Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells

Cross-modal enhancement of defensive behavior via parabigemino-collicular projections

Effective detection and avoidance from environmental threats are crucial for animals' survival. Integration of sensory cues associated with threats across different modalities can significantly enhance animals' detection and behavioral responses. However, the neural circuit-level mechanisms underlying the modulation of defensive behavior or fear response under simultaneous multimodal sensory inputs remain poorly understood. Here, we report in mice that bimodal looming stimuli combining coherent visual and auditory signals elicit more robust defensive/fear reactions than unimodal stimuli. These include intensified escape and prolonged hiding, suggesting a heightened defensive/fear state. These various responses depend on the activity of the superior colliculus (SC), while its downstream nucleus, the parabigeminal nucleus (PBG), predominantly influences the duration of hiding behavior. PBG temporally integrates visual and auditory signals and enhances the salience of threat signals by amplifying SC sensory responses through its feedback projection to the visual layer of the SC. Our results suggest an evolutionarily conserved pathway in defense circuits for multisensory integration and cross-modality enhancement.

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

Effects of neural oscillation power and phase on discrimination performance in a visual tilt illusion

Neural oscillations reflect fluctuations in the relative excitation/inhibition of neural systems1,2,3,4,5 and are theorized to play a critical role in canonical neural computations6,7,8,9 and cognitive processes.10,11,12,13,14 These theories have been supported by findings that detection of visual stimuli fluctuates with the phase of oscillations prior to stimulus onset.15,16,17,18,19,20,21,22,23 However, null results have emerged in studies seeking to demonstrate these effects in visual discrimination tasks,24,25,26,27 raising questions about the generalizability of these phenomena to wider neural processes. Recently, we suggested that methodological limitations may mask effects of phase in higher-level sensory processing.28 To test the generality of phasic influences on perception requires a task that involves stimulus discrimination while also depending on early sensory processing. Here, we examined the influence of oscillation phase on the visual tilt illusion, in which a center grating has its perceived orientation biased away from the orientation of a surround grating29 due to lateral inhibitory interactions in early visual processing.30,31,32 We presented center gratings at participants' subjective vertical angle and had participants report whether the grating appeared tilted clockwise or counterclockwise from vertical on each trial while measuring their brain activity with electroencephalography (EEG). In addition to effects of alpha power and aperiodic slope, we observed robust associations between orientation perception and alpha and theta phase, consistent with fluctuating illusion magnitude across the oscillatory cycle. These results confirm that oscillation phase affects the complex processing involved in stimulus discrimination, consistent with its purported role in canonical computations that underpin cognition.

Functional specificity of recurrent inhibition in visual cortex

In the neocortex, neural activity is shaped by the interaction of excitatory and inhibitory neurons, defined by the organization of their synaptic connections. Although connections among excitatory pyramidal neurons are sparse and functionally tuned, inhibitory connectivity is thought to be dense and largely unstructured. By measuring in vivo visual responses and synaptic connectivity of parvalbumin-expressing (PV+) inhibitory cells in mouse primary visual cortex, we show that the synaptic weights of their connections to nearby pyramidal neurons are specifically tuned according to the similarity of the cells' responses. Individual PV+ cells strongly inhibit those pyramidal cells that provide them with strong excitation and share their visual selectivity. This structured organization of inhibitory synaptic weights provides a circuit mechanism for tuned inhibition onto pyramidal cells despite dense connectivity, stabilizing activity within feature-specific excitatory ensembles while supporting competition between them.

Bidirectional Regulation of GABAA Reversal Potential in the Adult Brain: Physiological and Pathological Implications

In physiological conditions, the intracellular chloride concentration is much lower than the extracellular. As GABAA channels are permeable to anions, the reversal potential of GABAA is very close to that of Cl-, which is the most abundant free anion in the intra- and extracellular spaces. Intracellular chloride is regulated by the activity ratio of NKCC1 and KCC2, two chloride-cation cotransporters that import and export Cl-, respectively. Due to the closeness between GABAA reversal potential and the value of the resting membrane potential in most neurons, small changes in intracellular chloride have a major functional impact, which makes GABAA a uniquely flexible signaling system. In most neurons of the adult brain, the GABAA reversal potential is slightly more negative than the resting membrane potential, which makes GABAA hyperpolarizing. Alterations in GABAA reversal potential are a common feature in numerous conditions as they are the consequence of an imbalance in the NKCC1-KCC2 activity ratio. In most conditions (including Alzheimer's disease, schizophrenia, and Down's syndrome), GABAA becomes depolarizing, which causes network desynchronization and behavioral impairment. In other conditions (neonatal inflammation and neuropathic pain), however, GABAA reversal potential becomes hypernegative, which affects behavior through a potent circuit deactivation.

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.

Learning shapes cortical dynamics to enhance integration of relevant sensory input

Adaptive sensory behavior is thought to depend on processing in recurrent cortical circuits, but how dynamics in these circuits shapes the integration and transmission of sensory information is not well understood. Here, we study neural coding in recurrently connected networks of neurons driven by sensory input. We show analytically how information available in the network output varies with the alignment between feedforward input and the integrating modes of the circuit dynamics. In light of this theory, we analyzed neural population activity in the visual cortex of mice that learned to discriminate visual features. We found that over learning, slow patterns of network dynamics realigned to better integrate input relevant to the discrimination task. This realignment of network dynamics could be explained by changes in excitatory-inhibitory connectivity among neurons tuned to relevant features. These results suggest that learning tunes the temporal dynamics of cortical circuits to optimally integrate relevant sensory input.

Spatiotemporal patterns of population response in the visual cortex under isoflurane: from wakefulness to loss of consciousness

Anesthetic drugs are widely used in medicine and research to mediate loss of consciousness (LOC). Isoflurane is a commonly used anesthetic drug; however, its effects on cortical sensory processing, in particular around LOC, are not well understood. Using voltage-sensitive dye imaging, we measured visually evoked neuronal population response from the visual cortex in awake and anesthetized mice at 3 increasing concentrations of isoflurane, thus controlling the level of anesthesia from wakefulness to deep anesthesia. At low concentration of isoflurane, the effects on neuronal measures were minor relative to the awake condition. These effects augmented with increasing isoflurane concentration, while around LOC point, they showed abrupt and nonlinear changes. At the network level, we found that isoflurane decreased the stimulus-evoked intra-areal spatial spread of local neural activation, previously reported to be mediated by horizontal connections, and also reduced intra-areal synchronization of neuronal population. The synchronization between different visual areas decreased with higher isoflurane levels. Isoflurane reduced the population response amplitude and prolonged their latencies while higher visual areas showed increased vulnerability to isoflurane concentration. Our results uncover the changes in neural activity and synchronization at isoflurane concentrations leading to LOC and suggest reverse hierarchical shutdown of cortical areas.

A brainstem map for visceral sensations

The nervous system uses various coding strategies to process sensory inputs. For example, the olfactory system uses large receptor repertoires and is wired to recognize diverse odours, whereas the visual system provides high acuity of object position, form and movement^1-5. Compared to external sensory systems, principles that underlie sensory processing by the interoceptive nervous system remain poorly defined. Here we developed a two-photon calcium imaging preparation to understand internal organ representations in the nucleus of the solitary tract (NTS), a sensory gateway in the brainstem that receives vagal and other inputs from the body. Focusing on gut and upper airway stimuli, we observed that individual NTS neurons are tuned to detect signals from particular organs and are topographically organized on the basis of body position. Moreover, some mechanosensory and chemosensory inputs from the same organ converge centrally. Sensory inputs engage specific NTS domains with defined locations, each containing heterogeneous cell types. Spatial representations of different organs are further sharpened in the NTS beyond what is achieved by vagal axon sorting alone, as blockade of brainstem inhibition broadens neural tuning and disorganizes visceral representations. These findings reveal basic organizational features used by the brain to process interoceptive inputs.

Urethane Improves the Response of Auditory Neurons to Tone

Urethane has little effect on nervous system and is often used in neuroscience studies. However, the effect of urethane in neurons is not thoroughly clear. In this study, we investigated changes in neuron responses to tones in inferior colliculus during urethane anesthesia. As urethane was metabolized, the best and characteristic frequencies did not obviously change, but the minimal threshold (MT) remained relatively stable or was elevated. The frequency tuning bandwidth at 60 dB SPL (BW_60dBSPL) remained unchanged or decreased, and the average evoked spike of effective frequencies at 60 dB SPL (ES_60dBSPL) gradually decreased. Although the average evoked spike of effective frequencies at a tone intensity of 20 dB SPL above MT (ES_{20dBSPLaboveMT}) decreased, the frequency tuning bandwidth at a tone intensity of 20 dB SPL above MT (BW_{20dBSPLaboveMT}) did not change. In addition, the changes in MT, ES_60dBSPL, BW_60dBSPL, and ES_{20dBSPLaboveMT} increased with the MT in pre-anesthesia awake state (MT_{pre−anesthesiaawake}). In some neurons, the MT was lower, BW_60dBSPL was broader, and ES_60dBSPL and ES_{20dBSPLaboveMT} were higher in urethane anesthesia state than in pre-anesthesia awake state. During anesthesia, the inhibitory effect of urethane reduced the ES_{20dBSPLaboveMT}, but did not change the MT, characteristic frequency, or BW_{20dBSPLaboveMT}. In the recording session with the strongest neuron response, the first spike latency did not decrease, and the spontaneous spike did not increase. Therefore, we conclude that urethane can reduce/not change the MT, increase the evoked spike, or broaden/not change the frequency tuning range, and eventually improve the response of auditory neurons to tone with or without “pushing down” the tonal receptive field in thresholding model. The improved effect increases with the MT_{pre−anesthesiaawake} of neurons. The changes induced by the inhibitory and improved effects of urethane abide by similar regularities, but the change directions are contrary. The improvement mechanism may be likely due to the increase in the ratio of excitatory/inhibitory postsynaptic inputs to neurons.

Neocortex saves energy by reducing coding precision during food scarcity

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy use are regulated during food scarcity. Using whole-cell recordings and two-photon imaging in layer 2/3 mouse visual cortex, we found that food restriction reduced AMPA receptor conductance, reducing synaptic ATP use by 29%. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting potential. Consequently, neurons spiked at similar rates as controls but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost because it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening of orientation tuning and impaired fine visual discrimination. This reduction in coding precision was associated with reduced levels of the fat mass-regulated hormone leptin and was restored by exogenous leptin supplementation. Our findings reveal that metabolic state dynamically regulates the energy spent on coding precision in neocortex.

Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network.

Synaptic plasticity is crucial for the development of efficient input representation in the different sensory cortices, such as the primary visual cortex. Efficient visual representation is determined by two factors: representational efficiency, i.e. how many different input features can be represented, and metabolic efficiency, i.e. how many spikes are required to represent a specific feature. Previous research has pointed out the importance of plasticity at excitatory synapses to achieve high representational efficiency and feedback inhibition as a gain control mechanism for controlling metabolic efficiency. However, it is only partially understood how the influence of inhibitory plasticity on excitatory plasticity can lead to an efficient representation. Using a spiking neural network, we show that plasticity at feed-forward and feedback inhibitory synapses is necessary for the emergence of well-distributed neuronal selectivity to improve representational efficiency. Further, the emergent balance between excitatory and inhibitory currents improves the metabolic efficiency, and leads to contrast-invariant tuning as an inherent network property. Extending previous work, our simulation results highlight the importance of plasticity at inhibitory synapses.

Schizophrenia risk-gene Crmp2 deficiency causes precocious critical period plasticity and deteriorated binocular vision

Brain-specific loss of a microtubule-binding protein collapsin response mediator protein-2 (CRMP2) in the mouse recapitulates many schizophrenia-like behaviors of human patients, possibly resulting from associated developmental deficits in neuronal differentiation, path-finding, and synapse formation. However, it is still unclear how the Crmp2 loss affects neuronal circuit function and plasticity. By conducting in vivo and ex vivo electrophysiological recording in the mouse primary visual cortex (V1), we reveal that CRMP2 exerts a key regulation on the timing of postnatal critical period (CP) for experience-dependent circuit plasticity of sensory cortex. In the developing V1, the Crmp2 deficiency induces not only a delayed maturation of visual tuning functions but also a precocious CP for visual input-induced ocular dominance plasticity and its induction activity - coincident binocular inputs right after eye-opening. Mechanistically, the Crmp2 deficiency accelerates the maturation process of cortical inhibitory transmission and subsequently promotes an early emergence of balanced excitatory-inhibitory cortical circuits during the postnatal development. Moreover, the precocious CP plasticity results in deteriorated binocular depth perception in adulthood. Thus, these findings suggest that the Crmp2 deficiency dysregulates the timing of CP for experience-dependent refinement of circuit connections and further leads to impaired sensory perception in later life.

Modality-Specific Modulation of Temperature Representations in the Spinal Cord after Injury

Different types of tissue injury, such as inflammatory and neuropathic conditions, cause modality-specific alternations on temperature perception. There are profound changes in peripheral sensory neurons after injury, but how patterned neuronal activities in the CNS encode injury-induced sensitization to temperature stimuli is largely unknown. Using in vivo calcium imaging and mouse genetics, we show that formalin- and prostaglandin E2-induced inflammation dramatically increase spinal responses to heating and decrease responses to cooling in male and female mice. The reduction of cold response is largely eliminated on ablation of TRPV1-expressing primary sensory neurons, indicating a crossover inhibition of cold response from the hyperactive heat inputs in the spinal cord. Interestingly, chemotherapy medication oxaliplatin can rapidly increase spinal responses to cooling and suppress responses to heating. Together, our results suggest a push-pull mechanism in processing cold and heat inputs and reveal a synergic mechanism to shift thermosensation after injury.SIGNIFICANCE STATEMENT In this paper, we combine our novel in vivo spinal cord two-photon calcium imaging, mouse genetics, and persistent pain models to study how tissue injury alters the sensation of temperature. We discover modality-specific changes of spinal temperature responses in different models of injury. Chemotherapy medication oxaliplatin leads to cold hypersensitivity and heat hyposensitivity. By contrast, inflammation increases heat sensitivity and decreases cold sensitivity. This decrease in cold sensitivity results from the stronger crossover inhibition from the hyperactive heat inputs. Our work reveals the bidirectional change of thermosensitivity by injury and suggests that the crossover inhibitory circuit underlies the shifted thermosensation, providing a mechanism to the biased perception toward a unique thermal modality that was observed clinically in chronic pain patients.

Restoration of Visual Function and Cortical Connectivity After Ischemic Injury Through NeuroD1-Mediated Gene Therapy

Neural circuits underlying brain functions are vulnerable to damage, including ischemic injury, leading to neuronal loss and gliosis. Recent technology of direct conversion of endogenous astrocytes into neurons in situ can simultaneously replenish the neuronal population and reverse the glial scar. However, whether these newly reprogrammed neurons undergo normal development, integrate into the existing neuronal circuit, and acquire functional properties specific for this circuit is not known. We investigated the effect of NeuroD1-mediated in vivo direct reprogramming on visual cortical circuit integration and functional recovery in a mouse model of ischemic injury. After performing electrophysiological extracellular recordings and two-photon calcium imaging of reprogrammed cells in vivo and mapping the synaptic connections formed onto these cells ex vivo, we discovered that NeuroD1 reprogrammed neurons were integrated into the cortical microcircuit and acquired direct visual responses. Furthermore, following visual experience, the reprogrammed neurons demonstrated maturation of orientation selectivity and functional connectivity. Our results show that NeuroD1-reprogrammed neurons can successfully develop and integrate into the visual cortical circuit leading to vision recovery after ischemic injury.

The role of early visual experience in the development of spatial-frequency preference in the primary visual cortex

KEY POINTS

The mature functioning of the primary visual cortex depends on postnatal visual experience, while the orientation/direction preference is established just after eye-opening, independently of visual experience. In this study, we find that visual experience is required for the normal development of spatial-frequency (SF) preference in mouse primary visual cortex. We show that age- and experience-dependent shifts in optimal SFs towards higher frequencies occurred similarly in excitatory neurons and parvalbumin-positive interneurons. We also show that some excitatory and parvalbumin-positive neurons preferentially responded to visual stimuli consisting of very high SFs and posterior directions, and that the preference was established at earlier developmental stages than the SF preference in the standard frequency range. These results suggest that early visual experience is required for the development of SF representation and shed light on the experience-dependent developmental mechanisms underlying visual cortical functions.

ABSTRACT

Early visual experience is crucial for the maturation of visual cortical functions. It has been demonstrated that the orientation and direction preferences in individual neurons of the primary visual cortex are well established immediately after eye-opening. The postnatal development of spatial frequency (SF) tuning and its dependence on visual experience, however, has not been thoroughly quantified. In this study, macroscopic imaging with flavoprotein autofluorescence revealed that the optimal SFs shift towards higher frequency values during normal development in mouse primary visual cortex. This developmental shift was impaired by binocular deprivation during the sensitive period, postnatal 3 weeks (PW3) to PW6. Furthermore, two-photon Ca²⁺ imaging revealed that the developmental shift of the optimal SFs, depending on visual experience, concurrently occurs in excitatory neurons and parvalbumin-positive inhibitory interneurons (PV neurons). In addition, some excitatory and PV neurons exhibited a preference for visual stimuli consisting of particularly high SFs and posterior directions at relatively early developmental stages; this preference was not affected by binocular deprivation. Thus, there may be two distinct developmental mechanisms for the establishment of SF preference depending on the frequency values. After PW3, SF tuning for neurons tuned to standard frequency ranges was sharper in excitatory neurons and slightly broader in PV neurons, leading to considerably attenuated SF tuning in PV neurons compared to excitatory neurons by PW5. Our findings suggest that early visual experience is far more important than orientation/direction selectivity for the development of the neural representation of the diverse SFs.

How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model

The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.

Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions

Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model of peripheral lesioning and accurately reproduced the characteristics of network repair after deafferentation that are reported in experiments to study the activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed structural plasticity growth rules and the inhibitory synaptic plasticity mechanism that also balances our AI network both contribute to the restoration of the network to pre-deafferentation stable activity levels.

An accumulating body of evidence suggests that our brain can compensate for peripheral lesions by adaptive rewiring of its neuronal circuitry. The underlying process, structural plasticity, can modify the connectivity of neuronal networks in the brain, thus affecting their function. To better understand the mechanisms of structural plasticity in the brain, we have developed a novel model of peripheral lesions and the resulting activity-dependent rewiring in a simplified balanced cortical network model that exhibits biologically realistic Asynchronous Irregular (AI) activity. In order to accurately reproduce the directionality and course of network rewiring after injury that is observed in peripheral lesion experiments, we derive activity dependent growth rules for different synaptic elements: dendritic and axonal contacts. Our simulation results suggest that excitatory and inhibitory synaptic elements have to react to changes in neuronal activity in opposite ways. We show that these rules result in a homeostatic stabilisation of activity in individual neurons. In our simulations, both synaptic and structural plasticity mechanisms contribute to network repair. Furthermore, our simulations indicate that while activity is restored in neurons deprived by the peripheral lesion, the temporal firing characteristics of the network may not be retained by the rewiring process.

Assessment of optogenetically-driven strategies for prosthetic restoration of cortical vision in large-scale neural simulation of V1

The neural encoding of visual features in primary visual cortex (V1) is well understood, with strong correlates to low-level perception, making V1 a strong candidate for vision restoration through neuroprosthetics. However, the functional relevance of neural dynamics evoked through external stimulation directly imposed at the cortical level is poorly understood. Furthermore, protocols for designing cortical stimulation patterns that would induce a naturalistic perception of the encoded stimuli have not yet been established. Here, we demonstrate a proof of concept by solving these issues through a computational model, combining (1) a large-scale spiking neural network model of cat V1 and (2) a virtual prosthetic system transcoding the visual input into tailored light-stimulation patterns which drive in situ the optogenetically modified cortical tissue. Using such virtual experiments, we design a protocol for translating simple Fourier contrasted stimuli (gratings) into activation patterns of the optogenetic matrix stimulator. We then quantify the relationship between spatial configuration of the imposed light pattern and the induced cortical activity. Our simulations in the absence of visual drive (simulated blindness) show that optogenetic stimulation with a spatial resolution as low as 100 [Formula: see text]m, and light intensity as weak as [Formula: see text] photons/s/cm[Formula: see text] is sufficient to evoke activity patterns in V1 close to those evoked by normal vision.

Multidimensional population activity in an electrically coupled inhibitory circuit in the cerebellar cortex

Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (<1 s) differential population activity, arising from spatially mixed heterogeneous GoC responses, encodes more precise information. A biologically detailed GoC circuit model reproduced the common population mode and the dimensionality observed experimentally, but these properties disappeared when electrical coupling was removed. Our results establish that local GoC circuits exhibit multidimensional activity patterns that could be used for inhibition-mediated adaptive gain control and spatiotemporal patterning of downstream granule cells.

Action-dependent processing of self-motion in parietal cortex of macaque monkeys

Successful interaction with the environment requires the dissociation of self-induced from externally induced sensory stimulation. Temporal proximity of action and effect is hereby often used as an indicator of whether an observed event should be interpreted as a result of own actions or not. We tested how the delay between an action (press of a touch bar) and an effect (onset of simulated self-motion) influences the processing of visually simulated self-motion in the ventral intraparietal area (VIP) of macaque monkeys. We found that a delay between the action and the start of the self-motion stimulus led to a rise of activity above the baseline activity before motion onset in a subpopulation of 21% of the investigated neurons. In the responses to the stimulus, we found a significantly lower sustained activity when the press of a touch bar and the motion onset were contiguous compared to the condition when the motion onset was delayed. We speculate that this weak inhibitory effect might be part of a mechanism that sharpens the tuning of VIP neurons during self-induced motion and thus has the potential to increase the precision of heading information that is required to adjust the orientation of self-motion in everyday navigational tasks.NEW & NOTEWORTHY Neurons in macaque ventral intraparietal area (VIP) are responding to sensory stimulation related to self-motion, e.g. visual optic flow. Here, we found that self-motion induced activation depends on the sense of agency, i.e., it differed when optic flow was perceived as self- or externally induced. This demonstrates that area VIP is well suited for study of the interplay between active behavior and sensory processing during self-motion.

Scaling of Network Excitability and Inhibition may Contribute to the Septotemporal Differentiation of Sharp Waves-Ripples in Rat Hippocampus In Vitro

The functional organization of the hippocampus along its longitudinal (septotemporal or dorsoventral) axis is conspicuously heterogeneous. This functional diversification includes the activity of sharp wave and ripples (SPW-Rs), a complex intrinsic network pattern involved in memory consolidation. In this study, using transverse slices from the ventral and the dorsal rat hippocampus and recordings of CA1 field potentials we studied the development of SPW-Rs and possible changes in local network excitability and inhibition, during in vitro maintenance of the hippocampal tissue. We found that SPW-Rs develop gradually in terms of magnitude and rate of occurrence in the ventral hippocampus. On the contrary, neither the magnitude nor the rate of occurrence significantly changed in dorsal hippocampal slices during their in vitro maintenance. The development of SPW-Rs was accompanied by an increase in local network excitability more in the ventral than in the dorsal hippocampus, and an increase in local network inhibition in the ventral hippocampus only. Furthermore, the amplitude of SPWs positively correlated with the level of maximum excitation of the local neuronal network in both segments of the hippocampus, and the local network excitability and inhibition in the ventral but not the dorsal hippocampus. Blockade of α5 subunit-containing GABA_A receptor by L-655,708 significantly reduced the rate of occurrence of SPWs and enhanced the probability of their generation in the form of clusters in the ventral hippocampus without affecting activity in the dorsal hippocampus. The present evidence suggests that a dynamic upregulation of excitation and inhibition in the local neuronal network may significantly contribute to the generation of SPW-Rs, particularly in the ventral hippocampus.

Spatial connectivity matches direction selectivity in visual cortex

The selectivity of neuronal responses arises from the architecture of excitatory and inhibitory connections. In the primary visual cortex, the selectivity of a neuron in layer 2/3 for stimulus orientation and direction is thought to arise from intracortical inputs that are similarly selective^1-8. However, the excitatory inputs of a neuron can have diverse stimulus preferences^1-4,6,7,9, and inhibitory inputs can be promiscuous¹⁰ and unselective¹¹. Here we show that the excitatory and inhibitory intracortical connections to a layer 2/3 neuron accord with its selectivity by obeying precise spatial patterns. We used rabies tracing^1,12 to label and functionally image the excitatory and inhibitory inputs to individual pyramidal neurons of layer 2/3 of the mouse visual cortex. Presynaptic excitatory neurons spanned layers 2/3 and 4 and were distributed coaxial to the preferred orientation of the postsynaptic neuron, favouring the region opposite to its preferred direction. By contrast, presynaptic inhibitory neurons resided within layer 2/3 and favoured locations near the postsynaptic neuron and ahead of its preferred direction. The direction selectivity of a postsynaptic neuron was unrelated to the selectivity of presynaptic neurons, but correlated with the spatial displacement between excitatory and inhibitory presynaptic ensembles. Similar asymmetric connectivity establishes direction selectivity in the retina^13-17. This suggests that this circuit motif might be canonical in sensory processing.

Sparse Representation in Awake Auditory Cortex: Cell-type Dependence, Synaptic Mechanisms, Developmental Emergence, and Modulation

Sparse representation is considered an important coding strategy for cortical processing in various sensory modalities. It remains unclear how cortical sparseness arises and is being regulated. Here, unbiased recordings from primary auditory cortex of awake adult mice revealed salient sparseness in layer (L)2/3, with a majority of excitatory neurons exhibiting no increased spiking in response to each of sound types tested. Sparse representation was not observed in parvalbumin (PV) inhibitory neurons. The nonresponding neurons did receive auditory-evoked synaptic inputs, marked by weaker excitation and lower excitation/inhibition (E/I) ratios than responding cells. Sparse representation arises during development in an experience-dependent manner, accompanied by differential changes of excitatory input strength and a transition from unimodal to bimodal distribution of E/I ratios. Sparseness level could be reduced by suppressing PV or L1 inhibitory neurons. Thus, sparse representation may be dynamically regulated via modulating E/I balance, optimizing cortical representation of the external sensory world.

Synaptic Mechanisms for Bandwidth Tuning in Awake Mouse Primary Auditory Cortex

Spatial size tuning in the visual cortex has been considered as an important neuronal functional property for sensory perception. However, an analogous mechanism in the auditory system has remained controversial. In the present study, cell-attached recordings in the primary auditory cortex (A1) of awake mice revealed that excitatory neurons can be categorized into three types according to their bandwidth tuning profiles in response to band-passed noise (BPN) stimuli: nonmonotonic (NM), flat, and monotonic, with the latter two considered as non-tuned for bandwidth. The prevalence of bandwidth-tuned (i.e., NM) neurons increases significantly from layer 4 to layer 2/3. With sequential cell-attached and whole-cell voltage-clamp recordings from the same neurons, we found that the bandwidth preference of excitatory neurons is largely determined by the excitatory synaptic input they receive, and that the bandwidth selectivity is further enhanced by flatly tuned inhibition observed in all cells. The latter can be attributed at least partially to the flat tuning of parvalbumin inhibitory neurons. The tuning of auditory cortical neurons for bandwidth of BPN may contribute to the processing of complex sounds.

Laminar Subnetworks of Response Suppression in Macaque Primary Visual Cortex

Cortical inhibition plays an important role in information processing in the brain. However, the mechanisms by which inhibition and excitation are coordinated to generate functions in the six layers of the cortex remain unclear. Here, we measured laminar-specific responses to stimulus orientations in primary visual cortex (V1) of awake monkeys (male, Macaca mulatta). We distinguished inhibitory effects (suppression) from excitation, by taking advantage of the separability of excitation and inhibition in the orientation and time domains. We found two distinct types of suppression governing different layers. Fast suppression (FS) was strongest in input layers (4C and 6), and slow suppression (SS) was 3 times stronger in output layers (2/3 and 5). Interestingly, the two types of suppression were correlated with different functional properties measured with drifting gratings. FS was primarily correlated with orientation selectivity in input layers (r = −0.65, p < 10⁻⁹), whereas SS was primarily correlated with surround suppression in output layers (r = 0.61, p < 10⁻⁴). The earliest SS in layer 1 indicates the origin of cortical feedback for SS, in contrast to the feedforward/recurrent origin of FS. Our results reveal two V1 laminar subnetworks with different response suppression that may provide a general framework for laminar processing in other sensory cortices.

SIGNIFICANCE STATEMENT This study sought to understand inhibitory effects (suppression) and their relationships with functional properties in the six different layers of the cortex. We found that the diversity of neural responses across layers in primary visual cortex (V1) could be fully explained by one excitatory and two suppressive components (fast and slow suppression). The distinct laminar distributions, origins, and functional roles of the two types of suppression provided a simplified representation of the differences between two V1 subnetworks (input network and output network). These results not only help to elucidate computational principles in macaque V1, but also provide a framework for general computation of cortical laminae in other sensory cortices.

Light Up the Brain: The Application of Optogenetics in Cell-Type Specific Dissection of Mouse Brain Circuits

The exquisite intricacies of neural circuits are fundamental to an animal’s diverse and complex repertoire of sensory and motor functions. The ability to precisely map neural circuits and to selectively manipulate neural activity is critical to understanding brain function and has, therefore been a long-standing goal for neuroscientists. The recent development of optogenetic tools, combined with transgenic mouse lines, has endowed us with unprecedented spatiotemporal precision in circuit analysis. These advances greatly expand the scope of tractable experimental investigations. Here, in the first half of the review, we will present applications of optogenetics in identifying connectivity between different local neuronal cell types and of long-range projections with both in vitro and in vivo methods. We will then discuss how these tools can be used to reveal the functional roles of these cell-type specific connections in governing sensory information processing, and learning and memory in the visual cortex, somatosensory cortex, and motor cortex. Finally, we will discuss the prospect of new optogenetic tools and how their application can further advance modern neuroscience. In summary, this review serves as a primer to exemplify how optogenetics can be used in sophisticated modern circuit analyses at the levels of synapses, cells, network connectivity and behaviors.

Patterned perturbation of inhibition can reveal the dynamical structure of neural processing

Perturbation of neuronal activity is key to understanding the brain's functional properties, however, intervention studies typically perturb neurons in a nonspecific manner. Recent optogenetics techniques have enabled patterned perturbations, in which specific patterns of activity can be invoked in identified target neurons to reveal more specific cortical function. Here, we argue that patterned perturbation of neurons is in fact necessary to reveal the specific dynamics of inhibitory stabilization, emerging in cortical networks with strong excitatory and inhibitory functional subnetworks, as recently reported in mouse visual cortex. We propose a specific perturbative signature of these networks and investigate how this can be measured under different experimental conditions. Functionally, rapid spontaneous transitions between selective ensembles of neurons emerge in such networks, consistent with experimental results. Our study outlines the dynamical and functional properties of feature-specific inhibitory-stabilized networks, and suggests experimental protocols that can be used to detect them in the intact cortex.

Enhanced robustness of convolutional networks with a push–pull inhibition layer

Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen during training. In this paper, we propose a new layer for CNNs that increases their robustness to several types of corruptions of the input images. We call it a ‘push–pull’ layer and compute its response as the combination of two half-wave rectified convolutions, with kernels of different size and opposite polarity. Its implementation is based on a biologically motivated model of certain neurons in the visual system that exhibit response suppression, known as push–pull inhibition. We validate our method by replacing the first convolutional layer of the LeNet, ResNet and DenseNet architectures with our push–pull layer. We train the networks on original training images from the MNIST and CIFAR data sets and test them on images with several corruptions, of different types and severities, that are unseen by the training process. We experiment with various configurations of the ResNet and DenseNet models on a benchmark test set with typical image corruptions constructed on the CIFAR test images. We demonstrate that our push–pull layer contributes to a considerable improvement in robustness of classification of corrupted images, while maintaining state-of-the-art performance on the original image classification task. We released the code and trained models at the url http://github.com/nicstrisc/Push-Pull-CNN-layer.

The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex

Transcranial magnetic stimulation (TMS) is a noninvasive method to modulate brain activity and behavior in humans. Still, stimulation effects substantially vary across studies and individuals, thereby restricting the large-scale application of TMS in research or clinical settings. We revealed that low-frequency stimulation had opposite impact on the functional connectivity of sensory and cognitive brain regions. Biophysical modeling then identified a neuronal mechanism underlying these region-specific effects. Stimulation of the frontal cortex decreased local inhibition and disrupted feedforward and feedback connections. Conversely, identical stimulation increased local inhibition and enhanced forward signaling in the occipital cortex. Last, we identified functional integration as a macroscale network parameter to predict the region-specific effect of stimulation in individual subjects. In summary, we revealed how TMS modulation critically depends on the connectivity profile of target regions and propose an imaging marker to improve sensitivity of noninvasive brain stimulation for research and clinical applications.

A Differential Circuit via Retino-Colliculo-Pulvinar Pathway Enhances Feature Selectivity in Visual Cortex through Surround Suppression

In the mammalian visual system, information from the retina streams into parallel bottom-up pathways. It remains unclear how these pathways interact to contribute to contextual modulation of visual cortical processing. By optogenetic inactivation and activation of mouse lateral posterior nucleus (LP) of thalamus, a homolog of pulvinar, or its projection to primary visual cortex (V1), we found that LP contributes to surround suppression of layer (L) 2/3 responses in V1 by driving L1 inhibitory neurons. This results in subtractive suppression of visual responses and an overall enhancement of orientation, direction, spatial, and size selectivity. Neurons in V1-projecting LP regions receive bottom-up input from the superior colliculus (SC) and respond preferably to non-patterned visual noise. The noise-dependent LP activity allows V1 to "cancel" noise effects and maintain its orientation selectivity under varying noise background. Thus, the retina-SC-LP-V1 pathway forms a differential circuit with the canonical retino-geniculate pathway to achieve context-dependent sharpening of visual representations.

Robust Inhibition-Augmented Operator for Delineation of Curvilinear Structures

Delineation of curvilinear structures in images is an important basic step of several image processing applications, such as segmentation of roads or rivers in aerial images, vessels or staining membranes in medical images, and cracks in pavements and roads, among others. Existing methods suffer from insufficient robustness to noise. In this paper, we propose a novel operator for the detection of curvilinear structures in images, which we demonstrate to be robust to various types of noise and effective in several applications. We call it RUSTICO, which stands for RobUST Inhibition-augmented Curvilinear Operator. It is inspired by the push-pull inhibition in visual cortex and takes as input the responses of two trainable B-COSFIRE filters of opposite polarity. The output of RUSTICO consists of a magnitude map and an orientation map. We carried out experiments on a data set of synthetic stimuli with noise drawn from different distributions, as well as on several benchmark data sets of retinal fundus images, crack pavements, and aerial images and a new data set of rose bushes used for automatic gardening. We evaluated the performance of RUSTICO by a metric that considers the structural properties of line networks (connectivity, area, and length) and demonstrated that RUSTICO outperforms many existing methods with high statistical significance. RUSTICO exhibits high robustness to noise and texture.

Functional Logic of Layer 2/3 Inhibitory Connectivity in the Ferret Visual Cortex

Understanding how cortical inhibition shapes circuit function requires identifying the connectivity rules relating the response properties of inhibitory interneurons and their postsynaptic targets. Here we explore the orientation tuning of layer 2/3 inhibitory inputs in the ferret visual cortex using a combination of in vivo axon imaging, functional input mapping, and physiology. Inhibitory boutons exhibit robust orientation-tuned responses with preferences that can differ significantly from the cortical column in which they reside. Inhibitory input fields measured with patterned optogenetic stimulation and intracellular recordings revealed that these inputs originate from a wide range of orientation domains, inconsistent with a model of co-tuned inhibition and excitation. Intracellular synaptic conductance measurements confirm that individual neurons can depart from a co-tuned regime. Our results argue against a simple rule for the arrangement of inhibitory inputs supplied by layer 2/3 circuits and suggest that heterogeneity in presynaptic inhibitory networks contributes to neural response properties.

Jensen's force and the statistical mechanics of cortical asynchronous states

Cortical networks are shaped by the combined action of excitatory and inhibitory interactions. Among other important functions, inhibition solves the problem of the all-or-none type of response that comes about in purely excitatory networks, allowing the network to operate in regimes of moderate or low activity, between quiescent and saturated regimes. Here, we elucidate a noise-induced effect that we call “Jensen’s force” –stemming from the combined effect of excitation/inhibition balance and network sparsity– which is responsible for generating a phase of self-sustained low activity in excitation-inhibition networks. The uncovered phase reproduces the main empirically-observed features of cortical networks in the so-called asynchronous state, characterized by low, un-correlated and highly-irregular activity. The parsimonious model analyzed here allows us to resolve a number of long-standing issues, such as proving that activity can be self-sustained even in the complete absence of external stimuli or driving. The simplicity of our approach allows for a deep understanding of asynchronous states and of the phase transitions to other standard phases it exhibits, opening the door to reconcile, asynchronous-state and critical-state hypotheses, putting them within a unified framework. We argue that Jensen’s forces are measurable experimentally and might be relevant in contexts beyond neuroscience.

Sequence specificity despite intrinsic disorder: How a disease-associated Val/Met polymorphism rearranges tertiary interactions in a long disordered protein

The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) in precursor brain-derived neurotrophic factor (BDNF) is one of the earliest SNPs to be associated with neuropsychiatric disorders, and the underlying molecular mechanism is unknown. Here we report on over 250 μs of fully-atomistic, explicit solvent, temperature replica-exchange molecular dynamics (MD) simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence. The simulations were able to correctly reproduce the location of both local and non-local secondary structure changes due to the Val66Met mutation, when compared with NMR spectroscopy. We find that the change in local structure is mediated via entropic and sequence specific effects. We developed a hierarchical sequence-based framework for analysis and conceptualization, which first identifies “blobs” of 4-15 residues representing local globular regions or linkers. We use this framework within a novel test for enrichment of higher-order (tertiary) structure in disordered proteins; the size and shape of each blob is extracted from MD simulation of the real protein (RP), and used to parameterize a self-avoiding heterogenous polymer (SAHP). The SAHP version of the BDNF prodomain suggested a protein segmented into three regions, with a central long, highly disordered polyampholyte linker separating two globular regions. This effective segmentation was also observed in full simulations of the RP, but the Val66Met substitution significantly increased interactions across the linker, as well as the number of participating residues. The Val66Met substitution replaces β-bridging between V66 and V94 (on either side of the linker) with specific side-chain interactions between M66 and M95. The protein backbone in the vicinity of M95 is then free to form β-bridges with residues 31-41 near the N-terminus, which condenses the protein. A significant role for Met/Met interactions is consistent with previously-observed non-local effects of the Val66Met SNP, as well as established interactions between the Met66 sequence and a Met-rich receptor that initiates neuronal growth cone retraction.

Intrinsically disordered proteins are proteins that have no well-defined structure in at least one functional form. Mutations in one amino acid may still affect their function significantly, especially in subtle ways with cumulative adverse effects on health. Here we report on molecular dynamics simulations of a protein that is critical for neuronal health throughout adulthood (brain-derived neurotrophic factor). We investigate the effects of a mutation carried by 30% of human population, which has been widely studied for its association with aging-related and stress-related disorders, reduced volume of the hippocampus, and variations in episodic memory. We identify a molecular mechanism in which the mutation may change the global conformations of the protein and its ability to bind to receptors.

Spatial Asymmetry and Short-Term Suppression Underlie Direction Selectivity of Synaptic Excitation in the Mouse Visual Cortex

Direction selectivity (DS) of neuronal responses is fundamental for motion detection. With in vivo whole-cell voltage-clamp recordings from layer (L)4 neurons in the mouse visual cortex, we observed a strong correlation between DS and spatial asymmetry in the distribution of excitatory input strengths. This raises an interesting possibility that the latter may contribute to DS. The preferred direction of excitatory input was found from the stronger to weaker side of its spatial receptive field. A simple linear summation of asymmetrically distributed excitatory responses to stationary flash stimuli however failed to predict the correct directionality: it at best resulted in weak DS with preferred direction opposite to what was observed experimentally. Further studies with sequential 2 flash-bar stimulation revealed a short-term suppression of excitatory input evoked by the late bar. More importantly, the level of the suppression positively correlated with the relative amplitude of the early-bar response. Implementing this amplitude-dependent suppressive interaction can successfully predict DS of excitatory input. Our results suggest that via nonlinear temporal interactions, the spatial asymmetry can be transformed into differential temporal integration of inputs under opposite directional movements. This mechanism may contribute to the DS of excitatory inputs to L4 neurons.

Thalamocortical and Intracortical Inputs Differentiate Layer-Specific Mouse Auditory Corticocollicular Neurons

Long-range descending projections from the auditory cortex play key roles in shaping response properties in the inferior colliculus. The auditory corticocollicular projection is massive and heterogeneous, with axons emanating from cortical layers 5 and 6, and plays a key role in directing plastic changes in the inferior colliculus. However, little is known about the cortical and thalamic networks within which corticocollicular neurons are embedded. Here, laser scanning photostimulation glutamate uncaging and photoactivation of channelrhodopsin-2 were used to probe the local and long-range network differences between preidentified layer 5 and layer 6 auditory corticocollicular neurons from male and female mice in vitro Layer 5 corticocollicular neurons were found to vertically integrate supragranular excitatory and inhibitory input to a substantially greater degree than their layer 6 counterparts. In addition, all layer 5 corticocollicular neurons received direct and large thalamic inputs from channelrhodopsin-2-labeled thalamocortical fibers, whereas such inputs were less common in layer 6 corticocollicular neurons. Finally, a new low-calcium/synaptic blockade approach to separate direct from indirect inputs using laser photostimulation was validated. These data demonstrate that layer 5 and 6 corticocollicular neurons receive distinct sets of cortical and thalamic inputs, supporting the hypothesis that they have divergent roles in modulating the inferior colliculus. Furthermore, the direct connection between the auditory thalamus and layer 5 corticocollicular neurons reveals a novel and rapid link connecting ascending and descending pathways.SIGNIFICANCE STATEMENT Descending projections from the cortex play a critical role in shaping the response properties of sensory neurons. The projection from the auditory cortex to the inferior colliculus is a massive, yet poorly understood, pathway emanating from two distinct cortical layers. Here we show, using a range of optical techniques, that mouse auditory corticocollicular neurons from different layers are embedded into different cortical and thalamic networks. Specifically, we observed that layer 5 corticocollicular neurons integrate information across cortical lamina and receive direct thalamic input. The latter connection provides a hyperdirect link between acoustic sensation and descending control, thus demonstrating a novel mechanism for rapid "online" modulation of sensory perception.

Different Inhibitory Interneuron Cell Classes Make Distinct Contributions to Visual Contrast Perception

While recent work has revealed how different inhibitory interneurons influence responses of cortical neurons to sensory stimuli, little is known about their distinct contributions to sensory perception. Here, we optogenetically activated different genetically defined interneurons [parvalbumin (PV), somatostatin (SST), vasoactive intestinal peptide (VIP)] in visual cortex (V1) of mice working at threshold in a contrast increment detection task. The visual stimulus was paired with optogenetic stimulation to assess how enhancing V1 inhibitory neuron activity during visual processing altered task performance. PV or SST activation impaired, while VIP stimulation improved, contrast increment detection. The impairment produced by PV or SST activation persisted over several weeks of testing. In contrast, mice learned to reliably detect VIP activation in the absence of any natural visual stimulus. Thus, different inhibitory signals make distinct contributions to visual contrast perception.

Developmental 'awakening' of primary motor cortex to the sensory consequences of movement

Before primary motor cortex (M1) develops its motor functions, it functions like a somatosensory area. Here, by recording from neurons in the forelimb representation of M1 in postnatal day (P) 8–12 rats, we demonstrate a rapid shift in its sensory responses. At P8-10, M1 neurons respond overwhelmingly to feedback from sleep-related twitches of the forelimb, but the same neurons do not respond to wake-related movements. By P12, M1 neurons suddenly respond to wake movements, a transition that results from opening the sensory gate in the external cuneate nucleus. Also at P12, fewer M1 neurons respond to individual twitches, but the full complement of twitch-related feedback observed at P8 is unmasked through local disinhibition. Finally, through P12, M1 sensory responses originate in the deep thalamorecipient layers, not primary somatosensory cortex. These findings demonstrate that M1 initially establishes a sensory framework upon which its later-emerging role in motor control is built.

The Circuit Motif as a Conceptual Tool for Multilevel Neuroscience

Modern neuroscientific techniques that specifically manipulate and measure neuronal activity in behaving animals now allow bridging of the gap from the cellular to the behavioral level. However, in doing so, they also pose new challenges. Research using incompletely defined manipulations in a high-dimensional space without clear hypotheses is likely to suffer from multiple well-known conceptual and statistical problems. In this context it is essential to develop hypotheses with testable implications across levels. Here we propose that a focus on circuit motifs can help achieve this goal. Viewing neural structures as an assembly of circuit motif building blocks is not new. However, recent tool advances have made it possible to extensively map, specifically manipulate, and quantitatively investigate circuit motifs and thereby reexamine their relevance to brain function.

Mechanisms underlying contrast-dependent orientation selectivity in mouse V1

Recently, sophisticated optogenetic tools for mouse have enabled many detailed studies of the neuronal circuits of its primary visual cortex (V1), providing much more specific information than is available for cat or monkey. Among various other differences, they show a striking contrast dependency in orientation selectivity in mouse V1 rather than the well-known contrast invariance for cat and monkey. Constrained by the existing experiment data, we develop a comprehensive large-scale model of an effective input layer of mouse V1 that successfully reproduces the contrast-dependent phenomena and many other response properties. The model helps to probe different mechanisms based on excitation–inhibition balance that underlie both contrast dependencies and invariance, and it provides implications for future studies on these circuits.

Recent experiments have shown that mouse primary visual cortex (V1) is very different from that of cat or monkey, including response properties—one of which is that contrast invariance in the orientation selectivity (OS) of the neurons’ firing rates is replaced in mouse with contrast-dependent sharpening (broadening) of OS in excitatory (inhibitory) neurons. These differences indicate a different circuit design for mouse V1 than that of cat or monkey. Here we develop a large-scale computational model of an effective input layer of mouse V1. Constrained by experiment data, the model successfully reproduces experimentally observed response properties—for example, distributions of firing rates, orientation tuning widths, and response modulations of simple and complex neurons, including the contrast dependence of orientation tuning curves. Analysis of the model shows that strong feedback inhibition and strong orientation-preferential cortical excitation to the excitatory population are the predominant mechanisms underlying the contrast-sharpening of OS in excitatory neurons, while the contrast-broadening of OS in inhibitory neurons results from a strong but nonpreferential cortical excitation to these inhibitory neurons, with the resulting contrast-broadened inhibition producing a secondary enhancement on the contrast-sharpened OS of excitatory neurons. Finally, based on these mechanisms, we show that adjusting the detailed balances between the predominant mechanisms can lead to contrast invariance—providing insights for future studies on contrast dependence (invariance).

Differential tuning of excitation and inhibition shapes direction selectivity in ferret visual cortex

To encode specific sensory inputs, cortical neurons must generate selective responses for distinct stimulus features. In principle, a variety of factors contribute to a cortical neuron’s response selectivity: the tuning and strength of excitatory^1–3 and inhibitory synaptic inputs^4–6, dendritic nonlinearities^7–9, and spike threshold^10,11. Here we employ a combination of techniques including in vivo whole-cell recording, synaptic and cellular resolution in vivo two photon calcium imaging, and GABAergic-selective optogenetic manipulation to dissect the factors contributing to direction selective responses of layer 2/3 neurons in ferret visual cortex (V1). Two-photon calcium imaging of dendritic spines^12,13 revealed that each neuron receives a mixture of excitatory synaptic inputs selective for the somatic preferred or null direction of motion. The relative number of preferred- and null-tuned excitatory inputs predicted a neuron’s somatic direction preference, but failed to account for the degree of direction selectivity. In contrast, in vivo whole-cell patch clamp recordings revealed a striking degree of direction selectivity in subthreshold responses that was significantly correlated with spiking direction selectivity. Subthreshold direction selectivity was predicted by the magnitude and variance of the response to the null direction of motion, and several lines of evidence including conductance measurements demonstrate that differential tuning of excitation and inhibition suppresses responses to the null direction of motion. Consistent with this idea, optogenetic inactivation of GABAergic neurons in layer 2/3 reduced direction selectivity by enhancing responses to the null direction. Furthermore, using a new technique to optogenetically map connections of inhibitory neurons in layer 2/3 in vivo, we find that layer 2/3 inhibitory neurons make long-range, intercolumnar projections to excitatory neurons that prefer the opposite direction of motion. We conclude that intracortical inhibition exerts a major influence on the degree of direction selectivity in layer 2/3 of ferret V1 by suppressing responses to the null direction of motion.

Adaptation to stimulus orientation in mouse primary visual cortex

Information processing in the visual system is shaped by recent stimulus history, such that prolonged viewing of an adapting stimulus can alter the perception of subsequently presented test stimuli. In the tilt-after-effect, the perceived orientation of a grating is often repelled away from the orientation of a previously viewed adapting grating. A possible neural correlate for the tilt-after-effect has been described in cat and macaque primary visual cortex (V1), where adaptation produces repulsive shifts in the orientation tuning curves of V1 neurons. We investigated adaptation to stimulus orientation in mouse V1 to determine whether known species differences in orientation processing, notably V1 functional architecture and proportion of tightly tuned cells, are important for these repulsive shifts. Unlike the consistent repulsion reported in other species, we found that repulsion was only about twice as common as attraction in our mouse data. Furthermore, adapted responses were attenuated across all orientations. A simple model that captured key physiological findings reported in cats and mice indicated that the greater proportion of broadly tuned neurons in mice may explain the observed species differences in adaptation.

Synaptic E-I Balance Underlies Efficient Neural Coding

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

A Non-canonical Reticular-Limbic Central Auditory Pathway via Medial Septum Contributes to Fear Conditioning

In the mammalian brain, auditory information is known to be processed along a central ascending pathway leading to auditory cortex (AC). Whether there exist any major pathways beyond this canonical auditory neuraxis remains unclear. In awake mice, we found that auditory responses in entorhinal cortex (EC) cannot be explained by a previously proposed relay from AC based on response properties. By combining anatomical tracing and optogenetic/pharmacological manipulations, we discovered that EC received auditory input primarily from the medial septum (MS), rather than AC. A previously uncharacterized auditory pathway was then revealed: it branched from the cochlear nucleus, and via caudal pontine reticular nucleus, pontine central gray, and MS, reached EC. Neurons along this non-canonical auditory pathway responded selectively to high-intensity broadband noise, but not pure tones. Disruption of the pathway resulted in an impairment of specifically noise-cued fear conditioning. This reticular-limbic pathway may thus function in processing aversive acoustic signals.

Dendritic Spines Prevent Synaptic Voltage Clamp

Synapses are the fundamental units of information processing in the mammalian brain. Much of our understanding of their functional properties comes from voltage-clamp analysis, the predominant approach for investigating synaptic physiology. Here, we reveal that voltage clamp is completely ineffective for most excitatory synapses due to spine electrical compartmentalization. Under local dendritic voltage clamp, single-spine activation produced large spine head depolarizations that severely distorted measurements and recruited voltage-dependent channels. To overcome these voltage-clamp errors, we developed an approach to provide new, accurate measurements of synaptic conductance. Single-synapse AMPA conductance was much larger than previously appreciated, producing saturation effects on synaptic currents. We conclude that electrical compartmentalization profoundly shapes both synaptic function and how that function can be assessed with electrophysiological methods.