Biology subjects

von Kriegstein, K.

Publications and source records attributed to von Kriegstein, K..

7 recordsLinked to original sources

bioRxiv2026

Dyslexia is characterized by atypical predictive coding specific to the left subcortical auditory pathway

Developmental dyslexia is a specific, highly prevalent and often debilitating reading and spelling disorder with unknown neurocomputational mechanisms. Here we discovered, in a preregistered functional magnetic resonance imaging study optimized for the subcortical sensory pathway, that dyslexia is characterized by altered predictive coding in left-hemispheric auditory sensory pathway nuclei. The neurocomputational alterations were related to one of the two main dyslexia risk scores, indicating a crucial role for dyslexia pathophysiology.

neuroscience↗

bioRxiv2024

Progressive changes in functional connectivity between thalamic nuclei and cortical networks across learning

The thalamus is connected to cerebral cortex and subcortical regions, serving as a node within cognitive networks. It is a heterogeneous structure formed of functionally distinct nuclei with unique connectivity patterns. However, their contributions to cognitive functioning within networks is poorly understood. Recent animal research suggests that thalamic nuclei such as the mediodorsal nucleus play critical roles in goal-directed behaviour. Our aim was to investigate how functional integration of thalamic nuclei within cortical and subcortical networks changes whilst transitioning from more controlled goal-directed behaviour towards more automatic or habitual behaviour in humans. We analysed functional magnetic resonance imaging (fMRI) data from a stimulus-response learning study to investigate functional connectivity (FC) changes across learning between thalamic nuclei with cortical networks and subcortical structures in healthy subjects. We defined subcortical regions-of-interest (ROIs) individually in native space, segmenting the thalamus into 47 nuclei and segmenting 38 subregions within the basal ganglia and hippocampus. Additionally, we defined 12 cerebral cortex ROIs via maximum-probability network templates. Learning-related connectivity changes were examined via ROI-to-ROI functional network analysis. Our results showed that learning was associated with: 1) decreasing FC between the frontoparietal network and higher order thalamic nuclei; 2) increasing FC between the cingulo-opercular network and pulvinar nuclei, 3) decreasing FC between the default mode network (DMN) and right mediodorsal nuclei; 4) increasing FC between the DMN and left mediodorsal nuclei; 5) altered functional connectivity between thalamic nuclei and putamen subregions, and 6) increasing intrathalamic FC. Together, this suggests that several thalamic nuclei are involved in the learning-related transition from controlled to more automatic behaviour.

neuroscience↗

bioRxiv2022

Dysfunction of the visual sensory thalamus in developmental dyslexia

Developmental dyslexia (DD) is a reading disorder with a prevalence of 5-10%. Neuroscientific research has typically focused on explaining DD symptoms based on pathophysiological changes in the cerebral cortex. However, DD might also be associated with alterations in sensory thalami - central subcortical stations of sensory pathways. A post-mortem study on the visual sensory thalamus (lateral geniculate nucleus, LGN) showed histopathological changes in the magnocellular (M-LGN), but not in the parvocellular (P-LGN), subdivisions. M-LGN and P-LGN have different functional properties and belong to two different visual systems. Whether M-LGN alterations also exist in DD in-vivo is unclear. Also, the potential relevance of M-LGN alterations to DD symptoms is unknown. This lack of knowledge is partly due to considerable technical challenges in investigating LGN subdivisions non-invasively in humans. Here, we employed recent advances in high-field 7 Tesla functional magnetic resonance imaging (fMRI) to map the M- and P-LGN in-vivo in DD adults (n=26) and matched controls (n=28). We show that (i) M-LGN responses differ between DD and control participants, (ii) these differences are more pronounced in male than in female DD participants, and (iii) M-LGN alterations predict a core symptom of DD in male DD participants only, i.e., rapid naming ability. Our results provide a first functional interpretation of M-LGN changes in DD and support DD theories that propose a direct relevance of sensory thalamus alterations for DD symptoms. In addition, the sex-specific behavioral relevance of M-LGN alterations within DD calls for taking sex differences into account when planning brain-based therapeutic interventions. Significance StatementDevelopmental dyslexia (DD) is one of the most common learning disorders affecting millions of children and adults world-wide. Several decades ago, pioneering research in five DD post-mortem brains suggested that DD is characterized not only by alterations of the cerebral cortex, but also by changes in a subsection of the visual sensory thalamus - the so-called M-LGN. The relevance of these findings for DD remained highly controversial. Using recent developments in high-resolution functional neuroimaging, we now discovered that M-LGN alterations are present also in DD in-vivo and predict a core symptom of DD in males. Our results provide a first functional interpretation of M-LGN alterations in DD and provide a basis for better understanding sex-specific differences in DD.

neuroscience↗

bioRxiv2020

Mapping the Human Visual Thalamus and its Cytoarchitectonic Subdivisions Using Quantitative MRI

The human lateral geniculate nucleus (LGN) of the visual thalamus is a key subcortical processing site for visual information analysis. A non-invasive assessment of the LGN and its functionally and microstructurally distinct magnocellular (M) and parvocellular (P) subdivisions in-vivo in humans is challenging, because of its small size and location deep inside the brain. Here we tested whether recent advances in high-field structural quantitative MRI (qMRI) can enable MR-based mapping of human LGN subdivisions. We employed ultra-high resolution 7 Tesla qMRI of a post-mortem human LGN specimen and high-resolution 7 Tesla in-vivo qMRI in a large participant sample. We found that a quantitative assessment of the LGN and a differentiation of its subdivisions was possible based on microstructure-informed MR-contrast alone. In both the post-mortem and in-vivo qMRI data, we identified two components of shorter and longer longitudinal relaxation time (T1) within the LGN that coincided with the known anatomical locations of a dorsal P and a ventral M subdivision, respectively. Through a subsequent ground truth histological examination of the same post-mortem LGN specimen, we showed that the observed T1 contrast pertains to cyto- and myeloarchitectonic differences between LGN subdivisions. These differences were based on cell and myelin density, but not on iron content. Our qMRI-based mapping strategy overcomes shortcomings of previous fMRI-based mapping approaches. It paves the way for an in-depth understanding of the function and microstructure of the LGN in humans. It also enables investigations into the selective contributions of LGN subdivisions to human behavior in health and disease. Significance StatementThe lateral geniculate nucleus (LGN) is a key processing site for the analysis of visual information. Due to its small size and deep location within the brain, non-invasive mapping of the LGN and its microstructurally distinct subdivisions in humans is challenging. Using quantitative MRI methods that are sensitive to underlying microstructural tissue features, we show that a differentiation of the LGN and its microstructurally distinct subdivisions is feasible in humans non-invasively. These findings are important because they open up novel opportunities to assess the hitherto poorly understood complex role of the LGN in human perception and cognition, as well as the contribution of selective LGN subdivision impairments to various clinical conditions including developmental dyslexia, glaucoma and multiple sclerosis.

neuroscience↗

bioRxiv2019

The role of the ventral MGB in speech in noise comprehension

Recognising speech in background noise is a strenuous daily activity, yet most humans can master it. A mechanistic explanation of how the human brain deals with such sensory uncertainty is the Bayesian Brain Hypothesis. In this view, the brain uses a dynamic generative model to simulate the most likely trajectory of the speech signal. Such simulation account can explain why there is a task-dependent modulation of sensory pathway structures (i.e., the sensory thalami) for recognition tasks that require tracking of fast-varying stimulus properties (i.e., speech) in contrast to relatively constant stimulus properties (e.g., speaker identity) despite the same stimulus input. Here we test the specific hypothesis that this task-dependent modulation for speech recognition increases in parallel with the sensory uncertainty in the speech signal. In accordance with this hypothesis, we show--by using ultra-high-resolution functional magnetic resonance imaging in human participants--that the task-dependent modulation of the left primary sensory thalamus (ventral medial geniculate body, vMGB) for speech is particularly strong when recognizing speech in noisy listening conditions in contrast to situations where the speech signal is clear. Exploratory analyses showed that this finding was specific to the left vMGB; it was not present in the midbrain structure of the auditory pathway (left inferior colliculus, IC). The results imply that speech in noise recognition is supported by modifications at the level of the subcortical sensory pathway providing driving input to the auditory cortex.

neuroscience↗

bioRxiv2019

Modulation of tonotopic ventral MGB is behaviorally relevant for speech recognition.

Recognising speech in background noise is a strenuous daily activity, yet most humans can master it. An explanation of how the human brain deals with such sensory uncertainty during speech recognition is to-date missing. Previous work has shown that recognition of speech without background noise involves modulation of the auditory thalamus (medial geniculate body, MGB): There are higher responses in left MGB for speech recognition tasks that require tracking of fast-varying stimulus properties in contrast to relatively constant stimulus properties (e.g., speaker identity tasks) despite the same stimulus input. Here we tested the hypotheses that (i) this task-dependent modulation for speech recognition increases in parallel with the sensory uncertainty in the speech signal, i.e., the amount of background noise and that (ii) this increase is present in the ventral MGB, which corresponds to the primary sensory part of the auditory thalamus. In accordance with our hypothesis, we show--by using ultra-high-resolution functional magnetic resonance imaging in human participants--that the task-dependent modulation of the left vMGB for speech is particularly strong when recognizing speech in noisy listening conditions in contrast to situations where the speech signal is clear. Exploratory analyses showed that this finding was specific to the left vMGB; it was not present in the right vMGB or the midbrain structure of the auditory pathway (left inferior colliculus, IC). The results imply that speech in noise recognition is supported by modifications at the level of the subcortical sensory pathway providing driving input to the auditory cortex. Significance StatementSpeech recognition in noisy environments is a challenging everyday task. One reason why humans can master this task is the recruitment of additional cognitive resources as reflected in recruitment of non-language cerebral cortex areas. Here, we show that also modulation in the primary sensory pathway is specifically involved in speech in noise recognition. We found that the left primary sensory thalamus (ventral medial geniculate body, vMGB) is more involved when recognizing speech signals as opposed to a control task (speaker identity recognition) when heard in background noise vs. when the noise was absent. This finding implies that the brain optimises sensory processing in subcortical sensory pathway structures in a task-specific manner to deal with speech recognition in noisy environments.

neuroscience↗

bioRxiv2018

Human primary motor cortex represents evidence for a perceptual decision before motor response

In perceptual decision making the brain extracts and accumulates decision evidence from a stimulus over time and eventually makes a decision based on the accumulated evidence. Several characteristics of this process have been observed in human electrophysiological experiments, especially an average build-up of motor-related signals supposedly reflecting accumulated evidence, when averaged across trials. A more direct approach to investigate the representation of decision evidence in brain signals is to correlate the trial-to-trial fluctuations of a model-based prediction of evidence with the measured signals. We here report results for an experiment in which we applied this approach to human magnetoencephalographic recordings. These results consolidate a range of previous findings and suggest that decision evidence is processed in three consecutive phases in the human brain: In an early phase around 120 ms after the evidence became visible on the screen, in a transition phase around 180 ms and a plateau phase roughly from 300 to 500 ms. We located sources of evidence representations in these phases in early visual (early), parietal (transition) and motor (plateau) regions of the brain while signals in posterior cingulate cortex represented decision evidence in all three phases. These findings imply that parietal cortex is only transiently involved in the processing of decision evidence, that motor areas represent accumulated evidence throughout decision making and that posterior cingulate cortex may have a central role in processing and maintaining decision evidence.

neuroscience↗