Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation.

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (WE←E, WE←I, WI←E, and WI←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of "cross-homeostatic" rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how-beginning from a silent network-self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

Differential Short-Term Plasticity of PV and SST Neurons Accounts for Adaptation and Facilitation of Cortical Neurons to Auditory Tones.

Cortical responses to sensory stimuli are strongly modulated by temporal context. One of the best studied examples of such modulation is sensory adaptation. We first show that in response to repeated tones pyramidal (Pyr) neurons in male mouse auditory cortex (A1) exhibit facilitating and stable responses, in addition to adapting responses. To examine the potential mechanisms underlying these distinct temporal profiles, we developed a reduced spiking model of sensory cortical circuits that incorporated the signature short-term synaptic plasticity (STP) profiles of the inhibitory parvalbumin (PV) and somatostatin (SST) interneurons. The model accounted for all three temporal response profiles as the result of dynamic changes in excitatory/inhibitory balance produced by STP, primarily through shifts in the relative latency of Pyr and inhibitory neurons. Transition between the three response profiles was possible by changing the strength of the inhibitory PV→Pyr and SST→Pyr synapses. The model predicted that a unit's latency would be related to its temporal profile. Consistent with this prediction, the latency of stable units was significantly shorter than that of adapting and facilitating units. Furthermore, because of the history-dependence of STP the model generated a paradoxical prediction: that inactivation of inhibitory neurons during one tone would decrease the response of A1 neurons to a subsequent tone. Indeed, we observed that optogenetic inactivation of PV neurons during one tone counterintuitively decreased the spiking of Pyr neurons to a subsequent tone 400 ms later. These results provide evidence that STP is critical to temporal context-dependent responses in the sensory cortex.SIGNIFICANCE STATEMENT Our perception of speech and music depends strongly on temporal context, i.e., the significance of a stimulus depends on the preceding stimuli. Complementary neural mechanisms are needed to sometimes ignore repetitive stimuli (e.g., the tic of a clock) or detect meaningful repetition (e.g., consecutive tones in Morse code). We modeled a neural circuit that accounts for diverse experimentally-observed response profiles in auditory cortex (A1) neurons, based on known forms of short-term synaptic plasticity (STP). Whether the simulated circuit reduced, maintained, or enhanced its response to repeated tones depended on the relative dominance of two different types of inhibitory cells. The model made novel predictions that were experimentally validated. Results define an important role for STP in temporal context-dependent perception.

Density and Dichotomous Family History Measures of Alcohol Use Disorder as Predictors of Behavioral and Neural Phenotypes: A Comparative Study Across Gender and Race/Ethnicity.

BACKGROUND: Family history (FH) is an important risk factor for the development of alcohol use disorder (AUD). A variety of dichotomous and density measures of FH have been used to predict alcohol outcomes; yet, a systematic comparison of these FH measures is lacking. We compared 4 density and 4 commonly used dichotomous FH measures and examined variations by gender and race/ethnicity in their associations with age of onset of regular drinking, parietal P3 amplitude to visual target, and likelihood of developing AUD. METHODS: Data from the Collaborative Study on the Genetics of Alcoholism (COGA) were utilized to compute the density and dichotomous measures. Only subjects and their family members with DSM-5 AUD diagnostic information obtained through direct interviews using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) were included in the study. Area under receiver operating characteristic curves were used to compare the diagnostic accuracy of FH measures at classifying DSM-5 AUD diagnosis. Logistic and linear regression models were used to examine associations of FH measures with alcohol outcomes. RESULTS: Density measures had greater diagnostic accuracy at classifying AUD diagnosis, whereas dichotomous measures presented diagnostic accuracy closer to random chance. Both dichotomous and density measures were significantly associated with likelihood of AUD, early onset of regular drinking, and low parietal P3 amplitude, but density measures presented consistently more robust associations. Further, variations in these associations were observed such that among males (vs. females) and Whites (vs. Blacks), associations of alcohol outcomes with density (vs. dichotomous) measures were greater in magnitude. CONCLUSIONS: Density (vs. dichotomous) measures seem to present more robust associations with alcohol outcomes. However, associations of dichotomous and density FH measures with different alcohol outcomes (behavioral vs. neural) varied across gender and race/ethnicity. These findings have great applicability for alcohol research examining FH of AUD.

Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing.

The ability to detect time intervals and temporal patterns is critical to some of the most fundamental computations the brain performs, including the ability to communicate and appraise a dynamically changing environment. Many of these computations take place on the scale of tens to hundreds of milliseconds. Electrophysiological evidence shows that some neurons respond selectively to duration, interval, rate, or order. Because the time constants of many time-varying neural and synaptic properties, including short-term synaptic plasticity (STP), are also in the range of tens to hundreds of milliseconds, they are strong candidates to underlie the formation of temporally selective neurons. Neurophysiological studies indicate that STP is indeed one of the mechanisms that contributes to temporal selectivity, and computational models demonstrate that neurons embedded in local microcircuits exhibit temporal selectivity if their synapses undergo STP. Converging evidence suggests that some forms of temporal selectivity emerge from the dynamic changes in the balance of excitation and inhibition imposed by STP.

Rapid cortical dynamics associated with auditory spatial attention gradients.

Behavioral and EEG studies suggest spatial attention is allocated as a gradient in which processing benefits decrease away from an attended location. Yet the spatiotemporal dynamics of cortical processes that contribute to attentional gradients are unclear. We measured EEG while participants (n = 35) performed an auditory spatial attention task that required a button press to sounds at one target location on either the left or right. Distractor sounds were randomly presented at four non-target locations evenly spaced up to 180° from the target location. Attentional gradients were quantified by regressing ERP amplitudes elicited by distractors against their spatial location relative to the target. Independent component analysis was applied to each subject's scalp channel data, allowing isolation of distinct cortical sources. Results from scalp ERPs showed a tri-phasic response with gradient slope peaks at ~300 ms (frontal, positive), ~430 ms (posterior, negative), and a plateau starting at ~550 ms (frontal, positive). Corresponding to the first slope peak, a positive gradient was found within a central component when attending to both target locations and for two lateral frontal components when contralateral to the target location. Similarly, a central posterior component had a negative gradient that corresponded to the second slope peak regardless of target location. A right posterior component had both an ipsilateral followed by a contralateral gradient. Lateral posterior clusters also had decreases in α and ß oscillatory power with a negative slope and contralateral tuning. Only the left posterior component (120-200 ms) corresponded to absolute sound location. The findings indicate a rapid, temporally-organized sequence of gradients thought to reflect interplay between frontal and parietal regions. We conclude these gradients support a target-based saliency map exhibiting aspects of both right-hemisphere dominance and opponent process models.