Evoked Response Strength in Primary Auditory Cortex Predicts Performance in a Spectro-Spatial Discrimination Task in Rats

Neural correlates of novelty detection in the primary auditory cortex of behaving monkeys

The neural mechanisms underlying novelty detection are not well understood, especially in relation to behavior. Here, we present single-unit responses from the primary auditory cortex (A1) from two monkeys trained to detect deviant tones amid repetitive ones. Results show that monkeys can detect deviant sounds, and there is a strong correlation between late neuronal responses (250-350 ms after deviant onset) and the monkeys' perceptual decisions. The magnitude and timing of both neuronal and behavioral responses are increased by larger frequency differences between the deviant and standard tones and by increasing the number of standard tones preceding the deviant. This suggests that A1 neurons encode novelty detection in behaving monkeys, influenced by stimulus relevance and expectations. This study provides evidence supporting aspects of predictive coding in the sensory cortex.

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative-choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in the auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that, in spite of modulation of auditory cortical activity by task priors, the auditory cortex does not represent sufficient information about these priors to exploit them optimally. Thus, the combination of rapidly changing sensory information with more slowly varying task information required for decisions in this task might be represented in brain regions other than the auditory cortex.

Novelty detection in an auditory oddball task on freely moving rats

The relative importance or saliency of sensory inputs depend on the animal's environmental context and the behavioural responses to these same inputs can vary over time. Here we show how freely moving rats, trained to discriminate between deviant tones embedded in a regular pattern of repeating stimuli and different variations of the classic oddball paradigm, can detect deviant tones, and this discriminability resembles the properties that are typical of neuronal adaptation described in previous studies. Moreover, the auditory brainstem response (ABR) latency decreases after training, a finding consistent with the notion that animals develop a type of plasticity to auditory stimuli. Our study suggests the existence of a form of long-term memory that may modulate the level of neuronal adaptation according to its behavioural relevance, and sets the ground for future experiments that will help to disentangle the functional mechanisms that govern behavioural habituation and its relation to neuronal adaptation.

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that in spite of modulation of auditory cortical activity by task priors, auditory cortex does not represent sufficient information about these priors to exploit them optimally and that decisions in this task require that rapidly changing sensory information be combined with more slowly varying task information extracted and represented in brain regions other than auditory cortex.

An automated, low-latency environment for studying the neural basis of behavior in freely moving rats

BACKGROUND

Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes).

RESULTS

To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle.

CONCLUSIONS

The RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.

Stimulus-Specific Adaptation (SSA) in the Auditory System: Functional Relevance and Underlying Mechanisms

Rapid detection of novel stimuli that appear suddenly in the surrounding environment is crucial for an animal's survival. Stimulus-specific adaptation (SSA) may be an important mechanism underlying novelty detection. In this review, we discuss the latest advances in SSA research by addressing four main aspects: 1) the frequency dependence of SSA and the origin of SSA in the auditory cortex: 2) spatial SSA and its comparison with frequency SSA: 3) feature integration in SSA and its implications in novelty detection: 4) functional significance and the physiological mechanism of SSA. Although SSA has been extensively investigated, the cognitive insights from SSA studies are extremely limited. Future work should aim to bridge these gaps.

Choice-related activity and neural encoding in primary auditory cortex and lateral belt during feature-selective attention

Selective attention is necessary to sift through, form a coherent percept of, and make behavioral decisions on the vast amount of information present in most sensory environments. How and where selective attention is employed in cortex and how this perceptual information then informs the relevant behavioral decisions is still not well understood. Studies probing selective attention and decision-making in visual cortex have been enlightening as to how sensory attention might work in that modality; whether or not similar mechanisms are employed in auditory attention is not yet clear. Therefore, we trained rhesus macaques on a feature-selective attention task, where they switched between reporting changes in temporal (amplitude modulation, AM) and spectral (carrier bandwidth) features of a broadband noise stimulus. We investigated how the encoding of these features by single neurons in primary (A1) and secondary (middle lateral belt, ML) auditory cortex was affected by the different attention conditions. We found that neurons in A1 and ML showed mixed selectivity to the sound and task features. We found no difference in AM encoding between the attention conditions. We found that choice-related activity in both A1 and ML neurons shifts between attentional conditions. This finding suggests that choice-related activity in auditory cortex does not simply reflect motor preparation or action and supports the relationship between reported choice-related activity and the decision and perceptual process.NEW & NOTEWORTHY We recorded from primary and secondary auditory cortex while monkeys performed a nonspatial feature attention task. Both areas exhibited rate-based choice-related activity. The manifestation of choice-related activity was attention dependent, suggesting that choice-related activity in auditory cortex does not simply reflect arousal or motor influences but relates to the specific perceptual choice.

Spectral plasticity in monkey primary auditory cortex limits performance generalization in a temporal discrimination task

Auditory experience and behavioral training can modify perceptual performance. However, the consequences of temporal perceptual learning for temporal and spectral neural processing remain unclear. Specifically, the attributes of neural plasticity that underlie task generalization in behavioral performance remain uncertain. To assess the relationship between behavioral and neural plasticity, we evaluated neuronal temporal processing and spectral tuning in primary auditory cortex (AI) of anesthetized owl monkeys trained to discriminate increases in the envelope frequency (e.g., 4-Hz standard vs. >5-Hz targets) of sinusoidally amplitude-modulated (SAM) 1-kHz or 2-kHz carriers. Behavioral and neuronal performance generalization was evaluated for carriers ranging from 0.5 kHz to 8 kHz. Psychophysical thresholds revealed high SAM discrimination acuity for carriers from one octave below to ∼0.6 octave above the trained carrier frequency. However, generalization of SAM discrimination learning progressively declined for carrier frequencies >0.6 octave above the trained carrier frequency. Neural responses in AI showed that SAM discrimination training resulted in 1) increases in temporal modulation preference, especially at carriers close to the trained frequency, 2) narrowing of spectral tuning for neurons with characteristic frequencies near the trained carrier frequency, potentially limiting spectral generalization of temporal training effects, and 3) enhancement of firing-rate contrast for rewarded versus nonrewarded SAM frequencies, providing a potential cue for behavioral temporal discrimination near the trained carrier frequency. Our findings suggest that temporal training at a specific spectral location sharpens local frequency tuning, thus, confining the training effects to a narrow frequency range and limiting generalization of temporal discrimination learning across a wider frequency range.NEW & NOTEWORTHY Monkeys' ability to generalize amplitude modulation discrimination to nontrained carriers was limited to one octave below and 0.6 octave above the trained carrier frequency. Asymmetric generalization was paralleled by sharpening in cortical spectral tuning and enhanced firing-rate contrast between rewarded and nonrewarded SAM stimuli at carriers near the trained frequency. The spectral content of the training stimulus specified spectral and temporal plasticity that may provide a neural substrate for limitations in generalization of temporal discrimination learning.