Biomedical subjects

Michael R W Dawson

Publications and source records attributed to Michael R W Dawson.

6 recordsLinked to original sources

PubMed2006

Statistical classification of black-capped (Poecile atricapillus) and mountain chickadee (Poecile gambeli) call notes.

Both black-capped (Poecile atricapillus) and mountain chickadees (Poecile gambeli) produce a chick-a-dee call that consists of several distinct note types. In some regions, these 2 species live sympatrically, and it has been shown that 1 species will respond weakly to songs of the other. This suggests that chickadee song, and potentially other of their vocalizations, contains species-specific information. We tested the possibility that call notes were acoustically sufficient for species identification. Black-capped and mountain non-D notes were summarized as a set of 9 features and then analyzed by linear discriminant analysis. Linear discriminant analysis was able to use these notes to identify species with 100% accuracy. We repeated this approach, but with black-capped and mountain D notes that were summarized as a set of 4 features. Linear discriminant analysis was able to use these notes to identify species with 94% accuracy. This demonstrates that any of the note types in these chickadee calls possesses sufficient information for species classification.

Acoustics↗

PubMed2006

Using an artificial neural network to classify black-capped chickadee (Poecile atricapillus) call note types.

The "chick-a-dee" call of the black-capped chickadee (Poecile atricapillus) contains four note types, A, B, C, and D that have important functional roles. This provides strong motivation for studying the classification of acoustic components of the call into different note types. In this paper, the spectrograms from a sample of A, B, and C notes (370 in total) were each described as a set of 9 summary features. An artificial neural network was trained to identify note type on the basis of these features, and was able to obtain better than 98% accuracy. An internal analysis of this network revealed a distributed code in which different hidden units generated high activities to different subsets of notes. By combining these different sensitivities, the network could discriminate all three types of notes. The performance of this network was compared to a discriminant analysis of the same data. This analysis also achieved a high level of performance (95%). A comparison between the two approaches revealed some striking similarities, but also some intriguing differences. These results are discussed in terms of two related issues: developing a research tool for note classification, and developing a theory of how birds themselves might classify notes.

Animals↗

PubMed2006

Artificial neural network discrimination of black-capped chickadee (Poecile atricapillus) call notes.

Artificial neural networks were trained to discriminate between two different notes from the "chick-a-dee" call of the black-capped chickadee (Poecile atricapillus). An individual note was represented as a vector of nine summary features taken from note spectrograms. A network was trained to respond to exemplar notes of one type (e.g., A notes) and to fail to respond to exemplar notes of another type (e.g., B notes). After this training, the network was presented novel notes of the two different types, as well as notes of the same two types that had been shifted upwards or downwards in frequency. The strength of the response of the network to each novel and shifted note was recorded. When network responses were plotted as a function of the degree of frequency shift, the results were very similar to those observed in birds that were trained in an analogous task [Charrier et al., J. Comp. Psychol. 119(4), 371-380 (2005)]. The implications of these results to simulating behavioral studies of animal communication are discussed.

Animals↗

PubMed2005

Functional localization and double dissociations: the relationship between internal structure and behavior.

Lesioning studies are often used in cognitive neuroscience to make inferences about the architecture of cognition. Recently, computational models have been used to address some of the underlying assumptions-such as modularity and locality-often implicitly used when interpreting lesion data. In this article, we explore the "functional localization" assumption and its role in interpreting lesioning data, especially from double dissociations. The functional localization assumption states that units or subunits within an information processing system become functionally specialized for dealing with specific aspects of the input environment. Networks were trained on one of two problems-an abstract "rules and sub-rules" problem, and a more concrete "logic classification" problem-and then systematically lesioned. Networks were analyzed in terms of their overt behavior, and more importantly, in terms of their internal structure. Performance deficits in both form and magnitude could be directly related to the ablated internal structure of the networks. That is, if an ablated area had little or no functional localization, then little or no behavioral dissociations were observed. If, however, the ablated area had very specific internal structure, then very specific behavioral dissociations were observed. It is important to note, however, that there was not a one-to-one correspondence between internal structure and behavioral dissociations, implying that cognitive neuroscientists must be careful when using lesioning data to theorize about the functional architecture of cognition.

Brain↗

PubMed2004

Hemispheric performance in object-based attention.

The goal of the present study was to investigate whether object-based attention effects differ across the cerebral hemispheres. Previous research has suggested that object-based attention is preferentially lateralized to the left hemisphere (Egly, Driver, & Rafal, 1994; Egly, Rafal, Driver, & Starrveveld, 1994). However, work by Vecera (1994) has suggested that these previous studies may have failed to obtain a pure measure of object-based attention. The present study applied modified versions of Duncan's (1984) seminal object-based attention paradigm. Subjects were typically presented with one target object to a single visual field (one-object display), two target objects to the same visual field (two-object unilateral display), or two target objects to different visual fields (two-object bilateral display). In all three experiments, response accuracy was higher for the one-object displays than for the two-object displays. Most important, this object-based cost was especially severe when selection of two target elements was isolated to the right visual field (left hemisphere). We confirmed that this effect was specific to object-based attention in three different ways: Experiment 1 manipulated stimulus distance, as recommended by Vecera; Experiment 2 ensured that target selection was based on nonspatial attributes; and Experiment 3 used overlapping displays, as in Duncan (1984). Collectively, the data are in accord with previous conclusions that object-based attention is a specialized form of orienting subserved by lateralized cortical brain mechanisms. However, contrary to previous research, it appears that it is the right hemisphere, and not the left hemisphere, that is preferentially biased for committing object-based attention to elements in the visual environment.

Attention↗

PubMed2003

Temporal frequency and velocity-like tuning in the pigeon accessory optic system.

Neurons in the accessory optic system (AOS) and pretectum are involved in the analysis of optic flow and the generation of the optokinetic response. Previous studies found that neurons in the pretectum and AOS exhibit direction selectivity in response to large-field motion and are tuned in the spatiotemporal domain. Furthermore, it has been emphasized that pretectal and AOS neurons are tuned to a particular temporal frequency, consistent with the "correlation" model of motion detection. We examined the responses of neurons in the nucleus of the basal optic root (nBOR) of the AOS in pigeons to large-field drifting sine wave gratings of varying spatial (SF) and temporal frequencies (TF). nBOR neurons clustered into two categories: "Fast" neurons preferred low SFs and high TFs, and "Slow" neurons preferred high SFs and low TFs. The fast neurons were tuned for TF, but the slow nBOR neurons had spatiotemporally oriented peaks that suggested velocity tuning (TF/SF). However, the peak response was not independent of SF; thus we refer to the tuning as "apparent velocity tuning" or "velocity-like tuning." Some neurons showed peaks in both the fast and slow regions. These neurons were TF-tuned at low SFs, and showed velocity-like tuning at high SFs. We used computer simulations of the response of an elaborated Reichardt detector to show that both the TF-tuning and velocity-like tuning shown by the fast and slow neurons, respectively, may be explained by modified versions of the correlation model of motion detection.

Action Potentials↗