Functional Brain Circuitry Related to Arousal and Learning in Rats

González-Lima, Francisco

doi:10.1007/978-1-4899-0897-1_25

Cited by 18 publications

(19 citation statements)

References 63 publications

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“…This resulted in a C-shaped pattern of labeling delineated by activity in Areas 17, 18, retrosplenial cortex, and subiculum that was characteristic of EC brains (Figure 1). This regional pattern of labeling has not been seen by us in IC rats or in any untreated adult rats used in our previous 2-DG studies (Garrosa et al, 1990;Gonzalez-Lima, 1989Gonzalez-Lima, Helmstetter, & Agudo, 1993;Gonzalez-Lima & Scheich, 1985. The nucleus accumbens showed the greatest significant difference (40%) in mean activity between the groups, and was characterized by a uniform pattern of activation difficult to detect by visual inspection of autoradiographs, and more pronounced on its medial aspects.…”

Section: Resultsmentioning

confidence: 59%

“…We wanted to test the hypothesis that although rats are behaviorally inactive after termination of exposure to a complex environment, their brains may be quite metabolically active (Doyle, Nolan, & Regan, 1990;Martinez, Petty, & Messing, 1982;Saari, Armstrong, Nobrega, Pappas, & Coscina, 1990). This period of 2-DG uptake is also comparable to the duration of 2-DG sessions in our learning studies (Gonzalez-Lima, 1989Gonzalez-Lima & Scheich, 1986).…”

Section: Introductionmentioning

confidence: 96%

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Metabolic activation of the brain of young rats after exposure to environmental complexity

González-Lima

Ferchmin

Eterović

et al. 1994

Developmental Psychobiology

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Autoradiography with 14C-2-deoxyglucose was used to determine brain metabolic activity during the quiet period that follows after daily exploratory experiences in new complex environments. Eight 1-month-old, male Tryon rats were selected from two litters. Pairs of littermates matched by body weight were assigned to one of two conditions: rats housed individually in small home cages as the "impoverished condition," or rats exposed twice daily to changing and complex environments of two large cages with inanimate objects and conspecifics as the "enriched condition." After 4 days, rats were injected with 2-deoxyglucose, placed individually in a home cage and left undisturbed for 90 min until sacrificed. The brains of "enriched" rats were heavier than their "impoverished" littermates, and showed a global trend for metabolic enhancement. They also showed significantly greater amounts of 2-deoxyglucose in occipital cortex (27%), hippocampal subiculum (36%), and nucleus accumbens (40%).

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Section: Resultsmentioning

confidence: 59%

Section: Introductionmentioning

confidence: 96%

Metabolic activation of the brain of young rats after exposure to environmental complexity

González-Lima

Ferchmin

Eterović

et al. 1994

Developmental Psychobiology

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“…These and previous studies [Gonzalez-Lima, 1989 and1992 for review] indicate that multiple levels within the auditory system show learning changes. Furthermore, the use of structural equation modeling permitted characterization of the specific functional interactions among parallel neural pathways that presumably reflected the associated behavioral properties of the tone stimulus.…”

Section: General Discussion and Conclusionmentioning

confidence: 78%

“…These techniques determine patterns of regional interrelations independent of influences mediated by specific neuroanatomical pathways. However, brain functions related to learning are likely to be highly dependent on the specific connectivity between brain regions [Gonzalez-Lima, 1989McIntosh and Gonzalez-Lima, 19941.…”

Section: Introductionmentioning

confidence: 99%

Neural network interactions related to auditory learning analyzed with structural equation modeling

González-Lima

McLntosh

1994

Human Brain Mapping

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Abstract:If learning is an emergent property of interacting brain regions, understanding it requires a network analysis of the patterns of interaction between brain regions. Brain mapping techniques have the potential of providing information about functional interactions within entire neural systems, but computational methods are needed to make sense of the complex interactions that take place in the brain. This review paper illustrates, with examples from auditory learning studies, the application of a computational method that quantifies the interactions among neural regions in terms of networks, and what is gained from this approach. The method is Structural Equation Modeling, and it computes network interactions by combining anatomical circuitry with the covariation in the activity between auditory structures. Activity was assessed by fluorodeoxyglucose uptake, and the functional strengths of auditory pathways were quantified by computing path coefficients representing the strength of the functional influence through each anatomical path. Changes in these values were used as indices of how learned information was processed and modified within the auditory system. Structural models of the auditory system revealed the patterns of network interactions related to habituation to a sound, as well as the patterns related to the opposite learned associative properties of the same sound. They illustrated how the functional interactions among parallel auditory neural pathways were modified as a result of auditory learning. This analysis supports the hypothesis that auditory learning is an emergent network property, distributed among connected brain regions showing specific patterns of interaction.

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“…Both in anurans and mammals the activity in (certain) striatal structures increases towards novel stimuli and decreases towards familiar stimuli, while (certain) structures of the ventral medial pallium and hippocampus, respectively, display an opposite pattern of activity [94,95,136]. Striatal efferent neurons in toads may be considered also in a striato-nigro-tectal pathway [26,28,107].…”

Section: Gating Directed Attentionmentioning

confidence: 99%

Modulation of visual perception and action by forebrain structures and their interactions in amphibians

Ewert

Schwippert

Neurotransmitter Interactions and Cognitive Function

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Nervous systems of lower animals appraised simple prove to be relatively complexDo amphibians "know" while humans "learn"?Towards the middle of the last century, many ethologists suggested that behaviors displayed among so-called "lower" invertebrates or vertebrates -such as some crustaceans or amphibians, respectively -are predominantly innate and rigid in their performance (e.g., [1]). Moreover, responses to behaviorally significant sign stimuli should proceed reflex-like, for example, the lobster's tailflip-reflex in response to a threatening stimulus (e.g., [2]) and the toad's snap-reflex in response to a prey stimulus (e.g., [3]). In detail it was assumed, that a sign [key] stimulus activates an innate releasing mechanism (IRM), that -much like a safe is unlocked by a keyreleases the corresponding action pattern (e.g., [4,5]). According to the IRM concept, (re-)cognition and motor skills are innate. Neurophysiologically, the concept of IRM suggests an inborn sensorimotor interface that translates perception into action: recognizing ("detecting") the sign stimulus at its afferent input-side and activating ("commanding") the corresponding motor system at the efferent output-side. Hence, the concepts of "feature detector" and "command neuron" were born (e.g., [6,7]). Theoretically, the simplest innate releasing mechanism would consist of a command neuron, CN, operating in a chain like: sign-stimulus → CN → motor pattern generator → behavior In this case, the commanding neuron should be a cell specifically tuned to the feature of the sign stimulus, and the axon of that neuron should have access to the motor pattern generating network.Meanwhile, the concepts of command neuron and innate releasing mechanism were revisited and revised from many points of view (e.g., [8][9][10][11][12][13]). First of all, appetitive and consummative behavioral responses both in so-called lower and higher animals depend on state-dependent modulatory influences (referring to motivation

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Functional Brain Circuitry Related to Arousal and Learning in Rats

Cited by 18 publications

References 63 publications

Metabolic activation of the brain of young rats after exposure to environmental complexity

Metabolic activation of the brain of young rats after exposure to environmental complexity

Neural network interactions related to auditory learning analyzed with structural equation modeling

Modulation of visual perception and action by forebrain structures and their interactions in amphibians

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