Unifying prospective and retrospective interval-time estimation: a fading-gaussian activation-based model of interval-timing

Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies (Block et al., 2010) reveals a striking interaction between the way in which temporal judgments are queried and cognitive load on participants’ judgments of interval duration. For retrospective time judgments, estimates under high cognitive load are longer than under low cognitive load. For prospective judgments, the reverse pattern holds, with increased cognitive load leading to shorter estimates. We describe GAMIT, a Gaussian spreading-activation model, in which the sampling rate of an activation trace is differentially affected by cognitive load. The model unifies prospective and retrospective time estimation, normally considered separately, by relating them to the same underlying process. The scalar property of time estimation arises naturally from the model dynamics and the model shows the appropriate interaction between mode of query and cognitive load

Bridging thrombolysis in atrial fibrillation stroke is associated with increased hemorrhagic complications without improved outcomes

BACKGROUND: Atrial fibrillation (AF) associated ischemic stroke is associated with worse functional outcomes, less effective recanalization, and increased rates of hemorrhagic complications after intravenous thrombolysis (IVT). Conversely, AF is not associated with hemorrhagic complications or functional outcomes in patients undergoing mechanical thrombectomy (MT). This differential effect of MT and IVT in AF associated stroke raises the question of whether bridging thrombolysis increases hemorrhagic complications in AF patients undergoing MT. METHODS: This international cohort study of 22 comprehensive stroke centers analyzed patients with large vessel occlusion (LVO) undergoing MT between June 1, 2015 and December 31, 2020. Patients were divided into four groups based on comorbid AF and IVT exposure. Baseline patient characteristics, complications, and outcomes were reported and compared. RESULTS: 6461 patients underwent MT for LVO. 2311 (35.8%) patients had comorbid AF. In non-AF patients, bridging therapy improved the odds of good 90 day functional outcomes (adjusted OR (aOR) 1.29, 95% CI 1.03 to 1.60, p=0.025) and did not increase hemorrhagic complications. In AF patients, bridging therapy led to significant increases in symptomatic intracranial hemorrhage and parenchymal hematoma type 2 (aOR 1.66, 1.07 to 2.57, p=0.024) without any benefit in 90 day functional outcomes. Similar findings were noted in a separate propensity score analysis. CONCLUSION: In this large thrombectomy registry, AF patients exposed to IVT before MT had increased hemorrhagic complications without improved functional outcomes, in contrast with non-AF patients. Prospective trials are warranted to assess whether AF patients represent a subgroup of LVO patients who may benefit from a direct to thrombectomy approach at thrombectomy capable centers

Association of Noncontrast Computed Tomography and Perfusion Modalities With Outcomes in Patients Undergoing Late-Window Stroke Thrombectomy

Importance: There is substantial controversy with regards to the adequacy and use of noncontrast head computed tomography (NCCT) for late-window acute ischemic stroke in selecting candidates for mechanical thrombectomy. Objective: To assess clinical outcomes of patients with acute ischemic stroke presenting in the late window who underwent mechanical thrombectomy stratified by NCCT admission in comparison with selection by CT perfusion (CTP) and diffusion-weighted imaging (DWI). Design, setting, and participants: In this multicenter retrospective cohort study, prospectively maintained Stroke Thrombectomy and Aneurysm (STAR) database was used by selecting patients within the late window of acute ischemic stroke and emergent large vessel occlusion from 2013 to 2021. Patients were selected by NCCT, CTP, and DWI. Admission Alberta Stroke Program Early CT Score (ASPECTS) as well as confounding variables were adjusted. Follow-up duration was 90 days. Data were analyzed from November 2021 to March 2022. Exposures: Selection by NCCT, CTP, or DWI. Main outcomes and measures: Primary outcome was functional independence (modified Rankin scale 0-2) at 90 days. Results: Among 3356 patients, 733 underwent late-window mechanical thrombectomy. The median (IQR) age was 69 (58-80) years, 392 (53.5%) were female, and 449 (65.1%) were White. A total of 419 were selected with NCCT, 280 with CTP, and 34 with DWI. Mean (IQR) admission ASPECTS were comparable among groups (NCCT, 8 [7-9]; CTP, 8 [7-9]; DWI 8, [7-9]; P = .37). There was no difference in the 90-day rate of functional independence (aOR, 1.00; 95% CI, 0.59-1.71; P = .99) after adjusting for confounders. Symptomatic intracerebral hemorrhage (NCCT, 34 [8.6%]; CTP, 37 [13.5%]; DWI, 3 [9.1%]; P = .12) and mortality (NCCT, 78 [27.4%]; CTP, 38 [21.1%]; DWI, 7 [29.2%]; P = .29) were similar among groups. Conclusions and relevance: In this cohort study, comparable outcomes were observed in patients in the late window irrespective of neuroimaging selection criteria. Admission NCCT scan may triage emergent large vessel occlusion in the late window

Predictive regularity representations in deviance detection and auditory stream segregation: from conceptual to computational models

Predictive accounts of perception have received increasing attention in the past twenty years. Detecting violations of auditory regularities, as reflected by the Mismatch Negativity (MMN) auditory event-related potential, is amongst the phenomena seamlessly fitting this approach. Largely based on the MMN literature, we propose a psychological conceptual framework called the Auditory Event Representation System (AERS), which is based on the assumption that auditory regularity violation detection and the formation of auditory perceptual objects are based on the same predictive regularity representations. Based on this notion, a computational model of auditory stream segregation, called CHAINS, has been developed. In CHAINS, the auditory sensory event representation of each incoming sound is considered for being the continuation of likely combinations of the preceding sounds in the sequence, thus providing alternative interpretations of the auditory input. Detecting repeating patterns allows predicting upcoming sound events, thus providing a test and potential support for the corresponding interpretation. Alternative interpretations continuously compete for perceptual dominance. In this paper, we briefly describe AERS and deduce some general constraints from this conceptual model. We then go on to illustrate how these constraints are computationally specified in CHAINS