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637 results for “Monkey”
Two-probe macaque monkey auditory LFP
<p>Dataset accompanying paper Klein, N., Siegle, J.H., Teichert, T., Kass, R.E. (2021) "Cross-population coupling of neural activity based on Gaussian process current source densities". </p> <p>Auditory local field potential (LFP) recordings and evoked multi-unit activity (MUA) from two 24-electrode linear probes (V-Probes from Plexon) inserted in primary auditory cortex of a macaque monkey. The probes were arranged parallel to the iso-frequency bands in primary auditory cortex (A1), and had similar tonal response fields with preferred frequencies close to 1000 Hz. The first probe (which we call the lateral probe) was located centrally in A1, while the second probe (which we call the medial probe) was located more medially and closer to the boundary of A1 with the medio-lateral belt. The medial probe had lower response threshold, shorter MUA latencies, and overall stronger current sinks and sources than the lateral probe. The spacing between electrodes on each probe was 100 microns so that the probe spanned 2,300 microns. The treatment of the animals was in accordance with the guidelines set by the U.S. Department of Health and Human Services (NIH) for the care and use of laboratory animals, and all methods were approved by the Institutional Animal Care and Use Committee at the University of Pittsburgh.</p> <p>See README.txt for precise description of data files.</p>
Small-angle X-ray scattering datasets for imaging crossing fibers in mouse, pig, monkey, and human brain
<p>Small-angle X-ray scattering datasets for resolving crossing fibers (myelinated neuronal axon bundles), as described in</p> <p>"<strong><em>Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering</em></strong>"</p> <p>deposited in bioRxiv:</p> <p>https://doi.org/10.1101/2022.09.30.510198</p>
Reproductive hormones mediate changes in the gut microbiome during pregnancy and lactation in Phayre's leaf monkeys
Studies in multiple host species have shown that gut microbial diversity and composition change during pregnancy and lactation. However, the specific mechanisms underlying these shifts are not well understood. Here, we use longitudinal data from wild Phayre's leaf monkeys to test the hypothesis that fluctuations in reproductive hormone concentrations contribute to gut microbial shifts during pregnancy. We described the microbial taxonomic composition of 91 fecal samples from 15 females (n=16 cycling, n=36 pregnant, n=39 lactating) using 16S rRNA gene amplicon sequencing and assessed whether the resulting data were better explained by overall reproductive stage or by fecal estrogen (fE) and progesterone (fP) concentrations. Our results indicate that while overall reproductive stage affected gut microbiome composition, the observed patterns were driven by reproductive hormones. Females had lower gut microbial diversity during pregnancy and fP concentration was negatively correlated with diversity. Additionally, fP concentration predicted both unweighted and weighted UniFrac distances, while reproductive state only predicted unweighted UniFrac distances. Seasonality (rainfall and periods of phytoprogestin consumption) additionally influenced gut microbial diversity and composition. Our results indicate that reproductive hormones, specifically progestagens, contribute to the shifts in the gut microbiome during pregnancy and lactation.
Data for investigation of Ugandan red colobus monkey response to Hepatocystis parasites
<p>Supplemental data for analysis of gene expression response of Ugandan red colobus monkeys (<em>Piliocolobus tephrosceles</em>) to <em>Hepatocystis</em>, a malaria-like parasite.</p>
Seasonal Effects in Gastrointestinal Parasite Prevalence, Richness and Intensity in Vervet Monkeys Living in a Semi-Arid Environment
<p>Data and R Notebook for Seasonal Effects in Gastrointestinal Parasite Prevalence, Richness and Intensity in Vervet Monkeys Living in a Semi-Arid Environment</p>
Data from: Creating small food-habituated groups might alter genetic diversity in the endangered Yunnan snub-nosed monkey. https://doi.org/10.1016/j.gecco.2020.e01422
<p>Ecotourism is increasing worldwide for financial, educational and social purposes. Organized viewing of wildlife, especially at feeding sites where wildlife is “ready-to-view”, increases the opportunities for tourists to observe animals in the wild. However, feeding sites might retain only a subsample of wild populations. We thus hypothesized that such human intervention could induce population subdivisions and alter random mating by artificially creating small groups. The endangered Yunnan snub-nosed monkey (Rhinopithecus bieti) is an emblematic example reflecting the contradictions between conservation and ecotourism. In Gehuaqing/Xiangguqing (Yunnan, China), some individuals are maintained at feeding sites, while the rest of the monkey subpopulation wanders in a large surrounding area. Using faecal sampling and molecular analyses, we showed that this subpopulation is genetically structured into two moderately differentiated subgroups. The fed subgroup exhibited lower genetic diversity and higher relatedness than the rest of the subpopulation. Simulation model results indicated that a single translocation probably would not restore genetic diversity in fed individuals. Thus, feeding sites implementation and associated management practices might rapidly induce founder effects. We discuss the possibilities of conciliating ecotourism and the conservation of endangered animal species from this viewpoint.</p>
Data from Churan et al. Action-dependent processing of self-motion in parietal cortex of macaque monkeys
<p><strong>Animals</strong></p> <p>Two adult male monkeys (macaca mulatta) participated in the study. Single-unit recordings were done using standard tungsten microelectrodes (FHC, Bowdoin, USA) with an impedance of ~2 MΩ at 1 kHz that were positioned by an hydraulic micromanipulator (MO-95, Narishige, Tokyo, Japan). A stainless-steel guiding tube was used for transdural penetration and support of the electrode. The neuronal signal was processed using a commercial system (Alpha Omega, Nof HaGalil, Israel). It was band-pass filtered (cut-off frequencies at 500 Hz and 8000 Hz) and sampled at 44 kHz.</p> <p><strong>Apparatus</strong></p> <p>During recordings, the monkeys were sitting head-fixed in a primate chair in a dark room, and their eye-position was monitored at 1000 Hz using a video-based eye tracker (EyeLink 1000, SR Research, Ottawa, Canada). The chair was positioned at a distance of 97 cm from a semi-transparent screen (size 160 cm x 90 cm, subtending the central 79 deg x 50 deg of the visual field) on which the visual stimuli were back-projected using a PROPixx-projector (VPixx Technologies, St-Bruno de Montarville, Canada) running at a resolution of 1920 x 1080 pixels and at a frame rate of 100 Hz. A custom-made touch sensor (length 10 cm, diameter 1 cm) was integrated into the monkey chair in front of the monkey and its status was monitored online at a sampling rate of 1 kHz.</p> <p><strong>Data processing</strong></p> <p>Single units were isolated using a semi-manual spike sorter (Plexon Inc, Dallas, Texas). To this end we used a threshold on the electrode signal that was set manually to separate the action potentials from noise. The samples that exceeded the threshold were further analyzed using principal components as well as other features that were derived from the signal (like local maxima and minima). Then clusters of samples with similar properties were identified visually and each defined as representing a single unit. For a detailed description of the sorting process see the offline User Guide (Plexon, 2020).</p> <p>Further description of the Methods, see: Churan et al. 2021, doi: 10.1152/jn.00049.2021</p> <p><strong>Data:</strong></p> <p>The file '<strong>data_active_passive.mat</strong>' contains following variables:</p> <p>monkey: code for the tested monkey (1=monkey S, 2=monkey O)</p> <p>baseline: Mean and standard deviation of the activity in a time window of 150 ms to 20 ms before the press of the button.</p> <p>reaction: Mean time between the switch of the color of the fixation point from red to green and the time of the button press.</p> <p>anti_p: Significance of a one sided t-test between the baseline activity and activity 200 ms to 0 ms prior to the onset of stimulus motion.</p> <p>p_win (a (1-3),b (1-3),c (1-3),n(1-110)): 4D matrix containing p-values of t-tests</p> <p>a:</p> <p>1: Was preparatory activity significantly higher in the passive relative to the active condition?</p> <p>2: Was preparatory activity significantly lower in the passive relative to the active condition?</p> <p>3: Was the tonic motion response (200 ms to 500 ms after motion onset) significantly different between the active and the passive conditions?</p> <p>b:</p> <p>1: Calculation was made based on all motion directions</p> <p>2: Calculation was made based on the preferred motion direction</p> <p>3: Calculation was made based on the flanking motion directions</p> <p>c:</p> <p>1: Calculation was made based on all presented delays</p> <p>2: Calculation was made based on the shorter set of delays (500 ms to 700 ms)</p> <p>3: Calculation was made based on the longer set of delays (701 ms to 1000 ms)</p> <p>n: number of the investigated neuron</p> <p>psth_alldir: cell array containing the PSTHs (obtained by convolving each spike with a Gaussian as described in the manuscript) in a time window between 1000 ms before and 800 ms after the onset of motion (in 1 ms steps). PSTHs were calculated based on data from all tested directions. Each cell array consists of 4 elements containing different conditions:</p> <p>1: active condition</p> <p>2: passive condition shorter set of delays (500 ms to 700 ms)</p> <p>3: passive condition longer set of delays (701 ms to 1000 ms)</p> <p>4: passive condition all delays</p> <p>psth_bestdir: same as above - using only the preferred direction</p> <p>psth_nbestdir: same as above - using only the flanking directions</p> <p>d_alldir: cell array containing the continuous d-prime (as described in the manuscript) in a time window between 1000 ms before and 800 ms after the onset of motion (in 1 ms steps). d' were calculated based on data from all tested directions. Each cell array consists of 4 elements containing different conditions:</p> <p>1: active condition</p> <p>2: passive condition shorter set of delays (500 ms to 700 ms)</p> <p>3: passive condition longer set of delays (701 ms to 1000 ms)</p> <p>4: passive condition all delays</p> <p>d_bestdir: same as above - using only the preferred direction</p> <p>d_nbestdir: same as above - using only the flanking directions</p> <p>The file '<strong>timecourse_preparatory.mat</strong>' contains the cell array 'd_alldir_preparatory' that consists of 201 elements. Each of the elements contains PSTHs of 23 neurons that have exhibited significant preparatory activity in the passive condition in a time window 1000 ms to 0 ms before the motion onset. Each of the 201 elements describes a specific range of delays between button press and motion onset. This delay range is always a 100 ms wide sliding window, e.g. the element 1 represents delays between 500 and 600 ms, in element 2, the delays are between 501 and 601 ms and so on with the last element (201) representing delays between 700 and 800 ms.</p> <p>Some example code that re-creates most of the figures from the manuscript and that may serve as a starting point for further exploration of the data is available on request from the corresponding author.</p>
Fig. 3 in Proboscis Monkeys (Nasalis Larvatus (Wurmb, 1787)) Have Unusually High-Pitched Vocalizations
Fig. 3. Cumulative curve of mean frequencies of calls in the study. Graph omits the one call that has a frequency <2.7 kHz.
Fig. 2. A in Proboscis Monkeys (Nasalis Larvatus (Wurmb, 1787)) Have Unusually High-Pitched Vocalizations
Fig. 2. A sample spectrogram of a high frequency vocalization of the proboscis monkey, Nasalis larvatus, that shows the harmonic structure of these calls. The fundamental frequency of this call ranges from 3.4–5.4 kHz and the mean frequency is 4.9 kHz.
Figure 2 in Forest monkeys and Pleistocene refugia: a phylogeographic window onto the disjunct distribution of the Chlorocebus lhoesti species group
Figure 2. All possible patterns of relationships among the lhoesti group species. A, topology consistent with a vicariant scenario in which the distribution of a widespread common ancestor fragments into three segments – nearly simultaneously – as the result of habitat deterioration associated with a Pleistocene glacial cycle. B, topology consistent with an alternative vicariant scenario, in which ancestral populations of Chlorocebus preussi and Chlorocebus solatus remain in contact for a short time after the divergence of Chlorocebus lhoesti, because the former two stocks range within the same Pleistocene refuge. C, tree consistent with a dispersal hypothesis in which early C. preussi populations (following divergence from C. solatus) migrate along the northern rim of the Congo Basin, and found a new lineage (C. lhoesti) in the Albertine region (see Fig. 1). D, tree consistent with a dispersal hypothesis in which early C. solatus populations (following divergence from C. preussi) conduct a similar transcontinental migration, but along the southern rim of the Congo Basin (see Fig. 1).
Dataset for monkeys A and B from AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
<p>ECoG data from two monkeys, affi (A) and beignet (B) used in AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. Jingyuan Li, Leo Scholl, Trung Le, Pavithra Rajeswaran, Amy L Orsborn, and Eli Shlizerman. NeurIPS. 2023. https://openreview.net/forum?id=7ntI4kcoqG</p><p>See also https://github.com/shlizee/AMAG</p>
Fig. 5. Trypanoxyuris kotudoi n in Pinworms of the red howler monkey (Alouatta seniculus) in Colombia: Gathering the pieces of the pinworm-primate puzzle
Fig. 5. Trypanoxyuris kotudoi n. sp. (A) Male full body, lateral view. (B) Male cephalic end, apical view. (C) Male posterior end, ventral view; (D) Male posterior end, lateral view, (E) Female full body, lateral view; (F) Female cephalic end, apical view; (G) Female cross section showing lateral alae; (H) Egg.
Fig. 6 in Pinworms of the red howler monkey (Alouatta seniculus) in Colombia: Gathering the pieces of the pinworm-primate puzzle
Fig. 6. SEM of buccal structures of males of Trypanoxyuris species found in howler monkeys (A) Trypanoxyuris seunimii n. sp. (B) T. keumimae n. sp. (C) T. kotudoi n. sp. (D) T. minutus from Alouatta seniculus. (E) T. pigrae. (F) T. minutus from Mesoamerican howler monkeys. R: right ventral lip; L: left ventral lip. White arrow pointing at the sharp protuberances formed as a result of the notches in the lips.
Fig. 4 in Pinworms of the red howler monkey (Alouatta seniculus) in Colombia: Gathering the pieces of the pinworm-primate puzzle
Fig. 4. SEM of buccal structures of females of Trypanoxyuris species found in howler monkeys (A) Trypanoxyuris seunimii n. sp. (B) T. keumimae n. sp. (C) T. kotudoi n. sp. (D) T. minutus from Alouatta seniculus. (E) T. pigrae. (F) T. minutus from Mesoamerican howler monkeys. R: right ventral lip; L: left ventral lip. White arrow pointing at the lateral indentations. Black arrow pointing at the square-shaped edge.
Fig. 3. Trypanoxyuris keumimae n in Pinworms of the red howler monkey (Alouatta seniculus) in Colombia: Gathering the pieces of the pinworm-primate puzzle
Fig. 3. Trypanoxyuris keumimae n. sp. (A) Female full body, lateral view. (B) Female cephalic end, apical view. (C) Male cephalic end, apical view, (D) Male full body, lateral view; (E) Male posterior end, lateral view, (F) Male posterior end, ventral view; (G) Female cross section showing lateral alae (H) Egg.
Fig. 2. Trypanoxyuris seunimii n in Pinworms of the red howler monkey (Alouatta seniculus) in Colombia: Gathering the pieces of the pinworm-primate puzzle
Fig. 2. Trypanoxyuris seunimii n. sp. (A) Female full body, lateral view. (B) Female cephalic end, apical view. (C) Male cephalic end, apical view, (D) Female cross section showing lateral ala; (E) Egg; (F) Male full body, lateral view; (G) Male posterior end, ventral view; (H) Male posterior end, lateral view.
Working memory capacity of crows and monkeys arises from similar neuronal computations
<p>Complex cognition relies on flexible working memory, which is severely limited in its capacity. The neuronal computations underlying these capacity limits have been extensively studied in humans and in monkeys, resulting in competing theoretical models. We probed the working memory capacity of crows (<em>Corvus corone</em>) in a change detection task, developed for monkeys (<em>Macaca mulatta</em>), while we performed extracellular recordings of the prefrontal-like area nidopallium caudolaterale. We found that neuronal encoding and maintenance of information were affected by item load, in a way that is virtually identical to results obtained from monkey prefrontal cortex. Contemporary neurophysiological models of working memory employ divisive normalization as an important mechanism that may result in the capacity limitation. As these models are usually conceptualized and tested in an exclusively mammalian context, it remains unclear if they fully capture a general concept of working memory or if they are restricted to the mammalian neocortex. Here we report that carrion crows and macaque monkeys share divisive normalization as a neuronal computation that is in line with mammalian models. This indicates that computational models of working memory developed in the mammalian cortex can also apply to non-cortical associative brain regions of birds.</p>
FIG. 11. — Sawecolobus lukeinoensis n. gen., n in The Late Miocene colobine monkeys from Aragai (Lukeino Formation, Tugen Hills, Kenya)
FIG. 11. — Sawecolobus lukeinoensis n. gen., n. sp., postcranial bones: A, proximal right metatarsal V, BAR 914'04: A1, plantar view; A2, lateral view; A3, superior view; A4, medial view; A5, distal view; B, right distal humerus OCO102'11: B1, anterior view; B2, posterior view; B3, distal view; C, left distal humerus OCO 336'10: C1, anterior view; C2, posterior view; C3, distal view. Scale bars: 1 cm.
FIG. 3. — The mandible OCO 608 in The Late Miocene colobine monkeys from Aragai (Lukeino Formation, Tugen Hills, Kenya)
FIG. 3. — The mandible OCO 608'10 in hard phosphatic matrix before mechanical preparation. Scale bar: 1 cm.
FIG. 6. — Sawecolobus lukeinoensis n. gen., n in The Late Miocene colobine monkeys from Aragai (Lukeino Formation, Tugen Hills, Kenya)
FIG. 6. — Sawecolobus lukeinoensis n. gen., n. sp.: A, skull BAR 757'00: A1, palatal view; A2, facial view; A3, superior view; A4, posterior view; A5, left lateral view; A6, right lateral view; B, Maxilla BAR 756'00: B1, left lateral view; B2, palatal view; B3, right lateral view. Scale bars: 1 cm.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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