Eduardo Mercado

MEMORY FOR RECENT ACTIONS IN THE BOTTLENOSED DOLPHIN (TURSIOPS TRUNCATUS) : REPETITION OF ARBITRARY BEHAVIORS USING AN ABSTRACT RULE

Little is known about how animals represent their own actions in working memory. We investigated whether bottlenosed dolphins could recall actions they had recently performed and reveal those recollections using an abstract rule. Two dolphins were trained to respond to a specific gestural command by repeating the last behavior performed. Both dolphins proved to be able to repeat a wide variety of behaviors on command and were able to generalize the repeating rule to novel behaviors and situations. One dolphin was able to repeat all 36 behaviors she was tested on, including behaviors involving multiple simultaneous actions and self-selected behaviors. These results suggest that dolphins can flexibly access memories of their recent actions and that these memories are of sufficient detail to allow for reenactments. The repeating task can potentially be used to investigate short-term action and event representations in a variety of species.

Acoustic sequences in non-human animals: a tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well‐known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near‐future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial‐style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

Neural and Cognitive Plasticity: From Maps to Minds.

Some species and individuals are able to learn cognitive skills more flexibly than others. Learning experiences and cortical function are known to contribute to such differences, but the specific factors that determine an organisms intellectual capacities remain unclear. Here, an integrative framework is presented suggesting that variability in cognitive plasticity reflects neural constraints on the precision and extent of an organisms stimulus representations. Specifically, it is hypothesized that cognitive plasticity depends on the number and diversity of cortical modules that an organism has available as well as the brains capacity to flexibly reconfigure and customize networks of these modules. The author relates this framework to past proposals on the neural mechanisms of intelligence, including (a) the relationship between brain size and intellectual capacity; (b) the role of prefrontal cortex in cognitive control and the maintenance of stimulus representations; and (c) the impact of neural plasticity and efficiency on the acquisition and performance of cognitive skills. The proposed framework provides a unified account of variability in cognitive plasticity as a function of species, age, and individual, and it makes specific predictions about how manipulations of cortical structure and function will impact intellectual capacity.

The neural network classification of false killer whale (Pseudorca crassidens) vocalizations

This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional characterization of false killer whale vocalization, where each vocalization was characterized by a sequence of short-time measurements of duty cycle and peak frequency. The first neural network used competitive learning, where units in a competitive layer distributed themselves to recognize frequently presented input vectors. This network resulted in classes representing typical patterns in the vocalizations. The second network was a Kohonen feature map which organized the outputs topologically, providing a graphical organization of pattern relationships. The networks performed well as measured by (1) the average correlation between the input vectors and the weight vectors for each category, and (2) the ability of the networks to classify novel vocalizations. The techniques used in this study could easily be applied to other species and facilitate the development of objective, comprehensive repertoire models.

Atypical Categorization in Children with High Functioning Autism Spectrum Disorder

Children with autism spectrum disorder process many perceptual and social events differently from typically developing children, suggesting that they may also form and recognize categories differently. We used a dot pattern categorization task and prototype comparison modeling to compare categorical processing in children with high-functioning autism spectrum disorder and matched typical controls. We were interested in whether there were differences in how children with autism use average similarity information about a category to make decisions. During testing, the group with autism spectrum disorder endorsed prototypes less and was seemingly less sensitive to differences between to-be-categorized items and the prototype. The findings suggest that individuals with high-functioning autism spectrum disorder are less likely to use overall average similarity when forming categories or making categorical decisions. Such differences in category formation and use may negatively impact processing of socially relevant information, such as facial expressions. A supplemental appendix for this article may be downloaded from http://pbr.psychonomic-journals.org/content/supplemental.

Basal forebrain stimulation changes cortical sensitivities to complex sound

Experience affects how brains respond to sound. Here, we examined how the sensitivity and selectivity of auditory cortical neuronal responses were affected in adult rats by the repeated presentation of a complex sound that was paired with basal forebrain stimulation. The auditory cortical region that was responsive to complex sound was 2–5 five times greater in area in paired-stimulation rats than in naive rats. Magnitudes of neuronal responses evoked by complex sounds were also greatly increased by associative pairing, as were the percentages of neurons that responded selectively to the specific spectrotemporal features that were paired with stimulation. These findings demonstrate that feature selectivity within the auditory cortex can be flexibly altered in adult mammals through appropriate intensive training.

Spectrotemporal sensitivities in rat auditory cortical neurons

Studies in several mammalian species have demonstrated that auditory cortical neurons respond strongly to single frequency-modulated (FM) sweeps, and that most responses are selective for sweep direction and/or rate. In the present study, we used extracellular recordings to examine how neurons in the auditory cortices of anesthetized rats respond to continuous, periodic trains of FM sweeps (described previously by deCharms et al., Science 280 (1998) pp. 1439-1444, as moving auditory gratings). Consistent with previous observations in owl monkeys, we found that the majority of cortical neurons responded selectively to trains of either up-sweeps or down-sweeps; selectivity for down-sweeps was most common. Periodic responses were typically evoked only by sweep trains with repetition rates less than 12 sweeps per second. Directional differences in responses were dependent on repetition rate. Our results support the proposal that a combination of both spectral and temporal acoustic features determines the responses of auditory cortical neurons to sound, and add to the growing body of evidence indicating that the traditional view of the auditory cortex as a frequency analyzer is not sufficient to explain how the mammalian brain represents complex sounds.

Song copying by humpback whales: themes and variations

Male humpback whales (Megaptera novaeangliae) produce long, structured sequences of sound underwater, commonly called “songs.” Humpbacks progressively modify their songs over time in ways that suggest that individuals are copying song elements that they hear being used by other singers. Little is known about the factors that determine how whales learn from their auditory experiences. Song learning in birds is better understood and appears to be constrained by stable core attributes such as species-specific sound repertoires and song syntax. To clarify whether similar constraints exist for song learning by humpbacks, we analyzed changes over 14 years in the sounds used by humpback whales singing in Hawaiian waters. We found that although the properties of individual sounds within songs are quite variable over time, the overall distribution of certain acoustic features within the repertoire appears to be stable. In particular, our findings suggest that species-specific constraints on temporal features of song sounds determine song form, whereas spectral variability allows whales to flexibly adapt song elements.

Changes in NMDA receptor expression in auditory cortex after learning

Extensive practice on auditory learning tasks dramatically alters the functional organization and response properties of neurons in the auditory cortex. The cellular mechanisms responsible for this auditory learning-induced cortical plasticity are unclear; however, changes in synaptic function involving NMDA receptors have been strongly implicated. To test this hypothesis, we measured the change in gene expression of NMDA receptors and associated proteins in the auditory cortex of adult rats trained to perform an auditory identification task. NMDA receptor 2A and 2B gene expression in auditory cortex decreased significantly as auditory discrimination improved whereas expression of Arc, an immediate early gene involved in memory stabilization, increased. These results suggest that changes in NMDA receptors 2A and 2B and Arc enhance synaptic plasticity, thereby facilitating experience-dependent cortical remodeling and auditory learning.

A connectionist model of septohippocampal dynamics during conditioning: closing the loop.

Septohippocampal interactions determine how stimuli are encoded during conditioning. This study extends a previous neurocomputational model of corticohippocampal processing to incorporate hippocamposeptal feedback and examines how the presence or absence of such feedback affects learning in the model. The effects of septal modulation in conditioning were simulated by dynamically adjusting the hippocampal learning rate on the basis of how well the hippocampal system encoded stimuli. The model successfully accounts for changes in behavior and septohippocampal activity observed in studies of the acquisition, retention, and generalization of conditioned responses and accounts for the effects of septal disruption on conditioning. The model provides a computational, neurally based synthesis of prior learning theories that predicts changes in medial septal activity based on the novelty of stimulus events.