Learning-Related Plasticity of Gerbil Auditory Cortex: Feature Maps Versus Meaning Maps

Scheich, Henning; Simonis, C.; Ohl, Frank W.; Thomas, H.; Tillein, Jochen

doi:10.1007/978-94-011-2712-7_17

Cited by 17 publications

(11 citation statements)

References 22 publications

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“…Interestingly, some early electrophysiological evidence for learning-related changes in visual cortex exists (21), and a more recent magnetoencephalographic study has demonstrated similar changes in auditory cortex (22). These findings, with those of the present study, are also consistent with animal data suggesting that primary sensory (auditory) cortex has a role in associative learning beyond simple stimulus reception (23)(24)(25)(26) and are anticipated by the occurrence of learning-related alterations in primary sensory receptors in invertebrates (27).…”

Section: Discussionsupporting

confidence: 90%

“…Learning-related alterations in rCBF found during conditioning in brain regions, which are relatively neglected in studies of human learning-e.g., primary sensory cortex and the cerebellum-add to evidence that these areas are involved in cognitive functions beyond stimulus reception (23)(24)(25)(26) and the integration of motor activity (44), respectively. Regardless of whether these regions are critical for associative learning, the findings presented here demonstrate that the normal brain operations underlying associative learning involve cooperative interactions among many brain areas (45).…”

Section: Discussionmentioning

confidence: 92%

See 1 more Smart Citation

A functional anatomical study of associative learning in humans.

Molchan

Sunderland

McIntosh

et al. 1994

Proc. Natl. Acad. Sci. U.S.A.

257

161

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The purpose of the study was to map the functional neuroanatomy of simple associative learning in humans. Eyeblink conditioning was studied in eight normal volunteers using positron emission tomography and H2150.Regional cerebral blood flow was assessed during three sequential phases: (i) explicitly unpaired presentations of the unconditioned stimulus (air puff to the right eye) and conditioned stimulus (binaural tone), (ii) paired presentations of the two stimuli (associative learning), and (Wi) presentation of the conditioned stimulus alone. During associative learning, relative to the unpaired phase, blood flow was significantly increased in primary auditory and left posterior cingulate cortices and significantly decreased in areas of the right cerebellar, right prefrontal, right parietal, and insular cortices and right neostriatum. The lateralization of the changes may relate to the functional organization of memory and learning processes in the brain. The activation in primary auditory cortex is an example, using a neuroimaging technique, of a learning-related change in primary sensory cortex in humans. The changes in areas such as the cerebellum, prefrontal cortex, and neostriatum provide support for their roles in associative learning as proposed by animal models. Moreover, these findings show that in humans, even simple classical conditioning involves distributed changes in multiple neural systems.The behavioral laws underlying classical conditioning of skeletal responses, such as eyeblink, are well defined, making this paradigm especially attractive for studying human associative learning (1, 2). Although animal studies of associative learning have provided considerable information on neurophysiological and neuroanatomical substrates (3-7), little is known about the neural systems involved in associative learning in humans.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 92%

A functional anatomical study of associative learning in humans.

Molchan

Sunderland

McIntosh

et al. 1994

Proc. Natl. Acad. Sci. U.S.A.

257

161

View full text Add to dashboard Cite

show abstract

“…These examples suggest that different brain areas can play important roles in multiple functions beyond their classical distinctions, and this may be a general property of the central nervous system rather than specific to only a few brain regions. Indeed, these views are consistent with the adaptive characteristics of the central nervous system, in which functional organiza-tion is viewed as dynamically related to the particular environmental demands rather than a static property [John and Schwartz, 1978;GonzalezLima, 1993, 1994;Merzenich and Sameshima, 1993;Pascaul-Leone et al, 1994;Recanzone et al, 1992;Scheich et al, 1992;Wolpaw and Lee, 1989;Zohary et al, 19941. Brain imaging techniques will make an important contribution to the understanding of this property, given their ability to asses5 activity across many neural regions.…”

Section: What Is the Benefit Of Analytic Approaches Toward The Study mentioning

confidence: 68%

“…The important point is that it may be possible for parts of the same anatomical network to be involved in another function when the interactions change. For example, numerous behavioral brain studies have suggested that primary auditory areas show activity related both to the perceptual components of a stimulus and its learned behavioral relevance [Gonzalez-Lima, 1992, McIntosh andGonzalez-Lima, 1993;Scheich et al, 1992;Weinberger et al, 19901. Thus, the same anatomical network can code, in parallel, the perceptual and behavioral properties of stimuli depending on the nature of the interactions between the parts of the network.…”

Section: What Is the Benefit Of Analytic Approaches Toward The Study mentioning

confidence: 99%

Structural equation modeling and its application to network analysis in functional brain imaging

McLntosh

González-Lima

1994

Human Brain Mapping

771

614

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4Abstract: The analysis of brain imaging data has recently focused on the examination of the covariances of activity among neural regions during different behaviors. We present some of the theoretical and technical issues surrounding one of these covariance-based methods: structural equation modeling. In structural equation modeling, connections between brain areas are based on known neuroanatomy, and the interregional covariances of activity are used to calculate path coefficients representing the magnitude of the influence of each directional path. The logic behind the use of structural equation modeling stems from the suggestion that brain function is the result of changes in the covariances of activity among neural elements. The technical foundations for neural structural equation models are presented, emphasizing the ability to make inferential comparisons to evaluate the experimental changes in path coefficients. Simulated data sets were used to test the effects of omitted regions and omitted connections. The results suggested that structural modeling algorithms can give hints as to possible external influences and missing paths, but that the final decision as to model modifications requires the guidance of the researcher. The utility of anatomically based models to distinguish between the direct effect of one regon on another, and indirect effects mediated through intervening regions, is demonstrated in an empirical data set that examined the effects of darkness or patterned light on the metabolic activity in the rat visual system. The anatomical framework for the structural equation models revealed that the total impact of ascending thalamocortical influences was modified by corticocortical interactions. Extensions of structural equation modeling to human brain imaging experiments are presented. We conclude by suggesting that neural covariances may be a more accurate way to examine the dynamic functional organization of the central nervous system.

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“…First, studies in humans and lower mammals suggest that conditioning-dependent retuning of sensory representations of the conditioned danger cue toward resembling stimuli leads to overgeneralization by rendering perceptual discrimination of the danger cue from its approximations more difficult (34,35). This conditioning-dependent effect has been tightly linked to the cholinergic system (35,36).…”

Section: Treatment Implicationsmentioning

confidence: 99%

Neural Substrates of Overgeneralized Conditioned Fear in PTSD

Kaczkurkin

Burton

Chazin

et al. 2017

AJP

213

175

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Objective: Heightened generalization of fear from an aversively reinforced conditioned stimulus (CS+, a conditioned danger cue) to resembling stimuli is widely accepted as a pathogenic marker of posttraumatic stress disorder (PTSD). Indeed, a distress response to benign stimuli that "resemble" aspects of the trauma is a central feature of the disorder. To date, the link between overgeneralization of conditioned fear and PTSD derives largely from clinical observations, with limited empirical work on the subject. This represents the first effort to examine behavioral and brain indices of generalized conditioned fear in PTSD using systematic methods developed in animals known as generalization gradients: the gradual decline in conditioned responding as the presented stimulus gradually differentiates from CS+.Method: Gradients of conditioned fear generalization were assessed using functional MRI and behavioral measures in U.S. combat veterans who served in Iraq or Afghanistan and had PTSD (N=26), subthreshold PTSD (N=19), or no PTSD (referred to as trauma control subjects) (N=17). Presented stimuli included rings of graded size, with extreme sizes serving as CS+ (paired with shock) and as a nonreinforced conditioned stimulus (CS-, a conditioned safety cue), and with intermediate sizes forming a continuum of similarity between CS+ and CS-. Generalization gradients were assessed as response slopes from CS+, through intermediate ring sizes, to CS-, with less steep slopes indicative of stronger generalization.Results: Relative to trauma control subjects, PTSD patients showed stronger conditioned generalization, as evidenced by less steep generalization gradients in both behavioral risk ratings and brain responses in the left and right anterior insula, left ventral hippocampus, dorsolateral and dorsomedial prefrontal cortex, and caudate nucleus. Severity of PTSD symptoms across the three study groups was positively correlated with levels of generalization at two such loci: the right anterior insula and left ventral hippocampus. Conclusions:The results point to evidence of brain-based markers of overgeneralized fear conditioning related to PTSD. These findings provide further understanding of a central yet understudied symptom of trauma-related psychopathology. Am J Psychiatry 2017; 174:125-134; doi: 10.1176/appi.ajp.2016 Generalization of conditioned fear is a basic, cross-species, associative-learning process whereby fear acquired to a conditioned stimulus (CS+), paired with an aversive unconditioned stimulus, transfers to safe stimuli resembling the CS+ (1). Heightened levels of generalized conditioned fear have been adopted as a core feature of trauma-related psychopathology (2), and DSM-5 criteria for posttraumatic stress disorder (PTSD) include heightened distress to situations "resembling" aspects of the trauma. The pathogenic contribution of conditioned generalization to PTSD follows from the undue proliferation of trauma cues in an individual's posttrauma environment that then increases and/or sustains PTSD sympt...

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Learning-Related Plasticity of Gerbil Auditory Cortex: Feature Maps Versus Meaning Maps

Cited by 17 publications

References 22 publications

A functional anatomical study of associative learning in humans.

A functional anatomical study of associative learning in humans.

Structural equation modeling and its application to network analysis in functional brain imaging

Neural Substrates of Overgeneralized Conditioned Fear in PTSD

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