• 2015-2024close
• Open Access close
• Closed Access close
• Publications close
• Research data close
• Other research products close
• Natural Sciences and Engineering Re... close
• CA close
• English close
• Neuroinformatics close

OBJECTIVE. To assess whether HS severity is mirrored at the level of large-scale networks. METHODS. We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 TLE patients with histopathological diagnosis of HS (n=25; TLE-HS) and isolated gliosis (n=19; TLE-G), and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm which simulates functional dynamics from structural network data. RESULTS. Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from grey matter atrophy. CONCLUSIONS. Severe HS is associated with marked remodeling of connectome topology and structurally-governed functional dynamics in TLE, as opposed to isolated gliosis which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales. Data_phen_conn_dryadPhenotypic information and mean connectome feature data for Bernhardt et al. (2019) Temporal lobe epilepsy: hippocampal pathology modulates white matter connectome topology and controllability. Neurology

The cholinergic system is one of the most influential and essential signalling systems in the body. In the brain, cholinergic neurons innervate many brain regions where they influence a wide variety of behaviours. However, the precise role of each cholinergic region on distinct types of behaviour is not well known. Furthermore, in recent years there has been evidence that many cholinergic neurons in the brain have a capacity for co-transmission. Yet the functional significance of secreting two classical neurotransmitters from the same neuron is still largely unidentified. In this thesis, we investigated how different cholinergic nuclei modulate behavioural functions. To do that we selectively eliminated acetylcholine (ACh) release from cholinergic neurons of the striatum, brainstem and basal forebrain in mice. We then evaluated cognitive and non-cognitive behaviours using classical behavioural tests as well as sophisticated automated touchscreens tasks. In the striatum cholinergic interneurons are known to co-release ACh and glutamate (Glu), so we focused our investigation on how the individual neurotransmitters modulate striatal-dependent behaviours. We demonstrated that ACh modulates cognitive behaviours such as cognitive flexibility, extinction and cue detection. Glu released from striatal cholinergic interneurons also affects striatal-dependent behaviours but usually in an opposing manner to ACh, so, a balance between ACh and Glu is critical to regulating behaviours. As dopaminergic signalling in the striatum is widely influenced by ACh and Glu released by cholinergic interneurons, we also investigated how dopaminergic signalling changes while animals are performing a striatal-dependent cognitive task. In the brainstem, we showed that ACh influences motor functions and stress but does not have a major impact on cognition. However, stress induced by brainstem ACh-deficiency can interfere with results from cognitive tasks. In the forebrain, we find that ACh signalling is essential for maintaining social memory. Decreased cholinergic signalling in the hippocampus and cortex lead to deficits in social recognition. In conclusion, we demonstrate the complexity that ACh brings into behavioural regulation and how changes in its release can contribute to the pathophysiology of diseases such as Parkinson’s disease and Alzheimer’s disease. Ultimately, this data helps define novel pharmacological mechanisms tailored to improve specific cholinergic-mediated symptoms.

Juveniles of the cooperatively-breeding cichlid fish Neolamprologus pulcher either consistently provide help in form of alloparental egg care ('cleaners') or consistently abstain from helping ('non-cleaners'). These phenotypes are not based on heritable genetic differences. Instead they arise during ontogeny, which should lead to differences in brain structure or physiology, a currently untested prediction. We compared brain gene expression profiles of cleaners and non-cleaners in two experimental conditions, a helping opportunity and a control condition. We aimed to identify (i) expression differences between cleaners and non-cleaners in the control, (ii) changes in gene expression induced by the opportunity, and (iii) differences in plasticity of gene expression between cleaners and non-cleaners. Control cleaners and non-cleaners differed in the expression of a single gene, irx2, which regulates neural differentiation. During the opportunity, cleaners and non-cleaners had three up-regulated genes in common, which were implicated in neuroplasticity, hormonal signalling, and cell proliferation. Thus, the stimulus in the opportunity was sufficiently salient. Cleaners also showed higher expression of seven additional genes that were unique to the opportunity. One of these cleaner-specific genes is implicated in neuropeptide metabolism, indicating that this process is associated with cleaning performance. This suggests that the two types employed different pathways to integrate social information, preparing them for accelerated reaction to future opportunities. Interestingly, three developmental genes were down-regulated between the control and the opportunity in cleaners only. Our results indicate that the two behavioural types responded differently to the helping opportunity, and that only cleaners responded by down-regulating developmental genes. Read count matrix and treatment information on individualsRead count matrix from RNA-seq experiment of two distinct helper types in the cooperatively breeding cichlid fish Neolamprologus pulcher. 48 individuals in a 2x2 full-factorial design of cleaners and non-cleaners in control and opportunity. 38,2425 genes expressed in the telencephalon 45 min after the onset of the cooperation opportunity.data_Kasper_cichlid_helping_transcriptome.xlsx

Entrainment of neural oscillations on multiple time scales is important for the perception of speech. Musical rhythms, and in particular the perception of a regular beat in musical rhythms, is also likely to rely on entrainment of neural oscillations. One recently proposed approach to studying beat perception in the context of neural entrainment and resonance (the “frequency-tagging” approach) has received an enthusiastic response from the scientific community. A specific version of the approach involves comparing frequency-domain representations of acoustic rhythm stimuli to the frequency-domain representations of neural responses to those rhythms (measured by electroencephalography, EEG). The relative amplitudes at specific EEG frequencies are compared to the relative amplitudes at the same stimulus frequencies, and enhancements at beat-related frequencies in the EEG signal are interpreted as reflecting an internal representation of the beat. Here, we show that frequency-domain representations of rhythms are sensitive to the acoustic features of the tones making up the rhythms (tone duration, onset/offset ramp duration); in fact, relative amplitudes at beat-related frequencies can be completely reversed by manipulating tone acoustics. Crucially, we show that changes to these acoustic tone features, and in turn changes to the frequency-domain representations of rhythms, do not affect beat perception. Instead, beat perception depends on the pattern of onsets (i.e., whether a rhythm has a simple or complex metrical structure). Moreover, we show that beat perception can differ for rhythms that have numerically identical frequency-domain representations. Thus, frequency-domain representations of rhythms are dissociable from beat perception. For this reason, we suggest caution in interpreting direct comparisons of rhythms and brain signals in the frequency domain. Instead, we suggest that combining EEG measurements of neural signals with creative behavioral paradigms is of more benefit to our understanding of beat perception. single participant behavioral data files.mat files for single participants. README.txt file in each zipped folder describes columnsdryad_data.zip

Comparative studies have revealed that vasopressin-oxytocin pathways are associated with both pair bonding and grouping behaviour. However, the relationship between pair bonding and grouping behaviourremains unclear.In this study,our aim was to identify whether two species that differ in grouping behaviourdisplay a corresponding difference in their pair bonds, and in the underlying vasopressin-oxytocinhormonal pathways. Using two species of cichlid fishes, the highly social Neolamprologuspulcher and the non-social Telmatochromis temporalis, we measuredproximity of pairs during pair bond formation, and then measured social behaviors (proximity, aggression, submission,affiliation)and brain gene expression of isotocin and arginine vasotocin (the teleost homologues of oxytocin and vasopressin, respectively), as well as their receptors, after a temporary separation and subsequent reunion of the bonded pairs. Pairs of the social species spent more time in close proximity relative to the non-social species. Rates of aggression increased in both species following the separation and reunion treatment, relative to controls that were not separated.Overall, whole brain expression of isotocin was higher in the social species relative to the non-social species, and correlated with proximity, submission, and affiliation, but only in the social species. Our results suggest that both a social and a non-social cichlid species have similar behavioural responses to a temporary separation from a mate, and we found no differencein the brain gene expression of measured hormones and receptors based on our separation-reunion treatment. However, our results highlight the importance of isotocin in mediating submissive and affiliativebehaviourin cichlid fishes, and demonstrate thatisotocinhas species-specific correlations with socially relevantbehaviours. Cichlid pair bonding IT AVT dataRT-qPCR values and behavioral scores

Khoomei is a unique singing style originating from the Central Asian republic of Tuva. Singers produce two pitches simultaneously: a booming low-frequency rumble alongside a hovering high-pitched whistle-like tone. The biomechanics of this biphonation are not well-understood. Here, we use sound analysis, dynamic magnetic resonance imaging, and vocal tract modeling to demonstrate how biphonation is achieved by modulating vocal tract morphology. Tuvan singers show remarkable control in shaping their vocal tract to narrowly focus the harmonics (or overtones) emanating from their vocal cords. The biphonic sound is a combination of the fundamental pitch and a focused filter state, which is at the higher pitch (1-2 kHz) and formed by merging two formants, thereby greatly enhancing sound-production in a very narrow frequency range. Most importantly, we demonstrate that this biphonation is a phenomenon arising from linear filtering rather than a nonlinear source. Data is placed in four zipped files (compression done via Mac OS 10.12.4). The four files each contain a particular subset of the data: 1. Model.zip - Modeling software (Tube Talker) and several illustrative simulations 2. CroppedMRI_CB.zip - Both statis and dynamic MRI images (as .dcm files). Note that the DICOM files have been cropped (so to only show the relevant anatomical features) and metadata have been stripped. 3. SoundboothRecordings.zip - All soundbooth recordings, saved as .wav files (SR 96 kHz) 4. STL.zip - Reonstruction of the 3-D airspace, saved as a .stl file 5. MRIaudio.zip - Audio files collected during the MRI runs 6. MRImoviesC.zip - Movies of the dynamic data (with audio). Data is a combination of acoustical recordings, MRI data, and vocal tract modeling. Movie of the dynamic MRI data are also included. All details are included in the manuscript "Overtone focusing in biphonic Tuvan throat singing".

Dynamic processes, such as intracellular calcium signaling, are hallmark of cellular biology. As real-time imaging modalities become widespread, a need for analytical tools to reliably characterize time-series data without prior knowledge of the nature of the recordings becomes more pressing. The goal of this study is to develop a signal-processing algorithm for MATLAB that autonomously computes the parameters characterizing prominent single transient responses (TR) and/or multi-peaks responses (MPR). The algorithm corrects for signal contamination and decomposes experimental recordings into contributions from drift, TRs, and MPRs. It subsequently provides numerical estimates for the following parameters: time of onset after stimulus application, activation time (time for signal to increase from 10 to 90% of peak), and amplitude of response. It also provides characterization of the (i) TRs by quantifying their area under the curve (AUC), response duration (time between 1/2 amplitude on ascent and descent of the transient), and decay constant of the exponential decay region of the deactivation phase of the response, and (ii) MPRs by quantifying the number of peaks, mean peak magnitude, mean periodicity, standard deviation of periodicity, oscillatory persistence (time between first and last discernable peak), and duty cycle (fraction of period during which system is active) for all the peaks in the signal, as well as coherent oscillations (i.e., deterministic spikes). We demonstrate that the signal detection performance of this algorithm is in agreement with user-mediated detection and that parameter estimates obtained manually and algorithmically are correlated. We then apply this algorithm to study how metabolic acidosis affects purinergic (P2) receptor-mediated calcium signaling in osteoclast precursor cells. Our results reveal that acidosis significantly attenuates the amplitude and AUC calcium responses at high ATP concentrations. Collectively, our data validated this algorithm as a general framework for comprehensively analyzing dynamic time-series.

1) Sample registration data. Stitch2p is a function that registeres 2p and 1p images of retina. INPUT: PATH: is the string path where the recordings are saved. RANGE is a 1x2 matrix that defines the range of movies to include in the analysis this works because each recording is assigned a number matching their order(movie_n). eg: calling [0 3] will analyze movie_0 to movie_3 in the specified path. CENTER is a path containing the blood vessel pattern acquired during the recording session. OUTPUT: ROIS = struct with all the 2p recording movies and bloodvessels used in the stiching STITCHED: Array with raw stitched image TESTIMAGE: converted 8bit image with color multiplier for visualization to use with provided sample images open matlab and set the path and center variables. For example: path = "C:\Downloads\Remapping process files\sample 2p recordings" center = "C:\Downloads\Remapping process files\sample 2p recordings\movie_10" Stich2p(path,[0 3],center); Should display a stitched image and save it, along with a matfile, to the path defined in 'center' Example images: any folder in the "sample 2p recordings" folder will contain example files of remapped images along with original recording data. Remapped images are based on the image in the "confocal ROIs" folder. File naming definitions: RoiSet: mask containing the cells of interest. bloodvessels: mask containing the bloodvessels for marker intensity calculations stim_x: individual presented stimuli along with relevant information expression_23_06_20_mx: CSV file containing assigned markers remap: the remapped image from which the markers where assigned remap_points: land mark points used to make the Remapped image landmark points are listed as the confocal and 2p image. 2) Visual response data: Matfile (*.mat) containing a single struct called 'compiled'. Struct field definitions: mb: struct containing rawTrace: Response averaged from 2 presentations of a bar moving in 8 different directions. Bar velocity = 1000um/sec. 8-bar sequence was preceded by a brief (.5s) flash. stimTrace: vector showing stimulus timing allignedTrace: Time x bar array with RGC responses corrected for position mbAngleOrder: bar direction vcctor rawTime: time vector for rawTrace allignedTime: time vector for allignedTrace ff: struct containing rawTrace: response averaged from 3 presentations of a full field flash. rawtime: time vector for rawTrace stimTrace: vector showing stimulus timing mbs: struct ordered the same way as mb. Contains data averaged from 2 presentations of a bar moving in 8 different directions. Bar velocity = 200um/sec. 8-bar sequence was preceded by a brief (.5s) flash. ROI: struct containing: mask - binary mask that defines RGC. xy: Roi centroid position. ost, Brn3c, nr2, calb, gfp: 8bit intensity of the indicated marker within RGC ROI defined by mask. size: Roi area. mrk: Marker classification. theta: angular preference computed from moving bar stimulus and set relative to retinal orientation. dsi: direction selective index computed from moving bar stimulus. osi: orientation selective index computed from moving bar stimulus. Nearly 50 different mouse retinal ganglion cell (RGC) types sample the visual scene for distinct features. RGC feature selectivity arises from its synapses with a specific subset of amacrine (AC) and bipolar cell (BC) types, but how RGC dendrites arborize and collect input from these specific subsets remains poorly understood. Here we examine the hypothesis that RGCs employ molecular recognition systems to meet this challenge. By combining calcium imaging and type-specific histological stains we define a family of circuits that express the recognition molecule Sidekick 1 (Sdk1) which include a novel RGC type (S1-RGC) that responds to local edges. Genetic and physiological studies revealed that Sdk1 loss selectively disrupts S1-RGC visual responses which result from a loss of excitatory and inhibitory inputs and selective dendritic deficits on this neuron. We conclude that Sdk1 shapes dendrite growth and wiring to help S1-RGCs become feature selective. Two Datasets are provided. 1) Sample registration data - contains images, code, and ROIs to register two-photon imaged fields of retinae containing GCaMP6f+ RGCs with the same retinae following staining with antibodies to marker genes for Sdk1 RGC types. 2) Visual response data - contains responses of Sdk1 RGCs to a full-field flash and moving bar, grouped according to expression of Ost, Brn3c, Nr2f2, and Calbindin.

For foveated animals, visual tracking of moving stimuli requires the synergy between saccades and smooth pursuit eye movements. Deciding to trigger a catch-up saccade during pursuit influences the quality of visual input. This decision is a trade-off between tolerating sustained position error when no saccade is triggered or a transient loss of vision during the saccade due to saccadic suppression. Although catch-up saccades have been extensively investigated, it remains unclear how the trigger decision is made by the brain. de Brouwer et al (2002) demonstrated that catch-up saccades were less likely to occur when the expected time to foveate a target using pursuit alone is between 40 and 180ms into the future, referred to as the smooth zone. However, this descriptive result lacks a mechanistic explanation for how the trigger decision is made. More recently, we proposed a decision model (Coutinho et al., 2018) that relies on a probabilistic estimation of predicted position error (PEpred) during visual tracking. To test the model predictions, we investigated how human participants combined predicted position error, retinal slip, and the uncertainty in those estimates to make trigger decisions. We found a significant effect of the pre-saccadic magnitude of PEpred on trigger time and occurrence of catch-up saccades. To test the role of uncertainty, we blurred the moving target which led to longer and more variable saccade trigger times and more smooth pursuit trials, consistent with model predictions. As predicted by our model, large PEpred (>10deg) produced early saccades regardless of the level of uncertainty while saccades preceded by small PEpred (<10deg) were significantly modulated by high uncertainty. Our model also predicted increased signal dependent noise as retinal slip increases, which resulted in longer saccade trigger times and more smooth trials. In conclusion, the data supports our hypothesized role of PEpred in deciding when to trigger a catch-up saccade during smooth pursuit while taking into account uncertainty in sensory estimates. RawRaw double-step ramp eye-tracking data of 15 subjects from EyeLink 1000 and Matlab.LabeledS1-S5Labeled data file for subjects 1-5LabeledS7-S11Labeled data for subjects 7-11LabeledS12-S16Labeled data for subjects 12-16Data Collection Log