Traditionally, the focus in cognitive neuroscience has been on so-called evoked neural activity in response to certain stimuli or experiences. However, most of the brain’s activity is actually spontaneous and therefore not ascribed to the processing of a certain task or stimulus – or in other words, uncoupled to overt stimuli or motor outputs. In this thesis I investigated the functional role of spontaneous activity with a focus on its role in contextual changes ranging from recent experiences of individuals to trial-by-trial variability in a certain task. I studied the nature of ongoing activity from two perspectives: One looking at changes in the ongoing activity due to learning, and the other one looking at the predictive role of prestimulus activity using different methodologies, i.e. EEG and fMRI. Finally, I ventured into the realm of inter-individual differences and mind-wandering to investigate the relationship between ongoing activity, certain behavioural traits and neuronal connectivity.
Contents
Chapter 1 General introduction
1.1 Spontaneous and evoked activity
1.2 The study of spontaneous activity
1.2.1 Electrophysiological research of ongoing activity
1.2.1.1 Cortical states and response variability
1.2.1.2 Predictive coding and predictive timing
1.2.2 Neuroimaging research of ongoing activity
1.2.2.1 Resting state fluctuations
1.2.2.2 Vascular basis
1.2.2.3 Neural basis
1.2.2.4 Functional networks
1.3 The functional role of spontaneous activity
1.3.1 Perceptual domain
1.3.2 Motor domain
1.3.3 Cognitive domain
1.4 Conclusions
1.5 This thesis
Chapter 2 Methods – measuring spontaneous activity
2.1 Introduction
2.2 Group versus inter-individual differences versus lesion studies
2.3 Functional Magnetic Resonance Imaging (fMRI)
2.3.1 Overview
2.3.2 The BOLD response
2.3.3 How to collect resting state data
2.3.4 Pre-processing and noise correction
2.3.5 Functional connectivity analyses of resting state data
2.3.6 DCM – or: going beyond functional connectivity
2.3.6.1 Effective connectivity
2.3.6.2 Deterministic dynamic causal modelling
2.3.6.3 Stochastic DCM
2.3.6.4 Model selection
2.4 Electroencephalography (EEG)
2.4.1 Event-related potentials (ERPs)
2.4.2 Time-frequency analyses (TFAs)
Chapter 3 Early visual learning induces long-lasting connectivity changes during rest in the human brain
3.1 Introduction
3.2 Materials and methods
3.2.1 Participants
3.2.2 Stimuli and task design
3.2.3 Experimental procedure
3.2.4 Behavioural analysis
3.2.5 fMRI data acquisition
3.2.6 fMRI data analysis
3.2.6.1 Perceptual learning session
3.2.6.2 Psychophysiological interaction analysis
3.2.6.3 Dynamic causal modelling
3.3 Results
3.3.1 Participants showed early rapid learning of the motion task
3.3.2 Motion task activated visual, frontal and parietal areas
3.3.3 Early learning-related modulation of hippocampal activity during task performance
3.3.4 Learning-related changes in connectivity during rest
3.3.5 Dynamic causal modelling
3.4 Discussion
3.5 Conclusion
Chapter 4 The role of prestimulus activity in visual extinction
4.1 Introduction
4.1.1 The phenomenon of visual extinction
4.1.2 How does visual extinction relate to spatial neglect?
4.1.3 Mechanisms of visual extinction
4.1.4 Prestimulus activity affects perception
4.1.5 Can I analyse visual extinction using prestimulus activity?
4.2 Materials and methods
4.2.1 Participant
4.2.2 Design and procedure
4.2.2.1 Neuropsychological testing
4.2.2.2 fMRI paradigms
4.2.2.2.1 Extinction paradigm (event related design)
4.2.2.2.2 Stimulus localiser (block design)
4.2.2.2.3 Stimuli
4.2.3 fMRI data acquisition
4.2.4 Data analysis
4.2.4.1 Behavioural data
4.2.4.2 fMRI data
4.2.4.2.1 Extinction paradigm
4.2.4.2.2 Stimulus localiser
4.2.4.2.3 Peristimulus time histograms (PSTH)
4.2.4.2.4 Dynamic causal modelling (DCM)
4.3 Results
4.3.1 Patient showed signs of visual extinction
4.3.2 Stimulus localiser activated visual areas
4.3.3 Extinction paradigm produced unseen trials
4.3.4 Prestimulus activity in visually responsive areas affects perception
4.3.5 Time-course of responses to seen and unseen trials
4.3.6 Perception depends on the coupling between visual areas
4.4 Discussion
4.4.1 Prestimulus activity in visual areas affects stimulus perception
4.4.2 Prestimulus activity in other brain areas might play a role
4.4.3 Mechanisms behind visual extinction
4.4.4 Limitations of the study
4.4.5 Methodological aspects
4.5 Conclusion
Chapter 5 Effects of ongoing cortical state on ambiguous perception
5.1 Introduction
5.2 Materials and methods
5.2.1 Participants and apparatus
5.2.1.1 Stimuli
5.2.1.2 Training and thresholding
5.2.1.3 Behavioural task during EEG
5.2.1.4 EEG data acquisition
5.2.1.5 fMRI data acquisition and analysis
5.2.2 EEG data analysis
5.2.2.1 Pre-processing
5.2.2.2 ERP analysis
5.2.2.3 Prestimulus analysis
5.3 Results
5.3.1 Behavioural results
5.3.1.1 Performance and response patterns
5.3.1.2 Reaction times
5.3.2 Event-related potentials
5.3.3 Time frequency analysis of prestimulus activity
5.4 Discussion
5.4.1 ERP results
5.4.2 Alpha band oscillations
5.4.3 Beta band oscillations
5.4.4 Gamma band oscillations
5.4.5 Conclusion and future direction
Chapter 6 The relationship between mind-wandering, creativity and neuronal coupling
6.1 Introduction
6.2 Materials and methods
6.2.1 Participants
6.2.2 Stimuli and task design
6.2.3 Experimental procedure
6.2.4 Behavioural analysis
6.2.4.1 UUT
6.2.4.2 Thought probes
6.2.4.3 Target detection
6.2.5 fMRI data acquisition
6.2.6 fMRI data analysis
6.2.6.1 Pre-processing
6.2.6.2 Block task
6.2.6.3 Incubation task
6.2.6.4 ROIs
6.2.6.5 Dynamic causal modelling
6.3 Results
6.3.1 Behavioural results
6.3.2 Imaging results
6.3.2.1 Task-active regions
6.3.2.2 DMN regions
6.3.2.3 Stochastic DCM
6.4 Discussion
6.4.1 Behavioural results
6.4.2 Imaging results
6.4.3 Limitations
6.5 Conclusion
Chapter 7 General discussion
7.1 Overview of findings
7.2 Implications of this research
7.2.1 Ongoing activity predicts perception
7.2.2 Ongoing activity is modulated by learning and trait variables
7.2.3 Cause and effect: the interplay between ongoing and evoked activity
7.3 Outstanding questions and conclusion
7.3.1 Timescale of changes in ongoing activity and its relation to structural changes
7.3.2 Origin and scale of ongoing activity
7.3.3 Conclusion or: The function of ongoing activity
Research Objectives and Themes
This thesis investigates the functional role of spontaneous brain activity by focusing on its contextual changes, ranging from recent individual experiences, such as learning, to trial-by-trial variability. The primary research goal is to understand how spontaneous "ongoing" activity interacts with evoked neural processes and how it predicts behavior in both healthy individuals and in patients with neurological deficits, utilizing various neuroimaging methods.
- Characterizing the role of spontaneous neural fluctuations in contextual changes and learning.
- Exploring the predictive power of prestimulus neural activity on subsequent sensory perception and behavioral outcomes.
- Utilizing advanced neuroimaging methodologies like fMRI and EEG, combined with Dynamic Causal Modelling (DCM), to analyze connectivity patterns.
- Investigating inter-individual differences, mind-wandering, and their relationship with brain connectivity and creative traits.
- Bridging the gap between spontaneous brain activity, cognitive states, and task-related behavior.
Excerpt from the Book
1.1 Spontaneous and evoked activity
Traditionally, the focus in cognitive neuroscience has been on so-called evoked neural activity in response to certain stimuli or experiences. However, most of the brain’s activity is actually spontaneous and therefore not ascribed to the processing of a certain task or stimulus – or in other words, uncoupled to overt stimuli or motor outputs. Possibly, the existence of ongoing intrinsic activity was first noted by Hans Berger when he introduced electroencephalography for humans in 1929 (Berger, 1929), asking whether “it [is] possible to demonstrate the influence of intellectual work upon the human electroencephalogram, insofar as it has been reported here?” to conclude subsequently that “[o]f course, one should not at first entertain too high hopes with regard to this, because mental work, as I explained elsewhere, adds only a small increment to the cortical work which is going on continuously and not only in the waking state”. Four years later, Bishop (1933) reported the potential physiological significance of the ongoing activity describing his experiments with rabbits. He observed cyclic changes in the excitability in visual cortex during stimulation of the optic nerve. Summarising his findings, he stated that “[…] we would look upon the cortex as being in constant activity, the physiological activity of the whole network of neurons bearing some direct relationship to the ‘present state’ of the animal’s complex behavio[u]r which is sometimes referred to as his ‘mental state’”.
Indeed, ongoing activity occurs throughout the brain and its existence is manifested in the variability of cortical responses in repeated responses to physically identical conditions or stimuli. In the past, this variability had simply been labelled as noise and scientists got rid of it by averaging over repeated trials (Gerstein, 1960; Zohary et al., 1994). However, during the last two decades an increasing number of neuroscientists recognised that ongoing neural activity is not mere noise, but plays a fundamental role in stimulus-driven processing (Arieli et al., 1996; Tsodyks et al., 1999) and behavioural variability indeed (Hesselmann, Kell, Eger, et al., 2008; Coste et al., 2011; Kleinschmidt et al., 2012).
Summary of Chapters
Chapter 1 General introduction: Provides the foundational context for the study, establishing the focus on spontaneous versus evoked neural activity and introducing core concepts like predictive coding and functional networks.
Chapter 2 Methods – measuring spontaneous activity: Details the various methodological approaches used to measure spontaneous activity, including fMRI, EEG, and advanced analytical frameworks like Dynamic Causal Modelling.
Chapter 3 Early visual learning induces long-lasting connectivity changes during rest in the human brain: Examines how rapid perceptual learning leads to persistent changes in effective connectivity within the hippocampus and striatum that extend into the resting state.
Chapter 4 The role of prestimulus activity in visual extinction: Explores, through a case study, how prestimulus neural activity in visually responsive regions influences perceptual awareness in patients suffering from visual extinction.
Chapter 5 Effects of ongoing cortical state on ambiguous perception: Investigates the relationship between prestimulus neural oscillations and the perceptual outcome of ambiguous visual stimuli using EEG spectral analysis.
Chapter 6 The relationship between mind-wandering, creativity and neuronal coupling: Connects individual creative traits and mind-wandering behavior to the physiological coupling between the Default Mode Network (DMN) and task-active networks.
Chapter 7 General discussion: Synthesizes the findings across all experimental chapters, addressing the bidirectional interaction between ongoing activity and behavior, and discussing implications and future research directions.
Keywords
Ongoing activity, Spontaneous activity, fMRI, EEG, Dynamic Causal Modelling, Perceptual learning, Visual extinction, Neural connectivity, Hippocampus, Mind-wandering, Creativity, Predictive coding, Cortical oscillations, Prestimulus activity, Default Mode Network.
Frequently Asked Questions
What is the primary focus of this research?
The research explores the functional role of spontaneous or "ongoing" brain activity—activity that occurs without being driven by specific external tasks or stimuli—and investigates how it interacts with and influences task-based performance and perception.
What are the main thematic fields addressed?
The thesis covers various areas including perceptual learning, visual extinction in patients, the impact of ongoing cortical states on ambiguous perception, and the relationship between creative traits, mind-wandering, and neural network connectivity.
What is the primary goal of the study?
The primary goal is to shift the traditional neuroscientific focus from purely evoked responses to understanding how the brain's internal, ongoing state primes or modulates the processing of external information, and how this state is itself plastic and influenced by individual history and traits.
Which scientific methods were utilized?
The research employed a multimodal approach, primarily using functional Magnetic Resonance Imaging (fMRI) and Electroencephalography (EEG). To analyze these data, sophisticated mathematical models like Dynamic Causal Modelling (DCM) and Stochastic DCM were used to infer directed effective connectivity between brain regions.
What is covered in the main body of the work?
The main chapters detail specific experiments: one on visual learning and its persistence in resting state connectivity, a case study on visual extinction predicting stimulus perception, an investigation into EEG oscillations and ambiguous perception, and a study linking creative traits to the DMN and task-network coupling.
Which keywords best characterize the work?
Key terms include Ongoing activity, fMRI, EEG, Dynamic Causal Modelling, Perceptual learning, Visual extinction, Neural connectivity, Mind-wandering, Creativity, and the Default Mode Network.
How does the research on visual extinction specifically contribute to the field?
This work provides evidence that fluctuations in ongoing neural activity in visual areas prior to stimulus arrival are a significant determinant of whether a stimulus reaches perceptual awareness in patients with visual extinction, offering a mechanism for the "unconscious" processing observed in such cases.
What is the significance of the "consolidation model" found in the learning study?
The study found that learning effects on neural connectivity were not merely transient but were consolidated, meaning they persisted into the following day at a modified level, suggesting that spontaneous activity is continuously updated by experience-dependent plasticity.
- Citation du texte
- Maren Urner (Auteur), 2013, Investigating the dynamic role of fluctuations in ongoing activity in the human brain, Munich, GRIN Verlag, https://www.grin.com/document/299815
