Biology subjects

Tempelmann, C.

Publications and source records attributed to Tempelmann, C..

9 recordsLinked to original sources

bioRxiv2020

Functional dynamics of de-afferented early visual cortex in glaucoma

fMRI studies in macular degeneration (MD) and retinitis pigmentosa (RP) demonstrated that responses in the lesion projection zones (LPZ) of V1 are task related, indicating significant limits of bottom-up visual system plasticity in MD and RP. In advanced glaucoma (GL), a prevalent eye disease and leading cause of blindness, the scope of visual system plasticity is currently unknown. We performed 3T fMRI in patients with extensive visual field defects due to GL (n=5), RP (n=2) and healthy controls (n=7; with simulated defects). Participants viewed contrast patterns drifting in 8 directions alternating with uniform gray and performed 3 tasks: (1) passive viewing (PV), (2) one-back task (OBT) and (3) fixation-dot task (FDT). During PV, they passively viewed the stimulus with central fixation, during OBT they reported the succession of the same two motion directions, and during FDT a change in the fixation color. In GL, LPZ responses of the early visual cortex (V1, V2 and V3) shifted from negative during PV to positive for OBT [p (corrected): V1(0.006); V2(0.04); V3(0.008)], while they were negative in the controls simulated LPZ for all stimulation conditions. For RP a similar pattern as for GL was observed. Consequently, activity in the de-afferented visual cortex in glaucoma is, similar to MD and RP, task-related. In conclusion, the lack of bottom-up plasticity appears to be a general feature of the human visual system. These insights are of importance for the development of treatment and rehabilitation schemes in glaucoma. HighlightsO_LIFunctional dynamics of early visual cortex LPZ depend on task demands in glaucoma C_LIO_LIBrain activity in deprived visual cortex suggests absence of large-scale remapping C_LIO_LILimited scope of bottom-up plasticity is a general feature of human visual system C_LIO_LIVisual system stability and plasticity is of relevance for therapeutic advances C_LI

neuroscience↗

bioRxiv2020

Reinstatement of cortical outcome representations during higher-order learning

Naturalistic learning scenarios are characterized by infrequent experience of external feedback to guide behavior. Higher-order learning mechanisms like second-order conditioning (SOC) may allow stimuli that were never experienced together with reinforcement to acquire motivational value. Despite its explanatory potential for real-world learning, surprisingly little is known about the neural mechanism underlying such associative transfer of value in SOC. Here, we used multivariate cross-session, cross-modality searchlight classification on functional magnetic resonance imaging data obtained from humans during SOC. We show that visual first-order conditioned stimuli (CS) reinstate cortical patterns representing previously paired gustatory outcomes in the lateral orbitofrontal cortex (OFC). During SOC, this OFC region showed increased functional covariation with amygdala, where neural pattern similarity between second-order CS and outcomes increased from early to late stages of SOC. Our data suggest a mechanism by which motivational value is conferred to stimuli that were never paired with reinforcement.

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bioRxiv2019

Decisions bias future choices by modifying hippocampal associative memories

Decision making is guided by memories of option values. However, retrieving items from memory renders them malleable. Here, we show that merely retrieving values from memory and making a choice between options is sufficient both to induce changes to stimulus-reward associations in the hippocampus and to bias future decision making. After allowing participants to make repeated choices between reward-conditioned stimuli, in the absence of any outcome, we observed that participants preferred stimuli they had previously chosen, and neglected previously unchosen stimuli, over otherwise identical-valued options. Using functional brain imaging, we show that decisions induced changes to hippocampal representations of stimulus-outcome associations. These changes were correlated with future decision biases. Our results indicate that choice-induced preference changes are partially driven by choice-induced modification of memory representations and suggest that merely making a choice - even without experiencing any outcomes - induces associative plasticity.

neuroscience↗

bioRxiv2019

Information-based taste maps in insular cortex are shaped by stimulus concentration

Taste processing is an essential ability in all animals signaling potential harm or benefit of ingestive behavior. Although the peripheral taste coding is well understood, current evidence for central taste processing remains contradictory. To address this issue, human participants judged pleasantness and intensity of low and high-concentration tastes (salty, sweet, sour, bitter) in two fMRI-experiments. High-resolution fMRI and multivariate pattern analysis were used to characterize taste-related informational content in human gustatory cortex (GC). Clusters within GC were narrowly tuned to specific tastants consistently across tasks. Importantly, taste concentrations completely altered the spatial layout of putative taste-specific maps with distinct, non-overlapping patterns for each taste category at different concentration levels. Together, our results point at population-level representations in human GC as a complex function of taste category and concentration.

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bioRxiv2019

Increased hippocampal excitability and reduced modulation in relevant neural networks underlying age-related cognitive mapping deficits

Learning the spatial layout of a novel environment is associated with dynamic activity changes in the hippocampus and in medial parietal areas. With advancing age, the ability to learn spatial environments deteriorates substantially but the underlying neural mechanisms are unknown. Here, we report findings from a behavioral and a fMRI experiment where older and younger adults performed a spatial learning task in a photorealistic virtual environment. We modeled individual learning states using a Bayesian state-space model and found that activity in retrosplenial cortex/parieto-occipital sulcus and anterior hippocampus did not change systematically as a function learning in older compared to younger adults across repeated episodes in the environment. Moreover, effective connectivity analyses revealed that the age-related learning deficits are linked to an increase in hippocampal excitability. Together, these results provide important insights into how human aging affects computations in the brains navigation system, highlighting the critical role of the hippocampus.

neuroscience↗

bioRxiv2019

The anterior insula channels prefrontal expectancy signals during affective processing

Expectancy shapes our perception of impending events. Although such an interplay between cognitive and affective processes is often impaired in mental disorders, it is not well understood how top-down expectancy signals modulate future affect. We therefore track the information flow in the brain during cognitive and affective processing segregated in time using task-specific cross-correlations. Participants in two independent fMRI studies (N1 = 37 & N2 = 55) were instructed to imagine a situation with affective content as indicated by a cue, which was then followed by an emotional picture congruent with expectancy. To correct for intrinsic covariance of brain function, we calculate resting-state cross-correlations analogous to the task. First, using factorial modeling of delta cross-correlations (task-rest) of the first study, we find that the magnitude of expectancy signals in the anterior insula cortex (AIC) modulates the BOLD response to emotional pictures in the anterior cingulate and dorsomedial prefrontal cortex in opposite directions. Second, using hierarchical linear modeling of lagged connectivity, we demonstrate that expectancy signals in the AIC indeed foreshadow this opposing pattern in the prefrontal cortex. Third, we replicate the results in the second study using a higher temporal resolution, showing that our task-specific cross-correlation approach robustly uncovers the dynamics of information flow. We conclude that the AIC arbitrates the recruitment of distinct prefrontal networks during cued picture processing according to triggered expectations. Taken together, our study provides new insights into neuronal pathways channeling cognition and affect within well-defined brain networks. Better understanding of such dynamics could lead to new applications tracking aberrant information processing in mental disorders.

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bioRxiv2018

Evidence for allocentric boundary and goal direction information in the human entorhinal cortex and subiculum

In rodents, cells in the medial entorhinal cortex (EC) and subiculum code for the allocentric direction to environment boundaries, which is an important prerequisite for accurate positional coding. Although in humans boundary-related signals have been reported, there is no evidence that they contain allocentric direction information. Furthermore, it has not been possible to separate boundary versus goal direction signals in the EC/subiculum. To address these important questions, participants learned a virtual environment containing four unique boundaries, after which they underwent fMRI scanning where they made judgments about the allocentric direction of a cue object. Using multivariate decoding, we found information regarding allocentric boundary direction in posterior EC and subiculum, whereas in anterior EC and subiculum we could decode allocentric goal direction. These data provide the first evidence of allocentric boundary coding in humans, and are consistent with recent conceptualisations of a division of labour within the EC.

neuroscience↗

bioRxiv2018

Motion and physiological noise effects on amygdala real-time fMRI neurofeedback learning

Real-time fMRI neurofeedback allows to learn control over activity in a localized brain region. However, with fMRI, physiological factors such as the cardiac cycle and respiration interfere with the measurement of brain activation. In conventional fMRI studies this is usually mitigated by inclusion of motion parameters and/or physiological parameters as nuisance regressors at the analysis stage, allowing to correct for and filter out such confounders. In real-time fMRI, however, such an approach is not routinely feasible due to the necessity to process all signals during the runtime of an experiment. The absence of on-line correction can therefore compromise real-time fMRI study outcomes reporting volitional self-regulation capability as BOLD signal changes. This is especially true for BOLD signal changes in subcortical regions situated close to blood vessels or air cavities, such as the amygdala. We therefore aimed to establish the effects of motion, heart rate, heart rate variability, and respiratory volume on learning effects, which means here an increase in BOLD signal change over NF training, in an amygdala neurofeedback experiment. Specifically, we investigate motion parameters from two emotion regulation studies - performed at 3T and 7T scanners - and additionally acquired physiological variance for the latter one. Our results revealed differences in these parameters between groups and especially between regulation and resting periods within each participant. However, strictly considering these parameters as nuisance regressors in data analysis revealed that the learning of volitional self-regulation of the amygdala is not driven by motion and physiological changes. As validation of our real-time findings, we compare them to the gold standard of assessment of motion and physiology from the Human Connectome Project. Based on this, we recommend to carefully report neurofeedback study results including physiological nuisance regression. To our knowledge, this is the first study investigating the effects of motion and physiological noise correction on neurofeedback BOLD effects.

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bioRxiv2018

The effect of acquisition resolution on orientation decoding from V1: comparison of 3T and 7T

Previously published results indicate that the accuracy of decoding visual orientation from 7T fMRI data of V1 peaks at spatial acquisition resolutions that are routinely accessible with more conventional 3T scanners. This study directly compares the decoding performance between a 3T and a 7T dataset that were acquired using the same stimulation paradigm by applying an identical analysis procedure. The results indicate that decoding models built on 3T data are comparatively impaired. Moreover, we found no evidence for a strong coupling of BOLD signal change magnitude or temporal signal to noise ratio (tSNR) with decoding performance. Direct enhancement of tSNR via multiband fMRI acquisition at the same resolution did not translate into improved decoding performance. Additional voxel selection can boost 3T decoding performance to the 7T level only at a 3mm acquisition resolution. In both datasets the BOLD signal available for orientation decoding is spatially broadband, but, consistent with the size of the BOLD point-spread-function, decoding models at 3T utilize spatially coarser image components.

neuroscience↗