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Songbirds are a well-established animal model to study the neural basis of learning, perception and production of complex vocalizations. In this system, telencephalic neurons in HVC present a state-dependent, highly selective response to auditory presentations of the bird's own song (BOS). This property provides an opportunity to study the neural code behind a complex motor behavior. In this work, we explore whether changes in the temporal structure of the sound envelope can drive changes in the neural responses of highly selective HVC units. We generated an envelope-modified BOS (MOD) by reversing each syllable's envelope but leaving the overall temporal structure of syllable spectra unchanged, which resulted in a subtle modification for each song syllable. We conducted in vivo electrophysiological recordings of HVC neurons in anaesthetized zebra finches (Taeniopygia guttata). Units analyzed presented a high BOS selectivity and lower response to MOD, but preserved the profile response shape. These results show that the temporal evolution of the sound envelope is being sensed by the avian song system and suggest that the biomechanical properties of the vocal apparatus could play a role in enhancing subtle sound differences.

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Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections ("Mexican hat" connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range ("inverse Mexican hat" connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons.

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Several studies have shown that connexin channels play an important role in retinal neural coding in nocturnal rodents. However, the contribution of these channels to signal processing in the retina of diurnal rodents remains unclear. To gain insight into this problem, we studied connexin expression and the contribution of connexin channels to the retinal light response in the diurnal rodent Octodon degus (degu) compared to rat, using in vivo ERG recording under scotopic and photopic light adaptation. Analysis of the degu genome showed that the common retinal connexins present a high degree of homology to orthologs expressed in other mammals, and expression of Cx36 and Cx43 was confirmed in degu retina. Cx36 localized mainly to the outer and inner plexiform layers (IPLs), while Cx43 was expressed mostly in cells of the retinal pigment epithelium. Under scotopic conditions, the b-wave response amplitude was strongly reduced by 18-ß-glycyrrhetinic acid (ß-GA) (-45.1% in degu, compared to -52.2% in rat), suggesting that connexins are modulating this response. Remarkably, under photopic adaptation, ß-GA increased the ERG b-wave amplitude in degu (+107.2%) while reducing it in rat (-62.3%). Moreover, ß-GA diminished the spontaneous action potential firing rate in ganglion cells (GCs) and increased the response latency of ON and OFF GCs. Our results support the notion that connexins exert a fine-tuning control of the retinal light response and have an important role in retinal neural coding.

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As most sensory modalities, the visual system needs to deal with very fast changes in the environment. Instead of processing all sensory stimuli, the brain is able to construct a perceptual experience by combining selected sensory input with an ongoing internal activity. Thus, the study of visual perception needs to be approached by examining not only the physical properties of stimuli, but also the brain's ongoing dynamical states onto which these perturbations are imposed. At least three different models account for this internal dynamics. One model is based on cardinal cells where the activity of few cells by itself constitutes the neuronal correlate of perception, while a second model is based on a population coding that states that the neuronal correlate of perception requires distributed activity throughout many areas of the brain. A third proposition, known as the temporal correlation hypothesis states that the distributed neuronal populations that correlate with perception, are also defined by synchronization of the activity on a millisecond time scale. This would serve to encode contextual information by defining relations between the features of visual objects. If temporal properties of neural activity are important to establish the neural mechanisms of perception, then the study of appropriate dynamical stimuli should be instrumental to determine how these systems operate. The use of natural stimuli and natural behaviors such as free viewing, which features fast changes of internal brain states as seen by motor markers, is proposed as a new experimental paradigm to study visual perception.

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Consciousness, that experienced flow of subjective states, is one of the mysteries, and perhaps, the fundamental challenge of science until now. It is also a field of exploration specially active and fruitful, a field that has passed over the frontier of XIX and XX centuries, and recently arrived again with a strong impetus in the XXI century. However, there is a great controversy about the plausibility of a theoretical, analytical and formal (v.g.: computational) explanation of the phenomena that we associate with consciousness. Is it possible to establish a reductionist explanation of consciousness? Or in other words, is it possible to make a description of the conscious phenomena expressed in terms of functional and/or causal relationships? In this article I give some relevant elements to sketch the sufficiency of explanation of the connectionist computational paradigm, and how we could elucidate the formal principles embedded in the study of consciousness. The purpose of the present article is to suggest that the plausibility of the connectionist paradigm is supported by the following issues: (1) the level of fine-grained detail with which we define the representation and computability of conscious states, (2) the methodological and conceptual advances of brain sciences, and (3) the difference that we assume between the notions of simulation, modelling and computational representation of consciousness. With these ideas in mind, through the manuscript I will show a basic framework to understand why connectionism can be a plausible candidate to think about a formal theory of consciousness. Finally, in the light of the previous statements, I will point out some important issues to discuss the plausibility of a computational theory of consciousness.

La actividad conciente, ese devenir que experimentamos como una serie de estados de subjetividad, es uno de los misterios, y quizás el desafío fundamental de la ciencia contemporánea. Es también un campo de exploración especialmente activo y fructífero que sobrevivió la transición entre los siglos XIX y XX, y nuevamente ha tomado un fuerte impulso ahora en el XXI. Existe, sin embargo, una gran controversia sobre la plausibilidad de una explicación teórica, analítica y formal (v.g.: computacional) de los fenómenos que asociamos a la actividad conciente. ¿Es factible formular una explicación reduccionista de la actividad conciente, es decir, una descripción del fenómeno expresada en términos de relaciones funcionales y/o causales? Los párrafos del presente ensayo escudriñan algunos elementos relevantes a fin de establecer la suficiencia explicativa que tiene el paradigma computacional conexionista para dilucidar los principios formales imbricados en el estudio de la actividad conciente. El propósito que subyace la elaboración siguiente es sugerir que la viabilidad del conexionismo y del proyecto computacional depende de los siguientes aspectos: (1) El grado de refinamiento con el que se defina la representación y la computabilidad de los estados concientes, (2) Los avances metodológicos y conceptuales de las ciencias del cerebro, y (3) La distinción que se haga entre simulación, modelamiento y representación computacional de la actividad conciente. Con estas ideas en mente, a través del capítulo mostraré un esquema conceptual básico para entender por qué el paradigma conexionista puede ser un candidato plausible para pensar una teoría formal de la actividad conciente. Finalmente, a la luz de los planteamientos presentados, señalaré algunos aspectos importantes para establecer la viabilidad de una teoría computacional de la actividad conciente.