The Correlation between Astrocytic Calcium and fMRI Signals is Related to the Thalamic Regulation of Cortical States

BOLD fMRI has been wildly used for mapping brain activity, but the cellular contribution of BOLD signals is still controversial. In this study, we investigated the correlation between neuronal/astrocytic calcium and the BOLD signal using simultaneous GCaMP-mediated calcium and BOLD signal recording, in the event-related state and in resting state, in anesthetized and in free-moving rats. To our knowledge, the results provide the first demonstration that evoked and intrinsic astrocytic calcium signals could occur concurrently accompanied by opposite BOLD signals which are associated with vasodilation and vasoconstriction. We show that the intrinsic astrocytic calcium is involved in brain state changes and is related to the activation of central thalamus. First, by simultaneous LFP and fiber optic calcium recording, the results show that the coupling between LFP and calcium indicates that neuronal activity is the basis of the calcium signal in both neurons and astrocytes. Second, we found that evoked neuronal and astrocytic calcium signals are always positively correlated with BOLD responses. However, intrinsic astrocytic calcium signals are accompanied by the activation of the central thalamus followed by a striking negative BOLD signal in cortex, which suggests that central thalamus may be involved in the initiation of the intrinsic astrocytic calcium signal. Third, we confirmed that the intrinsic astrocytic calcium signal is preserved in free moving rats. Moreover, the occurrences of intrinsic astrocytic calcium spikes are coincident with the transition between different sleep stages, which suggests intrinsic astrocytic calcium spikes reflect brain state transitions. These results demonstrate that the correlation between astrocytic calcium and fMRI signals is related to the thalamic regulation of cortical states. On the other hand, by studying the relationship between vessel–specific BOLD signals and spontaneous calcium activity from adjacent neurons, we show that low frequency spontaneous neuronal activity is the cellular mechanism of the BOLD signal during resting state

Identifying characteristics of thalamo-cortical changes and their relationship with symptoms in schizophrenia [Utvrđivanje obilježja talamo-kortikalnih promjena i njihovog odnosa sa simptomima u shizofreniji]

Hypothesis of the doctoral thesis was that, using resting-state functional magnetic resonance imaging (fMRI), patients diagnosed with schizophrenia would exhibit stable and specific patterns of thalamic connectivity changes that will show different relationship with specific symptoms of psychotic disorders. The aims of the study were to characterize in a more detailed way changes in thalamo-cortical connectivity (over- and under-connectivity) in a clinical sample compared to healthy controls, by using state-of-the-art resting-state functional resonance and Human Connectome Project protocols, as well as to more specifically determine within-thalamus differences and their relative contribution to described connectivity changes. Finally, the aim was to determine relationship between identified connectivity changes and specific symptoms of the disorder. Subjects for the study were pooled from multiple centers, as part of an existing initiative, Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium, created with a goal of investigating intermediate phenotypes across psychotic disorders. Study procedures and data analyses were done under the approved Yale University project Characterizing Clinical and Pharmacological Neuroimaging Biomarkers. Following identification of subjects that passed stringent quality controls for fMRI data, and matching with the clinical and healthy control populations, study included 436 psychosis probands (167 schizophrenia patients, 119 schizoaffective disorder patients, and 150 patients diagnosed with bipolar disorder with history of psychosis) and 219 matched healthy controls. Whole-thalamus seed-based analyses were used to determine thalamic connectivity changes, followed by parcellation of thalamus using a priori defined functional subnuclei, and data-driven clustering, to define details of the thalamo-cortical dysconnectivity in schizophrenia and psychotic disorders. Both in schizophrenia, and in the wider psychosis spectrum, there was a robust pattern of thalamic over-connectivity with sensory and motor regions, as well as with associative areas tasked with integration of lower-level inputs, and under-connectivity with cerebellar regions. Interestingly, previously reported under-connectivity with prefrontal regions was evident only in dorsal attention functional thalamic subnucleus connectivity map. Nine functional thalamic subnuclei showed relatively different thalamic connectivity changes, ranging from altogether missing effects to wide-spread over- /under-connectivity, but overall followed same general dysconnectivity pattern described for the whole thalamus. Clustering analyses revealed that the data-driven clustering, released from constraints of a priori defined thalamic subnuclei, resulted in solutions that significantly differed from existing functional subnuclei or anatomical divisions, with areas centered on mediodorsal nucleus and ventral lateral areas driving the dysconnectivity effect. In schizophrenia, thalamo-cortical connectivity changes showed relationship with negative symptoms, as well as with excitation and disorganization subscale scores, suggesting that a more pronounced over- or under-connectivity effect predicted more pronounced specific symptoms. Under-connectivity effect of the dorsal attention functional subnucleus (including reduced connectivity with prefrontal cortical regions) also correlated with disorientation. In conclusion, thalamo-cortical dysconnectivity patterns of seemingly correlated over- and under-connectivity effects seems to be robustly present in schizophrenia, but also across the psychosis spectrum. Although the same general pattern exists across different thalamic regions, its extent differs among different thalamic functional subnuclei suggesting that the effect is driven by specific associative functional subnuclei. Finally, although thalamo-cortical connectivity changes might be linked to a more non-specific disease severity or trait indicators, negative symptoms, disorganization, and excitation seem to be connected more directly to those changes than positive symptoms or emotional dysregulation

Studying the behavioural, physiological, and neural indices of associative learning in multi-trial paradigms: methodological and analytical considerations

Since the pioneering work of Ivan Pavlov nearly a century ago, the empirical study of associative learning through classical conditioning has continued to grow. However, the high volume of classical conditioning investigations has resulted in an equal in magnitude methodological and analytical variation, which can often challenge cross-study comparisons, replicability and generalisability of findings (Haaker et al., 2019; Lonsdorf et al., 2017). Consequently, the field of conditioning has begun to focus on reducing excessive flexibility in data practices through increasing methodological rigour, consistency, and transparency. So far, research has concentrated on improving methods in areas such as the quantification of conditioned responding, analytical strategies, translational research and individual differences (Bach et al., 2018; Haaker et al., 2019; Korn et al., 2017; Lonsdorf et al., 2019; Lonsdorf & Merz, 2017; Ney et al., 2018; Sjouwerman & Lonsdorf, 2019). The aim of this thesis was to provide an additional contribution to recent methodological efforts in the field by focusing on an area that has not received as much empirical attention. Specifically, we discuss and examine the potential utility of multi-trial conditioning for studying psychophysiological indices of learning. In addition, throughout this thesis, we aimed to reinforce the value of transparent and robust data practises in aiding replicability and generalisability of conditioning research. In Chapter 2, we report findings from an indirect behavioural replication of an established multi-trial task (i.e., Multi-CS Conditioning, Steinberg et al., 2013), accompanied by a discussion about the role of contingency awareness in conditioning. We also provide a re-analysis of a previous Multi-CS dataset (Rehbein et al., 2014) to highlight the value of robust and transparent data visualisation in guiding analytical decisions, and to illustrate how poor consideration of individual differences and underlying data distributions may explain the inconsistency in previous research using this task. Chapter 3 reports a novel visual blocked conditioning paradigm that delivers a high number of trials through attempting to elicit associative learning in multiple successive blocks. We investigated the potential utility of this task to overcome some of the technical and design challenges (e.g., detecting deep source activity, time-frequency analysis) present in magnetoencephalography (MEG) research, studying the cortical and subcortical oscillatory dynamics of learning and extinction. The findings from this study suggested that the task does not reliably elicit conditioning in any of the outcome measures that we considered (MEG, pupil size, valence, and arousal ratings). Nevertheless, the reported results identified several design modifications that can aid future paradigm development. These were related to aspects such as trial duration, the type of CSs employed, and maintaining attention and contingency awareness. Chapter 4 reports findings from an auditory blocked conditioning task, modified based on the results from Chapter 3. The task was examined in the context of pupillary and subjective behavioural indices of conditioning, with a discussion of its application in future MEG designs. In addition, the study considers the potential of this multi-trial paradigm to offer better generalisability of findings when used in combination with robust analytical strategies (i.e., data-driven time window selection and design-appropriate mixed modelling). Finally, Chapter 5 discusses the implications of the findings reported in this thesis for future multi-trial conditioning research