Attention to Detail: Why Considering Task Demands Is Essential for Single-Trial Analysis of BOLD Correlates of the Visual P1 and N1

2014 ◽  
Vol 26 (3) ◽  
pp. 529-542 ◽  
Author(s):  
Tracy Warbrick ◽  
Jorge Arrubla ◽  
Franks Boers ◽  
Irene Neuner ◽  
N. Jon Shah
Keyword(s):  
Response Selection ◽  
Sensory Information ◽  
Prediction Method ◽  
Brain Regions ◽  
Task Demands ◽  
Fmri Data ◽  
Single Trial ◽  
Oddball Task ◽  
Sensory Encoding ◽  
Visual Oddball

Single-trial fluctuations in the EEG signal have been shown to temporally correlate with the fMRI BOLD response and are valuable for modeling trial-to-trial fluctuations in responses. The P1 and N1 components of the visual ERP are sensitive to different attentional modulations, suggesting that different aspects of stimulus processing can be modeled with these ERP parameters. As such, different patterns of BOLD covariation for P1 and N1 informed regressors would be expected; however, current findings are equivocal. We investigate the effects of variations in attention on P1 and N1 informed BOLD activation in a visual oddball task. Simultaneous EEG-fMRI data were recorded from 13 healthy participants during three conditions of a visual oddball task: Passive, Count, and Respond. We show that the P1 and N1 components of the visual ERP can be used in the integration-by-prediction method of EEG-fMRI data integration to highlight brain regions related to target detection and response production. Our data suggest that the P1 component of the ERP reflects changes in sensory encoding of stimulus features and is more informative for the Passive and Count conditions. The N1, on the other hand, was more informative for the Respond condition, suggesting that it can be used to model the processing of stimulus, meaning specifically discriminating one type of stimulus from another, and processes involved in integrating sensory information with response selection. Our results show that an understanding of the underlying electrophysiology is necessary for a thorough interpretation of EEG-informed fMRI analysis.

scholarly journals Recurrent interactions can explain the variance in single trial responses

2019 ◽  
Author(s):  
Subhodh Kotekal ◽  
Jason N. MacLean
Keyword(s):  
Functional Groups ◽  
Cortical Neurons ◽  
Sensory Information ◽  
Operational Definition ◽  
Single Trial ◽  
Running Speed ◽  
Local Correlations ◽  
Sensory Encoding ◽  
Definition Of ◽  
Visual Cortical

1.AbstractTo develop a complete description of sensory encoding, it is necessary to account for trial-to-trial variability in cortical neurons. Using a generalized linear model with terms corresponding to the visual stimulus, mouse running speed, and experimentally measured neuronal correlations, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups, in encoding and decoding frameworks, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials.

scholarly journals Transferability of Training Benefits Differs across Neural Events: Evidence from ERPs

2015 ◽  
Vol 27 (10) ◽  
pp. 2079-2094 ◽  
Author(s):  
Kelly G. Garner ◽  
Natasha Matthews ◽  
Roger W. Remington ◽  
Paul E. Dux
Keyword(s):  
Response Selection ◽  
Sensory Information ◽  
Training Group ◽  
Control Group ◽  
Choice Response ◽  
Sensorimotor Processing ◽  
Stimulus Response ◽  
Sensory Encoding ◽  
Alternative Choice ◽  
Choice Tasks

Humans can show striking capacity limitations in sensorimotor processing. Fortunately, these limitations can be attenuated with training. However, less fortunately, training benefits often remain limited to trained tasks. Recent behavioral observations suggest that the extent to which training transfers may depend on the specific stage of information processing that is being executed. Training benefits for a task that taps the consolidation of sensory information (sensory encoding) transfer to new stimulus–response mappings, whereas benefits for selecting an appropriate action (decision-making/response selection) remain specific to the trained mappings. Therefore, training may have dissociable influences on the neural events underlying subsequent sensorimotor processing stages. Here, we used EEG to investigate this possibility. In a pretraining baseline session, participants completed two four-alternative-choice response time tasks, presented both as a single task and as part of a dual task (with another task). The training group completed a further 3,000 training trials on one of the four-alternative-choice tasks. Hence, one task became trained, whereas the other remained untrained. At test, a negative-going component that is sensitive to sensory-encoding demands (N2) showed increased amplitudes and reduced latencies for trained and untrained mappings relative to a no-train control group. In contrast, the onset of the stimulus-locked lateralized readiness potential, a component that reflects the activation of motor plans, was reduced only for tasks that employed trained stimulus–response mappings, relative to untrained stimulus–response mappings and controls. Collectively, these results show that training benefits are dissociable for the brain events that reflect distinct sensorimotor processing stages.

scholarly journals Late Divergence of Target and Nontarget ERPs in a Visual Oddball Task

2012 ◽  
pp. 307-318 ◽  
Author(s):  
A. DAMBORSKÁ ◽  
M. BRÁZDIL ◽  
I. REKTOR ◽  
E. JANOUŠOVÁ ◽  
J. CHLÁDEK ◽  
...  
Keyword(s):  
Late Phase ◽  
Brain Regions ◽  
Opposite Polarity ◽  
Epileptic Activity ◽  
Stimulus Onset ◽  
Parahippocampal Gyrus ◽  
Oddball Task ◽  
Divergence Point ◽  
Depth Electrodes ◽  
Visual Oddball

Different mental operations were expected in the late phase of intracerebral ERPs obtained in the visual oddball task with mental counting. Therefore we searched for late divergences of target and nontarget ERPs followed by components exceeding the temporal window of the P300 wave. Electrical activity from 152 brain regions of 14 epileptic patients was recorded by means of depth electrodes. Average target and nontarget records from 1800 ms long EEG periods free of epileptic activity were compared. Late divergence preceded by almost identical course of the target and nontarget ERPs was found in 16 brain regions of 6 patients. The mean latency of the divergence point was 570±93 ms after the stimulus onset. The target post-divergence section of the ERP differed from the nontarget one by opposite polarity, different latency of the components, or even different number of the components. Generators of post-divergence ERP components were found in the parahippocampal gyrus, superior, middle and inferior temporal gyri, amygdala, and fronto-orbital cortex. Finding of late divergence indicates that functional differences exist even not sooner than during the final phase of the task.

Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia

2021 ◽  
pp. 1-14
Author(s):  
Debo Dong ◽  
Dezhong Yao ◽  
Yulin Wang ◽  
Seok-Jun Hong ◽  
Sarah Genon ◽  
...  
Keyword(s):  
Sensory Information ◽  
Resting State Fmri ◽  
Brain Regions ◽  
High Order ◽  
Hierarchical Organization ◽  
System Level ◽  
Integrative System ◽  
Sensorimotor Region ◽  
Cortical Hierarchy ◽  
High Level

Abstract Background Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Methods We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls). Results We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal−parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05). Conclusions The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory−motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

scholarly journals Microcanonical and Canonical Ensembles for fMRI Brain Networks in Alzheimer’s Disease

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 216 ◽  
Author(s):  
Jianjia Wang ◽  
Xichen Wu ◽  
Mingrui Li ◽  
Hui Wu ◽  
Edwin Hancock
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Ensemble Methods ◽  
Brain Regions ◽  
Fmri Data ◽  
Thermal Systems ◽  
Network Construction ◽  
Network Characteristics ◽  
Network Entropy ◽  
Canonical Ensembles

This paper seeks to advance the state-of-the-art in analysing fMRI data to detect onset of Alzheimer’s disease and identify stages in the disease progression. We employ methods of network neuroscience to represent correlation across fMRI data arrays, and introduce novel techniques for network construction and analysis. In network construction, we vary thresholds in establishing BOLD time series correlation between nodes, yielding variations in topological and other network characteristics. For network analysis, we employ methods developed for modelling statistical ensembles of virtual particles in thermal systems. The microcanonical ensemble and the canonical ensemble are analogous to two different fMRI network representations. In the former case, there is zero variance in the number of edges in each network, while in the latter case the set of networks have a variance in the number of edges. Ensemble methods describe the macroscopic properties of a network by considering the underlying microscopic characterisations which are in turn closely related to the degree configuration and network entropy. When applied to fMRI data in populations of Alzheimer’s patients and controls, our methods demonstrated levels of sensitivity adequate for clinical purposes in both identifying brain regions undergoing pathological changes and in revealing the dynamics of such changes.

scholarly journals Dissociable Mechanisms of Verbal Working Memory Revealed through Multivariate Lesion Mapping

2019 ◽  
Vol 30 (4) ◽  
pp. 2542-2554 ◽  
Author(s):  
Maryam Ghaleh ◽  
Elizabeth H Lacey ◽  
Mackenzie E Fama ◽  
Zainab Anbari ◽  
Andrew T DeMarco ◽  
...  
Keyword(s):  
Working Memory ◽  
Spatial Working Memory ◽  
Superior Temporal Gyrus ◽  
Verbal Working Memory ◽  
Brain Structures ◽  
Brain Regions ◽  
Task Demands ◽  
Auditory Information ◽  
Verbal Information ◽  
Task Conditions

Abstract Two maintenance mechanisms with separate neural systems have been suggested for verbal working memory: articulatory-rehearsal and non-articulatory maintenance. Although lesion data would be key to understanding the essential neural substrates of these systems, there is little evidence from lesion studies that the two proposed mechanisms crucially rely on different neuroanatomical substrates. We examined 39 healthy adults and 71 individuals with chronic left-hemisphere stroke to determine if verbal working memory tasks with varying demands would rely on dissociable brain structures. Multivariate lesion–symptom mapping was used to identify the brain regions involved in each task, controlling for spatial working memory scores. Maintenance of verbal information relied on distinct brain regions depending on task demands: sensorimotor cortex under higher demands and superior temporal gyrus (STG) under lower demands. Inferior parietal cortex and posterior STG were involved under both low and high demands. These results suggest that maintenance of auditory information preferentially relies on auditory-phonological storage in the STG via a nonarticulatory maintenance when demands are low. Under higher demands, sensorimotor regions are crucial for the articulatory rehearsal process, which reduces the reliance on STG for maintenance. Lesions to either of these regions impair maintenance of verbal information preferentially under the appropriate task conditions.

The Role of Neuronal Synchronization in Response Selection: A Biologically Plausible Theory of Structured Representations in the Visual Cortex

1996 ◽  
Vol 8 (6) ◽  
pp. 603-625 ◽  
Author(s):  
Pieter R. Roelfsema ◽  
Andreas K. Engel ◽  
Peter König ◽  
Wolf Singer
Keyword(s):  
Visual Cortex ◽  
Response Selection ◽  
Sensory Information ◽  
Motor Program ◽  
Dynamic Parameter ◽  
Object Identification ◽  
Multiple Objects ◽  
Structured Representations ◽  
Purposeful Behavior ◽  
Behavioral Requirements

Recent experimental results in the visual cortex of cats and monkeys have suggested an important role for synchronization of neuronal activity on a millisecond time scale. Synchronization has been found to occur selectively between neuronal responses to related image components. This suggests that not only the firing rates of neurons but also the relative timing of their action potentials is used as a coding dimension. Thus, a powerful relational code would be available, in addition to the rate code, for the representation of perceptual objects. This could alleviate difficulties in the simultaneous representation of multiple objects. In this article we present a set of theoretical arguments and predictions concerning the mechanisms that could group neurons responding to related image components into coherently active aggregates. Synchrony is likely to be mediated by synchronizing connections; we introduce the concept of an interaction skeleton to refer to the subset of synchronizing connections that are rendered effective by a particular stimulus configuration. If the image is segmented into objects, these objects can typically be segmented further into their constituent parts. The synchronization behavior of neurons that represent the various image components may accurately reflect this hierarchical clustering. We propose that the range of synchronizing interactions is a dynamic parameter of the cortical network, so that the grain of the resultant grouping process may be adapted to the actual behavioral requirements. It can be argued that different aspects of purposeful behavior rely on separable processes by which sensory input is transformed into adjustments of motor activity. Indeed, neurophysiological evidence has suggested separate processing streams originating in the primary visual cortex for object identification and sensorimotor coordination. However, such a separation calls for a mechanism that avoids interference effects in the presence of multiple objects, or when multiple motor programs are simultaneously prepared. In this article we suggest that synchronization between responses of neurons in both the visual cortex and in areas that are involved in response selection and execution might allow for a selective routing of sensory information to the appropriate motor program.

scholarly journals Visual Information Shapes the Dynamics of Corticobasal Ganglia Pathways during Response Selection and Inhibition

2015 ◽  
Vol 27 (7) ◽  
pp. 1344-1359 ◽  
Author(s):  
Sara Jahfari ◽  
Lourens Waldorp ◽  
K. Richard Ridderinkhof ◽  
H. Steven Scholte
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Response Selection ◽  
Selection Process ◽  
Effective Connectivity ◽  
Action Selection ◽  
Visual Input ◽  
Fmri Data ◽  
Response Strategies ◽  
Fast Flow

Action selection often requires the transformation of visual information into motor plans. Preventing premature responses may entail the suppression of visual input and/or of prepared muscle activity. This study examined how the quality of visual information affects frontobasal ganglia (BG) routes associated with response selection and inhibition. Human fMRI data were collected from a stop task with visually degraded or intact face stimuli. During go trials, degraded spatial frequency information reduced the speed of information accumulation and response cautiousness. Effective connectivity analysis of the fMRI data showed action selection to emerge through the classic direct and indirect BG pathways, with inputs deriving form both prefrontal and visual regions. When stimuli were degraded, visual and prefrontal regions processing the stimulus information increased connectivity strengths toward BG, whereas regions evaluating visual scene content or response strategies reduced connectivity toward BG. Response inhibition during stop trials recruited the indirect and hyperdirect BG pathways, with input from visual and prefrontal regions. Importantly, when stimuli were nondegraded and processed fast, the optimal stop model contained additional connections from prefrontal to visual cortex. Individual differences analysis revealed that stronger prefrontal-to-visual connectivity covaried with faster inhibition times. Therefore, prefrontal-to-visual cortex connections appear to suppress the fast flow of visual input for the go task, such that the inhibition process can finish before the selection process. These results indicate response selection and inhibition within the BG to emerge through the interplay of top–down adjustments from prefrontal and bottom–up input from sensory cortex.

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