scholarly journals Modality-independent coding of scene categories in prefrontal cortex

2017 ◽  
Author(s):  
Yaelan Jung ◽  
Bart Larsen ◽  
Dirk B. Walther

AbstractNatural environments convey information through multiple sensory modalities, all of which contribute to people’s percepts. Although it has been shown that visual or auditory content of scene categories can be decoded from brain activity, it remains unclear where and how humans integrate different sensory inputs and represent scene information beyond a specific sensory modality domain. To address this question, we investigated how categories of scene images and sounds are represented in several brain regions. A mixed gender group of healthy human subjects participated the present study, where their brain activity was measured with fMRI while viewing images or listening to sounds of different places. We found that both visual and auditory scene categories can be decoded not only from modality-specific areas, but also from several brain regions in the temporal, parietal, and prefrontal cortex. Intriguingly, only in the prefrontal cortex, but not in any other regions, categories of scene images and sounds appear to be represented in similar activation patterns, suggesting that scene representations in the prefrontal cortex are modality-independent. Furthermore, the error patterns of neural decoders indicate that category-specific neural activity patterns in the middle and superior frontal gyri are tightly linked to categorization behavior. Our findings demonstrate that complex scene information is represented at an abstract level in the prefrontal cortex, regardless of the sensory modality of the stimulus.Statement of SignificanceOur experience in daily life requires the integration of multiple sensory inputs such as images, sounds, or scents from the environment. Here, for the first time, we investigated where and how in the brain information about the natural environment from multiple senses is merged to form modality-independent representations of scene categories. We show direct decoding of scene categories across sensory modalities from patterns of neural activity in the prefrontal cortex. We also conclusively tie these neural representations to human categorization behavior based on the errors from the neural decoder and behavior. Our findings suggest that the prefrontal cortex is a central hub for integrating sensory information and computing modality-independent representations of scene categories.

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 296
Author(s):  
Rodrigo Araneda ◽  
Sandra Silva Moura ◽  
Laurence Dricot ◽  
Anne G. De Volder

Using functional magnetic resonance imaging, here we monitored the brain activity in 12 early blind subjects and 12 blindfolded control subjects, matched for age, gender and musical experience, during a beat detection task. Subjects were required to discriminate regular (“beat”) from irregular (“no beat”) rhythmic sequences composed of sounds or vibrotactile stimulations. In both sensory modalities, the brain activity differences between the two groups involved heteromodal brain regions including parietal and frontal cortical areas and occipital brain areas, that were recruited in the early blind group only. Accordingly, early blindness induced brain plasticity changes in the cerebral pathways involved in rhythm perception, with a participation of the visually deprived occipital brain areas whatever the sensory modality for input. We conclude that the visually deprived cortex switches its input modality from vision to audition and vibrotactile sense to perform this temporal processing task, supporting the concept of a metamodal, multisensory organization of this cortex.


Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He

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.


2016 ◽  
Vol 26 (07) ◽  
pp. 1650026 ◽  
Author(s):  
E. Giraldo-Suarez ◽  
J. D. Martinez-Vargas ◽  
G. Castellanos-Dominguez

We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.


2021 ◽  
Vol 15 ◽  
Author(s):  
Yan He ◽  
Yinying Hu ◽  
Yaxi Yang ◽  
Defeng Li ◽  
Yi Hu

Recent neuroimaging research has suggested that unequal cognitive efforts exist between interpreting from language 1 (L1) to language 2 (L2) compared with interpreting from L2 to L1. However, the neural substrates that underlie this directionality effect are not yet well understood. Whether directionality is modulated by interpreting expertise also remains unknown. In this study, we recruited two groups of Mandarin (L1)/English (L2) bilingual speakers with varying levels of interpreting expertise and asked them to perform interpreting and reading tasks. Functional near-infrared spectroscopy (fNIRS) was used to collect cortical brain data for participants during each task, using 68 channels that covered the prefrontal cortex and the bilateral perisylvian regions. The interpreting-related neuroimaging data was normalized by using both L1 and L2 reading tasks, to control the function of reading and vocalization respectively. Our findings revealed the directionality effect in both groups, with forward interpreting (from L1 to L2) produced more pronounced brain activity, when normalized for reading. We also found that directionality was modulated by interpreting expertise in both normalizations. For the group with relatively high expertise, the activated brain regions included the right Broca’s area and the left premotor and supplementary motor cortex; whereas for the group with relatively low expertise, the activated brain areas covered the superior temporal gyrus, the dorsolateral prefrontal cortex (DLPFC), the Broca’s area, and visual area 3 in the right hemisphere. These findings indicated that interpreting expertise modulated brain activation, possibly because of more developed cognitive skills associated with executive functions in experienced interpreters.


2021 ◽  
Vol 4 (1) ◽  
pp. p8
Author(s):  
Michael Oler ◽  
Anthony Johnson ◽  
Anna McCulloh ◽  
Munqith Dagher ◽  
Anita Day ◽  
...  

Sectarian violence continues in Iraq affecting regional and world security. Neuroscience techniques are used to assess the mentalizing process and counter-arguing in response to videos designed to prevent extremist radicalization. Measurement of neural activity in brain Regions of Interest (ROI) assists identification of messages which can promote favorable behavior. Activation of the Medial Prefrontal Cortex (MPFC) is associated with message adoption and behavior change. Public Service Announcements (PSAs) have not been effective in reducing violence in Iraq. This study demonstrates that the four PSAs investigated in this study do not activate the MPFC. The RLPFC is a brain ROI associated with counter-arguing and message resistance. This study demonstrates that reduction in activity in the Right Lateral Prefrontal Cortex (RLPFC) is associated with decreased sectarianism. Engagement was measured and is associated with activity in the frontal pole regions.We introduce Functional Near-infrared Spectroscopy (fNIRS) to measure the neural activity of highly sectarian Iraqis in response to these anti-sectarian messages. Neural activity was measured while viewing three PSAs and a fourth unpublished video. All four videos are intended to reduce sectarianism. A novel sectarianism scale is introduced to measure sectarian beliefs before and after the messages. This sectarian scale has high internal consistency as measured by Cronbach’s alpha. Measured activation of brain ROIs are correlated with changes in the sectarian scale. Twelve Sunni and twelve Shi’a Iraqis participated in the study. Subjects were shown the four videos in randomized order, while equipped with a fNIRS neural imaging device. All four videos produced significant engagement. None of the videos reduced sectarianism nor caused brain activation of adoption. This is consistent with the widely held Iraqi public perception that the PSAs are ineffective. Only one video, which was un-published, caused reduced sectarian beliefs. This un-published fourth video was associated with decreased counter-arguing. Counter-arguing is associated with message resistance.


2020 ◽  
Author(s):  
Anna-Katharina R. Bauer ◽  
Freek van Ede ◽  
Andrew J. Quinn ◽  
Anna C. Nobre

AbstractAt any given moment our sensory systems receive multiple, often rhythmic, inputs from the environment. Processing of temporally structured events in one sensory modality can guide both behavioural and neural processing of events in other sensory modalities, but how this occurs remains unclear. Here, we used human electroencephalography (EEG) to test the cross-modal influences of a continuous auditory frequency-modulated (FM) sound on visual perception and visual cortical activity. We report systematic fluctuations in perceptual discrimination of brief visual stimuli in line with the phase of the FM sound. We further show that this rhythmic modulation in visual perception is related to an accompanying rhythmic modulation of neural activity recorded over visual areas. Importantly, in our task, perceptual and neural visual modulations occurred without any abrupt and salient onsets in the energy of the auditory stimulation and without any rhythmic structure in the visual stimulus. As such, the results provide a critical validation for the existence and functional role of cross-modal entrainment and demonstrates its utility for organising the perception of multisensory stimulation in the natural environment.Highlightscross-modal influences are mediated by the synchronisation of neural oscillationsvisual performance fluctuates in line with the phase of a frequency-modulated soundcross-modal entrainment of neural activity predicts fluctuation in visual performancecross-modal entrainment organises perception of multisensory stimuli


2020 ◽  
Author(s):  
Michael X Cohen ◽  
Bernhard Englitz ◽  
Arthur S C França

AbstractNeural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, due to limited data availability and to the difficulty of analyzing rich multivariate datasets. Here we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (~4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.Significance statementNeural activity is synchronized over space, time, and frequency. To characterize the dynamics of large-scale networks spanning multiple brain regions, we recorded data from the prefrontal cortex, parietal cortex, and hippocampus in awake behaving mice, and pooled data from spiking activity and local field potentials into one data matrix. Frequency-specific multivariate decomposition methods revealed a cornucopia of neural networks defined by coherent spatiotemporal patterns over time. These findings reveal a rich, dynamic, and multivariate landscape of large-scale neural activity patterns during foraging behavior.


Author(s):  
Pushpinder Walia ◽  
Abhishek Ghosh ◽  
Shubhmohan Singh ◽  
Anirban Dutta

Background: Maladaptive neuroplasticity related learned response in substance use disorder (SUD) can be ameliorated using non-invasive brain stimulation (NIBS); however, inter-individual variability needs to be addressed for clinical translation. Objective: Our first objective was to develop a hypothesis for NIBS for learned response in SUD based on competing neurobehavioral decision systems model. Next objective was to conduct computational simulation of NIBS of cortico-cerebello-thalamo-cortical (CCTC) loop in cannabis use disorder (CUD) related dysfunctional “cue-reactivity” – a closely related construct of “craving” that is a core symptom. Our third objective was to test the feasibility of our neuroimaging guided rational NIBS approach in healthy humans. Methods: “Cue-reactivity” can be measured using behavioral paradigms and portable neuroimaging, including functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG), metrics of sensorimotor gating. Therefore, we conducted computational simulation of NIBS, including transcranial direct current stimulation(tDCS) and transcranial alternating current stimulation(tACS) of the cerebellar cortex and deep cerebellar nuclei(DCN), of the CCTC loop for its postulated effects on fNIRS and EEG metrics. We also developed a rational neuroimaging guided NIBS approach for cerebellar lobule (VII) and prefrontal cortex based on healthy human study. Results: Simulation study of cerebellar tDCS induced gamma oscillations in the cerebral cortex while tTIS induced gamma-to-beta frequency shift. Experimental fNIRS study found that 2mA cerebellar tDCS evoked similar oxyhemoglobin(HbO) response in-the-range of 5x10-6M across cerebellum and PFC brain regions (=0.01); however, infra-slow (0.01–0.10 Hz) prefrontal cortex HbO driven(phase-amplitude-coupling, PAC) 4Hz, ±2mA (max.) cerebellar tACS evoked HbO in-the-range of 10-7M that was statistically different (=0.01) across those brain regions. Conclusion: Our healthy human study showed the feasibility of fNIRS of cerebellum and PFC as well as fNIRS-driven ctACS at 4Hz that may facilitate cerebellar cognitive function via the frontoparietal network. Future work needs to combine fNIRS with EEG for multi-modal imaging.


2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Atsumichi Tachibana ◽  
J. Adam Noah ◽  
Yumie Ono ◽  
Daisuke Taguchi ◽  
Shuichi Ueda

Abstract Understanding how the brain modulates improvisation has been the focus of numerous studies in recent years. Models have suggested regulation of activity between default mode and executive control networks play a role in improvisational execution. Several studies comparing formulaic to improvised sequences support this framework and document increases in activity in medial frontal lobe with decreased activity in the dorsolateral prefrontal cortex (DLPFC). These patterns can be influenced through training and neural responses may differ between in beginner and expert musicians. Our goal was to test the generalizability of this framework and determine similarity in neural activity in the prefrontal cortex during improvisation. Twenty guitarists performed improvised and formulaic sequences in a blues rock format while brain activity was recorded using functional near-infrared spectroscopy. Results indicate similar modulation in DLPFC as seen previously. Specific decreases of activity from left DLPFC in the end compared to beginning or middle of improvised sequences were also found. Despite the range of skills of participants, we also found significant correlation between subjective feelings of improvisational performance and modulation in left DLPFC. Processing of subjective feelings regardless of skill may contribute to neural modulation and may be a factor in understanding neural activity during improvisation.


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