Why the Assessment of Causality in Brain–Behavior Relations Requires Brain Stimulation

2012 ◽  
Vol 24 (4) ◽  
pp. 775-777 ◽  
Author(s):  
Juha Silvanto ◽  
Alvaro Pascual-Leone
Keyword(s):  
Opposite Direction ◽  
Brain Stimulation ◽  
Cognitive Neuroscience ◽  
Neural Activity ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Causal Link ◽  
And Behavior ◽  
Brain Behavior

A central aim in cognitive neuroscience is to explain how neural activity gives rise to perception and behavior; the causal link of paramount interest is thus from brain to behavior. Functional neuroimaging studies, however, tend to provide information in the opposite direction by informing us how manipulation of behavior may affect neural activity. Although this may provide valuable insights into neuronal properties, one cannot use such evidence to make inferences about the behavioral significance of the observed activations; if A causes B, it does not necessarily follow that B causes A. In contrast, brain stimulation techniques enable us to directly modulate brain activity as the source of behavior and thus establish causal links.

Behavior in the Brain

2010 ◽  
Vol 24 (2) ◽  
pp. 76-82 ◽  
Author(s):  
Martin M. Monti ◽  
Adrian M. Owen
Keyword(s):  
Motor Behavior ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Motor Output ◽  
The Unconscious ◽  
Ethical Implications ◽  
Brain Responses ◽  
Minimally Conscious ◽  
Brain Insults ◽  
Brain Behavior

Recent evidence has suggested that functional neuroimaging may play a crucial role in assessing residual cognition and awareness in brain injury survivors. In particular, brain insults that compromise the patient’s ability to produce motor output may render standard clinical testing ineffective. Indeed, if patients were aware but unable to signal so via motor behavior, they would be impossible to distinguish, at the bedside, from vegetative patients. Considering the alarming rate with which minimally conscious patients are misdiagnosed as vegetative, and the severe medical, legal, and ethical implications of such decisions, novel tools are urgently required to complement current clinical-assessment protocols. Functional neuroimaging may be particularly suited to this aim by providing a window on brain function without requiring patients to produce any motor output. Specifically, the possibility of detecting signs of willful behavior by directly observing brain activity (i.e., “brain behavior”), rather than motoric output, allows this approach to reach beyond what is observable at the bedside with standard clinical assessments. In addition, several neuroimaging studies have already highlighted neuroimaging protocols that can distinguish automatic brain responses from willful brain activity, making it possible to employ willful brain activations as an index of awareness. Certainly, neuroimaging in patient populations faces some theoretical and experimental difficulties, but willful, task-dependent, brain activation may be the only way to discriminate the conscious, but immobile, patient from the unconscious one.

scholarly journals Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior

2019 ◽  
Author(s):  
Jennifer Stiso ◽  
Marie-Constance Corsi ◽  
Javier Omar Garcia ◽  
Jean M Vettel ◽  
Fabrizio De Vico Fallani ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Activity ◽  
Brain Computer Interface ◽  
Distributed Networks ◽  
Motor Dysfunction ◽  
Computer Interface ◽  
Specific Method ◽  
Temporal Expression ◽  
And Behavior ◽  
Brain Behavior

Motor imagery-based brain-computer interfaces (BCIs) use an individual’s ability to volitionally modulate localized brain activity, often as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However, many individuals cannot learn to successfully modulate their brain activity, greatly limiting the efficacy of BCI for therapy and for basic scientific inquiry. Formal experiments designed to probe the nature of BCI learning have offered initial evidence that coherent activity across diverse cognitive systems is a hallmark of individuals who can successfully learn to control the BCI. However, little is known about how these distributed networks interact through time to support learning. Here, we address this gap in knowledge by constructing and applying a multimodal network approach to decipher brain-behavior relations in motor imagery-based brain-computer interface learning using magnetoencephalography. Specifically, we employ a minimally constrained matrix decomposition method -- non-negative matrix factorization -- to simultaneously identify regularized, covarying subgraphs of functional connectivity and behavior, and to detect the time-varying expression of each subgraph. We find that learning is marked by distributed brain-behavior relations: swifter learners displayed many subgraphs whose temporal expression tracked performance. Learners also displayed marked variation in the spatial properties of subgraphs such as the connectivity between the frontal lobe and the rest of the brain, and in the temporal properties of subgraphs such as the stage of learning at which they reached maximum expression. From these observations, we posit a conceptual model in which certain subgraphs support learning by modulating brain activity in networks important for sustaining attention. After formalizing the model in the framework of network control theory, we test the model and find that good learners display a single subgraph whose temporal expression tracked performance and whose architecture supports easy modulation of brain regions important for attention. The nature of our contribution to the neuroscience of BCI learning is therefore both computational and theoretical; we first use a minimally-constrained, individual specific method of identifying mesoscale structure in dynamic brain activity to show how global connectivity and interactions between distributed networks supports BCI learning, and then we use a formal network model of control to lend theoretical support to the hypothesis that these identified subgraphs are well suited to modulate attention.

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.

scholarly journals A Role for Endogenous Brain States in Organizational Research: Moving Toward a Dynamic View of Cognitive Processes

2017 ◽  
Vol 22 (1) ◽  
pp. 332-353 ◽  
Author(s):  
Sven Braeutigam ◽  
Nick Lee ◽  
Carl Senior
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Neural System ◽  
Reactive System ◽  
Organizational Research ◽  
Dynamic View ◽  
Brain States ◽  
Living Organisms ◽  
And Behavior ◽  
Intrinsic Brain Activity

The dominant view in neuroscience, including functional neuroimaging, is that the brain is an essentially reactive system, in which some sensory input causes some neural activity, which in turn results in some important response such as a motor activity or some hypothesized higher-level cognitive or affective process. This view has driven the rise of neuroscience methods in management and organizational research. However, the reactive view offers at best a partial understanding of how living organisms function in the real world. In fact, like any neural system, the human brain exhibits a constant ongoing activity. This intrinsic brain activity is produced internally, not in response to some environmental stimulus, and is thus termed endogenous brain activity (EBA). In the present article we introduce EBA to organizational research conceptually, explain its measurement, and go on to show that including EBA in management and organizational theory and empirical research has the potential to revolutionize how we think about human choice and behavior in organizations.

scholarly journals Inferring Causality from Noninvasive Brain Stimulation in Cognitive Neuroscience

2021 ◽  
Vol 33 (2) ◽  
pp. 195-225 ◽  
Author(s):  
Til Ole Bergmann ◽  
Gesa Hartwigsen
Keyword(s):  
Brain Stimulation ◽  
Cognitive Neuroscience ◽  
Brain Activity ◽  
Sensory Stimulation ◽  
Causal Chain ◽  
Behavioral Measure ◽  
Noninvasive Brain Stimulation ◽  
Confounding Variables ◽  
Remote Sites ◽  
Stimulation Experiments

Noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation or transcranial direct and alternating current stimulation, are advocated as measures to enable causal inference in cognitive neuroscience experiments. Transcending the limitations of purely correlative neuroimaging measures and experimental sensory stimulation, they allow to experimentally manipulate brain activity and study its consequences for perception, cognition, and eventually, behavior. Although this is true in principle, particular caution is advised when interpreting brain stimulation experiments in a causal manner. Research hypotheses are often oversimplified, disregarding the underlying (implicitly assumed) complex chain of causation, namely, that the stimulation technique has to generate an electric field in the brain tissue, which then evokes or modulates neuronal activity both locally in the target region and in connected remote sites of the network, which in consequence affects the cognitive function of interest and eventually results in a change of the behavioral measure. Importantly, every link in this causal chain of effects can be confounded by several factors that have to be experimentally eliminated or controlled to attribute the observed results to their assumed cause. This is complicated by the fact that many of the mediating and confounding variables are not directly observable and dose–response relationships are often nonlinear. We will walk the reader through the chain of causation for a generic cognitive neuroscience NIBS study, discuss possible confounds, and advise appropriate control conditions. If crucial assumptions are explicitly tested (where possible) and confounds are experimentally well controlled, NIBS can indeed reveal cause–effect relationships in cognitive neuroscience studies.

Beyond establishing involvement: quantifying the contribution of anticipatory α- and β-band suppression to perceptual improvement with attention

2012 ◽  
Vol 108 (9) ◽  
pp. 2352-2362 ◽  
Author(s):  
Freek van Ede ◽  
Malte Köster ◽  
Eric Maris
Keyword(s):  
Cognitive Neuroscience ◽  
Brain Activity ◽  
Detection Task ◽  
Attentional Orienting ◽  
Neural Signals ◽  
Upper Limit ◽  
Neurophysiological Mechanisms ◽  
Novel Method ◽  
Human Participants ◽  
And Behavior

Systems and cognitive neuroscience aim at understanding the neurophysiological mechanisms that underlie cognition and behavior. Many studies have revealed the involvement of many types of neural signals in diverse cognitive and behavioral phenomena. Here, we go beyond establishing such involvement and address two fundamental, yet largely unaddressed, questions: 1) exactly how much does a given neural signal contribute to a cognitive or behavioral phenomenon of interest; and 2) to what extent are distinct neural signals independently related to this phenomenon? We recorded brain activity using magnetoencephalography while human participants performed a cued somatosensory detection task. Using a novel method, we then quantified the contribution (in a predictive but not causal sense) of two well-established neural phenomena to the improvement in perception with attentional orienting. In our sample, the anticipatory suppression of extracranially recorded oscillatory α- and β-band amplitudes from contralateral primary somatosensory cortex could account for maximally 29% of the attention-induced improvement in tactile perception. In addition, although amplitude suppressions in the α- and β-frequency bands both contributed to this improvement, their contribution was largely shared. These data reveal the upper limit of the cognitive/behavioral relevance of this type of signal and show that at least 71% of the perceptual improvement with attention must be accounted for by other signals.

scholarly journals Individualizing Representational Similarity Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Seth M. Levine ◽  
Jens V. Schwarzbach
Keyword(s):  
Individual Differences ◽  
Cognitive Neuroscience ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Similarity Analysis ◽  
Representational Similarity Analysis ◽  
Analysis Technique ◽  
Neuroimaging Data ◽  
Translational Studies ◽  
Transfer Of Information

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.

scholarly journals Focal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Kartik K. Iyer ◽  
Kai Hwang ◽  
Luke J. Hearne ◽  
Eli Muller ◽  
Mark D’Esposito ◽  
...  
Keyword(s):  
Working Memory ◽  
Neural Activity ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Memory Performance ◽  
Functional Link ◽  
Low Dimensional Topology ◽  
Brain Functions ◽  
Human Participants ◽  
Low Dimensional

AbstractThe emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain’s low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

If a picture is worth a thousand words, how many pictures is a word worth?

1995 ◽  
Vol 18 (2) ◽  
pp. 367-368 ◽  
Author(s):  
Ken A. Paller
Keyword(s):  
Cognitive Neuroscience ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Normal Brain ◽  
Human Thought ◽  
Neurocognitive Functions ◽  
Spatial Dimensions ◽  
Temporal And Spatial

AbstractPictures of normal brain activity during human thought can be worth a great deal. Electrophysiology and functional neuroimaging together allow both temporal and spatial dimensions of neurocognitive functions to be explored. Although these techniqueshave their limitations, the Cognitive Neuroscience approach is well-suited to pursuing questions about how words are perceived, understood, and remembered.

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