Pectoral sound generation in the blue catfish Ictalurus furcatus

Catfishes produce pectoral stridulatory sounds by “jerk” movements that rub ridges on the dorsal process against the cleithrum. We recorded sound synchronized with high-speed video to investigate the hypothesis that blue catfish Ictalurus furcatus produce sounds by a slip–stick mechanism, previously described only in invertebrates. Blue catfish produce a variably paced series of sound pulses during abduction sweeps (pulsers) although some individuals (sliders) form longer duration sound units (slides) interspersed with pulses. Typical pulser sounds are evoked by short 1–2 ms movements with a rotation of 2°–3°. Jerks excite sounds that increase in amplitude after motion stops, suggesting constructive interference, which decays before the next jerk. Longer contact of the ridges produces a more steady-state sound in slides. Pulse pattern during stridulation is determined by pauses without movement: the spine moves during about 14 % of the abduction sweep in pulsers (~45 % in sliders) although movement appears continuous to the human eye. Spine rotation parameters do not predict pulse amplitude, but amplitude correlates with pause duration suggesting that force between the dorsal process and cleithrum increases with longer pauses. Sound production, stimulated by a series of rapid movements that set the pectoral girdle into resonance, is caused by a slip–stick mechanism

Variation in sound production of the blue catfish, Ictalurus furcatus.

The blue catfish, Ictalurus furcatus, is an invasive species introduced to Virginia in 1974 and is the largest catfish in the United States. Like other Ictalurids, they are capable of producing disturbance calls via stridulation of the pectoral spine. These sounds can be made in air and water, and catfish can be preyed upon by both aerial and underwater predators. I characterized these putative distress calls by recording them in air and in the fish’s natural habitat. Sounds exhibited a wide variation in acoustic parameters relative to fish ontogeny: larger fish produced higher amplitude sounds with lower frequency bands. Sweep and pulse duration increased with fish size, but pulse rate and the number of pulses per sweep decreased. Sounds were more robust in water with a 1400 fold increase in sound pressure compared to air. Frequency response was much more peaked underwater with a considerable amount of high frequency absorption. These sounds appear to be better adapted to water, suggesting that their use in air may be inconsequential

Distribution and Activation of Catecholaminergic Neurons in the Brain of Male Plainfin Midshipman Fish: Divergence in Behavior and Reproductive Phenotype

The plainfin midshipman fish, Porichthys notatus, provides an excellent opportunity for delimiting the influence of neurochemical content on vertebrate vocal behavior, in part because the production and recognition of social-acoustic signals is vital to their reproductive behavior. There are two distinct reproductive male morphs that follow divergent developmental trajectories with corresponding alternative reproductive tactics: type I males are the territorial/nesting morph that vocally court females during the summer breeding season while type II males do not court females, but instead sneak spawn in competition with type I males. Catecholaminergic neurons, which synthesize and release the neurotransmitters dopamine or noradrenaline, are well-established modulators of various motivated vertebrate sociosexual behaviors, including intraspecific vocal communication. Tyrosine hydroxylase (TH) is the rate-limiting enzyme in catecholamine synthesis, and TH immunoreactivity (-ir) can be utilized to demarcate neurons in the brain that produce and release dopamine and noradrenaline. Key components of the sexually polymorphic neural circuitry essential to midshipman vocal-acoustic behavior express robust TH-ir innervation, overlap with the social behavior network, and are conserved (in part) across vertebrate taxa. The primary goal of this work was to determine if differential distribution and activation of catecholamines in the brain serve as a substrate for variation in alternative reproductive tactics and vocal behavior between type I and type II male midshipman. Firstly, an intrasexual morphometric comparison of TH-ir neuron number and fiber density revealed that type II males had a greater TH-ir innervation within and in close proximity to the hindbrain vocal pattern generator. Secondly, using the immediate early gene protein cFos as a proxy for neural activation, it was found that two forebrain dopaminergic nuclei were more active in type II males that were exposed to playbacks of conspecific hums compared to ambient noise. Thirdly, cFos-ir induction within diencephalic dopaminergic neurons and brainstem noradrenergic neurons shared positive relationships with the total amount of time type I males spent humming. Furthermore, it was found that exposure to acoustic stimuli with different valences (hums, grunts, or ambient noise) as well as divergent states of calling behavior (humming versus non-humming) evoked contrastive shifts in functional connectivity among TH-ir and social behavior network nuclei. Taken together, this work provides cogent evidence that the differential distribution and activation of catecholaminergic neurons may contribute to both processing of social-acoustic signals and divergent intrasexual behavior expressed as alternative reproductive tactics in midshipman fish

Catecholaminergic Innervation of Central and Peripheral Auditory Circuitry Varies with Reproductive State in Female Midshipman Fish, Porichthys notatus

In seasonal breeding vertebrates, hormone regulation of catecholamines, which include dopamine and noradrenaline, may function, in part, to modulate behavioral responses to conspecific vocalizations. However, natural seasonal changes in catecholamine innervation of auditory nuclei is largely unexplored, especially in the peripheral auditory system, where encoding of social acoustic stimuli is initiated. The plainfin midshipman fish, Porichthys notatus, has proven to be an excellent model to explore mechanisms underlying seasonal peripheral auditory plasticity related to reproductive social behavior. Recently, we demonstrated robust catecholaminergic (CA) innervation throughout the auditory system in midshipman. Most notably, dopaminergic neurons in the diencephalon have widespread projections to auditory circuitry including direct innervation of the saccule, the main endorgan of hearing, and the cholinergic octavolateralis efferent nucleus (OE) which also projects to the inner ear. Here, we tested the hypothesis that gravid, reproductive summer females show differential CA innervation of the auditory system compared to non-reproductive winter females. We utilized quantitative immunofluorescence to measure tyrosine hydroxylase immunoreactive (TH-ir) fiber density throughout central auditory nuclei and the sensory epithelium of the saccule. Reproductive females exhibited greater density of TH-ir innervation in two forebrain areas including the auditory thalamus and greater density of TH-ir on somata and dendrites of the OE. In contrast, non-reproductive females had greater numbers of TH-ir terminals in the saccule and greater TH-ir fiber density in a region of the auditory hindbrain as well as greater numbers of TH-ir neurons in the preoptic area. These data provide evidence that catecholamines may function, in part, to seasonally modulate the sensitivity of the inner ear and, in turn, the appropriate behavioral response to reproductive acoustic signals

Plex: Towards Reliability using Pretrained Large Model Extensions

A recent trend in artificial intelligence is the use of pretrained models for language and vision tasks, which have achieved extraordinary performance but also puzzling failures. Probing these models' abilities in diverse ways is therefore critical to the field. In this paper, we explore the reliability of models, where we define a reliable model as one that not only achieves strong predictive performance but also performs well consistently over many decision-making tasks involving uncertainty (e.g., selective prediction, open set recognition), robust generalization (e.g., accuracy and proper scoring rules such as log-likelihood on in- and out-of-distribution datasets), and adaptation (e.g., active learning, few-shot uncertainty). We devise 10 types of tasks over 40 datasets in order to evaluate different aspects of reliability on both vision and language domains. To improve reliability, we developed ViT-Plex and T5-Plex, pretrained large model extensions for vision and language modalities, respectively. Plex greatly improves the state-of-the-art across reliability tasks, and simplifies the traditional protocol as it improves the out-of-the-box performance and does not require designing scores or tuning the model for each task. We demonstrate scaling effects over model sizes up to 1B parameters and pretraining dataset sizes up to 4B examples. We also demonstrate Plex's capabilities on challenging tasks including zero-shot open set recognition, active learning, and uncertainty in conversational language understanding.Comment: Code available at https://goo.gle/plex-cod

Pre-training helps Bayesian optimization too

Bayesian optimization (BO) has become a popular strategy for global optimization of many expensive real-world functions. Contrary to a common belief that BO is suited to optimizing black-box functions, it actually requires domain knowledge on characteristics of those functions to deploy BO successfully. Such domain knowledge often manifests in Gaussian process priors that specify initial beliefs on functions. However, even with expert knowledge, it is not an easy task to select a prior. This is especially true for hyperparameter tuning problems on complex machine learning models, where landscapes of tuning objectives are often difficult to comprehend. We seek an alternative practice for setting these functional priors. In particular, we consider the scenario where we have data from similar functions that allow us to pre-train a tighter distribution a priori. To verify our approach in realistic model training setups, we collected a large multi-task hyperparameter tuning dataset by training tens of thousands of configurations of near-state-of-the-art models on popular image and text datasets, as well as a protein sequence dataset. Our results show that on average, our method is able to locate good hyperparameters at least 3 times more efficiently than the best competing methods.Comment: ICML2022 Workshop on Adaptive Experimental Design and Active Learning in the Real World. arXiv admin note: substantial text overlap with arXiv:2109.0821

Pre-trained Gaussian processes for Bayesian optimization

Bayesian optimization (BO) has become a popular strategy for global optimization of many expensive real-world functions. Contrary to a common belief that BO is suited to optimizing black-box functions, it actually requires domain knowledge on characteristics of those functions to deploy BO successfully. Such domain knowledge often manifests in Gaussian process priors that specify initial beliefs on functions. However, even with expert knowledge, it is not an easy task to select a prior. This is especially true for hyperparameter tuning problems on complex machine learning models, where landscapes of tuning objectives are often difficult to comprehend. We seek an alternative practice for setting these functional priors. In particular, we consider the scenario where we have data from similar functions that allow us to pre-train a tighter distribution a priori. Theoretically, we show a bounded regret of BO with pre-trained priors. To verify our approach in realistic model training setups, we collected a large multi-task hyperparameter tuning dataset by training tens of thousands of configurations of near-state-of-the-art models on popular image and text datasets, as well as a protein sequence dataset. Our results show that on average, our method is able to locate good hyperparameters at least 3 times more efficiently than the best competing methods

Seasonal difference in TH-ir innervation of the cholinergic octavolateralis efferent nucleus (OE).

<p>(A, B) Transverse sections through the rostral OE showing TH-ir fibers and terminals on somata and dendrites (d) of OE neurons labeled by choline acetyltransferase (ChAT)-ir. Data in C and D are expressed as the percent area of ChAT-ir in the OE that is covered by TH-ir fibers (mean ± SE). Mean percent area TH-ir overlap of OE somata and dendrites for animal in A = 22.4% and 33.4%; B = 17% and 29.7%, respectively. *<i>p</i> = 0.01, *** <i>p</i> = 0.0001. Abbreviations: MLF, medial longitudinal fasciculus; VIIm, facial motor nucleus. Scale bar = 100 μm.</p

Seasonal differences in TH-ir area but not cell number in the dopaminergic periventricular posterior tuberculum (TPp).

<p>(A, B) Large, pear-shaped TH-ir neurons and thick processes are seen just dorsal and lateral to the paraventricular organ (PVO) and medial to the medial forebrain bundle (MFB) along the midline in transverse section through the diencephalon. Data in C are expressed as number of TH-ir neurons per section (mean ± SE). (D) TH-ir area including cells and processes are quantified per unit area (143,139 μm²). Mean TH-ir area for animal in A = 6205.1μm²; B = 2658.4 μm². **<i>p</i> = 0.001. Scale bar = 100 μm.</p