Distinct timescales of population coding across cortex.

The cortex represents information across widely varying timescales. For instance, sensory cortex encodes stimuli that fluctuate over few tens of milliseconds, whereas in association cortex behavioural choices can require the maintenance of information over seconds. However, it remains poorly understood whether diverse timescales result mostly from features intrinsic to individual neurons or from neuronal population activity. This question remains unanswered, because the timescales of coding in populations of neurons have not been studied extensively, and population codes have not been compared systematically across cortical regions. Here we show that population codes can be essential to achieve long coding timescales. Furthermore, we find that the properties of population codes differ between sensory and association cortices. We compared coding for sensory stimuli and behavioural choices in auditory cortex and posterior parietal cortex as mice performed a sound localization task. Auditory stimulus information was stronger in auditory cortex than in posterior parietal cortex, and both regions contained choice information. Although auditory cortex and posterior parietal cortex coded information by tiling in time neurons that were transiently informative for approximately 200 milliseconds, the areas had major differences in functional coupling between neurons, measured as activity correlations that could not be explained by task events. Coupling among posterior parietal cortex neurons was strong and extended over long time lags, whereas coupling among auditory cortex neurons was weak and short-lived. Stronger coupling in posterior parietal cortex led to a population code with long timescales and a representation of choice that remained consistent for approximately 1 second. In contrast, auditory cortex had a code with rapid fluctuations in stimulus and choice information over hundreds of milliseconds. Our results reveal that population codes differ across cortex and that coupling is a variable property of cortical populations that affects the timescale of information coding and the accuracy of behaviour.

Jointly reduced inhibition and excitation underlies circuit-wide changes in cortical processing in Rett syndrome.

Rett syndrome (RTT) arises from loss-of-function mutations in methyl-CpG binding protein 2 gene (Mecp2), but fundamental aspects of its physiological mechanisms are unresolved. Here, by whole-cell recording of synaptic responses in MeCP2 mutant mice in vivo, we show that visually driven excitatory and inhibitory conductances are both reduced in cortical pyramidal neurons. The excitation-to-inhibition (E/I) ratio is increased in amplitude and prolonged in time course. These changes predict circuit-wide reductions in response reliability and selectivity of pyramidal neurons to visual stimuli, as confirmed by two-photon imaging. Targeted recordings reveal that parvalbumin-expressing (PV+) interneurons in mutant mice have reduced responses. PV-specific MeCP2 deletion alone recapitulates effects of global MeCP2 deletion on cortical circuits, including reduced pyramidal neuron responses and reduced response reliability and selectivity. Furthermore, MeCP2 mutant mice show reduced expression of the cation-chloride cotransporter KCC2 (K+/Cl- exporter) and a reduced KCC2/NKCC1 (Na+/K+/Cl- importer) ratio. Perforated patch recordings demonstrate that the reversal potential for GABA is more depolarized in mutant mice, but is restored by application of the NKCC1 inhibitor bumetanide. Treatment with recombinant human insulin-like growth factor-1 restores responses of PV+ and pyramidal neurons and increases KCC2 expression to normalize the KCC2/NKCC1 ratio. Thus, loss of MeCP2 in the brain alters both excitation and inhibition in brain circuits via multiple mechanisms. Loss of MeCP2 from a specific interneuron subtype contributes crucially to the cell-specific and circuit-wide deficits of RTT. The joint restoration of inhibition and excitation in cortical circuits is pivotal for functionally correcting the disorder.

Division and subtraction by distinct cortical inhibitory networks in vivo.

Brain circuits process information through specialized neuronal subclasses interacting within a network. Revealing their interplay requires activating specific cells while monitoring others in a functioning circuit. Here we use a new platform for two-way light-based circuit interrogation in visual cortex in vivo to show the computational implications of modulating different subclasses of inhibitory neurons during sensory processing. We find that soma-targeting, parvalbumin-expressing (PV) neurons principally divide responses but preserve stimulus selectivity, whereas dendrite-targeting, somatostatin-expressing (SOM) neurons principally subtract from excitatory responses and sharpen selectivity. Visualized in vivo cell-attached recordings show that division by PV neurons alters response gain, whereas subtraction by SOM neurons shifts response levels. Finally, stimulating identified neurons while scanning many target cells reveals that single PV and SOM neurons functionally impact only specific subsets of neurons in their projection fields. These findings provide direct evidence that inhibitory neuronal subclasses have distinct and complementary roles in cortical computations.

Response selectivity is correlated to dendritic structure in parvalbumin-expressing inhibitory neurons in visual cortex.

Inhibitory neurons have been shown to perform a variety of functions within brain circuits, including shaping response functions in target cells. Still, how the properties of specific inhibitory neuron classes relate to their local circuits remains unclear. To better understand the distribution and origins of orientation selectivity in inhibitory neurons expressing the calcium binding protein parvalbumin (PV) in the mouse primary visual cortex, we labeled PV(+) neurons with red fluorescent protein (RFP) and targeted them for cell-attached electrophysiological recordings. PV(+) neurons could be broadly tuned or sharply tuned for orientation but tended to be more broadly tuned than unlabeled neurons on average. The dendritic morphology of PV(+) cells, revealed by intracellular labeling, was strongly correlated with tuning: highly tuned PV(+) neurons had shorter dendrites that branched nearer to the soma and had smaller dendritic fields overall, whereas broadly tuned PV(+) neurons had longer dendrites that branched farther from the soma, producing larger dendritic fields. High-speed two-photon calcium imaging of visual responses showed that the orientation preferences of highly tuned PV(+) neurons resembled the preferred orientations of neighboring cells. These results suggest that the diversity of the local neighborhood and the nature of dendritic sampling may both contribute to the response selectivity of PV(+) neurons.

Different state-dependence of population codes across cortex.

During perceptual decision-making, behavioral performance varies with changes in internal states such as arousal, motivation, and strategy. Yet it is unknown how these internal states affect information coding across cortical regions involved in differing aspects of sensory perception and decision-making. We recorded neural activity from the primary auditory cortex (AC) and posterior parietal cortex (PPC) in mice performing a navigation-based sound localization task. We then modeled transitions in the behavioral strategies mice used during task performance. Mice transitioned between three latent performance states with differing decision-making strategies: an 'optimal' state and two 'sub-optimal' states characterized by choice bias and frequent errors. Performance states strongly influenced population activity patterns in association but not sensory cortex. Surprisingly, activity of individual PPC neurons was better explained by external inputs and behavioral variables during suboptimal behavioral performance than in the optimal performance state. Furthermore, shared variability across neurons (coupling) in PPC was strongest in the optimal state. In AC, shared variability was similarly weak across all performance states. Together, these findings indicate that neural activity in association cortex is more strongly linked to internal state than in sensory cortex.

Simultaneous interneuron labeling reveals population-level interactions among parvalbumin, somatostatin, and pyramidal neurons in cortex.

Cortical interneurons shape network activity in cell type-specific ways, and are also influenced by interactions with other cell types. These specific cell-type interactions are understudied, as transgenic labeling methods typically restrict labeling to one neuron type at a time. Although recent methods have enabled post-hoc identification of cell types, these are not available to many labs. Here, we present a method to distinguish between two red fluorophores in vivo, which allowed imaging of activity in somatostatin (SOM), parvalbumin (PV), and putative pyramidal neurons (PYR) in mouse association cortex. We compared population events of elevated activity and observed that the PYR network state corresponded to the ratio between mean SOM and PV neuron activity, demonstrating the importance of simultaneous labeling to explain dynamics. These results extend previous findings in sensory cortex, as activity became sparser and less correlated when the ratio between SOM and PV activity was high.

Arousal and Locomotion Differently Modulate Activity of Somatostatin Neurons across Cortex.

Arousal powerfully influences cortical activity, in part by modulating local inhibitory circuits. Somatostatin (SOM)-expressing inhibitory interneurons are particularly well situated to shape local population activity in response to shifts in arousal, yet the relationship between arousal state and SOM activity has not been characterized outside of sensory cortex. To determine whether SOM activity is similarly modulated by behavioral state across different levels of the cortical processing hierarchy, we compared the behavioral modulation of SOM-expressing neurons in auditory cortex (AC), a primary sensory region, and posterior parietal cortex (PPC), an association-level region of cortex, in mice. Behavioral state modulated activity differently in AC and PPC. In PPC, transitions to high arousal were accompanied by large increases in activity across the full PPC neural population, especially in SOM neurons. In AC, arousal transitions led to more subtle changes in overall activity, as individual SOM and Non-SOM neurons could be either positively or negatively modulated during transitions to high arousal states. The coding of sensory information in population activity was enhanced during periods of high arousal in AC, but not in PPC. Our findings suggest unique relationships between activity in local circuits and arousal across cortex, which may be tailored to the roles of specific cortical regions in sensory processing or the control of behavior.

The spatial scale of somatostatin subnetworks increases from sensory to association cortex.

Incoming signals interact with rich, ongoing population activity dynamics in cortical circuits. These intrinsic dynamics are the consequence of interactions among local excitatory and inhibitory neurons and affect inter-region communication and information coding. It is unclear whether specializations in the patterns of interactions among excitatory and inhibitory neurons underlie systematic differences in activity dynamics across the cortex. Here, in mice, we compare the functional interactions among somatostatin (SOM)-expressing inhibitory interneurons and the rest of the neural population in auditory cortex (AC), a sensory region of the cortex, and posterior parietal cortex (PPC), an association region. The spatial structure of shared variability among SOM and non-SOM neurons differs across regions: correlations decay rapidly with distance in AC but not in PPC. However, in both regions, activity of SOM neurons is more highly correlated than non-SOM neurons' activity. Our results imply both generalization and specialization in the functional structure of inhibitory subnetworks across the cortex.

Correlations enhance the behavioral readout of neural population activity in association cortex.

Noise correlations (that is, trial-to-trial covariations in neural activity for a given stimulus) limit the stimulus information encoded by neural populations, leading to the widely held prediction that they impair perceptual discrimination behaviors. However, this prediction neglects the effects of correlations on information readout. We studied how correlations affect both encoding and readout of sensory information. We analyzed calcium imaging data from mouse posterior parietal cortex during two perceptual discrimination tasks. Correlations reduced the encoded stimulus information, but, seemingly paradoxically, were higher when mice made correct rather than incorrect choices. Single-trial behavioral choices depended not only on the stimulus information encoded by the whole population, but unexpectedly also on the consistency of information across neurons and time. Because correlations increased information consistency, they enhanced the conversion of sensory information into behavioral choices, overcoming their detrimental information-limiting effects. Thus, correlations in association cortex can benefit task performance even if they decrease sensory information.

Two-way communication with neural networks in vivo using focused light.

Neuronal networks process information in a distributed, spatially heterogeneous manner that transcends the layout of electrodes. In contrast, directed and steerable light offers the potential to engage specific cells on demand. We present a unified framework for adapting microscopes to use light for simultaneous in vivo stimulation and recording of cells at fine spatiotemporal resolutions. We use straightforward optics to lock onto networks in vivo, to steer light to activate circuit elements and to simultaneously record from other cells. We then actualize this 'free' augmentation on both an 'open' two-photon microscope and a leading commercial one. By following this protocol, setup of the system takes a few days, and the result is a noninvasive interface to brain dynamics based on directed light, at a network resolution that was not previously possible and which will further improve with the rapid advance in development of optical reporters and effectors. This protocol is for physiologists who are competent with computers and wish to extend hardware and software to interface more fluidly with neuronal networks.

Modeling two-photon calcium fluorescence of episodic V1 recordings using multifrequency analysis.

The use of two-photon microscopy allows for imaging of deep neural tissue in vivo. This paper examines frequency-based analysis to two-photon calcium fluorescence images with the goal of deriving smooth tuning curves. We present a multifrequency analysis approach for improved extraction of calcium responses in episodic stimulation experiments, that is, when the stimulus is applied for a number of frames, then turned off for the next few frames, and so on. Episodic orientation stimulus was applied while recording from the primary visual cortex of an anesthetized mouse. The multifrequency model demonstrated improved tuning curve descriptions of the neurons. It also offers perspective regarding the characteristics of calcium fluorescence imaging of the brain.

Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex.

Inhibitory interneurons in the cerebral cortex include a vast array of subtypes, varying in their molecular signatures, electrophysiological properties, and connectivity patterns. This diversity suggests that individual inhibitory classes have unique roles in cortical circuits; however, their characterization to date has been limited to broad classifications including many subtypes. We used the Cre/LoxP system, specifically labeling parvalbumin(PV)-expressing interneurons in visual cortex of PV-Cre mice with red fluorescent protein (RFP), followed by targeted loose-patch recordings and two-photon imaging of calcium responses in vivo to characterize the visual receptive field properties of these cells. Despite their relative molecular and morphological homogeneity, we find that PV+ neurons have a diversity of feature-specific visual responses that include sharp orientation and direction-selectivity, small receptive fields, and band-pass spatial frequency tuning. These results suggest that subsets of parvalbumin interneurons are components of specific cortical networks and that perisomatic inhibition contributes to the generation of precise response properties.

Age-related changes of n-3 and n-6 polyunsaturated fatty acids in the anterior cingulate cortex of individuals with major depressive disorder.

Accumulating evidence finds a relative deficiency of peripheral membrane fatty acids in persons with affective disorders such as unipolar and bipolar depression. Here we sought to investigate whether postmortem brain fatty acids within the anterior cingulate cortex (BA-24) varied according to the presence of major depression at the time of death. Using capillary gas chromatography we measured fatty acids in a depressed group (n=12), and in a control group without lifetime history of psychiatric diagnosis (n=14). Compared to the control group, the depressed group showed significantly lower concentrations of numerous saturated and polyunsaturated fatty acids including both the n-3 and n-6 fatty acids. Additionally, significant correlations between age at death and precursor (or metabolites) in the n-3 fatty acid pathway were demonstrated in the depressed group but not in control subjects. In the n-6 fatty acid family, the ratio of 20:3(n-6)/18:2(n-6) was higher in patients than in control groups, whereas the ratio of 20:4(n-6)/20:3(n-6) was relatively decreased in patients. Lastly, a significant negative correlation between age and the ratio of 20:4(n-6) to 22:6(n-3) was found in patients, but not in controls. Taken together, decreases in 22:6(n-3) may be caused, at least in part, by the diminished formation of 20:5(n-3), which is derived from 20:4(n-3) through a Delta5 desaturase reaction. The present findings from postmortem brain tissue raise the possibility that an increased ratio of 20:4(n-6) to 22:6(n-3) may provide us with a biomarker for depression. Future research should further investigate these relationships.