“Grammar box” in the brain

2003 ◽  
Vol 26 (6) ◽  
pp. 672-673
Author(s):  
Valéria Csépe
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Neural Correlates ◽  
Modular Architecture ◽  
Activity Data ◽  
The Brain ◽  
Semantic Domains

Brain activity data prove the existence of qualitatively different structures in the brain. However, the question is whether the human brain acts as linguists assume in their models. The modular architecture of grammar that has been claimed by many linguists raises some empirical questions. One of the main questions is whether the threefold abstract partition of language (into syntactic, phonological, and semantic domains) has distinct neural correlates.

scholarly journals Inferring brain-computational mechanisms with models of activity measurements

2016 ◽  
Vol 371 (1705) ◽  
pp. 20160278 ◽  
Author(s):  
Nikolaus Kriegeskorte ◽  
Jörn Diedrichsen
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Summary Statistics ◽  
Activity Data ◽  
Individual Measurement ◽  
Activity Measurements ◽  
The Brain ◽  
The Way

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

Mortal Body, Immortal Mind

2012 ◽  
Vol 17 (1) ◽  
pp. 5-26
Author(s):  
Hans Goller
Keyword(s):  
Brain Activity ◽  
The Body ◽  
Activity Data ◽  
Brain Functions ◽  
Body Experiences ◽  
Research Findings ◽  
The Relationship ◽  
Near Death Experiences ◽  
The Brain ◽  
Alternative Theories

Neuroscientists keep telling us that the brain produces consciousness and consciousness does not survive brain death because it ceases when brain activity ceases. Research findings on near-death-experiences during cardiac arrest contradict this widely held conviction. They raise perplexing questions with regard to our current understanding of the relationship between consciousness and brain functions. Reports on veridical perceptions during out-of-body experiences suggest that consciousness may be experienced independently of a functioning brain and that self-consciousness may continue even after the termination of brain activity. Data on studies of near-death-experiences could be an incentive to develop alternative theories of the body-mind relation as seen in contemporary neuroscience.

scholarly journals Estimation of the Directions of Alpha Rhythm Elementary Sources Using the Method of Human Brain Functional Tomography Based On the Magnetic Encephalography Data

2018 ◽  
Vol 13 (2) ◽  
pp. 426-436 ◽  
Author(s):  
M.N. Ustinin ◽  
S.D. Rykunov ◽  
A.I. Boyko ◽  
O.A. Maslova ◽  
K.D. Walton ◽  
...  
Keyword(s):  
Inverse Problem ◽  
Time Series ◽  
Human Brain ◽  
Alpha Rhythm ◽  
Brain Activity ◽  
Problem Solution ◽  
New York University ◽  
Magnetic Encephalography ◽  
The Brain ◽  
Calculation Grid

New method for the magnetic encephalography data analysis was proposed. The method transforms multichannel time series into the spatial structure of the human brain activity. In this paper we further develop this method to determine the dominant direction of the electrical sources of brain activity at each node of the calculation grid. We have considered the experimental data, obtained with three 275-channel magnetic encephalographs in New York University, McGill University and Montreal University. The human alpha rhythm phenomenon was selected as a model object. Magnetic encephalograms of the brain spontaneous activity were registered for 5-7 minutes in magnetically shielded room. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. For all spectral components, the inverse problem was solved in elementary current dipole model and the functional structure of the brain activity was calculated in the frequency band 8-12 Hz. In order to estimate the local activity direction, at the each node of calculation grid the vector of the inverse problem solution was selected, having the maximal spectral power. So, the 3D-map of the brain activity vector field was produced – the directional functional tomogram. Such maps were generated for 15 subjects and some common patterns were revealed in the directions of the alpha rhythm elementary sources. The proposed method can be used to study the local properties of the brain activity in any spectral band and in any brain compartment.

scholarly journals Sleeping While Awake: The Intrusion of Neural Activity Associated with Sleep Onset in the Awake Human Brain

2020 ◽  
Author(s):  
Stephanie Hawes ◽  
Carrie R. H. Innes ◽  
Nicholas Parsons ◽  
Sean P.A. Drummond ◽  
Karen Caeyensberghs ◽  
...  
Keyword(s):  
Human Brain ◽  
Basal Forebrain ◽  
Brain Activity ◽  
Cognitive Task ◽  
Sleep Onset ◽  
Theoretical Modelling ◽  
Related Activity ◽  
Independent Dataset ◽  
Time Graph ◽  
The Brain

AbstractSleep can intrude into the awake human brain when sleep deprived or fatigued, even while performing cognitive tasks. However, how the brain activity associated with sleep onset can co-exist with the activity associated with cognition in the awake humans remains unexplored. Here, we used simultaneous fMRI and EEG to generate fMRI activity maps associated with EEG theta (4-7 Hz) activity associated with sleep onset. We implemented a method to track these fMRI activity maps in individuals performing a cognitive task after well-rested and sleep-deprived nights. We found frequent intrusions of the fMRI maps associated with sleep-onset in the task-related fMRI data. These sleep events elicited a pattern of transient fMRI activity, which was spatially distinct from the task-related activity in the frontal and parietal areas of the brain. They were concomitant with reduced arousal as indicated by decreased pupil size and increased response time. Graph theoretical modelling showed that the activity associated with sleep onset emerges from the basal forebrain and spreads anterior-posteriorly via the brain’s structural connectome. We replicated the key findings in an independent dataset, which suggests that the approach can be reliably used in understanding the neuro-behavioural consequences of sleep and circadian disturbances in humans.

Is Artistic Composition in Abstract Art Detected Automatically?

2021 ◽  
pp. 102-106
Author(s):  
Claudia Menzel ◽  
Gyula Kovács ◽  
Gregor U. Hayn-Leichsenring ◽  
Christoph Redies
Keyword(s):  
Human Brain ◽  
Significant Role ◽  
Mismatch Negativity ◽  
Brain Activity ◽  
Perceptual Processing ◽  
Abstract Art ◽  
Electrical Brain Activity ◽  
Image Set ◽  
The Brain

Most artists who create abstract paintings place the pictorial elements not at random, but arrange them intentionally in a specific artistic composition. This arrangement results in a pattern of image properties that differs from image versions in which the same pictorial elements are randomly shuffled. In the article under discussion, the original abstract paintings of the author’s image set were rated as more ordered and harmonious but less interesting than their shuffled counterparts. The authors tested whether the human brain distinguishes between these original and shuffled images by recording electrical brain activity in a particular paradigm that evokes a so-called visual mismatch negativity. The results revealed that the brain detects the differences between the two types of images fast and automatically. These findings are in line with models that postulate a significant role of early (low-level) perceptual processing of formal image properties in aesthetic evaluations.

scholarly journals Change Is Good for the Brain: Activity Diversity and Cognitive Functioning Across Adulthood

2020 ◽  
Author(s):  
Soomi Lee ◽  
Susan T Charles ◽  
David M Almeida
Keyword(s):  
Executive Functioning ◽  
Cognitive Functioning ◽  
Brain Activity ◽  
Paid Work ◽  
Work Time ◽  
Activity Data ◽  
Future Work ◽  
Increased Activity ◽  
The Brain ◽  
Cognitive Data

Abstract Objectives Participating in a variety of daily activities (i.e., activity diversity) requires people to adjust to a variety of situations and engage in a greater diversity of behaviors. These experiences may, in turn, enhance cognitive functioning. This study examined associations between activity diversity and cognitive functioning across adulthood. Method Activity diversity was defined as the breadth and evenness of participation in seven common daily activity domains (e.g., paid work, time with children, leisure, physical activities, volunteering). Participants from the National Survey of Daily Experiences (NSDE: N = 732, Mage = 56) provided activity data during eight consecutive days at Wave 1 (W1) and Wave 2 (W2) 10 years apart. They also provided cognitive data at W2. Results Greater activity diversity at W2 was associated with higher overall cognitive functioning and higher executive functioning at W2. Individuals who increased activity diversity from W1 to W2 also exhibited higher scores in overall cognitive functioning and executive functioning at W2. Overall cognitive functioning, executive functioning, and episodic memory were better in those who had higher activity diversity at both waves, or increased activity diversity from W1 to W2, compared to those who had lower activity diversity or decreased activity diversity over time. Discussion Activity diversity is important for cognitive health in adulthood. Future work can study the directionality between activity diversity and cognitive functioning and underlying social and neurological mechanisms for these associations.

Is the human brain only responsive?

1995 ◽  
Vol 18 (2) ◽  
pp. 365-366
Author(s):  
Rumyana Kristeva-Feige ◽  
Bernd Feige
Keyword(s):  
Human Brain ◽  
Spontaneous Activity ◽  
Cognitive Functions ◽  
Evoked Potential ◽  
Imaging Techniques ◽  
Brain Activity ◽  
External Events ◽  
Potential Methods ◽  
The Brain

AbstractPosner & Raichle's (1994) book is a fascinating and readable account of the studies the authors have conducted on the localization of cognitive functions in the brain mainly using PET and EEC evoked potential methods. Our criticism concerns the underrepresentation of some imaging techniques (magnetoencephalography) and some forms of brain activity (spontaneous activity). Furthermore, the book leaves the reader with the impression that the brain only responds to external events.

scholarly journals Pain Prediction in Humans using Human Brain Activity Data

2018 ◽  
Author(s):  
Zara Mansoor ◽  
Mustansar Ali Ghazanfar ◽  
Syed Muhammad Anwar ◽  
Ahmed S. Alfakeeh ◽  
Khaled H. Alyoubi
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Activity Data ◽  
Pain Prediction

scholarly journals Dissociating Neural Correlates of Action Monitoring and Metacognition of Agency

2011 ◽  
Vol 23 (11) ◽  
pp. 3620-3636 ◽  
Author(s):  
David B. Miele ◽  
Tor D. Wager ◽  
Jason P. Mitchell ◽  
Janet Metcalfe
Keyword(s):  
Brain Activity ◽  
Dorsal Striatum ◽  
Neural Correlates ◽  
Action Monitoring ◽  
Fmri Study ◽  
Metacognitive Judgments ◽  
The Right ◽  
Reflective Processing ◽  
Increased Activity ◽  
The Brain

Judgments of agency refer to people's self-reflective assessments concerning their own control: their assessments of the extent to which they themselves are responsible for an action. These self-reflective metacognitive judgments can be distinguished from action monitoring, which involves the detection of the divergence (or lack of divergence) between observed states and expected states. Presumably, people form judgments of agency by metacognitively reflecting on the output of their action monitoring and then consciously inferring the extent to which they caused the action in question. Although a number of previous imaging studies have been directed at action monitoring, none have assessed judgments of agency as a potentially separate process. The present fMRI study used an agency paradigm that not only allowed us to examine the brain activity associated with action monitoring but that also enabled us to investigate those regions associated with metacognition of agency. Regarding action monitoring, we found that being “out of control” during the task (i.e., detection of a discrepancy between observed and expected states) was associated with increased brain activity in the right TPJ, whereas being “in control” was associated with increased activity in the pre-SMA, rostral cingulate zone, and dorsal striatum (regions linked to self-initiated action). In contrast, when participants made self-reflective metacognitive judgments about the extent of their own control (i.e., judgments of agency) compared with when they made judgments that were not about control (i.e., judgments of performance), increased activity was observed in the anterior PFC, a region associated with self-reflective processing. These results indicate that action monitoring is dissociable from people's conscious self-attributions of control.

scholarly journals Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain

2020 ◽  
Author(s):  
Sreejan Kumar ◽  
Cameron T. Ellis ◽  
Thomas O’Connell ◽  
Marvin M Chun ◽  
Nicholas B. Turk-Browne
Keyword(s):  
Human Brain ◽  
Language Processing ◽  
Brain Function ◽  
Computational Models ◽  
Brain Activity ◽  
Functional Space ◽  
Semantic Features ◽  
Brain Functions ◽  
Auditory Features ◽  
The Brain

AbstractThe extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model are more widely distributed across the brain than previously acknowledged. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.

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