Motor sequences; separating the sequence from the motor: A longitudinal rsfMRI study

In motor learning, sequence specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific decreases in functional connectivity during overall learning in the right supplementary motor area (SMA). We found that connectivity changes in a key region of the motor network, the superior parietal cortex (SPC) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA that has previously been identified in online task-based learning studies, and extends it to resting state network changes after sequence-specific MSL

Activity-driven formation and stabilization of functional spine synapses

Physical changes in neuronal connections, dictated by the neuronal network activity, are believed to be essential for learning and memory. Long-term potentiation (LTP) of synaptic transmission has emerged as a model to study activity-driven plasticity. The majority of excitatory contacts between neurons, called synapses, are found on spines, small dendritic protrusions. LTP is known to trigger the formation and stabilization of new dendritic spines in vitro. Similarly, experience-dependent plasticity in vivo is associated with changes in the number and stability of spines. However, to date, the contribution of excitatory synaptogenesis to the enhanced synaptic transmission after LTP remains elusive. Do new spines form functional synapses with the inputs stimulated during LTP induction and thereby follow Hebbian co-activation rules, or do they connect with random partners? Furthermore, at which time-point are de novo spines functionally integrated into the network? I developed an optical approach to stably and exclusively stimulate the axons of a defined channelrhodopsin-2 (ChR2)-transduced subset of CA3 cell in mature hippocampal slice culture over extended periods of time (up to 24h). I continuously monitored synaptic activation and synaptic structure of CA1 cells dendrites using two-photon imaging. To control the dendritic location where LTP and associated spinogenesis were allowed to take place, I globally blocked Na+-dependent action potential firing and directly evoke neurotransmitter release by local light-evoked depolarization of ChR2-expressing presynaptic boutons (in TTX, 4-AP). I induced optical LTP specifically at this location by combining optogenetic activation with chemical pairing (in low [Mg2+]o, high [Ca2+]o, forskolin, and rolipram). Taking advantage of the NMDA-receptor mediated calcium influx during synaptic activation I assessed the formation of functional synapses using the genetically encoded calcium indicator GCaMP6s. I find that optical LTP led to the generation of new spines, decreased the stability of preexisting spines and increased the stability of new spines. Under optical LTP conditions, a fraction of new spines responded to optical presynaptic stimulation within hours after formation. However, the occurrence of the first synaptic calcium response in de novo spines varied considerably, ranging from 8.5 min to 25 h. Most new spines became responsive within 4 h (1.2 ± 0.9 h, mean ± S.D., n = 16 out of 20), whereas the remainder showed their first response only on the second experimental day (18.2 ± 3.7 h). Importantly, new spines generated under optical LTP were more likely to build functional synapses with light-activated, ChR2-expressing axons than spontaneously formed spines (new responsive spines under optical LTP: 64 ± 4 %; control 1: 0%; control 2: 13 ± 4 %; control 3: 11 ± 4 %). Furthermore, new spines that were responsive to optical presynaptic stimulation were less prone to be eliminated after overnight incubation than new spines that failed to respond (% overnight spine survival; 81 ± 3 % new responsive spines; 58 ± 4 % of new unresponsive spines). In summary, the results from my thesis demonstrate that synapses can form rapidly in an input-specific manner

Identifying diurnal variability of brain connectivity patterns using graph theory

Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks

Towards a learning fingerprint: new methods and paradigms for complex motor skill learning in fMRI

Functional Magnetic Resonance Imaging (fMRI) research in sensorimotor learning focus on two separate paradigms: (1) task-based (tfMRI), where brain changes are evaluated ac- cording to activity elicited by performance of the task, or (2) task-free, i.e., resting-state (rsfMRI), where changes are reflected in spontaneous, internally generated brain activity. While the former paradigm allows careful control and manipulation of the task, the later allows unrestrained motor learning tasks to take place beyond the limitations of the scanner environment. Machine learning approaches attempting to model these two types of measure- ments together to explain physiological effects of learning remained unexplored. Although these paradigms yield results showing considerable overlap between their topographical pat- terns, they are usually treated separately. Consequently, their relationship, and how or if any behaviorally relevant neural information processing mediates it, remains unclear. To resolve this ambiguity, new methodology was developed guided by questions of sensorimotor learning in motor tasks having dynamics completely specified mathematically. First, basic fMRI methodological considerations were made. Machine learning methods that claimed to predict individual tfMRI task maps from rsfMRI activity were improved. In reviewing previous methodology, most methods were found to underperform against trivial baseline model performances based on massive group averaging. New methods were devel- oped that remedies this problem to a great extent. Benchmark comparisons and model evaluation metrics demonstrating empirical properties related to this predictive mapping previously unconsidered were also further developed. With these newly formed empirical ob- servations, a relationship between individual prediction scores and behavioral performance measured during the task could be established. Second, a complex motor learning task performed during an fMRI measurement was designed to relate learning effects observed in both types of measurements from a single longitudinal learning session. Participants measured while performing the task show they learn to exploit a property that drives brain activity in certain regions towards a state requiring less active control and error correction. Reconfiguration of functional activity in task-evoked and task- free activity from these behavioral learning effects were investigated, applying methodology developed earlier in an attempt to relate them together. Predictions of individual task- evoked responses from rsfMRI provide a relative measure of dependence, however, remain limited for reasons understood from the methodological study. No rsfMRI reconfiguration due to learning was detected, yet changes over the course of learning in task-evoked activity appear significant. Increasing recruitment of the Default Mode Network (DMN) during the task explain these changes. These results support that minimal reconfiguration of the cortex suggestive of plasticity effects are needed to find task solutions in a passively stable space

Social and Affective Neuroscience of Everyday Human Interaction

This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers

DETECTING BRAIN-WIDE INTRINSIC CONNECTIVITY NETWORKS USING fMRI IN MICE

Functional neuroimaging methods in mice are essential for unraveling complex neuronal networks that underlie maladaptive behavior in neurological disorder models. By using fMRI to detect intrinsic connectivity networks in mice, we can examine large scale alteration in brain activity and functional connectivity to establish causal associations in brain network changes. The work presented in this dissertation is organized into five chapters. Chapter 1 provides the necessary background required to understand how functional neuroimaging tools such as fMRI detect signal changes attributed to spontaneous neuronal activity of intrinsic connectivity networks in mice. Chapter 2 describes the development of our isotropic fMRI acquisition sequence in mice and semi-automated pipeline for mouse fMRI data. Naïve mouse fMRI scans were used to validated the pipeline by reliably and reproducibly extracting intrinsic connectivity networks. Chapter 3 establishes the development and validation of a novel superparamagenetic iron-oxide nanoparticle to enhance fMRI signal sensitivity. Chapter 4 studies the effects norepinephrine released by locus coeruleus neurons on the default mode network in mice. Norepinephrine release selectively enhanced neuronal activity and connectivity in the Frontal module of the default mode network by suppressing information flow from the Retrosplenial-Hippocampal to the Association modules. Chapter 5 addresses the implications of our findings and addresses the limitations and future studies that can be conducted to expand on this research.Doctor of Philosoph

Recent Advances in Autism Spectrum Disorders

The pace of research on Autism Spectrum Disorders (ASD) has expanded exponentially in recent years. It is difficult for anyone to keep up with all developments. This book will assist the experienced and non-specialist reader to keep up with recent developments. The book opens with a focus on the evolutionary aspects of autism and then focuses on the public's attitude towards autism including the stigma issue. Then there is a focus on cortical modularity and electrophysiology followed by treatment issues including sensory, medical and community-based interventions. Finally, forensic issues are dealt with and the importance of the built environment is focused on. The book will be relevant to psychiatrists, psychologists, paediatricians, social workers, speech and language therapists, occupational therapists and care workers

Social and Affective Neuroscience of Everyday Human Interaction

This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers