scholarly journals Mirror neuron: a beautiful unnecessary concept

2021 ◽  
Vol 11 (6) ◽  
pp. 172-174
Author(s):  
Jahan N Schad
Keyword(s):  
Mirror Neurons ◽  
Brain Activity ◽  
Activity Patterns ◽  
Mirror Neuron ◽  
Prima Facie ◽  
Living Environment ◽  
Intentional Stance ◽  
Neural Structure ◽  
Tactile Input ◽  
The Brain

Mirror neurons theory, which had been put forward in the eighties based on the results of cognitive research experiments on the macaque monkeys, has prima facie been further validated by the extensive cognitive neurosciences investigations of primates and humans, over the past three decades. The concept was initially prompted by the fact that the brain activity patterns of the subjects were nearly similar, whether the activity was performed or observed by them. And presently, learning of various natures and empathy, and perhaps some aspects of survival, are ascribed to the operations of this class of neurons. Obviously the added complexity on the already complex field of neurosciences cannot be underestimated; and of course there are opponents of the theory, and some profound questions have been raised. Present work, though also in opposition, is based on completely different ground: the fact that the ingenious and grand efforts of the proponents of the theory can be explicated in the realm of the established neural structure of the brain and its computational operations. This possibility is based on the recent discovery of the tactile nature of the vision sensation. Ironically all the results, which form the basis of the mirror neuron concept, also serve to provide the conceptual proof of the new vision theory, which preempts any need for the introduction of the new class of neurons. The vision theory, partially validated through the efforts of the development of the tactile vision substitution systems (TVSS) and ironically also by some to the point mirror neuron experimental works, are sufficient to explain the processes behind empathy, learning and perhaps other mental phenomena; and as such, the need for presumption of additional class of neurons is dispelled. The mental phenomena, which rendered the claim of the mirror neurons, are simply the consequence of subjects beings variably touched by the state of the living environment, through the coherent tactile operation of all senses (four already known as having tactile nature); eyes having the most prominent role: It is the brain’s response (the computations outputs) as motor cortex activity,-- subsequent to the discernment of the streaming massive tactile input data, to appropriately coordinate the observer’s perceived (tactile) engagement, conditioned by the her mental intentional stance sourced in the brain’s protocols (acquired neural patterns)--which is misinterpreted as the evidence for the conceptualization of the mirror neuron.

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 A "global" network dysfunction in the mirror neuron system in autism is modulated by task complexity and age: A meta-analysis of neuroimaging studies

2020 ◽  
Author(s):  
Mei Yan Melody Chan ◽  
Yvonne M.Y. Han
Keyword(s):  
Mirror Neurons ◽  
Task Complexity ◽  
Mirror Neuron System ◽  
Meta Analysis ◽  
Mirror Neuron ◽  
Brain Regions ◽  
Local Network ◽  
Activation Patterns ◽  
Neuron System ◽  
The Brain

Abstract Background Impaired imitation has been found to be an important factor contributing to social communication deficits in individuals with autism spectrum disorder (ASD). It has been hypothesized that the neural correlates of imitation, the mirror neuron system (MNS), are dysfunctional in ASD, resulting in imitation impairment as one of the key behavioral manifestations in ASD. Previous MNS studies produced inconsistent results, leaving the debate of whether mirror neurons are “broken” in ASD unresolved.Methods This meta-analysis aimed to explore the differences in MNS activation patterns between typically developing (TD) and ASD individuals when they observe/imitate biological motions with/without emotional components. Effect-size signed differential mapping (ES-SDM) was adopted to synthesize the available fMRI data. Results The MNS is dysfunctional in ASD; not only the brain regions containing mirror neurons were affected, the brain regions supporting MNS functioning were also impaired. Second, MNS dysfunction in ASD is modulated by task complexity; differential activation patterns during the presentation of “cold” and “hot” stimuli might be a result of atypical functional connectivity in ASD. Third, MNS dysfunction in ASD individuals is modulated by age. MNS regions were found to show delayed maturation; abnormal lateralization development in some of the brain regions also contributed to the atypical development of the MNS in ASD. Limitations We have attempted to include a comprehensive set of original data for this analysis. However, whole brain analysis data were not obtainable from some of the published papers, these studies could not be included as a result. Moreover, the results indicating the age effect on MNS in ASD could only be generalized to individuals aged 11-37, as MNS activation remains unstudied for populations beyond this age range. Also, the ES-SDM linear regression modelling might not be ideal to illustrate the associations between age and MNS activation; the meta-regression results should be treated with caution. Conclusion There is a “global” rather than a “local” network dysfunction, which may underlie the imitation impairments in individuals with ASD. Task complexity and age modulate the functioning of the MNS, which may explain the previous peculiar results contributing to the unresolved “broken mirror neuron” debate.

scholarly journals Sensory-modality independent activation of the brain network for language

2019 ◽  
Author(s):  
Sophie Arana ◽  
André Marquand ◽  
Annika Hultén ◽  
Peter Hagoort ◽  
Jan-Mathijs Schoffelen
Keyword(s):  
Language Processing ◽  
Sentence Processing ◽  
Human Subjects ◽  
Brain Activity ◽  
Activity Patterns ◽  
Sensory Modality ◽  
Brain Network ◽  
Large Network ◽  
Individual Subject ◽  
The Brain

AbstractThe meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neuromagnetic brain signals of 200 human subjects (102 males) either reading or listening to sentences. We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations, consistent across subjects and at a fine temporal scale. Quantifying this consistency in activation across both reading and listening tasks revealed a mostly left hemispheric cortical network. Areas showing consistent activity patterns include not only areas previously implicated in higher-level language processing, such as left prefrontal, superior & middle temporal areas and anterior temporal lobe, but also parts of the control-network as well as subcentral and more posterior temporal-parietal areas. Activity in this supramodal sentence processing network starts in temporal areas and rapidly spreads to the other regions involved. The findings do not only indicate the involvement of a large network of brain areas in supramodal language processing, but also indicate that the linguistic information contained in the unfolding sentences modulates brain activity in a word-specific manner across subjects.

scholarly journals Other people’s gaze encoded as implied motion in the human brain

2020 ◽  
Vol 117 (23) ◽  
pp. 13162-13167 ◽  
Author(s):  
Arvid Guterstam ◽  
Andrew I. Wilterson ◽  
Davis Wachtell ◽  
Michael S. A. Graziano
Keyword(s):  
Social Cognition ◽  
Theory Of Mind ◽  
Visual Motion ◽  
Brain Activity ◽  
Activity Patterns ◽  
Human Motion ◽  
Fundamental Aspect ◽  
Implied Motion ◽  
Motion System ◽  
The Brain

Keeping track of other people’s gaze is an essential task in social cognition and key for successfully reading other people’s intentions and beliefs (theory of mind). Recent behavioral evidence suggests that we construct an implicit model of other people’s gaze, which may incorporate physically incoherent attributes such as a construct of force-carrying beams that emanate from the eyes. Here, we used functional magnetic resonance imaging and multivoxel pattern analysis to test the prediction that the brain encodes gaze as implied motion streaming from an agent toward a gazed-upon object. We found that a classifier, trained to discriminate the direction of visual motion, significantly decoded the gaze direction in static images depicting a sighted face, but not a blindfolded one, from brain activity patterns in the human motion-sensitive middle temporal complex (MT+) and temporo-parietal junction (TPJ). Our results demonstrate a link between the visual motion system and social brain mechanisms, in which the TPJ, a key node in theory of mind, works in concert with MT+ to encode gaze as implied motion. This model may be a fundamental aspect of social cognition that allows us to efficiently connect agents with the objects of their attention. It is as if the brain draws a quick visual sketch with moving arrows to help keep track of who is attending to what. This implicit, fluid-flow model of other people’s gaze may help explain culturally universal myths about the mind as an energy-like, flowing essence.

scholarly journals Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis

2016 ◽  
Author(s):  
Jörn Diedrichsen ◽  
Nikolaus Kriegeskorte
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Similarity Analysis ◽  
Mathematical Framework ◽  
Advantages And Disadvantages ◽  
Representational Similarity Analysis ◽  
Powerful Test ◽  
Activity Measurements ◽  
The Brain ◽  
Representational Models

AbstractRepresentational models specify how activity patterns in populations of neurons (or, more generally, in multivariate brain-activity measurements) relate to sensory stimuli, motor responses, or cognitive processes. In an experimental context, representational models can be defined as hypotheses about the distribution of activity profiles across experimental conditions. Currently, three different methods are being used to test such hypotheses: encoding analysis, pattern component modeling (PCM), and representational similarity analysis (RSA). Here we develop a common mathematical framework for understanding the relationship of these three methods, which share one core commonality: all three evaluate the second moment of the distribution of activity profiles, which determines the representational geometry, and thus how well any feature can be decoded from population activity with any readout mechanism capable of a linear transform. Using simulated data for three different experimental designs, we compare the power of the methods to adjudicate between competing representational models. PCM implements a likelihood-ratio test and therefore provides the most powerful test if its assumptions hold. However, the other two approaches – when conducted appropriately – can perform similarly. In encoding analysis, the linear model needs to be appropriately regularized, which effectively imposes a prior on the activity profiles. With such a prior, an encoding model specifies a well-defined distribution of activity profiles. In RSA, the unequal variances and statistical dependencies of the dissimilarity estimates need to be taken into account to reach near-optimal power in inference. The three methods render different aspects of the information explicit (e.g. single-response tuning in encoding analysis and population-response representational dissimilarity in RSA) and have specific advantages in terms of computational demands, ease of use, and extensibility. The three methods are properly construed as complementary components of a single data-analytical toolkit for understanding neural representations on the basis of multivariate brain-activity data.Author SummaryModern neuroscience can measure activity of many neurons or the local blood oxygenation of many brain locations simultaneously. As the number of simultaneous measurements grows, we can better investigate how the brain represents and transforms information, to enable perception, cognition, and behavior. Recent studies go beyond showing that a brain region is involved in some function. They use representational models that specify how different perceptions, cognitions, and actions are encoded in brain-activity patterns. In this paper, we provide a general mathematical framework for such representational models, which clarifies the relationships between three different methods that are currently used in the neuroscience community. All three methods evaluate the same core feature of the data, but each has distinct advantages and disadvantages. Pattern component modelling (PCM) implements the most powerful test between models, and is analytically tractable and expandable. Representational similarity analysis (RSA) provides a highly useful summary statistic (the dissimilarity) and enables model comparison with weaker distributional assumptions. Finally, encoding models characterize individual responses and enable the study of their layout across cortex. We argue that these methods should be considered components of a larger toolkit for testing hypotheses about the way the brain represents information.

scholarly journals Temporo-parietal cortex involved in modeling one’s own and others’ attention

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

In a traditional view, in social cognition, attention is equated with gaze and people track other people’s attention by tracking their gaze. Here, we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.

scholarly journals Translation of Brain Activity Patterns of a user into Commands using Electroencephalography (EEG)

2021 ◽  
pp. 62-68
Author(s):  
Ranjana B. Jadekar ◽  
A. R. Sindhu ◽  
M. T. Vinay
Keyword(s):  
Environmental Control ◽  
Brain Activity ◽  
Activity Patterns ◽  
Eeg Signals ◽  
Computer Interfaces ◽  
Control Option ◽  
Electrophysiological Signals ◽  
Interactive Application ◽  
The Brain ◽  
Bci System

Brain-Computer Interfaces (BCI) are systems that can translate the brain activity patterns of a user into messages or commands for an interactive application. The brain activity which is processed by the BCI systems is usually measured using Electroencephalography (EEG). The BCI system uses oscillatory Electroencephalography (EEG) signals, recorded using specific mental activity, as input and provides a control option by its output. A brain-computer interface uses electrophysiological signals to control the remote devices. They consist of electrodes applied to the scalp of an individual or worn in an electrode cap. The computer processes the EEG signals and uses it in order to accomplish tasks such as communication and environmental control.

scholarly journals Stimulation-specific information is represented as local activity patterns across the brain

2019 ◽  
Author(s):  
Amirouche Sadoun ◽  
Tushar Chauhan ◽  
Samir Mameri ◽  
Yifan Zhang ◽  
Pascal Barone ◽  
...  
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Three Dimensional ◽  
Correlation Method ◽  
Brain Regions ◽  
Specific Information ◽  
Spatially Correlated ◽  
Face Area ◽  
Spatial Configurations ◽  
The Brain

AbstractModern neuroimaging represents three-dimensional brain activity, which varies across brain regions. It remains unknown whether activity within brain regions is organized in spatial configurations to reflect perceptual and cognitive processes. We developed a rotational cross-correlation method allowing a straightforward analysis of spatial activity patterns for the precise detection of the spatially correlated distributions of brain activity. Using several statistical approaches, we found that the seed patterns in the fusiform face area were robustly correlated to brain regions involved in face-specific representations. These regions differed from the non-specific visual network meaning that activity structure in the brain is locally preserved in stimulation-specific regions. Our findings indicate spatially correlated perceptual representations in cerebral activity and suggest that the 3D coding of the processed information is organized in locally preserved activity patterns. More generally, our results provide the first demonstration that information is represented and transmitted as local spatial configurations of brain activity.

scholarly journals Temporo-Parietal Cortex Involved in Modeling One’s Own and Others’ Attention

2020 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael SA Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

AbstractIn a traditional view, in social cognition, attention is equated with gaze and people track attention by tracking other people’s gaze. Here we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.Impact statementThis study used fMRI to show that the human brain encodes other people’s attention in enough richness to distinguish whether that attention was directed exogenously (stimulus-driven) or endogenously (internally driven).

The brain represents people as the mental states they habitually experience

2018 ◽  
Author(s):  
Mark Allen Thornton ◽  
Miriam E. Weaverdyck ◽  
Diana Tamir
Keyword(s):  
Social Life ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Activity Patterns ◽  
Reaction Times ◽  
Mental States ◽  
Weighted Sums ◽  
Famous Person ◽  
Binary Choices ◽  
The Brain

Social life requires us to treat each person according to their unique disposition: habitually enthusiastic friends need occasional grounding, whereas pessimistic colleagues require cheering-up. To tailor our behavior to specific individuals, we must represent their idiosyncrasies. Here we advance a hypothesis about how the brain achieves this goal: our representations of other people reflect the mental states we perceive those people to habitually experience. That is, rather than representing other people via traits, our brains represent people as the sums of their states. For example, if a perceiver observes that another person is frequently cheerful, sometimes thoughtful, and rarely grumpy, the perceiver’s representation of that person will be comprised of their representations of the mental states cheerfulness, thoughtfulness, and grumpiness, combined in a corresponding ratio. We tested this hypothesis by measuring whether neural representations of people could be accurately reconstructed by summing state representations. Separate participants underwent functional neuroimaging while considering famous individuals and individual mental states. Online participants rated how often each famous person experiences each state. Results supported the summed state hypothesis: frequency-weighted sums of state-specific brain activity patterns accurately reconstructed person-specific patterns. Moreover, the summed state account outperformed the established alternative – that people represent others using trait dimensions – in explaining interpersonal similarity, as measured through neural patterns, explicit ratings, binary choices, reaction times, and the semantics of biographical text. Together these findings demonstrate that the brain represents other people as the sums of the mental states they are perceived to experience.

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