The Representation of Time Windows in Primate Auditory Cortex.

Whether human and nonhuman primates process the temporal dimension of sound similarly remains an open question. We examined the brain basis for the processing of acoustic time windows in rhesus macaques using stimuli simulating the spectrotemporal complexity of vocalizations. We conducted functional magnetic resonance imaging in awake macaques to identify the functional anatomy of response patterns to different time windows. We then contrasted it against the responses to identical stimuli used previously in humans. Despite a similar overall pattern, ranging from the processing of shorter time windows in core areas to longer time windows in lateral belt and parabelt areas, monkeys exhibited lower sensitivity to longer time windows than humans. This difference in neuronal sensitivity might be explained by a specialization of the human brain for processing longer time windows in speech.

Viewing ambiguous social interactions increases functional connectivity between frontal and temporal nodes of the social brain.

Social behaviour is coordinated by a network of brain regions, including those involved in the perception of social stimuli and those involved in complex functions like inferring perceptual and mental states and controlling social interactions. The properties and function of many of these regions in isolation is relatively well-understood, but less is known about how these regions interact whilst processing dynamic social interactions. To investigate whether the functional connectivity between brain regions is modulated by social context, we collected functional MRI (fMRI) data from male monkeys (Macaca mulatta) viewing videos of social interactions labelled as "affiliative", "aggressive", or "ambiguous". We show activation related to the perception of social interactions along both banks of the superior temporal sulcus, parietal cortex, medial and lateral frontal cortex, and the caudate nucleus. Within this network, we show that fronto-temporal functional connectivity is significantly modulated by social context. Crucially, we link the observation of specific behaviours to changes in functional connectivity within our network. Viewing aggressive behaviour was associated with a limited increase in temporo-temporal and a weak increase in cingulate-temporal connectivity. By contrast, viewing interactions where the outcome was uncertain was associated with a pronounced increase in temporo-temporal, and cingulate-temporal functional connectivity. We hypothesise that this widespread network synchronisation occurs when cingulate and temporal areas coordinate their activity when more difficult social inferences are being made.SIGNIFICANCE STATEMENT:Processing social information from our environment requires the activation of several brain regions, which are concentrated within the frontal and temporal lobes. However, little is known about how these areas interact to facilitate the processing of different social interactions. Here we show that functional connectivity within and between the frontal and temporal lobes is modulated by social context. Specifically, we demonstrate that viewing social interactions where the outcome was unclear is associated with increased synchrony within and between the cingulate cortex and temporal cortices. These findings suggest that the coordination between the cingulate and temporal cortices is enhanced when more difficult social inferences are being made.

Auditory motion-specific mechanisms in the primate brain.

This work examined the mechanisms underlying auditory motion processing in the auditory cortex of awake monkeys using functional magnetic resonance imaging (fMRI). We tested to what extent auditory motion analysis can be explained by the linear combination of static spatial mechanisms, spectrotemporal processes, and their interaction. We found that the posterior auditory cortex, including A1 and the surrounding caudal belt and parabelt, is involved in auditory motion analysis. Static spatial and spectrotemporal processes were able to fully explain motion-induced activation in most parts of the auditory cortex, including A1, but not in circumscribed regions of the posterior belt and parabelt cortex. We show that in these regions motion-specific processes contribute to the activation, providing the first demonstration that auditory motion is not simply deduced from changes in static spatial location. These results demonstrate that parallel mechanisms for motion and static spatial analysis coexist within the auditory dorsal stream.

Effect of nitrite on the electroencephalographic activity in the healthy brain.

BACKGROUND: Nitrite is a major intravascular store for nitric oxide. The conversion of nitrite to the active nitric oxide occurs mainly under hypoxic conditions to increase blood flow where it is needed the most. The use of nitrite is, therefore, being evaluated widely to reduce the brain injury in conditions resulting in cerebral hypoxia, such as cardiac arrest, ischaemic stroke or subarachnoid haemorrhage. However, as it is still unknown how exogenous nitrite affects the brain activity of healthy individuals, it is difficult to clearly understand how it affects the ischaemic brain. OBJECTIVE: Here we performed a double-blind placebo-controlled crossover study to investigate the effects of nitrite on neural activity in the healthy brain. METHODS: Twenty-one healthy volunteers were recruited into the study. All participants received a continuous infusion of sodium nitrite (0.6 mg/kg/h) on one occasion and placebo (sodium chloride) on another occasion. Electroencephalogram was recorded before the start and during the infusion. We computed the power spectrum density within the conventional frequency bands (delta, theta, alpha, beta), and the ratio of the power within the alpha and delta bands. We also measured peripheral cardiorespiratory physiology and cerebral blood flow velocities. RESULTS: We found no significant effect of nitrite on the power spectrum density in any frequency band. Similarly, the alpha-delta power ratio did not differ between the two conditions. The peripheral cardiorespiratory physiology and middle cerebral artery velocity and associated indices were also unaffected by the nitrite infusion. However, nitrite infusion decreased the mean blood pressure and increased the methaemoglobin concentration in the blood. CONCLUSION: Our study shows that exogenous sodium nitrite does not alter the electrical activity in the healthy brain. This might be because the sodium nitrite is converted to vasoactive nitric oxide in areas of hypoxia, and in the healthy brain there is no significant amount of conversion due to lack of hypoxia. However, this lack of change in the power spectrum density in healthy people emphasises the specificity of the brain's response to nitrite in disease.

Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans.

Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more likely to have good outcomes and ranges from 0 (no collaterals) to 3 (complete collaterals). In this study, we used a machine learning approach to categorise the degree of collateral flow in 98 patients who were eligible for mechanical thrombectomy and generate an e-CTA collateral score (CTA-CS) for each patient (e-STROKE SUITE, Brainomix Ltd., Oxford, UK). Three experienced neuroradiologists (NRs) independently estimated the CTA-CS, first without and then with knowledge of the e-CTA output, before finally agreeing on a consensus score. Addition of the e-CTA improved the intraclass correlation coefficient (ICC) between NRs from 0.58 (0.46-0.67) to 0.77 (0.66-0.85, p = 0.003). Automated e-CTA, without NR input, agreed with the consensus score in 90% of scans with the remaining 10% within 1 point of the consensus (ICC 0.93, 0.90-0.95). Sensitivity and specificity for identifying favourable collateral flow (collateral score 2-3) were 0.99 (0.93-1.00) and 0.94 (0.70-1.00), respectively. e-CTA correlated with the Alberta Stroke Programme Early CT Score (Spearman correlation 0.46, p < 0.001) highlighting the value of good collateral flow in maintaining tissue viability prior to reperfusion. In conclusion, -e-CTA provides a real-time and fully automated approach to collateral scoring with the potential to improve consistency of image interpretation and to independently quantify collateral scores even without expert rater input.

Quantitative EEG parameters correlate with the progression of human prion diseases.

BACKGROUND: Prion diseases are universally fatal and often rapidly progressive neurodegenerative diseases. EEG has long been used in the diagnosis of sporadic Creutzfeldt-Jakob disease; however, the characteristic waveforms do not occur in all types of prion diseases. Here, we re-evaluate the utility of EEG by focusing on the development of biomarkers. We test whether abnormal quantitative EEG parameters can be used to measure disease progression in prion diseases or predict disease onset in healthy individuals at risk of disease. METHODS: In the National Prion Monitoring Cohort study, we did quantitative encephalography on 301 occasions in 29 healthy controls and 67 patients with prion disease. The patients had either inherited prion disease or sporadic Creutzfeldt-Jakob disease. We computed the main background frequency, the α and θ power and the α/θ power ratio, then averaged these within 5 electrode groups. These measurements were then compared among participant groups and correlated with functional and cognitive scores cross-sectionally and longitudinally. RESULTS: We found lower main background frequency, α power and α/θ power ratio and higher θ power in patients compared to control participants. The main background frequency, the power in the α band and the α/θ power ratio also differed in a consistent way among the patient groups. Moreover, the main background frequency and the α/θ power ratio correlated significantly with functional and cognitive scores. Longitudinally, change in these parameters also showed significant correlation with the change in clinical and cognitive scores. CONCLUSIONS: Our findings support the use of quantitative EEG to follow the progression of prion disease, with potential to help evaluate the treatment effects in future clinical-trials.

A new approach to corpus callosum anomalies in idiopathic scoliosis using diffusion tensor magnetic resonance imaging.

PURPOSE: Idiopathic scoliosis (IS) is a frequent 3D structural deformity of the spine with a multi-factorial aetiology which remains largely unclear. In the last decade, human magnetic resonance imaging (MRI) morphometry studies (e.g. cortical thickness, 2D shape of the corpus callosum) have aimed to investigate the potential contribution of the central nervous system in the etiopathogenesis of IS. Recent developments in diffusion tensor imaging (DTI) allow us to extend the previous work to the study of white matter microstructure. Here, we hypothesized that part of the corpus callosum could show a difference in white matter microstructure in IS patients as compared to healthy controls. METHODS: We acquired DTI in 10 girls with IS and in 49 gender-matched controls to quantify the fractional anisotropy (FA) along the corpus callosum. RESULTS: Despite a very similar pattern of FA along the corpus callosum (maxima in the splenium and the genu and minimum in the isthmus), we found a significantly lower FA in the body in patients with IS as compared to control subjects. This region is known to connect the motor and premotor cortices of the two hemispheres. CONCLUSION: This first diffusion magnetic resonance imaging brain study in IS patients, suggests that differences in white matter development, such as synchronization of axonal myelination and pruning could be involved in the etiopathogenesis of IS.

Interhemispheric differences in auditory processing revealed by fMRI in awake rhesus monkeys.

Lesion studies in monkeys have suggested a modest left hemisphere dominance for processing species-specific vocalizations, the neural basis of which has thus far remained unclear. We used contrast agent-enhanced functional magnetic resonance imaging to map the regions of the rhesus monkey brain involved in processing conspecific vocalizations as well as human speech and emotional sounds. Control conditions included scrambled versions of all 3 stimuli and silence. Compared with silence, all stimuli activated widespread parts of the auditory cortex and subcortical auditory structures with a right hemispheric bias at the level of the auditory core. However, comparing intact with scrambled sounds revealed a leftward bias in the auditory belt and the parabelt. The left-sided dominance was stronger and more robust for human speech than for rhesus vocalizations and hence does not reflect conspecific call selectivity but rather the processing of complex spectrotemporal patterns, such as those present in human speech and in some of the rhesus monkey vocalizations. This was confirmed by regressing brain activity with a model-derived parameter indexing the prevalence of such patterns. Our results indicate that processing of vocal sounds in the lateral belt and parabelt is asymmetric in monkeys, as predicted from lesion studies.

Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study.

Background: The Alberta Stroke Program Early CT Score (ASPECTS) is used to quantify the extent of injury to the brain following acute ischemic stroke (AIS) and to inform treatment decisions. The e-ASPECTS software uses artificial intelligence methods to automatically process non-contrast CT (NCCT) brain scans from patients with AIS affecting the middle cerebral artery (MCA) territory and generate an ASPECTS. This study aimed to evaluate the impact of e-ASPECTS (Brainomix, Oxford, UK) on the performance of US physicians compared to a consensus ground truth. Methods: The study used a multi-reader, multi-case design. A total of 10 US board-certified physicians (neurologists and neuroradiologists) scored 54 NCCT brain scans of patients with AIS affecting the MCA territory. Each reader scored each scan on two occasions: once with and once without reference to the e-ASPECTS software, in random order. Agreement with a reference standard (expert consensus read with reference to follow-up imaging) was evaluated with and without software support. Results: A comparison of the area under the curve (AUC) for each reader showed a significant improvement from 0.81 to 0.83 (p = 0.028) with the support of the e-ASPECTS tool. The agreement of reader ASPECTS scoring with the reference standard was improved with e-ASPECTS compared to unassisted reading of scans: Cohen's kappa improved from 0.60 to 0.65, and the case-based weighted Kappa improved from 0.70 to 0.81. Conclusion: Decision support with the e-ASPECTS software significantly improves the accuracy of ASPECTS scoring, even by expert US neurologists and neuroradiologists.

Default mode of brain function in monkeys.

Human neuroimaging has revealed a specific network of brain regions-the default-mode network (DMN)-that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment.

Processing of vocalizations in humans and monkeys: a comparative fMRI study.

Humans and many other animals use acoustical signals to mediate social interactions with conspecifics. The evolution of sound-based communication is still poorly understood and its neural correlates have only recently begun to be investigated. In the present study, we applied functional MRI to humans and macaque monkeys listening to identical stimuli in order to compare the cortical networks involved in the processing of vocalizations. At the first stages of auditory processing, both species showed similar fMRI activity maps within and around the lateral sulcus (the Sylvian fissure in humans). Monkeys showed remarkably similar responses to monkey calls and to human vocal sounds (speech or otherwise), mainly in the lateral sulcus and the adjacent superior temporal gyrus (STG). In contrast, a preference for human vocalizations and especially for speech was observed in the human STG and superior temporal sulcus (STS). The STS and Broca's region were especially responsive to intelligible utterances. The evolution of the language faculty in humans appears to have recruited most of the STS. It may be that in monkeys, a much simpler repertoire of vocalizations requires less involvement of this temporal territory.

Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction.

Background and Purpose: Mechanical thrombectomy greatly improves stroke outcomes. Nonetheless, some patients fall short of full recovery despite good reperfusion. The purpose of this study was to develop machine learning (ML) models for the pre-interventional prediction of functional outcome at 3 months of thrombectomy in acute ischemic stroke (AIS), using clinical and auto-extractable radiological information consistently available upon first emergency evaluation. Materials and Methods: A two-center retrospective cohort of 293 patients with AIS who underwent thrombectomy was analyzed. ML models were developed to predict dichotomized modified Rankin score at 90 days (mRS-90) using clinical and imaging features, both separately and combined. Conventional and experimental imaging biomarkers were quantified using automated image-processing software from non-contract computed tomography (CT) and computed tomography angiography (CTA). Shapley Additive Explanation (SHAP) was applied for model interpretability and predictor importance analysis of the optimal model. Results: Merging clinical and imaging features returned the best results for mRS-90 prediction. The best performing classifier was Extreme Gradient Boosting (XGB) with an area under the receiver operating characteristic curve (AUC) = 84% using selected features. The most important classifying features were age, baseline National Institutes of Health Stroke Scale (NIHSS), occlusion side, degree of brain atrophy [primarily represented by cortical cerebrospinal fluid (CSF) volume and lateral ventricle volume], early ischemic core [primarily represented by e-Alberta Stroke Program Early CT Score (ASPECTS)], and collateral circulation deficit volume on CTA. Conclusion: Machine learning that is applied to quantifiable image features from CT and CTA alongside basic clinical characteristics constitutes a promising automated method in the pre-interventional prediction of stroke prognosis. Interpretable models allow for exploring which initial features contribute the most to post-thrombectomy outcome prediction overall and for each individual patient outcome.

Hyperdense Artery Sign in Patients With Acute Ischemic Stroke-Automated Detection With Artificial Intelligence-Driven Software.

Background: Hyperdense artery sign (HAS) on non-contrast CT (NCCT) can indicate a large vessel occlusion (LVO) in patients with acute ischemic stroke. HAS detection belongs to routine reporting in patients with acute stroke and can help to identify patients in whom LVO is not initially suspected. We sought to evaluate automated HAS detection by commercial software and compared its performance to that of trained physicians against a reference standard. Methods: Non-contrast CT scans from 154 patients with and without LVO proven by CT angiography (CTA) were independently rated for HAS by two blinded neuroradiologists and an AI-driven algorithm (Brainomix®). Sensitivity and specificity were analyzed for the clinicians and the software. As a secondary analysis, the clot length was automatically calculated by the software and compared with the length manually outlined on CTA images as the reference standard. Results: Among 154 patients, 84 (54.5%) had CTA-proven LVO. HAS on the correct side was detected with a sensitivity and specificity of 0.77 (CI:0.66-0.85) and 0.87 (0.77-0.94), 0.8 (0.69-0.88) and 0.97 (0.89-0.99), and 0.93 (0.84-0.97) and 0.71 (0.59-0.81) by the software and readers 1 and 2, respectively. The automated estimation of the thrombus length was in moderate agreement with the CTA-based reference standard [intraclass correlation coefficient (ICC) 0.73]. Conclusion: Automated detection of HAS and estimation of thrombus length on NCCT by the tested software is feasible with a sensitivity and specificity comparable to that of trained neuroradiologists.

Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy.

Background: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute changes (most commonly Alberta Stroke Programme Early CT Score, ASPECTS, at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome. Aims: To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT. Methods: In 215 patients with anterior circulation stroke, who subsequently underwent EVT, automated analysis of presenting non-contrast CT scans was used to determine acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Univariate and multivariate logistic regression were used to identify significant predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT. Results: For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0-2 and death at 90 days, whereas age did not reach significance in multivariate analysis. Conversely, for short-term NIHSS improvement, AIV and age were significant predictors, unlike presenting NIHSS. The interaction between age and NIHSS was similar to the interaction of AIV and atrophy for mRS 0-2 at 90 days. Conclusion: Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcome and may improve long-term prognostication in EVT. These results provide a basis for future development of predictive tools built into decision-aiding software in stroke.

Anterior regions of monkey parietal cortex process visual 3D shape.

The intraparietal cortex is involved in the control of visually guided actions, like reach-to-grasp movements, which require extracting the 3D shape and position of objects from 2D retinal images. Using fMRI in behaving monkeys, we investigated the role of the intraparietal cortex in processing stereoscopic information for recovering the depth structure and the position in depth of objects. We found that while several areas (CIP, LIP, and AIP on the lateral bank; PIP and MIP on the medial bank) are activated by stereoscopic stimuli, AIP and an adjoining portion of LIP are sensitive only to depth structure. Furthermore, only these two regions are sensitive to both the depth structure and the 2D shape of small objects. These results indicate that extracting 3D spatial information from stereo involves several intraparietal areas, among which AIP and anterior LIP are more specifically engaged in extracting the 3D shape of objects.

Direct visualization of non-human primate subcortical nuclei with contrast-enhanced high field MRI.

Subcortical nuclei are increasingly targeted for deep brain stimulation (DBS) and for gene transfer to treat neurological and psychiatric disorders. For a successful outcome in patients, it is critical to place DBS electrodes or infuse viral vectors accurately within targeted nuclei. However current MRI approaches are still limited to localize brainstem and basal ganglia nuclei accurately. By combining ultra-high resolution structural MRI and contrast-enhanced MRI using iron oxide nanoparticles at high field (3T and 7T), we could precisely locate the subcortical nuclei, in particular the subthalamic nucleus in macaques, and validate this location by intracranial electrophysiological mapping. The present data pave the way to a clinical application.

Social prediction modulates activity of macaque superior temporal cortex.

The ability to attribute thoughts to others, also called theory of mind (TOM), has been extensively studied in humans; however, its evolutionary origins have been challenged. Computationally, the basis of TOM has been interpreted within the predictive coding framework and associated with activity in the temporoparietal junction (TPJ). Here, we revealed, using a nonlinguistic task and functional magnetic resonance imaging, that activity in a region of the macaque middle superior temporal cortex was specifically modulated by the predictability of social situations. As in human TPJ, this region could be distinguished from other temporal regions involved in face processing. Our result suggests the existence of a precursor for the TOM ability in the last common ancestor of human and Old World monkeys.

Rapid event-related, BOLD fMRI, non-human primates (NHP): choose two out of three.

Human functional magnetic resonance imaging (fMRI) typically employs the blood-oxygen-level-dependent (BOLD) contrast mechanism. In non-human primates (NHP), contrast enhancement is possible using monocrystalline iron-oxide nanoparticles (MION) contrast agent, which has a more temporally extended response function. However, using BOLD fMRI in NHP is desirable for interspecies comparison, and the BOLD signal's faster response function promises to be beneficial for rapid event-related (rER) designs. Here, we used rER BOLD fMRI in macaque monkeys while viewing real-world images, and found visual responses and category selectivity consistent with previous studies. However, activity estimates were very noisy, suggesting that the lower contrast-to-noise ratio of BOLD, suboptimal behavioural performance, and motion artefacts, in combination, render rER BOLD fMRI challenging in NHP. Previous studies have shown that rER fMRI is possible in macaques with MION, despite MION's prolonged response function. To understand this, we conducted simulations of the BOLD and MION response during rER, and found that no matter how fast the design, the greater amplitude of the MION response outweighs the contrast loss caused by greater temporal smoothing. We conclude that although any two of the three elements (rER, BOLD, NHP) have been shown to work well, the combination of all three is particularly challenging.