William B. Levy

A sequence predicting CA3 is a flexible associator that learns and uses context to solve hippocampal-like tasks

The model discussed in this paper is, by hypothesis, a minimal, biologically plausible model of hippocampal region CA3. Because cognitive mapping can be viewed as a sequence prediction problem, we qualify this model as a successful sequence predictor. Since the model solves problems which require the use of context, the model is also able to learn and use context. The model also solves configural learning problems of which, at least one, requires a hippocampus. Thus, by solving sequence problems, by solving configural learning problems, and by creating codes for context, this model provides a computational unification of hippocampal functions which are often viewed as disparate.

Synaptic correlates of associative potentiation/depression: an ultrastructural study in the hippocampus

Brief high-frequency trains delivered to the monosynaptic entorhinal cortical input to the dentate gyrus result in both increases and decreases of synaptic strength as a function of whether a particular afferent is active during conditioning (associative potentiation/depression). The present report concerns the effect of such brief, high-frequency conditioning trains upon the asymmetric synapses of the rat dentate gyrus molecular layer. Only those animals whose responses increased at least 50% following conditioning stimulation were included in the study. Additional animals were used for one-dimensional current source density analyses to localize the activated synaptic region. Double blind scoring procedures were used to classify and quantify electron micrographic data. Asymmetric synapses were scored as a function of their position in the molecular layer, spine head size and shape, and postsynaptic density length. All data were treated as inherently matched comparisons between the conditioned and control sides of each animal. The number of large, concave spine synapses with large postsynaptic densities significantly increases in the central zone of synaptic activation. Bordering this zone are regions with increases in synaptic number following conditioning, primarily due to an increased number of small spine synapses. The increased number of large, concave spine synapses in the central zone is postulated to mediate associative potentiation. The many small spine heads just adjacent to the zone of strongest synaptic activation may reflect synaptic depression evoked at synapses inactive during conditioning.

A Computational Approach to Hippocampal Function

Publisher Summary This chapter describes the early, formative stages of a theory of hippocampal function. This theory has been stimulated by the psychological observations indicating a role for the hippocampus in short-term working memory and spatial behavior and develops mainly through the consideration of computational issues. These computational issues are related to the psychological viewpoint through physiological and anatomical observations. The hippocampus participates in the prediction of future representations based on past and present representations. All three classes of representations are derived from a multiplicity of sensory modalities, such as auditory, visual, and olfactory signals from neo- and piriform cortices. This fusion of sensory modalities requires recoding because of computational complexity problems. The CA1 region of the hippocampus is postulated to be a prediction-generating layer or tier. This region produces a prediction based on its input from hippocampal region CA3. The combined hippocampal dentate gyrus/CA3 (DG/CA3) system is postulated to be a preprocessor serving the CA1 prediction layer. The computational complexity problems arise from the combinatorial explosion of possible representations resulting when the hippocampus and supporting limbic structures mix representations from multiple sensory modalities.

Granule cell dendritic spine density in the rat hippocampus varies with spine shape and location

The number of granule cell dendritic spines per micrometer of dendritic length in the dorsal and ventral leaves of the dentate gyrus was quantified using light microscopic-Golgi preparations of normal adult rats. Spines were counted in terms of 3 categories of spine form for the 3 afferent termination zones of the molecular layer and corrected for shading errors. Total spine density averaged 1.6 spines/micron of dendritic length in the dorsal leaf and 1.3 spines/micron of dendritic length in the ventral leaf. Statistically significant differences in spine density existed among the 3 shape categories. Variations in spine density occurred by shape category among the afferent termination zones.

Synaptic interface surface area increases with long-term potentiation in the hippocampal dentate gyrus.

The present study continues our attempt to understand the ultrastructural changes that accompany and may underlie long-term potentiation (LTP). This report describes changes with LTP in the surface area of the pre- and postsynaptic membrane apposition at the synapses formed by entorhinal cortical (EC) axons with granule cell dendritic spines of the dentate gyrus (DG). The electrophysiology and electron microscopy of the DGs from each animal followed conventional procedures. The trace length of the pre- and postsynaptic apposition was measured for identified asymmetric synapses in the dentate molecular layer. The total apposed membrane surface area per unit volume (Sv) was then computed for 4 categories of synaptic profiles for each third of the molecular layer. Statistical analysis of the Sv data used multivariate analyses of variance. Across the entire molecular layer, total apposed Sv does not change significantly with LTP. However, in the activated portion of the molecular layer, total apposed Sv increases significantly, reflecting a significant increase in the apposed Sv for the concave spine profiles there. For these spine profiles, the increased apposed Sv is due to the increased membrane area both at the postsynaptic density and beyond. The average apposed surface area per individual synapse also increases markedly with LTP. The present data support the hypothesis of coordinated pre- and postsynaptic anatomical changes with LTP in the EC-DG system.

Energy-efficient neuronal computation via quantal synaptic failures.

Organisms evolve as compromises, and many of these compromises can be expressed in terms of energy efficiency. For example, a compromise between rate of information processing and the energy consumed might explain certain neurophysiological and neuroanatomical observations (e.g., average firing frequency and number of neurons). Using this perspective reveals that the randomness injected into neural processing by the statistical uncertainty of synaptic transmission optimizes one kind of information processing relative to energy use. A critical hypothesis and insight is that neuronal information processing is appropriately measured, first, by considering dendrosomatic summation as a Shannon-type channel (1948) and, second, by considering such uncertain synaptic transmission as part of the dendrosomatic computation rather than as part of axonal information transmission. Using such a model of neural computation and matching the information gathered by dendritic summation to the axonal information transmitted,H(p*), conditions are defined that guarantee synaptic failures can improve the energetic efficiency of neurons. Further development provides a general expression relating optimal failure rate, f, to average firing rate, p*, and is consistent with physiologically observed values. The expression providing this relationship, f ≈ 4−H(p*), generalizes across activity levels and is independent of the number of inputs to a neuron.

Relational learning with and without awareness: Transitive inference using nonverbal stimuli in humans

Learning complex relationships among items and representing them flexibly have been shown to be highly similar in function and structure to conscious forms of learning. However, it is unclear whether conscious learning is essential for the exhibition of flexibility in learning. Successful performance on the transitive inference task requires representational flexibility. Participants learned four overlapping premise pairs (A > B, B > C, C > D, D > E) that could be encoded separately or as a sequential hierarchy (A > B > C > D > E). Some participants (informed) were told prior to training that the task required an inference made from premise pairs. Other participants (uninformed) were told simply that they were to learn a series of pairs by trial and error. Testing consisted of unreinforced trials that included the nonadjacent pair, B versus D, to assess capacity for transitive inference. Not surprisingly, those in the informed condition outperformed those in the uninformed condition. After completion of training and testing, uninformed participants were given a postexperimental questionnaire to assess awareness of the task structure. In contrast with expectations, successful performance on the transitive inference task for uninformed participants does not depend on or correlate with postexperimental awareness. The present results suggest that relational learning tasks do not necessarily require conscious processes.

Astrocytic volume fluctuates in the hippocampal CA1 region across the estrous cycle

The number of dendritic spine synapses in the hippocampal CA1 stratum radiatum fluctuates across the rat estrous cycle, being high on proestrus and low on estrus [20]. We hypothesized that the volume occupied by astrocytic processes changes in a complementary manner. The volume fraction of astrocytic processes was determined stereologically in CA1 s. radiatum and s. lacunosum-moleculare of cycling female rats. Consistent with our hypothesis, the volume fraction was significantly lower on the afternoon of proestrus than on the afternoon of estrus in both laminae.

Blockade of inhibition in a pathway with dual excitatory and inhibitory action unmasks a capability for LTP that is otherwise not expressed.

Long-term potentiation (LTP) can be readily elicited in a number of hippocampal pathways, but has not been seen in the dentate commissural pathway. The dentate commissural pathway is similar to the commissural/Schaffer collateral projection to CA1 except that it produces powerful inhibition that occurs nearly concurrently with the excitation. The present study evaluates whether this inhibition prevents the pathway from expressing LTP. Acute neurophysiological experiments were carried out in urethane anesthetized rats. To locally block inhibition in the dentate gyrus, a recording micropipette filled with 8 mM bicuculline was positioned in the dentate gyrus. A control saline-filled micropipette was positioned nearby. The commissural pathway was activated by stimulating electrodes in the contralateral CA3/CA4 region. Brief high-frequency stimulation of the commissural pathway reliably elicited LTP at the bicuculline electrode but not at the control electrode. This LTP required a threshold level of stimulation for its initiation, suggesting that like most other examples of LTP, the LTP in the commissural system depended upon activation of a voltage-dependent receptor. The high-frequency stimuli used to induce LTP produced an extracellular negativity at the bicuculline electrode that was not present at the control electrode. This negative potential was selectively blocked by ketamine and MK801, suggesting that the negative potential reflects N-methyl-D-aspartate (NMDA) receptor activation. Taken together, these results suggest that LTP is not normally expressed by the dentate commissural pathway because the simultaneous inhibition prevents the depolarization-related relief of Mg2+ blockade of the NMDA receptor.

Ovarian steroidal control of connectivity in the female hippocampus: an overview of recent experimental findings and speculations on its functional consequences.

Experimental evidence accumulated over the past 5 years clearly indicates that ovarian steroids regulate the number of synapses in the rat hippocampal CA1 region. When estradiol levels are high such as during proestrus and ovulation, the number of synapses is high; when estradiol levels are low such as during estrus, the number of synapses is low. Here we address three questions that are frequently raised by these phasic fluctuations in synapse number in a brain region to which cognitive functions are classically attributed. First, what neuronal signals might produce the changes in synapse number? Second, how are the hippocampal functions of memory encoding and cognitive mapping affected by fluctuating levels of ovarian steroids? Third, for mammals in general, what might be the ecological/cognitive significance of such changes? In this last section, we integrate some of the relevant human and rodent cognitive/behavioral literature and propose a hypothesis. Namely, by altering its quantitative connectivity, the female hippocampus is optimized for different cognitive/behavioral functions when the female is sexually receptive and ovarian steroid levels are high rather than when she is not receptive and steroid levels are low. The hippocampus thus shifts its optimal computational functions across the estrous/menstrual cycle. Hippocampus 7:239–245, 1997.