scholarly journals Stimulus Familiarity and Expectation Jointly Modulate Neural Activity in the Visual Ventral Stream

2018 ◽  
Vol 30 (9) ◽  
pp. 1366-1377 ◽  
Author(s):  
Mariya E. Manahova ◽  
Pim Mostert ◽  
Peter Kok ◽  
Jan-Mathijs Schoffelen ◽  
Floris P. de Lange
Keyword(s):  
Prior Knowledge ◽  
Neural Activity ◽  
Brain Activity ◽  
Ventral Stream ◽  
Sensory Response ◽  
Inferotemporal Cortex ◽  
Response Dynamics ◽  
Lateral Occipital Complex ◽  
Neurophysiological Studies ◽  
Stimulus Familiarity

Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex. It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. To address this issue and to examine whether previous findings generalize to noninvasively measured neural activity in humans, we separately manipulated stimulus familiarity and expectation while noninvasively recording human brain activity using magnetoencephalography. We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex, the putative human homologue of monkey inferotemporal cortex. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

scholarly journals Stimulus familiarity and expectation jointly modulate neural activity in the visual ventral stream

2017 ◽  
Author(s):  
Mariya E. Manahova ◽  
Pim Mostert ◽  
Peter Kok ◽  
Jan-Mathijs Schoffelen ◽  
Floris P. de Lange
Keyword(s):  
Prior Knowledge ◽  
Neural Activity ◽  
Brain Activity ◽  
Ventral Stream ◽  
Sensory Response ◽  
Response Dynamics ◽  
Object Processing ◽  
Lateral Occipital Complex ◽  
Neurophysiological Studies ◽  
Stimulus Familiarity

AbstractPrior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex (IT). It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. In order to address this issue and to examine whether previous findings generalize to non-invasively measured neural activity in humans of both sexes, we separately manipulated stimulus familiarity and expectation, while non-invasively recording human brain activity using magnetoencephalography (MEG). We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex (LOC), the putative human homologue of monkey IT. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

Learning to See Biological Motion: Brain Activity Parallels Behavior

2004 ◽  
Vol 16 (9) ◽  
pp. 1669-1679 ◽  
Author(s):  
Emily D. Grossman ◽  
Randolph Blake ◽  
Chai-Youn Kim
Keyword(s):  
Neural Activity ◽  
Biological Motion ◽  
Brain Activity ◽  
Daily Practice ◽  
Superior Temporal Sulcus ◽  
Fusiform Face Area ◽  
Face Area ◽  
Perceptual Performance ◽  
Trained Observers ◽  
Posterior Superior Temporal Sulcus

Individuals improve with practice on a variety of perceptual tasks, presumably reflecting plasticity in underlying neural mechanisms. We trained observers to discriminate biological motion from scrambled (nonbiological) motion and examined whether the resulting improvement in perceptual performance was accompanied by changes in activation within the posterior superior temporal sulcus and the fusiform “face area,” brain areas involved in perception of biological events. With daily practice, initially naive observers became more proficient at discriminating biological from scrambled animations embedded in an array of dynamic “noise” dots, with the extent of improvement varying among observers. Learning generalized to animations never seen before, indicating that observers had not simply memorized specific exemplars. In the same observers, neural activity prior to and following training was measured using functional magnetic resonance imaging. Neural activity within the posterior superior temporal sulcus and the fusiform “face area” reflected the participants' learning: BOLD signals were significantly larger after training in response both to animations experienced during training and to novel animations. The degree of learning was positively correlated with the amplitude changes in BOLD signals.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis

2019 ◽  
Author(s):  
Lin Wang ◽  
Edward Wlotko ◽  
Edward Alexander ◽  
Lotte Schoot ◽  
Minjae Kim ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Language Comprehension ◽  
Neural Activity ◽  
Semantic Processing ◽  
Sentence Comprehension ◽  
Brain Activity ◽  
Coarse Grained ◽  
Similarity Analysis ◽  
Semantic Features ◽  
Representational Similarity Analysis

AbstractIt has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used Magnetoencephalography (MEG) and Electroencephalography (EEG), in combination with Representational Similarity Analysis (RSA), to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate constraining verbs was greater than following inanimate constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.Significance statementLanguage inputs unfold very quickly during real-time communication. By predicting ahead we can give our brains a “head-start”, so that language comprehension is faster and more efficient. While most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context, “they cautioned the…”, we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

scholarly journals Dynamic Altered Amplitude of Low-Frequency Fluctuations in Patients With Major Depressive Disorder

2021 ◽  
Vol 12 ◽  
Author(s):  
Ruiping Zheng ◽  
Yuan Chen ◽  
Yu Jiang ◽  
Mengmeng Wen ◽  
Bingqian Zhou ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Neural Activity ◽  
Temporal Variability ◽  
Brain Activity ◽  
Low Frequency ◽  
First Episode ◽  
Posterior Lobe ◽  
Major Depressive ◽  
Drug Naïve ◽  
The Right

Background: Major depressive disorder (MDD) has demonstrated abnormalities of static intrinsic brain activity measured by amplitude of low-frequency fluctuation (ALFF). Recent studies regarding the resting-state functional magnetic resonance imaging (rs-fMRI) have found the brain activity is inherently dynamic over time. Little is known, however, regarding the temporal dynamics of local neural activity in MDD. Here, we investigated whether temporal dynamic changes in spontaneous neural activity are influenced by MDD.Methods: We recruited 81 first-episode, drug-naive MDD patients and 64 age-, gender-, and education-matched healthy controls who underwent rs-fMRI. A sliding-window approach was then adopted for the estimation of dynamic ALFF (dALFF), which was used to measure time-varying brain activity and then compared between the two groups. The relationship between altered dALFF variability and clinical variables in MDD patients was also analyzed.Results: MDD patients showed increased temporal variability (dALFF) mainly focused on the bilateral thalamus, the bilateral superior frontal gyrus, the right middle frontal gyrus, the bilateral cerebellum posterior lobe, and the vermis. Furthermore, increased dALFF variability values in the right thalamus and right cerebellum posterior lobe were positively correlated with MDD symptom severity.Conclusions: The overall results suggest that altered temporal variability in corticocerebellar–thalamic–cortical circuit (CCTCC), involved in emotional, executive, and cognitive, is associated with drug-naive, first-episode MDD patients. Moreover, our study highlights the vital role of abnormal dynamic brain activity in the cerebellar hemisphere associated with CCTCC in MDD patients. These findings may provide novel insights into the pathophysiological mechanisms of MDD.

scholarly journals Multi-shanks SiNAPS Active Pixel Sensor CMOS probe: 1024 simultaneously recording channels for high-density intracortical brain mapping

2019 ◽  
Author(s):  
Fabio Boi ◽  
Nikolas Perentos ◽  
Aziliz Lecomte ◽  
Gerrit Schwesig ◽  
Stefano Zordan ◽  
...  
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Brain Area ◽  
Large Population ◽  
Brain Structures ◽  
High Density ◽  
Single Neurons ◽  
Electrode Arrays ◽  
Unit Recording ◽  
Recording Channels

AbstractThe advent of implantable active dense CMOS neural probes opened a new era for electrophysiology in neuroscience. These single shank electrode arrays, and the emerging tailored analysis tools, provide for the first time to neuroscientists the neurotechnology means to spatiotemporally resolve the activity of hundreds of different single-neurons in multiple vertically aligned brain structures. However, while these unprecedented experimental capabilities to study columnar brain properties are a big leap forward in neuroscience, there is the need to spatially distribute electrodes also horizontally. Closely spacing and consistently placing in well-defined geometrical arrangement multiple isolated single-shank probes is methodologically and economically impractical. Here, we present the first high-density CMOS neural probe with multiple shanks integrating thousand’s of closely spaced and simultaneously recording microelectrodes to map neural activity across 2D lattice. Taking advantage from the high-modularity of our electrode-pixels-based SiNAPS technology, we realized a four shanks active dense probe with 256 electrode-pixels/shank and a pitch of 28 µm, for a total of 1024 simultaneously recording channels. The achieved performances allow for full-band, whole-array read-outs at 25 kHz/channel, show a measured input referred noise in the action potential band (300-7000 Hz) of 6.5 ± 2.1µVRMS, and a power consumption <6 µW/electrode-pixel. Preliminary recordings in awake behaving mice demonstrated the capability of multi-shanks SiNAPS probes to simultaneously record neural activity (both LFPs and spikes) from a brain area >6 mm2, spanning cortical, hippocampal and thalamic regions. High-density 2D array enables combining large population unit recording across distributed networks with precise intra- and interlaminar/nuclear mapping of the oscillatory dynamics. These results pave the way to a new generation of high-density and extremely compact multi-shanks CMOS-probes with tunable layouts for electrophysiological mapping of brain activity at the single-neurons resolution.

Abstract WMP117: Regional Homogeneity Changes In Patients With Transient Ischemic Attack: A Resting-state Functional Magnetic Resonance Imaging Study

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He
Keyword(s):  
Transient Ischemic Attack ◽  
Neural Activity ◽  
Resting State ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Imaging Study ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Ischemic Attack

Background: Transient ischemic attack (TIA) can increase the risk of some neurologic dysfunctions, of which the mechanism remains unclear. Resting-state functional MRI (rfMRI) is suggested to be a valuable tool to study the relation between spontaneous brain activity and behavioral performance. However, little is known about whether the local synchronization of spontaneous neural activity is altered in TIA patients. The purpose of this study is to detect differences in regional spontaneous activities throughout the whole brain between TIAs and normal controls. Methods: Twenty one TIA patients suffered an ischemic event in the right hemisphere and 21 healthy volunteers were enrolled in the study. All subjects were investigated using cognitive tests and rfMRI. The regional homogeneity (ReHo) was calculate and compared between two groups. Then a correlation analysis was performed to explore the relationship between ReHo values of brain regions showing abnormal resting-state properties and clinical variables in TIA group. Results: Compared with controls, TIA patients exhibited decreased ReHo in right dorsolateral prefrontal cortex (DLPFC), right inferior prefrontal gyrus, right ventral anterior cingulate cortex and right dorsal posterior cingular cortex. Moreover, the mean ReHo in right DLPFC and right inferior prefrontal gyrus were significantly correlated with MoCA in TIA patients. Conclusions: Neural activity in the resting state is changed in patients with TIA. The positive correlation between regional homogeneity of rfMRI and cognition suggests that ReHo may be a promising tool to better our understanding of the neurobiological consequences of TIA.

scholarly journals Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis

2020 ◽  
Vol 14 ◽  
Author(s):  
David A. Tovar ◽  
Jacob A. Westerberg ◽  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Thomas A. Carlson ◽  
...  
Keyword(s):  
Neural Activity ◽  
Visual Stimulation ◽  
Brain Activity ◽  
Contextual Information ◽  
Univariate Analysis ◽  
Stimulus Presentation ◽  
Population Level ◽  
Granular Cell ◽  
Stimulus Orientation ◽  
Specific Information

Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.

Imagine imaging neural activity in crying infants and in their caring parents

2004 ◽  
Vol 27 (4) ◽  
pp. 465-467 ◽  
Author(s):  
Steven Laureys ◽  
Serge Goldman
Keyword(s):  
Neural Activity ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Objective Measurement ◽  
Signal Function ◽  
Infant Crying ◽  
Early Infant ◽  
Neural Substrate

Soltis' paper contains little data on the underlying neural substrate of the discussed signal function of early infant crying – probably because there is amazingly little known about it. We here discuss the interest of functional neuroimaging as an objective measurement of brain activity in (1) early infants during crying and (2) parents hearing their offspring cry.

Mapping Alterations of the Functional Structure of the Cerebral Cortex in Obsessive–Compulsive Disorder

2019 ◽  
Vol 29 (11) ◽  
pp. 4753-4762 ◽  
Author(s):  
Jesus Pujol ◽  
Laura Blanco-Hinojo ◽  
Dídac Maciá ◽  
Pino Alonso ◽  
Ben J Harrison ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Obsessive Compulsive Disorder ◽  
Neural Activity ◽  
Orbitofrontal Cortex ◽  
Inhibitory Neuron ◽  
Functional Structure ◽  
Neuron Activity ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Neurophysiological Studies

AbstractWe mapped alterations of the functional structure of the cerebral cortex using a novel imaging approach in a sample of 160 obsessive–compulsive disorder (OCD) patients. Whole-brain functional connectivity maps were generated using multidistance measures of intracortical neural activity coupling defined within isodistant local areas. OCD patients demonstrated neural activity desynchronization within the orbitofrontal cortex and in primary somatosensory, auditory, visual, gustatory, and olfactory areas. Symptom severity was significantly associated with the degree of functional structure alteration in OCD-relevant brain regions. By means of a novel imaging perspective, we once again identified brain alterations in the orbitofrontal cortex, involving areas purportedly implicated in the pathophysiology of OCD. However, our results also indicated that weaker intracortical activity coupling is also present in each primary sensory area. On the basis of previous neurophysiological studies, such cortical activity desynchronization may best be interpreted as reflecting deficient inhibitory neuron activity and altered sensory filtering.

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