Intracellular Correlates of Stimulus-Specific Adaptation

Hershenhoren, Itai; Taaseh, Nevo; Antunes, Flora M.; Nelken, Israel

doi:10.1523/jneurosci.2166-13.2014

Cited by 67 publications

(107 citation statements)

References 42 publications

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“…As pointed out previously (Farley et al, 2010), the higher response to the deviant might have been due to a greater cross-stimulus adaptation in the equiprobable compared with the oddball sequence. The importance of cross-stimulus adaptation in the equiprobable control conditions has been demonstrated by Taaseh et al (2011) and Hershenhoren et al (2014) in single-unit recordings in the auditory cortex of anesthetized rats. This group also found that the responses to the deviant in the oddball sequences were underestimated by a model that incorporates cross-frequency adaptation, suggesting a real surprise response.…”

Section: Discussionmentioning

confidence: 83%

Neurons in Macaque Inferior Temporal Cortex Show No Surprise Response to Deviants in Visual Oddball Sequences

Kaliukhovich

Vogels

2014

Journal of Neuroscience

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Many studies measured neural responses in oddball paradigms, showing a different response to the same stimulus when presented with a low (deviant) compared with a high probability (standard) in a sequence. Such a differential response is manifested in event-related potential studies as the mismatch negativity (MMN) and has been observed in several sensory modalities, including vision. Other studies showed that stimulus repetition suppresses the neural response. It has been suggested that this adaptation effect underlies the smaller responses to the standard compared with the deviant stimulus in oddball sequences. However, the MMN may also reflect the violation of a prediction based on the sequence of standards, i.e., a surprise response. We examined the presence of a surprise response to deviants in visual oddball sequences in macaque (Macaca mulatta) inferior temporal (IT) cortex, a higher-order cortical area. In agreement with visual MMN studies, single-unit IT responses were greater for the deviant than for the standard stimuli. However, single IT neurons showed no greater response to the deviant stimulus in the oddball sequence than to the same stimulus presented with the same probability in a sequence that consisted of many stimuli. LFPs also showed no evidence of a surprise response. These data suggest that stimulus-specific adaptation, without a surprise-related boost of activity to the deviant, underlies the responses in visual oddball sequences even in higher visual cortex. Furthermore, we show that for IT neurons such adaptive mechanisms take into account a relatively short stimulus history, with weaker effects at longer time scales.

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Section: Discussionmentioning

confidence: 83%

Neurons in Macaque Inferior Temporal Cortex Show No Surprise Response to Deviants in Visual Oddball Sequences

Kaliukhovich

Vogels

2014

Journal of Neuroscience

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“…Although the adaptation in narrow frequency channels model presents a simple feedforward mechanism for the generation of SSA from the upstream driving inputs, it has been shown that the model is insufficient to fully account for the properties of SSA seen in primary auditory cortex (A1) (Hershenhoren et al, 2014; Yaron et al, 2012), suggesting that there are also locally generated mechanisms of SSA. In A1, there are a variety of cell types classified broadly into excitatory and inhibitory neurons that form complex cortical circuits which are proposed to enhance SSA (Taaseh et al, 2011).…”

Section: Differential Adaptation Of Specific Populations Of Tuned Neumentioning

confidence: 99%

Rapid Sensory Adaptation Redux: A Circuit Perspective

Whitmire

Stanley

2016

Neuron

122

116

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Summary Adaptation is fundamental to life. All organisms adapt over timescales that span from evolution to generations and lifetimes to moment-by-moment interactions. The nervous system is particularly adept at rapidly adapting to change, and this in fact may be one of its fundamental principles of organization and function. Rapid forms of sensory adaptation have been well-documented across all sensory modalities in a wide range of organisms, yet we do not have a comprehensive understanding of the adaptive cellular mechanisms that ultimately give rise to the corresponding percepts due in part to the complexity of the circuitry. In this Perspective, we aim to build links between adaptation at multiple scales of neural circuitry by investigating the differential adaptation across brain regions and sub-regions and across specific cell-types, for which the explosion of modern tools has just begun to enable. This investigation points to a set of challenges for the field to link functional observations to adaptive properties of the neural circuit that ultimately underlie percepts.

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“…Indeed, computational models based on purely feed-forward connectivity show SSA [4,25,26]. However, these models provide predictions that are inconsistent with some of the experimental data [4,12]. Here we study an alternative mechanism: SSA may arise from the heavily recurrent cortical connectivity and the depression of the local, intracortical synapses in A1 [27].…”

Section: Introductionmentioning

confidence: 98%

“…Although SSA is present in the inferior colliculus [5–7] and the auditory thalamus [8–11], it is mostly confined to the non-lemniscal pathway [8,9] and is thus likely generated de novo in A1, whose major thalamic input is from the lemniscal part of the medial geniculate body. SSA in A1 has true deviance sensitivity: The response to a rare stimulus presented within a sequence composed mostly of the same standard tone (which violates the expectation for yet another repeat of the standard) is larger than the response to the same rare stimulus when presented within a sequence composed of many different tones (that doesn't generate strong expectations for any stimulus) although the level of sensory adaptation in the multi-tone sequence may be lower [4,12,13]. SSA is therefore an appealing test case for linking high-level concepts such as deviance sensitivity with mechanistic models.…”

Section: Introductionmentioning

confidence: 99%

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

Yarden¹,

Nelken²

2017

PLoS Comput Biol

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Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments.

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Intracellular Correlates of Stimulus-Specific Adaptation

Cited by 67 publications

References 42 publications

Neurons in Macaque Inferior Temporal Cortex Show No Surprise Response to Deviants in Visual Oddball Sequences

Neurons in Macaque Inferior Temporal Cortex Show No Surprise Response to Deviants in Visual Oddball Sequences

Rapid Sensory Adaptation Redux: A Circuit Perspective

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

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