Visual and acoustic avoidance conditioning. Bars represent the percentages of conditioned avoidance responses for 50 trials. The values are the mean ± SEM. of 8–10 animals on each group. For statistical comparisons was used the Student t-test 
Morphometric analysis of flat Inferior colliculus (IC) and wide-field superior colliculus (SC) neurons. Total dendrite length or the total number of dendrite branches of IC neurons, and total dendrite length or branch number of wide-field type neurons of the SC (Data obtained in n = 80 cells from n = 8 animals )
In conclusion, the different performances in conditioned behavior were associated with morphological changes in specific brain regions in rats. Given that these changes are correlated with learning, such plasticity seems to be an important predictor of learning-induced behavior . Additionally, morphological and behavioral evidence indicates that the preferred channel for data input in rat brain seems to be the acoustic channel.
Neuroplasticity: Learning and Memory
We know that memory is a complex process necessary for cognition and that the ability to form memories requires changes in the synapses between neurons. Neurobiology development has shown that synapses structures are used not only to transmit information, but they are also extremely plastic and this plasticity is the basis for learning and memory. Synaptic plasticity, or the ability of synapses to modify their functional strength in an activity-dependent manner, also includes the ability of neuronal circuits to change as a result of certain patterns of neuronal activity. Neuroplasticity involves modulation of synaptic ion channels and receptors, dendritic branching, and spine density through genetic and epigenetic mechanisms.  Thus, learning could be considered as a change in behavior in response to environmental stimuli, and it depends critically on plasticity within the nervous system. As learning events occurs in the brain, physical changes are produced within brain circuitry and in its structure-function relations. Then, the most important factor in learning is the existing networks of neurons in the brain of the learner. Thus, knowledge induces physical changes in the brain .
Neural mechanisms that affect sensory function during states of attention, motivation, and vigilance (sleep and wakefulness) also affect how incoming sensory information is received (i.e., how neurons respond to sensory input), how neuronal responses are altered over time by changing sensory input (i.e., sensory plasticity), and how information about the environment is encoded, processed, stored for future use, and integrated with past experiences (i.e., memory formation ).
Memory is quite fluid, therefore, the brain continues to revisit and organize stored information with each subsequent experience in a cyclical manner, reprogramming its contents through a repetitive updating procedure known as brain plasticity. This is advantageous because knowledge is revised based on new input, resulting in a more accurate representation of the world.
Neuroplasticity could also be responsible for priming effects observed in various memory paradigms. For example, a single training trial may not be sufficient to elicit a memory of the trial, however, a subsequent trial may allow for memory formation in a time-dependent manner.
Sensory memory takes the information provided by the senses and retains it accurately, but briefly. Sensory memory lasts such a short time (from a few hundred milliseconds to one or two seconds) that it is often considered part of the process of perception. Nevertheless, it represents an essential step for storing information in short-term memory.
Short-term memory temporarily records the succession of events in our lives. However, this information will quickly disappear forever unless we make a conscious effort to retain it. Just as sensory memory is a necessary step for short-term memory, short-term memory is a necessary step toward the next stage of retention, long-term memory.
Long-term memory not only stores all the significant events that mark our lives, it lets us retain the meanings of words and the physical skills that we have learned. Its capacity seems unlimited, and it can last days, months, years, or even an entire lifetime.
Learning and Memory in Humans
In humans, learning can be considered as the process by which we acquire, develop, and process new information. However, it is clear that not all individuals learn in the same way, and the variability can be through age, motivation, prior cultural background, social context, and learning styles.
According Alonso et al. , learning represents the acquisition of a relatively enduring disposition to change the perception or behavior as a result of experience.
On the other hand, memory allows us to remember facts and experiences. It consists of encoding, storing information, and retrieval, making that information available for recall. When we see or experience something, it leaves a trace in our brain. Thus, learning is about acquiring information and memory is about storing it. In this way, we could say that learning is a process, and memory is the record of that process.
Zull  showed the connection between brain structures and learning and the relation between the functions of the cerebral cortex and the Kolb’s learning cycle. At the beginning, the nervous system senses the environment through the sense organs, then these signals are recognized and integrated and, finally, a movement is generated as an appropriate response.
On the other hand, the learning cycle by Kolb arises from the structure of the brain, thus beginning with concrete experience that comes through the sensory cortex, continues with reflective observation what involves the temporal integrative cortex, then the abstract hypothesis occurs in the frontal integrative cortex, and active testing involves the motor brain .
Knowing the learning brain cycle induces to think in the importance that has the sensory input for adequate learning. The sensory cortex that receives input from the outside world correlated with concrete experience, depending on direct physical information from the world. The back integrative cortex that is related with integration of sensory information to create images and meaning, matches with reflection. The frontal integrative cortex that is responsible for organizing actions for the entire body is related to the generation of abstractions and development of plans for future actions. Finally, the motor cortex that triggers all voluntary muscle to produce movement correlates with the necessity for action in completion of the learning cycle. Thus, learning requires conversion of ideas into muscular actions, including written and spoken language.
Student Learning Styles
There are different ways of understanding the learning process,one of them is provided by cognitive theories focused on how to learn and based on a constructivist postulate in which the subject constructs his knowledge of the world from the perception and the action.
Learning is considered not as a passive and receptive process, but as an interactive and dynamic process through which external information is interpreted and reinterpreted by the mind, gradually building increasingly complex explanatory models .
Even the best teachers have difficulty communicating knowledge to students when trying to apply the theoretical and pedagogical foundations in practice. The methodology used by the teacher and the evaluation method used can either promote or inhibit student learning strategies. In turn, in addition to using their cognitive abilities to structure the form of study, they must organize and prioritize their learning materials by providing adequate time for it.
How students perform these tasks depends, to a large extent, on their way of being and thinking and, above all, on their preference to use different learning strategies. Thus, defining the construct learning style is essential to delineate the areas covered, and particularly its possible applications.
The term “learning style” refers to the fact that each person uses their own method or strategies when learning. While strategies vary depending on what you want to learn, each tends to develop certain preferences or global trends, trends that define a particular style. Therefore, learning styles are like conclusions we reached about the way people act. However, when addressing the study of learning styles, it is difficult to provide a single definition that truly explains what this construct is. This difficulty occurs because it is a concept that has been addressed from many different perspectives, and in the literature we observe a large plurality of definitions according to various authors, some of which we note below.
Some learn skills that stand out above others as a result of hereditary apparatus of their own life experiences and the demands of the current environment .
Learning style is a particular set of behaviors and attitudes related to the learning context .
The manner in which people gather, process, internalize, and remember new information .
One of the most inclusive definitions is from Keefe , who stated: “Learning styles are cognitive, affective, and physiological traits that serve as relatively stable indicators of how learners perceive, interact and respond to their learning environments”. That is, the cognitive traits pertain to how students structure the content, form and use concepts, interpret information, solve problems, and select means of representation (visual, auditory, kinaesthetic). They are highly individualized preferences and trends that influence learning and they are dependent on the way that new acquired information is selected, represented, and processed. The previous cognitive structure provides meaning and organization to experiences and allows the student to go beyond the information given.