scholarly journals Functional Neuroimaging and Psychology: What Have You Done for Me Lately?

2013 ◽  
Vol 25 (6) ◽  
pp. 834-842 ◽  
Author(s):  
Joseph M. Moran ◽  
Jamil Zaki
Keyword(s):  
Functional Imaging ◽  
Brain Mapping ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Psychological Theory ◽  
Quarter Century ◽  
Psychological Phenomena ◽  
Neuroimaging Data ◽  
Subsequent Behavior ◽  
Reverse Inference

Functional imaging has become a primary tool in the study of human psychology but is not without its detractors. Although cognitive neuroscientists have made great strides in understanding the neural instantiation of countless cognitive processes, commentators have sometimes argued that functional imaging provides little or no utility for psychologists. And indeed, myriad studies over the last quarter century have employed the technique of brain mapping—identifying the neural correlates of various psychological phenomena—in ways that bear minimally on psychological theory. How can brain mapping be made more relevant to behavioral scientists broadly? Here, we describe three trends that increase precisely this relevance: (i) the use of neuroimaging data to adjudicate between competing psychological theories through forward inference, (ii) isolating neural markers of information processing steps to better understand complex tasks and psychological phenomena through probabilistic reverse inference, and (iii) using brain activity to predict subsequent behavior. Critically, these new approaches build on the extensive tradition of brain mapping, suggesting that efforts in this area—although not initially maximally relevant to psychology—can indeed be used in ways that constrain and advance psychological theory.

scholarly journals Recent advances in functional neuroimaging analysis for cognitive neuroscience

2018 ◽  
Vol 2 ◽  
pp. 239821281775272 ◽  
Author(s):  
Nitin Williams ◽  
Richard N. Henson
Keyword(s):  
Functional Neuroimaging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Recent Analysis ◽  
Temporal Data ◽  
New Methods ◽  
Neuroimaging Data ◽  
The Rich ◽  
Scientific Questions ◽  
The Brain

Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.

scholarly journals Contrasting Cortical Activity Associated with Category Memory and Recognition Memory

1998 ◽  
Vol 5 (6) ◽  
pp. 420-428 ◽  
Author(s):  
Paul J. Reber ◽  
Craig E.L. Stark ◽  
Larry R. Squire
Keyword(s):  
Recognition Memory ◽  
Visual Processing ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Recognition Task ◽  
Occipital Cortex ◽  
Fmri Data ◽  
Categorization Task ◽  
Neuroimaging Data ◽  
Familiar Stimuli

We collected functional neuroimaging data while volunteers performed similar categorization and recognition memory tasks. In the categorization task, volunteers first studied a series of 40 dot patterns that were distortions of a nonstudied prototype dot pattern. After a delay, while fMRI data were collected, they categorized 72 novel dot patterns according to whether or not they belonged to the previously studied category. In the recognition task, volunteers first studied five dot patterns eight times each. After a delay, while fMRI data were collected, they judged whether each of 72 dot patterns had been studied earlier. We found strikingly different patterns of brain activity in visual processing areas for the two tasks. During the categorization task, the familiar stimuli were associated with decreased activity in posterior occipital cortex, whereas during the recognition task, the familiar stimuli were associated with increased activity in this area. The findings indicate that these two types of memory have contrasting effects on early visual processing and reinforce the view that declarative and nondeclarative memory operate independently.

scholarly journals Bridging psychology and genetics using large-scale spatial analysis of neuroimaging and neurogenetic data

2014 ◽  
Author(s):  
Andrew S Fox ◽  
Luke J Chang ◽  
Krzysztof J Gorgolewski ◽  
Tal Yarkoni
Keyword(s):  
Biological Sciences ◽  
Cognitive Processes ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Psychological Phenomena ◽  
Allen Brain ◽  
Neuroimaging Data ◽  
Meta Analyses ◽  
Or Genes ◽  
Novel Associations

Understanding how microscopic molecules give rise to complex cognitive processes is a major goal of the biological sciences. The countless hypothetical molecule-cognition relationships necessitate discovery-based techniques to guide scientists toward the most productive lines of investigation. To this end, we present a novel discovery tool that uses spatial patterns of neural gene expression from the Allen Brain Institute (ABI) and large-scale functional neuroimaging meta-analyses from the Neurosynth framework to bridge neurogenetic and neuroimaging data. We quantified the spatial similarity between over 20,000 genes from the ABI and 48 psychological topics derived from lexical analysis of neuroimaging articles, producing a comprehensive set of gene/cognition mappings that we term the Neurosynth-gene atlas. We demonstrate the ability to independently replicate known gene/cognition associations (e.g., between dopamine and reward), and subsequently use it to identify a range of novel associations between individual molecules or genes and complex psychological phenomena such as reward, memory and emotion. Our results complement existing discovery-based methods such as GWAS, and provide a novel means of generating hypotheses about the neurogenetic substrates of complex cognitive functions.

Functional neuroimaging in neuropsychiatry

2020 ◽  
pp. 95-104
Author(s):  
Robin A. Hurley ◽  
Shane C. Masters ◽  
Katherine H. Taber
Keyword(s):  
Functional Imaging ◽  
Resting State ◽  
Functional Neuroimaging ◽  
Imaging Techniques ◽  
Brain Activity ◽  
Management And Development ◽  
Technical Details ◽  
Neuropsychiatric Conditions ◽  
Multiple Aspect ◽  
Neuroimaging Techniques

Neuroimaging is making increasing contributions to multiple aspect of clinical neuropsychiatry, including differential diagnosis, prognosis, clinical management, and development of new interventions. Functional neuroimaging techniques provide measures that are directly or indirectly related to brain activity. Functional neuroimaging is particularly useful for areas that are dysfunctional but look normal on structural neuroimaging. Evaluation of the resting state also has shown potential for prediction of treatment response in some conditions. In this chapter, the functional imaging techniques available for clinical use are reviewed with respect to their underlying technical details and the advantages and the limitations of each technique. Classic functional imaging findings in the most frequently occurring neuropsychiatric conditions are discussed, as well as examples provided. Future advances in techniques and their possible application to the practice of neuropsychiatry are also summarized.

Theoretical, Statistical, and Practical Perspectives on Pattern-based Classification Approaches to the Analysis of Functional Neuroimaging Data

2007 ◽  
Vol 19 (11) ◽  
pp. 1735-1752 ◽  
Author(s):  
Alice J. O'Toole ◽  
Fang Jiang ◽  
Hervé Abdi ◽  
Nils Pénard ◽  
Joseph P. Dunlop ◽  
...  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Point Of View ◽  
Experimental Conditions ◽  
Theoretical Terms ◽  
Activation Patterns ◽  
Neural Representations ◽  
The Status ◽  
Neuroimaging Data

The goal of pattern-based classification of functional neuroimaging data is to link individual brain activation patterns to the experimental conditions experienced during the scans. These “brain-reading” analyses advance functional neuroimaging on three fronts. From a technical standpoint, pattern-based classifiers overcome fatal f laws in the status quo inferential and exploratory multivariate approaches by combining pattern-based analyses with a direct link to experimental variables. In theoretical terms, the results that emerge from pattern-based classifiers can offer insight into the nature of neural representations. This shifts the emphasis in functional neuroimaging studies away from localizing brain activity toward understanding how patterns of brain activity encode information. From a practical point of view, pattern-based classifiers are already well established and understood in many areas of cognitive science. These tools are familiar to many researchers and provide a quantitatively sound and qualitatively satisfying answer to most questions addressed in functional neuroimaging studies. Here, we examine the theoretical, statistical, and practical underpinnings of pattern-based classification approaches to functional neuroimaging analyses. Pattern-based classification analyses are well positioned to become the standard approach to analyzing functional neuroimaging data.

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.

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 Delta band activity contributes to the identification of command following in disorder of consciousness

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gonzalo Rivera-Lillo ◽  
Emmanuel A. Stamatakis ◽  
Tristan A. Bekinschtein ◽  
David K. Menon ◽  
Srivas Chennu
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Disorder Of Consciousness ◽  
Fine Grained ◽  
Electrical Brain Activity ◽  
Delta Band ◽  
Delta Modulation ◽  
Command Following ◽  
Band Activity

AbstractThe overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.

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