Aberrant hemodynamic responses in autism: Implications for resting state fMRI functional connectivity studies

Functional MRI (fMRI) is modeled as a convolution of the hemodynamic response function (HRF) and an unmeasured latent neural signal. However, HRF itself is variable across brain regions and subjects. This variability is induced by both neural and non-neural factors. Aberrations in underlying neurochemical mechanisms, which control HRF shape, have been reported in autism spectrum disorders (ASD). Therefore, we hypothesized that this will lead to voxel-specific, yet systematic differences in HRF shape between ASD and healthy controls. As a corollary, we also hypothesized that such alterations will lead to differences in estimated functional connectivity in fMRI space compared to latent neural space. To test these hypotheses, we performed blind deconvolution of resting-state fMRI time series acquired from large number of ASD and control subjects obtained from the Autism Brain Imaging Data Exchange (ABIDE) database (N = 1102). Many brain regions previously implicated in autism showed systematic differences in HRF shape in ASD. Specifically, we found that precuneus had aberrations in all HRF parameters. Consequently, we obtained precuneus-seed-based functional connectivity differences between ASD and controls using fMRI as well as using latent neural signals. We found that non-deconvolved fMRI data failed to detect group differences in connectivity between precuneus and certain brain regions that were instead observed in deconvolved data. Our results are relevant for the understanding of hemodynamic and neurochemical aberrations in ASD, as well as have methodological implications for resting-state functional connectivity studies in Autism, and more generally in disorders that are accompanied by neurochemical alterations that may impact HRF shape.

Macroscale variation in resting-state neuronal activity and connectivity assessed by simultaneous calcium imaging, hemodynamic imaging and electrophysiology

Functional imaging of spontaneous activity continues to play an important role in the field of connectomics. The most common imaging signal used for these experiments is the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal, but how this signal relates to spontaneous neuronal activity remains incompletely understood. Genetically encoded calcium indicators represent a promising tool to study this problem, as they can provide brain-wide measurements of neuronal activity compared to point measurements afforded by electrophysiological recordings. However, the relationship between the calcium signal and neurophysiological parameters at the mesoscopic scale requires further systematic characterization. Therefore, we collected simultaneous resting-state measurements of electrophysiology, along with calcium and hemodynamic imaging, in lightly anesthetized mice to investigate two aims. First, we examined the relationship between each imaging signal and the simultaneously recorded electrophysiological signal in a single brain region, finding that both signals are better correlated with multi-unit activity compared to local field potentials, with the calcium signal possessing greater signal-to-noise ratio and regional specificity. Second, we used the resting-state imaging data to model the relationship between the calcium and hemodynamic signals across the brain. We found that this relationship varied across brain regions in a way that is consistent across animals, with delays increasing by600 ms towards posterior cortical regions. Furthermore, while overall functional connectivity (FC) measured by the hemodynamic signal is significantly correlated with FC measured by calcium, the two estimates were found to be significantly different. We hypothesize that these differences arise at least in part from the observed regional variation in the hemodynamic response. In total, this work highlights some of the caveats needed in interpreting hemodynamic-based measurements of FC, as well as the need for improved modeling methods to reduce this potential source of bias.

Genes influence the amplitude and timing of brain hemodynamic responses

In functional magnetic resonance imaging (fMRI), the hemodynamic response function (HRF) reflects regulation of regional cerebral blood flow in response to neuronal activation. The HRF varies significantly between individuals. This study investigated the genetic contribution to individual variation in HRF using fMRI data from 125 monozygotic (MZ) and 149 dizygotic (DZ) twin pairs. The resemblance in amplitude, latency, and duration of the HRF in six regions in the frontal and parietal lobes was compared between MZ and DZ twin pairs. Heritability was estimated using an ACE (Additive genetic, Common environmental, and unique Environmental factors) model. The genetic influence on the temporal profile and amplitude of HRF was moderate to strong (24%-51%). The HRF may be used in the genetic analysis of diseases with a cerebrovascular etiology.

Variability in blood oxygen level dependent (BOLD) signal in patients with stroke-induced and primary progressive aphasia

Although fMRI is increasingly used to assess language-related brain activation in patients with aphasia, few studies have examined the hemodynamic response function (HRF) in perilesional, and contralesional areas of the brain. In addition, the relationship between HRF abnormalities and other variables such as lesion size and severity of aphasia has not been explored. The objective of this study was to investigate changes in HRF signal during language-related neural activation in patients with stroke-induced aphasia (SA). We also examined the status of the HRF in patients with aphasia due to nonvascular etiology, namely, primary progressive aphasia (PPA). Five right handed SA patients, three PPA patients, and five healthy individuals participated in the study. Structural damage was quantified with T1-weighted MR images. Functional MR imaging was performed with long trial event-related design and an overt naming task to measure BOLD signal time to peak (TTP) and percent signal change (ΔS). In SA patients, the average HRF TTP was significantly delayed in the left hemisphere regions involved in naming compared to healthy participants and PPA patients. However, ΔS was not different in SA patients compared to the other two groups. Delay in HRF TTP in the left hemisphere naming network of SA patients was correlated with lesion size and showed a negative correlation with global language function. There were no significant differences in the HRF TTP and ΔS in the right hemisphere homologues of the naming network or in the left and the right occipital control regions across the three groups. In PPA patients, HRF had a normal pattern. Our results indicate that abnormal task-related HRF is primarily found in the left hemisphere language network of SA patients and raise the possibility that abnormal physiology superimposed on structural damage may contribute to the clinical deficit. Follow-up investigations in a larger sample of age-matched healthy individuals, SA, and PPA patients will be needed to further confirm and extend our findings.