Multiparametric Auditory Receptive Field Organization Across Five Cortical Fields in the Albino Rat

Polley, Daniel B.; Read, Heather L.; Storace, Douglas A.; Merzenich, Michael M.

doi:10.1152/jn.01298.2006

Cited by 300 publications

(397 citation statements)

References 77 publications

(106 reference statements)

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“…Common principles of cortical organization are also observed in other mammalian species including bats (Esser and Eiermann, 1999; Hoffmann et al, 2008), gerbils (Budinger et al, 2000), guinea pigs (Wallace et al, 2002), rats (Polley et al, 2007; Storace et al, 2010), and mice (Hofstetter and Ehret, 1992; Hackett et al, 2011). Like the ferret, each of these species has a number of tonotopic areas, which are highly interconnected and which receive distinct patterns of thalamic input.…”

Section: Discussionmentioning

confidence: 76%

Cortico‐cortical connectivity within ferret auditory cortex

Bizley

Bajo

Nodal³

et al. 2015

J of Comparative Neurology

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Despite numerous studies of auditory cortical processing in the ferret (Mustela putorius), very little is known about the connections between the different regions of the auditory cortex that have been characterized cytoarchitectonically and physiologically. We examined the distribution of retrograde and anterograde labeling after injecting tracers into one or more regions of ferret auditory cortex. Injections of different tracers at frequency‐matched locations in the core areas, the primary auditory cortex (A1) and anterior auditory field (AAF), of the same animal revealed the presence of reciprocal connections with overlapping projections to and from discrete regions within the posterior pseudosylvian and suprasylvian fields (PPF and PSF), suggesting that these connections are frequency specific. In contrast, projections from the primary areas to the anterior dorsal field (ADF) on the anterior ectosylvian gyrus were scattered and non‐overlapping, consistent with the non‐tonotopic organization of this field. The relative strength of the projections originating in each of the primary fields differed, with A1 predominantly targeting the posterior bank fields PPF and PSF, which in turn project to the ventral posterior field, whereas AAF projects more heavily to the ADF, which then projects to the anteroventral field and the pseudosylvian sulcal cortex. These findings suggest that parallel anterior and posterior processing networks may exist, although the connections between different areas often overlap and interactions were present at all levels. J. Comp. Neurol. 523:2187–2210, 2015. © 2015 Wiley Periodicals, Inc.

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Section: Discussionmentioning

confidence: 76%

Cortico‐cortical connectivity within ferret auditory cortex

Bizley

Bajo

Nodal³

et al. 2015

J of Comparative Neurology

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“…Although the increases in Arc expression in A1 of animals that had just learned the task were robust, such changes did not generalize to the entire cortex, because the percentage of Arcexpressing neurons remained low in the perirhinal cortex, which is located just ventral of the auditory-responsive fields (0.92 ± 0.13%) (25,26).…”

Section: Resultsmentioning

confidence: 98%

Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

Carpenter-Hyland

Plummer

Vazdarjanova

et al. 2010

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

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Models of learning-dependent sensory cortex plasticity require local activity and reinforcement. An alternative proposes that neural activity involved in anticipation of a sensory stimulus, or the preparatory set, can direct plasticity so that changes could occur in regions of sensory cortex lacking activity. To test the necessity of target-induced activity for initial sensory learning, we trained rats to detect a low-frequency sound. After learning, Arc expression and physiologically measured neuroplasticity were strong in a high-frequency auditory cortex region with very weak target-induced activity in control animals. After 14 sessions, Arc and neuroplasticity were aligned with target-induced activity. The temporal and topographic correspondence between Arc and neuroplasticity suggests Arc may be intrinsic to the neuroplasticity underlying perceptual learning. Furthermore, not all neuroplasticity could be explained by activity-dependent models but can be explained if the neural activity involved in the preparatory set directs plasticity.rat | instrumental learning | neurophysiology T he brain's ability to modify its own structure and function is currently used in diverse therapies involving remediation of language-learning impairment, reversing age-related cognitive decline, stroke rehabilitation, and others. These powers of neuroplasticity stem from the mammalian brain's ability to reorganize in response to experience (1-4). In sensory cortex, plasticity induced by sensory tasks optimizes the brain's capacity for future performance through amplifying activity that is most informative about reinforcement (4-6). Dominant models of this plasticity are activity-dependent (2,7,8), and associated learning is presumed to be a function of endogenous processes reliant on gene activation, because long-term plasticity and long-term memory require protein synthesis (9) following expression of immediate-early genes such as Arc (10, 11). Although models of sensory cortex plasticity are dependent on activity, these models fail to account for plasticity and behavioral phenomena observed shortly after learning.A prediction of activity-dependent models is that the strongest and most selective population responses to a target stimulus should grow the most. However, in contrast to this prediction, cortical patterns of activity early after learning enter a weakly selective and highly responsive state that is subsequently refined into a highly selective and less responsive state (3). The same phenomenon is reflected behaviorally. If auditory stimuli are paired with nucleus basalis stimulation, acoustically induced changes in respiratory rate can initially be induced by a wide range of sound frequencies, and these induced respiratory changes become more frequency-specific with time (12). These findings suggest that cortical regions representing sensory stimuli other than the learned sensory stimulus may be recruited in brain plasticity shortly after learning. This conclusion contrasts with activity-dependent models. Although memor...

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“…Gerbils, guinea pigs, and rats have overlapping hearing ranges and similar frequency organization of A1 relative to the anterior auditory field (AAF) and a third ventral field with distinct frequency organization (Wallace et al, 2000;Kalatsky et al, 2005;Donishi et al, 2006;Budinger and Scheich, 2009). In the rat, this ventral field is called the suprarhinal auditory field (SRAF) (Polley et al, 2007). Neurons in caudal SRAF (cSRAF) respond more selectively to sound frequency and position cues than their frequency-matched counterparts in A1 (Polley et al, 2007;Higgins et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…In the rat, this ventral field is called the suprarhinal auditory field (SRAF) (Polley et al, 2007). Neurons in caudal SRAF (cSRAF) respond more selectively to sound frequency and position cues than their frequency-matched counterparts in A1 (Polley et al, 2007;Higgins et al, 2010). These sound-encoding differences could stem from physiologic and anatomic differences evident along the caudal-rostral axis of MGBv (Redies et al, 1989;Rodrigues-Dagaeff et al, 1989;Cant and Benson, 2007;Storace et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Gene Expression Identifies Distinct Ascending Glutamatergic Pathways to Frequency-Organized Auditory Cortex in the Rat Brain

et al. 2012

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A conserved feature of sound processing across species is the presence of multiple auditory cortical fields with topographically organized responses to sound frequency. Current organizational schemes propose that the ventral division of the medial geniculate body (MGBv) is a single functionally homogenous structure that provides the primary source of input to all neighboring frequency-organized cortical fields. These schemes fail to account for the contribution of MGBv to functional diversity between frequency-organized cortical fields. Here, we report response property differences for two auditory fields in the rat, and find they have nonoverlapping sources of thalamic input from the MGBv that are distinguished by the gene expression for type 1 vesicular glutamate transporter. These data challenge widely accepted organizational schemes and demonstrate a genetic plurality in the ascending glutamatergic pathways to frequency-organized auditory cortex.

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Multiparametric Auditory Receptive Field Organization Across Five Cortical Fields in the Albino Rat

Abstract: Polley DB, Read HL, Storace DA, Merzenich MM. Multiparametric auditory receptive field organization across five cortical fields in the albino rat.

Cited by 300 publications

References 77 publications

Cortico‐cortical connectivity within ferret auditory cortex

Cortico‐cortical connectivity within ferret auditory cortex

Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

Gene Expression Identifies Distinct Ascending Glutamatergic Pathways to Frequency-Organized Auditory Cortex in the Rat Brain

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