Visual Stimulation Task Research Articles

Infants' fast neural categorization of artificial objects: The impact of stimulus and task characteristics.

This study explores how 7-month-old infants categorize graphical images varying in basic perceptual features by using a fast periodic visual stimulation (FPVS) task. Most participants were Caucasian and their parents had a higher education, but the family's socioeconomic background was mixed. Experiment 1 (N = 23) tested brain responses to configurational versus scrambled image sequences and found an oddball effect for both conditions, with configurational information leading to stronger neural responses. Experiment 2 explored the role of category learning for later FPVS performance: Group A (control; n = 22) participated in the FPVS categorization task only. Group B (fam; n = 21) was first familiarized with standard exemplars. Group C (fam + contrast; n = 29) was presented an additional exemplar of the contrasting category before the FPVS task. Electroencephalogram analyses revealed a decrease in Nc amplitude (measuring attention) throughout the familiarization phase. Long looking at the out-of-category exemplar in Group C indicated infants' visual interest. Brain responses in the subsequently presented FPVS were strong but did not differ between groups. This highlights the ability of the infant brain to organize perceptual input very rapidly without requiring familiarization but also points to the need for further studies exploring brain processes associated with infants' category learning and categorization at the brain level. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Influence Assessment of Artifact Subspace Reconstruction on the EEG Signal Characteristics

EEG signals may be affected by physiological and non-physiological artifacts hindering the analysis of brain activity. Blind source separation methods such as independent component analysis (ICA) are effective ways of improving signal quality by removing components representing non-brain activity. However, most ICA-based artifact removal strategies have limitations, such as individual differences in visual assessment of components. These limitations might be reduced by introducing automatic selection methods for ICA components. On the other hand, new fully automatic artifact removal methods are developed. One of such method is artifact subspace reconstruction (ASR). ASR is a component-based approach, which can be used automatically and with small calculation requirements. The ASR was originally designed to be run not instead of, but in addition to ICA. We compared two automatic signal quality correction approaches: the approach based only on ICA method and the approach where ASR was applied additionally to ICA and run before the ICA. The case study was based on the analysis of data collected from 10 subjects performing four popular experimental paradigms, including resting-state, visual stimulation and oddball task. Statistical analysis of the signal-to-noise ratio showed a significant difference, but not between ICA and ASR followed by ICA. The results show that both methods provided a signal of similar quality, but they were characterised by different usabilities.

Evaluation and comparison of most prevalent artifact reduction methods for EEG acquired simultaneously with fMRI.

Multimodal neuroimaging using EEG and fMRI provides deeper insights into brain function by improving the spatial and temporal resolution of the acquired data. However, simultaneous EEG-fMRI inevitably compromises the quality of the EEG and fMRI signals due to the high degree of interaction between the two systems. Fluctuations in the magnetic flux flowing through the participant and the EEG system, whether due to movement within the magnetic field of the scanner or to changes in magnetic field strength, induce electrical potentials in the EEG recordings that mask the much weaker electrical activity of the neuronal populations. A number of different methods have been proposed to reduce MR artifacts. We present an overview of the most commonly used methods and an evaluation of the methods using three sets of diverse EEG data. We limited the evaluation to open-access and easy-to-use methods and a reference signal regression method using a set of six carbon-wire loops (CWL), which allowed evaluation of their added value. The evaluation was performed by comparing EEG signals recorded outside the MRI scanner with artifact-corrected EEG signals recorded simultaneously with fMRI. To quantify and evaluate the quality of artifact reduction methods in terms of the spectral content of the signal, we analyzed changes in oscillatory activity during a resting-state and a finger tapping motor task. The quality of artifact reduction in the time domain was assessed using data collected during a visual stimulation task. In the study we utilized hierarchical Bayesian probabilistic modeling for statistical inference and observed significant differences between the evaluated methods in the success of artifact reduction and associated signal quality in both the frequency and time domains. In particular, the CWL system proved superior to the other methods evaluated in improving spectral contrast in the alpha and beta bands and in recovering visual evoked responses. Based on the results of the evaluation study, we proposed guidelines for selecting the optimal method for MR artifact reduction.

Vector-valued spline method for the spherical multiple-shell electro-magnetoencephalography problem

Human brain activity is based on electrochemical processes, which can only be measured invasively. Thus, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem though the visualization of the cerebral activity is one of the main research tools in cognitive neuroscience. Here, using an isotropic multiple-shell model for the human head and a quasi-static approach for the electro-magnetic processes, we derive a novel vector-valued spline method based on reproducing kernel Hilbert spaces in order to reconstruct the current from the measurements. The presented method follows the path of former spline approaches and provides classical minimum norm properties. Besides, it minimizes the (infinite-dimensional) Tikhonov–Philips functional which handles the instability of the inverse problem. This optimization problem reduces to solving a finite-dimensional system of linear equations without loss of information, due to its construction. It results in a unique solution which takes into account that only the harmonic and solenoidal component of the neuronal current affects the measurements. Furthermore, we prove a convergence result: the solution achieved by the novel method converges to the generator of the data as the number of measurements increases. The vector splines are applied to the inversion of three synthetic test cases, where the irregularly distributed data situation could be handled very well. Combined with five parameter choice methods, numerical results are shown for synthetic test cases with and without additional Gaussian white noise. Former approaches based on scalar splines are outperformed by the novel vector splines results with respect to the normalized root mean square error. Finally, results for real data acquired during a visual stimulation task are demonstrated. They can be computed quickly and are reasonable with respect to physiological expectations.

Brain Activation During Processing of Depression Emotion in College Students With Premenstrual Syndrome in China: Preliminary Findings.

BackgroundThis study aimed to investigate the neural substrates of processing depression emotion in premenstrual syndrome (PMS) and healthy subjects of college students using blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI).MethodsDuring BOLD-fMRI scanning, 13 PMS patients and 15 healthy controls (HC) performed a picture visual stimulation task during luteal and follicular phases, in which participants and HC were asked to see pictures containing depression and non-depression emotions. Simultaneously, self-rating depression scales (SDS) were employed to evaluate the emotional status of participants.ResultsCompared to HC, right inferior occipital gyrus, right middle occipital gyrus, right lingual gyrus, right fusiform gyrus, right inferior temporal gyrus, cerebelum_crus1_R, cerebelum_6_R, culmen, the cerebellum anterior lobe, tuber, and cerebellar tonsil of PMS patients showed enhanced activation. In contrast, sub-lobar, sub-gyral, extra-nuclear, right orbit part of superior frontal gyrus, right middle temporal gyrus, right orbit part of inferior frontal gyrus, limbic lobe, right insula, bilateral anterior and adjacent cingulate gyrus, bilateral caudate, caudate head, bilateral putamen, and left globus pallidus exhibited decreased activation.ConclusionThe findings indicate that abnormal functional regulation of brain regions such as occipital lobe and cerebellum leads to abnormal changes in emotional regulation, cognitive ability, and attention distribution in PMS patients, implying significant central pathogenesis.

Time-Frequency Representations of Brain Oscillations: Which One Is Better?

Brain oscillations are thought to subserve important functions by organizing the dynamical landscape of neural circuits. The expression of such oscillations in neural signals is usually evaluated using time-frequency representations (TFR), which resolve oscillatory processes in both time and frequency. While a vast number of methods exist to compute TFRs, there is often no objective criterion to decide which one is better. In feature-rich data, such as that recorded from the brain, sources of noise and unrelated processes abound and contaminate results. The impact of these distractor sources is especially problematic, such that TFRs that are more robust to contaminants are expected to provide more useful representations. In addition, the minutiae of the techniques themselves impart better or worse time and frequency resolutions, which also influence the usefulness of the TFRs. Here, we introduce a methodology to evaluate the “quality” of TFRs of neural signals by quantifying how much information they retain about the experimental condition during visual stimulation and recognition tasks, in mice and humans, respectively. We used machine learning to discriminate between various experimental conditions based on TFRs computed with different methods. We found that various methods provide more or less informative TFRs depending on the characteristics of the data. In general, however, more advanced techniques, such as the superlet transform, seem to provide better results for complex time-frequency landscapes, such as those extracted from electroencephalography signals. Finally, we introduce a method based on feature perturbation that is able to quantify how much time-frequency components contribute to the correct discrimination among experimental conditions. The methodology introduced in the present study may be extended to other analyses of neural data, enabling the discovery of data features that are modulated by the experimental manipulation.

Altered linear coupling between stimulus-evoked blood flow and oxygen metabolism in the aging human brain.

Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC. To test this hypothesis, calibrated functional magnetic resonance imaging (cfMRI) was used to characterize age-related changes in cerebral blood flow (CBF) and oxygen metabolism during visual cortex stimulation. Thirty-three younger and 27 older participants underwent cfMRI scanning during both an attention-controlled visual stimulation task and a hypercapnia paradigm used to calibrate the blood-oxygen-level-dependent signal. Measurement of stimulus-evoked blood flow and oxygen metabolism permitted calculation of the NVC ratio to assess the integrity of neural-vascular communication. Consistent with our hypothesis, we observed monotonic NVC ratio increases with increasing visual stimulation frequency in younger adults but not in older adults. Age-related changes in stimulus-evoked cerebrovascular and neurometabolic signal could not fully explain this disruption; increases in stimulus-evoked neurometabolic activity elicited corresponding increases in stimulus-evoked CBF in younger but not in older adults. These results implicate age-related, demand-dependent failures of the neural-glial-vascular structures that comprise the NVC system.

Sparse EEG source localization in frequency domain.

This work presents an approach for EEG source localization when strong priors on predominant frequencies in the activities of the source are available. We describe the fundamentals of the used source reconstruction method based on a greedy approach, which can be applied indifferently in the time or frequency domain. The method is evaluated using simulated data reproducing realistic recorded activities in the context of fast periodic visual stimulation. In particular the advantage of reconstructing the source in the frequency domain against time domain is quantified in a realistic setup. Finally, the performances of the method are illustrated on real EEG signals recorded during a fast periodic visual stimulation task.

A line through the brain: implementation of human line-scanning at 7T for ultra-high spatiotemporal resolution fMRI

Functional magnetic resonance imaging (fMRI) is a widely used tool in neuroscience to detect neurally evoked responses, e.g. the blood oxygenation level-dependent (BOLD) signal. Typically, BOLD fMRI has millimeter spatial resolution and temporal resolution of one to few seconds. To study the sub-millimeter structures and activity of the cortical gray matter, the field needs an fMRI method with high spatial and temporal resolution. Line-scanning fMRI achieves very high spatial resolution and high sampling rate, at the cost of a sacrifice in volume coverage. Here, we present a human line-scanning implementation on a 7T MRI system. First, we investigate the quality of the saturation pulses that suppress MR signal outside the line. Second, we established the best coil combination for reconstruction. Finally, we applied the line-scanning method in the occipital lobe during a visual stimulation task, showing BOLD responses along cortical depth, every 250 µm with a 200 ms repetition time (TR). We found a good correspondence of t-statistics values with 2D gradient-echo echo planar imaging (GE-EPI) BOLD fMRI data with the same temporal resolution and voxel volume (R = 0.6 ± 0.2). In summary, we demonstrate the feasibility of line-scanning in humans and this opens line-scanning fMRI for applications in cognitive and clinical neuroscience.

Multichannel near-infrared spectroscopy brain imaging system for small animals in mobile conditions.

.Significance: We propose a customized animal-specific head cap and an near-infrared spectroscopy (NIRS) system to obtain NIRS signals in mobile small animals. NIRS studies in mobile small animals provide a feasible solution for comprehensive brain function studies.Aim: We aim to develop and validate a multichannel NIRS system capable of performing functional brain imaging along with a closed-box stimulation kit for small animals in mobile conditions.Approach: The customized NIRS system uses light-weight long optical fibers, along with a customized light-weight head cap to securely attach the optical fibers to the mouse. A customized stimulation box was designed to perform various stimuli in a controlled environment. The system performance was tested in a visual stimulation task on eight anesthetized mice and eight freely moving mice.Results: Following the visual stimulation task, we observed a significant stimulation-related oxyhemoglobin (HbO) increase in the visual cortex of freely moving mice during the task. In contrast, HbO concentration did not change significantly in the visual cortex of anesthetized mice.Conclusions: We demonstrate the feasibility of a wearable, multichannel NIRS system for small animals in a less confined experimental design.

Incorporation of anatomical MRI knowledge for enhanced mapping of brain metabolism using functional PET

Functional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static or dynamic bolus PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional denosing methods using both simulated and in vivo task fPET datasets. The results demonstrate that the MR-guided fPET framework denoises the fPET images and improves the partial volume correction, consequently enhancing the sensitivity to identify brain activation, and improving the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.

An analysis framework for the integration of broadband NIRS and EEG to assess neurovascular and neurometabolic coupling

With the rapid growth of optical-based neuroimaging to explore human brain functioning, our research group has been developing broadband Near Infrared Spectroscopy (bNIRS) instruments, a technological extension to functional Near Infrared Spectroscopy (fNIRS). bNIRS has the unique capacity of monitoring brain haemodynamics/oxygenation (measuring oxygenated and deoxygenated haemoglobin), and metabolism (measuring the changes in the redox state of cytochrome-c-oxidase). When combined with electroencephalography (EEG), bNIRS provides a unique neuromonitoring platform to explore neurovascular coupling mechanisms. In this paper, we present a novel pipeline for the integrated analysis of bNIRS and EEG signals, and demonstrate its use on multi-channel bNIRS data recorded with concurrent EEG on healthy adults during a visual stimulation task. We introduce the use of the Finite Impulse Response functions within the General Linear Model for bNIRS and show its feasibility to statistically localize the haemodynamic and metabolic activity in the occipital cortex. Moreover, our results suggest that the fusion of haemodynamic and metabolic measures unveils additional information on brain functioning over haemodynamic imaging alone. The cross-correlation-based analysis of interrelationships between electrical (EEG) and haemodynamic/metabolic (bNIRS) activity revealed that the bNIRS metabolic signal offers a unique marker of brain activity, being more closely coupled to the neuronal EEG response.

Estimation of simultaneous BOLD and dynamic FDG metabolic brain activations using a multimodality concatenated ICA (mcICA) method

Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analysing the simultaneously acquired blood-oxygen-level dependant functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyse cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.

The role of anterior and posterior insula in male genital response and in visual attention: an exploratory multimodal fMRI study

Several studies highlighted the role of insula on several functions and in sexual behavior. This exploratory study examines the relationships among genital responses, brain responses, and eye movements, to disentangle the role played by the anterior and posterior insula during different stages of male sexual response and during visual attention to sexual stimuli. In 19 healthy men, fMRI, eye movement, and penile tumescence data were collected during a visual sexual stimulation task. After a whole-brain analysis comparing neutral and sexual clips and confirming a role for the bilateral insulae, we selected two bilateral seed regions in anterior and posterior insula for functional connectivity analysis. Single-ROI-GLMs were run for the FC target regions. Single-ROI-GLMs were performed based on areas to which participants fixate: “Faces”, “Genitals,” and “Background” with the contrast “Genitals > Faces”. Single-ROI-GLMs with baseline, onset, and sustained PT response for the sexual clips were performed. We found stronger effects for the posterior than the anterior insula. In the target regions of the posterior insula, we found three different pathways: the first involved in visual attention, onset of erection, and sustained erection; the second involved only in the onset of erection, and the third limited to sustained erection.

Binding of the synaptic vesicle radiotracer [11C]UCB-J is unchanged during functional brain activation using a visual stimulation task

The positron emission tomography radioligand [11C]UCB-J binds to synaptic vesicle glycoprotein 2 A (SV2A), a regulator of vesicle release. Increased neuronal firing could potentially affect tracer concentrations if binding site availability is altered during vesicle exocytosis. This study assessed whether physiological brain activation induces changes in [11C]UCB-J tissue influx (K1), volume of distribution (VT), or binding potential (BPND). Healthy volunteers (n = 7) underwent 60-min [11C]UCB-J PET scans at baseline and during intermittent presentation of 8-Hz checkerboard visual stimulation. Sensitivity to intermittent changes in kinetic parameters was assessed in simulations, and visual stimulation was repeated using functional magnetic resonance imaging to characterize neural responses. VT and K1 were determined using the one-tissue compartment model and BPND using the simplified reference tissue model. In primary visual cortex, K1 increased 34.3 ± 15.5% (p = 0.001) during stimulation, with no change in other regions (ps > 0.12). K1 change was correlated with fMRI BOLD response (r = 0.77, p = 0.043). There was no change in VT (−3.9 ± 8.8%, p = 0.33) or BPND (−0.2 ± 9.6%, p = 0.94) in visual cortex nor other regions (ps > 0.19). Therefore, despite robust increases in regional tracer influx due to blood flow increases, binding measures were unchanged during stimulation. [11C]UCB-J VT and BPND are likely to be stable in vivo measures of synaptic density.

APOE gene-dependent BOLD responses to a breath-hold across the adult lifespan.

Age and apolipoprotein E (APOE) e4 genotype are two of the strongest known risk factors for sporadic Alzheimer's disease (AD). Neuroimaging has shown hemodynamic response changes with age, in asymptomatic carriers of the APOE e4 allele, and in AD. In this study, we aimed to characterize and differentiate age- and APOE gene-specific hemodynamic changes to breath-hold and visual stimulation. A further aim was to study whether these responses were modulated by 3-day intake of nitrate, a nitric oxide (NO) source. The study was designed as a randomized, double-blinded, placebo-controlled crossover study, and the study cohort comprised 41 APOE e4 carriers (e3/e4 or e4/e4 genotype) and 40 non-carriers (e3/e3 genotype) aged 30–70 years at enrollment. The participants underwent two scanning sessions, each preceded by ingestion of sodium nitrate or sodium chloride (control). During functional magnetic resonance imaging (fMRI) sessions, participants performed two concurrent tasks; a breath-hold task to probe cerebrovascular reactivity and a visual stimulation task to evoke functional hyperemia, respectively. We found that the blood oxygenation level dependent (BOLD) hemodynamic response to breath-hold was altered in APOE e4 carriers relative to non-carriers. Mid-aged (50–60 years of age) e4 carriers exhibited a significantly increased peak time relative to mid-aged e3 carriers, and peak time for younger (30–40 years of age) e4 carriers was significantly shorter than that of mid-aged e4 carriers. The response width was significantly increased for e4 carriers. The response peak magnitude significantly decreased with age. For the visual stimulation task, we found age-related changes, with reduced response magnitude with age but no significant effect of APOE allele type. We found no effect of nitrate ingestion on BOLD responses evoked by the breath-hold and visual stimulation tasks. The APOE gene-dependent response to breath-hold may reflect NO-independent differences in vascular function.

The developmental time course and topographic distribution of individual-level monkey face discrimination in the infant brain

The ability to discriminate between faces from unfamiliar face groups has previously been found to decrease across the first year of life. Here, individual-level discrimination of faces within a previously unfamiliar group was investigated by measuring neural responses to monkey faces. Six- and 9-month-old infants (n = 42) completed a Fast Periodic Visual Stimulation (FPVS) task while steady state visual evoked potentials (ssVEPs) were recorded. Using an oddball task design (e.g., infrequent changes in face identity) faces were presented at a 6Hz (1 face approximately every 167ms) stimulation rate and every 1.2Hz different individual monkey faces were presented. Significant SNRs at 1.2Hz in both 6- and 9-month-old infants suggest that neural responses, recorded over posterior scalp regions, remain sensitive to individual-level differences within an unfamiliar face group despite previous behavioral evidence of decreased discrimination. However, the topographic distribution of the 1.2Hz response varied by age, suggesting that 6- and 9-month-old infants are using different neural populations to discriminate unfamiliar faces at the individual level.

Evaluation of Visual-Evoked Cerebral Metabolic Rate of Oxygen as a Diagnostic Marker in Multiple Sclerosis.

A multiple sclerosis (MS) diagnosis often relies upon clinical presentation and qualitative analysis of standard, magnetic resonance brain images. However, the accuracy of MS diagnoses can be improved by utilizing advanced brain imaging methods. We assessed the accuracy of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO2), in classifying MS patients and closely age- and sex-matched healthy control (HC) participants. MS patients and HCs underwent calibrated functional magnetic resonance imaging (cfMRI) during a visual stimulation task, diffusion tensor imaging, T1- and T2-weighted imaging, neuropsychological testing, and completed self-report questionnaires. Using resampling techniques to avoid bias and increase the generalizability of the results, we assessed the accuracy of veCMRO2 in classifying MS patients and HCs. veCMRO2 classification accuracy was also examined in the context of other evoked visuofunctional measures, white matter microstructural integrity, lesion-based measures from T2-weighted imaging, atrophy measures from T1-weighted imaging, neuropsychological tests, and self-report assays of clinical symptomology. veCMRO2 was significant and within the top 16% of measures (43 total) in classifying MS status using both within-sample (82% accuracy) and out-of-sample (77% accuracy) observations. High accuracy of veCMRO2 in classifying MS demonstrated an encouraging first step toward establishing veCMRO2 as a neurodiagnostic marker of MS.

Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data.

.In diffuse optical tomography (DOT), overlapping and multidistance measurements are required to reconstruct depth-resolved images of oxy- () and deoxy- (HHb) hemoglobin concentration changes occurring in the brain. These can be considered an indirect measure of brain activity, under the assumption of intact neurovascular coupling. Broadband systems also allow changes in the redox state of cytochrome c oxidase (oxCCO) to be measured, which can be an important biomarker when neurovascular coupling is impaired. We used DOT to reconstruct images of , , and from data acquired with a broadband system. Four healthy volunteers were measured while performing a visual stimulation task (4-Hz inverting checkerboard). The broadband system was configured to allow multidistance and overlapping measurements of the participants’ visual cortex with 32 channels. A multispectral approach was employed to reconstruct changes in concentration of the three chromophores during the visual stimulation. A clear and focused activation was reconstructed in the left occipital cortex of all participants. The difference between the residuals of the three-chromophore model and of the two-chromophore model (recovering only and ) exhibits a spectrum similar to that of oxCCO. These results form a basis for further studies aimed to further optimize image reconstruction of .

Identification of neurovascular changes associated with cerebral amyloid angiopathy from subject-specific hemodynamic response functions

Cerebral amyloid angiopathy (CAA) is a small-vessel disease preferentially affecting posterior brain regions. Recent evidence has demonstrated the efficacy of functional MRI in detecting CAA-related neurovascular injury, however, it is unknown whether such perturbations are associated with changes in the hemodynamic response function (HRF). Here we estimated HRFs from two different brain regions from block design activation data, in light of recent findings demonstrating how block designs can accurately reflect HRF parameter estimates while maximizing signal detection. Patients with a diagnosis of probable CAA and healthy controls performed motor and visual stimulation tasks. Time-to-peak (TTP), full-width at half-maximum (FWHM), and area under the curve (AUC) of the estimated HRFs were compared between groups and to MRI features associated with CAA including cerebral microbleed (CMB) count. Motor HRFs in CAA patients showed significantly wider FWHM (P = 0.006) and delayed TTP (P = 0.03) compared to controls. In the patient group, visual HRF FWHM was positively associated with CMB count (P = 0.03). These findings indicate that hemodynamic abnormalities in patients with CAA may be reflected in HRFs estimated from block designs across different brain regions. Moreover, visual FWHM may be linked to structural MR indications associated with CAA.