Adaptive Changes in Cortical Receptive Fields Induced by Attention to Complex Sounds

Center for Auditory and Acoustic Research, Institute for Systems Research, Electrical and Computer Engineering, University of Maryland, College Park, MD 20742, USA.
Journal of Neurophysiology (Impact Factor: 2.89). 11/2007; 98(4):2337-46. DOI: 10.1152/jn.00552.2007
Source: PubMed

ABSTRACT Receptive fields in primary auditory cortex (A1) can be rapidly and adaptively reshaped to enhance responses to salient frequency cues when using single tones as targets. To explore receptive field changes to more complex spectral patterns, we trained ferrets to detect variable, multitone targets in the context of background, rippled noise. Recordings from A1 of behaving ferrets showed a consistent pattern of plasticity, at both the single-neuron level and the population level, with enhancement for each component tone frequency and suppression for intertone frequencies. Plasticity was strongest near neuronal best frequency, rapid in onset, and slow to fade. Although attention may trigger cortical plasticity, the receptive field changes persisted after the behavioral task was completed. The observed comb filter plasticity is an example of an adaptive contrast matched filter, which may generally improve discriminability between foreground and background sounds and, we conjecture, may predict A1 cortical plasticity for any complex spectral target.

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    • "As suggested previously in Figure 3, the suppressed sidebands surrounding the target tones show that the active STRFs were suppressed in between each of the target tones. The inhibitory effect is also relatively stronger for tones near BF compared to those far from BF. Importantly, this analysis has parallels with that of Fritz et al. (2007c), and we again find a general correspondence with those previously reported results. Finally, in Figure 4D, we consider the distribution of A TGT for near vs. far targets across all ensembles. "
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    ABSTRACT: To navigate complex acoustic environments, listeners adapt neural processes to focus on behaviorally relevant sounds in the acoustic foreground while minimizing the impact of distractors in the background, an ability referred to as top-down selective attention. Particularly striking examples of attention-driven plasticity have been reported in primary auditory cortex via dynamic reshaping of spectro-temporal receptive fields (STRFs). By enhancing the neural response to features of the foreground while suppressing those to the background, STRFs can act as adaptive contrast matched filters that directly contribute to an improved cognitive segregation between behaviorally relevant and irrelevant sounds. In this study, we propose a novel discriminative framework for modeling attention-driven plasticity of STRFs in primary auditory cortex. The model describes a general strategy for cortical plasticity via an optimization that maximizes discriminability between the foreground and distractors while maintaining a degree of stability in the cortical representation. The first instantiation of the model describes a form of feature-based attention and yields STRF adaptation patterns consistent with a contrast matched filter previously reported in neurophysiological studies. An extension of the model captures a form of object-based attention, where top-down signals act on an abstracted representation of the sensory input characterized in the modulation domain. The object-based model makes explicit predictions in line with limited neurophysiological data currently available but can be readily evaluated experimentally. Finally, we draw parallels between the model and anatomical circuits reported to be engaged during active attention. The proposed model strongly suggests an interpretation of attention-driven plasticity as a discriminative adaptation operating at the level of sensory cortex, in line with similar strategies previously described across different sensory modalities.
    Frontiers in Computational Neuroscience 09/2015; 9:106. DOI:10.3389/fncom.2015.00106 · 2.20 Impact Factor
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    • "Using this paradigm, STRFs showed the same facilitative enhancement at the target frequency, but also showed suppression at the reference tone frequency. These kinds of effects also occurred when the targets were multi-tone complexes, where STRFs showed enhancement at each tone frequency in the complex (with the greatest change occurring at a neuron's best frequency) and suppression at non-tone frequencies (Fritz et al. 2007). Interestingly, these STRF shape changes are highly dependent on the specific requirements of the training paradigm. "
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    ABSTRACT: Neural responses in the auditory cortex have historically been measured from either anesthetized or awake but non-behaving animals. A growing body of work has begun to focus instead on recording from auditory cortex of animals actively engaged in behavior tasks. These studies have shown that auditory cortical responses are dependent upon the behavioral state of the animal. The longer ascending subcortical pathway of the auditory system and unique characteristics of auditory processing suggest that such dependencies may have a more profound influence on cortical processing in the auditory system compared to other sensory systems. It is important to understand the nature of these dependencies and their functional implications. In this article, we review the literature on this topic pertaining to cortical processing of sounds.
    Brain Topography 02/2015; 28(3). DOI:10.1007/s10548-015-0428-4 · 3.47 Impact Factor
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    • "In developing our current understanding of how the cortico-thalamic network constructs awareness, new emphasis is being placed on the pre-eminence of intracortical network activity that is perturbed periodically by volleys of ascending information (Bastos et al., 2012; Singer, 2013). This view is more consistent with the observations that perception depends heavily on internallygenerated processes such as expectation, attention and arousal (Warren, 1970; Davis and Johnsrude, 2007; Fritz et al., 2007), that ascending afferents account for a small fraction of synaptic connections in neocortical circuits (Benshalom and White, 1986; Peters and Payne, 1993; Budd, 1998; Schoonover et al., 2014), and that cortical responses to sensory stimuli exhibit a high degree of trial-by-trial variability, due largely to variable cortical activity levels at the time of stimulation (Kisley and Gerstein, 1999; Lakatos et al., 2005; Curto et al., 2009; Pasley et al., 2009; White et al., 2012; Goris et al., 2014). Nearly ubiquitous in classical descriptions of neocortical function , the " canonical microcircuit model " sought to capture the sequential activation of cells in a neocortical column driven by bottom-up input following a sensory stimulus. "
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    ABSTRACT: The state of the sensory cortical network can have a profound impact on neural responses and perception. In rodent auditory cortex, sensory responses are reported to occur in the context of network events, similar to brief UP states, that produce "packets" of spikes and are associated with synchronized synaptic input (Bathellier et al., 2012; Hromadka et al., 2013; Luczak et al., 2013). However, traditional models based on data from visual and somatosensory cortex predict that ascending sensory thalamocortical (TC) pathways sequentially activate cells in layers 4 (L4), L2/3, and L5. The relationship between these two spatio-temporal activity patterns is unclear. Here, we used calcium imaging and electrophysiological recordings in murine auditory TC brain slices to investigate the laminar response pattern to stimulation of TC afferents. We show that although monosynaptically driven spiking in response to TC afferents occurs, the vast majority of spikes fired following TC stimulation occurs during brief UP states and outside the context of the L4>L2/3>L5 activation sequence. Specifically, monosynaptic subthreshold TC responses with similar latencies were observed throughout layers 2-6, presumably via synapses onto dendritic processes located in L3 and L4. However, monosynaptic spiking was rare, and occurred primarily in L4 and L5 non-pyramidal cells. By contrast, during brief, TC-induced UP states, spiking was dense and occurred primarily in pyramidal cells. These network events always involved infragranular layers, whereas involvement of supragranular layers was variable. During UP states, spike latencies were comparable between infragranular and supragranular cells. These data are consistent with a model in which activation of auditory cortex, especially supragranular layers, depends on internally generated network events that represent a non-linear amplification process, are initiated by infragranular cells and tightly regulated by feed-forward inhibitory cells.
    Frontiers in Systems Neuroscience 09/2014; 8:170. DOI:10.3389/fnsys.2014.00170
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