author(s):  
Keiichi Kitajo ◽  
Takumi Sase ◽  
Yoko Mizuno ◽  
Hiromichi Suetani
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Brain Dynamics ◽  
Time Varying ◽  
Ongoing Activity ◽  
Visual Inputs ◽  
Brain Responses ◽  
Individual Variations ◽  
Open Question ◽  
The Brain

AbstractIt is an open question as to whether macroscopic human brain responses to repeatedly presented external inputs show consistent patterns across trials. We here provide experimental evidence that human brain responses to noisy time-varying visual inputs, as measured by scalp electroencephalography (EEG), show a signature of consistency. The results indicate that the EEG-recorded responses are robust against fluctuating ongoing activity, and that they respond to visual stimuli in a repeatable manner. This consistency presumably mediates robust information processing in the brain. Moreover, the EEG response waveforms were discriminable between individuals, and were invariant over a number of days within individuals. We reveal that time-varying noisy visual inputs can harness macroscopic brain dynamics and can manifest hidden individual variations.

scholarly journals Author response: Fine-scale computations for adaptive processing in the human brain

2020 ◽  
Author(s):  
Elisa Zamboni ◽  
Valentin G Kemper ◽  
Nuno Reis Goncalves ◽  
Ke Jia ◽  
Vasilis M Karlaftis ◽  
...  
Keyword(s):  
Human Brain ◽  
Author Response ◽  
Adaptive Processing ◽  
Fine Scale

scholarly journals Identifying task-relevant spectral signatures of perceptual categorization in the human cortex

2018 ◽  
Author(s):  
Ilya Kuzovkin ◽  
Juan R. Vidal ◽  
Marcela Perrone-Bertlotti ◽  
Philippe Kahane ◽  
Sylvain Rheims ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Sensory Information ◽  
Classification Model ◽  
Artificial System ◽  
Local Networks ◽  
Random Forest Classification ◽  
Spectral Signatures ◽  
Forest Classification ◽  
Sensory Cortices

Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks' selectivity for categorical information processing is still unknown. By mimicking the decoding of the sensory information with machine learning we can obtain accurate artificial decoding models. Having the artificial system functionally on par with the biological one we can analyze the mechanics of the artificial system to gain insights into the inner workings of its biological counterpart. In this work we train a Random Forest classification model to decode eight perceptual categories from visual stimuli given a broad spectrum of human intracranial signals 4-150 Hz obtained during a visual perception task, and analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low 4-50 Hz and high 50-150 Hz frequency bands. We demonstrate that the locations and patterns of activity that are identified by the algorithm not only coincide with the known spectro-spatial signatures, but extend our knowledge by uncovering additional spectral signatures describing neural mechanisms of visual category perception in human brain.

Language processing is not a race against time

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Language Processing ◽  
Cognitive Functions ◽  
Memory Systems ◽  
Language System ◽  
Moderating Factors

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.

scholarly journals Sensory over-responsivity is related to GABAergic inhibition in thalamocortical circuits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily T. Wood ◽  
Kaitlin K. Cummings ◽  
Jiwon Jung ◽  
Genevieve Patterson ◽  
Nana Okada ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Sensory Information ◽  
Network Connectivity ◽  
Sensory Stimulation ◽  
Autism Spectrum ◽  
Future Research ◽  
Resonance Spectroscopy ◽  
Gamma Aminobutyric Acid ◽  
Sensory Stimuli ◽  
Brain Responses

AbstractSensory over-responsivity (SOR), extreme sensitivity to or avoidance of sensory stimuli (e.g., scratchy fabrics, loud sounds), is a highly prevalent and impairing feature of neurodevelopmental disorders such as autism spectrum disorders (ASD), anxiety, and ADHD. Previous studies have found overactive brain responses and reduced modulation of thalamocortical connectivity in response to mildly aversive sensory stimulation in ASD. These findings suggest altered thalamic sensory gating which could be associated with an excitatory/inhibitory neurochemical imbalance, but such thalamic neurochemistry has never been examined in relation to SOR. Here we utilized magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to examine the relationship between thalamic and somatosensory cortex inhibitory (gamma-aminobutyric acid, GABA) and excitatory (glutamate) neurochemicals with the intrinsic functional connectivity of those regions in 35 ASD and 35 typically developing pediatric subjects. Although there were no diagnostic group differences in neurochemical concentrations in either region, within the ASD group, SOR severity correlated negatively with thalamic GABA (r = −0.48, p < 0.05) and positively with somatosensory glutamate (r = 0.68, p < 0.01). Further, in the ASD group, thalamic GABA concentration predicted altered connectivity with regions previously implicated in SOR. These variations in GABA and associated network connectivity in the ASD group highlight the potential role of GABA as a mechanism underlying individual differences in SOR, a major source of phenotypic heterogeneity in ASD. In ASD, abnormalities of the thalamic neurochemical balance could interfere with the thalamic role in integrating, relaying, and inhibiting attention to sensory information. These results have implications for future research and GABA-modulating pharmacologic interventions.

scholarly journals The Right Hemisphere Is Responsible for the Greatest Differences in Human Brain Response to High-Arousing Emotional versus Neutral Stimuli: A MEG Study

2021 ◽  
Vol 11 (8) ◽  
pp. 960
Author(s):  
Mina Kheirkhah ◽  
Philipp Baumbach ◽  
Lutz Leistritz ◽  
Otto W. Witte ◽  
Martin Walter ◽  
...  
Keyword(s):  
Human Brain ◽  
Right Hemisphere ◽  
Emotional Stimuli ◽  
Brain Response ◽  
Whole Brain ◽  
Brain Responses ◽  
Cortical Regions ◽  
The Right ◽  
Healthy Participants

Studies investigating human brain response to emotional stimuli—particularly high-arousing versus neutral stimuli—have obtained inconsistent results. The present study was the first to combine magnetoencephalography (MEG) with the bootstrapping method to examine the whole brain and identify the cortical regions involved in this differential response. Seventeen healthy participants (11 females, aged 19 to 33 years; mean age, 26.9 years) were presented with high-arousing emotional (pleasant and unpleasant) and neutral pictures, and their brain responses were measured using MEG. When random resampling bootstrapping was performed for each participant, the greatest differences between high-arousing emotional and neutral stimuli during M300 (270–320 ms) were found to occur in the right temporo-parietal region. This finding was observed in response to both pleasant and unpleasant stimuli. The results, which may be more robust than previous studies because of bootstrapping and examination of the whole brain, reinforce the essential role of the right hemisphere in emotion processing.

Sign in / Sign up

Export Citation Format

Share Document