Multi-electrode array for measuring evoked potentials from surface of ferret primary auditory cortex

Owens, Anthony L.; Denison, Timothy; Versnel, Huib; Rebbert, Milton; Peckerar, Martin C.; Shamma, Shihab A.

doi:10.1016/0165-0270(94)00178-j

Cited by 43 publications

(19 citation statements)

References 12 publications

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“…On the other hand, physiological studies of owl (36) and squirrel monkey (37) AI suggest multiple spectral-tuning modules in primates. The AI isofrequency axis is small (Ͻ2 mm) in many species (24,(33)(34)(35) relative to that of cat (Fig. 5) and primates (refs.…”

Section: Discussionmentioning

confidence: 93%

“…Studies in birds (33) and bats (34) find patchy connections between the primary and secondary auditory fields, but there is no evidence for multiple functional or anatomic modules within the isofrequency axis in bird, bat, rat, or ferret AI (24,(33)(34)(35). On the other hand, physiological studies of owl (36) and squirrel monkey (37) AI suggest multiple spectral-tuning modules in primates.…”

Section: Discussionmentioning

confidence: 99%

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Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex

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Winer

Schreiner

2001

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

133

103

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Many response properties in primary auditory cortex (AI) are segregated spatially and organized topographically as those in primary visual cortex. Intensive study has not revealed an intrinsic, anatomical organizing principle related to an AI functional topography. We used retrograde anatomic tracing and topographic physiologic mapping of acoustic response properties to reveal long-range (>1.5 mm) convergent intrinsic horizontal connections between AI subregions with similar bandwidth and characteristic frequency selectivity. This suggests a modular organization for processing spectral bandwidth in AI.corticocortical projections ͉ cortical modules L ittle is known about how intrinsic connections in cat primary auditory cortex (AI) are organized and what their functions are. These connections form a discontinuous and elongated spatial pattern (1-3) different from that in the primary visual cortex (4 -6). After artificial rerouting of visual thalamic afferents into AI, intrinsic connectivity takes on spatial and functional characteristics of primary visual cortex (VI) (7). However, the relationship between acoustic response properties and intracortical connectivity in AI is unknown. Studies of the spatial organization of frequency (2,3,8) and binaurality (8 -11) show that these features cannot account for the topography of AI horizontal connections. Injections of AI with anterograde tracers that involve supragranular cortical layers find many intrinsic terminal patches in the dorsoventral (isofrequency) axis and few that cross the caudorostral (cochleotopic) dimension of AI. The frequency preference of the patches was believed to match the injection site because most labeling followed the dorsoventral axis (2, 3). However, it has been suggested that the dorsal patches of labeling are tuned preferentially to higher frequencies (1); hence, the frequency alignment of intrinsic connections in AI is still unresolved. AI neurons also segregate according to binaural properties, and the spatial pattern of excitatory and inhibitory binaural bands covaries with bands of commissural terminal labeling (8 -11). However, the spatial arrangement of AI horizontal intrinsic connections differs from that of binaural bands (1).Features other than characteristic frequency (CF) and binaurality that are represented in AI include intensity dependence, excitatory bandwidth, preferred speed of frequency sweeps, and response latency (12)(13)(14)(15)(16)(17)(18)(19). Each feature has a slightly different topographic organization. However, most align dorsoventrally to a central cluster of neurons with narrow bandwidth (NB) tuning (19). This region crosses all frequencies and is flanked above and below (along the isofrequency axis) by clusters of broadbandwidth (BB) neurons (12,14,19). We mapped bandwidth topography (14) to target deposits of a tracer in the central NB region. We found multiple patches of retrograde labeling at consistent and predictable locations within AI. One, and perhaps all, of these patches contain neurons with spectra...

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex

Read

Winer

Schreiner

2001

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

133

103

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“…This gap in our knowledge is due, in part, to our inability to record simultaneously from large regions of the auditory cortex with high spatial and temporal resolution and large cortical area coverage. Although providing important principles, previous single-unit and electrocortigraphical studies have been limited to simultaneous recordings from fewer cortical sites Mesgarani and Chang 2012;Ogawa et al 2011;Owens et al 1995;Pasley et al 2012;Takahashi et al 2003). Large-scale recordings have been obtained with intrinsic imaging; however, these recordings reflect slow metabolic activity and not temporally precise neural activity (Besle et al 2011;Ebner and Chen 1995).…”

Section: Discussionmentioning

confidence: 99%

“…A similar approach has been used to record STRFs in A1 of rodents previously (Geffen et al 2011;Linden et al 2003;Machens et al 2004). This approach also has been adapted to quantify temporally precise A1 local field potential responses with ECoG arrays (Owens et al 1995;Takahashi et al 2003). Here, we assess temporally precise and reliable ECoG STRFs in A1, ventral auditory field (VAF), and a region dorsal to A1.…”

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confidence: 99%

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings

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Viventi

et al. 2014

Journal of Neurophysiology

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“…Different kinds of polyimide-based microdevices have been also fabricated for interfacing with regenerating peripheral nerves (Stieglitz et al, , 1997Stieglitz, 2001). However, there have been only a few reported attempts to develop flexible polyimide-based microelectrode arrays for recording cortical surface field potentials (Owens et al, 1995;Hollenberg et al, 2006;Takahashi et al, 2003;Myllymaa et al, 2008b).…”

Section: Introductionmentioning

confidence: 99%

Fabrication and testing of polyimide-based microelectrode arrays for cortical mapping of evoked potentials

Myllymaa

Korhonen

et al. 2009

Biosensors and Bioelectronics

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Multi-electrode array for measuring evoked potentials from surface of ferret primary auditory cortex

Cited by 43 publications

References 12 publications

Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex

Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings

Fabrication and testing of polyimide-based microelectrode arrays for cortical mapping of evoked potentials

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