Context-Dependent Inhibitory Control of Stimulus-Specific Adaptation

Inter and intralaminar excitation of parvalbumin interneurons in mouse barrel cortex

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition and control rhythmic activity. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes in many L2/3 and L4 PV interneurons simultaneously, with stimulation applied to either L2/3 or L4. A semi-automated procedure was developed to identify small regions of interest corresponding to single responsive PV interneurons. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus, PV interneurons in different cortical layers of BC respond in a layer specific and input specific manner, and these differences have potential roles in cortical computations.

Concurrent Encoding of Sequence Predictability and Event-Evoked Prediction Error in Unfolding Auditory Patterns

Human listeners possess an innate capacity to discern patterns within rapidly unfolding sensory input. Core questions, guiding ongoing research, focus on the mechanisms through which these representations are acquired and whether the brain prioritizes or suppresses predictable sensory signals. Previous work, using fast auditory sequences (tone-pips presented at a rate of 20 Hz), revealed sustained response effects that appear to track the dynamic predictability of the sequence. Here, we extend the investigation to slower sequences (4 Hz), permitting the isolation of responses to individual tones. Stimuli were 50 ms tone-pips, ordered into random (RND) and regular (REG; a repeating pattern of 10 frequencies) sequences; Two timing profiles were created: in "fast" sequences, tone-pips were presented in direct succession (20 Hz); in "slow" sequences, tone-pips were separated by a 200 ms silent gap (4 Hz). Naive participants (N = 22; both sexes) passively listened to these sequences, while brain responses were recorded using magnetoencephalography (MEG). Results unveiled a heightened magnitude of sustained brain responses in REG when compared to RND patterns. This manifested from three tones after the onset of the pattern repetition, even in the context of slower sequences characterized by extended pattern durations (2,500 ms). This observation underscores the remarkable implicit sensitivity of the auditory brain to acoustic regularities. Importantly, brain responses evoked by single tones exhibited the opposite pattern-stronger responses to tones in RND than REG sequences. The demonstration of simultaneous but opposing sustained and evoked response effects reveals concurrent processes that shape the representation of unfolding auditory patterns.

Acetylcholine modulates the precision of prediction error in the auditory cortex

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

Sequential maturation of stimulus-specific adaptation in the mouse lemniscal auditory system

Stimulus-specific adaptation (SSA), the reduction of neural activity to a common stimulus that does not generalize to other, rare stimuli, is an essential property of our brain. Although well characterized in adults, it is still unknown how it develops during adolescence and what neuronal circuits are involved. Using in vivo electrophysiology and optogenetics in the lemniscal pathway of the mouse auditory system, we observed SSA to be stable from postnatal day 20 (P20) in the inferior colliculus, to develop until P30 in the auditory thalamus and even later in the primary auditory cortex (A1). We found this maturation process to be experience-dependent in A1 but not in thalamus and to be related to alterations in deep but not input layers of A1. We also identified corticothalamic projections to be implicated in thalamic SSA development. Together, our results reveal different circuits underlying the sequential SSA maturation and provide a unique perspective to understand predictive coding and surprise across sensory systems.

A sparse code for natural sound context in auditory cortex

Accurate sound perception can require integrating information over hundreds of milliseconds or even seconds. Spectro-temporal models of sound coding by single neurons in auditory cortex indicate that the majority of sound-evoked activity can be attributed to stimuli with a few tens of milliseconds. It remains uncertain how the auditory system integrates information about sensory context on a longer timescale. Here we characterized long-lasting contextual effects in auditory cortex (AC) using a diverse set of natural sound stimuli. We measured context effects as the difference in a neuron's response to a single probe sound following two different context sounds. Many AC neurons showed context effects lasting longer than the temporal window of a traditional spectro-temporal receptive field. The duration and magnitude of context effects varied substantially across neurons and stimuli. This diversity of context effects formed a sparse code across the neural population that encoded a wider range of contexts than any constituent neuron. Encoding model analysis indicates that context effects can be explained by activity in the local neural population, suggesting that recurrent local circuits support a long-lasting representation of sensory context in 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.

Input-specific synaptic depression shapes temporal integration in mouse visual cortex

Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.

Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks

Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD.

Inter and Intralaminar Excitation of Parvalbumin Interneurons in Mouse Barrel Cortex

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition, control rhythmic activity, and have been linked to disorders including autism spectrum and schizophrenia. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes simultaneously in many L2/3 and L4 PV interneurons to stimulation in either L2/3 or L4. Decay-times were consistent across L2/3 and L4. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus PV interneurons in different cortical layers of BC show differences in response properties with potential roles in cortical computations.

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.

Adaptation in auditory processing

Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recurring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by continually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the auditory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adaptation to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.

Plasticity in auditory cortex during parenthood

Most animals display robust parental behaviors that support the survival and well-being of their offspring. The manifestation of parental behaviors is accompanied by physiological and hormonal changes, which affect both the body and the brain for better care giving. Rodents exhibit a behavior called pup retrieval - a stereotyped sequence of perception and action - used to identify and retrieve their newborn pups back to the nest. Pup retrieval consists of a significant auditory component, which depends on plasticity in the auditory cortex (ACx). We review the evidence of neural changes taking place in the ACx of rodents during the transition to parenthood. We discuss how the plastic changes both in and out of the ACx support the encoding of pup vocalizations. Key players in the mechanism of this plasticity are hormones and experience, both of which have a clear dynamic signature during the transition to parenthood. Mothers, co caring females, and fathers have been used as models to understand parental plasticity at disparate levels of organization. Yet, common principles of cortical plasticity and the biological mechanisms underlying its involvement in parental behavior are just beginning to be unpacked.

The local and long-range input landscape of inhibitory neurons in mouse auditory cortex

Roughly 20% of the neurons in the mouse cortex are inhibitory interneurons (INs). Of these, the three major subtypes are parvalbumin (PV), somatostatin (SST), and vasoactive intestinal polypeptide (VIP) expressing neurons. We used monosynaptic rabies tracing to compare the presynaptic input landscape onto these three IN subtypes in the mouse primary auditory cortex (A1). We compared both local patterns of monosynaptic inputs as well as long-range input patterns. The local monosynaptic input landscape to SST neurons was more widespread as compared to PV and VIP neurons. The brain-wide input landscape was rich and heterogeneous with >40 brain regions connecting to all the three INs subtypes from both hemispheres. The general pattern of the long-range input landscape was similar among the groups of INs. Nevertheless, a few differences could be identified. At low resolution, the proportion of local versus long-range inputs was smaller for PV neurons. At mesoscale resolution, we found fewer inputs from temporal association area to VIP INs, and more inputs to SST neurons from basal forebrain and lateral amygdala. Our work can be used as a resource for a quantitative comparison of the location and level of inputs impinging onto discrete populations of neurons in mouse A1.

Auditory memory of complex sounds in sparsely distributed, highly correlated neurons in the auditory cortex

Listening in complex sound environments requires rapid segregation of different sound sources e.g., speakers from each other, speakers from other sounds, or different instruments in an orchestra, and also adjust auditory processing on the prevailing sound conditions. Thus, fast encoding of inputs and identifying and adapting to reoccurring sounds are necessary for efficient and agile sound perception. This adaptation process represents an early phase of developing implicit learning of sound statistics and thus represents a form of auditory memory. The auditory cortex (ACtx) is known to play a key role in this encoding process but the underlying circuits and if hierarchical processing exists are not known. To identify ACtx regions and cells involved in this process, we simultaneously imaged population of neurons in different ACtx subfields using in vivo 2-photon imaging in awake mice. We used an experimental stimulus paradigm adapted from human studies that triggers rapid and robust implicit learning to passively present complex sounds and imaged A1 Layer 4 (L4), A1 L2/3, and A2 L2/3. In this paradigm, a frozen spectro-temporally complex 'Target' sound would be randomly re-occurring within a stream of random other complex sounds. We find distinct groups of cells that are specifically responsive to complex acoustic sequences across all subregions indicating that even the initial thalamocortical input layers (A1 L4) respond to complex sounds. Cells in all imaged regions showed decreased response amplitude for reoccurring Target sounds indicating that a memory signature is present even in the thalamocortical input layers. On the population level we find increased synchronized activity across cells to the Target sound and that this synchronized activity was more consistent across cells regardless of the duration of frozen token within Target sounds in A2, compared to A1. These findings suggest that ACtx and its input layers play a role in auditory memory for complex sounds and suggest a hierarchical structure of processes for auditory memory.

Auditory representations for long lasting sounds: Insights from event-related brain potentials and neural oscillations

The basic features of short sounds, such as frequency and intensity including their temporal dynamics, are integrated in a unitary representation. Knowledge on how our brain processes long lasting sounds is scarce. We review research utilizing the Mismatch Negativity event-related potential and neural oscillatory activity for studying representations for long lasting simple versus complex sounds such as sinusoidal tones versus speech. There is evidence for a temporal constraint in the formation of auditory representations: Auditory edges like sound onsets within long lasting sounds open a temporal window of about 350 ms in which the sounds' dynamics are integrated into a representation, while information beyond that window contributes less to that representation. This integration window segments the auditory input into short chunks. We argue that the representations established in adjacent integration windows can be concatenated into an auditory representation of a long sound, thus, overcoming the temporal constraint.