Biology subjects

Stockert, A.

Publications and source records attributed to Stockert, A..

3 recordsLinked to original sources

bioRxiv2026

Changes in Neural Dynamics of Brain Activity and Connectivity Independently Predict Post-Stroke Aphasia Recovery

Post-stroke language recovery involves reorganization of left-hemisphere language and bilateral domain-general multiple-demand networks. Neuroimaging predictors of recovery are widely used, yet, they are often grouped into broad predictor families, limiting clinical translation and the identification of specific therapeutic targets. Here, we assess brain region-specific neural predictors of recovery using task-related activity and connectivity within a multivariate, cross-validated predictive framework. Forty-seven patients with aphasia were examined longitudinally in the acute, subacute, and chronic phases after ischemic stroke using a sentence comprehension paradigm during functional neuroimaging, with regions of interest spanning language and multiple-demand networks. Confound-controlled multivariate regularized regression with feature ablation tested whether predictor families explained language recovery beyond lesion, age, and aphasia severity, and identified the most relevant region-specific predictors. Early recovery was independently predicted by acute and subacute activity and connectivity, whereas later improvement was predicted by activity alone. Subacute connectivity from multiple-demand to language regions predicted early recovery, while acute multiple-demand network activity predicted long-term outcomes. Later subacute-to-chronic recovery was instead predicted by subacute and chronic activity in bilateral inferior frontal regions. These findings identify phase-specific functional biomarkers of aphasia recovery beyond traditional clinical measures, highlighting multiple-demand and inferior frontal regions as candidate targets for phase-adapted neurostimulation approaches.

neuroscience↗

bioRxiv2026

Spatial Bias in Lesion Network Mapping Is Connectome-Independent

Lesion network mapping (LNM) is increasingly used to link focal brain lesions to distributed functional networks. Recent work has raised concerns that LNM results may be spatially biased by dominant features of the normative connectome. If this were the case, three testable predictions would follow: (i) a consistent spatial pattern of false positives across LNM studies, (ii) that this pattern can be consistently explained by intrinsic connectome organization, and (iii) that symptom-associated LNM findings preferentially occur in regions with high spatial bias. We tested these predictions across three independent LNM datasets (n = 49/101/200), evaluating each prediction in all cohorts. Spatial bias maps derived from 4,000,000 random permutations under the null hypothesis showed minimal correspondence across cohorts (R2 = 0.4-0.8%), indicating strong cohort specificity. Moreover, dominant connectome features--captured by the first 10 principal components of connectivity profiles from 1,000 atlas regions--did not systematically explain these bias maps. Finally, symptom-associated results showed no enrichment in high-bias regions. Together, these findings provide strong evidence that spatial bias in LNM is not driven by dominant connectome features. With appropriate inferential statistics and rigorous study design, LNM remains a valid approach for mapping symptom-related brain networks.

neuroscience↗

bioRxiv2021

Temporo-cerebellar connectivity underlies timing constraints in audition

The flexible and efficient adaptation to dynamic, rapid changes in the auditory environment likely involves generating and updating of internal models. Such models arguably exploit connections between the neocortex and the cerebellum, supporting proactive adaptation. Here we test the functional mechanisms associated with temporo-cerebellar connectivity, verifying these mechanisms for speech sounds. First, we identify lesion-specific deficits for the encoding of short timescale spectro-temporal non-speech and speech properties in patients with left posterior temporal cortex stroke. Second, using lesion-guided probabilistic tractography in healthy participants, we reveal bidirectional temporo-cerebellar connectivity with cerebellar dentate nuclei and crura I/II. These findings imply that the encoding and modeling of rapidly modulated auditory spectro-temporal properties engage a temporo-cerebellar interface. The data further support the conjecture that proactive adaptation to a dynamic environment via internal models is a generalizable principle. Significance StatementAsymmetric sampling in time, the principle of duration-sensitive hemispheric specialization of the cerebral cortex in the sensory decomposition of sound, is a widely tested hypothesis in auditory neuroscience. This functional organization is mirrored in the cerebellar cortex, implicated in the internal forward-modeling of sensory feedback that arises from motor actions. The potential structural and functional integration of these systems is not well understood. Using a unique combination of causal lesion-symptom mapping in persons with temporal lobe damage and diffusion-weighted magnetic resonance neuroimaging in healthy persons, we identify one key missing link and provide evidence for cross-lateral temporo-cerebellar connectivity using probabilistic white matter fiber tractography. These cerebellar-pontine-temporal cortex connections not only support asymmetric sampling in time but also establish the basis for a generalizable role of cerebellar forward-modeling in sensation beyond the monitoring of sensory feedback in the motor domain.

neuroscience↗